Sample records for decision making learning

  1. Categorization = Decision Making + Generalization

    PubMed Central

    Seger, Carol A; Peterson, Erik J.

    2013-01-01

    We rarely, if ever, repeatedly encounter exactly the same situation. This makes generalization crucial for real world decision making. We argue that categorization, the study of generalizable representations, is a type of decision making, and that categorization learning research would benefit from approaches developed to study the neuroscience of decision making. Similarly, methods developed to examine generalization and learning within the field of categorization may enhance decision making research. We first discuss perceptual information processing and integration, with an emphasis on accumulator models. We then examine learning the value of different decision making choices via experience, emphasizing reinforcement learning modeling approaches. Next we discuss how value is combined with other factors in decision making, emphasizing the effects of uncertainty. Finally, we describe how a final decision is selected via thresholding processes implemented by the basal ganglia and related regions. We also consider how memory related functions in the hippocampus may be integrated with decision making mechanisms and contribute to categorization. PMID:23548891

  2. Learning to Make Decisions Through Constructive Controversy.

    ERIC Educational Resources Information Center

    Tjosvold, Dean

    Students must make decisions about their lifestyle, future careers, academic pursuits, and classroom and school issues. Learning to make effective decisions for themselves and for society is an important aspect of competence. They can learn decision making through interacting and solving problems with others. A central ingredient for successful…

  3. Predicting explorative motor learning using decision-making and motor noise.

    PubMed

    Chen, Xiuli; Mohr, Kieran; Galea, Joseph M

    2017-04-01

    A fundamental problem faced by humans is learning to select motor actions based on noisy sensory information and incomplete knowledge of the world. Recently, a number of authors have asked whether this type of motor learning problem might be very similar to a range of higher-level decision-making problems. If so, participant behaviour on a high-level decision-making task could be predictive of their performance during a motor learning task. To investigate this question, we studied performance during an explorative motor learning task and a decision-making task which had a similar underlying structure with the exception that it was not subject to motor (execution) noise. We also collected an independent measurement of each participant's level of motor noise. Our analysis showed that explorative motor learning and decision-making could be modelled as the (approximately) optimal solution to a Partially Observable Markov Decision Process bounded by noisy neural information processing. The model was able to predict participant performance in motor learning by using parameters estimated from the decision-making task and the separate motor noise measurement. This suggests that explorative motor learning can be formalised as a sequential decision-making process that is adjusted for motor noise, and raises interesting questions regarding the neural origin of explorative motor learning.

  4. Predicting explorative motor learning using decision-making and motor noise

    PubMed Central

    Galea, Joseph M.

    2017-01-01

    A fundamental problem faced by humans is learning to select motor actions based on noisy sensory information and incomplete knowledge of the world. Recently, a number of authors have asked whether this type of motor learning problem might be very similar to a range of higher-level decision-making problems. If so, participant behaviour on a high-level decision-making task could be predictive of their performance during a motor learning task. To investigate this question, we studied performance during an explorative motor learning task and a decision-making task which had a similar underlying structure with the exception that it was not subject to motor (execution) noise. We also collected an independent measurement of each participant’s level of motor noise. Our analysis showed that explorative motor learning and decision-making could be modelled as the (approximately) optimal solution to a Partially Observable Markov Decision Process bounded by noisy neural information processing. The model was able to predict participant performance in motor learning by using parameters estimated from the decision-making task and the separate motor noise measurement. This suggests that explorative motor learning can be formalised as a sequential decision-making process that is adjusted for motor noise, and raises interesting questions regarding the neural origin of explorative motor learning. PMID:28437451

  5. [The effects of case-based learning using video on clinical decision making and learning motivation in undergraduate nursing students].

    PubMed

    Yoo, Moon-Sook; Park, Jin-Hee; Lee, Si-Ra

    2010-12-01

    The purpose of this study was to examine the effects of case-base learning (CBL) using video on clinical decision-making and learning motivation. This research was conducted between June 2009 and April 2010 as a nonequivalent control group non-synchronized design. The study population was 44 third year nursing students who enrolled in a college of nursing, A University in Korea. The nursing students were divided into the CBL and the control group. The intervention was the CBL with three cases using video. The controls attended a traditional live lecture on the same topics. With questionnaires objective clinical decision-making, subjective clinical decision-making, and learning motivation were measured before the intervention, and 10 weeks after the intervention. Significant group differences were observed in clinical decision-making and learning motivation. The post-test scores of clinical decision-making in the CBL group were statistically higher than the control group. Learning motivation was also significantly higher in the CBL group than in the control group. These results indicate that CBL using video is effective in enhancing clinical decision-making and motivating students to learn by encouraging self-directed learning and creating more interest and curiosity in learning.

  6. Manipulating memory efficacy affects the behavioral and neural profiles of deterministic learning and decision-making.

    PubMed

    Tremel, Joshua J; Ortiz, Daniella M; Fiez, Julie A

    2018-06-01

    When making a decision, we have to identify, collect, and evaluate relevant bits of information to ensure an optimal outcome. How we approach a given choice can be influenced by prior experience. Contextual factors and structural elements of these past decisions can cause a shift in how information is encoded and can in turn influence later decision-making. In this two-experiment study, we sought to manipulate declarative memory efficacy and decision-making in a concurrent discrimination learning task by altering the amount of information to be learned. Subjects learned correct responses to pairs of items across several repetitions of a 50- or 100-pair set and were tested for memory retention. In one experiment, this memory test interrupted learning after an initial encoding experience in order to test for early encoding differences and associate those differences with changes in decision-making. In a second experiment, we used fMRI to probe neural differences between the two list-length groups related to decision-making across learning and assessed subsequent memory retention. We found that a striatum-based system was associated with decision-making patterns when learning a longer list of items, while a medial cortical network was associated with patterns when learning a shorter list. Additionally, the hippocampus was exclusively active for the shorter list group. Altogether, these behavioral, computational, and imaging results provide evidence that multiple types of mnemonic representations contribute to experienced-based decision-making. Moreover, contextual and structural factors of the task and of prior decisions can influence what types of evidence are drawn upon during decision-making. Copyright © 2018 Elsevier Ltd. All rights reserved.

  7. Distinct Roles of Dopamine and Subthalamic Nucleus in Learning and Probabilistic Decision Making

    ERIC Educational Resources Information Center

    Coulthard, Elizabeth J.; Bogacz, Rafal; Javed, Shazia; Mooney, Lucy K.; Murphy, Gillian; Keeley, Sophie; Whone, Alan L.

    2012-01-01

    Even simple behaviour requires us to make decisions based on combining multiple pieces of learned and new information. Making such decisions requires both learning the optimal response to each given stimulus as well as combining probabilistic information from multiple stimuli before selecting a response. Computational theories of decision making…

  8. Enhancing Decision-Making in STSE Education by Inducing Reflection and Self-Regulated Learning

    NASA Astrophysics Data System (ADS)

    Gresch, Helge; Hasselhorn, Marcus; Bögeholz, Susanne

    2017-02-01

    Thoughtful decision-making to resolve socioscientific issues is central to science, technology, society, and environment (STSE) education. One approach for attaining this goal involves fostering students' decision-making processes. Thus, the present study explores whether the application of decision-making strategies, combined with reflections on the decision-making processes of others, enhances decision-making competence. In addition, this study examines whether this process is supported by elements of self-regulated learning, i.e., self-reflection regarding one's own performance and the setting of goals for subsequent tasks. A computer-based training program which involves the resolution of socioscientific issues related to sustainable development was developed in two versions: with and without elements of self-regulated learning. Its effects on decision-making competence were analyzed using a pre test-post test follow-up control-group design ( N = 242 high school students). Decision-making competence was assessed using an open-ended questionnaire that focused on three facets: consideration of advantages and disadvantages, metadecision aspects, and reflection on the decision-making processes of others. The findings suggest that students in both training groups incorporated aspects of metadecision into their statements more often than students in the control group. Furthermore, both training groups were more successful in reflecting on the decision-making processes of others. The students who received additional training in self-regulated learning showed greater benefits in terms of metadecision aspects and reflection, and these effects remained significant two months later. Overall, our findings demonstrate that the application of decision-making strategies, combined with reflections on the decision-making process and elements of self-regulated learning, is a fruitful approach in STSE education.

  9. The Three-Part Harmony of Adult Learning, Critical Thinking, and Decision-Making

    ERIC Educational Resources Information Center

    Moore, Kyle

    2010-01-01

    Adult learning, critical thinking, and decision-making are fields that receive attention individually, although they are interspersed with elements of each other's theories and philosophies. In addressing adult learning precepts, it is essential to include critical thinking and decision-making. One without the other creates weakness; all must be…

  10. Low Cognitive Impulsivity Is Associated with Better Gain and Loss Learning in a Probabilistic Decision-Making Task

    PubMed Central

    Cáceres, Pablo; San Martín, René

    2017-01-01

    Many advances have been made over the last decades in describing, on the one hand, the link between reward-based learning and decision-making, and on the other hand, the link between impulsivity and decision-making. However, the association between reward-based learning and impulsivity remains poorly understood. In this study, we evaluated the association between individual differences in loss-minimizing and gain-maximizing behavior in a learning-based probabilistic decision-making task and individual differences in cognitive impulsivity. We found that low cognitive impulsivity was associated both with a better performance minimizing losses and maximizing gains during the task. These associations remained significant after controlling for mathematical skills and gender as potential confounders. We discuss potential mechanisms through which cognitive impulsivity might interact with reward-based learning and decision-making. PMID:28261137

  11. Low Cognitive Impulsivity Is Associated with Better Gain and Loss Learning in a Probabilistic Decision-Making Task.

    PubMed

    Cáceres, Pablo; San Martín, René

    2017-01-01

    Many advances have been made over the last decades in describing, on the one hand, the link between reward-based learning and decision-making, and on the other hand, the link between impulsivity and decision-making. However, the association between reward-based learning and impulsivity remains poorly understood. In this study, we evaluated the association between individual differences in loss-minimizing and gain-maximizing behavior in a learning-based probabilistic decision-making task and individual differences in cognitive impulsivity. We found that low cognitive impulsivity was associated both with a better performance minimizing losses and maximizing gains during the task. These associations remained significant after controlling for mathematical skills and gender as potential confounders. We discuss potential mechanisms through which cognitive impulsivity might interact with reward-based learning and decision-making.

  12. Dissociation of emotional decision-making from cognitive decision-making in chronic schizophrenia.

    PubMed

    Lee, Yanghyun; Kim, Yang-Tae; Seo, Eugene; Park, Oaktae; Jeong, Sung-Hun; Kim, Sang Heon; Lee, Seung-Jae

    2007-08-30

    Recent studies have examined the decision-making ability of schizophrenic patients using the Iowa Gambling Task (IGT). These studies, however, were restricted to the assessment of emotional decision-making. Decision-making depends on cognitive functions as well as on emotion. The purpose of this study was to examine the performance of schizophrenic patients on the IGT and the Game of Dice Task (GDT), a decision-making task with explicit rules for gains and losses. In addition, it was intended to test whether poor performance on IGT is attributable to impairments in reversal learning within the schizophrenia group using the Simple Reversal Learning Task (SRLT), which is sensitive to measure the deficit of reversal learning following ventromedial prefrontal cortex damage. A group of 23 stable schizophrenic patients and 28 control subjects performed computerized versions of the IGT, GDT, SRLT and Wisconsin Card Sorting Test (WCST). While schizophrenic patients performed poorly on the IGT relative to normal controls, there was no significant difference between the two groups on GDT performance. The performance of the schizophrenia group on the SRLT was poorer than that of controls, but was not related to IGT performance. These data suggest that schizophrenic patients have impaired emotional decision-making but intact cognitive decision-making, suggesting that these two processes of decision-making are different. Furthermore, the impairments in reversal learning did not contribute to poor performance on the IGT in schizophrenia. Therefore, schizophrenic patients have difficulty in making decisions under ambiguous and uncertain situations whereas they make choices easily in clear and unequivocal ones. The emotional decision-making deficits in schizophrenia might be attributable more to another mechanism such as a somatic marker hypothesis than to an impairment in reversal learning.

  13. Risky decision-making in children with and without ADHD: A prospective study.

    PubMed

    Humphreys, Kathryn L; Tottenham, Nim; Lee, Steve S

    2018-02-01

    Learning from past decisions can enhance successful decision-making. It is unclear whether difficulties in learning from experience may contribute to risky decision-making, which may be altered among individuals with attention-deficit/hyperactivity disorder (ADHD). This study follows 192 children with and without ADHD aged 5 to 10 years for approximately 2.5 years and examines their risky decision-making using the Balloon Emotional Learning Task (BELT), a computerized assessment of sequential risky decision-making in which participants pump up a series of virtual balloons for points. The BELT contains three task conditions: one with a variable explosion point, one with a stable and early explosion point, and one with a stable and late explosion point. These conditions may be learned via experience on the task. Contrary to expectations, ADHD status was not found to be related to greater risk-taking on the BELT, and among younger children ADHD status is in fact associated with reduced risk-taking. In addition, the typically-developing children without ADHD showed significant learning-related gains on both stable task conditions. However, the children with ADHD demonstrated learning on the condition with a stable and early explosion point, but not on the condition with the stable and late explosion point, in which more pumps are required before learning when the balloon will explode. Learning during decision-making may be more difficult for children with ADHD. Because adapting to changing environmental demands requires the use of feedback to guide future behavior, negative outcomes associated with childhood ADHD may partially reflect difficulties in learning from experience.

  14. Altered Risk-Based Decision Making following Adolescent Alcohol Use Results from an Imbalance in Reinforcement Learning in Rats

    PubMed Central

    Hart, Andrew S.; Collins, Anne L.; Bernstein, Ilene L.; Phillips, Paul E. M.

    2012-01-01

    Alcohol use during adolescence has profound and enduring consequences on decision-making under risk. However, the fundamental psychological processes underlying these changes are unknown. Here, we show that alcohol use produces over-fast learning for better-than-expected, but not worse-than-expected, outcomes without altering subjective reward valuation. We constructed a simple reinforcement learning model to simulate altered decision making using behavioral parameters extracted from rats with a history of adolescent alcohol use. Remarkably, the learning imbalance alone was sufficient to simulate the divergence in choice behavior observed between these groups of animals. These findings identify a selective alteration in reinforcement learning following adolescent alcohol use that can account for a robust change in risk-based decision making persisting into later life. PMID:22615989

  15. Lifelong Transfer Learning for Heterogeneous Teams of Agents in Sequential Decision Processes

    DTIC Science & Technology

    2016-06-01

    making (SDM) tasks in dynamic environments with simulated and physical robots . 15. SUBJECT TERMS Sequential decision making, lifelong learning, transfer...sequential decision-making (SDM) tasks in dynamic environments with both simple benchmark tasks and more complex aerial and ground robot tasks. Our work...and ground robots in the presence of disturbances: We applied our methods to the problem of learning controllers for robots with novel disturbances in

  16. Practice guidelines in the context of primary care, learning and usability in the physicians' decision-making process--a qualitative study.

    PubMed

    Ingemansson, Maria; Bastholm-Rahmner, Pia; Kiessling, Anna

    2014-08-20

    Decision-making is central for general practitioners (GP). Practice guidelines are important tools in this process but implementation of them in the complex context of primary care is a challenge. The purpose of this study was to explore how GPs approach, learn from and use practice guidelines in their day-to-day decision-making process in primary care. A qualitative approach using focus-group interviews was chosen in order to provide in-depth information. The participants were 22 GPs with a median of seven years of experience in primary care, representing seven primary healthcare centres in Stockholm, Sweden in 2011. The interviews focused on how the GPs use guidelines in their decision-making, factors that influence their decision how to approach these guidelines, and how they could encourage the learning process in routine practice.Data were analysed by qualitative content analysis. Meaning units were condensed and grouped in categories. After interpreting the content in the categories, themes were created. Three themes were conceptualized. The first theme emphasized to use guidelines by interactive contextualized dialogues. The categories underpinning this theme: 1. Feedback by peer-learning 2. Feedback by collaboration, mutual learning, and equality between specialties, identified important ways to achieve this learning dialogue. Confidence was central in the second theme, learning that establishes confidence to provide high quality care. Three aspects of confidence were identified in the categories of this theme: 1. Confidence by confirmation, 2. Confidence by reliability and 3. Confidence by evaluation of own results. In the third theme, learning by use of relevant evidence in the decision-making process, we identified two categories: 1. Design and lay-out visualizing the evidence 2. Accessibility adapted to the clinical decision-making process as prerequisites for using the practice guidelines. Decision-making in primary care is a dual process that involves use of intuitive and analytic thinking in a balanced way in order to provide high quality care. Key aspects of effective learning in this clinical decision-making process were: contextualized dialogue, which was based on the GPs' own experiences, feedback on own results and easy access to short guidelines perceived as trustworthy.

  17. Neural Correlates of Sequence Learning with Stochastic Feedback

    ERIC Educational Resources Information Center

    Averbeck, Bruno B.; Kilner, James; Frith, Christopher D.

    2011-01-01

    Although much is known about decision making under uncertainty when only a single step is required in the decision process, less is known about sequential decision making. We carried out a stochastic sequence learning task in which subjects had to use noisy feedback to learn sequences of button presses. We compared flat and hierarchical behavioral…

  18. Collective learning and optimal consensus decisions in social animal groups.

    PubMed

    Kao, Albert B; Miller, Noam; Torney, Colin; Hartnett, Andrew; Couzin, Iain D

    2014-08-01

    Learning has been studied extensively in the context of isolated individuals. However, many organisms are social and consequently make decisions both individually and as part of a collective. Reaching consensus necessarily means that a single option is chosen by the group, even when there are dissenting opinions. This decision-making process decouples the otherwise direct relationship between animals' preferences and their experiences (the outcomes of decisions). Instead, because an individual's learned preferences influence what others experience, and therefore learn about, collective decisions couple the learning processes between social organisms. This introduces a new, and previously unexplored, dynamical relationship between preference, action, experience and learning. Here we model collective learning within animal groups that make consensus decisions. We reveal how learning as part of a collective results in behavior that is fundamentally different from that learned in isolation, allowing grouping organisms to spontaneously (and indirectly) detect correlations between group members' observations of environmental cues, adjust strategy as a function of changing group size (even if that group size is not known to the individual), and achieve a decision accuracy that is very close to that which is provably optimal, regardless of environmental contingencies. Because these properties make minimal cognitive demands on individuals, collective learning, and the capabilities it affords, may be widespread among group-living organisms. Our work emphasizes the importance and need for theoretical and experimental work that considers the mechanism and consequences of learning in a social context.

  19. Collective Learning and Optimal Consensus Decisions in Social Animal Groups

    PubMed Central

    Kao, Albert B.; Miller, Noam; Torney, Colin; Hartnett, Andrew; Couzin, Iain D.

    2014-01-01

    Learning has been studied extensively in the context of isolated individuals. However, many organisms are social and consequently make decisions both individually and as part of a collective. Reaching consensus necessarily means that a single option is chosen by the group, even when there are dissenting opinions. This decision-making process decouples the otherwise direct relationship between animals' preferences and their experiences (the outcomes of decisions). Instead, because an individual's learned preferences influence what others experience, and therefore learn about, collective decisions couple the learning processes between social organisms. This introduces a new, and previously unexplored, dynamical relationship between preference, action, experience and learning. Here we model collective learning within animal groups that make consensus decisions. We reveal how learning as part of a collective results in behavior that is fundamentally different from that learned in isolation, allowing grouping organisms to spontaneously (and indirectly) detect correlations between group members' observations of environmental cues, adjust strategy as a function of changing group size (even if that group size is not known to the individual), and achieve a decision accuracy that is very close to that which is provably optimal, regardless of environmental contingencies. Because these properties make minimal cognitive demands on individuals, collective learning, and the capabilities it affords, may be widespread among group-living organisms. Our work emphasizes the importance and need for theoretical and experimental work that considers the mechanism and consequences of learning in a social context. PMID:25101642

  20. Free-Choice Learning Suited to Women's Participation Needs in Environmental Decision-Making Processes

    ERIC Educational Resources Information Center

    Skanavis, Constantina; Sakellari, Maria

    2012-01-01

    United Nations mandates recognize the need to promote the full participation of women in environmental decision-making processes on the basis of gender equality. But, there remains a profound lack of effective women's participation in some sectors of environmental decision-making. Free-choice environmental learning offers an effective educational…

  1. Preschool Teaching Students' Prediction of Decision Making Strategies and Academic Achievement on Learning Motivations

    ERIC Educational Resources Information Center

    Acat, M. Bahaddin; Dereli, Esra

    2012-01-01

    The purpose of this study was to identify problems and motivation sources and strategies of decision-making of the students' attending preschool education teacher department, was to determine the relationship between learning motivation and strategies of decision-making, academic achievement of students, was to determine whether strategies of…

  2. Anatomy of a Decision: Striato-Orbitofrontal Interactions in Reinforcement Learning, Decision Making, and Reversal

    ERIC Educational Resources Information Center

    Frank, Michael J.; Claus, Eric D.

    2006-01-01

    The authors explore the division of labor between the basal ganglia-dopamine (BG-DA) system and the orbitofrontal cortex (OFC) in decision making. They show that a primitive neural network model of the BG-DA system slowly learns to make decisions on the basis of the relative probability of rewards but is not as sensitive to (a) recency or (b) the…

  3. People learn other people's preferences through inverse decision-making.

    PubMed

    Jern, Alan; Lucas, Christopher G; Kemp, Charles

    2017-11-01

    People are capable of learning other people's preferences by observing the choices they make. We propose that this learning relies on inverse decision-making-inverting a decision-making model to infer the preferences that led to an observed choice. In Experiment 1, participants observed 47 choices made by others and ranked them by how strongly each choice suggested that the decision maker had a preference for a specific item. An inverse decision-making model generated predictions that were in accordance with participants' inferences. Experiment 2 replicated and extended a previous study by Newtson (1974) in which participants observed pairs of choices and made judgments about which choice provided stronger evidence for a preference. Inverse decision-making again predicted the results, including a result that previous accounts could not explain. Experiment 3 used the same method as Experiment 2 and found that participants did not expect decision makers to be perfect utility-maximizers. Copyright © 2017 Elsevier B.V. All rights reserved.

  4. On acquiring decision making skills for endovascular interventions.

    PubMed

    Lanzer, Peter; Prechelt, Lutz

    2008-11-01

    To improve interventional training we propose a staged rational approach for decision making and skill acquisition. Education and training for endovascular interventions should start to develop the learners' decision-making skills by learning from explicit representations of master interventionist's tacit decision-making knowledge through implementation of the notions of generic interventional modules, interventional strategic and tactical designs. We hope that these suggestions will encourage action, stimulate dialogue and advance the precision of our learning, procedures, practice and patient care.

  5. Decision making under uncertainty in a spiking neural network model of the basal ganglia.

    PubMed

    Héricé, Charlotte; Khalil, Radwa; Moftah, Marie; Boraud, Thomas; Guthrie, Martin; Garenne, André

    2016-12-01

    The mechanisms of decision-making and action selection are generally thought to be under the control of parallel cortico-subcortical loops connecting back to distinct areas of cortex through the basal ganglia and processing motor, cognitive and limbic modalities of decision-making. We have used these properties to develop and extend a connectionist model at a spiking neuron level based on a previous rate model approach. This model is demonstrated on decision-making tasks that have been studied in primates and the electrophysiology interpreted to show that the decision is made in two steps. To model this, we have used two parallel loops, each of which performs decision-making based on interactions between positive and negative feedback pathways. This model is able to perform two-level decision-making as in primates. We show here that, before learning, synaptic noise is sufficient to drive the decision-making process and that, after learning, the decision is based on the choice that has proven most likely to be rewarded. The model is then submitted to lesion tests, reversal learning and extinction protocols. We show that, under these conditions, it behaves in a consistent manner and provides predictions in accordance with observed experimental data.

  6. Neural signatures of experience-based improvements in deterministic decision-making.

    PubMed

    Tremel, Joshua J; Laurent, Patryk A; Wolk, David A; Wheeler, Mark E; Fiez, Julie A

    2016-12-15

    Feedback about our choices is a crucial part of how we gather information and learn from our environment. It provides key information about decision experiences that can be used to optimize future choices. However, our understanding of the processes through which feedback translates into improved decision-making is lacking. Using neuroimaging (fMRI) and cognitive models of decision-making and learning, we examined the influence of feedback on multiple aspects of decision processes across learning. Subjects learned correct choices to a set of 50 word pairs across eight repetitions of a concurrent discrimination task. Behavioral measures were then analyzed with both a drift-diffusion model and a reinforcement learning model. Parameter values from each were then used as fMRI regressors to identify regions whose activity fluctuates with specific cognitive processes described by the models. The patterns of intersecting neural effects across models support two main inferences about the influence of feedback on decision-making. First, frontal, anterior insular, fusiform, and caudate nucleus regions behave like performance monitors, reflecting errors in performance predictions that signal the need for changes in control over decision-making. Second, temporoparietal, supplementary motor, and putamen regions behave like mnemonic storage sites, reflecting differences in learned item values that inform optimal decision choices. As information about optimal choices is accrued, these neural systems dynamically adjust, likely shifting the burden of decision processing from controlled performance monitoring to bottom-up, stimulus-driven choice selection. Collectively, the results provide a detailed perspective on the fundamental ability to use past experiences to improve future decisions. Copyright © 2016 Elsevier B.V. All rights reserved.

  7. Neural signatures of experience-based improvements in deterministic decision-making

    PubMed Central

    Tremel, Joshua J.; Laurent, Patryk A.; Wolk, David A.; Wheeler, Mark E.; Fiez, Julie A.

    2016-01-01

    Feedback about our choices is a crucial part of how we gather information and learn from our environment. It provides key information about decision experiences that can be used to optimize future choices. However, our understanding of the processes through which feedback translates into improved decision-making is lacking. Using neuroimaging (fMRI) and cognitive models of decision-making and learning, we examined the influence of feedback on multiple aspects of decision processes across learning. Subjects learned correct choices to a set of 50 word pairs across eight repetitions of a concurrent discrimination task. Behavioral measures were then analyzed with both a drift-diffusion model and a reinforcement learning model. Parameter values from each were then used as fMRI regressors to identify regions whose activity fluctuates with specific cognitive processes described by the models. The patterns of intersecting neural effects across models support two main inferences about the influence of feedback on decision-making. First, frontal, anterior insular, fusiform, and caudate nucleus regions behave like performance monitors, reflecting errors in performance predictions that signal the need for changes in control over decision-making. Second, temporoparietal, supplementary motor, and putamen regions behave like mnemonic storage sites, reflecting differences in learned item values that inform optimal decision choices. As information about optimal choices is accrued, these neural systems dynamically adjust, likely shifting the burden of decision processing from controlled performance monitoring to bottom-up, stimulus-driven choice selection. Collectively, the results provide a detailed perspective on the fundamental ability to use past experiences to improve future decisions. PMID:27523644

  8. Consumer Decision-Making Styles as a Function of Individual Learning Styles.

    ERIC Educational Resources Information Center

    Sproles, Elizabeth Kendall; Sproles, George B.

    1990-01-01

    The Secondary Learning Styles Inventory and the Consumer Styles Inventory were administered to 501 secondary home economics students. Factor analysis of the learning style characteristics from the sample of 482 found significant correlations between 21 of the 48 pairs of learning and decision-making characteristics. (SK)

  9. Map for Decision Making in Operating Distance Learning System--Research Results.

    ERIC Educational Resources Information Center

    Offir, Baruch

    2000-01-01

    Examines decision-making aspects of the introduction of distance learning into university instruction and learning based on experiences in Israel. Discusses the introduction of information technology into the classroom; examines teacher/student interactions; and suggests a model for introducing distance learning that focuses on the role of the…

  10. Decision Making Impairment: A Shared Vulnerability in Obesity, Gambling Disorder and Substance Use Disorders?

    PubMed Central

    Mallorquí-Bagué, Nuria; Fagundo, Ana B.; Jimenez-Murcia, Susana; de la Torre, Rafael; Baños, Rosa M.; Botella, Cristina; Casanueva, Felipe F.; Crujeiras, Ana B.; Fernández-García, Jose C.; Fernández-Real, Jose M.; Frühbeck, Gema; Granero, Roser; Rodríguez, Amaia; Tolosa-Sola, Iris; Ortega, Francisco J.; Tinahones, Francisco J.; Alvarez-Moya, Eva; Ochoa, Cristian; Menchón, Jose M.

    2016-01-01

    Introduction Addictions are associated with decision making impairments. The present study explores decision making in Substance use disorder (SUD), Gambling disorder (GD) and Obesity (OB) when assessed by Iowa Gambling Task (IGT) and compares them with healthy controls (HC). Methods For the aims of this study, 591 participants (194 HC, 178 GD, 113 OB, 106 SUD) were assessed according to DSM criteria, completed a sociodemographic interview and conducted the IGT. Results SUD, GD and OB present impaired decision making when compared to the HC in the overall task and task learning, however no differences are found for the overall performance in the IGT among the clinical groups. Results also reveal some specific learning across the task patterns within the clinical groups: OB maintains negative scores until the third set where learning starts but with a less extend to HC, SUD presents an early learning followed by a progressive although slow improvement and GD presents more random choices with no learning. Conclusions Decision making impairments are present in the studied clinical samples and they display individual differences in the task learning. Results can help understanding the underlying mechanisms of OB and addiction behaviors as well as improve current clinical treatments. PMID:27690367

  11. Dynamic Educational e-Content Selection Using Multiple Criteria in Web-Based Personalized Learning Environments.

    ERIC Educational Resources Information Center

    Manouselis, Nikos; Sampson, Demetrios

    This paper focuses on the way a multi-criteria decision making methodology is applied in the case of agent-based selection of offered learning objects. The problem of selection is modeled as a decision making one, with the decision variables being the learner model and the learning objects' educational description. In this way, selection of…

  12. Weather to Make a Decision

    ERIC Educational Resources Information Center

    Hoyle, Julie E.; Mjelde, James W.; Litzenberg, Kerry K.

    2006-01-01

    DECIDE is a teacher-friendly, integrated approach designed to stimulate learning by allowing students to make decisions about situations they face in their lives while using scientific weather principles. This learning unit integrates weather science, decision theory, mathematics, statistics, geography, and reading in a context of decision…

  13. Game theory and neural basis of social decision making

    PubMed Central

    Lee, Daeyeol

    2008-01-01

    Decision making in a social group displays two unique features. First, humans and other animals routinely alter their behaviors in response to changes in their physical and social environment. As a result, the outcomes of decisions that depend on the behaviors of multiple decision makers are difficult to predict, and this requires highly adaptive decision-making strategies. Second, decision makers may have other-regarding preferences and therefore choose their actions to improve or reduce the well-beings of others. Recently, many neurobiological studies have exploited game theory to probe the neural basis of decision making, and found that these unique features of social decision making might be reflected in the functions of brain areas involved in reward evaluation and reinforcement learning. Molecular genetic studies have also begun to identify genetic mechanisms for personal traits related to reinforcement learning and complex social decision making, further illuminating the biological basis of social behavior. PMID:18368047

  14. Developing an Initial Learning Progression for the Use of Evidence in Decision-Making Contexts

    ERIC Educational Resources Information Center

    Bravo-Torija, Beatriz; Jiménez-Aleixandre, María-Pilar

    2018-01-01

    This paper outlines an initial learning progression for the use of evidence to support scientific arguments in the context of decision-making. Use of evidence is a central feature of knowledge evaluation and, therefore, of argumentation. The proposal is based on the literature on argumentation and use of evidence in decision-making contexts. The…

  15. An Examination of the Effects of Career Development Courses on Career Decision-Making Self-Efficacy, Adjustment to College, Learning Integration, and Academic Success

    ERIC Educational Resources Information Center

    Hansen, Michele J.; Pedersen, Joan S.

    2012-01-01

    This study investigated the effects of career development courses on career decision-making self-efficacy (CDMSE), college adjustment, learning integration, academic achievement, and retention among undecided undergraduates. It also investigated the effects of course format on career decision-making abilities and academic success outcomes and…

  16. Analyzing the effectiveness of teaching and factors in clinical decision-making.

    PubMed

    Hsieh, Ming-Chen; Lee, Ming-Shinn; Chen, Tsung-Ying; Tsai, Tsuen-Chiuan; Pai, Yi-Fong; Sheu, Min-Muh

    2017-01-01

    The aim of this study is to prepare junior physicians, clinical education should focus on the teaching of clinical decision-making. This research is designed to explore teaching of clinical decision-making and to analyze the benefits of an "Analogy guide clinical decision-making" as a learning intervention for junior doctors. This study had a "quasi-experimental design" and was conducted in a medical center in eastern Taiwan. Participants and Program Description: Thirty junior doctors and three clinical teachers were involved in the study. The experimental group (15) received 1 h of instruction from the "Analogy guide for teaching clinical decision-making" every day for 3 months. Program Evaluation: A "Clinical decision-making self-evaluation form" was used as the assessment tool to evaluate participant learning efficiency before and after the teaching program. Semi-structured qualitative research interviews were also conducted. We found using the analogy guide for teaching clinical decision-making could help enhance junior doctors' self-confidence. Important factors influencing clinical decision-making included workload, decision-making, and past experience. Clinical teaching using the analogy guide for clinical decision-making may be a helpful tool for training and can contribute to a more comprehensive understanding of decision-making.

  17. The impact of simulation sequencing on perceived clinical decision making.

    PubMed

    Woda, Aimee; Hansen, Jamie; Paquette, Mary; Topp, Robert

    2017-09-01

    An emerging nursing education trend is to utilize simulated learning experiences as a means to optimize competency and decision making skills. The purpose of this study was to examine differences in students' perception of clinical decision making and clinical decision making-related self-confidence and anxiety based on the sequence (order) in which they participated in a block of simulated versus hospital-based learning experiences. A quasi-experimental crossover design was used. Between and within group differences were found relative to self-confidence with the decision making process. When comparing groups, at baseline the simulation followed by hospital group had significantly higher self-confidence scores, however, at 14-weeks both groups were not significantly different. Significant within group differences were found in the simulation followed by hospital group only, demonstrating a significant decrease in clinical decision making related anxiety across the semester. Finally, there were no significant difference in; perceived clinical decision making within or between the groups at the two measurement points. Preliminary findings suggest that simulated learning experiences can be offered with alternating sequences without impacting the process, anxiety or confidence with clinical decision making. This study provides beginning evidence to guide curriculum development and allow flexibility based on student needs and available resources. Copyright © 2017. Published by Elsevier Ltd.

  18. Local dynamics in decision making: The evolution of preference within and across decisions

    NASA Astrophysics Data System (ADS)

    O'Hora, Denis; Dale, Rick; Piiroinen, Petri T.; Connolly, Fionnuala

    2013-07-01

    Within decisions, perceived alternatives compete until one is preferred. Across decisions, the playing field on which these alternatives compete evolves to favor certain alternatives. Mouse cursor trajectories provide rich continuous information related to such cognitive processes during decision making. In three experiments, participants learned to choose symbols to earn points in a discrimination learning paradigm and the cursor trajectories of their responses were recorded. Decisions between two choices that earned equally high-point rewards exhibited far less competition than decisions between choices that earned equally low-point rewards. Using positional coordinates in the trajectories, it was possible to infer a potential field in which the choice locations occupied areas of minimal potential. These decision spaces evolved through the experiments, as participants learned which options to choose. This visualisation approach provides a potential framework for the analysis of local dynamics in decision-making that could help mitigate both theoretical disputes and disparate empirical results.

  19. Grade 7 students' normative decision making in science learning about global warming through science technology and society (STS) approach

    NASA Astrophysics Data System (ADS)

    Luengam, Piyanuch; Tupsai, Jiraporn; Yuenyong, Chokchai

    2018-01-01

    This study reported Grade 7 students' normative decision making in teaching and learning about global warming through science technology and society (STS) approach. The participants were 43 Grade 7 students in Sungkom, Nongkhai, Thailand. The teaching and learning about global warming through STS approach had carried out for 5 weeks. The global warming unit through STS approach was developed based on framework of Yuenyong (2006) that consisted of five stages including (1) identification of social issues, (2) identification of potential solutions, (3) need for knowledge, (4) decision-making, and (5) socialization stage. Students' normative decision making was collected during their learning by questionnaire, participant observation, and students' tasks. Students' normative decision making were analyzed from both pre-and post-intervention and students' ideas during the intervention. The aspects of normative include influences of global warming on technology and society; influences of values, culture, and society on global warming; and influences of technology on global warming. The findings revealed that students have chance to learn science concerning with the relationship between science, technology, and society through their giving reasons about issues related to global warming. The paper will discuss implications of these for science teaching and learning through STS in Thailand.

  20. Sharing Power with Parents: Improving Educational Decision Making for Students with Learning Disabilities

    ERIC Educational Resources Information Center

    Connor, David J.; Cavendish, Wendy

    2018-01-01

    In this closing commentary to the special edition of "Learning Disability Quarterly" ("LDQ") on parent voice in educational decision making for students with learning disabilities, we briefly survey main topics from each article, illuminating important findings from the authors, along with several questions they raise, and…

  1. Decision making under ambiguity and under risk in mesial temporal lobe epilepsy.

    PubMed

    Delazer, Margarete; Zamarian, Laura; Bonatti, Elisabeth; Kuchukhidze, Giorgi; Koppelstätter, Florian; Bodner, Thomas; Benke, Thomas; Trinka, Eugen

    2010-01-01

    Decision making is essential in everyday life. Though the importance of the mesial temporal lobe in emotional processing and feedback learning is generally recognized, decision making in mesial temporal lobe epilepsy (mTLE) is almost unexplored so far. Twenty-eight consecutive epilepsy patients with drug resistant mTLE and fifty healthy controls performed decision tasks under initial ambiguity (participants have to learn by feedback to make advantageous decisions) and under risk (advantageous choices may be made by estimating risks and by rational strategies). A subgroup analysis compared the performance of patients affected by MRI-verified abnormalities of the hippocampus or amygdala. The effect of lesion side was also assessed. In decision under ambiguity, mTLE patients showed marked deficits and did not improve over the task. Patients with hippocampus abnormality and patients with amygdala abnormality showed comparable deficits. No difference was found between right and left TLE groups. In decision under risk, mTLE patients performed at the same level as controls. Results suggest that mTLE patients have difficulties in learning from feedback and in making decisions in uncertain, ambiguous situations. By contrast, they are able to make advantageous decisions when full information is given and risks, possible gains and losses are exactly defined.

  2. "Decisions, decisions, decisions": transfer and specificity of decision-making skill between sports.

    PubMed

    Causer, Joe; Ford, Paul R

    2014-08-01

    The concept of transfer of learning holds that previous practice or experience in one task or domain will enable successful performance in another related task or domain. In contrast, specificity of learning holds that previous practice or experience in one task or domain does not transfer to other related tasks or domains. The aim of the current study is to examine whether decision-making skill transfers between sports that share similar elements, or whether it is specific to a sport. Participants (n = 205) completed a video-based temporal occlusion decision-making test in which they were required to decide on which action to execute across a series of 4 versus 4 soccer game situations. A sport engagement questionnaire was used to identify 106 soccer players, 43 other invasion sport players and 58 other sport players. Positive transfer of decision-making skill occurred between soccer and other invasion sports, which are related and have similar elements, but not from volleyball, supporting the concept of transfer of learning.

  3. Teaching a Rational Approach to Career Decision Making: Who Benefits Most?

    ERIC Educational Resources Information Center

    Krumboltz, John D.; And Others

    1986-01-01

    Rational, intuitive, fatalistic, and dependent decision makers were compared on how much they learned from a rational decision-making training intervention. Individuals who had been highly impulsive, dependent, or fatalistic in prior course selections and those who exhibited dependency in prior job choices appeared to learn most from the rational…

  4. Enhancing Decision-Making in STSE Education by Inducing Reflection and Self-Regulated Learning

    ERIC Educational Resources Information Center

    Gresch, Helge; Hasselhorn, Marcus; Bögeholz, Susanne

    2017-01-01

    Thoughtful decision-making to resolve socioscientific issues is central to science, technology, society, and environment (STSE) education. One approach for attaining this goal involves fostering students' decision-making processes. Thus, the present study explores whether the application of decision-making strategies, combined with reflections on…

  5. What Learning Environments Help Improve Decision-Making?

    ERIC Educational Resources Information Center

    O'Connor, Donna; Larkin, Paul; Williams, A. Mark

    2017-01-01

    Background: Decision-making is a key component of performance in sport. However, there has been minimal investigation of how coaches may adapt practice sessions to specifically develop decision-making. Purpose: The aim in this exploratory study was to investigate the pedagogical approaches coaches use to develop decision-making in soccer. Method:…

  6. Cloud E-Learning Service Strategies for Improving E-Learning Innovation Performance in a Fuzzy Environment by Using a New Hybrid Fuzzy Multiple Attribute Decision-Making Model

    ERIC Educational Resources Information Center

    Su, Chiu Hung; Tzeng, Gwo-Hshiung; Hu, Shu-Kung

    2016-01-01

    The purpose of this study was to address this problem by applying a new hybrid fuzzy multiple criteria decision-making model including (a) using the fuzzy decision-making trial and evaluation laboratory (DEMATEL) technique to construct the fuzzy scope influential network relationship map (FSINRM) and determine the fuzzy influential weights of the…

  7. Probabilistic learning and inference in schizophrenia

    PubMed Central

    Averbeck, Bruno B.; Evans, Simon; Chouhan, Viraj; Bristow, Eleanor; Shergill, Sukhwinder S.

    2010-01-01

    Patients with schizophrenia make decisions on the basis of less evidence when required to collect information to make an inference, a behavior often called jumping to conclusions. The underlying basis for this behaviour remains controversial. We examined the cognitive processes underpinning this finding by testing subjects on the beads task, which has been used previously to elicit jumping to conclusions behaviour, and a stochastic sequence learning task, with a similar decision theoretic structure. During the sequence learning task, subjects had to learn a sequence of button presses, while receiving noisy feedback on their choices. We fit a Bayesian decision making model to the sequence task and compared model parameters to the choice behavior in the beads task in both patients and healthy subjects. We found that patients did show a jumping to conclusions style; and those who picked early in the beads task tended to learn less from positive feedback in the sequence task. This favours the likelihood of patients selecting early because they have a low threshold for making decisions, and that they make choices on the basis of relatively little evidence. PMID:20810252

  8. Probabilistic learning and inference in schizophrenia.

    PubMed

    Averbeck, Bruno B; Evans, Simon; Chouhan, Viraj; Bristow, Eleanor; Shergill, Sukhwinder S

    2011-04-01

    Patients with schizophrenia make decisions on the basis of less evidence when required to collect information to make an inference, a behavior often called jumping to conclusions. The underlying basis for this behavior remains controversial. We examined the cognitive processes underpinning this finding by testing subjects on the beads task, which has been used previously to elicit jumping to conclusions behavior, and a stochastic sequence learning task, with a similar decision theoretic structure. During the sequence learning task, subjects had to learn a sequence of button presses, while receiving a noisy feedback on their choices. We fit a Bayesian decision making model to the sequence task and compared model parameters to the choice behavior in the beads task in both patients and healthy subjects. We found that patients did show a jumping to conclusions style; and those who picked early in the beads task tended to learn less from positive feedback in the sequence task. This favours the likelihood of patients selecting early because they have a low threshold for making decisions, and that they make choices on the basis of relatively little evidence. Published by Elsevier B.V.

  9. Distinct roles of dopamine and subthalamic nucleus in learning and probabilistic decision making.

    PubMed

    Coulthard, Elizabeth J; Bogacz, Rafal; Javed, Shazia; Mooney, Lucy K; Murphy, Gillian; Keeley, Sophie; Whone, Alan L

    2012-12-01

    Even simple behaviour requires us to make decisions based on combining multiple pieces of learned and new information. Making such decisions requires both learning the optimal response to each given stimulus as well as combining probabilistic information from multiple stimuli before selecting a response. Computational theories of decision making predict that learning individual stimulus-response associations and rapid combination of information from multiple stimuli are dependent on different components of basal ganglia circuitry. In particular, learning and retention of memory, required for optimal response choice, are significantly reliant on dopamine, whereas integrating information probabilistically is critically dependent upon functioning of the glutamatergic subthalamic nucleus (computing the 'normalization term' in Bayes' theorem). Here, we test these theories by investigating 22 patients with Parkinson's disease either treated with deep brain stimulation to the subthalamic nucleus and dopaminergic therapy or managed with dopaminergic therapy alone. We use computerized tasks that probe three cognitive functions-information acquisition (learning), memory over a delay and information integration when multiple pieces of sequentially presented information have to be combined. Patients performed the tasks ON or OFF deep brain stimulation and/or ON or OFF dopaminergic therapy. Consistent with the computational theories, we show that stopping dopaminergic therapy impairs memory for probabilistic information over a delay, whereas deep brain stimulation to the region of the subthalamic nucleus disrupts decision making when multiple pieces of acquired information must be combined. Furthermore, we found that when participants needed to update their decision on the basis of the last piece of information presented in the decision-making task, patients with deep brain stimulation of the subthalamic nucleus region did not slow down appropriately to revise their plan, a pattern of behaviour that mirrors the impulsivity described clinically in some patients with subthalamic nucleus deep brain stimulation. Thus, we demonstrate distinct mechanisms for two important facets of human decision making: first, a role for dopamine in memory consolidation, and second, the critical importance of the subthalamic nucleus in successful decision making when multiple pieces of information must be combined.

  10. The role of moral utility in decision making: an interdisciplinary framework.

    PubMed

    Tobler, Philippe N; Kalis, Annemarie; Kalenscher, Tobias

    2008-12-01

    What decisions should we make? Moral values, rules, and virtues provide standards for morally acceptable decisions, without prescribing how we should reach them. However, moral theories do assume that we are, at least in principle, capable of making the right decisions. Consequently, an empirical investigation of the methods and resources we use for making moral decisions becomes relevant. We consider theoretical parallels of economic decision theory and moral utilitarianism and suggest that moral decision making may tap into mechanisms and processes that have originally evolved for nonmoral decision making. For example, the computation of reward value occurs through the combination of probability and magnitude; similar computation might also be used for determining utilitarian moral value. Both nonmoral and moral decisions may resort to intuitions and heuristics. Learning mechanisms implicated in the assignment of reward value to stimuli, actions, and outcomes may also enable us to determine moral value and assign it to stimuli, actions, and outcomes. In conclusion, we suggest that moral capabilities can employ and benefit from a variety of nonmoral decision-making and learning mechanisms.

  11. The drift diffusion model as the choice rule in reinforcement learning.

    PubMed

    Pedersen, Mads Lund; Frank, Michael J; Biele, Guido

    2017-08-01

    Current reinforcement-learning models often assume simplified decision processes that do not fully reflect the dynamic complexities of choice processes. Conversely, sequential-sampling models of decision making account for both choice accuracy and response time, but assume that decisions are based on static decision values. To combine these two computational models of decision making and learning, we implemented reinforcement-learning models in which the drift diffusion model describes the choice process, thereby capturing both within- and across-trial dynamics. To exemplify the utility of this approach, we quantitatively fit data from a common reinforcement-learning paradigm using hierarchical Bayesian parameter estimation, and compared model variants to determine whether they could capture the effects of stimulant medication in adult patients with attention-deficit hyperactivity disorder (ADHD). The model with the best relative fit provided a good description of the learning process, choices, and response times. A parameter recovery experiment showed that the hierarchical Bayesian modeling approach enabled accurate estimation of the model parameters. The model approach described here, using simultaneous estimation of reinforcement-learning and drift diffusion model parameters, shows promise for revealing new insights into the cognitive and neural mechanisms of learning and decision making, as well as the alteration of such processes in clinical groups.

  12. The drift diffusion model as the choice rule in reinforcement learning

    PubMed Central

    Frank, Michael J.

    2017-01-01

    Current reinforcement-learning models often assume simplified decision processes that do not fully reflect the dynamic complexities of choice processes. Conversely, sequential-sampling models of decision making account for both choice accuracy and response time, but assume that decisions are based on static decision values. To combine these two computational models of decision making and learning, we implemented reinforcement-learning models in which the drift diffusion model describes the choice process, thereby capturing both within- and across-trial dynamics. To exemplify the utility of this approach, we quantitatively fit data from a common reinforcement-learning paradigm using hierarchical Bayesian parameter estimation, and compared model variants to determine whether they could capture the effects of stimulant medication in adult patients with attention-deficit hyper-activity disorder (ADHD). The model with the best relative fit provided a good description of the learning process, choices, and response times. A parameter recovery experiment showed that the hierarchical Bayesian modeling approach enabled accurate estimation of the model parameters. The model approach described here, using simultaneous estimation of reinforcement-learning and drift diffusion model parameters, shows promise for revealing new insights into the cognitive and neural mechanisms of learning and decision making, as well as the alteration of such processes in clinical groups. PMID:27966103

  13. Withdrawal from Cocaine Self-Administration Produces Long-Lasting Deficits in Orbitofrontal-Dependent Reversal Learning in Rats

    ERIC Educational Resources Information Center

    Calu, Donna J.; Stalnaker, Thomas A.; Franz, Theresa M.; Singh, Teghpal; Shaham, Yavin; Schoenbaum, Geoffrey

    2007-01-01

    Drug addicts make poor decisions. These decision-making deficits have been modeled in addicts and laboratory animals using reversal-learning tasks. However, persistent reversal-learning impairments have been shown in rats and monkeys only after noncontingent cocaine injections. Current thinking holds that to represent the human condition…

  14. Reinforcement learning signals in the human striatum distinguish learners from nonlearners during reward-based decision making.

    PubMed

    Schönberg, Tom; Daw, Nathaniel D; Joel, Daphna; O'Doherty, John P

    2007-11-21

    The computational framework of reinforcement learning has been used to forward our understanding of the neural mechanisms underlying reward learning and decision-making behavior. It is known that humans vary widely in their performance in decision-making tasks. Here, we used a simple four-armed bandit task in which subjects are almost evenly split into two groups on the basis of their performance: those who do learn to favor choice of the optimal action and those who do not. Using models of reinforcement learning we sought to determine the neural basis of these intrinsic differences in performance by scanning both groups with functional magnetic resonance imaging. We scanned 29 subjects while they performed the reward-based decision-making task. Our results suggest that these two groups differ markedly in the degree to which reinforcement learning signals in the striatum are engaged during task performance. While the learners showed robust prediction error signals in both the ventral and dorsal striatum during learning, the nonlearner group showed a marked absence of such signals. Moreover, the magnitude of prediction error signals in a region of dorsal striatum correlated significantly with a measure of behavioral performance across all subjects. These findings support a crucial role of prediction error signals, likely originating from dopaminergic midbrain neurons, in enabling learning of action selection preferences on the basis of obtained rewards. Thus, spontaneously observed individual differences in decision making performance demonstrate the suggested dependence of this type of learning on the functional integrity of the dopaminergic striatal system in humans.

  15. A constructivist approach to studying the bullwhip effect by simulating the supply chain

    NASA Astrophysics Data System (ADS)

    González-Torre, Pilar L.; Adenso-Díaz, B.; Moreno, Plácido

    2015-11-01

    The Cider Game is a simulator for a supply chain-related learning environment. Its main feature is that it provides support to students in the constructivist discovery process when learning how to make logistics decisions, at the same time as noting the occurrence of the bullwhip phenomenon. This learning environment seeks a balance between direct instruction in the learning process on the part of the tutor, and a suitable and sufficient degree of freedom to regulate independent learning on the part of students. This article describes the basic learning mechanisms using the Cider Game and the graphical learning environments that it provides. We describe the functionality provided by this application, and analyse the effect over the rational understanding of the bullwhip phenomenon by the students and whether they are able to make decisions to minimise its impact, studying the differences when that decision-making learning is done individually or in groups.

  16. To Achieve or Not To Achieve: A Self-Regulation Perspective on Adolescents' Academic Decision Making.

    ERIC Educational Resources Information Center

    Miller, David C.; Byrnes, James P.

    2001-01-01

    This study investigated the utility of the self-regulation model of decision making for explaining and predicting adolescents' academic decision making. Measures included an assessment of decision-making skill; academic goals; select scales of Learning and Study Strategies Inventory; and teacher ratings of achievement behavior. Adolescents'…

  17. Moogle, Google, and Garbage Cans: The Impact of Technology on Decision Making

    ERIC Educational Resources Information Center

    Sellers, Martin P.

    2005-01-01

    Decision makers are faced daily with making important and pervasive decisions. This is especially significant in higher education, where decisions about academics will have considerable impact on the next generation of leaders. In place of rational decisions about the substance of learning and instruction, academic administrators make incremental…

  18. Improving "At-Action" Decision-Making in Team Sports through a Holistic Coaching Approach

    ERIC Educational Resources Information Center

    Light, Richard L.; Harvey, Stephen; Mouchet, Alain

    2014-01-01

    This article draws on Game Sense pedagogy and complex learning theory (CLT) to make suggestions for improving decision-making ability in team sports by adopting a holistic approach to coaching with a focus on decision-making "at-action". It emphasizes the complexity of decision-making and the need to focus on the game as a whole entity,…

  19. Role of the medial prefrontal cortex in impaired decision making in juvenile attention-deficit/hyperactivity disorder.

    PubMed

    Hauser, Tobias U; Iannaccone, Reto; Ball, Juliane; Mathys, Christoph; Brandeis, Daniel; Walitza, Susanne; Brem, Silvia

    2014-10-01

    Attention-deficit/hyperactivity disorder (ADHD) has been associated with deficient decision making and learning. Models of ADHD have suggested that these deficits could be caused by impaired reward prediction errors (RPEs). Reward prediction errors are signals that indicate violations of expectations and are known to be encoded by the dopaminergic system. However, the precise learning and decision-making deficits and their neurobiological correlates in ADHD are not well known. To determine the impaired decision-making and learning mechanisms in juvenile ADHD using advanced computational models, as well as the related neural RPE processes using multimodal neuroimaging. Twenty adolescents with ADHD and 20 healthy adolescents serving as controls (aged 12-16 years) were examined using a probabilistic reversal learning task while simultaneous functional magnetic resonance imaging and electroencephalogram were recorded. Learning and decision making were investigated by contrasting a hierarchical Bayesian model with an advanced reinforcement learning model and by comparing the model parameters. The neural correlates of RPEs were studied in functional magnetic resonance imaging and electroencephalogram. Adolescents with ADHD showed more simplistic learning as reflected by the reinforcement learning model (exceedance probability, Px = .92) and had increased exploratory behavior compared with healthy controls (mean [SD] decision steepness parameter β: ADHD, 4.83 [2.97]; controls, 6.04 [2.53]; P = .02). The functional magnetic resonance imaging analysis revealed impaired RPE processing in the medial prefrontal cortex during cue as well as during outcome presentation (P < .05, family-wise error correction). The outcome-related impairment in the medial prefrontal cortex could be attributed to deficient processing at 200 to 400 milliseconds after feedback presentation as reflected by reduced feedback-related negativity (ADHD, 0.61 [3.90] μV; controls, -1.68 [2.52] μV; P = .04). The combination of computational modeling of behavior and multimodal neuroimaging revealed that impaired decision making and learning mechanisms in adolescents with ADHD are driven by impaired RPE processing in the medial prefrontal cortex. This novel, combined approach furthers the understanding of the pathomechanisms in ADHD and may advance treatment strategies.

  20. Making Market Decisions in the Classroom.

    ERIC Educational Resources Information Center

    Rose, Stephen A.

    1986-01-01

    Computer software that will help intermediate and secondary social studies students learn to make rational decisions about personal and societal concerns are described. The courseware places students in the roles of business managers who make decisions about operating their firms. (RM)

  1. Seeing the forest through the trees: improving decision making on the Iowa gambling task by shifting focus from short- to long-term outcomes

    PubMed Central

    Buelow, Melissa T.; Okdie, Bradley M.; Blaine, Amber L.

    2013-01-01

    Introduction: The present study sought to examine two methods by which to improve decision making on the Iowa Gambling Task (IGT): inducing a negative mood and providing additional learning trials. Method: In the first study, 194 undergraduate students [74 male; Mage = 19.44 (SD = 3.69)] were randomly assigned to view a series of pictures to induce a positive, negative, or neutral mood immediately prior to the IGT. In the second study, 276 undergraduate students [111 male; Mage = 19.18 (SD = 2.58)] completed a delay discounting task and back-to-back administrations of the IGT. Results: Participants in an induced negative mood selected more from Deck C during the final trials than those in an induced positive mood. Providing additional learning trials resulted in better decision making: participants shifted their focus from the frequency of immediate gains/losses (i.e., a preference for Decks B and D) to long-term outcomes (i.e., a preference for Deck D). In addition, disadvantageous decision making on the additional learning trials was associated with larger delay discounting (i.e., a preference for more immediate but smaller rewards). Conclusions: The present results indicate that decision making is affected by negative mood state, and that decision making can be improved by increasing the number of learning trials. In addition, the current results provide evidence of a relationship between performance on the IGT and on a separate measure of decision making, the delay discounting task. Moreover, the present results indicate that improved decision making on the IGT can be attributed to shifting focus toward long-term outcomes, as evidenced by increased selections from advantageous decks as well as correlations between the IGT and delay discounting task. Implications for the assessment of decision making using the IGT are discussed. PMID:24151485

  2. Strategic Decision Making Cycle in Higher Education: Case Study of E-Learning

    ERIC Educational Resources Information Center

    Divjak, Blaženka; Redep, Nina Begicevic

    2015-01-01

    This paper presents the methodology for strategic decision making in higher education (HE). The methodology is structured as a cycle of strategic decision making with four phases, and it is focused on institutional and national perspective, i.e. on decision making that takes place at institutions of HE and relevant national authorities, in case…

  3. Data-Based Decision-Making: Developing a Method for Capturing Teachers' Understanding of CBM Graphs

    ERIC Educational Resources Information Center

    Espin, Christine A.; Wayman, Miya Miura; Deno, Stanley L.; McMaster, Kristen L.; de Rooij, Mark

    2017-01-01

    In this special issue, we explore the decision-making aspect of "data-based decision-making". The articles in the issue address a wide range of research questions, designs, methods, and analyses, but all focus on data-based decision-making for students with learning difficulties. In this first article, we introduce the topic of…

  4. Development and evaluation of learning module on clinical decision-making in Prosthodontics.

    PubMed

    Deshpande, Saee; Lambade, Dipti; Chahande, Jayashree

    2015-01-01

    Best practice strategies for helping students learn the reasoning skills of problem solving and critical thinking (CT) remain a source of conjecture, particularly with regard to CT. The dental education literature is fundamentally devoid of research on the cognitive components of clinical decision-making. This study was aimed to develop and evaluate the impact of blended learning module on clinical decision-making skills of dental graduates for planning prosthodontics rehabilitation. An interactive teaching module consisting of didactic lectures on clinical decision-making and a computer-assisted case-based treatment planning software was developed Its impact on cognitive knowledge gain in clinical decision-making was evaluated using an assessment involving problem-based multiple choice questions and paper-based case scenarios. Mean test scores were: Pretest (17 ± 1), posttest 1 (21 ± 2) and posttest 2 (43 ± 3). Comparison of mean scores was done with one-way ANOVA test. There was overall significant difference in between mean scores at all the three points (P < 0.001). A pair-wise comparison of mean scores was done with Bonferroni test. The mean difference is significant at the 0.05 level. The pair-wise comparison shows that posttest 2 score is significantly higher than posttest 1 and posttest 1 is significantly higher than pretest that is, pretest 2 > posttest 1 > pretest. Blended teaching methods employing didactic lectures on the clinical decision-making as well as computer assisted case-based learning can be used to improve quality of clinical decision-making in prosthodontic rehabilitation for dental graduates.

  5. Computational prediction of multidisciplinary team decision-making for adjuvant breast cancer drug therapies: a machine learning approach.

    PubMed

    Lin, Frank P Y; Pokorny, Adrian; Teng, Christina; Dear, Rachel; Epstein, Richard J

    2016-12-01

    Multidisciplinary team (MDT) meetings are used to optimise expert decision-making about treatment options, but such expertise is not digitally transferable between centres. To help standardise medical decision-making, we developed a machine learning model designed to predict MDT decisions about adjuvant breast cancer treatments. We analysed MDT decisions regarding adjuvant systemic therapy for 1065 breast cancer cases over eight years. Machine learning classifiers with and without bootstrap aggregation were correlated with MDT decisions (recommended, not recommended, or discussable) regarding adjuvant cytotoxic, endocrine and biologic/targeted therapies, then tested for predictability using stratified ten-fold cross-validations. The predictions so derived were duly compared with those based on published (ESMO and NCCN) cancer guidelines. Machine learning more accurately predicted adjuvant chemotherapy MDT decisions than did simple application of guidelines. No differences were found between MDT- vs. ESMO/NCCN- based decisions to prescribe either adjuvant endocrine (97%, p = 0.44/0.74) or biologic/targeted therapies (98%, p = 0.82/0.59). In contrast, significant discrepancies were evident between MDT- and guideline-based decisions to prescribe chemotherapy (87%, p < 0.01, representing 43% and 53% variations from ESMO/NCCN guidelines, respectively). Using ten-fold cross-validation, the best classifiers achieved areas under the receiver operating characteristic curve (AUC) of 0.940 for chemotherapy (95% C.I., 0.922-0.958), 0.899 for the endocrine therapy (95% C.I., 0.880-0.918), and 0.977 for trastuzumab therapy (95% C.I., 0.955-0.999) respectively. Overall, bootstrap aggregated classifiers performed better among all evaluated machine learning models. A machine learning approach based on clinicopathologic characteristics can predict MDT decisions about adjuvant breast cancer drug therapies. The discrepancy between MDT- and guideline-based decisions regarding adjuvant chemotherapy implies that certain non-clincopathologic criteria, such as patient preference and resource availability, are factored into clinical decision-making by local experts but not captured by guidelines.

  6. The Impact of Cooperative Learning on Developing the Sixth Grade Students Decision-Making Skill and Academic Achievement

    ERIC Educational Resources Information Center

    Asha, Intisar K.; Al Hawi, Asma M.

    2016-01-01

    This study aimed at investigating the effect of cooperative learning on developing the sixth graders' decision making skill and their academic achievement. The study sample, which was selected randomly, consisted of (46) students and divided into two groups: the experimental group that taught using the cooperative learning strategy and the control…

  7. Strategic Decision-Making Learning from Label Distributions: An Approach for Facial Age Estimation.

    PubMed

    Zhao, Wei; Wang, Han

    2016-06-28

    Nowadays, label distribution learning is among the state-of-the-art methodologies in facial age estimation. It takes the age of each facial image instance as a label distribution with a series of age labels rather than the single chronological age label that is commonly used. However, this methodology is deficient in its simple decision-making criterion: the final predicted age is only selected at the one with maximum description degree. In many cases, different age labels may have very similar description degrees. Consequently, blindly deciding the estimated age by virtue of the highest description degree would miss or neglect other valuable age labels that may contribute a lot to the final predicted age. In this paper, we propose a strategic decision-making label distribution learning algorithm (SDM-LDL) with a series of strategies specialized for different types of age label distribution. Experimental results from the most popular aging face database, FG-NET, show the superiority and validity of all the proposed strategic decision-making learning algorithms over the existing label distribution learning and other single-label learning algorithms for facial age estimation. The inner properties of SDM-LDL are further explored with more advantages.

  8. Strategic Decision-Making Learning from Label Distributions: An Approach for Facial Age Estimation

    PubMed Central

    Zhao, Wei; Wang, Han

    2016-01-01

    Nowadays, label distribution learning is among the state-of-the-art methodologies in facial age estimation. It takes the age of each facial image instance as a label distribution with a series of age labels rather than the single chronological age label that is commonly used. However, this methodology is deficient in its simple decision-making criterion: the final predicted age is only selected at the one with maximum description degree. In many cases, different age labels may have very similar description degrees. Consequently, blindly deciding the estimated age by virtue of the highest description degree would miss or neglect other valuable age labels that may contribute a lot to the final predicted age. In this paper, we propose a strategic decision-making label distribution learning algorithm (SDM-LDL) with a series of strategies specialized for different types of age label distribution. Experimental results from the most popular aging face database, FG-NET, show the superiority and validity of all the proposed strategic decision-making learning algorithms over the existing label distribution learning and other single-label learning algorithms for facial age estimation. The inner properties of SDM-LDL are further explored with more advantages. PMID:27367691

  9. Learning Strategy Preferences, Decision-Making Styles, Ways of Knowing, and Cultural Awareness of Members of the National Academic Advising Association

    ERIC Educational Resources Information Center

    Trout, Donna K.

    2009-01-01

    Academic advisors help students with the process of decision making, of making sense of their world, of understanding how they go about learning, and of understanding how to appreciate diversity in their world. If advisors are to help students in these areas, academic advisors should be aware of the cognitive processes of how they make sense of…

  10. Risky decision making from childhood through adulthood: Contributions of learning and sensitivity to negative feedback.

    PubMed

    Humphreys, Kathryn L; Telzer, Eva H; Flannery, Jessica; Goff, Bonnie; Gabard-Durnam, Laurel; Gee, Dylan G; Lee, Steve S; Tottenham, Nim

    2016-02-01

    Decision making in the context of risk is a complex and dynamic process that changes across development. Here, we assessed the influence of sensitivity to negative feedback (e.g., loss) and learning on age-related changes in risky decision making, both of which show unique developmental trajectories. In the present study, we examined risky decision making in 216 individuals, ranging in age from 3-26 years, using the balloon emotional learning task (BELT), a computerized task in which participants pump up a series of virtual balloons to earn points, but risk balloon explosion on each trial, which results in no points. It is important to note that there were 3 balloon conditions, signified by different balloon colors, ranging from quick- to slow-to-explode, and participants could learn the color-condition pairings through task experience. Overall, we found age-related increases in pumps made and points earned. However, in the quick-to-explode condition, there was a nonlinear adolescent peak for points earned. Follow-up analyses indicated that this adolescent phenotype occurred at the developmental intersection of linear age-related increases in learning and decreases in sensitivity to negative feedback. Adolescence was marked by intermediate values on both these processes. These findings show that a combination of linearly changing processes can result in nonlinear changes in risky decision making, the adolescent-specific nature of which is associated with developmental improvements in learning and reduced sensitivity to negative feedback. (c) 2016 APA, all rights reserved).

  11. Understanding medical decision making in hand surgery.

    PubMed

    Myers, John; McCabe, Steven J

    2005-10-01

    The practice of medicine takes place in an environment of uncertainty. Expected value decision making, prospect theory, and regret theory are three theories of decision making under uncertainty that may be used to help us learn how patients and physicians make decisions. These theories form the underpinnings of decision analysis and provide the opportunity to introduce the broad discipline of decision science. Because decision analysis and economic analysis are underrepresented in upper extremity surgery, the authors believe these are important areas for future research.

  12. Teacher Decision-Making.

    ERIC Educational Resources Information Center

    Smith, Carl B.

    Since teaching is fundamentally a decision-making process, analyzing teachers' decisions can lead to a better understanding of learning and of management in the classroom. Three major features of teacher decision making are (1) that teaching is an intensely active profession; (2) that most of the work of teaching occurs in a group setting; and (3)…

  13. Making the case for evidence-based design in healthcare: a descriptive case study of organizational decision making.

    PubMed

    Shoemaker, Lorie K; Kazley, Abby Swanson; White, Andrea

    2010-01-01

    The aim of this study was to describe the organizational decision-making process used in the selection of evidence-based design (EBD) concepts, the criteria used to make these decisions, and the extent to which leadership style may have influenced the decision-making process. Five research questions were formulated to frame the direction of this study, including: (1) How did healthcare leaders learn of innovations in design? (2) How did healthcare leaders make decisions in the selection of healthcare design concepts? (3) What criteria did healthcare leaders use in the decision-making process? (4) How did healthcare leaders consider input from the staff in design decisions? and (5) To what extent did the leadership style of administrators affect the outcomes of the decision-making process? Current issues affecting healthcare in the community led the principal investigator's organization to undertake an ambitious facilities expansion project. As part of its planning process, the organization learned of EBD principles that seemingly had a positive impact on patient care and safety and staff working conditions. Although promising, a paucity of empirical research addressed the cost/benefit of incorporating many EBD concepts into one hospital setting, and there was no research that articulated the organizational decision-making process used by healthcare administrators when considering the use of EBD in expansion projects. A mixed-method, descriptive, qualitative, single-case study and quantitative design were used to address the five research questions. The Systems Research Organizing Model provided the theoretical framework. A variety of data collection methods was used, including interviews of key respondents, the review of documentary evidence, and the Multifactor Leadership Questionnaire. A participatory process was used throughout the design decision phases, involving staff at all levels of the organization. The Internet and architects facilitated learning about EBD. Financial considerations were a factor in decision making. The prevalence of the transformational leadership style among the organization's administrators exceeded the U.S. mean.

  14. Conceptual Frameworks for the Workplace Change Adoption Process: Elements Integration from Decision Making and Learning Cycle Process.

    PubMed

    Radin Umar, Radin Zaid; Sommerich, Carolyn M; Lavender, Steve A; Sanders, Elizabeth; Evans, Kevin D

    2018-05-14

    Sound workplace ergonomics and safety-related interventions may be resisted by employees, and this may be detrimental to multiple stakeholders. Understanding fundamental aspects of decision making, behavioral change, and learning cycles may provide insights into pathways influencing employees' acceptance of interventions. This manuscript reviews published literature on thinking processes and other topics relevant to decision making and incorporates the findings into two new conceptual frameworks of the workplace change adoption process. Such frameworks are useful for thinking about adoption in different ways and testing changes to traditional intervention implementation processes. Moving forward, it is recommended that future research focuses on systematic exploration of implementation process activities that integrate principles from the research literature on sensemaking, decision making, and learning processes. Such exploration may provide the groundwork for development of specific implementation strategies that are theoretically grounded and provide a revised understanding of how successful intervention adoption processes work.

  15. The contribution of apathy and increased learning trials to risky decision-making in Parkinson's disease.

    PubMed

    Buelow, Melissa T; Frakey, Laura L; Grace, Janet; Friedman, Joseph H

    2014-02-01

    Impairments in executive functioning are commonly found in Parkinson's disease (PD); however, the research into risky decision making has been mixed. The present study sought to investigate three potential hypotheses: difficulty learning the task probabilities, levodopa equivalent dose (LED), and the presence of apathy. Twenty-four individuals with idiopathic PD and 13 healthy controls completed the Frontal Systems Behavior Scale to assess current apathy, the Iowa Gambling Task, and the Balloon Analog Risk Task (BART). Results indicated that individuals with PD selected more from Deck B, a disadvantageous deck. However, with an additional set of trials, participants with PD and apathy selected more from the most risky deck (Deck A). Apathy was not related to the BART, and LED was not related to either task. Results indicate that apathy is associated with decision-making in PD, and providing additional learning trials can improve decision-making in PD without apathy.

  16. Learning to make collective decisions: the impact of confidence escalation.

    PubMed

    Mahmoodi, Ali; Bang, Dan; Ahmadabadi, Majid Nili; Bahrami, Bahador

    2013-01-01

    Little is known about how people learn to take into account others' opinions in joint decisions. To address this question, we combined computational and empirical approaches. Human dyads made individual and joint visual perceptual decision and rated their confidence in those decisions (data previously published). We trained a reinforcement (temporal difference) learning agent to get the participants' confidence level and learn to arrive at a dyadic decision by finding the policy that either maximized the accuracy of the model decisions or maximally conformed to the empirical dyadic decisions. When confidences were shared visually without verbal interaction, RL agents successfully captured social learning. When participants exchanged confidences visually and interacted verbally, no collective benefit was achieved and the model failed to predict the dyadic behaviour. Behaviourally, dyad members' confidence increased progressively and verbal interaction accelerated this escalation. The success of the model in drawing collective benefit from dyad members was inversely related to confidence escalation rate. The findings show an automated learning agent can, in principle, combine individual opinions and achieve collective benefit but the same agent cannot discount the escalation suggesting that one cognitive component of collective decision making in human may involve discounting of overconfidence arising from interactions.

  17. Sensorimotor Learning Biases Choice Behavior: A Learning Neural Field Model for Decision Making

    PubMed Central

    Schöner, Gregor; Gail, Alexander

    2012-01-01

    According to a prominent view of sensorimotor processing in primates, selection and specification of possible actions are not sequential operations. Rather, a decision for an action emerges from competition between different movement plans, which are specified and selected in parallel. For action choices which are based on ambiguous sensory input, the frontoparietal sensorimotor areas are considered part of the common underlying neural substrate for selection and specification of action. These areas have been shown capable of encoding alternative spatial motor goals in parallel during movement planning, and show signatures of competitive value-based selection among these goals. Since the same network is also involved in learning sensorimotor associations, competitive action selection (decision making) should not only be driven by the sensory evidence and expected reward in favor of either action, but also by the subject's learning history of different sensorimotor associations. Previous computational models of competitive neural decision making used predefined associations between sensory input and corresponding motor output. Such hard-wiring does not allow modeling of how decisions are influenced by sensorimotor learning or by changing reward contingencies. We present a dynamic neural field model which learns arbitrary sensorimotor associations with a reward-driven Hebbian learning algorithm. We show that the model accurately simulates the dynamics of action selection with different reward contingencies, as observed in monkey cortical recordings, and that it correctly predicted the pattern of choice errors in a control experiment. With our adaptive model we demonstrate how network plasticity, which is required for association learning and adaptation to new reward contingencies, can influence choice behavior. The field model provides an integrated and dynamic account for the operations of sensorimotor integration, working memory and action selection required for decision making in ambiguous choice situations. PMID:23166483

  18. The Neuropsychology of Ventral Prefrontal Cortex: Decision-Making and Reversal Learning

    ERIC Educational Resources Information Center

    Clark, L.; Cools, R.; Robbins, T. W.

    2004-01-01

    Converging evidence from human lesion, animal lesion, and human functional neuroimaging studies implicates overlapping neural circuitry in ventral prefrontal cortex in decision-making and reversal learning. The ascending 5-HT and dopamine neurotransmitter systems have a modulatory role in both processes. There is accumulating evidence that…

  19. Lessons learned in applying ecosystem goods and services to community decision making

    EPA Science Inventory

    This report is intended to describe lessons learned from the application of FEGS-based research in a series of PBS conducted by EPA’s Office of Research and Development (ORD) and make this information available and useful for planning future research into local decision sup...

  20. Factors Affecting Decision-Making by Young Adults with Intellectual Disabilities.

    ERIC Educational Resources Information Center

    Jenkinson, Josephine C.

    1999-01-01

    Forty-eight young adults with mental retardation were placed into high and low learned helplessness groups based on responses to a questionnaire. Participants were presented with vignettes and asked what they would do. Results found low learned helplessness participants obtained significantly higher decision-making scores. Additional information…

  1. The Effects of Cognitive Process and Decision Making Training in Reading Experience on Meaningful Learning with Underachieving College Students

    ERIC Educational Resources Information Center

    Dean, Rebecca J.

    2010-01-01

    The ability of underprepared college students to read and learn from their reading is essential to their academic success and to their ability to persist towards completing their degree. The purposes of this study were to (a) assess the relationship between the cognitive processes of reading-based decision making and meaningful learning and (b)…

  2. A new computational account of cognitive control over reinforcement-based decision-making: Modeling of a probabilistic learning task.

    PubMed

    Zendehrouh, Sareh

    2015-11-01

    Recent work on decision-making field offers an account of dual-system theory for decision-making process. This theory holds that this process is conducted by two main controllers: a goal-directed system and a habitual system. In the reinforcement learning (RL) domain, the habitual behaviors are connected with model-free methods, in which appropriate actions are learned through trial-and-error experiences. However, goal-directed behaviors are associated with model-based methods of RL, in which actions are selected using a model of the environment. Studies on cognitive control also suggest that during processes like decision-making, some cortical and subcortical structures work in concert to monitor the consequences of decisions and to adjust control according to current task demands. Here a computational model is presented based on dual system theory and cognitive control perspective of decision-making. The proposed model is used to simulate human performance on a variant of probabilistic learning task. The basic proposal is that the brain implements a dual controller, while an accompanying monitoring system detects some kinds of conflict including a hypothetical cost-conflict one. The simulation results address existing theories about two event-related potentials, namely error related negativity (ERN) and feedback related negativity (FRN), and explore the best account of them. Based on the results, some testable predictions are also presented. Copyright © 2015 Elsevier Ltd. All rights reserved.

  3. The capacity of people with a 'mental disability' to make a health care decision.

    PubMed

    Wong, J G; Clare, C H; Holland, A J; Watson, P C; Gunn, M

    2000-03-01

    Based on the developing clinical and legal literature, and using the framework adopted in draft legislation, capacity to make a valid decision about a clinically required blood test was investigated in three groups of people with a 'mental disability' (i.e. mental illness (chronic schizophrenia), 'learning disability' ('mental retardation', or intellectual or developmental disability), or, dementia) and a fourth, comparison group. The three 'mental disability' groups (N = 20 in the 'learning disability' group, N = 21 in each of the other two groups) were recruited through the relevant local clinical services; and through a phlebotomy clinic for the 'general population' comparison group (N = 20). The decision-making task was progressively simplified by presenting the relevant information as separate elements and modifying the assessment of capacity so that responding became gradually less dependent on expressive verbal ability. Compared with the 'general population' group, capacity to make the particular decision was significantly more impaired in the 'learning disability' and 'dementia' groups. Importantly, however, it was not more impaired among the 'mental illness' group. All the groups benefited as the decision-making task was simplified, but at different stages. In each of the 'mental disability' groups, one participant benefited only when responding did not require any expensive verbal ability. Consistent with current views, capacity reflected an interaction between the decision-maker and the demands of the decision-making task. The findings have implications for the way in which decisions about health care interventions are sought from people with a 'mental disability'. The methodology may be extended to assess capacity to make other legally-significant decisions.

  4. Maladaptive Decision Making in Adults with a History of Adolescent Alcohol use, in a Preclinical Model, Is Attributable to the Compromised Assignment of Incentive Value during Stimulus-Reward Learning.

    PubMed

    Kruse, Lauren C; Schindler, Abigail G; Williams, Rapheal G; Weber, Sophia J; Clark, Jeremy J

    2017-01-01

    According to recent WHO reports, alcohol remains the number one substance used and abused by adolescents, despite public health efforts to curb its use. Adolescence is a critical period of biological maturation where brain development, particularly the mesocorticolimbic dopamine system, undergoes substantial remodeling. These circuits are implicated in complex decision making, incentive learning and reinforcement during substance use and abuse. An appealing theoretical approach has been to suggest that alcohol alters the normal development of these processes to promote deficits in reinforcement learning and decision making, which together make individuals vulnerable to developing substance use disorders in adulthood. Previously we have used a preclinical model of voluntary alcohol intake in rats to show that use in adolescence promotes risky decision making in adulthood that is mirrored by selective perturbations in dopamine network dynamics. Further, we have demonstrated that incentive learning processes in adulthood are also altered by adolescent alcohol use, again mirrored by changes in cue-evoked dopamine signaling. Indeed, we have proposed that these two processes, risk-based decision making and incentive learning, are fundamentally linked through dysfunction of midbrain circuitry where inputs to the dopamine system are disrupted by adolescent alcohol use. Here, we test the behavioral predictions of this model in rats and present the findings in the context of the prevailing literature with reference to the long-term consequences of early-life substance use on the vulnerability to develop substance use disorders. We utilize an impulsive choice task to assess the selectivity of alcohol's effect on decision-making profiles and conditioned reinforcement to parse out the effect of incentive value attribution, one mechanism of incentive learning. Finally, we use the differential reinforcement of low rates of responding (DRL) task to examine the degree to which behavioral disinhibition may contribute to an overall decision-making profile. The findings presented here support the proposition that early life alcohol use selectively alters risk-based choice behavior through modulation of incentive learning processes, both of which may be inexorably linked through perturbations in mesolimbic circuitry and may serve as fundamental vulnerabilities to the development of substance use disorders.

  5. Maladaptive Decision Making in Adults with a History of Adolescent Alcohol use, in a Preclinical Model, Is Attributable to the Compromised Assignment of Incentive Value during Stimulus-Reward Learning

    PubMed Central

    Kruse, Lauren C.; Schindler, Abigail G.; Williams, Rapheal G.; Weber, Sophia J.; Clark, Jeremy J.

    2017-01-01

    According to recent WHO reports, alcohol remains the number one substance used and abused by adolescents, despite public health efforts to curb its use. Adolescence is a critical period of biological maturation where brain development, particularly the mesocorticolimbic dopamine system, undergoes substantial remodeling. These circuits are implicated in complex decision making, incentive learning and reinforcement during substance use and abuse. An appealing theoretical approach has been to suggest that alcohol alters the normal development of these processes to promote deficits in reinforcement learning and decision making, which together make individuals vulnerable to developing substance use disorders in adulthood. Previously we have used a preclinical model of voluntary alcohol intake in rats to show that use in adolescence promotes risky decision making in adulthood that is mirrored by selective perturbations in dopamine network dynamics. Further, we have demonstrated that incentive learning processes in adulthood are also altered by adolescent alcohol use, again mirrored by changes in cue-evoked dopamine signaling. Indeed, we have proposed that these two processes, risk-based decision making and incentive learning, are fundamentally linked through dysfunction of midbrain circuitry where inputs to the dopamine system are disrupted by adolescent alcohol use. Here, we test the behavioral predictions of this model in rats and present the findings in the context of the prevailing literature with reference to the long-term consequences of early-life substance use on the vulnerability to develop substance use disorders. We utilize an impulsive choice task to assess the selectivity of alcohol’s effect on decision-making profiles and conditioned reinforcement to parse out the effect of incentive value attribution, one mechanism of incentive learning. Finally, we use the differential reinforcement of low rates of responding (DRL) task to examine the degree to which behavioral disinhibition may contribute to an overall decision-making profile. The findings presented here support the proposition that early life alcohol use selectively alters risk-based choice behavior through modulation of incentive learning processes, both of which may be inexorably linked through perturbations in mesolimbic circuitry and may serve as fundamental vulnerabilities to the development of substance use disorders. PMID:28790900

  6. Chronic Exposure to Methamphetamine Disrupts Reinforcement-Based Decision Making in Rats.

    PubMed

    Groman, Stephanie M; Rich, Katherine M; Smith, Nathaniel J; Lee, Daeyeol; Taylor, Jane R

    2018-03-01

    The persistent use of psychostimulant drugs, despite the detrimental outcomes associated with continued drug use, may be because of disruptions in reinforcement-learning processes that enable behavior to remain flexible and goal directed in dynamic environments. To identify the reinforcement-learning processes that are affected by chronic exposure to the psychostimulant methamphetamine (MA), the current study sought to use computational and biochemical analyses to characterize decision-making processes, assessed by probabilistic reversal learning, in rats before and after they were exposed to an escalating dose regimen of MA (or saline control). The ability of rats to use flexible and adaptive decision-making strategies following changes in stimulus-reward contingencies was significantly impaired following exposure to MA. Computational analyses of parameters that track choice and outcome behavior indicated that exposure to MA significantly impaired the ability of rats to use negative outcomes effectively. These MA-induced changes in decision making were similar to those observed in rats following administration of a dopamine D2/3 receptor antagonist. These data use computational models to provide insight into drug-induced maladaptive decision making that may ultimately identify novel targets for the treatment of psychostimulant addiction. We suggest that the disruption in utilization of negative outcomes to adaptively guide dynamic decision making is a new behavioral mechanism by which MA rigidly biases choice behavior.

  7. Lateral, not medial, prefrontal cortex contributes to punishment and aversive instrumental learning

    PubMed Central

    Jean-Richard-dit-Bressel, Philip

    2016-01-01

    Aversive outcomes punish behaviors that cause their occurrence. The prefrontal cortex (PFC) has been implicated in punishment learning and behavior, although the exact roles for different PFC regions in instrumental aversive learning and decision-making remain poorly understood. Here, we assessed the role of the orbitofrontal (OFC), rostral agranular insular (RAIC), prelimbic (PL), and infralimbic (IL) cortex in instrumental aversive learning and decision-making. Rats that pressed two individually presented levers for pellet rewards rapidly suppressed responding to one lever if it also caused mild punishment (punished lever) but continued pressing the other lever that did not cause punishment (unpunished lever). Inactivations of OFC, RAIC, IL, or PL via the GABA agonists baclofen and muscimol (BM) had no effect on the acquisition of instrumental learning. OFC inactivations increased responding on the punished lever during expression of well-learned instrumental aversive learning, whereas RAIC inactivations increased responding on the punished lever when both levers were presented simultaneously in an unpunished choice test. There were few effects of medial PFC (PL and IL) inactivation. These results suggest that lateral PFC, notably OFC and RAIC, have complementary functions in aversive instrumental learning and decision-making; OFC is important for using established aversive instrumental memories to guide behavior away from actions that cause punishment, whereas RAIC is important for aversive decision-making under conditions of choice. PMID:27918280

  8. Effects of Expertise and Cognitive Style on Information Use in Tactical Decision Making

    DTIC Science & Technology

    1988-06-01

    environmental situation. Demographic Characteristics Age Gender Rank/Command Level 5 Personality Characteristics Decision making style Cognitive style Learning...individuals with diverse decision making patterns to use a standard approach will adversely affect their decision making abilities. Further, the findings...Minneapolis MN: University of Minnesota, Cognitive, Science Research Group. Karp, S.A. (1963). Field dependence and overcoming embeddedness . J. Consult

  9. Neuroscientific evidence for contextual effects in decision making.

    PubMed

    Hytönen, Kaisa

    2014-02-01

    Both internal and external states can cause inconsistencies in decision behavior. I present examples from behavioral decision-making literature and review neuroscientific knowledge on two contextual influences: framing effects and social conformity. The brain mechanisms underlying these behavioral adjustments comply with the dual-process account and simple learning mechanisms, and are weak indicators for unintentionality in decision-making processes.

  10. Anticipatory stress restores decision-making deficits in heavy drinkers by increasing sensitivity to losses.

    PubMed

    Gullo, Matthew J; Stieger, Adam A

    2011-09-01

    Substance abusers are characterized by hypersensitivity to reward. This leads to maladaptive decisions generally, as well as those on laboratory-based decision-making tasks, such as the Iowa Gambling Task (IGT). Negative affect has also been shown to disrupt the decision-making of healthy individuals, particularly decisions made under uncertainty. Neuropsychological theories of learning, including the Somatic Marker Hypothesis (SMH), argue this occurs by amplifying affective responses to punishment. In substance abusers, this might serve to rebalance their sensitivity to reward with punishment, and improve decision-making. Before completing the IGT, 45 heavy and 47 light drinkers were randomly assigned to a control condition, or led to believe they had to give a stressful public speech. IGT performance was analyzed with the Expectancy-Valence (EV) learning model. Working memory and IQ were also assessed. Heavy drinkers made more disadvantageous decisions than light drinkers, due to higher attention to gains (versus losses) on the IGT. Anticipatory stress increased participants' attention to losses, significantly improving heavy drinkers' decision-making. Anticipatory stress increased attention to losses, effectively restoring decision-making deficits in heavy drinkers by rebalancing their reward sensitivity with punishment sensitivity. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  11. DECISION-MAKING IN THE SCHOOLS: AN OUTSIDER’S VIEW,

    DTIC Science & Technology

    DECISION MAKING , EDUCATION), (*EDUCATION, MANAGEMENT PLANNING AND CONTROL), (*MANAGEMENT PLANNING AND CONTROL, EDUCATION), BUDGETS, MANAGEMENT ENGINEERING, PERSONNEL MANAGEMENT, STUDENTS, LEARNING, OPTIMIZATION

  12. Team-Based Learning Instruction for Responsible Conduct of Research Positively Impacts Ethical Decision-Making

    PubMed Central

    McCormack, Wayne T.; Garvan, Cynthia W.

    2013-01-01

    Common practices for responsible conduct of research (RCR) instruction have recently been shown to have no positive impact on and possibly to undermine ethical decision-making (EDM). We show that a team-based learning (TBL) RCR curriculum results in some gains in decision ethicality, the use of more helpful meta-cognitive reasoning strategies in decision-making, and elimination of most negative effects of other forms of RCR instruction on social–behavioral responses. TBL supports the reasoning strategies and social mechanisms that underlie EDM and ethics instruction, and may provide a more effective method for RCR instruction than lectures and small group discussion. PMID:24073606

  13. Collaborative Strategic Decision Making in School Districts

    ERIC Educational Resources Information Center

    Brazer, S. David; Rich, William; Ross, Susan A.

    2010-01-01

    Purpose: The dual purpose of this paper is to determine how superintendents in US school districts work with stakeholders in the decision-making process and to learn how different choices superintendents make affect decision outcomes. Design/methodology/approach: This multiple case study of three school districts employs qualitative methodology to…

  14. Data Driven Decision Making in the Social Studies

    ERIC Educational Resources Information Center

    Ediger, Marlow

    2010-01-01

    Data driven decision making emphasizes the importance of the teacher using objective sources of information in developing the social studies curriculum. Too frequently, decisions of teachers have been made based on routine and outdated methods of teaching. Valid and reliable tests used to secure results from pupil learning make for better…

  15. Memory Accessibility and Medical Decision-Making for Significant Others: The Role of Socially Shared Retrieval-Induced Forgetting

    PubMed Central

    Coman, Dora; Coman, Alin; Hirst, William

    2013-01-01

    Medical decisions will often entail a broad search for relevant information. No sources alone may offer a complete picture, and many may be selective in their presentation. This selectivity may induce forgetting for previously learned material, thereby adversely affecting medical decision-making. In the study phase of two experiments, participants learned information about a fictitious disease and advantages and disadvantages of four treatment options. In the subsequent practice phase, they read a pamphlet selectively presenting either relevant (Experiment 1) or irrelevant (Experiment 2) advantages or disadvantages. A final cued recall followed and, in Experiment 2, a decision as to the best treatment for a patient. Not only did reading the pamphlet induce forgetting for related and unmentioned information, the induced forgetting adversely affected decision-making. The research provides a cautionary note about the risks of searching through selectively presented information when making a medical decision. PMID:23785320

  16. Beyond IQ: A Latent State-Trait Analysis of General Intelligence, Dynamic Decision Making, and Implicit Learning

    ERIC Educational Resources Information Center

    Danner, Daniel; Hagemann, Dirk; Schankin, Andrea; Hager, Marieke; Funke, Joachim

    2011-01-01

    The present study investigated cognitive performance measures beyond IQ. In particular, we investigated the psychometric properties of dynamic decision making variables and implicit learning variables and their relation with general intelligence and professional success. N = 173 employees from different companies and occupational groups completed…

  17. A Debate and Decision-Making Tool for Enhanced Learning

    ERIC Educational Resources Information Center

    López Garcia, Diego A.; Mateo Sanguino, Tomás de J.; Cortés Ancos, Estefania; Fernández de Viana González, Iñaki

    2016-01-01

    Debates have been used to develop critical thinking within teaching environments. Many learning activities are configured as working groups, which use debates to make decisions. Nevertheless, in a classroom debate, only a few students can participate; large work groups are similarly limited. Whilst the use of web tools would appear to offer a…

  18. Putting Bandits into Context: How Function Learning Supports Decision Making

    ERIC Educational Resources Information Center

    Schulz, Eric; Konstantinidis, Emmanouil; Speekenbrink, Maarten

    2018-01-01

    The authors introduce the contextual multi-armed bandit task as a framework to investigate learning and decision making in uncertain environments. In this novel paradigm, participants repeatedly choose between multiple options in order to maximize their rewards. The options are described by a number of contextual features which are predictive of…

  19. A Cross-National CAI Tool To Support Learning Operations Decision-Making and Market Analysis.

    ERIC Educational Resources Information Center

    Mockler, Robert J.; Afanasiev, Mikhail Y.; Dologite, Dorothy G.

    1999-01-01

    Describes bicultural (United States and Russia) development of a computer-aided instruction (CAI) tool to learn management decision-making using information systems technologies. The program has been used with undergraduate and graduate students in both countries; it integrates free and controlled market concepts and combines traditional computer…

  20. Entrepreneurial Decision Making Styles and Learning Strategies Preferences

    ERIC Educational Resources Information Center

    Hestand, Yana

    2012-01-01

    Scope and Method of Study: The scope of this study was the decision making styles and the learning strategies preferences among entrepreneurs. The study utilized a descriptive research design. Internet was utilized as a data collection tool, Participant in the study were 240 entrepreneurs from the Oklahoma state, Tulsa county members of the SBA.…

  1. Applying Social Learning Theory of Career Decision Making to Gay, Lesbian, Bisexual, Transgender, and Questioning Young Adults

    ERIC Educational Resources Information Center

    Datti, Paul A.

    2009-01-01

    Incorporating J. D. Krumboltz's (1979) social learning theory of career decision making, the author explores career development issues for gay, lesbian, bisexual, transgender, and questioning (GLBTQ) adolescents and young adults. Unique challenges for the GLBTQ population are discussed, specific recommendations for effective career counseling with…

  2. Cortical and Hippocampal Correlates of Deliberation during Model-Based Decisions for Rewards in Humans

    PubMed Central

    Bornstein, Aaron M.; Daw, Nathaniel D.

    2013-01-01

    How do we use our memories of the past to guide decisions we've never had to make before? Although extensive work describes how the brain learns to repeat rewarded actions, decisions can also be influenced by associations between stimuli or events not directly involving reward — such as when planning routes using a cognitive map or chess moves using predicted countermoves — and these sorts of associations are critical when deciding among novel options. This process is known as model-based decision making. While the learning of environmental relations that might support model-based decisions is well studied, and separately this sort of information has been inferred to impact decisions, there is little evidence concerning the full cycle by which such associations are acquired and drive choices. Of particular interest is whether decisions are directly supported by the same mnemonic systems characterized for relational learning more generally, or instead rely on other, specialized representations. Here, building on our previous work, which isolated dual representations underlying sequential predictive learning, we directly demonstrate that one such representation, encoded by the hippocampal memory system and adjacent cortical structures, supports goal-directed decisions. Using interleaved learning and decision tasks, we monitor predictive learning directly and also trace its influence on decisions for reward. We quantitatively compare the learning processes underlying multiple behavioral and fMRI observables using computational model fits. Across both tasks, a quantitatively consistent learning process explains reaction times, choices, and both expectation- and surprise-related neural activity. The same hippocampal and ventral stream regions engaged in anticipating stimuli during learning are also engaged in proportion to the difficulty of decisions. These results support a role for predictive associations learned by the hippocampal memory system to be recalled during choice formation. PMID:24339770

  3. Learning from Failed Decisions

    ERIC Educational Resources Information Center

    Nutt, Paul C.

    2010-01-01

    The consequences and dilemmas posed by learning issues for decision making are discussed. Learning requires both awareness of barriers and a coping strategy. The motives to hold back information essential for learning stem from perverse incentives, obscure outcomes, and the hindsight bias. There is little awareness of perverse incentives that…

  4. School-Based Decision Making: Linking Decisions to Learning. Third-Year Report to the Prichard Committee.

    ERIC Educational Resources Information Center

    David, Jane L.

    Under the Kentucky Education Reform Act (KERA), School-Based Decision Making (SBDM) is the provision that creates school councils and delegates to them the authority to make important educational decisions to improve student performance. This paper describes findings from the third year of a 5-year study of SBDM that focused on early examples of…

  5. Frequencies of decision making and monitoring in adaptive resource management

    PubMed Central

    Johnson, Fred A.

    2017-01-01

    Adaptive management involves learning-oriented decision making in the presence of uncertainty about the responses of a resource system to management. It is implemented through an iterative sequence of decision making, monitoring and assessment of system responses, and incorporating what is learned into future decision making. Decision making at each point is informed by a value or objective function, for example total harvest anticipated over some time frame. The value function expresses the value associated with decisions, and it is influenced by system status as updated through monitoring. Often, decision making follows shortly after a monitoring event. However, it is certainly possible for the cadence of decision making to differ from that of monitoring. In this paper we consider different combinations of annual and biennial decision making, along with annual and biennial monitoring. With biennial decision making decisions are changed only every other year; with biennial monitoring field data are collected only every other year. Different cadences of decision making combine with annual and biennial monitoring to define 4 scenarios. Under each scenario we describe optimal valuations for active and passive adaptive decision making. We highlight patterns in valuation among scenarios, depending on the occurrence of monitoring and decision making events. Differences between years are tied to the fact that every other year a new decision can be made no matter what the scenario, and state information is available to inform that decision. In the subsequent year, however, in 3 of the 4 scenarios either a decision is repeated or monitoring does not occur (or both). There are substantive differences in optimal values among the scenarios, as well as the optimal policies producing those values. Especially noteworthy is the influence of monitoring cadence on valuation in some years. We highlight patterns in policy and valuation among the scenarios, and discuss management implications and extensions. PMID:28800591

  6. Frequencies of decision making and monitoring in adaptive resource management

    USGS Publications Warehouse

    Williams, Byron K.; Johnson, Fred A.

    2017-01-01

    Adaptive management involves learning-oriented decision making in the presence of uncertainty about the responses of a resource system to management. It is implemented through an iterative sequence of decision making, monitoring and assessment of system responses, and incorporating what is learned into future decision making. Decision making at each point is informed by a value or objective function, for example total harvest anticipated over some time frame. The value function expresses the value associated with decisions, and it is influenced by system status as updated through monitoring. Often, decision making follows shortly after a monitoring event. However, it is certainly possible for the cadence of decision making to differ from that of monitoring. In this paper we consider different combinations of annual and biennial decision making, along with annual and biennial monitoring. With biennial decision making decisions are changed only every other year; with biennial monitoring field data are collected only every other year. Different cadences of decision making combine with annual and biennial monitoring to define 4 scenarios. Under each scenario we describe optimal valuations for active and passive adaptive decision making. We highlight patterns in valuation among scenarios, depending on the occurrence of monitoring and decision making events. Differences between years are tied to the fact that every other year a new decision can be made no matter what the scenario, and state information is available to inform that decision. In the subsequent year, however, in 3 of the 4 scenarios either a decision is repeated or monitoring does not occur (or both). There are substantive differences in optimal values among the scenarios, as well as the optimal policies producing those values. Especially noteworthy is the influence of monitoring cadence on valuation in some years. We highlight patterns in policy and valuation among the scenarios, and discuss management implications and extensions.

  7. 'Kids need to talk too': inclusive practices for children's healthcare education and participation.

    PubMed

    Koller, Donna

    2017-09-01

    To examine how children with chronic medical conditions view healthcare education and decision-making and to propose the application of the universal design for learning in paediatric settings. Children and adolescents with chronic medical conditions tend to be excluded from healthcare decision-making. In schools, the universal design for learning promotes access to education and participation in school communities for all children, regardless of their disabilities or medical needs, rendering it an appropriate model for children's participation in healthcare decision-making. This article presents findings from a qualitative study with 26 children and adolescents with chronic medical conditions about their views and experiences with healthcare education and decision-making. Twenty-six children and adolescents with chronic medical conditions were interviewed using semi-structured interviews. Findings provide evidence that clinical practices often fail to provide equal opportunities for paediatric patients to understand their condition, share their views and/or participate in decisions regarding their care. In response to ongoing concerns about paediatric decision-making, we propose that the universal design for learning be adapted in paediatrics. The model presents exemplary programmes as inclusive, accounting for the needs of all children through multiple means of engagement and expression. A discussion of how the principles of universal design for learning could be applied in paediatric settings is offered for the purpose of advancing ethical and psychosocial care for all children regardless of their age, developmental capacity or condition. © 2016 John Wiley & Sons Ltd.

  8. Parental Influence on Exploratory Students' College Choice, Major, and Career Decision Making

    ERIC Educational Resources Information Center

    Workman, Jamie L.

    2015-01-01

    This article explores parental influence on exploratory students' college choice, major, and career decision making. The research began with examination of a first year academic advising model and Living Learning Community. Parental influence emerged as a key theme in student decision making processes. The project was conducted using grounded…

  9. Effects of Direct and Indirect Instruction on Fostering Decision-Making Competence in Socioscientific Issues

    ERIC Educational Resources Information Center

    Bottcher, Florian; Meisert, Anke

    2013-01-01

    In this study the effects of different learning environments on the promotion of decision-making competence for the socioscientific issue of genetically modified crops is investigated. The comparison focuses on direct vs. indirect instructions. Therefore on the one hand a sophisticated decision-making strategy was presented to the directly…

  10. Discussion. Think SMART, Not Hard--A Review of Teaching Decision Making in Sport from an Ecological Rationality Perspective

    ERIC Educational Resources Information Center

    Raab, Markus

    2007-01-01

    Background: Recent developments of theories for teaching decision making in sport offer a large variety of applications for the context of physical education. Purpose: This review of current models of teaching tactical skills concludes that most models incorporate different cognitive learning mechanisms, such as implicit and explicit learning, and…

  11. A Feedback Learning and Mental Models Perspective on Strategic Decision Making

    ERIC Educational Resources Information Center

    Capelo, Carlos; Dias, Joao Ferreira

    2009-01-01

    This study aims to be a contribution to a theoretical model that explains the effectiveness of the learning and decision-making processes by means of a feedback and mental models perspective. With appropriate mental models, managers should be able to improve their capacity to deal with dynamically complex contexts, in order to achieve long-term…

  12. Brain Regions Involved in the Learning and Application of Reward Rules in a Two-Deck Gambling Task

    ERIC Educational Resources Information Center

    Hartstra, E.; Oldenburg, J. F. E.; Van Leijenhorst, L.; Rombouts, S. A. R. B.; Crone, E. A.

    2010-01-01

    Decision-making involves the ability to choose between competing actions that are associated with uncertain benefits and penalties. The Iowa Gambling Task (IGT), which mimics real-life decision-making, involves learning a reward-punishment rule over multiple trials. Patients with damage to ventromedial prefrontal cortex (VMPFC) show deficits…

  13. Valuing in Decision-Making Ability: Teaching, Learning, and Assessment across the Curriculum and Campus Culture at Alverno College

    ERIC Educational Resources Information Center

    Eastberg, Jodi R. B.

    2011-01-01

    For the past 40 years, Alverno College faculty, staff, and students have collaborated in the creation of an integrated learning and assessment model that requires students to demonstrate, and faculty to assess, eight core abilities: Communication, Analysis, Problem Solving, Valuing in Decision-Making, Social Interaction, Developing a Global…

  14. Gaze data reveal distinct choice processes underlying model-based and model-free reinforcement learning

    PubMed Central

    Konovalov, Arkady; Krajbich, Ian

    2016-01-01

    Organisms appear to learn and make decisions using different strategies known as model-free and model-based learning; the former is mere reinforcement of previously rewarded actions and the latter is a forward-looking strategy that involves evaluation of action-state transition probabilities. Prior work has used neural data to argue that both model-based and model-free learners implement a value comparison process at trial onset, but model-based learners assign more weight to forward-looking computations. Here using eye-tracking, we report evidence for a different interpretation of prior results: model-based subjects make their choices prior to trial onset. In contrast, model-free subjects tend to ignore model-based aspects of the task and instead seem to treat the decision problem as a simple comparison process between two differentially valued items, consistent with previous work on sequential-sampling models of decision making. These findings illustrate a problem with assuming that experimental subjects make their decisions at the same prescribed time. PMID:27511383

  15. Learning to choose: Cognitive aging and strategy selection learning in decision making.

    PubMed

    Mata, Rui; von Helversen, Bettina; Rieskamp, Jörg

    2010-06-01

    Decision makers often have to learn from experience. In these situations, people must use the available feedback to select the appropriate decision strategy. How does the ability to select decision strategies on the basis of experience change with age? We examined younger and older adults' strategy selection learning in a probabilistic inference task using a computational model of strategy selection learning. Older adults showed poorer decision performance compared with younger adults. In particular, older adults performed poorly in an environment favoring the use of a more cognitively demanding strategy. The results suggest that the impact of cognitive aging on strategy selection learning depends on the structure of the decision environment. (c) 2010 APA, all rights reserved

  16. Making the Most of Continuing Medical Education: Evidence of Transformative Learning During a Course in Evidence-Based Medicine and Decision Making.

    PubMed

    Sokol, Randi G; Shaughnessy, Allen F

    2018-01-01

    Continuing medical information courses have been criticized for not promoting behavior change among their participants. For behavior change to occur, participants often need to consciously reject previous ideas and transform their way of thinking. Transformational learning is a process that cultivates deep emotional responses and can lead to cognitive and behavioral change in learners, potentially facilitating rich learning experiences and expediting knowledge translation. We explored participants' experiences at a 2-day conference designed to support transformative learning as they encounter new concepts within Information Mastery, which challenge their previous frameworks around the topic of medical decision making. Using the lens of transformative learning theory, we asked: how does Information Mastery qualitatively promote perspective transformation and hence behavior change? We used a hermeneutic phenomenologic approach to capture the lived experience of 12 current and nine previous attendees of the "Information Mastery" course through individual interviews, focus groups, and observation. Data were thematically analyzed. Both prevoius and current conference attendees described how the delivery of new concepts about medical decision making evoked strong emotional responses, facilitated personal transformation, and propelled expedited behavior change around epistemological, moral, and information management themes, resulting in a newfound sense of self-efficacy, confidence, and ownership in their ability to make medical decisions. When the topic area holds the potential to foster a qualitative reframing of learners' guiding paradigms and worldviews, attention should be paid to supporting learners' personalized meaning-making process through transformative learning opportunities to promote translation into practice.

  17. Integrating advice and experience: learning and decision making with social and nonsocial cues.

    PubMed

    Collins, Elizabeth C; Percy, Elise J; Smith, Eliot R; Kruschke, John K

    2011-06-01

    When making decisions, people typically gather information from both social and nonsocial sources, such as advice from others and direct experience. This research adapted a cognitive learning paradigm to examine the process by which people learn what sources of information are credible. When participants relied on advice alone to make decisions, their learning of source reliability proceeded in a manner analogous to traditional cue learning processes and replicated the established learning phenomena. However, when advice and nonsocial cues were encountered together as an established phenomenon, blocking (ignoring redundant information) did not occur. Our results suggest that extant cognitive learning models can accommodate either advice or nonsocial cues in isolation. However, the combination of advice and nonsocial cues (a context more typically encountered in daily life) leads to different patterns of learning, in which mutually supportive information from different types of sources is not regarded as redundant and may be particularly compelling. For these situations, cognitive learning models still constitute a promising explanatory tool but one that must be expanded. As such, these findings have important implications for social psychological theory and for cognitive models of learning. 2011 APA, all rights reserved

  18. Anhedonia and anxiety underlying depressive symptomatology have distinct effects on reward-based decision-making.

    PubMed

    Harlé, Katia M; Guo, Dalin; Zhang, Shunan; Paulus, Martin P; Yu, Angela J

    2017-01-01

    Depressive pathology, which includes both heightened negative affect (e.g., anxiety) and reduced positive affect (e.g., anhedonia), is known to be associated with sub-optimal decision-making, particularly in uncertain environments. Here, we use a computational approach to quantify and disambiguate how individual differences in these affective measures specifically relate to different aspects of learning and decision-making in reward-based choice behavior. Fifty-three individuals with a range of depressed mood completed a two-armed bandit task, in which they choose between two arms with fixed but unknown reward rates. The decision-making component, which chooses among options based on current expectations about reward rates, is modeled by two different decision policies: a learning-independent Win-stay/Lose-shift (WSLS) policy that ignores all previous experiences except the last trial, and Softmax, which prefers the arm with the higher expected reward. To model the learning component for the Softmax choice policy, we use a Bayesian inference model, which updates estimated reward rates based on the observed history of trial outcomes. Softmax with Bayesian learning better fits the behavior of 55% of the participants, while the others are better fit by a learning-independent WSLS strategy. Among Softmax "users", those with higher anhedonia are less likely to choose the option estimated to be most rewarding. Moreover, the Softmax parameter mediates the inverse relationship between anhedonia and overall monetary gains. On the other hand, among WSLS "users", higher state anxiety correlates with increasingly better ability of WSLS, relative to Softmax, to explain subjects' trial-by-trial choices. In summary, there is significant variability among individuals in their reward-based, exploratory decision-making, and this variability is at least partly mediated in a very specific manner by affective attributes, such as hedonic tone and state anxiety.

  19. Preaching What We Practice: Teaching Ethical Decision-Making to Computer Security Professionals

    NASA Astrophysics Data System (ADS)

    Fleischmann, Kenneth R.

    The biggest challenge facing computer security researchers and professionals is not learning how to make ethical decisions; rather it is learning how to recognize ethical decisions. All too often, technology development suffers from what Langdon Winner terms technological somnambulism - we sleepwalk through our technology design, following past precedents without a second thought, and fail to consider the perspectives of other stakeholders [1]. Computer security research and practice involves a number of opportunities for ethical decisions. For example, decisions about whether or not to automatically provide security updates involve tradeoffs related to caring versus user autonomy. Decisions about online voting include tradeoffs between convenience and security. Finally, decisions about routinely screening e-mails for spam involve tradeoffs of efficiency and privacy. It is critical that these and other decisions facing computer security researchers and professionals are confronted head on as value-laden design decisions, and that computer security researchers and professionals consider the perspectives of various stakeholders in making these decisions.

  20. Goal-Proximity Decision-Making

    ERIC Educational Resources Information Center

    Veksler, Vladislav D.; Gray, Wayne D.; Schoelles, Michael J.

    2013-01-01

    Reinforcement learning (RL) models of decision-making cannot account for human decisions in the absence of prior reward or punishment. We propose a mechanism for choosing among available options based on goal-option association strengths, where association strengths between objects represent previously experienced object proximity. The proposed…

  1. Fast and Accurate Learning When Making Discrete Numerical Estimates.

    PubMed

    Sanborn, Adam N; Beierholm, Ulrik R

    2016-04-01

    Many everyday estimation tasks have an inherently discrete nature, whether the task is counting objects (e.g., a number of paint buckets) or estimating discretized continuous variables (e.g., the number of paint buckets needed to paint a room). While Bayesian inference is often used for modeling estimates made along continuous scales, discrete numerical estimates have not received as much attention, despite their common everyday occurrence. Using two tasks, a numerosity task and an area estimation task, we invoke Bayesian decision theory to characterize how people learn discrete numerical distributions and make numerical estimates. Across three experiments with novel stimulus distributions we found that participants fell between two common decision functions for converting their uncertain representation into a response: drawing a sample from their posterior distribution and taking the maximum of their posterior distribution. While this was consistent with the decision function found in previous work using continuous estimation tasks, surprisingly the prior distributions learned by participants in our experiments were much more adaptive: When making continuous estimates, participants have required thousands of trials to learn bimodal priors, but in our tasks participants learned discrete bimodal and even discrete quadrimodal priors within a few hundred trials. This makes discrete numerical estimation tasks good testbeds for investigating how people learn and make estimates.

  2. Fast and Accurate Learning When Making Discrete Numerical Estimates

    PubMed Central

    Sanborn, Adam N.; Beierholm, Ulrik R.

    2016-01-01

    Many everyday estimation tasks have an inherently discrete nature, whether the task is counting objects (e.g., a number of paint buckets) or estimating discretized continuous variables (e.g., the number of paint buckets needed to paint a room). While Bayesian inference is often used for modeling estimates made along continuous scales, discrete numerical estimates have not received as much attention, despite their common everyday occurrence. Using two tasks, a numerosity task and an area estimation task, we invoke Bayesian decision theory to characterize how people learn discrete numerical distributions and make numerical estimates. Across three experiments with novel stimulus distributions we found that participants fell between two common decision functions for converting their uncertain representation into a response: drawing a sample from their posterior distribution and taking the maximum of their posterior distribution. While this was consistent with the decision function found in previous work using continuous estimation tasks, surprisingly the prior distributions learned by participants in our experiments were much more adaptive: When making continuous estimates, participants have required thousands of trials to learn bimodal priors, but in our tasks participants learned discrete bimodal and even discrete quadrimodal priors within a few hundred trials. This makes discrete numerical estimation tasks good testbeds for investigating how people learn and make estimates. PMID:27070155

  3. The Relationship of Decision-Making Styles and Attributional Styles in Addicted and Non-addicted Men.

    PubMed

    Shaghaghy, Farhad; Saffarinia, Majid; Iranpoor, Mohadeseh; Soltanynejad, Ali

    2011-01-01

    One of social problems which has affected our society and resulted in problems for different groups of people is drug abuse. This issue indicates a serious psychological, physical and social problem in community. Social skills have positive and successful influences in prevention of substance abuse. This includes the ability to explain events correctly and then appropriate decision making. This study compares decision making styles and attributional styles between addicted and non addicted men to recognize their role in addiction. In this study, 200 addicted and non addicted men were randomly selected. Decision-making style and attributional style questionnaires were used. Data analysis was performed by independent Student's t and Pearson correlation tests. The study population included 81 addicted and 90 non-addicted men. Addicted and non addicted men were significantly different in rational decision-making style (P < 0.05). Negative relationship was found between rational decision making and optimistic attribution style (r = -0.305, P < 0.01) and direct relationship was found between rational decision making and learned helplessness (r = 0.309, P < 0.01). Our study showed that addicts are less rational in decision making and addicts that developed learned helplessness were less rational and did not have optimistic attribution style. These issues show that addiction institutions and therapists have to pay attention to cognitive factors for addiction prevention.

  4. Discovering Decision Knowledge from Web Log Portfolio for Managing Classroom Processes by Applying Decision Tree and Data Cube Technology.

    ERIC Educational Resources Information Center

    Chen, Gwo-Dong; Liu, Chen-Chung; Ou, Kuo-Liang; Liu, Baw-Jhiune

    2000-01-01

    Discusses the use of Web logs to record student behavior that can assist teachers in assessing performance and making curriculum decisions for distance learning students who are using Web-based learning systems. Adopts decision tree and data cube information processing methodologies for developing more effective pedagogical strategies. (LRW)

  5. How Citizens Learn and Use Scientific and Technical Information in Environmental Decision Making

    ERIC Educational Resources Information Center

    Hartley, Troy W.

    2005-01-01

    There is concern that laypersons participating in environmental or natural resource decision making cannot or do not engage the scientific and technical information sufficiently to integrate that information into the decisions and reach a highquality, science-based decision. This study examined how thirteen citizens participating in two Superfund…

  6. Decision Making for Democratic Leadership in a Guided Internship

    ERIC Educational Resources Information Center

    Klinker, JoAnn Franklin; Hoover, J. Duane; Valle, Fernando; Hardin, Fred

    2014-01-01

    Experience in problem-based learning, authentic experiences, on-the-job decision making, and critical reflection on decisions made formed the conceptual framework of an internship to develop democratic leadership as a professional ethic in interns. Interns in an on-the-job guided internship examined decisions over a 13-week period as they…

  7. Decision-Making in Elementary School-Age Children: Effects Upon Motor Learning and Self-Concept Development.

    ERIC Educational Resources Information Center

    Lydon, Mary C.; Cheffers, John T. F.

    1984-01-01

    This article reports on a study that sought to determine the effects of variable decision-making teaching models upon the development of body coordination and self-concept of elementary school children. Results indicated that level of motor skill achievement was maintained when students were given decision-making responsibility. (Author/DF)

  8. The Financial and Non-Financial Aspects of Developing a Data-Driven Decision-Making Mindset in an Undergraduate Business Curriculum

    ERIC Educational Resources Information Center

    Bohler, Jeffrey; Krishnamoorthy, Anand; Larson, Benjamin

    2017-01-01

    Making data-driven decisions is becoming more important for organizations faced with confusing and often contradictory information available to them from their operating environment. This article examines one college of business' journey of developing a data-driven decision-making mindset within its undergraduate curriculum. Lessons learned may be…

  9. American Academy of Hospice and Palliative Medicine

    MedlinePlus

    ... Connect. Learn more and register! New NQP Shared Decision Making Action Brief Released A new NQF National Quality Partners (NQP™) Shared Decision Making Action Brief has been issued calling for all ...

  10. Developing a Decision-Making Plan for the Reading Teacher. Learning Package No. 25.

    ERIC Educational Resources Information Center

    Smith, Carl, Comp.

    Originally developed for the Department of Defense Schools (DoDDS) system, this learning package on developing a decision-making plan for the reading teacher is designed for teachers who wish to upgrade or expand their teaching skills on their own. The package includes a comprehensive search of the ERIC database; a lecture giving an overview on…

  11. Active and passive spatial learning in human navigation: acquisition of graph knowledge.

    PubMed

    Chrastil, Elizabeth R; Warren, William H

    2015-07-01

    It is known that active exploration of a new environment leads to better spatial learning than does passive visual exposure. We ask whether specific components of active learning differentially contribute to particular forms of spatial knowledge-the exploration-specific learning hypothesis. Previously, we found that idiothetic information during walking is the primary active contributor to metric survey knowledge (Chrastil & Warren, 2013). In this study, we test the contributions of 3 components to topological graph and route knowledge: visual information, idiothetic information, and cognitive decision making. Four groups of participants learned the locations of 8 objects in a virtual hedge maze by (a) walking or (b) watching a video, crossed with (1) either making decisions about their path or (2) being guided through the maze. Route and graph knowledge were assessed by walking in the maze corridors from a starting object to the remembered location of a test object, with frequent detours. Decision making during exploration significantly contributed to subsequent route finding in the walking condition, whereas idiothetic information did not. Participants took novel routes and the metrically shortest routes on the majority of both direct and barrier trials, indicating that labeled graph knowledge-not merely route knowledge-was acquired. We conclude that, consistent with the exploration-specific learning hypothesis, decision making is the primary component of active learning for the acquisition of topological graph knowledge, whereas idiothetic information is the primary component for metric survey knowledge. (c) 2015 APA, all rights reserved.

  12. Impaired decision-making and selective cortical frontal thinning in Cushing's syndrome.

    PubMed

    Crespo, Iris; Esther, Granell-Moreno; Santos, Alicia; Valassi, Elena; Yolanda, Vives-Gilabert; De Juan-Delago, Manel; Webb, Susan M; Gómez-Ansón, Beatriz; Resmini, Eugenia

    2014-12-01

    Cushing's syndrome (CS) is caused by a glucocorticoid excess. This hypercortisolism can damage the prefrontal cortex, known to be important in decision-making. Our aim was to evaluate decision-making in CS and to explore cortical thickness. Thirty-five patients with CS (27 cured, eight medically treated) and thirty-five matched controls were evaluated using Iowa gambling task (IGT) and 3 Tesla magnetic resonance imaging (MRI) to assess cortical thickness. The IGT evaluates decision-making, including strategy and learning during the test. Cortical thickness was determined on MRI using freesurfer software tools, including a whole-brain analysis. There were no differences between medically treated and cured CS patients. They presented an altered decision-making strategy compared to controls, choosing a lower number of the safer cards (P < 0·05). They showed more difficulties than controls to learn the correct profiles of wins and losses for each card group (P < 0·05). In whole-brain analysis, patients with CS showed decreased cortical thickness in the left superior frontal cortex, left precentral cortex, left insular cortex, left and right rostral anterior cingulate cortex, and right caudal middle frontal cortex compared to controls (P < 0·001). Patients with CS failed to learn advantageous strategies and their behaviour was driven by short-term reward and long-term punishment, indicating learning problems because they did not use previous experience as a feedback factor to regulate their choices. These alterations in decision-making and the decreased cortical thickness in frontal areas suggest that chronic hypercortisolism promotes brain changes which are not completely reversible after endocrine remission. © 2014 John Wiley & Sons Ltd.

  13. How do beliefs and other factors such as prior experience influence the decision-making of new teachers during their first year teaching experience?

    NASA Astrophysics Data System (ADS)

    Short, Barbara J.

    2003-06-01

    The qualitative research project explored the perceptions of three new secondary education physics teachers. The content question stated: How do beliefs and other factors such as prior experience influence the decision-making of new teachers during their first year teaching experience? Specific questions includes: (1) What do first year teachers identify as their beliefs about teaching and learning? (2) How do first year teachers arrive at decisions about their instruction, materials, lessons, assessment, and student achievement? (3) How does decision-making occur in the learning environment from their perspective? (4) How do first year teachers solve problems? (5) To what extent do first year teachers actively think about what they do? The participants and their university professor were interviewed. Data was collected, transcribed, and coded using grounded theory techniques to conclude: (1) Belief systems take time to develop using filters. (2) Beliefs and perceptions help to fill gaps between knowledge. Gestalts change beliefs. (3) Modeling is a powerful technique influencing decision-making and beliefs over time. (4) Nurturing and preparation build confidence fostered at the university and public school. (5) New teachers' personalities, dispositions, and self-understandings effect filtering of perceptions, influencing behaviors in the learning environment. (6) Knowledge gained through experience, instruction, and reflection by the teacher enhances student learning. (7) Problem solving is learned and personality-based, helping to determine success. (8) Too many constraints to a novice cause limitations in his/her ability to be an effective teacher. (9) Early acceptance into a new environment helps to increase a sense of belonging leading to performance. (10) Positive attitudes towards students affect relationships with students in the classroom. (11) Backgrounds, personalities, and environments affect beliefs and decision-making. (12) New teachers focus more on their actions than on their students' learning. Implications are made for university pre-service instruction and public schools new teacher support systems.

  14. Constraints on decision making: implications from genetics, personality, and addiction.

    PubMed

    Baker, Travis E; Stockwell, Tim; Holroyd, Clay B

    2013-09-01

    An influential neurocomputational theory of the biological mechanisms of decision making, the "basal ganglia go/no-go model," holds that individual variability in decision making is determined by differences in the makeup of a striatal system for approach and avoidance learning. The model has been tested empirically with the probabilistic selection task (PST), which determines whether individuals learn better from positive or negative feedback. In accordance with the model, in the present study we examined whether an individual's ability to learn from positive and negative reinforcement can be predicted by genetic factors related to the midbrain dopamine system. We also asked whether psychiatric and personality factors related to substance dependence and dopamine affect PST performance. Although we found characteristics that predicted individual differences in approach versus avoidance learning, these observations were qualified by additional findings that appear inconsistent with the predictions of the go/no-go model. These results highlight a need for future research to validate the PST as a measure of basal ganglia reward learning.

  15. Category Learning by Clustering with Extension to Dynamic Environments

    DTIC Science & Technology

    2010-03-05

    and decision making when short- and long-term rewards are in conflict. In a paper published in Psychonomic Bulletin & Review , we examined whether...Navigating through Abstract Decision Spaces: Evaluating the Role of State Generalization in a Dynamic Decision-Making Task. Psychonomic Bulletin & Review , 16

  16. Distance-Based and Distributed Learning: A Decision Tool for Education Leaders.

    ERIC Educational Resources Information Center

    McGraw, Tammy M.; Ross, John D.

    This decision tool presents a progression of data collection and decision-making strategies that can increase the effectiveness of distance-based or distributed learning instruction. A narrative and flow chart cover the following steps: (1) basic assumptions, including purpose of instruction, market scan, and financial resources; (2) needs…

  17. Myopic Regret Avoidance: Feedback Avoidance and Learning in Repeated Decision Making

    ERIC Educational Resources Information Center

    Reb, Jochen; Connolly, Terry

    2009-01-01

    Decision makers can become trapped by "myopic regret avoidance" in which rejecting feedback to avoid short-term "outcome regret" (regret associated with counterfactual outcome comparisons) leads to reduced learning and greater long-term regret over continuing poor decisions. In a series of laboratory experiments involving repeated choices among…

  18. Dopamine D3 Receptor Availability Is Associated with Inflexible Decision Making.

    PubMed

    Groman, Stephanie M; Smith, Nathaniel J; Petrullli, J Ryan; Massi, Bart; Chen, Lihui; Ropchan, Jim; Huang, Yiyun; Lee, Daeyeol; Morris, Evan D; Taylor, Jane R

    2016-06-22

    Dopamine D2/3 receptor signaling is critical for flexible adaptive behavior; however, it is unclear whether D2, D3, or both receptor subtypes modulate precise signals of feedback and reward history that underlie optimal decision making. Here, PET with the radioligand [(11)C]-(+)-PHNO was used to quantify individual differences in putative D3 receptor availability in rodents trained on a novel three-choice spatial acquisition and reversal-learning task with probabilistic reinforcement. Binding of [(11)C]-(+)-PHNO in the midbrain was negatively related to the ability of rats to adapt to changes in rewarded locations, but not to the initial learning. Computational modeling of choice behavior in the reversal phase indicated that [(11)C]-(+)-PHNO binding in the midbrain was related to the learning rate and sensitivity to positive, but not negative, feedback. Administration of a D3-preferring agonist likewise impaired reversal performance by reducing the learning rate and sensitivity to positive feedback. These results demonstrate a previously unrecognized role for D3 receptors in select aspects of reinforcement learning and suggest that individual variation in midbrain D3 receptors influences flexible behavior. Our combined neuroimaging, behavioral, pharmacological, and computational approach implicates the dopamine D3 receptor in decision-making processes that are altered in psychiatric disorders. Flexible decision-making behavior is dependent upon dopamine D2/3 signaling in corticostriatal brain regions. However, the role of D3 receptors in adaptive, goal-directed behavior has not been thoroughly investigated. By combining PET imaging with the D3-preferring radioligand [(11)C]-(+)-PHNO, pharmacology, a novel three-choice probabilistic discrimination and reversal task and computational modeling of behavior in rats, we report that naturally occurring variation in [(11)C]-(+)-PHNO receptor availability relates to specific aspects of flexible decision making. We confirm these relationships using a D3-preferring agonist, thus identifying a unique role of midbrain D3 receptors in decision-making processes. Copyright © 2016 the authors 0270-6474/16/366732-10$15.00/0.

  19. Disadvantageous decision-making in borderline personality disorder: Partial support from a meta-analytic review.

    PubMed

    Paret, Christian; Jennen-Steinmetz, Christine; Schmahl, Christian

    2017-01-01

    To achieve long-term goals, organisms evaluate outcomes and expected consequences of their behaviors. Unfavorable decisions maintain many symptoms of borderline personality disorder (BPD); therefore, a better understanding of the mechanisms underlying decision-making in BPD is needed. In this review, the current literature comparing decision-making in patients with BPD versus healthy controls is analyzed. Twenty-eight empirical studies were identified through a structured literature search. The effect sizes from studies applying comparable experimental tasks were analyzed. It was found that (1) BPD patients discounted delayed rewards more strongly; (2) reversal learning was not significantly altered in BPD; and (3) BPD patients achieved lower net gains in the Iowa Gambling Task (IGT). Current psychotropic medication, sex and differences in age between the patient and control group moderated the IGT outcome. Altered decision-making in a variety of other tasks was supported by a qualitative review. In summary, current evidence supports the altered valuation of outcomes in BPD. A multifaceted influence on decision-making and adaptive learning is reflected in this literature. Copyright © 2016 Elsevier Ltd. All rights reserved.

  20. Understanding Drug Use and Addiction

    MedlinePlus

    ... as well, affecting functions that include: learning judgment decision-making stress memory behavior Despite being aware of these ... teens. Because areas in their brains that control decision-making, judgment, and self-control are still developing, teens ...

  1. Adults' Decision-Making about the Electronic Waste Issue: The Role of the Nature of Science Conceptualizations and Moral Concerns in Socio-Scientific Decision-Making

    ERIC Educational Resources Information Center

    Yu, Yuqing

    2010-01-01

    Socio-scientific issues have become increasingly important in Science-Technology-Society (STS) education as a means to make science learning more relevant to students' lives. This study used the e-waste issue as a context to investigate two aspects of socio-scientific decision-making: (1) the relationship between the nature of science (NOS)…

  2. Decision Making and Learning while Taking Sequential Risks

    ERIC Educational Resources Information Center

    Pleskac, Timothy J.

    2008-01-01

    A sequential risk-taking paradigm used to identify real-world risk takers invokes both learning and decision processes. This article expands the paradigm to a larger class of tasks with different stochastic environments and different learning requirements. Generalizing a Bayesian sequential risk-taking model to the larger set of tasks clarifies…

  3. History matching through dynamic decision-making

    PubMed Central

    Maschio, Célio; Santos, Antonio Alberto; Schiozer, Denis; Rocha, Anderson

    2017-01-01

    History matching is the process of modifying the uncertain attributes of a reservoir model to reproduce the real reservoir performance. It is a classical reservoir engineering problem and plays an important role in reservoir management since the resulting models are used to support decisions in other tasks such as economic analysis and production strategy. This work introduces a dynamic decision-making optimization framework for history matching problems in which new models are generated based on, and guided by, the dynamic analysis of the data of available solutions. The optimization framework follows a ‘learning-from-data’ approach, and includes two optimizer components that use machine learning techniques, such as unsupervised learning and statistical analysis, to uncover patterns of input attributes that lead to good output responses. These patterns are used to support the decision-making process while generating new, and better, history matched solutions. The proposed framework is applied to a benchmark model (UNISIM-I-H) based on the Namorado field in Brazil. Results show the potential the dynamic decision-making optimization framework has for improving the quality of history matching solutions using a substantial smaller number of simulations when compared with a previous work on the same benchmark. PMID:28582413

  4. URBAN DECISION MAKING - THE FINDINGS FROM A CONFERENCE (CHICAGO, NOVEMBER 5-12, 1965). APPLICATIONS OF HUMAN RELATIONS LABORATORY TRAINING, NUMBER 1, 1967.

    ERIC Educational Resources Information Center

    FRANKLIN, PAULA; FRANKLIN, RICHARD

    THIS NATIONAL TRAINING LABORATORIES (NTL) CONFERENCE, DEPARTING SOMEWHAT FROM ITS USUAL EXPERIENCE-BASED LEARNING PROGRAMS, FOCUSED LABORATORY TRAINING METHODS ON THE DECISION-MAKING PROCESS IN URBAN COMMUNITY PROBLEM SOLVING. THE CONFERENCE PRESENTED THEORY, INFORMATION, AND OPINION ON THE NATURE OF CITIES AND THEIR DECISION-MAKING PROCESSES.…

  5. A Model for Developing and Assessing Tactical Decision-Making Competency in Game Play

    ERIC Educational Resources Information Center

    Pagnano-Richardson, Karen; Henninger, Mary L.

    2008-01-01

    All teachers want their students to become better game players who are motivated to participate in and outside of class. Students need to learn how to make good tactical decisions, in addition to being skilled movers, in order to become competent game players. When students make better tactical decisions, they experience more success and therefore…

  6. Learning to Make More Effective Decisions: Changing Beliefs as a Prelude to Action

    ERIC Educational Resources Information Center

    Friedman, Sheldon

    2004-01-01

    Decision-makers in organizations often make what appear as being intuitively obviously and reasonable decisions, which often turn out to yield unintended outcomes. The cause of such ineffective decisions can be a combination of cognitive biases, poor mental models of complex systems, and errors in thinking provoked by anxiety, all of which tend to…

  7. Goal-directed decision making as probabilistic inference: A computational framework and potential neural correlates

    PubMed Central

    Solway, A.; Botvinick, M.

    2013-01-01

    Recent work has given rise to the view that reward-based decision making is governed by two key controllers: a habit system, which stores stimulus-response associations shaped by past reward, and a goal-oriented system that selects actions based on their anticipated outcomes. The current literature provides a rich body of computational theory addressing habit formation, centering on temporal-difference learning mechanisms. Less progress has been made toward formalizing the processes involved in goal-directed decision making. We draw on recent work in cognitive neuroscience, animal conditioning, cognitive and developmental psychology and machine learning, to outline a new theory of goal-directed decision making. Our basic proposal is that the brain, within an identifiable network of cortical and subcortical structures, implements a probabilistic generative model of reward, and that goal-directed decision making is effected through Bayesian inversion of this model. We present a set of simulations implementing the account, which address benchmark behavioral and neuroscientific findings, and which give rise to a set of testable predictions. We also discuss the relationship between the proposed framework and other models of decision making, including recent models of perceptual choice, to which our theory bears a direct connection. PMID:22229491

  8. Exploring the Learning from an Enterprise Simulation.

    ERIC Educational Resources Information Center

    Sawyer, John E.; Gopinath, C.

    1999-01-01

    A computer simulation used in teams by 151 business students tested their ability to translate strategy into decisions. Over eight weeks, the experiential learning activity encouraged strategic decision making and group behavior consistent with long-term strategy. (SK)

  9. Reinforcement learning and decision making in monkeys during a competitive game.

    PubMed

    Lee, Daeyeol; Conroy, Michelle L; McGreevy, Benjamin P; Barraclough, Dominic J

    2004-12-01

    Animals living in a dynamic environment must adjust their decision-making strategies through experience. To gain insights into the neural basis of such adaptive decision-making processes, we trained monkeys to play a competitive game against a computer in an oculomotor free-choice task. The animal selected one of two visual targets in each trial and was rewarded only when it selected the same target as the computer opponent. To determine how the animal's decision-making strategy can be affected by the opponent's strategy, the computer opponent was programmed with three different algorithms that exploited different aspects of the animal's choice and reward history. When the computer selected its targets randomly with equal probabilities, animals selected one of the targets more often, violating the prediction of probability matching, and their choices were systematically influenced by the choice history of the two players. When the computer exploited only the animal's choice history but not its reward history, animal's choice became more independent of its own choice history but was still related to the choice history of the opponent. This bias was substantially reduced, but not completely eliminated, when the computer used the choice history of both players in making its predictions. These biases were consistent with the predictions of reinforcement learning, suggesting that the animals sought optimal decision-making strategies using reinforcement learning algorithms.

  10. Young Children's Affective Decision-Making in a Gambling Task: Does Difficulty in Learning the Gain/Loss Schedule Matter?

    ERIC Educational Resources Information Center

    Gao, Shan; Wei, Yonggang; Bai, Junjie; Lin, Chongde; Li, Hong

    2009-01-01

    This research investigated the development of affective decision-making (ADM) during early childhood, in particular role of difficulty in learning a gain/loss schedule. In Experiment 1, we administrated the Children's Gambling Task (CGT) to 60 Chinese children aged 3 and 4, replicating the results obtained by Kerr and Zelazo [Kerr, A., & Zelazo,…

  11. Exploring Data-Driven Decision-Making in the Field: How Faculty Use Data and Other Forms of Information to Guide Instructional Decision-Making. WCER Working Paper No. 2014-3

    ERIC Educational Resources Information Center

    Hora, Matthew T.; Bouwma-Gearhart, Jana; Park, Hyoung Joon

    2014-01-01

    A defining characteristic of current U.S. educational policy is the use of data to inform decisions about resource allocation, teacher hiring, and curriculum and instruction. Perhaps the biggest challenge to data-driven decision making (DDDM) is that data use alone does not automatically result in improved teaching and learning. Research indicates…

  12. Shared Decisions & Technology-Assisted Learning

    ERIC Educational Resources Information Center

    Jacobs, Mary

    2005-01-01

    In this short article, the author discusses how Henderson Middle School in Jackson, Georgia used shared decision making to improve student achievement through the use of laptop computers. With effective use of technology and shared decision making, administrators at Henderson believe that they can continue to achieve Adequate Yearly Progress under…

  13. The Computational Development of Reinforcement Learning during Adolescence

    PubMed Central

    Palminteri, Stefano; Coricelli, Giorgio; Blakemore, Sarah-Jayne

    2016-01-01

    Adolescence is a period of life characterised by changes in learning and decision-making. Learning and decision-making do not rely on a unitary system, but instead require the coordination of different cognitive processes that can be mathematically formalised as dissociable computational modules. Here, we aimed to trace the developmental time-course of the computational modules responsible for learning from reward or punishment, and learning from counterfactual feedback. Adolescents and adults carried out a novel reinforcement learning paradigm in which participants learned the association between cues and probabilistic outcomes, where the outcomes differed in valence (reward versus punishment) and feedback was either partial or complete (either the outcome of the chosen option only, or the outcomes of both the chosen and unchosen option, were displayed). Computational strategies changed during development: whereas adolescents’ behaviour was better explained by a basic reinforcement learning algorithm, adults’ behaviour integrated increasingly complex computational features, namely a counterfactual learning module (enabling enhanced performance in the presence of complete feedback) and a value contextualisation module (enabling symmetrical reward and punishment learning). Unlike adults, adolescent performance did not benefit from counterfactual (complete) feedback. In addition, while adults learned symmetrically from both reward and punishment, adolescents learned from reward but were less likely to learn from punishment. This tendency to rely on rewards and not to consider alternative consequences of actions might contribute to our understanding of decision-making in adolescence. PMID:27322574

  14. Pitfalls of Counterfactual Thinking in Medical Practice: Preventing Errors by Using More Functional Reference Points

    PubMed Central

    Petrocelli, John V.

    2013-01-01

    Background Counterfactual thinking involves mentally simulating alternatives to reality. The current article reviews literature pertaining to the relevance counterfactual thinking has for the quality of medical decision making. Although earlier counterfactual thought research concluded that counterfactuals have important benefits for the individual, there are reasons to believe that counterfactual thinking is also associated with dysfunctional consequences. Of particular focus is whether or not medical experience, and its influence on counterfactual thinking, actually informs or improves medical practice. It is hypothesized that relatively more probable decision alternatives, followed by undesirable outcomes and counterfactual thought responses, can be abandoned for relatively less probable decision alternatives. Design and Methods Building on earlier research demonstrating that counterfactual thinking can impede memory and learning in a decision paradigm with undergraduate students, the current study examines the extent to which earlier findings can be generalized to practicing physicians (N=10). Participants were asked to complete 60 trials of a computerized Monty Hall Problem simulation. Learning by experience was operationalized as the frequency of switch-decisions. Results Although some learning was evidenced by a general increase in switch-decision frequency across block trials, the extent of learning demonstrated was not ideal, nor practical. Conclusions A simple, multiple-trial, decision paradigm demonstrated that doctors fail to learn basic decision-outcome associations through experience. An agenda for future research, which tests the functionality of reference points (other than counterfactual alternatives) for the purposes of medical decision making, is proposed. Significance for public health The quality of healthcare depends heavily on the judgments and decisions made by doctors and other medical professionals. Findings from this research indicate that doctors fail to learn basic decision-outcome associations through experience, as evidenced by the sample’s tendency to select the optimal decision strategy in only 50% of 60 trials (each of which was followed by veridical feedback). These findings suggest that professional experience is unlikely to enhance the quality of medical decision making. Thus, this research has implications for understanding how doctors’ reactions to medical outcomes shape their judgments and affect the degree to which their future treatment intentions are consistent with clinical practice guidelines. The current research is integrated with earlier research on counter-factual thinking, which appears to be a primary element inhibiting the learning of decision-outcome associations. An agenda for future research is proposed. PMID:25170495

  15. Interdisciplinary Collaborative Learning: Using Decision Analysts to Enhance Undergraduate International Management Education

    ERIC Educational Resources Information Center

    Palocsay, Susan W.; White, Marion M.; Zimmerman, D. Kent

    2004-01-01

    This article describes an experiential learning activity designed to promote the development of decision-making skills in international management students at the undergraduate level. Students from an undergraduate management science course in decision analysis served as consultants on a case assigned to teams in an international management class.…

  16. Enhancing emotion-based learning in decision-making under uncertainty.

    PubMed

    Alarcón, David; Amián, Josué G; Sánchez-Medina, José A

    2015-01-01

    The Iowa Gambling Task (IGT) is widely used to study decision-making differences between several clinical and healthy populations. Unlike the healthy participants, clinical participants have difficulty choosing between advantageous options, which yield long-term benefits, and disadvantageous options, which give high immediate rewards but lead to negative profits. However, recent studies have found that healthy participants avoid the options with a higher frequency of losses regardless of whether or not they are profitable in the long run. The aim of this study was to control for the confounding effect of the frequency of losses between options to improve the performance of healthy participants on the IGT. Eighty healthy participants were randomly assigned to the original IGT or a modified version of the IGT that diminished the gap in the frequency of losses between options. The participants who used the modified IGT version learned to make better decisions based on long-term profit, as indicated by an earlier ability to discriminate good from bad options, and took less time to make their choices. This research represents an advance in the study of decision making under uncertainty by showing that emotion-based learning is improved by controlling for the loss-frequency bias effect.

  17. The Structural Consequences of Big Data-Driven Education.

    PubMed

    Zeide, Elana

    2017-06-01

    Educators and commenters who evaluate big data-driven learning environments focus on specific questions: whether automated education platforms improve learning outcomes, invade student privacy, and promote equality. This article puts aside separate unresolved-and perhaps unresolvable-issues regarding the concrete effects of specific technologies. It instead examines how big data-driven tools alter the structure of schools' pedagogical decision-making, and, in doing so, change fundamental aspects of America's education enterprise. Technological mediation and data-driven decision-making have a particularly significant impact in learning environments because the education process primarily consists of dynamic information exchange. In this overview, I highlight three significant structural shifts that accompany school reliance on data-driven instructional platforms that perform core school functions: teaching, assessment, and credentialing. First, virtual learning environments create information technology infrastructures featuring constant data collection, continuous algorithmic assessment, and possibly infinite record retention. This undermines the traditional intellectual privacy and safety of classrooms. Second, these systems displace pedagogical decision-making from educators serving public interests to private, often for-profit, technology providers. They constrain teachers' academic autonomy, obscure student evaluation, and reduce parents' and students' ability to participate or challenge education decision-making. Third, big data-driven tools define what "counts" as education by mapping the concepts, creating the content, determining the metrics, and setting desired learning outcomes of instruction. These shifts cede important decision-making to private entities without public scrutiny or pedagogical examination. In contrast to the public and heated debates that accompany textbook choices, schools often adopt education technologies ad hoc. Given education's crucial impact on individual and collective success, educators and policymakers must consider the implications of data-driven education proactively and explicitly.

  18. Active and passive spatial learning in human navigation: acquisition of survey knowledge.

    PubMed

    Chrastil, Elizabeth R; Warren, William H

    2013-09-01

    It seems intuitively obvious that active exploration of a new environment would lead to better spatial learning than would passive visual exposure. It is unclear, however, which components of active learning contribute to spatial knowledge, and previous literature is decidedly mixed. This experiment tests the contributions of 4 components to metric survey knowledge: visual, vestibular, and podokinetic information and cognitive decision making. In the learning phase, 6 groups of participants learned the locations of 8 objects in a virtual hedge maze by (a) walking, (b) being pushed in a wheelchair, or (c) watching a video, crossed with (1) making decisions about their path or (2) being guided through the maze. In the test phase, survey knowledge was assessed by having participants walk a novel shortcut from a starting object to the remembered location of a test object, with the maze removed. Performance was slightly better than chance in the passive video condition. The addition of vestibular information did not improve performance in the wheelchair condition, but the addition of podokinetic information significantly improved angular accuracy in the walking condition. In contrast, there was no effect of decision making in any condition. The results indicate that visual and podokinetic information significantly contribute to survey knowledge, whereas vestibular information and decision making do not. We conclude that podokinetic information is the primary component of active learning for the acquisition of metric survey knowledge. PsycINFO Database Record (c) 2013 APA, all rights reserved.

  19. Neural basis of decision making guided by emotional outcomes

    PubMed Central

    Matsuda, Yoshi-Taka; Fujimura, Tomomi; Ueno, Kenichi; Asamizuya, Takeshi; Suzuki, Chisato; Cheng, Kang; Okanoya, Kazuo; Okada, Masato

    2015-01-01

    Emotional events resulting from a choice influence an individual's subsequent decision making. Although the relationship between emotion and decision making has been widely discussed, previous studies have mainly investigated decision outcomes that can easily be mapped to reward and punishment, including monetary gain/loss, gustatory stimuli, and pain. These studies regard emotion as a modulator of decision making that can be made rationally in the absence of emotions. In our daily lives, however, we often encounter various emotional events that affect decisions by themselves, and mapping the events to a reward or punishment is often not straightforward. In this study, we investigated the neural substrates of how such emotional decision outcomes affect subsequent decision making. By using functional magnetic resonance imaging (fMRI), we measured brain activities of humans during a stochastic decision-making task in which various emotional pictures were presented as decision outcomes. We found that pleasant pictures differentially activated the midbrain, fusiform gyrus, and parahippocampal gyrus, whereas unpleasant pictures differentially activated the ventral striatum, compared with neutral pictures. We assumed that the emotional decision outcomes affect the subsequent decision by updating the value of the options, a process modeled by reinforcement learning models, and that the brain regions representing the prediction error that drives the reinforcement learning are involved in guiding subsequent decisions. We found that some regions of the striatum and the insula were separately correlated with the prediction error for either pleasant pictures or unpleasant pictures, whereas the precuneus was correlated with prediction errors for both pleasant and unpleasant pictures. PMID:25695644

  20. Neural basis of decision making guided by emotional outcomes.

    PubMed

    Katahira, Kentaro; Matsuda, Yoshi-Taka; Fujimura, Tomomi; Ueno, Kenichi; Asamizuya, Takeshi; Suzuki, Chisato; Cheng, Kang; Okanoya, Kazuo; Okada, Masato

    2015-05-01

    Emotional events resulting from a choice influence an individual's subsequent decision making. Although the relationship between emotion and decision making has been widely discussed, previous studies have mainly investigated decision outcomes that can easily be mapped to reward and punishment, including monetary gain/loss, gustatory stimuli, and pain. These studies regard emotion as a modulator of decision making that can be made rationally in the absence of emotions. In our daily lives, however, we often encounter various emotional events that affect decisions by themselves, and mapping the events to a reward or punishment is often not straightforward. In this study, we investigated the neural substrates of how such emotional decision outcomes affect subsequent decision making. By using functional magnetic resonance imaging (fMRI), we measured brain activities of humans during a stochastic decision-making task in which various emotional pictures were presented as decision outcomes. We found that pleasant pictures differentially activated the midbrain, fusiform gyrus, and parahippocampal gyrus, whereas unpleasant pictures differentially activated the ventral striatum, compared with neutral pictures. We assumed that the emotional decision outcomes affect the subsequent decision by updating the value of the options, a process modeled by reinforcement learning models, and that the brain regions representing the prediction error that drives the reinforcement learning are involved in guiding subsequent decisions. We found that some regions of the striatum and the insula were separately correlated with the prediction error for either pleasant pictures or unpleasant pictures, whereas the precuneus was correlated with prediction errors for both pleasant and unpleasant pictures. Copyright © 2015 the American Physiological Society.

  1. Pupil dilation signals uncertainty and surprise in a learning gambling task.

    PubMed

    Lavín, Claudio; San Martín, René; Rosales Jubal, Eduardo

    2013-01-01

    Pupil dilation under constant illumination is a physiological marker where modulation is related to several cognitive functions involved in daily decision making. There is evidence for a role of pupil dilation change during decision-making tasks associated with uncertainty, reward-prediction errors and surprise. However, while some work suggests that pupil dilation is mainly modulated by reward predictions, others point out that this marker is related to uncertainty signaling and surprise. Supporting the latter hypothesis, the neural substrate of this marker is related to noradrenaline (NA) activity which has been also related to uncertainty signaling. In this work we aimed to test whether pupil dilation is a marker for uncertainty and surprise in a learning task. We recorded pupil dilation responses in 10 participants performing the Iowa Gambling Task (IGT), a decision-making task that requires learning and constant monitoring of outcomes' feedback, which are important variables within the traditional study of human decision making. Results showed that pupil dilation changes were modulated by learned uncertainty and surprise regardless of feedback magnitudes. Interestingly, greater pupil dilation changes were found during positive feedback (PF) presentation when there was lower uncertainty about a future negative feedback (NF); and by surprise during NF presentation. These results support the hypothesis that pupil dilation is a marker of learned uncertainty, and may be used as a marker of NA activity facing unfamiliar situations in humans.

  2. Pupil dilation signals uncertainty and surprise in a learning gambling task

    PubMed Central

    Lavín, Claudio; San Martín, René; Rosales Jubal, Eduardo

    2014-01-01

    Pupil dilation under constant illumination is a physiological marker where modulation is related to several cognitive functions involved in daily decision making. There is evidence for a role of pupil dilation change during decision-making tasks associated with uncertainty, reward-prediction errors and surprise. However, while some work suggests that pupil dilation is mainly modulated by reward predictions, others point out that this marker is related to uncertainty signaling and surprise. Supporting the latter hypothesis, the neural substrate of this marker is related to noradrenaline (NA) activity which has been also related to uncertainty signaling. In this work we aimed to test whether pupil dilation is a marker for uncertainty and surprise in a learning task. We recorded pupil dilation responses in 10 participants performing the Iowa Gambling Task (IGT), a decision-making task that requires learning and constant monitoring of outcomes’ feedback, which are important variables within the traditional study of human decision making. Results showed that pupil dilation changes were modulated by learned uncertainty and surprise regardless of feedback magnitudes. Interestingly, greater pupil dilation changes were found during positive feedback (PF) presentation when there was lower uncertainty about a future negative feedback (NF); and by surprise during NF presentation. These results support the hypothesis that pupil dilation is a marker of learned uncertainty, and may be used as a marker of NA activity facing unfamiliar situations in humans. PMID:24427126

  3. Learning decision making through serious games.

    PubMed

    Kaczmarczyk, Joseph; Davidson, Richard; Bryden, Daniele; Haselden, Stephen; Vivekananda-Schmidt, Pirashanthie

    2016-08-01

    In Serious Games (SGs), educational content is integrated into a game so that learning is intrinsic to play, thereby motivating players and improving engagement. SGs enable learning by developing situated understanding in users and by enabling players to practise safe clinical decision making; however, the use of SGs in medical education is not well established. We aimed to design a game-based resource to teach clinical decision making to medical students, and to assess user perceptions of educational value, usability and the role for SGs in undergraduate training. An SG focusing on the acute management of tachyarrhythmias was developed. Third- and fourth-year medical students at the medical school were invited to use and evaluate the game using questionnaires and focus groups. We invited 479 students, and 281 accessed the game. Only 47 students completed the questionnaire and 31 students participated in the focus groups. The data suggest that SGs: (1) can allow students to rehearse taking responsibility for decision making; (2) are fun and motivational; (3) have a role in revising and consolidating knowledge; and (4) could be formative assessment tools. Serious Games enable learning by developing situated understanding in users SGs could be employed as adjuvant learning resources to develop students' skills and knowledge. Further empirical research is required to assess the added value of games in medical education. © 2015 John Wiley & Sons Ltd.

  4. Making Consumer Choices. Secondary Learning Guide 6. Project Connect. Linking Self-Family-Work.

    ERIC Educational Resources Information Center

    Emily Hall Tremaine Foundation, Inc., Hartford, CT.

    This competency-based secondary learning guide on making consumer choices is part of a series that are adaptations of guides developed for adult consumer and homemaking education programs. The guides provide students with experiences that help them learn to do the following: make decisions; use creative approaches to solve problems; establish…

  5. Category Learning by Clustering with Extension to Dynamic Environments

    DTIC Science & Technology

    2010-05-03

    making when short- and long-term rewards are in conflict. In a paper published in Psychonomic Bulletin & Review , we examined whether state cues make...through Abstract Decision Spaces: Evaluating the Role of State Generalization in a Dynamic Decision-Making Task. Psychonomic Bulletin & Review , 16, 957

  6. Learning Theory Expertise in the Design of Learning Spaces: Who Needs a Seat at the Table?

    ERIC Educational Resources Information Center

    Rook, Michael M.; Choi, Koun; McDonald, Scott P.

    2015-01-01

    This study highlights the impact of including stakeholders with expertise in learning theory in a learning space design process. We present the decision-making process during the design of the Krause Innovation Studio on the campus of the Pennsylvania State University to draw a distinction between the architect and faculty member's decision-making…

  7. Understanding active sampling strategies: Empirical approaches and implications for attention and decision research.

    PubMed

    Gottlieb, Jacqueline

    2018-05-01

    In natural behavior we actively gather information using attention and active sensing behaviors (such as shifts of gaze) to sample relevant cues. However, while attention and decision making are naturally coordinated, in the laboratory they have been dissociated. Attention is studied independently of the actions it serves. Conversely, decision theories make the simplifying assumption that the relevant information is given, and do not attempt to describe how the decision maker may learn and implement active sampling policies. In this paper I review recent studies that address questions of attentional learning, cue validity and information seeking in humans and non-human primates. These studies suggest that learning a sampling policy involves large scale interactions between networks of attention and valuation, which implement these policies based on reward maximization, uncertainty reduction and the intrinsic utility of cognitive states. I discuss the importance of using such paradigms for formalizing the role of attention, as well as devising more realistic theories of decision making that capture a broader range of empirical observations. Copyright © 2017 Elsevier Ltd. All rights reserved.

  8. Elucidating Poor Decision-Making in a Rat Gambling Task

    PubMed Central

    Seriès, Peggy; Marchand, Alain R.; Dellu-Hagedorn, Françoise

    2013-01-01

    Although poor decision-making is a hallmark of psychiatric conditions such as attention deficit/hyperactivity disorder, pathological gambling or substance abuse, a fraction of healthy individuals exhibit similar poor decision-making performances in everyday life and specific laboratory tasks such as the Iowa Gambling Task. These particular individuals may provide information on risk factors or common endophenotypes of these mental disorders. In a rodent version of the Iowa gambling task – the Rat Gambling Task (RGT), we identified a population of poor decision makers, and assessed how these rats scored for several behavioral traits relevant to executive disorders: risk taking, reward seeking, behavioral inflexibility, and several aspects of impulsivity. First, we found that poor decision-making could not be well predicted by single behavioral and cognitive characteristics when considered separately. By contrast, a combination of independent traits in the same individual, namely risk taking, reward seeking, behavioral inflexibility, as well as motor impulsivity, was highly predictive of poor decision-making. Second, using a reinforcement-learning model of the RGT, we confirmed that only the combination of extreme scores on these traits could induce maladaptive decision-making. Third, the model suggested that a combination of these behavioral traits results in an inaccurate representation of rewards and penalties and inefficient learning of the environment. Poor decision-making appears as a consequence of the over-valuation of high-reward-high-risk options in the task. Such a specific psychological profile could greatly impair clinically healthy individuals in decision-making tasks and may predispose to mental disorders with similar symptoms. PMID:24339988

  9. Elucidating poor decision-making in a rat gambling task.

    PubMed

    Rivalan, Marion; Valton, Vincent; Seriès, Peggy; Marchand, Alain R; Dellu-Hagedorn, Françoise

    2013-01-01

    Although poor decision-making is a hallmark of psychiatric conditions such as attention deficit/hyperactivity disorder, pathological gambling or substance abuse, a fraction of healthy individuals exhibit similar poor decision-making performances in everyday life and specific laboratory tasks such as the Iowa Gambling Task. These particular individuals may provide information on risk factors or common endophenotypes of these mental disorders. In a rodent version of the Iowa gambling task--the Rat Gambling Task (RGT), we identified a population of poor decision makers, and assessed how these rats scored for several behavioral traits relevant to executive disorders: risk taking, reward seeking, behavioral inflexibility, and several aspects of impulsivity. First, we found that poor decision-making could not be well predicted by single behavioral and cognitive characteristics when considered separately. By contrast, a combination of independent traits in the same individual, namely risk taking, reward seeking, behavioral inflexibility, as well as motor impulsivity, was highly predictive of poor decision-making. Second, using a reinforcement-learning model of the RGT, we confirmed that only the combination of extreme scores on these traits could induce maladaptive decision-making. Third, the model suggested that a combination of these behavioral traits results in an inaccurate representation of rewards and penalties and inefficient learning of the environment. Poor decision-making appears as a consequence of the over-valuation of high-reward-high-risk options in the task. Such a specific psychological profile could greatly impair clinically healthy individuals in decision-making tasks and may predispose to mental disorders with similar symptoms.

  10. Air traffic control specialist decision making and strategic planning : a field survey

    DOT National Transportation Integrated Search

    2001-03-01

    This study investigated Air Traffic Control Specialists' perspective regarding decision making and planning and related cognitive processes such as learning, memory, and situation awareness. The results of 100 semi-structured interviews indicated tha...

  11. Lessons learned by (from?) an economist working in medical decision making.

    PubMed

    Wakker, Peter P

    2008-01-01

    This article is a personal account of the author's experiences as an economist working in medical decision making. He discusses the differences between economic decision theory and medical decision making and gives examples of the mutual benefits resulting from interactions. In particular, he discusses the pros and cons of different methods for measuring quality of life (or, as economists would call it, utility), including the standard gamble, the time tradeoff, and the healthy-years equivalent methods.

  12. Orbital frontal cortex updates state-induced value change for decision-making.

    PubMed

    Baltz, Emily T; Yalcinbas, Ege A; Renteria, Rafael; Gremel, Christina M

    2018-06-13

    Recent hypotheses have posited that orbital frontal cortex (OFC) is important for using inferred consequences to guide behavior. Less clear is OFC's contribution to goal-directed or model-based behavior, where the decision to act is controlled by previous experience with the consequence or outcome. Investigating OFC's role in learning about changed outcomes separate from decision-making is not trivial and often the two are confounded. Here we adapted an incentive learning task to mice, where we investigated processes controlling experience-based outcome updating independent from inferred action control. We found chemogenetic OFC attenuation did not alter the ability to perceive motivational state-induced changes in outcome value but did prevent the experience-based updating of this change. Optogenetic inhibition of OFC excitatory neuron activity selectively when experiencing an outcome change disrupted the ability to update, leaving mice unable to infer the appropriate behavior. Our findings support a role for OFC in learning that controls decision-making. © 2018, Baltz et al.

  13. Cortical topography of intracortical inhibition influences the speed of decision making.

    PubMed

    Wilimzig, Claudia; Ragert, Patrick; Dinse, Hubert R

    2012-02-21

    The neocortex contains orderly topographic maps; however, their functional role remains controversial. Theoretical studies have suggested a role in minimizing computational costs, whereas empirical studies have focused on spatial localization. Using a tactile multiple-choice reaction time (RT) task before and after the induction of perceptual learning through repetitive sensory stimulation, we extend the framework of cortical topographies by demonstrating that the topographic arrangement of intracortical inhibition contributes to the speed of human perceptual decision-making processes. RTs differ among fingers, displaying an inverted U-shaped function. Simulations using neural fields show the inverted U-shaped RT distribution as an emergent consequence of lateral inhibition. Weakening inhibition through learning shortens RTs, which is modeled through topographically reorganized inhibition. Whereas changes in decision making are often regarded as an outcome of higher cortical areas, our data show that the spatial layout of interaction processes within representational maps contributes to selection and decision-making processes.

  14. Cortical topography of intracortical inhibition influences the speed of decision making

    PubMed Central

    Wilimzig, Claudia; Ragert, Patrick; Dinse, Hubert R.

    2012-01-01

    The neocortex contains orderly topographic maps; however, their functional role remains controversial. Theoretical studies have suggested a role in minimizing computational costs, whereas empirical studies have focused on spatial localization. Using a tactile multiple-choice reaction time (RT) task before and after the induction of perceptual learning through repetitive sensory stimulation, we extend the framework of cortical topographies by demonstrating that the topographic arrangement of intracortical inhibition contributes to the speed of human perceptual decision-making processes. RTs differ among fingers, displaying an inverted U-shaped function. Simulations using neural fields show the inverted U-shaped RT distribution as an emergent consequence of lateral inhibition. Weakening inhibition through learning shortens RTs, which is modeled through topographically reorganized inhibition. Whereas changes in decision making are often regarded as an outcome of higher cortical areas, our data show that the spatial layout of interaction processes within representational maps contributes to selection and decision-making processes. PMID:22315409

  15. The Salida Valley Unified School District: A Case Study in Policy Making with Regard to the Award of Credit for Experience-Based Learning.

    ERIC Educational Resources Information Center

    Banker, Nancy Sirmay

    This case study of a small suburban school district in the San Francisco Bay Area examines the interplay among individuals and groups within the district who make and implement policy decisions. The issue of awarding credit for experience-based learning focuses and directs the study. As an introduction to examination of the ways decisions are…

  16. Aeronautical Decision Making for Student and Private Pilots.

    DTIC Science & Technology

    1987-05-01

    you learn to gain voluntary control over your body to achieve the relaxation response. In autogenic training , you learn to shut down many bodily...Ahstruct "Aviation accident data indicate that the majority of aircraft mishaps are due to judgment error. This training manual is part of a project to...develop materials and techniques to help improve pilot decision making. Training programs using prototype versions of these materials have

  17. Incorporating Learning Analytics in the Classroom

    ERIC Educational Resources Information Center

    Thille, Candace; Zimmaro, Dawn

    2017-01-01

    This chapter describes an open learning analytics system focused on learning process measures and designed to engage instructors and students in an evidence-informed decision-making process to improve learning.

  18. Instructional decision making of high school science teachers

    NASA Astrophysics Data System (ADS)

    Carver, Jeffrey S.

    The instructional decision-making processes of high school science teachers have not been well established in the literature. Several models for decision-making do exist in other teaching disciplines, business, computer game programming, nursing, and some fields of science. A model that incorporates differences in science teaching that is consistent with constructivist theory as opposed to conventional science teaching is useful in the current climate of standards-based instruction that includes an inquiry-based approach to teaching science. This study focuses on three aspects of the decision-making process. First, it defines what factors, both internal and external, influence high school science teacher decision-making. Second, those factors are analyzed further to determine what instructional decision-making processes are articulated or demonstrated by the participants. Third, by analyzing the types of decisions that are made in the classroom, the classroom learning environments established as a result of those instructional decisions are studied for similarities and differences between conventional and constructivist models. While the decision-making process for each of these teachers was not clearly articulated by the teachers themselves, the patterns that establish the process were clearly exhibited by the teachers. It was also clear that the classroom learning environments that were established were, at least in part, established as a result of the instructional decisions that were made in planning and implementation of instruction. Patterns of instructional decision-making were different for each teacher as a result of primary instructional goals that were different for each teacher. There were similarities between teachers who exhibited more constructivist epistemological tendencies as well as similarities between teachers who exhibited a more conventional epistemology. While the decisions that will result from these two camps may be different, the six step process for instructional decision-making that was established during this study shows promise for use in both situations.

  19. The roles of dopamine and serotonin in decision making: evidence from pharmacological experiments in humans.

    PubMed

    Rogers, Robert D

    2011-01-01

    Neurophysiological experiments in primates, alongside neuropsychological and functional magnetic resonance investigations in humans, have significantly enhanced our understanding of the neural architecture of decision making. In this review, I consider the more limited database of experiments that have investigated how dopamine and serotonin activity influences the choices of human adults. These include those experiments that have involved the administration of drugs to healthy controls, experiments that have tested genotypic influences upon dopamine and serotonin function, and, finally, some of those experiments that have examined the effects of drugs on the decision making of clinical samples. Pharmacological experiments in humans are few in number and face considerable methodological challenges in terms of drug specificity, uncertainties about pre- vs post-synaptic modes of action, and interactions with baseline cognitive performance. However, the available data are broadly consistent with current computational models of dopamine function in decision making and highlight the dissociable roles of dopamine receptor systems in the learning about outcomes that underpins value-based decision making. Moreover, genotypic influences on (interacting) prefrontal and striatal dopamine activity are associated with changes in choice behavior that might be relevant to understanding exploratory behaviors and vulnerability to addictive disorders. Manipulations of serotonin in laboratory tests of decision making in human participants have provided less consistent results, but the information gathered to date indicates a role for serotonin in learning about bad decision outcomes, non-normative aspects of risk-seeking behavior, and social choices involving affiliation and notions of fairness. Finally, I suggest that the role played by serotonin in the regulation of cognitive biases, and representation of context in learning, point toward a role in the cortically mediated cognitive appraisal of reinforcers when selecting between actions, potentially accounting for its influence upon the processing salient aversive outcomes and social choice.

  20. An information processing/associative learning account of behavioral disinhibition in externalizing psychopathology.

    PubMed

    Endres, Michael J; Donkin, Chris; Finn, Peter R

    2014-04-01

    Externalizing psychopathology (EXT) is associated with low executive working memory (EWM) capacity and problems with inhibitory control and decision-making; however, the specific cognitive processes underlying these problems are not well known. This study used a linear ballistic accumulator computational model of go/no-go associative-incentive learning conducted with and without a working memory (WM) load to investigate these cognitive processes in 510 young adults varying in EXT (lifetime problems with substance use, conduct disorder, ADHD, adult antisocial behavior). High scores on an EXT factor were associated with low EWM capacity and higher scores on a latent variable reflecting the cognitive processes underlying disinhibited decision-making (more false alarms, faster evidence accumulation rates for false alarms [vFA], and lower scores on a Response Precision Index [RPI] measure of information processing efficiency). The WM load increased disinhibited decision-making, decisional uncertainty, and response caution for all subjects. Higher EWM capacity was associated with lower scores on the latent disinhibited decision-making variable (lower false alarms, lower vFAs and RPI scores) in both WM load conditions. EWM capacity partially mediated the association between EXT and disinhibited decision-making under no-WM load, and completely mediated this association under WM load. The results underline the role that EWM has in associative-incentive go/no-go learning and indicate that common to numerous types of EXT are impairments in the cognitive processes associated with the evidence accumulation-evaluation-decision process. PsycINFO Database Record (c) 2014 APA, all rights reserved.

  1. An information processing/associative learning account of behavioral disinhibition in externalizing psychopathology

    PubMed Central

    Endres, Michael J.; Donkin, Chris; Finn, Peter R.

    2014-01-01

    Externalizing psychopathology (EXT) is associated with low executive working memory (EWM) capacity and problems with inhibitory control and decision-making; however, the specific cognitive processes underlying these problems are not well known. This study used a linear ballistic accumulator computational model of go/no-go associative-incentive learning conducted with and without a working memory (WM) load to investigate these cognitive processes in 510 young adults varying in EXT (lifetime problems with substance use, conduct disorder, ADHD, adult antisocial behavior). High scores on an EXT factor were associated with low EWM capacity and higher scores on a latent variable reflecting the cognitive processes underlying disinhibited decision making (more false alarms, faster evidence accumulation rates for false alarms (vFA), and lower scores on a Response Precision Index (RPI) measure of information processing efficiency). The WM load increased disinhibited decision making, decisional uncertainty, and response caution for all subjects. Higher EWM capacity was associated with lower scores on the latent disinhibited decision making variable (lower false alarms, lower vFAs and RPI scores) in both WM load conditions. EWM capacity partially mediated the association between EXT and disinhibited decision making under no-WM load, and completely mediated this association under WM load. The results underline the role that EWM has in associative – incentive go/no-go learning and indicate that common to numerous types of EXT are impairments in the cognitive processes associated with the evidence accumulation – evaluation – decision process. PMID:24611834

  2. Learning other agents` preferences in multiagent negotiation

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Bui, H.H.; Kieronska, D.; Venkatesh, S.

    In multiagent systems, an agent does not usually have complete information about the preferences and decision making processes of other agents. This might prevent the agents from making coordinated choices, purely due to their ignorance of what others want. This paper describes the integration of a learning module into a communication-intensive negotiating agent architecture. The learning module gives the agents the ability to learn about other agents` preferences via past interactions. Over time, the agents can incrementally update their models of other agents` preferences and use them to make better coordinated decisions. Combining both communication and learning, as two complementmore » knowledge acquisition methods, helps to reduce the amount of communication needed on average, and is justified in situations where communication is computationally costly or simply not desirable (e.g. to preserve the individual privacy).« less

  3. Studying the Impact of Three Different Instructional Methods on Preservice Teachers' Decision-Making

    ERIC Educational Resources Information Center

    Cevik, Yasemin Demiraslan; Andre, Thomas

    2014-01-01

    This study compared the impact of three types of instructional methods (case-based learning, worked example and faded worked example) on preservice teachers' (n?=?72) decision-making about classroom management. A quasi-experimental study was conducted to investigate both the outcomes and the processes of preservice teachers' decision-making…

  4. Repeated Causal Decision Making

    ERIC Educational Resources Information Center

    Hagmayer, York; Meder, Bjorn

    2013-01-01

    Many of our decisions refer to actions that have a causal impact on the external environment. Such actions may not only allow for the mere learning of expected values or utilities but also for acquiring knowledge about the causal structure of our world. We used a repeated decision-making paradigm to examine what kind of knowledge people acquire in…

  5. Hindsight Bias and Outcome-Consistent Thoughts when Observing and Making Service Provider Decisions

    ERIC Educational Resources Information Center

    Louie, Therese A.

    2005-01-01

    Two studies examined the relationship between hindsight bias and corresponding open-ended thoughts for decisions in a service provider setting. Perspectives of those observing and making decisions were examined. In study 1, business students who learned the results of a financial advisor's stock purchase showed the traditional hindsight effect…

  6. Integrated Bayesian models of learning and decision making for saccadic eye movements.

    PubMed

    Brodersen, Kay H; Penny, Will D; Harrison, Lee M; Daunizeau, Jean; Ruff, Christian C; Duzel, Emrah; Friston, Karl J; Stephan, Klaas E

    2008-11-01

    The neurophysiology of eye movements has been studied extensively, and several computational models have been proposed for decision-making processes that underlie the generation of eye movements towards a visual stimulus in a situation of uncertainty. One class of models, known as linear rise-to-threshold models, provides an economical, yet broadly applicable, explanation for the observed variability in the latency between the onset of a peripheral visual target and the saccade towards it. So far, however, these models do not account for the dynamics of learning across a sequence of stimuli, and they do not apply to situations in which subjects are exposed to events with conditional probabilities. In this methodological paper, we extend the class of linear rise-to-threshold models to address these limitations. Specifically, we reformulate previous models in terms of a generative, hierarchical model, by combining two separate sub-models that account for the interplay between learning of target locations across trials and the decision-making process within trials. We derive a maximum-likelihood scheme for parameter estimation as well as model comparison on the basis of log likelihood ratios. The utility of the integrated model is demonstrated by applying it to empirical saccade data acquired from three healthy subjects. Model comparison is used (i) to show that eye movements do not only reflect marginal but also conditional probabilities of target locations, and (ii) to reveal subject-specific learning profiles over trials. These individual learning profiles are sufficiently distinct that test samples can be successfully mapped onto the correct subject by a naïve Bayes classifier. Altogether, our approach extends the class of linear rise-to-threshold models of saccadic decision making, overcomes some of their previous limitations, and enables statistical inference both about learning of target locations across trials and the decision-making process within trials.

  7. Translational studies of goal-directed action as a framework for classifying deficits across psychiatric disorders

    PubMed Central

    Griffiths, Kristi R.; Morris, Richard W.; Balleine, Bernard W.

    2014-01-01

    The ability to learn contingencies between actions and outcomes in a dynamic environment is critical for flexible, adaptive behavior. Goal-directed actions adapt to changes in action-outcome contingencies as well as to changes in the reward-value of the outcome. When networks involved in reward processing and contingency learning are maladaptive, this fundamental ability can be lost, with detrimental consequences for decision-making. Impaired decision-making is a core feature in a number of psychiatric disorders, ranging from depression to schizophrenia. The argument can be developed, therefore, that seemingly disparate symptoms across psychiatric disorders can be explained by dysfunction within common decision-making circuitry. From this perspective, gaining a better understanding of the neural processes involved in goal-directed action, will allow a comparison of deficits observed across traditional diagnostic boundaries within a unified theoretical framework. This review describes the key processes and neural circuits involved in goal-directed decision-making using evidence from animal studies and human neuroimaging. Select studies are discussed to outline what we currently know about causal judgments regarding actions and their consequences, action-related reward evaluation, and, most importantly, how these processes are integrated in goal-directed learning and performance. Finally, we look at how adaptive decision-making is impaired across a range of psychiatric disorders and how deepening our understanding of this circuitry may offer insights into phenotypes and more targeted interventions. PMID:24904322

  8. Feedback Blunting: Total Sleep Deprivation Impairs Decision Making that Requires Updating Based on Feedback

    PubMed Central

    Whitney, Paul; Hinson, John M.; Jackson, Melinda L.; Van Dongen, Hans P.A.

    2015-01-01

    Study Objectives: To better understand the sometimes catastrophic effects of sleep loss on naturalistic decision making, we investigated effects of sleep deprivation on decision making in a reversal learning paradigm requiring acquisition and updating of information based on outcome feedback. Design: Subjects were randomized to a sleep deprivation or control condition, with performance testing at baseline, after 2 nights of total sleep deprivation (or rested control), and following 2 nights of recovery sleep. Subjects performed a decision task involving initial learning of go and no go response sets followed by unannounced reversal of contingencies, requiring use of outcome feedback for decisions. A working memory scanning task and psychomotor vigilance test were also administered. Setting: Six consecutive days and nights in a controlled laboratory environment with continuous behavioral monitoring. Subjects: Twenty-six subjects (22–40 y of age; 10 women). Interventions: Thirteen subjects were randomized to a 62-h total sleep deprivation condition; the others were controls. Results: Unlike controls, sleep deprived subjects had difficulty with initial learning of go and no go stimuli sets and had profound impairment adapting to reversal. Skin conductance responses to outcome feedback were diminished, indicating blunted affective reactions to feedback accompanying sleep deprivation. Working memory scanning performance was not significantly affected by sleep deprivation. And although sleep deprived subjects showed expected attentional lapses, these could not account for impairments in reversal learning decision making. Conclusions: Sleep deprivation is particularly problematic for decision making involving uncertainty and unexpected change. Blunted reactions to feedback while sleep deprived underlie failures to adapt to uncertainty and changing contingencies. Thus, an error may register, but with diminished effect because of reduced affective valence of the feedback or because the feedback is not cognitively bound with the choice. This has important implications for understanding and managing sleep loss-induced cognitive impairment in emergency response, disaster management, military operations, and other dynamic real-world settings with uncertain outcomes and imperfect information. Citation: Whitney P, Hinson JM, Jackson ML, Van Dongen HPA. Feedback blunting: total sleep deprivation impairs decision making that requires updating based on feedback. SLEEP 2015;38(5):745–754. PMID:25515105

  9. Goal-Directed Decision Making with Spiking Neurons.

    PubMed

    Friedrich, Johannes; Lengyel, Máté

    2016-02-03

    Behavioral and neuroscientific data on reward-based decision making point to a fundamental distinction between habitual and goal-directed action selection. The formation of habits, which requires simple updating of cached values, has been studied in great detail, and the reward prediction error theory of dopamine function has enjoyed prominent success in accounting for its neural bases. In contrast, the neural circuit mechanisms of goal-directed decision making, requiring extended iterative computations to estimate values online, are still unknown. Here we present a spiking neural network that provably solves the difficult online value estimation problem underlying goal-directed decision making in a near-optimal way and reproduces behavioral as well as neurophysiological experimental data on tasks ranging from simple binary choice to sequential decision making. Our model uses local plasticity rules to learn the synaptic weights of a simple neural network to achieve optimal performance and solves one-step decision-making tasks, commonly considered in neuroeconomics, as well as more challenging sequential decision-making tasks within 1 s. These decision times, and their parametric dependence on task parameters, as well as the final choice probabilities match behavioral data, whereas the evolution of neural activities in the network closely mimics neural responses recorded in frontal cortices during the execution of such tasks. Our theory provides a principled framework to understand the neural underpinning of goal-directed decision making and makes novel predictions for sequential decision-making tasks with multiple rewards. Goal-directed actions requiring prospective planning pervade decision making, but their circuit-level mechanisms remain elusive. We show how a model circuit of biologically realistic spiking neurons can solve this computationally challenging problem in a novel way. The synaptic weights of our network can be learned using local plasticity rules such that its dynamics devise a near-optimal plan of action. By systematically comparing our model results to experimental data, we show that it reproduces behavioral decision times and choice probabilities as well as neural responses in a rich set of tasks. Our results thus offer the first biologically realistic account for complex goal-directed decision making at a computational, algorithmic, and implementational level. Copyright © 2016 the authors 0270-6474/16/361529-18$15.00/0.

  10. Goal-Directed Decision Making with Spiking Neurons

    PubMed Central

    Lengyel, Máté

    2016-01-01

    Behavioral and neuroscientific data on reward-based decision making point to a fundamental distinction between habitual and goal-directed action selection. The formation of habits, which requires simple updating of cached values, has been studied in great detail, and the reward prediction error theory of dopamine function has enjoyed prominent success in accounting for its neural bases. In contrast, the neural circuit mechanisms of goal-directed decision making, requiring extended iterative computations to estimate values online, are still unknown. Here we present a spiking neural network that provably solves the difficult online value estimation problem underlying goal-directed decision making in a near-optimal way and reproduces behavioral as well as neurophysiological experimental data on tasks ranging from simple binary choice to sequential decision making. Our model uses local plasticity rules to learn the synaptic weights of a simple neural network to achieve optimal performance and solves one-step decision-making tasks, commonly considered in neuroeconomics, as well as more challenging sequential decision-making tasks within 1 s. These decision times, and their parametric dependence on task parameters, as well as the final choice probabilities match behavioral data, whereas the evolution of neural activities in the network closely mimics neural responses recorded in frontal cortices during the execution of such tasks. Our theory provides a principled framework to understand the neural underpinning of goal-directed decision making and makes novel predictions for sequential decision-making tasks with multiple rewards. SIGNIFICANCE STATEMENT Goal-directed actions requiring prospective planning pervade decision making, but their circuit-level mechanisms remain elusive. We show how a model circuit of biologically realistic spiking neurons can solve this computationally challenging problem in a novel way. The synaptic weights of our network can be learned using local plasticity rules such that its dynamics devise a near-optimal plan of action. By systematically comparing our model results to experimental data, we show that it reproduces behavioral decision times and choice probabilities as well as neural responses in a rich set of tasks. Our results thus offer the first biologically realistic account for complex goal-directed decision making at a computational, algorithmic, and implementational level. PMID:26843636

  11. Anxiety and Decision-Making

    PubMed Central

    Hartley, Catherine A.; Phelps, Elizabeth A.

    2013-01-01

    While the everyday decision-making of clinically anxious individuals is clearly influenced by their excessive fear and worry, the relationship between anxiety and decision-making remains relatively unexplored in neuroeconomic studies. In this review, we attempt to explore the role of anxiety in decision-making using a neuroeconomic approach. We first review the neural systems mediating fear and anxiety, which overlap with a network of brain regions implicated in studies of economic decision-making. We then discuss the potential influence of cognitive biases associated with anxiety upon economic choice, focusing on a set of decision-making biases involving choice in the face of potential aversive outcomes. We propose that the neural circuitry supporting fear learning and regulation may mediate the influence of anxiety upon choice, and suggest that techniques for altering fear and anxiety may also change decisions. PMID:22325982

  12. Managing and learning with multiple models: Objectives and optimization algorithms

    USGS Publications Warehouse

    Probert, William J. M.; Hauser, C.E.; McDonald-Madden, E.; Runge, M.C.; Baxter, P.W.J.; Possingham, H.P.

    2011-01-01

    The quality of environmental decisions should be gauged according to managers' objectives. Management objectives generally seek to maximize quantifiable measures of system benefit, for instance population growth rate. Reaching these goals often requires a certain degree of learning about the system. Learning can occur by using management action in combination with a monitoring system. Furthermore, actions can be chosen strategically to obtain specific kinds of information. Formal decision making tools can choose actions to favor such learning in two ways: implicitly via the optimization algorithm that is used when there is a management objective (for instance, when using adaptive management), or explicitly by quantifying knowledge and using it as the fundamental project objective, an approach new to conservation.This paper outlines three conservation project objectives - a pure management objective, a pure learning objective, and an objective that is a weighted mixture of these two. We use eight optimization algorithms to choose actions that meet project objectives and illustrate them in a simulated conservation project. The algorithms provide a taxonomy of decision making tools in conservation management when there is uncertainty surrounding competing models of system function. The algorithms build upon each other such that their differences are highlighted and practitioners may see where their decision making tools can be improved. ?? 2010 Elsevier Ltd.

  13. Use of Inverse Reinforcement Learning for Identity Prediction

    NASA Technical Reports Server (NTRS)

    Hayes, Roy; Bao, Jonathan; Beling, Peter; Horowitz, Barry

    2011-01-01

    We adopt Markov Decision Processes (MDP) to model sequential decision problems, which have the characteristic that the current decision made by a human decision maker has an uncertain impact on future opportunity. We hypothesize that the individuality of decision makers can be modeled as differences in the reward function under a common MDP model. A machine learning technique, Inverse Reinforcement Learning (IRL), was used to learn an individual's reward function based on limited observation of his or her decision choices. This work serves as an initial investigation for using IRL to analyze decision making, conducted through a human experiment in a cyber shopping environment. Specifically, the ability to determine the demographic identity of users is conducted through prediction analysis and supervised learning. The results show that IRL can be used to correctly identify participants, at a rate of 68% for gender and 66% for one of three college major categories.

  14. Practices and Prospects of Learner Autonomy: Teachers' Perceptions

    ERIC Educational Resources Information Center

    Al Asmari, AbdulRahman

    2013-01-01

    Language learning process works through the learners' own reflection on how they learn and it makes learners active in the sense that they learn to analyze their learning strategies. So they start making decisions, e.g., whether to improve them or not, and in which way. Generally, this trait is missing in traditional language teaching process and…

  15. How Service-Learning Can Ignite Thinking

    ERIC Educational Resources Information Center

    Serriere, Stephanie; McGarry, Lori; Fuentes, David; Mitra, Dana

    2012-01-01

    At its best, service learning involves students making meaningful connections to their own community and feeling empowered by the experience. Unfortunately, in the elementary years, student service-learning is often a one-shot effort in which adults make decisions for children, preventing them from truly having a hand in the project's direction…

  16. Post learning sleep improves cognitive-emotional decision-making: evidence for a 'deck B sleep effect' in the Iowa Gambling Task.

    PubMed

    Seeley, Corrine J; Beninger, Richard J; Smith, Carlyle T

    2014-01-01

    The Iowa Gambling Task (IGT) is widely used to assess real life decision-making impairment in a wide variety of clinical populations. Our study evaluated how IGT learning occurs across two sessions, and whether a period of intervening sleep between sessions can enhance learning. Furthermore, we investigate whether pre-sleep learning is necessary for this improvement. A 200-trial version of the IGT was administered at two sessions separated by wake, sleep or sleep and wake (time-of-day control). Participants were categorized as learners and non-learners based on initial performance in session one. In session one, participants initially preferred the high-frequency reward decks B and D, however, a subset of learners decreased choice from negative expected value 'bad' deck B and increased choices towards with a positive expected value 'good' decks (decks C and D). The learners who had a period of sleep (sleep and sleep/wake control conditions) between sessions showed significantly larger reduction in choices from deck B and increase in choices from good decks compared to learners that had intervening wake. Our results are the first to show that post-learning sleep can improve performance on a complex decision-making task such as the IGT. These results provide new insights into IGT learning and have important implications for understanding the neural mechanisms of "sleeping on" a decision.

  17. Enhancing Learning Outcomes with an Interactive Knowledge-Based Learning Environment Providing Narrative Feedback

    ERIC Educational Resources Information Center

    Stranieri, Andrew; Yearwood, John

    2008-01-01

    This paper describes a narrative-based interactive learning environment which aims to elucidate reasoning using interactive scenarios that may be used in training novices in decision-making. Its design is based on an approach to generating narrative from knowledge that has been modelled in specific decision/reasoning domains. The approach uses a…

  18. Resonant Cholinergic Dynamics in Cognitive and Motor Decision-Making: Attention, Category Learning, and Choice in Neocortex, Superior Colliculus, and Optic Tectum.

    PubMed

    Grossberg, Stephen; Palma, Jesse; Versace, Massimiliano

    2015-01-01

    Freely behaving organisms need to rapidly calibrate their perceptual, cognitive, and motor decisions based on continuously changing environmental conditions. These plastic changes include sharpening or broadening of cognitive and motor attention and learning to match the behavioral demands that are imposed by changing environmental statistics. This article proposes that a shared circuit design for such flexible decision-making is used in specific cognitive and motor circuits, and that both types of circuits use acetylcholine to modulate choice selectivity. Such task-sensitive control is proposed to control thalamocortical choice of the critical features that are cognitively attended and that are incorporated through learning into prototypes of visual recognition categories. A cholinergically-modulated process of vigilance control determines if a recognition category and its attended features are abstract (low vigilance) or concrete (high vigilance). Homologous neural mechanisms of cholinergic modulation are proposed to focus attention and learn a multimodal map within the deeper layers of superior colliculus. This map enables visual, auditory, and planned movement commands to compete for attention, leading to selection of a winning position that controls where the next saccadic eye movement will go. Such map learning may be viewed as a kind of attentive motor category learning. The article hereby explicates a link between attention, learning, and cholinergic modulation during decision making within both cognitive and motor systems. Homologs between the mammalian superior colliculus and the avian optic tectum lead to predictions about how multimodal map learning may occur in the mammalian and avian brain and how such learning may be modulated by acetycholine.

  19. Resonant Cholinergic Dynamics in Cognitive and Motor Decision-Making: Attention, Category Learning, and Choice in Neocortex, Superior Colliculus, and Optic Tectum

    PubMed Central

    Grossberg, Stephen; Palma, Jesse; Versace, Massimiliano

    2016-01-01

    Freely behaving organisms need to rapidly calibrate their perceptual, cognitive, and motor decisions based on continuously changing environmental conditions. These plastic changes include sharpening or broadening of cognitive and motor attention and learning to match the behavioral demands that are imposed by changing environmental statistics. This article proposes that a shared circuit design for such flexible decision-making is used in specific cognitive and motor circuits, and that both types of circuits use acetylcholine to modulate choice selectivity. Such task-sensitive control is proposed to control thalamocortical choice of the critical features that are cognitively attended and that are incorporated through learning into prototypes of visual recognition categories. A cholinergically-modulated process of vigilance control determines if a recognition category and its attended features are abstract (low vigilance) or concrete (high vigilance). Homologous neural mechanisms of cholinergic modulation are proposed to focus attention and learn a multimodal map within the deeper layers of superior colliculus. This map enables visual, auditory, and planned movement commands to compete for attention, leading to selection of a winning position that controls where the next saccadic eye movement will go. Such map learning may be viewed as a kind of attentive motor category learning. The article hereby explicates a link between attention, learning, and cholinergic modulation during decision making within both cognitive and motor systems. Homologs between the mammalian superior colliculus and the avian optic tectum lead to predictions about how multimodal map learning may occur in the mammalian and avian brain and how such learning may be modulated by acetycholine. PMID:26834535

  20. Facts and fiction of learning systems. [decision making intelligent control

    NASA Technical Reports Server (NTRS)

    Saridis, G. N.

    1975-01-01

    The methodology that will provide the updated precision for the hardware control and the advanced decision making and planning in the software control is called learning systems and intelligent control. It was developed theoretically as an alternative for the nonsystematic heuristic approaches of artificial intelligence experiments and the inflexible formulation of modern optimal control methods. Its basic concepts are discussed and some feasibility studies of some practical applications are presented.

  1. Nursing Student Perceptions Regarding Simulation Experience Sequencing.

    PubMed

    Woda, Aimee A; Gruenke, Theresa; Alt-Gehrman, Penny; Hansen, Jamie

    2016-09-01

    The use of simulated learning experiences (SLEs) have increased within nursing curricula with positive learning outcomes for nursing students. The purpose of this study is to explore nursing students' perceptions of their clinical decision making (CDM) related to the block sequencing of different patient care experiences, SLEs versus hospital-based learning experiences (HLEs). A qualitative descriptive design used open-ended survey questions to generate information about the block sequencing of SLEs and its impact on nursing students' perceived CDM. Three themes emerged from the data: Preexperience Anxiety, Real-Time Decision Making, and Increased Patient Care Experiences. Nursing students identified that having SLEs prior to HLEs provided several benefits. Even when students preferred SLEs prior to HLEs, the sequence did not impact their CDM. This suggests that alternating block sequencing can be used without impacting the students' perceptions of their ability to make decisions. [J Nurs Educ. 2016;55(9):528-532.]. Copyright 2016, SLACK Incorporated.

  2. Neural coding of basic reward terms of animal learning theory, game theory, microeconomics and behavioural ecology.

    PubMed

    Schultz, Wolfram

    2004-04-01

    Neurons in a small number of brain structures detect rewards and reward-predicting stimuli and are active during the expectation of predictable food and liquid rewards. These neurons code the reward information according to basic terms of various behavioural theories that seek to explain reward-directed learning, approach behaviour and decision-making. The involved brain structures include groups of dopamine neurons, the striatum including the nucleus accumbens, the orbitofrontal cortex and the amygdala. The reward information is fed to brain structures involved in decision-making and organisation of behaviour, such as the dorsolateral prefrontal cortex and possibly the parietal cortex. The neural coding of basic reward terms derived from formal theories puts the neurophysiological investigation of reward mechanisms on firm conceptual grounds and provides neural correlates for the function of rewards in learning, approach behaviour and decision-making.

  3. Dynamic adaptive learning for decision-making supporting systems

    NASA Astrophysics Data System (ADS)

    He, Haibo; Cao, Yuan; Chen, Sheng; Desai, Sachi; Hohil, Myron E.

    2008-03-01

    This paper proposes a novel adaptive learning method for data mining in support of decision-making systems. Due to the inherent characteristics of information ambiguity/uncertainty, high dimensionality and noisy in many homeland security and defense applications, such as surveillances, monitoring, net-centric battlefield, and others, it is critical to develop autonomous learning methods to efficiently learn useful information from raw data to help the decision making process. The proposed method is based on a dynamic learning principle in the feature spaces. Generally speaking, conventional approaches of learning from high dimensional data sets include various feature extraction (principal component analysis, wavelet transform, and others) and feature selection (embedded approach, wrapper approach, filter approach, and others) methods. However, very limited understandings of adaptive learning from different feature spaces have been achieved. We propose an integrative approach that takes advantages of feature selection and hypothesis ensemble techniques to achieve our goal. Based on the training data distributions, a feature score function is used to provide a measurement of the importance of different features for learning purpose. Then multiple hypotheses are iteratively developed in different feature spaces according to their learning capabilities. Unlike the pre-set iteration steps in many of the existing ensemble learning approaches, such as adaptive boosting (AdaBoost) method, the iterative learning process will automatically stop when the intelligent system can not provide a better understanding than a random guess in that particular subset of feature spaces. Finally, a voting algorithm is used to combine all the decisions from different hypotheses to provide the final prediction results. Simulation analyses of the proposed method on classification of different US military aircraft databases show the effectiveness of this method.

  4. Age-related changes in decision making: comparing informed and noninformed situations.

    PubMed

    Van Duijvenvoorde, Anna C K; Jansen, Brenda R J; Bredman, Joren C; Huizenga, Hilde M

    2012-01-01

    Advantageous decision making progressively develops into early adulthood, most specifically in complex and motivationally salient decision situations in which direct feedback on gains and losses is provided (Figner & Weber, 2011). However, the factors that underlie this developmental improvement in decision making are still not well understood. The current study therefore investigates 2 potential factors, long-term memory and working memory, by assigning a large developmental sample (7-29 years of age) to a condition with either high or low demands on long-term and working memory. The first condition featured an age-adapted version of the Iowa Gambling Task (IGT; Bechara, Damasio, Damasio, & Anderson, 1994; i.e., a noninformed situation), whereas the second condition provided an external store where explicit information on gains, losses, and probabilities per choice option was presented (i.e., an informed situation). Consistent with previous developmental IGT studies, children up to age 12 did not learn to prefer advantageous options in the noninformed condition. In contrast, all age groups learned to prefer the advantageous options in the informed conditions, although a slight developmental increase in advantageous decision making remained. These results indicate that lowering dependence on long-term and working memory improves children's advantageous decision making. The results additionally suggest that other factors, like inhibitory control processes, may play an additional role in the development of advantageous decision making.

  5. Feedback Blunting: Total Sleep Deprivation Impairs Decision Making that Requires Updating Based on Feedback.

    PubMed

    Whitney, Paul; Hinson, John M; Jackson, Melinda L; Van Dongen, Hans P A

    2015-05-01

    To better understand the sometimes catastrophic effects of sleep loss on naturalistic decision making, we investigated effects of sleep deprivation on decision making in a reversal learning paradigm requiring acquisition and updating of information based on outcome feedback. Subjects were randomized to a sleep deprivation or control condition, with performance testing at baseline, after 2 nights of total sleep deprivation (or rested control), and following 2 nights of recovery sleep. Subjects performed a decision task involving initial learning of go and no go response sets followed by unannounced reversal of contingencies, requiring use of outcome feedback for decisions. A working memory scanning task and psychomotor vigilance test were also administered. Six consecutive days and nights in a controlled laboratory environment with continuous behavioral monitoring. Twenty-six subjects (22-40 y of age; 10 women). Thirteen subjects were randomized to a 62-h total sleep deprivation condition; the others were controls. Unlike controls, sleep deprived subjects had difficulty with initial learning of go and no go stimuli sets and had profound impairment adapting to reversal. Skin conductance responses to outcome feedback were diminished, indicating blunted affective reactions to feedback accompanying sleep deprivation. Working memory scanning performance was not significantly affected by sleep deprivation. And although sleep deprived subjects showed expected attentional lapses, these could not account for impairments in reversal learning decision making. Sleep deprivation is particularly problematic for decision making involving uncertainty and unexpected change. Blunted reactions to feedback while sleep deprived underlie failures to adapt to uncertainty and changing contingencies. Thus, an error may register, but with diminished effect because of reduced affective valence of the feedback or because the feedback is not cognitively bound with the choice. This has important implications for understanding and managing sleep loss-induced cognitive impairment in emergency response, disaster management, military operations, and other dynamic real-world settings with uncertain outcomes and imperfect information. © 2015 Associated Professional Sleep Societies, LLC.

  6. Key Elements of a Successful Drive toward Marketing Strategy Making

    ERIC Educational Resources Information Center

    Cann, Cynthia W.; George, Marie A.

    2003-01-01

    A conceptual model is presented that depicts the relationship between an internal marketing function and an organization's readiness to learn. Learning and marketing orientations are identified as components to marketing strategy making. Key organizational functions, including communication and decision-making, are utilized in a framework for…

  7. Types of vicarious learning experienced by pre-dialysis patients.

    PubMed

    McCarthy, Kate; Sturt, Jackie; Adams, Ann

    2015-01-01

    Haemodialysis and peritoneal dialysis renal replacement treatment options are in clinical equipoise, although the cost of haemodialysis to the National Health Service is £16,411/patient/year greater than peritoneal dialysis. Treatment decision-making takes place during the pre-dialysis year when estimated glomerular filtration rate drops to between 15 and 30 mL/min/1.73 m(2). Renal disease can be familial, and the majority of patients have considerable health service experience when they approach these treatment decisions. Factors affecting patient treatment decisions are currently unknown. The objective of this article is to explore data from a wider study in specific relation to the types of vicarious learning experiences reported by pre-dialysis patients. A qualitative study utilised unstructured interviews and grounded theory analysis during the participant's pre-dialysis year. The interview cohort comprised 20 pre-dialysis participants between 24 and 80 years of age. Grounded theory design entailed thematic sampling and analysis, scrutinised by secondary coding and checked with participants. Participants were recruited from routine renal clinics at two local hospitals when their estimated glomerular filtration rate was between 15 and 30 mL/min/1.73 m(2). Vicarious learning that contributed to treatment decision-making fell into three main categories: planned vicarious leaning, unplanned vicarious learning and historical vicarious experiences. Exploration and acknowledgement of service users' prior vicarious learning, by healthcare professionals, is important in understanding its potential influences on individuals' treatment decision-making. This will enable healthcare professionals to challenge heuristic decisions based on limited information and to encourage analytic thought processes.

  8. Impaired Expected Value Computations Coupled With Overreliance on Stimulus-Response Learning in Schizophrenia.

    PubMed

    Hernaus, Dennis; Gold, James M; Waltz, James A; Frank, Michael J

    2018-04-03

    While many have emphasized impaired reward prediction error signaling in schizophrenia, multiple studies suggest that some decision-making deficits may arise from overreliance on stimulus-response systems together with a compromised ability to represent expected value. Guided by computational frameworks, we formulated and tested two scenarios in which maladaptive representations of expected value should be most evident, thereby delineating conditions that may evoke decision-making impairments in schizophrenia. In a modified reinforcement learning paradigm, 42 medicated people with schizophrenia and 36 healthy volunteers learned to select the most frequently rewarded option in a 75-25 pair: once when presented with a more deterministic (90-10) pair and once when presented with a more probabilistic (60-40) pair. Novel and old combinations of choice options were presented in a subsequent transfer phase. Computational modeling was employed to elucidate contributions from stimulus-response systems (actor-critic) and expected value (Q-learning). People with schizophrenia showed robust performance impairments with increasing value difference between two competing options, which strongly correlated with decreased contributions from expected value-based learning (Q-learning). Moreover, a subtle yet consistent contextual choice bias for the probabilistic 75 option was present in people with schizophrenia, which could be accounted for by a context-dependent reward prediction error in the actor-critic. We provide evidence that decision-making impairments in schizophrenia increase monotonically with demands placed on expected value computations. A contextual choice bias is consistent with overreliance on stimulus-response learning, which may signify a deficit secondary to the maladaptive representation of expected value. These results shed new light on conditions under which decision-making impairments may arise. Copyright © 2018 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  9. A Survey on Turkish nursing students' perception of clinical learning environment and its association with academic motivation and clinical decision making.

    PubMed

    Aktaş, Yeşim Yaman; Karabulut, Neziha

    2016-01-01

    Nursing education is a process that includes theoretical and practical learning and requires the acquisition of theoretical knowledge and skill. Nursing students need a good clinical practice environment in order to apply their knowledge and skills due to the fact that the clinical practice settings play an important role in the nursing profession. This study was carried out in an effort to explore nursing students' perception of the clinical learning environment and its association with academic motivation and clinical decision making. A descriptive survey design was used. This study was conducted in Giresun University in Turkey. Participants were second-, third- and fourth-year undergraduate students (n=222) in the Bachelor of Nursing Science Degree in the academic spring term of 2014-2015. The data was collected using the 'Clinical Learning Environment Scale', the 'Academic Motivation, and the 'The Clinical Decision Making in Nursing Scale'. Of the respondents in this study, 45% of the students were second class, 30.6% of the students were third class and 24.3% of the students were fourth class. There was a statistically significant positive correlation found between the clinical learning environment and the nursing students' academic motivation (r=0.182, p<.05). However, there was no correlation between the clinical learning environment and clinical decision making (r=0.082, p>.05). One of the prerequisites for the training of qualified students is to provide nursing students with a qualified clinical environment. It was found that nursing students' academic motivation increased as the quality of their clinical learning environment improved. Copyright © 2015 Elsevier Ltd. All rights reserved.

  10. Economic decision-making in the ultimatum game by smokers.

    PubMed

    Takahashi, Taiki

    2007-10-01

    No study to date compared degrees of inequity aversion in economic decision-making in the ultimatum game between non-addictive and addictive reinforcers. The comparison is potentially important in neuroeconomics and reinforcement learning theory of addiction. We compared the degrees of inequity aversion in the ultimatum game between money and cigarettes in habitual smokers. Smokers avoided inequity in the ultimatum game more dramatically for money than for cigarettes; i.e., there was a "domain effect" in decision-making in the ultimatum game. Reward-processing neural activities in the brain for non-addictive and addictive reinforcers may be distinct and the insula activation due to cue-induced craving may conflict with unfair offer-induced insula activation. Future studies in neuroeconomics of addiction should employ game-theoretic decision tasks for elucidating reinforcement learning processes in dopaminergic neural circuits.

  11. The Way We Learn

    ERIC Educational Resources Information Center

    Caine, Renate Nummela; Caine, Geoffrey

    2006-01-01

    Although students' eclecticism can be overwhelming, all students are identical in at least one respect--they are biologically equipped to learn from experiences. Caine and Caine discuss neurological findings about decision-making capacities built into the brain. They describe Elkhonen Goldberg's concept of actor-centered adaptive decision making…

  12. Agency and Error in Young Adults' Stories of Sexual Decision Making

    ERIC Educational Resources Information Center

    Allen, Katherine R.; Husser, Erica K.; Stone, Dana J.; Jordal, Christian E.

    2008-01-01

    We conducted a qualitative analysis of 148 college students' written comments about themselves as sexual decision makers. Most participants described experiences in which they were actively engaged in decision-making processes of "waiting it out" to "working it out." The four patterns were (a) I am in control, (b) I am experimenting and learning,…

  13. Episodic memories predict adaptive value-based decision-making

    PubMed Central

    Murty, Vishnu; FeldmanHall, Oriel; Hunter, Lindsay E.; Phelps, Elizabeth A; Davachi, Lila

    2016-01-01

    Prior research illustrates that memory can guide value-based decision-making. For example, previous work has implicated both working memory and procedural memory (i.e., reinforcement learning) in guiding choice. However, other types of memories, such as episodic memory, may also influence decision-making. Here we test the role for episodic memory—specifically item versus associative memory—in supporting value-based choice. Participants completed a task where they first learned the value associated with trial unique lotteries. After a short delay, they completed a decision-making task where they could choose to re-engage with previously encountered lotteries, or new never before seen lotteries. Finally, participants completed a surprise memory test for the lotteries and their associated values. Results indicate that participants chose to re-engage more often with lotteries that resulted in high versus low rewards. Critically, participants not only formed detailed, associative memories for the reward values coupled with individual lotteries, but also exhibited adaptive decision-making only when they had intact associative memory. We further found that the relationship between adaptive choice and associative memory generalized to more complex, ecologically valid choice behavior, such as social decision-making. However, individuals more strongly encode experiences of social violations—such as being treated unfairly, suggesting a bias for how individuals form associative memories within social contexts. Together, these findings provide an important integration of episodic memory and decision-making literatures to better understand key mechanisms supporting adaptive behavior. PMID:26999046

  14. Meta-Analytic Evidence for a Reversal Learning Effect on the Iowa Gambling Task in Older Adults.

    PubMed

    Pasion, Rita; Gonçalves, Ana R; Fernandes, Carina; Ferreira-Santos, Fernando; Barbosa, Fernando; Marques-Teixeira, João

    2017-01-01

    Iowa Gambling Task (IGT) is one of the most widely used tools to assess economic decision-making. However, the research tradition on aging and the Iowa Gambling Task (IGT) has been mainly focused on the overall performance of older adults in relation to younger or clinical groups, remaining unclear whether older adults are capable of learning along the task. We conducted a meta-analysis to examine older adults' decision-making on the IGT, to test the effects of aging on reversal learning (45 studies) and to provide normative data on total and block net scores (55 studies). From the accumulated empirical evidence, we found an average total net score of 7.55 (±25.9). We also observed a significant reversal learning effect along the blocks of the IGT, indicating that older adults inhibit the prepotent response toward immediately attractive options associated with high losses, in favor of initially less attractive options associated with long-run profit. During block 1, decisions of older adults led to a negative gambling net score, reflecting the expected initial pattern of risk-taking. However, the shift toward more safe options occurred between block 2 (small-to-medium effect size) and blocks 3, 4, 5 (medium-to-large effect size). These main findings highlight that older adults are able to move from the initial uncertainty, when the possible outcomes are unknown, to decisions based on risk, when the outcomes are learned and may be used to guide future adaptive decision-making.

  15. Resilience Education.

    ERIC Educational Resources Information Center

    Brown, Joel H.; D'Emidio-Caston, Marianne; Benard, Bonnie

    This book examines how young people who struggle with life's worst conditions somehow manage to overcome adversity, identifying significant factors that contribute to their resilience. The book presents information and decision making skills students need to make good decisions in the face of adversity; learning strategies and teaching techniques…

  16. Learning and Decision Making in Groups

    ERIC Educational Resources Information Center

    Rahimian, M. Amin

    2017-01-01

    Many important real-world decision-making problems involve group interactions among individuals with purely informational interactions. Such situations arise for example in jury deliberations, expert committees, medical diagnoses, etc. We model the purely informational interactions of group members, where they receive private information and act…

  17. A cognitive prosthesis for complex decision-making.

    PubMed

    Tremblay, Sébastien; Gagnon, Jean-François; Lafond, Daniel; Hodgetts, Helen M; Doiron, Maxime; Jeuniaux, Patrick P J M H

    2017-01-01

    While simple heuristics can be ecologically rational and effective in naturalistic decision making contexts, complex situations require analytical decision making strategies, hypothesis-testing and learning. Sub-optimal decision strategies - using simplified as opposed to analytic decision rules - have been reported in domains such as healthcare, military operational planning, and government policy making. We investigate the potential of a computational toolkit called "IMAGE" to improve decision-making by developing structural knowledge and increasing understanding of complex situations. IMAGE is tested within the context of a complex military convoy management task through (a) interactive simulations, and (b) visualization and knowledge representation capabilities. We assess the usefulness of two versions of IMAGE (desktop and immersive) compared to a baseline. Results suggest that the prosthesis helped analysts in making better decisions, but failed to increase their structural knowledge about the situation once the cognitive prosthesis is removed. Copyright © 2016 Elsevier Ltd. All rights reserved.

  18. Passive and active adaptive management: Approaches and an example

    USGS Publications Warehouse

    Williams, B.K.

    2011-01-01

    Adaptive management is a framework for resource conservation that promotes iterative learning-based decision making. Yet there remains considerable confusion about what adaptive management entails, and how to actually make resource decisions adaptively. A key but somewhat ambiguous distinction in adaptive management is between active and passive forms of adaptive decision making. The objective of this paper is to illustrate some approaches to active and passive adaptive management with a simple example involving the drawdown of water impoundments on a wildlife refuge. The approaches are illustrated for the drawdown example, and contrasted in terms of objectives, costs, and potential learning rates. Some key challenges to the actual practice of AM are discussed, and tradeoffs between implementation costs and long-term benefits are highlighted. ?? 2010 Elsevier Ltd.

  19. Bringing science to the table: Case studies in science-informed decision making on climate change and beyond

    NASA Astrophysics Data System (ADS)

    Goldman, G. T.; Phartiyal, P.; Mulvey, K.

    2016-12-01

    Federal government officials often rely on the research and advice of scientists to inform their decision making around climate change and other complex topics. Decision makers, however, are constrained by the time and accessibility needed to obtain and incorporate scientific information. At the same time, scientists have limited capacity and incentive to devote significant time to communicating their science to decision makers. The Union of Concerned Scientists has employed several strategies to produce policy-relevant scientific work and to facilitate engagement between scientists and decision makers across research areas. This talk will feature lessons learned and key strategies for science-informed decision making around climate change and other areas of the geosciences. Case studies will include conducting targeted sea level rise studies to inform rulemaking at federal agencies, bringing science to policy discussions on hydraulic fracturing, and leveraging the voice of the scientific community on specific policy proposals around climate change disclosure of companies. Recommendations and lessons learned for producing policy-relevant science and effectively communicating it with decision makers will be offered.

  20. Decision-making deficits in patients with chronic schizophrenia: Iowa Gambling Task and Prospect Valence Learning model.

    PubMed

    Kim, Myung-Sun; Kang, Bit-Na; Lim, Jae Young

    2016-01-01

    Decision-making is the process of forming preferences for possible options, selecting and executing actions, and evaluating the outcome. This study used the Iowa Gambling Task (IGT) and the Prospect Valence Learning (PVL) model to investigate deficits in risk-reward related decision-making in patients with chronic schizophrenia, and to identify decision-making processes that contribute to poor IGT performance in these patients. Thirty-nine patients with schizophrenia and 31 healthy controls participated. Decision-making was measured by total net score, block net scores, and the total number of cards selected from each deck of the IGT. PVL parameters were estimated with the Markov chain Monte Carlo sampling scheme in OpenBugs and BRugs, its interface to R, and the estimated parameters were analyzed with the Mann-Whitney U-test. The schizophrenia group received significantly lower total net scores compared to the control group. In terms of block net scores, an interaction effect of group × block was observed. The block net scores of the schizophrenia group did not differ across the five blocks, whereas those of the control group increased as the blocks progressed. The schizophrenia group obtained significantly lower block net scores in the fourth and fifth blocks of the IGT and selected cards from deck D (advantageous) less frequently than the control group. Additionally, the schizophrenia group had significantly lower values on the utility-shape, loss-aversion, recency, and consistency parameters of the PVL model. These results indicate that patients with schizophrenia experience deficits in decision-making, possibly due to failure in learning the expected value of each deck, and incorporating outcome experiences of previous trials into expectancies about options in the present trial.

  1. Understanding psychiatric disorder by capturing ecologically relevant features of learning and decision-making.

    PubMed

    Scholl, Jacqueline; Klein-Flügge, Miriam

    2017-09-28

    Recent research in cognitive neuroscience has begun to uncover the processes underlying increasingly complex voluntary behaviours, including learning and decision-making. Partly this success has been possible by progressing from simple experimental tasks to paradigms that incorporate more ecological features. More specifically, the premise is that to understand cognitions and brain functions relevant for real life, we need to introduce some of the ecological challenges that we have evolved to solve. This often entails an increase in task complexity, which can be managed by using computational models to help parse complex behaviours into specific component mechanisms. Here we propose that using computational models with tasks that capture ecologically relevant learning and decision-making processes may provide a critical advantage for capturing the mechanisms underlying symptoms of disorders in psychiatry. As a result, it may help develop mechanistic approaches towards diagnosis and treatment. We begin this review by mapping out the basic concepts and models of learning and decision-making. We then move on to consider specific challenges that emerge in realistic environments and describe how they can be captured by tasks. These include changes of context, uncertainty, reflexive/emotional biases, cost-benefit decision-making, and balancing exploration and exploitation. Where appropriate we highlight future or current links to psychiatry. We particularly draw examples from research on clinical depression, a disorder that greatly compromises motivated behaviours in real-life, but where simpler paradigms have yielded mixed results. Finally, we highlight several paradigms that could be used to help provide new insights into the mechanisms of psychiatric disorders. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

  2. Normative evidence accumulation in unpredictable environments

    PubMed Central

    Glaze, Christopher M; Kable, Joseph W; Gold, Joshua I

    2015-01-01

    In our dynamic world, decisions about noisy stimuli can require temporal accumulation of evidence to identify steady signals, differentiation to detect unpredictable changes in those signals, or both. Normative models can account for learning in these environments but have not yet been applied to faster decision processes. We present a novel, normative formulation of adaptive learning models that forms decisions by acting as a leaky accumulator with non-absorbing bounds. These dynamics, derived for both discrete and continuous cases, depend on the expected rate of change of the statistics of the evidence and balance signal identification and change detection. We found that, for two different tasks, human subjects learned these expectations, albeit imperfectly, then used them to make decisions in accordance with the normative model. The results represent a unified, empirically supported account of decision-making in unpredictable environments that provides new insights into the expectation-driven dynamics of the underlying neural signals. DOI: http://dx.doi.org/10.7554/eLife.08825.001 PMID:26322383

  3. Acute stress affects risk taking but not ambiguity aversion

    PubMed Central

    Buckert, Magdalena; Schwieren, Christiane; Kudielka, Brigitte M.; Fiebach, Christian J.

    2014-01-01

    Economic decisions are often made in stressful situations (e.g., at the trading floor), but the effects of stress on economic decision making have not been systematically investigated so far. The present study examines how acute stress influences economic decision making under uncertainty (risk and ambiguity) using financially incentivized lotteries. We varied the domain of decision making as well as the expected value of the risky prospect. Importantly, no feedback was provided to investigate risk taking and ambiguity aversion independent from learning processes. In a sample of 75 healthy young participants, 55 of whom underwent a stress induction protocol (Trier Social Stress Test for Groups), we observed more risk seeking for gains. This effect was restricted to a subgroup of participants that showed a robust cortisol response to acute stress (n = 26). Gambling under ambiguity, in contrast to gambling under risk, was not influenced by the cortisol response to stress. These results show that acute psychosocial stress affects economic decision making under risk, independent of learning processes. Our results further point to the importance of cortisol as a mediator of this effect. PMID:24834024

  4. Acute stress affects risk taking but not ambiguity aversion.

    PubMed

    Buckert, Magdalena; Schwieren, Christiane; Kudielka, Brigitte M; Fiebach, Christian J

    2014-01-01

    Economic decisions are often made in stressful situations (e.g., at the trading floor), but the effects of stress on economic decision making have not been systematically investigated so far. The present study examines how acute stress influences economic decision making under uncertainty (risk and ambiguity) using financially incentivized lotteries. We varied the domain of decision making as well as the expected value of the risky prospect. Importantly, no feedback was provided to investigate risk taking and ambiguity aversion independent from learning processes. In a sample of 75 healthy young participants, 55 of whom underwent a stress induction protocol (Trier Social Stress Test for Groups), we observed more risk seeking for gains. This effect was restricted to a subgroup of participants that showed a robust cortisol response to acute stress (n = 26). Gambling under ambiguity, in contrast to gambling under risk, was not influenced by the cortisol response to stress. These results show that acute psychosocial stress affects economic decision making under risk, independent of learning processes. Our results further point to the importance of cortisol as a mediator of this effect.

  5. Effects of invalid feedback on learning and feedback-related brain activity in decision-making.

    PubMed

    Ernst, Benjamin; Steinhauser, Marco

    2015-10-01

    For adaptive decision-making it is important to utilize only relevant, valid and to ignore irrelevant feedback. The present study investigated how feedback processing in decision-making is impaired when relevant feedback is combined with irrelevant and potentially invalid feedback. We analyzed two electrophysiological markers of feedback processing, the feedback-related negativity (FRN) and the P300, in a simple decision-making task, in which participants processed feedback stimuli consisting of relevant and irrelevant feedback provided by the color and meaning of a Stroop stimulus. We found that invalid, irrelevant feedback not only impaired learning, it also altered the amplitude of the P300 to relevant feedback, suggesting an interfering effect of irrelevant feedback on the processing of relevant feedback. In contrast, no such effect on the FRN was obtained. These results indicate that detrimental effects of invalid, irrelevant feedback result from failures of controlled feedback processing. Copyright © 2015 Elsevier Inc. All rights reserved.

  6. Decision theory, reinforcement learning, and the brain.

    PubMed

    Dayan, Peter; Daw, Nathaniel D

    2008-12-01

    Decision making is a core competence for animals and humans acting and surviving in environments they only partially comprehend, gaining rewards and punishments for their troubles. Decision-theoretic concepts permeate experiments and computational models in ethology, psychology, and neuroscience. Here, we review a well-known, coherent Bayesian approach to decision making, showing how it unifies issues in Markovian decision problems, signal detection psychophysics, sequential sampling, and optimal exploration and discuss paradigmatic psychological and neural examples of each problem. We discuss computational issues concerning what subjects know about their task and how ambitious they are in seeking optimal solutions; we address algorithmic topics concerning model-based and model-free methods for making choices; and we highlight key aspects of the neural implementation of decision making.

  7. Quantum ensembles of quantum classifiers.

    PubMed

    Schuld, Maria; Petruccione, Francesco

    2018-02-09

    Quantum machine learning witnesses an increasing amount of quantum algorithms for data-driven decision making, a problem with potential applications ranging from automated image recognition to medical diagnosis. Many of those algorithms are implementations of quantum classifiers, or models for the classification of data inputs with a quantum computer. Following the success of collective decision making with ensembles in classical machine learning, this paper introduces the concept of quantum ensembles of quantum classifiers. Creating the ensemble corresponds to a state preparation routine, after which the quantum classifiers are evaluated in parallel and their combined decision is accessed by a single-qubit measurement. This framework naturally allows for exponentially large ensembles in which - similar to Bayesian learning - the individual classifiers do not have to be trained. As an example, we analyse an exponentially large quantum ensemble in which each classifier is weighed according to its performance in classifying the training data, leading to new results for quantum as well as classical machine learning.

  8. Experiential Learning through Classroom Experiments

    ERIC Educational Resources Information Center

    Bowes, David; Johnson, Jay

    2008-01-01

    This paper describes classroom experiments in cooperative behavior as examples of experiential learning in economics classes. Several games are briefly discussed and a new game in cartel behavior is presented. In this game, Students make production decisions as a cartel and earn revenues based on their own output decision and the output decision…

  9. Cognitive Mechanisms in Decision-Making in Patients With Mild Alzheimer Disease.

    PubMed

    Alameda-Bailen, Jose Ramon; Salguero-Alcaniz, Maria Pilar; Merchan-Clavellino, Ana; Paino-Quesada, Susana

    2017-01-01

    Alzheimer's dementia is characterized by significant cortical and subcortical atrophy, causing diverse neuropsychological deficits. According to the somatic marker hypothesis, the areas responsible for generating the somatic markers that anticipate the consequences of a decision and thereby optimize the process would be affected in these patients. The aim of this experiment is to study the decision-making processes in Alzheimer type dementia patients to determine potential deficits in these processes as a result of the disease, aside from the cognitive impairment that is typical of aging. In addition, we wish to determine the defining characteristics of decision-making in these patients, on the basis of the prospect valence-learning parameters. We evaluated 30 patients with Alzheimer's disease and a control group of 30 healthy subjects. A short version of the Iowa Gambling Task was used. The results showed that patients made less advantageous choices than did controls. Group differences were quantitative and qualitative, as significant differences in cognitive mechanisms identified in the prospect valence-learning decisions were observed. These results are consistent with evidence from neuroimaging studies as well as with work carried out with amnesic patients. That problems in our patients' decision-making could be due to the characteristic memory deficits of this disease, which prevents them from establishing new stimulus-reward relationships and eliminating previously learned responses as a result of the parietal and temporal atrophy they present. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  10. Probabilistic Reward- and Punishment-based Learning in Opioid Addiction: Experimental and Computational Data

    PubMed Central

    Myers, Catherine E.; Sheynin, Jony; Baldson, Tarryn; Luzardo, Andre; Beck, Kevin D.; Hogarth, Lee; Haber, Paul; Moustafa, Ahmed A.

    2016-01-01

    Addiction is the continuation of a habit in spite of negative consequences. A vast literature gives evidence that this poor decision-making behavior in individuals addicted to drugs also generalizes to laboratory decision making tasks, suggesting that the impairment in decision-making is not limited to decisions about taking drugs. In the current experiment, opioid-addicted individuals and matched controls with no history of illicit drug use were administered a probabilistic classification task that embeds both reward-based and punishment-based learning trials, and a computational model of decision making was applied to understand the mechanisms describing individuals’ performance on the task. Although behavioral results showed thatopioid-addicted individuals performed as well as controls on both reward- and punishment-based learning, the modeling results suggested subtle differences in how decisions were made between the two groups. Specifically, the opioid-addicted group showed decreased tendency to repeat prior responses, meaning that they were more likely to “chase reward” when expectancies were violated, whereas controls were more likely to stick with a previously-successful response rule, despite occasional expectancy violations. This tendency to chase short-term reward, potentially at the expense of developing rules that maximize reward over the long term, may be a contributing factor to opioid addiction. Further work is indicated to better understand whether this tendency arises as a result of brain changes in the wake of continued opioid use/abuse, or might be a pre-existing factor that may contribute to risk for addiction. PMID:26381438

  11. A role of decision-making competency in science learning utilizing a social valuation framework

    NASA Astrophysics Data System (ADS)

    Katsuo, Akihito

    2005-11-01

    The role of decision-making in learning performance has been an occasional topic in the research literature in science education, but rarely has it been a central issue in the field. Nonetheless, recent studies regarding the topic in several fields other than education, such as cognitive neuroscience and social choice theory, indicate the fundamental importance(s) of the topic. This study focuses on a possible role of decision-making in science learning. Initially the study was designed to probe the decision-making ability of elementary school children with a modified version of the Iowa Gambling Task (IGT). The experiment involved six Montessori 3rd and 4th grade students as the experimental group and eight public school 3rd and 4th grade students as the control group. The result of the modified IGT revealed a tendency in choice trajectories favoring children at the Montessori school. However, the probabilistic value went below the statistically significant level set by the U test. A further study focused on the impact of better decision-making ability revealed in the first experiment on performances with a science learning module that emphasized collective reasoning. The instruction was based on a set of worksheets with multiple choices on which students were asked to make predictions with and to provide supportive arguments regarding outcomes of experiments introduced in the worksheet. Then the whole class was involved with a real experiment to see which choice was correct. The findings in the study indicated that the Montessori students often obtained higher scores than non-Montessori students in making decision with a tendency of consistency in terms of their choices of the alternatives on the worksheets. The findings of the experiments were supported by a correlational analysis that was performed at the end of study. Although no statistically significant correlations were found, there was a tendency for positively associative shifts between the scores of the modified IGT and the scores for the performances on the science module for the Montessori students.

  12. Reasoning, learning, and creativity: frontal lobe function and human decision-making.

    PubMed

    Collins, Anne; Koechlin, Etienne

    2012-01-01

    The frontal lobes subserve decision-making and executive control--that is, the selection and coordination of goal-directed behaviors. Current models of frontal executive function, however, do not explain human decision-making in everyday environments featuring uncertain, changing, and especially open-ended situations. Here, we propose a computational model of human executive function that clarifies this issue. Using behavioral experiments, we show that unlike others, the proposed model predicts human decisions and their variations across individuals in naturalistic situations. The model reveals that for driving action, the human frontal function monitors up to three/four concurrent behavioral strategies and infers online their ability to predict action outcomes: whenever one appears more reliable than unreliable, this strategy is chosen to guide the selection and learning of actions that maximize rewards. Otherwise, a new behavioral strategy is tentatively formed, partly from those stored in long-term memory, then probed, and if competitive confirmed to subsequently drive action. Thus, the human executive function has a monitoring capacity limited to three or four behavioral strategies. This limitation is compensated by the binary structure of executive control that in ambiguous and unknown situations promotes the exploration and creation of new behavioral strategies. The results support a model of human frontal function that integrates reasoning, learning, and creative abilities in the service of decision-making and adaptive behavior.

  13. Bayesian deterministic decision making: a normative account of the operant matching law and heavy-tailed reward history dependency of choices.

    PubMed

    Saito, Hiroshi; Katahira, Kentaro; Okanoya, Kazuo; Okada, Masato

    2014-01-01

    The decision making behaviors of humans and animals adapt and then satisfy an "operant matching law" in certain type of tasks. This was first pointed out by Herrnstein in his foraging experiments on pigeons. The matching law has been one landmark for elucidating the underlying processes of decision making and its learning in the brain. An interesting question is whether decisions are made deterministically or probabilistically. Conventional learning models of the matching law are based on the latter idea; they assume that subjects learn choice probabilities of respective alternatives and decide stochastically with the probabilities. However, it is unknown whether the matching law can be accounted for by a deterministic strategy or not. To answer this question, we propose several deterministic Bayesian decision making models that have certain incorrect beliefs about an environment. We claim that a simple model produces behavior satisfying the matching law in static settings of a foraging task but not in dynamic settings. We found that the model that has a belief that the environment is volatile works well in the dynamic foraging task and exhibits undermatching, which is a slight deviation from the matching law observed in many experiments. This model also demonstrates the double-exponential reward history dependency of a choice and a heavier-tailed run-length distribution, as has recently been reported in experiments on monkeys.

  14. Reasoning, Learning, and Creativity: Frontal Lobe Function and Human Decision-Making

    PubMed Central

    Collins, Anne; Koechlin, Etienne

    2012-01-01

    The frontal lobes subserve decision-making and executive control—that is, the selection and coordination of goal-directed behaviors. Current models of frontal executive function, however, do not explain human decision-making in everyday environments featuring uncertain, changing, and especially open-ended situations. Here, we propose a computational model of human executive function that clarifies this issue. Using behavioral experiments, we show that unlike others, the proposed model predicts human decisions and their variations across individuals in naturalistic situations. The model reveals that for driving action, the human frontal function monitors up to three/four concurrent behavioral strategies and infers online their ability to predict action outcomes: whenever one appears more reliable than unreliable, this strategy is chosen to guide the selection and learning of actions that maximize rewards. Otherwise, a new behavioral strategy is tentatively formed, partly from those stored in long-term memory, then probed, and if competitive confirmed to subsequently drive action. Thus, the human executive function has a monitoring capacity limited to three or four behavioral strategies. This limitation is compensated by the binary structure of executive control that in ambiguous and unknown situations promotes the exploration and creation of new behavioral strategies. The results support a model of human frontal function that integrates reasoning, learning, and creative abilities in the service of decision-making and adaptive behavior. PMID:22479152

  15. Preparing Students for the Future: Making Career Development a Priority.

    ERIC Educational Resources Information Center

    Hughey, Kenneth F.; Hughey, Judith K.

    1999-01-01

    Presents information relevant to school counseling about the implications of work changes. Outlines foundational guides for student success: improving decision making, learning about career paths, acquiring employability skills, and developing lifelong learning attitudes. Describes activities to facilitate career development. (SK)

  16. Relevance Judging, Evaluation, and Decision Making in Virtual Libraries: A Descriptive Study.

    ERIC Educational Resources Information Center

    Fitzgerald, Mary Ann; Galloway, Chad

    2001-01-01

    Describes a study that investigated the cognitive processes undergraduates used to select information while using a virtual library, GALILEO (Georgia Library Learning Online). Discusses higher order thinking processes, relevance judging, evaluation (critical thinking), decision making, reasoning involving documents, relevance-related reasoning,…

  17. Deep brain stimulation of the subthalamic nucleus modulates sensitivity to decision outcome value in Parkinson’s disease

    NASA Astrophysics Data System (ADS)

    Seymour, Ben; Barbe, Michael; Dayan, Peter; Shiner, Tamara; Dolan, Ray; Fink, Gereon R.

    2016-09-01

    Deep brain stimulation (DBS) of the subthalamic nucleus in Parkinson’s disease is known to cause a subtle but important adverse impact on behaviour, with impulsivity its most widely reported manifestation. However, precisely which computational components of the decision process are modulated is not fully understood. Here we probe a number of distinct subprocesses, including temporal discount, outcome utility, instrumental learning rate, instrumental outcome sensitivity, reward-loss trade-offs, and perseveration. We tested 22 Parkinson’s Disease patients both on and off subthalamic nucleus deep brain stimulation (STN-DBS), while they performed an instrumental learning task involving financial rewards and losses, and an inter-temporal choice task for financial rewards. We found that instrumental learning performance was significantly worse following stimulation, due to modulation of instrumental outcome sensitivity. Specifically, patients became less sensitive to decision values for both rewards and losses, but without any change to the learning rate or reward-loss trade-offs. However, we found no evidence that DBS modulated different components of temporal impulsivity. In conclusion, our results implicate the subthalamic nucleus in a modulation of outcome value in experience-based learning and decision-making in Parkinson’s disease, suggesting a more pervasive role of the subthalamic nucleus in the control of human decision-making than previously thought.

  18. Deep brain stimulation of the subthalamic nucleus modulates sensitivity to decision outcome value in Parkinson’s disease

    PubMed Central

    Seymour, Ben; Barbe, Michael; Dayan, Peter; Shiner, Tamara; Dolan, Ray; Fink, Gereon R.

    2016-01-01

    Deep brain stimulation (DBS) of the subthalamic nucleus in Parkinson’s disease is known to cause a subtle but important adverse impact on behaviour, with impulsivity its most widely reported manifestation. However, precisely which computational components of the decision process are modulated is not fully understood. Here we probe a number of distinct subprocesses, including temporal discount, outcome utility, instrumental learning rate, instrumental outcome sensitivity, reward-loss trade-offs, and perseveration. We tested 22 Parkinson’s Disease patients both on and off subthalamic nucleus deep brain stimulation (STN-DBS), while they performed an instrumental learning task involving financial rewards and losses, and an inter-temporal choice task for financial rewards. We found that instrumental learning performance was significantly worse following stimulation, due to modulation of instrumental outcome sensitivity. Specifically, patients became less sensitive to decision values for both rewards and losses, but without any change to the learning rate or reward-loss trade-offs. However, we found no evidence that DBS modulated different components of temporal impulsivity. In conclusion, our results implicate the subthalamic nucleus in a modulation of outcome value in experience-based learning and decision-making in Parkinson’s disease, suggesting a more pervasive role of the subthalamic nucleus in the control of human decision-making than previously thought. PMID:27624437

  19. HUMAN DECISIONS AND MACHINE PREDICTIONS.

    PubMed

    Kleinberg, Jon; Lakkaraju, Himabindu; Leskovec, Jure; Ludwig, Jens; Mullainathan, Sendhil

    2018-02-01

    Can machine learning improve human decision making? Bail decisions provide a good test case. Millions of times each year, judges make jail-or-release decisions that hinge on a prediction of what a defendant would do if released. The concreteness of the prediction task combined with the volume of data available makes this a promising machine-learning application. Yet comparing the algorithm to judges proves complicated. First, the available data are generated by prior judge decisions. We only observe crime outcomes for released defendants, not for those judges detained. This makes it hard to evaluate counterfactual decision rules based on algorithmic predictions. Second, judges may have a broader set of preferences than the variable the algorithm predicts; for instance, judges may care specifically about violent crimes or about racial inequities. We deal with these problems using different econometric strategies, such as quasi-random assignment of cases to judges. Even accounting for these concerns, our results suggest potentially large welfare gains: one policy simulation shows crime reductions up to 24.7% with no change in jailing rates, or jailing rate reductions up to 41.9% with no increase in crime rates. Moreover, all categories of crime, including violent crimes, show reductions; and these gains can be achieved while simultaneously reducing racial disparities. These results suggest that while machine learning can be valuable, realizing this value requires integrating these tools into an economic framework: being clear about the link between predictions and decisions; specifying the scope of payoff functions; and constructing unbiased decision counterfactuals. JEL Codes: C10 (Econometric and statistical methods and methodology), C55 (Large datasets: Modeling and analysis), K40 (Legal procedure, the legal system, and illegal behavior).

  20. HUMAN DECISIONS AND MACHINE PREDICTIONS*

    PubMed Central

    Kleinberg, Jon; Lakkaraju, Himabindu; Leskovec, Jure; Ludwig, Jens; Mullainathan, Sendhil

    2018-01-01

    Can machine learning improve human decision making? Bail decisions provide a good test case. Millions of times each year, judges make jail-or-release decisions that hinge on a prediction of what a defendant would do if released. The concreteness of the prediction task combined with the volume of data available makes this a promising machine-learning application. Yet comparing the algorithm to judges proves complicated. First, the available data are generated by prior judge decisions. We only observe crime outcomes for released defendants, not for those judges detained. This makes it hard to evaluate counterfactual decision rules based on algorithmic predictions. Second, judges may have a broader set of preferences than the variable the algorithm predicts; for instance, judges may care specifically about violent crimes or about racial inequities. We deal with these problems using different econometric strategies, such as quasi-random assignment of cases to judges. Even accounting for these concerns, our results suggest potentially large welfare gains: one policy simulation shows crime reductions up to 24.7% with no change in jailing rates, or jailing rate reductions up to 41.9% with no increase in crime rates. Moreover, all categories of crime, including violent crimes, show reductions; and these gains can be achieved while simultaneously reducing racial disparities. These results suggest that while machine learning can be valuable, realizing this value requires integrating these tools into an economic framework: being clear about the link between predictions and decisions; specifying the scope of payoff functions; and constructing unbiased decision counterfactuals. JEL Codes: C10 (Econometric and statistical methods and methodology), C55 (Large datasets: Modeling and analysis), K40 (Legal procedure, the legal system, and illegal behavior) PMID:29755141

  1. Decision-making in the adolescent brain.

    PubMed

    Blakemore, Sarah-Jayne; Robbins, Trevor W

    2012-09-01

    Adolescence is characterized by making risky decisions. Early lesion and neuroimaging studies in adults pointed to the ventromedial prefrontal cortex and related structures as having a key role in decision-making. More recent studies have fractionated decision-making processes into its various components, including the representation of value, response selection (including inter-temporal choice and cognitive control), associative learning, and affective and social aspects. These different aspects of decision-making have been the focus of investigation in recent studies of the adolescent brain. Evidence points to a dissociation between the relatively slow, linear development of impulse control and response inhibition during adolescence versus the nonlinear development of the reward system, which is often hyper-responsive to rewards in adolescence. This suggests that decision-making in adolescence may be particularly modulated by emotion and social factors, for example, when adolescents are with peers or in other affective ('hot') contexts.

  2. Shared Decision-Making and Patient Empowerment in Preventive Cardiology.

    PubMed

    Kambhampati, Swetha; Ashvetiya, Tamara; Stone, Neil J; Blumenthal, Roger S; Martin, Seth S

    2016-05-01

    Shared decision-making, central to evidence-based medicine and good patient care, begins and ends with the patient. It is the process by which a clinician and a patient jointly make a health decision after discussing options, potential benefits and harms, and considering the patient's values and preferences. Patient empowerment is crucial to shared decision-making and occurs when a patient accepts responsibility for his or her health. They can then learn to solve their own problems with information and support from professionals. Patient empowerment begins with the provider acknowledging that patients are ultimately in control of their care and aims to increase a patient's capacity to think critically and make autonomous, informed decisions about their health. This article explores the various components of shared decision-making in scenarios such as hypertension and hyperlipidemia, heart failure, and diabetes. It explores barriers and the potential for improving medication adherence, disease awareness, and self-management of chronic disease.

  3. Substitute decision-making for adults with intellectual disabilities living in residential care: learning through experience.

    PubMed

    Dunn, Michael C; Clare, Isabel C H; Holland, Anthony J

    2008-03-01

    In the UK, current policies and services for people with mental disorders, including those with intellectual disabilities (ID), presume that these men and women can, do, and should, make decisions for themselves. The new Mental Capacity Act (England and Wales) 2005 (MCA) sets this presumption into statute, and codifies how decisions relating to health and welfare should be made for those adults judged unable to make one or more such decisions autonomously. The MCA uses a procedural checklist to guide this process of substitute decision-making. The personal experiences of providing direct support to seven men and women with ID living in residential care, however, showed that substitute decision-making took two forms, depending on the type of decision to be made. The first process, 'strategic substitute decision-making', paralleled the MCA's legal and ethical framework, whilst the second process, 'relational substitute decision-making', was markedly different from these statutory procedures. In this setting, 'relational substitute decision-making' underpinned everyday personal and social interventions connected with residents' daily living, and was situated within a framework of interpersonal and interdependent care relationships. The implications of these findings for residential services and the implementation of the MCA are discussed.

  4. Neural Basis of Strategic Decision Making

    PubMed Central

    Lee, Daeyeol; Seo, Hyojung

    2015-01-01

    Human choice behaviors during social interactions often deviate from the predictions of game theory. This might arise partly from the limitations in cognitive abilities necessary for recursive reasoning about the behaviors of others. In addition, during iterative social interactions, choices might change dynamically, as knowledge about the intentions of others and estimates for choice outcomes are incrementally updated via reinforcement learning. Some of the brain circuits utilized during social decision making might be general-purpose and contribute to isomorphic individual and social decision making. By contrast, regions in the medial prefrontal cortex and temporal parietal junction might be recruited for cognitive processes unique to social decision making. PMID:26688301

  5. Ventral anterior cingulate cortex and social decision-making.

    PubMed

    Lockwood, Patricia L; Wittmann, Marco K

    2018-06-07

    Studies in the field of social neuroscience have recently made use of computational models of decision-making to provide new insights into how we learn about the self and others during social interactions. Importantly, these studies have increasingly drawn attention to brain areas outside of classical cortical "social brain" regions that may be critical for social processing. In particular, two portions of the ventral anterior cingulate cortex (vACC), subgenual anterior cingulate cortex and perigenual anterior cingulate cortex, have been linked to social and self learning signals, respectively. Here we discuss the emerging parallels between these studies. Uncovering the function of vACC during social interactions could provide important new avenues to understand social decision-making in health and disease. Copyright © 2018 Elsevier Ltd. All rights reserved.

  6. Michael Faraday on the Learning of Science and Attitudes of Mind.

    ERIC Educational Resources Information Center

    Crawford, Elspeth

    1998-01-01

    Makes use of Michael Faraday's ideas on learning, focusing on his attitudes toward the unknowns of science and the development of an attitude that improves scientific decision making. This approach acknowledges that there is an inner struggle involved in facing unknowns. (DDR)

  7. Educating patients: understanding barriers, learning styles, and teaching techniques.

    PubMed

    Beagley, Linda

    2011-10-01

    Health care delivery and education has become a challenge for providers. Nurses and other professionals are challenged daily to assure that the patient has the necessary information to make informed decisions. Patients and their families are given a multitude of information about their health and commonly must make important decisions from these facts. Obstacles that prevent easy delivery of health care information include literacy, culture, language, and physiological barriers. It is up to the nurse to assess and evaluate the patient's learning needs and readiness to learn because everyone learns differently. This article will examine how each of these barriers impact care delivery along with teaching and learning strategies will be examined. Copyright © 2011 American Society of PeriAnesthesia Nurses. Published by Elsevier Inc. All rights reserved.

  8. Reinforcement Learning for Weakly-Coupled MDPs and an Application to Planetary Rover Control

    NASA Technical Reports Server (NTRS)

    Bernstein, Daniel S.; Zilberstein, Shlomo

    2003-01-01

    Weakly-coupled Markov decision processes can be decomposed into subprocesses that interact only through a small set of bottleneck states. We study a hierarchical reinforcement learning algorithm designed to take advantage of this particular type of decomposability. To test our algorithm, we use a decision-making problem faced by autonomous planetary rovers. In this problem, a Mars rover must decide which activities to perform and when to traverse between science sites in order to make the best use of its limited resources. In our experiments, the hierarchical algorithm performs better than Q-learning in the early stages of learning, but unlike Q-learning it converges to a suboptimal policy. This suggests that it may be advantageous to use the hierarchical algorithm when training time is limited.

  9. Meta-Analytic Evidence for a Reversal Learning Effect on the Iowa Gambling Task in Older Adults

    PubMed Central

    Pasion, Rita; Gonçalves, Ana R.; Fernandes, Carina; Ferreira-Santos, Fernando; Barbosa, Fernando; Marques-Teixeira, João

    2017-01-01

    Iowa Gambling Task (IGT) is one of the most widely used tools to assess economic decision-making. However, the research tradition on aging and the Iowa Gambling Task (IGT) has been mainly focused on the overall performance of older adults in relation to younger or clinical groups, remaining unclear whether older adults are capable of learning along the task. We conducted a meta-analysis to examine older adults' decision-making on the IGT, to test the effects of aging on reversal learning (45 studies) and to provide normative data on total and block net scores (55 studies). From the accumulated empirical evidence, we found an average total net score of 7.55 (±25.9). We also observed a significant reversal learning effect along the blocks of the IGT, indicating that older adults inhibit the prepotent response toward immediately attractive options associated with high losses, in favor of initially less attractive options associated with long-run profit. During block 1, decisions of older adults led to a negative gambling net score, reflecting the expected initial pattern of risk-taking. However, the shift toward more safe options occurred between block 2 (small-to-medium effect size) and blocks 3, 4, 5 (medium-to-large effect size). These main findings highlight that older adults are able to move from the initial uncertainty, when the possible outcomes are unknown, to decisions based on risk, when the outcomes are learned and may be used to guide future adaptive decision-making. PMID:29075222

  10. Developing an Ethical Framework in Decision Making of Rural Elementary School Principals in Pennsylvania

    ERIC Educational Resources Information Center

    Hozien, Wafa Ismail

    2012-01-01

    The purpose of this study is to explore and describe individual Pennsylvania rural elementary principals' experiences of ethical decision-making in a complex era. Ethical dilemma, in this case, is the term used to depict an incident which calls for a decision to be made when moral values or ethical principles were in conflict. Also, to learn how…

  11. "I Think We Should Take This Offline...": Conversational Patterns that Undermine Effective Decision Making in Action Learning Sets

    ERIC Educational Resources Information Center

    Donovan, Paul

    2011-01-01

    Collective decision making is an increasing requirement in organizations where the emphasis is on team work at every level. It is, however, very complex and difficult to achieve in practice. Too frequently, important discussions are bypassed or, while the majority of the meeting participants remain mute, decisions are being made by a vocal few. In…

  12. The role of analogy-guided learning experiences in enhancing students' clinical decision-making skills.

    PubMed

    Edelen, Bonnie Gilbert; Bell, Alexandra Alice

    2011-08-01

    The purpose of this study was to address the need for effective educational interventions to promote students' clinical decision making (CDM) within clinical practice environments. Researchers used a quasi-experimental, non-equivalent groups, posttest-only design to assess differences in CDM ability between intervention group students who participated in analogy-guided learning activities and control group students who participated in traditional activities. For the intervention, analogy-guided learning activities were incorporated into weekly group discussions, reflective journal writing, and questioning with clinical faculty. The researcher-designed Assessment of Clinical Decision Making Rubric was used to assess indicators of CDM ability in all students' reflective journal entries. Results indicated that the intervention group demonstrated significantly higher levels of CDM ability in their journals compared with the control group (ES(sm) = 0.52). Recommendations provide nurse educators with strategies to maximize students' development of CDM ability, better preparing students for the demands they face when they enter the profession. Copyright 2011, SLACK Incorporated.

  13. Sharpened cortical tuning and enhanced cortico-cortical communication contribute to the long-term neural mechanisms of visual motion perceptual learning.

    PubMed

    Chen, Nihong; Bi, Taiyong; Zhou, Tiangang; Li, Sheng; Liu, Zili; Fang, Fang

    2015-07-15

    Much has been debated about whether the neural plasticity mediating perceptual learning takes place at the sensory or decision-making stage in the brain. To investigate this, we trained human subjects in a visual motion direction discrimination task. Behavioral performance and BOLD signals were measured before, immediately after, and two weeks after training. Parallel to subjects' long-lasting behavioral improvement, the neural selectivity in V3A and the effective connectivity from V3A to IPS (intraparietal sulcus, a motion decision-making area) exhibited a persistent increase for the trained direction. Moreover, the improvement was well explained by a linear combination of the selectivity and connectivity increases. These findings suggest that the long-term neural mechanisms of motion perceptual learning are implemented by sharpening cortical tuning to trained stimuli at the sensory processing stage, as well as by optimizing the connections between sensory and decision-making areas in the brain. Copyright © 2015 Elsevier Inc. All rights reserved.

  14. The neural representation of unexpected uncertainty during value-based decision making.

    PubMed

    Payzan-LeNestour, Elise; Dunne, Simon; Bossaerts, Peter; O'Doherty, John P

    2013-07-10

    Uncertainty is an inherent property of the environment and a central feature of models of decision-making and learning. Theoretical propositions suggest that one form, unexpected uncertainty, may be used to rapidly adapt to changes in the environment, while being influenced by two other forms: risk and estimation uncertainty. While previous studies have reported neural representations of estimation uncertainty and risk, relatively little is known about unexpected uncertainty. Here, participants performed a decision-making task while undergoing functional magnetic resonance imaging (fMRI), which, in combination with a Bayesian model-based analysis, enabled us to separately examine each form of uncertainty examined. We found representations of unexpected uncertainty in multiple cortical areas, as well as the noradrenergic brainstem nucleus locus coeruleus. Other unique cortical regions were found to encode risk, estimation uncertainty, and learning rate. Collectively, these findings support theoretical models in which several formally separable uncertainty computations determine the speed of learning. Copyright © 2013 Elsevier Inc. All rights reserved.

  15. Expanding the Union Contract: One Teacher's Perspective.

    ERIC Educational Resources Information Center

    Tuthill, Doug

    1990-01-01

    The National Education Association's approach to improving public education is founded on John Dewey's vision of democratic schooling and rational decision making, as the experience of Pinellas County, Florida, shows. This article describes the district's efforts to implement the Mastery in Learning project, a shared decision-making model.…

  16. Peer Coaching: Principals Learning from Principals. Pairing Novice and Experienced Principals Provides Both with Opportunities To Promote Reflective Thinking In Their Decision-Making

    ERIC Educational Resources Information Center

    Rich, Robert A.; Jackson, Sherion H.

    2005-01-01

    Unlike mentoring relationships, peer coaching is a voluntary partnership that uses reflections of past experiences to influence decision-making. The authors provide a step-by-step guide for establishing and maintaining peer-coaching partnerships.

  17. Conflict Management and Decision Making. Symposium.

    ERIC Educational Resources Information Center

    2002

    This symposium on conflict management and decision making is comprised of three papers. "Two Approaches to Conflict Management in Teams: A Case Study" (Mychal Coleman, Gary N. McLean) describes a study that provided conflict management training to two employee teams using the traditional lecture method and cooperative learning (CL).…

  18. Personal Decision Making. Focus on Economics.

    ERIC Educational Resources Information Center

    Leet, Don R.; Charkins, R. J.; Lang, Nancy A.; Lopus, Jane S.; Tamaribuchi, Gail

    This book highlights and examines basic economic concepts as they relate to consumer, business, social, and personal choices. Students are shown connections between their classroom learning and their real-world experiences in budgeting, career planning, credit management, and housing. The set of 15 lessons include: (1) "Decision Making: Scarcity,…

  19. Decision-Making Skills and Vocational Maturity Among Adolescents.

    ERIC Educational Resources Information Center

    Lokan, Janice J.; Trebilco, Geoffrey R.

    The learning of decision-making (DM) skills and appropriate attitudes is an important objective of career education. This study provides an empirical test of theoretical links between aspects of DM styles and vocational maturity (VM) in adolescence. Approximately 260 Australian students in grades ten and twelve answered questionnaires measuring…

  20. Leadership Decision Making and the Use of Data

    ERIC Educational Resources Information Center

    Guerra-Lopez, Ingrid; Blake, Anne M.

    2011-01-01

    Intelligence gathering, or data collection, is a preliminary and critical stage of decision making. Two key approaches to intelligence gathering are "discovery" and "idea imposition." The discovery approach allows us to learn about possibilities by gathering intelligence in order to identify and weigh options. The idea imposition approach limits…

  1. Training Volunteers in Community Education: A Manual for Staff Members in Community Decision-Making Settings.

    ERIC Educational Resources Information Center

    Slotnik, William J.; And Others

    Methods for encouraging community involvement and training community volunteers for decision making positions in community schools are described. The functions of community schools are to provide a broad diversity of learning opportunities and to involve citizens in assessing community needs, evaluating services, and advocating…

  2. Group Participation and Satisfaction: Results from a PBL Computer-Supported Module

    ERIC Educational Resources Information Center

    Ochoa, Theresa A.; Gottschall, Holly; Stuart, Shannon K.

    2004-01-01

    Special education policy requires schools to make disciplinary decisions concerning students with disabilities within a multidisciplinary team. In order to respond to this mandate, teacher educators must ensure that teachers have group collaboration and decision making skills. This article describes a multimedia problem-based learning module…

  3. Demonstrating Empathy: A Phenomenological Study of Instructional Designers Making Instructional Strategy Decisions for Adult Learners

    ERIC Educational Resources Information Center

    Vann, Linda S.

    2017-01-01

    Instructional designers are tasked with making instructional strategy decisions to facilitate achievement of learning outcomes as part of their professional responsibilities. While the instructional design process includes learner analysis, that analysis alone does not embody opportunities to assist instructional designers with demonstrations of…

  4. Learner Autonomy in a Task-Based 3D World and Production

    ERIC Educational Resources Information Center

    Collentine, Karina

    2011-01-01

    This study contributes to the research on learner autonomy by examining the relationship between Little's (1991) notions of "independent action" and "decision-making", input, and L2 production in computer-assisted language learning (CALL). Operationalizing "independent action" and "decision-making" with Dam's (1995) definition that focuses on…

  5. Pilot Decision-Making in Irreversible Emergencies

    ERIC Educational Resources Information Center

    Winter, Scott R.

    2013-01-01

    The purpose of this study was to determine if a reflexive learning treatment utilizing select case studies could enhance the decision-making of pilots who encounter an irreversible emergency. Participants, who consisted of members of the subject university's professional pilot program, were divided into either a control or experimental group and…

  6. Computer-Assisted Community Planning and Decision Making.

    ERIC Educational Resources Information Center

    College of the Atlantic, Bar Harbor, ME.

    The College of the Atlantic (COA) developed a broad-based, interdisciplinary curriculum in ecological policy and community planning and decision-making that incorporates two primary computer-based tools: ARC/INFO Geographic Information System (GIS) and STELLA, a systems-dynamics modeling tool. Students learn how to use and apply these tools…

  7. Using Data-Based Inquiry and Decision Making To Improve Instruction.

    ERIC Educational Resources Information Center

    Feldman, Jay; Tung, Rosann

    2001-01-01

    Discusses a study of six schools using data-based inquiry and decision-making process to improve instruction. Findings identified two conditions to support successful implementation of the process: administrative support, especially in providing teachers learning time, and teacher leadership to encourage and support colleagues to own the process.…

  8. Setting Proficiency Standards for School Leadership Assessment: An Examination of Cut Score Decision Making

    ERIC Educational Resources Information Center

    Cravens, Xiu Chen; Goldring, Ellen B.; Porter, Andrew C.; Polikoff, Morgan S.; Murphy, Joseph; Elliott, Stephen N.

    2013-01-01

    Purpose: Performance evaluation informs professional development and helps school personnel improve student learning. Although psychometric literature indicates that a rational, sound, and coherent standard-setting process adds to the credibility of an assessment, few studies have empirically examined the decision-making process. This article…

  9. Data-based Decision-making: Teachers' Comprehension of Curriculum-based Measurement Progress-monitoring Graphs

    ERIC Educational Resources Information Center

    van den Bosch, Roxette M.; Espin, Christine A.; Chung, Siuman; Saab, Nadira

    2017-01-01

    Teachers have difficulty using data from Curriculum-based Measurement (CBM) progress graphs of students with learning difficulties for instructional decision-making. As a first step in unraveling those difficulties, we studied teachers' comprehension of CBM graphs. Using think-aloud methodology, we examined 23 teachers' ability to…

  10. Understanding Decision Making in Teachers' Curriculum Design Approaches

    ERIC Educational Resources Information Center

    Boschman, Ferry; McKenney, Susan; Voogt, Joke

    2014-01-01

    The goal of this study was to reach a better understanding of the intuitive decisions teachers make when designing a technology-rich learning environment. A multiple case-study design was employed to examine what kinds of factors (external priorities, existing orientations or practical concerns) influence design interactions of teams of…

  11. Socio-Scientific Decision Making in the Science Classroom

    ERIC Educational Resources Information Center

    Siribunnam, Siripun; Nuangchalerm, Prasart; Jansawang, Natchanok

    2014-01-01

    The learning ability of students in science is improved by socio-scientific decision-making, an important activity that improves a student's scientific literacy, conceptual understanding, scientific inquiry, attitudes, and social values. The socio-scientific issues must be discussed during science classroom activities in the current state of 21st…

  12. Spatial education: improving conservation delivery through space-structured decision making

    USGS Publications Warehouse

    Moore, Clinton T.; Shaffer, Terry L.; Gannon, Jill J.

    2013-01-01

    Adaptive management is a form of structured decision making designed to guide management of natural resource systems when their behaviors are uncertain. Where decision making can be replicated across units of a landscape, learning can be accelerated, and biological processes can be understood in a larger spatial context. Broad-based partnerships among land management agencies, exemplified by Landscape Conservation Cooperatives (conservation partnerships created through the U.S. Department of the Interior), are potentially ideal environments for implementing spatially structured adaptive management programs.

  13. Mice learn to avoid regret.

    PubMed

    Sweis, Brian M; Thomas, Mark J; Redish, A David

    2018-06-01

    Regret can be defined as the subjective experience of recognizing that one has made a mistake and that a better alternative could have been selected. The experience of regret is thought to carry negative utility. This typically takes two distinct forms: augmenting immediate postregret valuations to make up for losses, and augmenting long-term changes in decision-making strategies to avoid future instances of regret altogether. While the short-term changes in valuation have been studied in human psychology, economics, neuroscience, and even recently in nonhuman-primate and rodent neurophysiology, the latter long-term process has received far less attention, with no reports of regret avoidance in nonhuman decision-making paradigms. We trained 31 mice in a novel variant of the Restaurant Row economic decision-making task, in which mice make decisions of whether to spend time from a limited budget to achieve food rewards of varying costs (delays). Importantly, we tested mice longitudinally for 70 consecutive days, during which the task provided their only source of food. Thus, decision strategies were interdependent across both trials and days. We separated principal commitment decisions from secondary reevaluation decisions across space and time and found evidence for regret-like behaviors following change-of-mind decisions that corrected prior economically disadvantageous choices. Immediately following change-of-mind events, subsequent decisions appeared to make up for lost effort by altering willingness to wait, decision speed, and pellet consumption speed, consistent with past reports of regret in rodents. As mice were exposed to an increasingly reward-scarce environment, we found they adapted and refined distinct economic decision-making strategies over the course of weeks to maximize reinforcement rate. However, we also found that even without changes in reinforcement rate, mice transitioned from an early strategy rooted in foraging to a strategy rooted in deliberation and planning that prevented future regret-inducing change-of-mind episodes from occurring. These data suggest that mice are learning to avoid future regret, independent of and separate from reinforcement rate maximization.

  14. Evaluating a mobile application for improving clinical laboratory test ordering and diagnosis.

    PubMed

    Meyer, Ashley N D; Thompson, Pamela J; Khanna, Arushi; Desai, Samir; Mathews, Benji K; Yousef, Elham; Kusnoor, Anita V; Singh, Hardeep

    2018-04-20

    Mobile applications for improving diagnostic decision making often lack clinical evaluation. We evaluated if a mobile application improves generalist physicians' appropriate laboratory test ordering and diagnosis decisions and assessed if physicians perceive it as useful for learning. In an experimental, vignette study, physicians diagnosed 8 patient vignettes with normal prothrombin times (PT) and abnormal partial thromboplastin times (PTT). Physicians made test ordering and diagnosis decisions for 4 vignettes using each resource: a mobile app, PTT Advisor, developed by the Centers for Disease Control and Prevention (CDC)'s Clinical Laboratory Integration into Healthcare Collaborative (CLIHC); and usual clinical decision support. Then, physicians answered questions regarding their perceptions of the app's usefulness for diagnostic decision making and learning using a modified Kirkpatrick Training Evaluation Framework. Data from 368 vignettes solved by 46 physicians at 7 US health care institutions show advantages for using PTT Advisor over usual clinical decision support on test ordering and diagnostic decision accuracy (82.6 vs 70.2% correct; P < .001), confidence in decisions (7.5 vs 6.3 out of 10; P < .001), and vignette completion time (3:02 vs 3:53 min.; P = .06). Physicians reported positive perceptions of the app's potential for improved clinical decision making, and recommended it be used to address broader diagnostic challenges. A mobile app, PTT Advisor, may contribute to better test ordering and diagnosis, serve as a learning tool for diagnostic evaluation of certain clinical disorders, and improve patient outcomes. Similar methods could be useful for evaluating apps aimed at improving testing and diagnosis for other conditions.

  15. Decision Making under Ambiguity and Objective Risk in Higher Age - A Review on Cognitive and Emotional Contributions.

    PubMed

    Liebherr, Magnus; Schiebener, Johannes; Averbeck, Heike; Brand, Matthias

    2017-01-01

    The ability of decision making plays a highly relevant role in our survival, but is adversely affected during the process of aging. The present review aims to provide a better understanding of age-related differences in decision making and the role of cognitive and emotional factors in this context. We reviewed the literature about age-effects on decision-making performance, focusing on decision making under ambiguous and objective risk. In decisions under ambiguous risks, as measured by the Iowa Gambling Task, decisions are based on the experiences with consequences. In this case, many articles have attributed age-related impairments in decision making to changes in emotional and somatic reward- and punishment processing. In decisions under objective risks, as measured for example by the Game of Dice Task, decisions can be based on explicit information about risks and consequences. In this case, age-related changes have been attributed mainly to a cognitive decline, particularly impaired executive functions. However, recent findings challenge these conclusions. The present review summarizes neuropsychological and neurophysiological findings of age-related differences in decision making under ambiguous and objective risk. In this context, the relevance of learning, but also of cognitive and emotional contributors - responsible for age-related differences in decision making - are additionally pointed out.

  16. Decision Making under Ambiguity and Objective Risk in Higher Age – A Review on Cognitive and Emotional Contributions

    PubMed Central

    Liebherr, Magnus; Schiebener, Johannes; Averbeck, Heike; Brand, Matthias

    2017-01-01

    The ability of decision making plays a highly relevant role in our survival, but is adversely affected during the process of aging. The present review aims to provide a better understanding of age-related differences in decision making and the role of cognitive and emotional factors in this context. We reviewed the literature about age-effects on decision-making performance, focusing on decision making under ambiguous and objective risk. In decisions under ambiguous risks, as measured by the Iowa Gambling Task, decisions are based on the experiences with consequences. In this case, many articles have attributed age-related impairments in decision making to changes in emotional and somatic reward- and punishment processing. In decisions under objective risks, as measured for example by the Game of Dice Task, decisions can be based on explicit information about risks and consequences. In this case, age-related changes have been attributed mainly to a cognitive decline, particularly impaired executive functions. However, recent findings challenge these conclusions. The present review summarizes neuropsychological and neurophysiological findings of age-related differences in decision making under ambiguous and objective risk. In this context, the relevance of learning, but also of cognitive and emotional contributors – responsible for age-related differences in decision making – are additionally pointed out. PMID:29270145

  17. Multiple Criteria Evaluation of Quality and Optimisation of e-Learning System Components

    ERIC Educational Resources Information Center

    Kurilovas, Eugenijus; Dagiene, Valentina

    2010-01-01

    The main research object of the paper is investigation and proposal of the comprehensive Learning Object Repositories (LORs) quality evaluation tool suitable for their multiple criteria decision analysis, evaluation and optimisation. Both LORs "internal quality" and "quality in use" evaluation (decision making) criteria are analysed in the paper.…

  18. Innovation Need Survey: Implementing a Technology Tool to Improve Early Data-Based Decisions to Address and Prevent Learning Disabilities. Technical Report #1602

    ERIC Educational Resources Information Center

    Irvin, P. Shawn; Pilger, Marissa; Sáez, Leilani; Alonzo, Julie

    2016-01-01

    Identifying and measuring indicators of learning difficulties among young children and implementing effective instructional approaches are complicated, particularly during the transition to kindergarten. Purposeful school-based transition policies and practices support teacher and school decision-making and, thus, can ease the…

  19. An Innovative Spreadsheet Application to Teach Management Science Decision Criteria

    ERIC Educational Resources Information Center

    Hozak, Kurt

    2018-01-01

    This article describes a Microsoft Excel-based application that uses humorous voice synthesis and timed competition to make it more fun and engaging to learn management science decision criteria. In addition to providing immediate feedback and easily customizable tips that facilitate self-learning, the software randomly generates both the problem…

  20. Computer-Based Aids for Learning, Job Performance, and Decision Making in Military Applications: Emergent Technology and Challenges

    DTIC Science & Technology

    2003-10-01

    paper, which addresses the following questions: Is it worth it? What do we know about the value of technology applications in learning ( education and......fax) fletcher@ida.org SUMMARY Technology -based systems for education , training, and performance aiding (including decision aiding) may pose the

  1. Cognitive decision modelling of emotion-based learning impairment in schizophrenia: the role of awareness.

    PubMed

    Cella, Matteo; Dymond, Simon; Cooper, Andrew; Turnbull, Oliver H

    2012-03-30

    Individuals with schizophrenia often lack insight or awareness. Resulting impairment has been observed in various cognitive domains and, recently, linked to problems in emotion-based learning. The Iowa Gambling Task (IGT) has been used to assess emotion-based decision-making in patients with schizophrenia, but results have been inconclusive. The current study further investigates emotion-based decision-making in schizophrenia by elucidating the unique contribution of awareness. Twenty-five patients with schizophrenia and 24 healthy controls were assessed with a modified version of the IGT recording awareness at regular intervals. Symptom assessment, medication and medical history were recorded for the clinical group. Patients with schizophrenia underperformed on the IGT compared to controls. Subjective awareness levels were significantly lower in the schizophrenia group and were associated with hallucination severity. Cognitive decision modelling further indicated that patients with schizophrenia had impaired attention to losses, compared to controls. This parameter was positively correlated with awareness. We also found that positive symptoms altered awareness levels and suggest that this disruption may contribute to sub-optimal decision-making. Overall, a lack of awareness may be an important aspect in understanding impaired social cognitive functioning and emotion-based learning observed in schizophrenia. Copyright © 2011 Elsevier Ltd. All rights reserved.

  2. Medical students, clinical preventive services, and shared decision-making.

    PubMed

    Keefe, Carole W; Thompson, Margaret E; Noel, Mary Margaret

    2002-11-01

    Improving access to preventive care requires addressing patient, provider, and systems barriers. Patients often lack knowledge or are skeptical about the importance of prevention. Physicians feel that they have too little time, are not trained to deliver preventive services, and are concerned about the effectiveness of prevention. We have implemented an educational module in the required family practice clerkship (1) to enhance medical student learning about common clinical preventive services and (2) to teach students how to inform and involve patients in shared decision making about those services. Students are asked to examine available evidence-based information for preventive screening services. They are encouraged to look at the recommendations of various organizations and use such resources as reports from the U.S. Preventive Services Task Force to determine recommendations they want to be knowledgeable about in talking with their patients. For learning shared decision making, students are trained to use a model adapted from Braddock and colleagues(1) to discuss specific screening services and to engage patients in the process of making informed decisions about what is best for their own health. The shared decision making is presented and modeled by faculty, discussed in small groups, and students practice using Web-based cases and simulations. The students are evaluated using formative and summative performance-based assessments as they interact with simulated patients about (1) screening for high blood cholesterol and other lipid abnormalities, (2) screening for colorectal cancer, (3) screening for prostate cancer, and (4) screening for breast cancer. The final student evaluation is a ten-minute, videotaped discussion with a simulated patient about screening for colorectal cancer that is graded against a checklist that focuses primarily on the elements of shared decision making. Our medical students appear quite willing to accept shared decision making as a skill that they should have in working with patients, and this was the primary focus of the newly implemented module. However, we have learned that students need to deepen their understanding of screening services in order to help patients understand the associated benefits and risks. The final videotaped interaction with a simulated patient about colorectal cancer screening has been very helpful in making it more obvious to faculty what students believe and know about screening for colorectal cancer. As the students are asked to discuss clinical issues with patients and discuss the pros and cons of screening tests as part of the shared decision-making process, their thinking becomes transparent and it is evident where curricular changes and enhancements are required. We have found that an explicit model that allows students to demonstrate a process for shared decision making is a good introductory tool. We think it would be helpful to provide students with more formative feedback. We would like to develop faculty development programs around shared decision making so that more of our clinical faculty would model such a process with patients. Performance-based assessments are resource-intensive, but they appear to be worth the added effort in terms of enhanced skills development and a more comprehensive appraisal of student learning.

  3. Emotion and decision making.

    PubMed

    Lerner, Jennifer S; Li, Ye; Valdesolo, Piercarlo; Kassam, Karim S

    2015-01-03

    A revolution in the science of emotion has emerged in recent decades, with the potential to create a paradigm shift in decision theories. The research reveals that emotions constitute potent, pervasive, predictable, sometimes harmful and sometimes beneficial drivers of decision making. Across different domains, important regularities appear in the mechanisms through which emotions influence judgments and choices. We organize and analyze what has been learned from the past 35 years of work on emotion and decision making. In so doing, we propose the emotion-imbued choice model, which accounts for inputs from traditional rational choice theory and from newer emotion research, synthesizing scientific models.

  4. Believer-Skeptic Meets Actor-Critic: Rethinking the Role of Basal Ganglia Pathways during Decision-Making and Reinforcement Learning

    PubMed Central

    Dunovan, Kyle; Verstynen, Timothy

    2016-01-01

    The flexibility of behavioral control is a testament to the brain's capacity for dynamically resolving uncertainty during goal-directed actions. This ability to select actions and learn from immediate feedback is driven by the dynamics of basal ganglia (BG) pathways. A growing body of empirical evidence conflicts with the traditional view that these pathways act as independent levers for facilitating (i.e., direct pathway) or suppressing (i.e., indirect pathway) motor output, suggesting instead that they engage in a dynamic competition during action decisions that computationally captures action uncertainty. Here we discuss the utility of encoding action uncertainty as a dynamic competition between opposing control pathways and provide evidence that this simple mechanism may have powerful implications for bridging neurocomputational theories of decision making and reinforcement learning. PMID:27047328

  5. Believer-Skeptic Meets Actor-Critic: Rethinking the Role of Basal Ganglia Pathways during Decision-Making and Reinforcement Learning.

    PubMed

    Dunovan, Kyle; Verstynen, Timothy

    2016-01-01

    The flexibility of behavioral control is a testament to the brain's capacity for dynamically resolving uncertainty during goal-directed actions. This ability to select actions and learn from immediate feedback is driven by the dynamics of basal ganglia (BG) pathways. A growing body of empirical evidence conflicts with the traditional view that these pathways act as independent levers for facilitating (i.e., direct pathway) or suppressing (i.e., indirect pathway) motor output, suggesting instead that they engage in a dynamic competition during action decisions that computationally captures action uncertainty. Here we discuss the utility of encoding action uncertainty as a dynamic competition between opposing control pathways and provide evidence that this simple mechanism may have powerful implications for bridging neurocomputational theories of decision making and reinforcement learning.

  6. The involvement of the striatum in decision making

    PubMed Central

    Goulet-Kennedy, Julie; Labbe, Sara; Fecteau, Shirley

    2016-01-01

    Decision making has been extensively studied in the context of economics and from a group perspective, but still little is known on individual decision making. Here we discuss the different cognitive processes involved in decision making and its associated neural substrates. The putative conductors in decision making appear to be the prefrontal cortex and the striatum. Impaired decision-making skills in various clinical populations have been associated with activity in the prefrontal cortex and in the striatum. We highlight the importance of strengthening the degree of integration of both cognitive and neural substrates in order to further our understanding of decision-making skills. In terms of cognitive paradigms, there is a need to improve the ecological value of experimental tasks that assess decision making in various contexts and with rewards; this would help translate laboratory learnings into real-life benefits. In terms of neural substrates, the use of neuroimaging techniques helps characterize the neural networks associated with decision making; more recently, ways to modulate brain activity, such as in the prefrontal cortex and connected regions (eg, striatum), with noninvasive brain stimulation have also shed light on the neural and cognitive substrates of decision making. Together, these cognitive and neural approaches might be useful for patients with impaired decision-making skills. The drive behind this line of work is that decision-making abilities underlie important aspects of wellness, health, security, and financial and social choices in our daily lives. PMID:27069380

  7. Exposure to Unsolvable Anagrams Impairs Performance on the Iowa Gambling Task

    PubMed Central

    Starcke, Katrin; Agorku, Janet D.; Brand, Matthias

    2017-01-01

    Recent research indicates that external manipulations, such as stress or mood induction, can affect decision-making abilities. In the current study, we investigated whether the exposure to an unsolvable task affected subsequent performance on the Iowa Gambling Task. Participants were randomly assigned to a condition in which they were exposed to unsolvable anagrams (n = 20), or a condition in which they worked on solvable anagrams (n = 22). Afterwards, all participants played the Iowa Gambling Task, a prominent task that measures decision making under uncertain conditions with no explicit rules for gains and losses. In this task, it is essential to process feedback from previous decisions. The results demonstrated that participants who worked on unsolvable anagrams made more disadvantageous decisions on the Iowa Gambling Task than the other participants. In addition, a significant gender effect was observed: Males who worked on unsolvable anagrams made a more disadvantageous decisions than the other male participants. Females who worked on unsolvable anagrams also made more disadvantageous decision than the other female participants, but differences were small and not significant. We conclude that the exposure to unsolvable anagrams induced the experience of uncontrollability which can elicit stress and learned helplessness. Stress and learned helplessness might have reduced the ability to learn from the given feedback, particularly in male participants. We assume that in real life, uncontrollable challenges that last longer than a single experimental manipulation can affect decision making severely, at least in males. PMID:28642693

  8. Temporal lobe epilepsy surgery: what do patients want to know?

    PubMed

    Choi, Hyunmi; Pargeon, Kim; Bausell, Rebecca; Wong, John B; Mendiratta, Anil; Bakken, Suzanne

    2011-11-01

    Patients with pharmacoresistant temporal lobe epilepsy (TLE) contemplating brain surgery must make a complex treatment decision involving trade-offs. Patient decision aids, containing information on the risks and benefits of treatment interventions, increase patient knowledge and facilitate shared decision making between patients and physicians. We conducted five focus groups to describe the information patients need to make informed decisions about TLE surgery. Twenty patients who had undergone TLE surgery described the information used in their decision-making process, and evaluated the potential for a patient decision aid to assist other patients who are considering surgery. Thematic analysis revealed information needs that were both experiential (i.e., learning about other patients' experiences through testimonials) and factual (i.e., individualized statistical information). Patients also made suggestions on how this information should be delivered to patients. These data will accelerate the development of a patient decision aid designed to assist TLE patients in their decision making about epilepsy surgery. Copyright © 2011 Elsevier Inc. All rights reserved.

  9. Probabilistic reward- and punishment-based learning in opioid addiction: Experimental and computational data.

    PubMed

    Myers, Catherine E; Sheynin, Jony; Balsdon, Tarryn; Luzardo, Andre; Beck, Kevin D; Hogarth, Lee; Haber, Paul; Moustafa, Ahmed A

    2016-01-01

    Addiction is the continuation of a habit in spite of negative consequences. A vast literature gives evidence that this poor decision-making behavior in individuals addicted to drugs also generalizes to laboratory decision making tasks, suggesting that the impairment in decision-making is not limited to decisions about taking drugs. In the current experiment, opioid-addicted individuals and matched controls with no history of illicit drug use were administered a probabilistic classification task that embeds both reward-based and punishment-based learning trials, and a computational model of decision making was applied to understand the mechanisms describing individuals' performance on the task. Although behavioral results showed that opioid-addicted individuals performed as well as controls on both reward- and punishment-based learning, the modeling results suggested subtle differences in how decisions were made between the two groups. Specifically, the opioid-addicted group showed decreased tendency to repeat prior responses, meaning that they were more likely to "chase reward" when expectancies were violated, whereas controls were more likely to stick with a previously-successful response rule, despite occasional expectancy violations. This tendency to chase short-term reward, potentially at the expense of developing rules that maximize reward over the long term, may be a contributing factor to opioid addiction. Further work is indicated to better understand whether this tendency arises as a result of brain changes in the wake of continued opioid use/abuse, or might be a pre-existing factor that may contribute to risk for addiction. Copyright © 2015 Elsevier B.V. All rights reserved.

  10. Genetic contributions of the serotonin transporter to social learning of fear and economic decision making.

    PubMed

    Crişan, Liviu G; Pana, Simona; Vulturar, Romana; Heilman, Renata M; Szekely, Raluca; Druğa, Bogdan; Dragoş, Nicolae; Miu, Andrei C

    2009-12-01

    Serotonin (5-HT) modulates emotional and cognitive functions such as fear conditioning (FC) and decision making. This study investigated the effects of a functional polymorphism in the regulatory region (5-HTTLPR) of the human 5-HT transporter (5-HTT) gene on observational FC, risk taking and susceptibility to framing in decision making under uncertainty, as well as multidimensional anxiety and autonomic control of the heart in healthy volunteers. The present results indicate that in comparison to the homozygotes for the long (l) version of 5-HTTLPR, the carriers of the short (s) version display enhanced observational FC, reduced financial risk taking and increased susceptibility to framing in economic decision making. We also found that s-carriers have increased trait anxiety due to threat in social evaluation, and ambiguous threat perception. In addition, s-carriers also show reduced autonomic control over the heart, and a pattern of reduced vagal tone and increased sympathetic activity in comparison to l-homozygotes. This is the first genetic study that identifies the association of a functional polymorphism in a key neurotransmitter-related gene with complex social-emotional and cognitive processes. The present set of results suggests an endophenotype of anxiety disorders, characterized by enhanced social learning of fear, impaired decision making and dysfunctional autonomic activity.

  11. Strong interactions between learned helplessness and risky decision-making in a rat gambling model.

    PubMed

    Nobrega, José N; Hedayatmofidi, Parisa S; Lobo, Daniela S

    2016-11-18

    Risky decision-making is characteristic of depression and of addictive disorders, including pathological gambling. However it is not clear whether a propensity to risky choices predisposes to depressive symptoms or whether the converse is the case. Here we tested the hypothesis that rats showing risky decision-making in a rat gambling task (rGT) would be more prone to depressive-like behaviour in the learned helplessness (LH) model. Results showed that baseline rGT choice behaviour did not predict escape deficits in the LH protocol. In contrast, exposure to the LH protocol resulted in a significant increase in risky rGT choices on retest. Unexpectedly, control rats subjected only to escapable stress in the LH protocol showed a subsequent decrease in riskier rGT choices. Further analyses indicated that the LH protocol affected primarily rats with high baseline levels of risky choices and that among these it had opposite effects in rats exposed to LH-inducing stress compared to rats exposed only to the escape trials. Together these findings suggest that while baseline risky decision making may not predict LH behaviour it interacts strongly with LH conditions in modulating subsequent decision-making behaviour. The suggested possibility that stress controllability may be a key factor should be further investigated.

  12. Strong interactions between learned helplessness and risky decision-making in a rat gambling model

    PubMed Central

    Nobrega, José N.; Hedayatmofidi, Parisa S.; Lobo, Daniela S.

    2016-01-01

    Risky decision-making is characteristic of depression and of addictive disorders, including pathological gambling. However it is not clear whether a propensity to risky choices predisposes to depressive symptoms or whether the converse is the case. Here we tested the hypothesis that rats showing risky decision-making in a rat gambling task (rGT) would be more prone to depressive-like behaviour in the learned helplessness (LH) model. Results showed that baseline rGT choice behaviour did not predict escape deficits in the LH protocol. In contrast, exposure to the LH protocol resulted in a significant increase in risky rGT choices on retest. Unexpectedly, control rats subjected only to escapable stress in the LH protocol showed a subsequent decrease in riskier rGT choices. Further analyses indicated that the LH protocol affected primarily rats with high baseline levels of risky choices and that among these it had opposite effects in rats exposed to LH-inducing stress compared to rats exposed only to the escape trials. Together these findings suggest that while baseline risky decision making may not predict LH behaviour it interacts strongly with LH conditions in modulating subsequent decision-making behaviour. The suggested possibility that stress controllability may be a key factor should be further investigated. PMID:27857171

  13. Genetic contributions of the serotonin transporter to social learning of fear and economic decision making

    PubMed Central

    Crişan, Liviu G.; Pană, Simona; Vulturar, Romana; Heilman, Renata M.; Szekely, Raluca; Drugă, Bogdan; Dragoş, Nicolae

    2009-01-01

    Serotonin (5-HT) modulates emotional and cognitive functions such as fear conditioning (FC) and decision making. This study investigated the effects of a functional polymorphism in the regulatory region (5-HTTLPR) of the human 5-HT transporter (5-HTT) gene on observational FC, risk taking and susceptibility to framing in decision making under uncertainty, as well as multidimensional anxiety and autonomic control of the heart in healthy volunteers. The present results indicate that in comparison to the homozygotes for the long (l) version of 5-HTTLPR, the carriers of the short (s) version display enhanced observational FC, reduced financial risk taking and increased susceptibility to framing in economic decision making. We also found that s-carriers have increased trait anxiety due to threat in social evaluation, and ambiguous threat perception. In addition, s-carriers also show reduced autonomic control over the heart, and a pattern of reduced vagal tone and increased sympathetic activity in comparison to l-homozygotes. This is the first genetic study that identifies the association of a functional polymorphism in a key neurotransmitter-related gene with complex social–emotional and cognitive processes. The present set of results suggests an endophenotype of anxiety disorders, characterized by enhanced social learning of fear, impaired decision making and dysfunctional autonomic activity. PMID:19535614

  14. Experts in offside decision making learn to compensate for their illusory perceptions.

    PubMed

    Put, Koen; Baldo M, V C; Cravo, André M; Wagemans, Johan; Helsen, Werner F

    2013-12-01

    In association football, the flash-lag effect appears to be a viable explanation for erroneous offside decision making. Due to this spatiotemporal illusion, assistant referees (ARs) perceive the player who receives the ball ahead of his real position. In this experiment, a laboratory decision-making task was used to demonstrate that international top-class ARs, compared with amateur soccer players, do not have superior perceptual sensitivity. They clearly modify their decision criterion according to the contextual needs and, therefore, show a higher response bias toward not responding to the stimulus, in particular in the most difficult situations. Thus, international ARs show evidence for response-level compensation, resulting in a specific cost (i.e., more misses), which clearly reflects the use of particular (cognitive) strategies. In summary, it appears that experts in offside decision making can be distinguished from novices more on the cognitive or decision-making level than on the perceptual level.

  15. Multi-criteria Integrated Resource Assessment (MIRA)

    EPA Pesticide Factsheets

    MIRA is an approach that facilitates stakeholder engagement for collaborative multi-objective decision making. MIRA is designed to facilitate and support an inclusive, explicit, transparent, iterative learning-based decision process.

  16. The use of team-based learning in a second year undergraduate pre-registration nursing course on evidence-informed decision making.

    PubMed

    Morris, Jenny

    2016-11-01

    More engaging teaching and learning strategies are needed to teach research-related courses to pre-registration nursing students. Team-based learning was implemented within a second year pre-registration nursing evidence-informed decision making course. Results from a questionnaire survey indicated that 70% believed team-based learning was appropriate for the course, 60% that it was an effective and motivating learning strategy, and 54% recommended using team-based learning in other courses. The results from ten student interviews illustrated the positive way in which team-based learning was perceived, and how the students thought it contributed to their learning. Test results were improved with an increase in the numbers of students achieving 70% or higher; and higher scores for students in the lowest quartile. Team-based learning was shown to be an effective strategy that preserved the benefits of small group teaching with large student groups. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

  17. Exploiting risk-reward structures in decision making under uncertainty.

    PubMed

    Leuker, Christina; Pachur, Thorsten; Hertwig, Ralph; Pleskac, Timothy J

    2018-06-01

    People often have to make decisions under uncertainty-that is, in situations where the probabilities of obtaining a payoff are unknown or at least difficult to ascertain. One solution to this problem is to infer the probability from the magnitude of the potential payoff and thus exploit the inverse relationship between payoffs and probabilities that occurs in many domains in the environment. Here, we investigated how the mind may implement such a solution: (1) Do people learn about risk-reward relationships from the environment-and if so, how? (2) How do learned risk-reward relationships impact preferences in decision-making under uncertainty? Across three experiments (N = 352), we found that participants can learn risk-reward relationships from being exposed to choice environments with a negative, positive, or uncorrelated risk-reward relationship. They were able to learn the associations both from gambles with explicitly stated payoffs and probabilities (Experiments 1 & 2) and from gambles about epistemic events (Experiment 3). In subsequent decisions under uncertainty, participants often exploited the learned association by inferring probabilities from the magnitudes of the payoffs. This inference systematically influenced their preferences under uncertainty: Participants who had been exposed to a negative risk-reward relationship tended to prefer the uncertain option over a smaller sure option for low payoffs, but not for high payoffs. This pattern reversed in the positive condition and disappeared in the uncorrelated condition. This adaptive change in preferences is consistent with the use of the risk-reward heuristic. Copyright © 2018 Elsevier B.V. All rights reserved.

  18. Foxfire As a Need-Satisfying, Non-Coercive Process.

    ERIC Educational Resources Information Center

    McDermott, J. Cynthia

    1995-01-01

    Teaching conformity through coercion limits students' willingness to take risks and make decisions regarding their learning. In contrast, a Foxfire classroom environment that meets psychological needs empowers students to make choices about their learning, eliminates fear of failure, allows students to establish their own standards of achievement,…

  19. An fMRI-Based Neural Signature of Decisions to Smoke Cannabis.

    PubMed

    Bedi, Gillinder; Lindquist, Martin A; Haney, Margaret

    2015-11-01

    Drug dependence may be at its core a pathology of choice, defined by continued decisions to use drugs irrespective of negative consequences. Despite evidence of dysregulated decision making in addiction, little is known about the neural processes underlying the most clinically relevant decisions drug users make: decisions to use drugs. Here, we combined functional magnetic resonance imaging (fMRI), machine learning, and human laboratory drug administration to investigate neural activation underlying decisions to smoke cannabis. Nontreatment-seeking daily cannabis smokers completed an fMRI choice task, making repeated decisions to purchase or decline 1-12 placebo or active cannabis 'puffs' ($0.25-$5/puff). One randomly selected decision was implemented. If the selected choice had been bought, the cost was deducted from study earnings and the purchased cannabis smoked in the laboratory; alternatively, the participant remained in the laboratory without cannabis. Machine learning with leave-one-subject-out cross-validation identified distributed neural activation patterns discriminating decisions to buy cannabis from declined offers. A total of 21 participants were included in behavioral analyses; 17 purchased cannabis and were thus included in fMRI analyses. Purchasing varied lawfully with dose and cost. The classifier discriminated with 100% accuracy between fMRI activation patterns for purchased vs declined cannabis at the level of the individual. Dorsal striatum, insula, posterior parietal regions, anterior and posterior cingulate, and dorsolateral prefrontal cortex all contributed reliably to this neural signature of decisions to smoke cannabis. These findings provide the basis for a brain-based characterization of drug-related decision making in drug abuse, including effects of psychological and pharmacological interventions on these processes.

  20. Model-based hierarchical reinforcement learning and human action control

    PubMed Central

    Botvinick, Matthew; Weinstein, Ari

    2014-01-01

    Recent work has reawakened interest in goal-directed or ‘model-based’ choice, where decisions are based on prospective evaluation of potential action outcomes. Concurrently, there has been growing attention to the role of hierarchy in decision-making and action control. We focus here on the intersection between these two areas of interest, considering the topic of hierarchical model-based control. To characterize this form of action control, we draw on the computational framework of hierarchical reinforcement learning, using this to interpret recent empirical findings. The resulting picture reveals how hierarchical model-based mechanisms might play a special and pivotal role in human decision-making, dramatically extending the scope and complexity of human behaviour. PMID:25267822

  1. Application of a computational decision model to examine acute drug effects on human risk taking.

    PubMed

    Lane, Scott D; Yechiam, Eldad; Busemeyer, Jerome R

    2006-05-01

    In 3 previous experiments, high doses of alcohol, marijuana, and alprazolam acutely increased risky decision making by adult humans in a 2-choice (risky vs. nonrisky) laboratory task. In this study, a computational modeling analysis known as the expectancy valence model (J. R. Busemeyer & J. C. Stout, 2002) was applied to individual-participant data from these studies, for the highest administered dose of all 3 drugs and corresponding placebo doses, to determine changes in decision-making processes that may be uniquely engendered by each drug. The model includes 3 parameters: responsiveness to rewards and losses (valence or motivation); the rate of updating expectancies about the value of risky alternatives (learning/memory); and the consistency with which trial-by-trial choices match expected outcomes (sensitivity). Parameter estimates revealed 3 key outcomes: Alcohol increased responsiveness to risky rewards and decreased responsiveness to risky losses (motivation) but did not alter expectancy updating (learning/memory); both marijuana and alprazolam produced increases in risk taking that were related to learning/memory but not motivation; and alcohol and marijuana (but not alprazolam) produced more random response patterns that were less consistently related to expected outcomes on the 2 choices. No significant main effects of gender or dose by gender interactions were obtained, but 2 dose by gender interactions approached significance. These outcomes underscore the utility of using a computational modeling approach to deconstruct decision-making processes and thus better understand drug effects on risky decision making in humans.

  2. Group Learning.

    ERIC Educational Resources Information Center

    Black, Susan

    1992-01-01

    Research suggests that cooperative learning works best when students are first taught group-processing skills, such as leadership, decision making, communication, trust building, and conflict management. Inadequate teacher training and boring assignments can torpedo cooperative learning efforts. Administrators should reassure teachers with…

  3. Neural Basis of Strategic Decision Making.

    PubMed

    Lee, Daeyeol; Seo, Hyojung

    2016-01-01

    Human choice behaviors during social interactions often deviate from the predictions of game theory. This might arise partly from the limitations in the cognitive abilities necessary for recursive reasoning about the behaviors of others. In addition, during iterative social interactions, choices might change dynamically as knowledge about the intentions of others and estimates for choice outcomes are incrementally updated via reinforcement learning. Some of the brain circuits utilized during social decision making might be general-purpose and contribute to isomorphic individual and social decision making. By contrast, regions in the medial prefrontal cortex (mPFC) and temporal parietal junction (TPJ) might be recruited for cognitive processes unique to social decision making. Copyright © 2015 Elsevier Ltd. All rights reserved.

  4. Fidelity of the representation of value in decision-making

    PubMed Central

    Dowding, Ben A.

    2017-01-01

    The ability to make optimal decisions depends on evaluating the expected rewards associated with different potential actions. This process is critically dependent on the fidelity with which reward value information can be maintained in the nervous system. Here we directly probe the fidelity of value representation following a standard reinforcement learning task. The results demonstrate a previously-unrecognized bias in the representation of value: extreme reward values, both low and high, are stored significantly more accurately and precisely than intermediate rewards. The symmetry between low and high rewards pertained despite substantially higher frequency of exposure to high rewards, resulting from preferential exploitation of more rewarding options. The observed variation in fidelity of value representation retrospectively predicted performance on the reinforcement learning task, demonstrating that the bias in representation has an impact on decision-making. A second experiment in which one or other extreme-valued option was omitted from the learning sequence showed that representational fidelity is primarily determined by the relative position of an encoded value on the scale of rewards experienced during learning. Both variability and guessing decreased with the reduction in the number of options, consistent with allocation of a limited representational resource. These findings have implications for existing models of reward-based learning, which typically assume defectless representation of reward value. PMID:28248958

  5. Within- and across-trial dynamics of human EEG reveal cooperative interplay between reinforcement learning and working memory.

    PubMed

    Collins, Anne G E; Frank, Michael J

    2018-03-06

    Learning from rewards and punishments is essential to survival and facilitates flexible human behavior. It is widely appreciated that multiple cognitive and reinforcement learning systems contribute to decision-making, but the nature of their interactions is elusive. Here, we leverage methods for extracting trial-by-trial indices of reinforcement learning (RL) and working memory (WM) in human electro-encephalography to reveal single-trial computations beyond that afforded by behavior alone. Neural dynamics confirmed that increases in neural expectation were predictive of reduced neural surprise in the following feedback period, supporting central tenets of RL models. Within- and cross-trial dynamics revealed a cooperative interplay between systems for learning, in which WM contributes expectations to guide RL, despite competition between systems during choice. Together, these results provide a deeper understanding of how multiple neural systems interact for learning and decision-making and facilitate analysis of their disruption in clinical populations.

  6. Leadership in a Performative Context: A Framework for Decision-Making

    ERIC Educational Resources Information Center

    Chitpin, Stephanie; Jones, Ken

    2015-01-01

    This paper examines a model of decision-making within the context of current and emerging regimes of accountability being proposed and implemented for school systems in a number of jurisdictions. These approaches to accountability typically involve the use of various measurable student learning outcomes as well as other measures of performance to…

  7. Headed for the Heartland: Decision Making Process of Community College Bound International Students

    ERIC Educational Resources Information Center

    Bohman, Eric

    2010-01-01

    Despite record growth in international student enrollment at U.S. community colleges, little is known regarding how the international students learn about--and ultimately decide to attend--community colleges. This research study identifies the decision making factors and explores the sources of information utilized by international students who…

  8. A Social Learning Theory of Career Decision Making.

    ERIC Educational Resources Information Center

    Mitchell, Anita M., Ed.; And Others

    This report contains an analysis of career decision making (CDM), a synthesis of theories and empirical studies related to CDM, and identification of areas in need of further research and/or development. The study includes contributions from the fields of psychology, economics, sociology, guidance and education. An attempt has been made to…

  9. Government: The Decision-Making Process. A Resource Manual for Teachers and Students. Revised Edition.

    ERIC Educational Resources Information Center

    Khanlian, John F.; Wallin, Katherine L.

    This guide for high school political science teachers focuses on political decision making. The program emphasizes experiential learning through utilizing community and state resources and implementing field study and internships for students. The document is presented in eight sections. The introduction includes a values survey and suggestions…

  10. Sustainability and Ethics as Decision-Making Paradigms in Engineering Curricula

    ERIC Educational Resources Information Center

    El-Zein, Abbas; Airey, David; Bowden, Peter; Clarkeburn, Henriikka

    2008-01-01

    Purpose: The aim of this paper is to explore the rationale for teaching sustainability and engineering ethics within a decision-making paradigm, and critically appraise ways of achieving related learning outcomes. Design/methodology/approach: The paper presents the experience of the School of Civil Engineering at the University of Sydney in…

  11. Improving Decision Making Skill Using an Online Volcanic Crisis Simulation: Impact of Data Presentation Format

    ERIC Educational Resources Information Center

    Barclay, Elizabeth J.; Renshaw, Carl E.; Taylor, Holly A.; Bilge, A. Reyan

    2011-01-01

    Creating effective computer-based learning exercises requires an understanding of optimal user interface designs for improving higher order cognitive skills. Using an online volcanic crisis simulation previously shown to improve decision making skill, we find that a user interface using a graphical presentation of the volcano monitoring data…

  12. Why a Data-Based Decision-Making Intervention Works in Some Schools and Not in Others

    ERIC Educational Resources Information Center

    Keuning, Trynke; Van Geel, Marieke; Visscher, Adrie

    2017-01-01

    The use of data for adaptive, tailor-made education can be beneficial for students with learning difficulties. While evaluating the effects of a data-based decision-making (DBDM) intervention on student outcomes, considerable variation between intervention effects, ranging from high-intervention effects to small or even negative intervention…

  13. Perspective Taking and Decision-Making in Educational Game Play: A Mixed-Methods Study

    ERIC Educational Resources Information Center

    Hilliard, Lacey J.; Buckingham, Mary H.; Geldhof, G. John; Gansert, Patricia; Stack, Caroline; Gelgoot, Erin S.; Bers, Marina U.; Lerner, Richard M.

    2018-01-01

    Video games have the potential to be contexts for moral learning. We investigated whether "Quandary," a video game designed to promote ethical thinking and moral considerations for decision-making, would help promote positive skills such as perspective taking and empathy in adolescents. We examined the effect of playing…

  14. Classroom Assessment: Concepts and Applications. Fourth Edition.

    ERIC Educational Resources Information Center

    Airasian, Peter W.

    This book is designed for students taking a first course in classroom assessment and measurement. It shows how assessment principles apply to the full range of teacher decision making and not just the formal evaluation of student learning. The book is organized in a way that follows the natural progression of teachers' decision making, from…

  15. Risky Decision Making Assessed With the Gambling Task in Adults with HIV

    PubMed Central

    Hardy, David J.; Hinkin, Charles H.; Castellon, Steven A.; Levine, Andrew J.; Lam, Mona N.

    2010-01-01

    Decision making was assessed using a laboratory gambling task in 67 adults with the Human Immunodeficiency Virus (HIV+) and in 19 HIV-seronegative (HIV−) control participants. Neurocognitive test performance across several domains was also analyzed to examine potential cognitive mechanisms of gambling task performance. As predicted, the HIV+ group performed worse on the gambling task, indicating greater risky decision making. Specifically, the HIV+ group selected more cards from the “risky” or disadvantageous deck that included relatively large payoffs but infrequent large penalties. The control group also selected such risky cards but quickly learned to avoid them. Exploratory analyses also indicated that in the HIV+ group, but not in the control group, gambling task performance was correlated with Stroop Interference performance and long delay free recall on the California Verbal Learning Test, suggesting the role of inhibitory processes and verbal memory in the poorer gambling task performance in HIV. These findings indicate the usefulness of the gambling task as a laboratory tool to examine risky decision making and cognition in the HIV population. PMID:16719628

  16. A heuristic framework for understanding the role of participatory decision making in community-based non-profits.

    PubMed

    Bess, Kimberly D; Perkins, Douglas D; Cooper, Daniel G; Jones, Diana L

    2011-06-01

    This paper explores the role of member participation in decision-making (PDM) from an organizational learning (OL) perspective. Community-based organizations (CBOs) serve as mediators between the individual and the local community, often providing the means for community member participation and benefiting organizationally from members' input. Community psychologists have recognized these benefits; however, the field has paid less attention to the role participation plays in increasing CBOs' capacity to meet community needs. We present a framework for exploring how CBO contextual factors influence the use of participatory decision-making structures and practices, and how these affect OL. We then use the framework to examine PDM in qualitative case study analysis of four CBOs: a youth development organization, a faith-based social action coalition, a low-income neighborhood organization, and a large human service agency. We found that organizational form, energy, and culture each had a differential impact on participation in decision making within CBOs. We highlight how OL is constrained in CBOs and document how civic aims and voluntary membership enhanced participation and learning.

  17. Executive functions, information sampling, and decision making in narcolepsy with cataplexy.

    PubMed

    Delazer, Margarete; Högl, Birgit; Zamarian, Laura; Wenter, Johanna; Gschliesser, Viola; Ehrmann, Laura; Brandauer, Elisabeth; Cevikkol, Zehra; Frauscher, Birgit

    2011-07-01

    Narcolepsy with cataplexy (NC) affects neurotransmitter systems regulating emotions and cognitive functions. This study aimed to assess executive functions, information sampling, reward processing, and decision making in NC. Twenty-one NC patients and 58 healthy participants performed an extensive neuropsychological test battery. NC patients scored as controls in executive function tasks assessing set shifting, reversal learning, working memory, and planning. Group differences appeared in a task measuring information sampling and reward sensitivity. NC patients gathered less information, tolerated a higher level of uncertainty, and were less influenced by reward contingencies than controls. NC patients also showed reduced learning in decision making and had significantly lower scores than controls in the fifth block of the IOWA gambling task. No correlations were found with measures of sleepiness. NC patients may achieve high performance in several neuropsychological domains, including executive functions. Specific differences between NC patients and controls highlight the importance of the hypocretin system in reward processing and decision making and are in line with previous neuroimaging and neurophysiological studies. PsycINFO Database Record (c) 2011 APA, all rights reserved.

  18. The importance of imagination (or lack thereof) in artificial, human and quantum decision making.

    PubMed

    Gustafson, Karl

    2016-01-13

    Enlarging upon experiments and analysis that I did jointly some years ago, in which artificial (symbolic, neural-net and pattern) learning and generalization were compared with that of humans, I will emphasize the role of imagination (or lack thereof) in artificial, human and quantum cognition and decision-making processes. Then I will look in more detail at some of the 'engineering details' of its implementation (or lack thereof) in each of these settings. In other words, the question posed is: What is actually happening? For example, we previously found that humans overwhelmingly seek, create or imagine context in order to provide meaning when presented with abstract, apparently incomplete, contradictory or otherwise untenable decision-making situations. Humans are intolerant of contradiction and will greatly simplify to avoid it. They can partially correlate but do not average. Human learning is not Boolean. These and other human reasoning properties will then be taken to critique how well artificial intelligence methods and quantum mechanical modelling might compete with them in decision-making tasks within psychology and economics. © 2015 The Author(s).

  19. Perceptual Training in Beach Volleyball Defence: Different Effects of Gaze-Path Cueing on Gaze and Decision-Making

    PubMed Central

    Klostermann, André; Vater, Christian; Kredel, Ralf; Hossner, Ernst-Joachim

    2015-01-01

    For perceptual-cognitive skill training, a variety of intervention methods has been proposed, including the so-called “color-cueing method” which aims on superior gaze-path learning by applying visual markers. However, recent findings challenge this method, especially, with regards to its actual effects on gaze behavior. Consequently, after a preparatory study on the identification of appropriate visual cues for life-size displays, a perceptual-training experiment on decision-making in beach volleyball was conducted, contrasting two cueing interventions (functional vs. dysfunctional gaze path) with a conservative control condition (anticipation-related instructions). Gaze analyses revealed learning effects for the dysfunctional group only. Regarding decision-making, all groups showed enhanced performance with largest improvements for the control group followed by the functional and the dysfunctional group. Hence, the results confirm cueing effects on gaze behavior, but they also question its benefit for enhancing decision-making. However, before completely denying the method’s value, optimisations should be checked regarding, for instance, cueing-pattern characteristics and gaze-related feedback. PMID:26648894

  20. Concept mapping in a critical care orientation program: a pilot study to develop critical thinking and decision-making skills in novice nurses.

    PubMed

    Wahl, Stacy E; Thompson, Anita M

    2013-10-01

    Newly graduated registered nurses who were hired into a critical care intensive care unit showed a lack of critical thinking skills to inform their clinical decision-making abilities. This study evaluated the effectiveness of concept mapping as a teaching tool to improve critical thinking and clinical decision-making skills in novice nurses. A self-evaluation tool was administered before and after the learning intervention. The 25-item tool measured five key indicators of the development of critical thinking skills: problem recognition, clinical decision-making, prioritization, clinical implementation, and reflection. Statistically significant improvements were seen in 10 items encompassing all five indicators. Concept maps are an effective tool for educators to use in assisting novice nurses to develop their critical thinking and clinical decision-making skills. Copyright 2013, SLACK Incorporated.

  1. A serious game for improving the decision making skills and knowledge levels of Turkish football referees according to the laws of the game.

    PubMed

    Gulec, Ulas; Yilmaz, Murat

    2016-01-01

    Digital game-based learning environments provide emerging opportunities to overcome learning barriers by combining newly developed technologies and traditional game design. This study proposes a quantitative research approach supported by expert validation interviews to designing a game-based learning framework. The goal is to improve the learning experience and decision-making skills of soccer referees in Turkey. A serious game was developed and tested on a group of referees (N = 54). The assessment results of these referees were compared with two sample t-test and the Wilcoxon signed-ranked test for both the experimental group and the control group. The findings of the current study confirmed that a game-based learning environment has greater merit over the paper-based alternatives.

  2. Play and Learn: Potentials of Game-Based Learning

    NASA Technical Reports Server (NTRS)

    Pivec, Maja

    2008-01-01

    Learners are encouraged to combine knowledge from different areas to choose a solution or to make a decision at acertain point. Learners can test how the outcome of the game changes based on their decisions and actions. Learners are encouraged to contact other team members and discuss and negotiate subsequent steps, thus improving their social skills.

  3. Big Data & Learning Analytics: A Potential Way to Optimize eLearning Technological Tools

    ERIC Educational Resources Information Center

    García, Olga Arranz; Secades, Vidal Alonso

    2013-01-01

    In the information age, one of the most influential institutions is education. The recent emergence of MOOCS [Massively Open Online Courses] is a sample of the new expectations that are offered to university students. Basing decisions on data and evidence seems obvious, and indeed, research indicates that data-driven decision-making improves…

  4. An Exploratory Qualitative Study of Ethical Beliefs among Early Childhood Teachers

    ERIC Educational Resources Information Center

    French-Lee, Stacey; Dooley, Caitlin McMunn

    2015-01-01

    The purpose of this study is to learn how early childhood educators make ethical decisions. The study also explores how these educators might learn to base their ethical decisions on a professionally accepted ethical code through a participatory professional development process. The professional code of ethics used in this study is the National…

  5. Case Study Methodology: Flexibility, Rigour, and Ethical Considerations for the Scholarship of Teaching and Learning

    ERIC Educational Resources Information Center

    Pearson, Marion L.; Albon, Simon P.; Hubball, Harry

    2015-01-01

    Individuals and teams engaging in the scholarship of teaching and learning (SoTL) in multidisciplinary higher education settings must make decisions regarding choice of research methodology and methods. These decisions are guided by the research context and the goals of the inquiry. With reference to our own recent experiences investigating…

  6. Modeling To Enhance Critical Thinking and Decision Making Skills Development in the Instructional Process: The Social Studies.

    ERIC Educational Resources Information Center

    Peters, Richard

    Students must be actively involved in the process of learning for it to have personal meaning and importance in their lives. Teachers must also become critical thinkers, creative individuals, and decision makers in order to create more challenging learning environments. Teachers need to blend structure and spontaneity into meaningful learning…

  7. Evidence-Based Decision-Making as a Practice-Based Learning Skill: A Pilot Study

    ERIC Educational Resources Information Center

    Falzer, Paul R.; Garman, Melissa

    2012-01-01

    Objectives: As physicians are being trained to adapt their practices to the needs and experience of patients, initiatives to standardize care have been gaining momentum. The resulting conflict can be addressed through a practice-based learning and improvement (PBL) program that develops competency in using treatment guidelines as decision aids and…

  8. Decision Making Under Objective Risk Conditions-a Review of Cognitive and Emotional Correlates, Strategies, Feedback Processing, and External Influences.

    PubMed

    Schiebener, Johannes; Brand, Matthias

    2015-06-01

    While making decisions under objective risk conditions, the probabilities of the consequences of the available options are either provided or calculable. Brand et al. (Neural Networks 19:1266-1276, 2006) introduced a model describing the neuro-cognitive processes involved in such decisions. In this model, executive functions associated with activity in the fronto-striatal loop are important for developing and applying decision-making strategies, and for verifying, adapting, or revising strategies according to feedback. Emotional rewards and punishments learned from such feedback accompany these processes. In this literature review, we found support for the role of executive functions, but also found evidence for the importance of further cognitive abilities in decision making. Moreover, in addition to reflective processing (driven by cognition), decisions can be guided by impulsive processing (driven by anticipation of emotional reward and punishment). Reflective and impulsive processing may interact during decision making, affecting the evaluation of available options, as both processes are affected by feedback. Decision-making processes are furthermore modulated by individual attributes (e.g., age), and external influences (e.g., stressors). Accordingly, we suggest a revised model of decision making under objective risk conditions.

  9. Decision-Making in Multiple Sclerosis Patients: A Systematic Review.

    PubMed

    Neuhaus, Mireille; Calabrese, Pasquale; Annoni, Jean-Marie

    2018-01-01

    Multiple sclerosis (MS) is frequently associated with cognitive and behavioural deficits. A growing number of studies suggest an impact of MS on decision-making abilities. The aim of this systematic review was to assess if (1) performance of MS patients in decision-making tasks was consistently different from controls and (2) whether this modification was associated with cognitive dysfunction and emotional alterations. The search was conducted on Pubmed/Medline database. 12 studies evaluating the difference between MS patients and healthy controls using validated decision-making tasks were included. Outcomes considered were quantitative (net scores) and qualitative measurements (deliberation time and learning from feedback). Quantitative and qualitative decision-making impairment in MS was present in 64.7% of measurements. Patients were equally impaired in tasks for decision-making under risk and ambiguity. A correlation to other cognitive functions was present in 50% of cases, with the highest associations in the domains of processing speed and attentional capacity. In MS patients, qualitative and quantitative modifications may be present in any kind of decision-making task and can appear independently of other cognitive measures. Since decision-making abilities have a significant impact on everyday life, this cognitive aspect has an influential importance in various MS-related treatment settings.

  10. Towards a cognitive robotics methodology for reward-based decision-making: dynamical systems modelling of the Iowa Gambling Task

    NASA Astrophysics Data System (ADS)

    Lowe, Robert; Ziemke, Tom

    2010-09-01

    The somatic marker hypothesis (SMH) posits that the role of emotions and mental states in decision-making manifests through bodily responses to stimuli of import to the organism's welfare. The Iowa Gambling Task (IGT), proposed by Bechara and Damasio in the mid-1990s, has provided the major source of empirical validation to the role of somatic markers in the service of flexible and cost-effective decision-making in humans. In recent years the IGT has been the subject of much criticism concerning: (1) whether measures of somatic markers reveal that they are important for decision-making as opposed to behaviour preparation; (2) the underlying neural substrate posited as critical to decision-making of the type relevant to the task; and (3) aspects of the methodological approach used, particularly on the canonical version of the task. In this paper, a cognitive robotics methodology is proposed to explore a dynamical systems approach as it applies to the neural computation of reward-based learning and issues concerning embodiment. This approach is particularly relevant in light of a strongly emerging alternative hypothesis to the SMH, the reversal learning hypothesis, which links, behaviourally and neurocomputationally, a number of more or less complex reward-based decision-making tasks, including the 'A-not-B' task - already subject to dynamical systems investigations with a focus on neural activation dynamics. It is also suggested that the cognitive robotics methodology may be used to extend systematically the IGT benchmark to more naturalised, but nevertheless controlled, settings that might better explore the extent to which the SMH, and somatic states per se, impact on complex decision-making.

  11. Serotonin and decision making processes.

    PubMed

    Homberg, Judith R

    2012-01-01

    Serotonin (5-HT) is an important player in decision making. Serotonergic antidepressant, anxiolytic and antipsychotic drugs are extensively used in the treatment of neuropsychiatric disorders characterized by impaired decision making, and exert both beneficial and harmful effects in patients. Detailed insight into the serotonergic mechanisms underlying decision making is needed to strengthen the first and weaken the latter. Although much remains to be done to achieve this, accumulating studies begin to deliver a coherent view. Thus, high central 5-HT levels are generally associated with improved reversal learning, improved attentional set shifting, decreased delay discounting, and increased response inhibition, but a failure to use outcome representations. Based on 5-HT's evolutionary role, I hypothesize that 5-HT integrates expected, or changes in, relevant sensory and emotional internal/external information, leading to vigilance behaviour affecting various decision making processes. 5-HT receptor subtypes play distinctive roles in decision making. 5-HT(2A) agonists and 5-HT2c antagonists decrease compulsivity, whereas 5-HT(2A) antagonists and 5-HT(2C) agonists decrease impulsivity. 5-HT(6) antagonists univocally affect decision making processes. Copyright © 2011 Elsevier Ltd. All rights reserved.

  12. Why humans deviate from rational choice.

    PubMed

    Hewig, Johannes; Kretschmer, Nora; Trippe, Ralf H; Hecht, Holger; Coles, Michael G H; Holroyd, Clay B; Miltner, Wolfgang H R

    2011-04-01

    Rational choice theory predicts that humans always optimize the expected utility of options when making decisions. However, in decision-making games, humans often punish their opponents even when doing so reduces their own reward. We used the Ultimatum and Dictator games to examine the affective correlates of decision-making. We show that the feedback negativity, an event-related brain potential that originates in the anterior cingulate cortex that has been related to reinforcement learning, predicts the decision to reject unfair offers in the Ultimatum game. Furthermore, the decision to reject is positively related to more negative emotional reactions and to increased autonomic nervous system activity. These findings support the idea that subjective emotional markers guide decision-making and that the anterior cingulate cortex integrates instances of reinforcement and punishment to provide such affective markers. Copyright © 2010 Society for Psychophysiological Research.

  13. Team-Based Simulations: Learning Ethical Conduct in Teacher Trainee Programs

    ERIC Educational Resources Information Center

    Shapira-Lishchinsky, Orly

    2013-01-01

    This study aimed to identify the learning aspects of team-based simulations (TBS) through the analysis of ethical incidents experienced by 50 teacher trainees. A four-dimensional model emerged: learning to make decisions in a "supportive-forgiving" environment; learning to develop standards of care; learning to reduce misconduct; and learning to…

  14. A Cognitive Modeling Approach to Strategy Formation in Dynamic Decision Making.

    PubMed

    Prezenski, Sabine; Brechmann, André; Wolff, Susann; Russwinkel, Nele

    2017-01-01

    Decision-making is a high-level cognitive process based on cognitive processes like perception, attention, and memory. Real-life situations require series of decisions to be made, with each decision depending on previous feedback from a potentially changing environment. To gain a better understanding of the underlying processes of dynamic decision-making, we applied the method of cognitive modeling on a complex rule-based category learning task. Here, participants first needed to identify the conjunction of two rules that defined a target category and later adapt to a reversal of feedback contingencies. We developed an ACT-R model for the core aspects of this dynamic decision-making task. An important aim of our model was that it provides a general account of how such tasks are solved and, with minor changes, is applicable to other stimulus materials. The model was implemented as a mixture of an exemplar-based and a rule-based approach which incorporates perceptual-motor and metacognitive aspects as well. The model solves the categorization task by first trying out one-feature strategies and then, as a result of repeated negative feedback, switching to two-feature strategies. Overall, this model solves the task in a similar way as participants do, including generally successful initial learning as well as reversal learning after the change of feedback contingencies. Moreover, the fact that not all participants were successful in the two learning phases is also reflected in the modeling data. However, we found a larger variance and a lower overall performance of the modeling data as compared to the human data which may relate to perceptual preferences or additional knowledge and rules applied by the participants. In a next step, these aspects could be implemented in the model for a better overall fit. In view of the large interindividual differences in decision performance between participants, additional information about the underlying cognitive processes from behavioral, psychobiological and neurophysiological data may help to optimize future applications of this model such that it can be transferred to other domains of comparable dynamic decision tasks.

  15. A Cognitive Modeling Approach to Strategy Formation in Dynamic Decision Making

    PubMed Central

    Prezenski, Sabine; Brechmann, André; Wolff, Susann; Russwinkel, Nele

    2017-01-01

    Decision-making is a high-level cognitive process based on cognitive processes like perception, attention, and memory. Real-life situations require series of decisions to be made, with each decision depending on previous feedback from a potentially changing environment. To gain a better understanding of the underlying processes of dynamic decision-making, we applied the method of cognitive modeling on a complex rule-based category learning task. Here, participants first needed to identify the conjunction of two rules that defined a target category and later adapt to a reversal of feedback contingencies. We developed an ACT-R model for the core aspects of this dynamic decision-making task. An important aim of our model was that it provides a general account of how such tasks are solved and, with minor changes, is applicable to other stimulus materials. The model was implemented as a mixture of an exemplar-based and a rule-based approach which incorporates perceptual-motor and metacognitive aspects as well. The model solves the categorization task by first trying out one-feature strategies and then, as a result of repeated negative feedback, switching to two-feature strategies. Overall, this model solves the task in a similar way as participants do, including generally successful initial learning as well as reversal learning after the change of feedback contingencies. Moreover, the fact that not all participants were successful in the two learning phases is also reflected in the modeling data. However, we found a larger variance and a lower overall performance of the modeling data as compared to the human data which may relate to perceptual preferences or additional knowledge and rules applied by the participants. In a next step, these aspects could be implemented in the model for a better overall fit. In view of the large interindividual differences in decision performance between participants, additional information about the underlying cognitive processes from behavioral, psychobiological and neurophysiological data may help to optimize future applications of this model such that it can be transferred to other domains of comparable dynamic decision tasks. PMID:28824512

  16. Informed decision-making with and for people with dementia - efficacy of the PRODECIDE education program for legal representatives: protocol of a randomized controlled trial (PRODECIDE-RCT).

    PubMed

    Lühnen, Julia; Haastert, Burkhard; Mühlhauser, Ingrid; Richter, Tanja

    2017-09-15

    In Germany, the guardianship system provides adults who are no longer able to handle their own affairs a court-appointed legal representative, for support without restriction of legal capacity. Although these representatives only rarely are qualified in healthcare, they nevertheless play decisive roles in the decision-making processes for people with dementia. Previously, we developed an education program (PRODECIDE) to address this shortcoming and tested it for feasibility. Typical, autonomy-restricting decisions in the care of people with dementia-namely, using percutaneous endoscopic gastrostomy (PEG) or physical restrains (PR), or the prescription of antipsychotic drugs (AP)-were the subject areas trained. The training course aims to enhance the competency of legal representatives in informed decision-making. In this study, we will evaluate the efficacy of the PRODECIDE education program. A randomized controlled trial with a six-month follow-up will be conducted to compare the PRODECIDE education program with standard care, enrolling legal representatives (N = 216). The education program lasts 10 h and comprises four modules: A, decision-making processes and methods; and B, C and D, evidence-based knowledge about PEG, PR and AP, respectively. The primary outcome measure is knowledge, which is operationalized as the understanding of decision-making processes in healthcare affairs and in setting realistic expectations about benefits and harms of PEG, PR and AP in people with dementia. Secondary outcomes are sufficient and sustainable knowledge and percentage of persons concerned affected by PEG, FEM or AP. A qualitative process evaluation will be performed. Additionally, to support implementation, a concept for translating the educational contents into e-learning modules will be developed. The study results will show whether the efficacy of the education program could justify its implementation into the regular training curricula for legal representatives. Additionally, it will determine whether an e-learning course provides a valuable backup or even alternative learning strategy. TRN: ISRCTN17960111 , Date: 01/06/2017.

  17. Altruistic learning.

    PubMed

    Seymour, Ben; Yoshida, Wako; Dolan, Ray

    2009-01-01

    The origin of altruism remains one of the most enduring puzzles of human behaviour. Indeed, true altruism is often thought either not to exist, or to arise merely as a miscalculation of otherwise selfish behaviour. In this paper, we argue that altruism emerges directly from the way in which distinct human decision-making systems learn about rewards. Using insights provided by neurobiological accounts of human decision-making, we suggest that reinforcement learning in game-theoretic social interactions (habitisation over either individuals or games) and observational learning (either imitative of inference based) lead to altruistic behaviour. This arises not only as a result of computational efficiency in the face of processing complexity, but as a direct consequence of optimal inference in the face of uncertainty. Critically, we argue that the fact that evolutionary pressure acts not over the object of learning ('what' is learned), but over the learning systems themselves ('how' things are learned), enables the evolution of altruism despite the direct threat posed by free-riders.

  18. Expanding the base for teaching of percutaneous coronary interventions: the explicit approach.

    PubMed

    Lanzer, Peter; Prechelt, Lutz

    2011-02-15

    Accelerate and improve the training and learning process of operators performing percutaneous coronary interventions (PCI). Operator cognitive, in particular decision-making skills and technical skills are a major factor for the success of coronary interventions. Currently, cognitive skills are commonly developed by three methods: (1) Cognitive learning of rules for which statistical evidence is available. This is very incomprehensive and isolates cognitive learning from skill acquisition. (2) Informal tutoring received from experienced operators, and (3) personal experience by trial-and-error are both very slow. We propose in this concept article a conceptual framework to elicit, capture, and transfer expert PCI skills to complement the current approach. This includes the development of an in-depth understanding of the nature of PCI skills, terminology, and nomenclature needed to streamline communication, propensity of reproducible performance assessment, and in particular an explication of intervention planning and intra-intervention decision-making. We illustrate the impact of improved decision-making by simulation results based on a stochastic model of intervention risk. We identify several key concepts that form the basis of this conceptual framework, in particular different risk types and the notions of strategy, interventional module, and tactic. The increasing complexity of cases have brought PCI to the point where the decision-making skills of master operators need to be made explicit to make them systematically learnable such that the skills of beginner and intermediate operators can be improved much faster than is currently possible. Copyright © 2010 Wiley-Liss, Inc.

  19. Overcoming Learning Aversion in Evaluating and Managing Uncertain Risks.

    PubMed

    Cox, Louis Anthony Tony

    2015-10-01

    Decision biases can distort cost-benefit evaluations of uncertain risks, leading to risk management policy decisions with predictably high retrospective regret. We argue that well-documented decision biases encourage learning aversion, or predictably suboptimal learning and premature decision making in the face of high uncertainty about the costs, risks, and benefits of proposed changes. Biases such as narrow framing, overconfidence, confirmation bias, optimism bias, ambiguity aversion, and hyperbolic discounting of the immediate costs and delayed benefits of learning, contribute to deficient individual and group learning, avoidance of information seeking, underestimation of the value of further information, and hence needlessly inaccurate risk-cost-benefit estimates and suboptimal risk management decisions. In practice, such biases can create predictable regret in selection of potential risk-reducing regulations. Low-regret learning strategies based on computational reinforcement learning models can potentially overcome some of these suboptimal decision processes by replacing aversion to uncertain probabilities with actions calculated to balance exploration (deliberate experimentation and uncertainty reduction) and exploitation (taking actions to maximize the sum of expected immediate reward, expected discounted future reward, and value of information). We discuss the proposed framework for understanding and overcoming learning aversion and for implementing low-regret learning strategies using regulation of air pollutants with uncertain health effects as an example. © 2015 Society for Risk Analysis.

  20. An integrative review of in-class activities that enable active learning in college science classroom settings

    NASA Astrophysics Data System (ADS)

    Arthurs, Leilani A.; Kreager, Bailey Zo

    2017-10-01

    Engaging students in active learning is linked to positive learning outcomes. This study aims to synthesise the peer-reviewed literature about 'active learning' in college science classroom settings. Using the methodology of an integrative literature review, 337 articles archived in the Educational Resources Information Center (ERIC) are examined. Four categories of in-class activities emerge: (i) individual non-polling activities, (ii) in-class polling activities, (iii) whole-class discussion or activities, and (iv) in-class group activities. Examining the collection of identified in-class activities through the lens of a theoretical framework informed by constructivism and social interdependence theory, we synthesise the reviewed literature to propose the active learning strategies (ALSs) model and the instructional decisions to enable active learning (IDEAL) theory. The ALS model characterises in-class activities in terms of the degrees to which they are designed to promote (i) peer interaction and (ii) social interdependence. The IDEAL theory includes the ALS model and provides a framework for conceptualising different levels of the general concept 'active learning' and how these levels connect to instructional decision-making about using in-class activities. The proposed ALS model and IDEAL theory can be utilised to inform instructional decision-making and future research about active learning in college science courses.

  1. Effects of additional team-based learning on students' clinical reasoning skills: a pilot study.

    PubMed

    Jost, Meike; Brüstle, Peter; Giesler, Marianne; Rijntjes, Michel; Brich, Jochen

    2017-07-14

    In the field of Neurology good clinical reasoning skills are essential for successful diagnosing and treatment. Team-based learning (TBL), an active learning and small group instructional strategy, is a promising method for fostering these skills. The aim of this pilot study was to examine the effects of a supplementary TBL-class on students' clinical decision-making skills. Fourth- and fifth-year medical students participated in this pilot study (static-group comparison design). The non-treatment group (n = 15) did not receive any additional training beyond regular teaching in the neurology course. The treatment group (n = 11) took part in a supplementary TBL-class optimized for teaching clinical reasoning in addition to the regular teaching in the neurology course. Clinical decision making skills were assessed using a key-feature problem examination. Factual and conceptual knowledge was assessed by a multiple-choice question examination. The TBL-group performed significantly better than the non-TBL-group (p = 0.026) in the key-feature problem examination. No significant differences between the results of the multiple-choice question examination of both groups were found. In this pilot study participants of a supplementary TBL-class significantly improved clinical decision-making skills, indicating that TBL may be an appropriate method for teaching clinical decision making in neurology. Further research is needed for replication in larger groups and other clinical fields.

  2. Review of experimental studies in social psychology of small groups when an optimal choice exists and application to operating room management decision-making.

    PubMed

    Prahl, Andrew; Dexter, Franklin; Braun, Michael T; Van Swol, Lyn

    2013-11-01

    Because operating room (OR) management decisions with optimal choices are made with ubiquitous biases, decisions are improved with decision-support systems. We reviewed experimental social-psychology studies to explore what an OR leader can do when working with stakeholders lacking interest in learning the OR management science but expressing opinions about decisions, nonetheless. We considered shared information to include the rules-of-thumb (heuristics) that make intuitive sense and often seem "close enough" (e.g., staffing is planned based on the average workload). We considered unshared information to include the relevant mathematics (e.g., staffing calculations). Multiple studies have shown that group discussions focus more on shared than unshared information. Quality decisions are more likely when all group participants share knowledge (e.g., have taken a course in OR management science). Several biases in OR management are caused by humans' limited abilities to estimate tails of probability distributions in their heads. Groups are more susceptible to analogous biases than are educated individuals. Since optimal solutions are not demonstrable without groups sharing common language, only with education of most group members can a knowledgeable individual influence the group. The appropriate model of decision-making is autocratic, with information obtained from stakeholders. Although such decisions are good quality, the leaders often are disliked and the decisions considered unjust. In conclusion, leaders will find the most success if they do not bring OR management operational decisions to groups, but instead act autocratically while obtaining necessary information in 1:1 conversations. The only known route for the leader making such decisions to be considered likable and for the decisions to be considered fair is through colleagues and subordinates learning the management science.

  3. Aging and the neuroeconomics of decision making: A review.

    PubMed

    Brown, Stephen B R E; Ridderinkhof, K Richard

    2009-12-01

    Neuroeconomics refers to a combination of paradigms derived from neuroscience, psychology, and economics for the study of decision making and is an area that has received considerable scientific attention in the recent literature. Using realistic laboratory tasks, researchers seek to study the neurocognitive processes underlying economic decision making and outcome-based decision learning, as well as individual differences in these processes and the social and affective factors that modulate them. To this point, one question has remained largely unanswered: What happens to decision-making processes and their neural substrates during aging? After all, aging is associated with neurocognitive change, which may affect outcome-based decision making. In our study, we use the subjective expected utility model-a well-established decision-making model in economics-as a descriptive framework. After a short survey of the brain areas and neurotransmitter systems associated with outcome-based decision making-and of the effects of aging thereon-we review a number of decision-making studies. Their general data pattern indicates that the decision-making process is changed by age: The elderly perform less efficiently than younger participants, as demonstrated, for instance, by the smaller total rewards that the elderly acquire in lab tasks. These findings are accounted for in terms of age-related deficiencies in the probability and value parameters of the subjective expected utility model. Finally, we discuss some implications and suggestions for future research.

  4. Context is everything or how could I have been that stupid?

    PubMed

    Croskerry, Pat

    2009-01-01

    Dual Process Theory provides a useful working model of decision-making. It broadly divides decision-making into intuitive (System 1) and analytical (System 2) processes. System 1 is especially dependent on contextual cues. There appears to be a universal human tendency to contextualize information, mostly in an effort to imbue meaning but also, perhaps, to conserve cognitive energy. Most decision errors occur in System 1, and this has two major implications. The first is that insufficient account may have been taken out of context when the original decision was made. Secondly, in trying to learn from decision failures, we need the highest fidelity of context reconstruction as possible. It should be appreciated that learning from past events is inevitably an imperfect process. Retrospective investigations, such as root-cause analysis, critical incident review, morbidity and mortality rounds and legal investigations, all suffer the limitation that they cannot faithfully reconstruct the context in which decisions were made and from which actions followed.

  5. Examining Whether Learning Space Affects the Retention of Experiential Knowledge

    ERIC Educational Resources Information Center

    Montgomery, Robert A.; Millenbah, Kelly F.

    2011-01-01

    Experiential learning describes structured educational opportunities that allow students to physically interact with the course material. This pedagogical technique promotes critical thinking, decision making, problem solving, and increases the retention of knowledge. Given that experiential learning can be employed in a variety of learning spaces…

  6. Supporting Collaboration with Technology: Does Shared Cognition Lead to Co-Regulation in Medicine?

    ERIC Educational Resources Information Center

    Lajoie, Susanne P.; Lu, Jingyan

    2012-01-01

    The theoretical distinctions between metacognition, self-regulation and self-regulated learning are often blurred which makes the definition of co-regulation in group learning situations even more difficult. We have started to explore co-regulation in the context of decision making in simulated emergencies where medical teams work together to…

  7. "What Would Make This a Successful Year for You?" How Students Define Success in College

    ERIC Educational Resources Information Center

    Jennings, Nancy; Lovett, Suzanne; Cuba, Lee; Swingle, Joe; Lindkvist, Heather

    2013-01-01

    The New England Consortium on Assessment and Student Learning (NECASL) seeks to understand how students make important decisions during college, assess the extent to which institutional policies and practices foster student learning, and modify those policies and practices accordingly. In this article, the authors analyze interviews with a…

  8. People and Decisions.

    ERIC Educational Resources Information Center

    Fortney, Nancy D.; Glover, Kathy H.

    1979-01-01

    Suggests that social studies classroom teachers should use the process of rational decision making to teach students how to think at higher intellectual levels, become more creative, clarify values, and increase moral development. Learning activities are described. (DB)

  9. Optimization as a Reasoning Strategy for Dealing with Socioscientific Decision-Making Situations

    ERIC Educational Resources Information Center

    Papadouris, Nicos

    2012-01-01

    This paper reports on an attempt to help 12-year-old students develop a specific optimization strategy for selecting among possible solutions in socioscientific decision-making situations. We have developed teaching and learning materials for elaborating this strategy, and we have implemented them in two intact classes (N = 48). Prior to and after…

  10. Ethical Decision Making: A Teaching and Learning Model for Graduate Students and New Professionals

    ERIC Educational Resources Information Center

    McDonald, William M.; Ebelhar, Marcus Walker; Orehovec, Elizabeth R.; Sanderson, Robyn H.

    2006-01-01

    Student affairs practitioners are inundated with a variety of ethical considerations when making day-to-day decisions regarding the welfare of students and colleagues. There is every reason to believe that confronting ethical issues will be an increasingly difficult issue for student affairs professionals in the future. This article provides a…

  11. Wrestling the Devil in the Details: An Early Look at Restructuring in California

    ERIC Educational Resources Information Center

    Scott, Caitlin

    2006-01-01

    To learn more about district and school decision making for No Child Left Behind (NCLB) restructuring, the Center on Education Policy (CEP) turned to California, a state with a substantial number of schools in restructuring and several state and regional supports for making decisions about restructuring. In the summer and fall of 2005, CEP…

  12. Caring Leadership Applied in the Classroom to Embrace the Needs of Students

    ERIC Educational Resources Information Center

    Journal of College Teaching & Learning, 2013

    2013-01-01

    On a daily basis, teachers make important decisions that impact the learning and growth process of student development. One of many important decisions that teachers make pertains to the methods used to impart knowledge to students while maintaining discipline and order in a caring manner. Using literature and secondary sources, the author…

  13. Longitudinal Analysis Technique to Assist School Leaders in Making Critical Curriculum and Instruction Decisions for School Improvement

    ERIC Educational Resources Information Center

    Bigham, Gary D.; Riney, Mark R.

    2017-01-01

    To meet the constantly changing needs of schools and diverse learners, educators must frequently monitor student learning, revise curricula, and improve instruction. Consequently, it is critical that careful analyses of student performance data are ongoing components of curriculum decision-making processes. The primary purpose of this study is to…

  14. A Developmental Study Examining the Value, Effectiveness, and Quality of a Data Literacy Intervention

    ERIC Educational Resources Information Center

    Rogers, Michelle Antionette

    2015-01-01

    Previous research indicates that pre- and in-service teachers are not receiving adequate training to implement data-informed instructional decision making. This is problematic given the promise this decision making process holds for improving instruction and student learning. At the same time, many educators do not see the value of different types…

  15. Teachers' Thoughts on Student Decision Making during Engineering Design Lessons

    ERIC Educational Resources Information Center

    Meyer, Helen

    2018-01-01

    In this paper, I share the results of a study of teachers' ideas about student decision-making at entry into a professional development program to integrate engineering into their instruction. The framework for the Engineering Design Process (EDP) was based on a Challenge-Based Learning (CBL) model. The EDP embedded within the CBL model suggests…

  16. Decision-Making in a Changing World: A Study in Autism Spectrum Disorders

    ERIC Educational Resources Information Center

    Robic, S.; Sonié, S.; Fonlupt, P.; Henaff, M.-A.; Touil, N.; Coricelli, G.; Mattout, J.; Schmitz, C.

    2015-01-01

    To learn to deal with the unexpected is essential to adaptation to a social, therefore often unpredictable environment. Fourteen adults with autism spectrum disorders (ASD) and 15 controls underwent a decision-making task aimed at investigating the influence of either a social or a non-social environment, and its interaction with either a stable…

  17. Anarchist, Neoliberal, & Democratic Decision-Making: Deepening the Joy in Learning and Teaching

    ERIC Educational Resources Information Center

    Briscoe, Felecia M.

    2012-01-01

    Using a critical postmodern framework, this article analyzes the relationship of the decision-making processes of anarchism and neoliberalism to that of deep democracy. Anarchist processes are found to share common core principals with deep democracy; but neoliberal processes are found to be antithetical to deep democracy. To increase the joy in…

  18. Career Instruments and High School Students with Learning Disabilities: Support for the Utility of Three Vocational Measures

    ERIC Educational Resources Information Center

    Dipeolu, Abiola O.

    2007-01-01

    Conventional wisdom in the area of assessment strongly supports the notion that instruments used for vocational or career decision-making purposes should possess sound psychometric properties. This study is a preliminary attempt to examine the reliability and validity of three important career decision-making measures administered to high school…

  19. A Successful Implementation Strategy to Support Adoption of Decision Making in Mental Health Services.

    PubMed

    MacDonald-Wilson, Kim L; Hutchison, Shari L; Karpov, Irina; Wittman, Paul; Deegan, Patricia E

    2017-04-01

    Individual involvement in treatment decisions with providers, often through the use of decision support aids, improves quality of care. This study investigates an implementation strategy to bring decision support to community mental health centers (CMHC). Fifty-two CMHCs implemented a decision support toolkit supported by a 12-month learning collaborative using the Breakthrough Series model. Participation in learning collaborative activities was high, indicating feasibility of the implementation model. Progress by staff in meeting process aims around utilization of components of the toolkit improved significantly over time (p < .0001). Survey responses by individuals in service corroborate successful implementation. Community-based providers were able to successfully implement decision support in mental health services as evidenced by improved process outcomes and sustained practices over 1 year through the structure of the learning collaborative model.

  20. Mobile learning app: A novel method to teach clinical decision making in prosthodontics.

    PubMed

    Deshpande, Saee; Chahande, Jaishree; Rathi, Akhil

    2017-01-01

    Prosthodontics involves replacing lost dentofacial structures using artificial substitutes. Due to availability of many materials and techniques, clinician's clinical decision-making regarding appropriate selection of prosthesis requires critical thinking abilities and is demanding. Especially during graduate training years, learners do not receive the exposure to a variety of cases, thus their clinical reasoning skills are not developed optimally. Therefore, using the trend of incorporating technology in education, we developed a mobile learning app for this purpose. The aim of this study was to evaluate learners' perceptions of this app's utility and impact on their clinical decision-making skills. After taking informed consent, interns of the Department of Prosthodontics of VSPM Dental College, Nagpur, India, during the academic year May 2015-May 2016 were sent the link for the app to be installed in their Android smartphones. Their perceptions were recorded on a feedback questionnaire using 5-point Likert scale. The script concordance test (SCT) was used to check for changes in clinical reasoning abilities. Out of 120 students who were sent the link, 102 downloaded the link and 92 completed the feedback questionnaire and appeared for the SCT (response rate: 76%). The overall response to the app was positive for more than two-thirds of interns, who reported a greater confidence in their clinical decision-making around prostheses through this app and 94% of the students felt that this app should be regularly used along with conventional teaching techniques. Mean SCT scores were pretest 41.5 (±1.7) and posttest 63 (±2.4) (P < 0.005). Clinical decision-making in prosthodontics, a mobile learning app, is an effective way to improve clinical reasoning skills for planning prosthodontic rehabilitation. It is well received by students.

  1. Agency and responsibility in adolescent students: A challenge for the societies of tomorrow.

    PubMed

    Mameli, Consuelo; Molinari, Luisa; Passini, Stefano

    2018-02-23

    The literature in educational psychology converges on the idea that students should take an active and accountable position in their learning processes. Nevertheless, there is still a lack of research that has systematically put the constructs of agency and responsibility at the core of their interests. In this study, we explore whether good experiences at school - here conceptualized as the general level of basic needs fulfilment and interpersonal justice - impact on student agency and responsibility, which in turn are considered as possible mediators between a good educational experience and two outcome measures, that is, academic achievement and career decision-making self-efficacy. The study was held on a sample of 911 high school students equally distributed between males and females. Data were collected through the use of a questionnaire comprising six measures assessing students' basic psychological need fulfilment, interpersonal justice, agentic engagement, responsibility for learning, academic achievement, and career decision-making self-efficacy. Structural equation modelling indicated that basic needs fulfilment positively predicts agency, responsibility, academic achievement, and career decision-making self-efficacy. Interpersonal justice positively predicts responsibility. The indirect effect from basic psychological needs on career decision-making self-efficacy through the mediating effects of student agentic engagement and student responsibility was significant. The indirect effect from interpersonal justice on career decision-making self-efficacy through the mediating effect of student responsibility for learning was significant. These results are commented at the light of their implications for teacher practices, as they emphasize the importance of good experiences at school for promoting in students an active civic sense and a greater accountability. © 2018 The British Psychological Society.

  2. District Decision-Makers' Considerations of Equity and Equality Related to Students' Opportunities to Learn Algebra

    ERIC Educational Resources Information Center

    Herbel-Eisenmann, Beth A.; Keazer, Lindsay; Traynor, Anne

    2018-01-01

    Background/Context: In this article we explore equity issues related to school district decision-making about students' opportunities to learn algebra. We chose algebra because of the important role it plays in the U.S. as a gatekeeper to future academic success. Current research has not yet explored issues of equity in district-level…

  3. Learning How to Think

    ERIC Educational Resources Information Center

    Deming, John C.; Cracolice, Mark S.

    2004-01-01

    Teaching strategies are becoming increasingly oriented toward guiding students' knowledge construction through cooperative learning. Enhancing students' cognitive development is a priority; students must "learn how to think." Inquiry instruction provides students with tools to make decisions based upon available evidence and an opportunity to…

  4. Neuromodulation of reward-based learning and decision making in human aging

    PubMed Central

    Eppinger, Ben; Hämmerer, Dorothea; Li, Shu-Chen

    2013-01-01

    In this paper, we review the current literature to highlight relations between age-associated declines in dopaminergic and serotonergic neuromodulation and adult age differences in adaptive goal-directed behavior. Specifically, we focus on evidence suggesting that deficits in neuromodulation contribute to older adults’ behavioral disadvantages in learning and decision making. These deficits are particularly pronounced when reward information is uncertain or the task context requires flexible adaptations to changing stimulus–reward contingencies. Moreover, emerging evidence points to age-related differences in the sensitivity to rewarding and aversive outcomes during learning and decision making if the acquisition of behavior critically depends on outcome processing. These age-related asymmetries in outcome valuation may be explained by age differences in the interplay of dopaminergic and serotonergic neuromodulation. This hypothesis is based on recent neurocomputational and psychopharmacological approaches, which suggest that dopamine and serotonin serve opponent roles in regulating the balance between approach behavior and inhibitory control. Studying adaptive regulation of behavior across the adult life span may shed new light on how the aging brain changes functionally in response to its diminishing resources. PMID:22023564

  5. Three dimensions of learning: experiential activity for engineering innovation education and research

    NASA Astrophysics Data System (ADS)

    Killen, Catherine P.

    2015-09-01

    This paper outlines a novel approach to engineering education research that provides three dimensions of learning through an experiential class activity. A simulated decision activity brought current research into the classroom, explored the effect of experiential activity on learning outcomes and contributed to the research on innovation decision making. The 'decision task' was undertaken by more than 480 engineering students. It increased their reported measures of learning and retention by an average of 0.66 on a five-point Likert scale, and revealed positive correlations between attention, enjoyment, ongoing interest and learning and retention. The study also contributed to innovation management research by revealing the influence of different data visualisation methods on decision quality, providing an example of research-integrated education that forms part of the research process. Such a dovetailing of different research studies demonstrates how engineering educators can enhance educational impact while multiplying the outcomes from their research efforts.

  6. Anticipatory stress influences decision making under explicit risk conditions.

    PubMed

    Starcke, Katrin; Wolf, Oliver T; Markowitsch, Hans J; Brand, Matthias

    2008-12-01

    Recent research has suggested that stress may affect memory, executive functioning, and decision making on the basis of emotional feedback processing. The current study examined whether anticipatory stress affects decision making measured with the Game of Dice Task (GDT), a decision-making task with explicit and stable rules that taps both executive functioning and feedback learning. The authors induced stress in 20 participants by having them anticipate giving a public speech and also examined 20 comparison subjects. The authors assessed the level of stress with questionnaires and endocrine markers (salivary cortisol and alpha-amylase), both revealing that speech anticipation led to increased stress. Results of the GDT showed that participants under stress scored significantly lower than the comparison group and that GDT performance was negatively correlated with the increase of cortisol. Our results indicate that stress can lead to disadvantageous decision making even when explicit and stable information about outcome contingencies is provided.

  7. Training of perceptual-cognitive skills in offside decision making.

    PubMed

    Catteeuw, Peter; Gilis, Bart; Jaspers, Arne; Wagemans, Johan; Helsen, Werner

    2010-12-01

    This study investigates the effect of two off-field training formats to improve offside decision making. One group trained with video simulations and another with computer animations. Feedback after every offside situation allowed assistant referees to compensate for the consequences of the flash-lag effect and to improve their decision-making accuracy. First, response accuracy improved and flag errors decreased for both training groups implying that training interventions with feedback taught assistant referees to better deal with the flash-lag effect. Second, the results demonstrated no effect of format, although assistant referees rated video simulations higher for fidelity than computer animations. This implies that a cognitive correction to a perceptual effect can be learned also when the format does not correspond closely with the original perceptual situation. Off-field offside decision-making training should be considered as part of training because it is a considerable help to gain more experience and to improve overall decision-making performance.

  8. Relationship between Student Pharmacist Decision Making Preferences and Experiential Learning.

    PubMed

    Williams, Charlene R; McLaughlin, Jacqueline E; Cox, Wendy C; Shepherd, Greene

    2016-09-25

    Objective. To determine if student pharmacists' preferences towards experiential and rational thinking are associated with performance on advanced pharmacy practice experiences (APPEs) and whether thinking style preference changes following APPEs. Methods. The Rational Experiential Inventory (REI), a validated survey of thinking style, was administered to student pharmacists before starting APPEs and re-administered after completing APPEs. APPE grades were compared to initial REI scores. Results. Rational Experiential Inventory scores remained consistent before and after APPEs. Overall, APPE grades were independent of REI scores. In a regression model, the REI experiential score was a significant negative predictor of hospital APPE grades. Conclusion. These findings suggest that overall APPE performance is independent of decision-making preference, and decision-making style does not change following immersion into APPEs. Instead of targeting teaching strategies towards a specific decision-making style, preceptors may use pedagogical approaches that promote sound clinical decision-making skills through critical thinking and reflection.

  9. Who Chokes Under Pressure? The Big Five Personality Traits and Decision-Making under Pressure.

    PubMed

    Byrne, Kaileigh A; Silasi-Mansat, Crina D; Worthy, Darrell A

    2015-02-01

    The purpose of the present study was to examine whether the Big Five personality factors could predict who thrives or chokes under pressure during decision-making. The effects of the Big Five personality factors on decision-making ability and performance under social (Experiment 1) and combined social and time pressure (Experiment 2) were examined using the Big Five Personality Inventory and a dynamic decision-making task that required participants to learn an optimal strategy. In Experiment 1, a hierarchical multiple regression analysis showed an interaction between neuroticism and pressure condition. Neuroticism negatively predicted performance under social pressure, but did not affect decision-making under low pressure. Additionally, the negative effect of neuroticism under pressure was replicated using a combined social and time pressure manipulation in Experiment 2. These results support distraction theory whereby pressure taxes highly neurotic individuals' cognitive resources, leading to sub-optimal performance. Agreeableness also negatively predicted performance in both experiments.

  10. Relationship between Student Pharmacist Decision Making Preferences and Experiential Learning

    PubMed Central

    McLaughlin, Jacqueline E.; Cox, Wendy C.; Shepherd, Greene

    2016-01-01

    Objective. To determine if student pharmacists’ preferences towards experiential and rational thinking are associated with performance on advanced pharmacy practice experiences (APPEs) and whether thinking style preference changes following APPEs. Methods. The Rational Experiential Inventory (REI), a validated survey of thinking style, was administered to student pharmacists before starting APPEs and re-administered after completing APPEs. APPE grades were compared to initial REI scores. Results. Rational Experiential Inventory scores remained consistent before and after APPEs. Overall, APPE grades were independent of REI scores. In a regression model, the REI experiential score was a significant negative predictor of hospital APPE grades. Conclusion. These findings suggest that overall APPE performance is independent of decision-making preference, and decision-making style does not change following immersion into APPEs. Instead of targeting teaching strategies towards a specific decision-making style, preceptors may use pedagogical approaches that promote sound clinical decision-making skills through critical thinking and reflection. PMID:27756927

  11. Modeling Search Behaviors during the Acquisition of Expertise in a Sequential Decision-Making Task.

    PubMed

    Moënne-Loccoz, Cristóbal; Vergara, Rodrigo C; López, Vladimir; Mery, Domingo; Cosmelli, Diego

    2017-01-01

    Our daily interaction with the world is plagued of situations in which we develop expertise through self-motivated repetition of the same task. In many of these interactions, and especially when dealing with computer and machine interfaces, we must deal with sequences of decisions and actions. For instance, when drawing cash from an ATM machine, choices are presented in a step-by-step fashion and a specific sequence of choices must be performed in order to produce the expected outcome. But, as we become experts in the use of such interfaces, is it possible to identify specific search and learning strategies? And if so, can we use this information to predict future actions? In addition to better understanding the cognitive processes underlying sequential decision making, this could allow building adaptive interfaces that can facilitate interaction at different moments of the learning curve. Here we tackle the question of modeling sequential decision-making behavior in a simple human-computer interface that instantiates a 4-level binary decision tree (BDT) task. We record behavioral data from voluntary participants while they attempt to solve the task. Using a Hidden Markov Model-based approach that capitalizes on the hierarchical structure of behavior, we then model their performance during the interaction. Our results show that partitioning the problem space into a small set of hierarchically related stereotyped strategies can potentially capture a host of individual decision making policies. This allows us to follow how participants learn and develop expertise in the use of the interface. Moreover, using a Mixture of Experts based on these stereotyped strategies, the model is able to predict the behavior of participants that master the task.

  12. Using Data to Understand How to Better Design Adaptive Learning

    ERIC Educational Resources Information Center

    Liu, Min; Kang, Jina; Zou, Wenting; Lee, Hyeyeon; Pan, Zilong; Corliss, Stephanie

    2017-01-01

    There is much enthusiasm in higher education about the benefits of adaptive learning and using big data to investigate learning processes to make data-informed educational decisions. The benefits of adaptive learning to achieve personalized learning are obvious. Yet, there lacks evidence-based research to understand how data such as user behavior…

  13. Case-based ethics instruction: the influence of contextual and individual factors in case content on ethical decision-making.

    PubMed

    Bagdasarov, Zhanna; Thiel, Chase E; Johnson, James F; Connelly, Shane; Harkrider, Lauren N; Devenport, Lynn D; Mumford, Michael D

    2013-09-01

    Cases have been employed across multiple disciplines, including ethics education, as effective pedagogical tools. However, the benefit of case-based learning in the ethics domain varies across cases, suggesting that not all cases are equal in terms of pedagogical value. Indeed, case content appears to influence the extent to which cases promote learning and transfer. Consistent with this argument, the current study explored the influences of contextual and personal factors embedded in case content on ethical decision-making. Cases were manipulated to include a clear description of the social context and the goals of the characters involved. Results indicated that social context, specifically the description of an autonomy-supportive environment, facilitated execution of sense making processes and resulted in greater decision ethicality. Implications for designing optimal cases and case-based training programs are discussed.

  14. Deal or No Deal: using games to improve student learning, retention and decision-making

    NASA Astrophysics Data System (ADS)

    Chow, Alan F.; Woodford, Kelly C.; Maes, Jeanne

    2011-03-01

    Student understanding and retention can be enhanced and improved by providing alternative learning activities and environments. Education theory recognizes the value of incorporating alternative activities (games, exercises and simulations) to stimulate student interest in the educational environment, enhance transfer of knowledge and improve learned retention with meaningful repetition. In this case study, we investigate using an online version of the television game show, 'Deal or No Deal', to enhance student understanding and retention by playing the game to learn expected value in an introductory statistics course, and to foster development of critical thinking skills necessary to succeed in the modern business environment. Enhancing the thinking process of problem solving using repetitive games should also improve a student's ability to follow non-mathematical problem-solving processes, which should improve the overall ability to process information and make logical decisions. Learning and retention are measured to evaluate the success of the students' performance.

  15. Fostering Synergies Among Organizations to put Climate in Context for Use in Decision Making

    NASA Astrophysics Data System (ADS)

    Garfin, G. M.; Parris, A.; Dow, K.; Meyer, R.; Close, S.

    2016-12-01

    Making science usable for decision making requires a knowledge of the social and institutional contexts of decision making, an ability to develop or tap into networks for sharing information and developing knowledge, a capacity for innovating or providing services, and a program for social learning to inform decisions and improve the processes of engagement and collaboration (i.e., mechanisms for feedback, evaluation, and changes in policy or practices). Active participation by and partnerships between researchers, practitioners, and decision-makers provides a foundation for making progress in each of the aforementioned areas of endeavor. In twenty years of incubating experimental climate services, the NOAA Regional Integrated Sciences and Assessments program offers not a few ideas and examples of practices to foster synergies among organizations, that result in tangible benefits to decision-makers. Strategies include (a) designing explicit mutual learning through temporary institutions, such as workshop series, in order to develop social capital and knowledge networks (e.g., to co-develop and disseminate experimental forecasts); (b) articulating ground rules, roles, and responsibilities in managing the boundary between scientists and practitioners (e.g., in multi-partner climate adaptation planning processes); and (c) cross-training between scientists and practitioners, by embedding team members in other organizations or recruiting members from those organizations (e.g., Cooperative Extension). A promising strategy is boundary chaining, pioneered by the Great Lakes Integrated Sciences and Assessments, in which science information and service providers partner with other boundary organizations, to leverage networks, expertise, resources, and to reduce transaction costs. Partners with complementary strengths and roles can then, work iteratively and synergize to mediate the co-production of a combination of services for decision making, such as data and information, facilitation, and evaluation.

  16. Development of a novel task for investigating decision making in a social context following traumatic brain injury.

    PubMed

    Kelly, Michelle; McDonald, Skye; Kellett, David

    2014-01-01

    Examination of social cognition as a target for assessment and intervention is beginning to gain momentum in a number of illnesses and acquired disorders. One facet of social cognition is decision making within interpersonal situations. This skill forms an important part of our everyday lives and is commonly impaired in those with neurological and mental health conditions. A novel task was developed to allow the assessment of decision making specifically within a social context and was examined within a group known to experience this difficulty. Participants with severe traumatic brain injury (TBI) were compared to healthy control participants on the Social Decision Making Task (SDMT), which required the participant to learn who the "friendly" players were in a game of toss. Participants also completed a nonsocial decision-making task, the Iowa Gambling Task (IGT) as well as a battery of neuropsychological tests and social cognition tasks. Current social functioning was also examined. Consistent with predictions, the TBI group made poorer decisions on the SDMT than the control group; however, group differences were not evident on the IGT. No significant relationships were observed between the SDMT and either measures of executive functioning (including working memory and reversal learning) or social cognition (including emotion recognition and theory of mind). Performance on the SDMT and the IGT were not associated, suggesting that the two tasks measure different constructs. The SDMT offers a novel way of examining decision making within a social context following TBI and may also be useful in other populations known to have specific social cognition impairment. Future research should aim to provide further clarification of the mechanisms of action and neuroanatomical correlates of poor performance on this task.

  17. Who do you trust? The impact of facial emotion and behaviour on decision making

    PubMed Central

    Campellone, Timothy R.; Kring, Ann M.

    2014-01-01

    During social interactions, we use available information to guide our decisions, including behaviour and emotional displays. In some situations, behaviour and emotional displays may be incongruent, complicating decision making. This study had two main aims: first, to investigate the independent contributions of behaviour and facial displays of emotion on decisions to trust, and, second, to examine what happens when the information being signalled by a facial display is incongruent with behaviour. Participants played a modified version of the Trust Game in which they learned simulated players’ behaviour with or without concurrent displays of facial emotion. Results indicated that displays of anger, but not happiness, influenced decisions to trust during initial encounters. Over the course of repeated interactions, however, emotional displays consistent with an established pattern of behaviour made independent contributions to decision making, strengthening decisions to trust. When facial display and behaviour were incongruent, participants used current behaviour to inform decision making. PMID:23017055

  18. Rodent models of adaptive decision making.

    PubMed

    Izquierdo, Alicia; Belcher, Annabelle M

    2012-01-01

    Adaptive decision making affords the animal the ability to respond quickly to changes in a dynamic environment: one in which attentional demands, cost or effort to procure the reward, and reward contingencies change frequently. The more flexible the organism is in adapting choice behavior, the more command and success the organism has in navigating its environment. Maladaptive decision making is at the heart of much neuropsychiatric disease, including addiction. Thus, a better understanding of the mechanisms that underlie normal, adaptive decision making helps achieve a better understanding of certain diseases that incorporate maladaptive decision making as a core feature. This chapter presents three general domains of methods that the experimenter can manipulate in animal decision-making tasks: attention, effort, and reward contingency. Here, we present detailed methods of rodent tasks frequently employed within these domains: the Attentional Set-Shift Task, Effortful T-maze Task, and Visual Discrimination Reversal Learning. These tasks all recruit regions within the frontal cortex and the striatum, and performance is heavily modulated by the neurotransmitter dopamine, making these assays highly valid measures in the study of psychostimulant addiction.

  19. Cognitive Tools for Assessment and Learning in a High Information Flow Environment.

    ERIC Educational Resources Information Center

    Lajoie, Susanne P.; Azevedo, Roger; Fleiszer, David M.

    1998-01-01

    Describes the development of a simulation-based intelligent tutoring system for nurses working in a surgical intensive care unit. Highlights include situative learning theories and models of instruction, modeling expertise, complex decision making, linking theories of learning to the design of computer-based learning environments, cognitive task…

  20. Numbers Are Not Enough. Why e-Learning Analytics Failed to Inform an Institutional Strategic Plan

    ERIC Educational Resources Information Center

    Macfadyen, Leah P.; Dawson, Shane

    2012-01-01

    Learning analytics offers higher education valuable insights that can inform strategic decision-making regarding resource allocation for educational excellence. Research demonstrates that learning management systems (LMSs) can increase student sense of community, support learning communities and enhance student engagement and success, and LMSs…

  1. The Power of Service-Learning.

    ERIC Educational Resources Information Center

    McCarthy, Mary H.; Corbin, Linda

    2003-01-01

    Describes key elements of service learning: response to the community, student-led decision-making, analytical reflection. Includes a case study of service learning in the Hudson, Massachusetts, Public School District, the main goal of which is to provide students with opportunities to learn the core values of empathy, ethics, and service. (PKP)

  2. Modeling Learner Situation Awareness in Collaborative Mobile Web 2.0 Learning

    ERIC Educational Resources Information Center

    Norman, Helmi; Nordin, Norazah; Din, Rosseni; Ally, Mohamed

    2016-01-01

    The concept of situation awareness is essential in enhancing collaborative learning. Learners require information from different awareness aspects to deduce a learning situation for decision-making. Designing learning environments that assist learners to understand situation awareness via monitoring actions and reaction of other learners has been…

  3. Conflict between place and response navigation strategies: effects on vicarious trial and error (VTE) behaviors.

    PubMed

    Schmidt, Brandy; Papale, Andrew; Redish, A David; Markus, Etan J

    2013-02-15

    Navigation can be accomplished through multiple decision-making strategies, using different information-processing computations. A well-studied dichotomy in these decision-making strategies compares hippocampal-dependent "place" and dorsal-lateral striatal-dependent "response" strategies. A place strategy depends on the ability to flexibly respond to environmental cues, while a response strategy depends on the ability to quickly recognize and react to situations with well-learned action-outcome relationships. When rats reach decision points, they sometimes pause and orient toward the potential routes of travel, a process termed vicarious trial and error (VTE). VTE co-occurs with neurophysiological information processing, including sweeps of representation ahead of the animal in the hippocampus and transient representations of reward in the ventral striatum and orbitofrontal cortex. To examine the relationship between VTE and the place/response strategy dichotomy, we analyzed data in which rats were cued to switch between place and response strategies on a plus maze. The configuration of the maze allowed for place and response strategies to work competitively or cooperatively. Animals showed increased VTE on trials entailing competition between navigational systems, linking VTE with deliberative decision-making. Even in a well-learned task, VTE was preferentially exhibited when a spatial selection was required, further linking VTE behavior with decision-making associated with hippocampal processing.

  4. A brief educational intervention to teach residents shared decision making in the intensive care unit.

    PubMed

    Yuen, Jacqueline K; Mehta, Sonal S; Roberts, Jordan E; Cooke, Joseph T; Reid, M Carrington

    2013-05-01

    Effective communication is essential for shared decision making with families of critically ill patients in the intensive care unit (ICU), yet there is limited evidence on effective strategies to teach these skills. The study's objective was to pilot test an educational intervention to teach internal medicine interns skills in discussing goals of care and treatment decisions with families of critically ill patients using the shared decision making framework. The intervention consisted of a PowerPoint online module followed by a four-hour workshop implemented at a retreat for medicine interns training at an urban, academic medical center. Participants (N=33) completed post-intervention questionnaires that included self-assessed skills learned, an open-ended question on the most important learning points from the workshop, and retrospective pre- and post-workshop comfort level with ICU communication skills. Participants rated their satisfaction with the workshop. Twenty-nine interns (88%) completed the questionnaires. Important self-assessed communication skills learned reflect key components of shared decision making, which include assessing the family's understanding of the patient's condition (endorsed by 100%) and obtaining an understanding of the patient/family's perspectives, values, and goals (100%). Interns reported significant improvement in their comfort level with ICU communication skills (pre 3.26, post 3.73 on a five-point scale, p=0.004). Overall satisfaction with the intervention was high (mean 4.45 on a five-point scale). The findings suggest that a brief intervention designed to teach residents communication skills in conducting goals of care and treatment discussions in the ICU is feasible and can improve their comfort level with these conversations.

  5. Annual Research Review: Transdiagnostic neuroscience of child and adolescent mental disorders--differentiating decision making in attention-deficit/hyperactivity disorder, conduct disorder, depression, and anxiety.

    PubMed

    Sonuga-Barke, Edmund J S; Cortese, Samuele; Fairchild, Graeme; Stringaris, Argyris

    2016-03-01

    Ineffective decision making is a major source of everyday functional impairment and reduced quality of life for young people with mental disorders. However, very little is known about what distinguishes decision making by individuals with different disorders or the neuropsychological processes or brain systems underlying these. This is the focus of the current review. We first propose a neuroeconomic model of the decision-making process with separate stages for the prechoice evaluation of expected utility of future options; choice execution and postchoice management; the appraisal of outcome against expectation; and the updating of value estimates to guide future decisions. According to the proposed model, decision making is mediated by neuropsychological processes operating within three domains: (a) self-referential processes involved in autobiographical reflection on past, and prospection about future, experiences; (b) executive functions, such as working memory, inhibition, and planning, that regulate the implementation of decisions; and (c) processes involved in value estimation and outcome appraisal and learning. These processes are underpinned by the interplay of multiple brain networks, especially medial and lateralized cortical components of the default mode network, dorsal corticostriatal circuits underpinning higher order cognitive and behavioral control, and ventral frontostriatal circuits, connecting to brain regions implicated in emotion processing, that control valuation and learning processes. Based on clinical insights and considering each of the decision-making stages in turn, we outline disorder-specific hypotheses about impaired decision making in four childhood disorders: attention-deficit/hyperactivity disorder (ADHD), conduct disorder (CD), depression, and anxiety. We hypothesize that decision making in ADHD is deficient (i.e. inefficient, insufficiently reflective, and inconsistent) and impulsive (biased toward immediate over delayed alternatives). In CD, it is reckless and insensitive to negative consequences. In depression, it is disengaged, perseverative, and pessimistic, while in anxiety, it is hesitant, risk-averse, and self-deprecating. A survey of current empirical indications related to these disorder-specific hypotheses highlights the limited and fragmentary nature of the evidence base and illustrates the need for a major research initiative in decision making in childhood disorders. The final section highlights a number of important additional general themes that need to be considered in future research. © 2015 The Authors. Journal of Child Psychology and Psychiatry published by John Wiley & Sons Ltd on behalf of Association for Child and Adolescent Mental Health.

  6. Mission at Mubasi - A Simulation for Leadership Development

    NASA Technical Reports Server (NTRS)

    Cummings, Pau; Aude, Steven; Fallesen, Jon

    2012-01-01

    The United States Army is investing in simulations as a way of providing practice for leader decision making. Such simulations, grounded in lessons learned from deployment experienced leaders, place less experienced and more junior leaders in challenging situations they might soon be confronted with. And given increased demands on the Army to become more efficient, while maintaining acceptable levels of mission readiness, simulations offer a cost effective complement to live field training. So too, the design parameters of such a simulation can be made to reinforce specific behavior responses which teach leaders known theory and application of effective (and ineffective) decision making. With this in mind, the Center for Army Leadership (CAL) determined that decision-making was of critical importance. Specifically, the following aspects of decision-making were viewed as particularly important for today's Army leaders: 1) Decision dilemmas, in the form of equally appealing or equally unappealing choices, such that there is no clear "right" or "wrong" choice 2) Making decisions with incomplete or ambiguous information, and 3) Predicting and experiencing second- and third-order consequences of decisions. It is decision making in such a setting or environment that Army leaders are increasingly confronted with given the full spectrum of military operations they must be prepared for. This paper details the approach and development of this decision making simulation.

  7. Decision-Making in Multiple Sclerosis Patients: A Systematic Review

    PubMed Central

    2018-01-01

    Background Multiple sclerosis (MS) is frequently associated with cognitive and behavioural deficits. A growing number of studies suggest an impact of MS on decision-making abilities. The aim of this systematic review was to assess if (1) performance of MS patients in decision-making tasks was consistently different from controls and (2) whether this modification was associated with cognitive dysfunction and emotional alterations. Methods The search was conducted on Pubmed/Medline database. 12 studies evaluating the difference between MS patients and healthy controls using validated decision-making tasks were included. Outcomes considered were quantitative (net scores) and qualitative measurements (deliberation time and learning from feedback). Results Quantitative and qualitative decision-making impairment in MS was present in 64.7% of measurements. Patients were equally impaired in tasks for decision-making under risk and ambiguity. A correlation to other cognitive functions was present in 50% of cases, with the highest associations in the domains of processing speed and attentional capacity. Conclusions In MS patients, qualitative and quantitative modifications may be present in any kind of decision-making task and can appear independently of other cognitive measures. Since decision-making abilities have a significant impact on everyday life, this cognitive aspect has an influential importance in various MS-related treatment settings. PMID:29721338

  8. Learning a New Selection Rule in Visual and Frontal Cortex.

    PubMed

    van der Togt, Chris; Stănişor, Liviu; Pooresmaeili, Arezoo; Albantakis, Larissa; Deco, Gustavo; Roelfsema, Pieter R

    2016-08-01

    How do you make a decision if you do not know the rules of the game? Models of sensory decision-making suggest that choices are slow if evidence is weak, but they may only apply if the subject knows the task rules. Here, we asked how the learning of a new rule influences neuronal activity in the visual (area V1) and frontal cortex (area FEF) of monkeys. We devised a new icon-selection task. On each day, the monkeys saw 2 new icons (small pictures) and learned which one was relevant. We rewarded eye movements to a saccade target connected to the relevant icon with a curve. Neurons in visual and frontal cortex coded the monkey's choice, because the representation of the selected curve was enhanced. Learning delayed the neuronal selection signals and we uncovered the cause of this delay in V1, where learning to select the relevant icon caused an early suppression of surrounding image elements. These results demonstrate that the learning of a new rule causes a transition from fast and random decisions to a more considerate strategy that takes additional time and they reveal the contribution of visual and frontal cortex to the learning process. © The Author 2016. Published by Oxford University Press.

  9. Neural systems analysis of decision making during goal-directed navigation.

    PubMed

    Penner, Marsha R; Mizumori, Sheri J Y

    2012-01-01

    The ability to make adaptive decisions during goal-directed navigation is a fundamental and highly evolved behavior that requires continual coordination of perceptions, learning and memory processes, and the planning of behaviors. Here, a neurobiological account for such coordination is provided by integrating current literatures on spatial context analysis and decision-making. This integration includes discussions of our current understanding of the role of the hippocampal system in experience-dependent navigation, how hippocampal information comes to impact midbrain and striatal decision making systems, and finally the role of the striatum in the implementation of behaviors based on recent decisions. These discussions extend across cellular to neural systems levels of analysis. Not only are key findings described, but also fundamental organizing principles within and across neural systems, as well as between neural systems functions and behavior, are emphasized. It is suggested that studying decision making during goal-directed navigation is a powerful model for studying interactive brain systems and their mediation of complex behaviors. Copyright © 2011. Published by Elsevier Ltd.

  10. The orbitofrontal cortex and beyond: from affect to decision-making.

    PubMed

    Rolls, Edmund T; Grabenhorst, Fabian

    2008-11-01

    The orbitofrontal cortex represents the reward or affective value of primary reinforcers including taste, touch, texture, and face expression. It learns to associate other stimuli with these to produce representations of the expected reward value for visual, auditory, and abstract stimuli including monetary reward value. The orbitofrontal cortex thus plays a key role in emotion, by representing the goals for action. The learning process is stimulus-reinforcer association learning. Negative reward prediction error neurons are related to this affective learning. Activations in the orbitofrontal cortex correlate with the subjective emotional experience of affective stimuli, and damage to the orbitofrontal cortex impairs emotion-related learning, emotional behaviour, and subjective affective state. With an origin from beyond the orbitofrontal cortex, top-down attention to affect modulates orbitofrontal cortex representations, and attention to intensity modulates representations in earlier cortical areas of the physical properties of stimuli. Top-down word-level cognitive inputs can bias affective representations in the orbitofrontal cortex, providing a mechanism for cognition to influence emotion. Whereas the orbitofrontal cortex provides a representation of reward or affective value on a continuous scale, areas beyond the orbitofrontal cortex such as the medial prefrontal cortex area 10 are involved in binary decision-making when a choice must be made. For this decision-making, the orbitofrontal cortex provides a representation of each specific reward in a common currency.

  11. Beyond negative valence: 2-week administration of a serotonergic antidepressant enhances both reward and effort learning signals.

    PubMed

    Scholl, Jacqueline; Kolling, Nils; Nelissen, Natalie; Browning, Michael; Rushworth, Matthew F S; Harmer, Catherine J

    2017-02-01

    To make good decisions, humans need to learn about and integrate different sources of appetitive and aversive information. While serotonin has been linked to value-based decision-making, its role in learning is less clear, with acute manipulations often producing inconsistent results. Here, we show that when the effects of a selective serotonin reuptake inhibitor (SSRI, citalopram) are studied over longer timescales, learning is robustly improved. We measured brain activity with functional magnetic resonance imaging (fMRI) in volunteers as they performed a concurrent appetitive (money) and aversive (effort) learning task. We found that 2 weeks of citalopram enhanced reward and effort learning signals in a widespread network of brain regions, including ventromedial prefrontal and anterior cingulate cortex. At a behavioral level, this was accompanied by more robust reward learning. This suggests that serotonin can modulate the ability to learn via a mechanism that is independent of stimulus valence. Such effects may partly underlie SSRIs' impact in treating psychological illnesses. Our results highlight both a specific function in learning for serotonin and the importance of studying its role across longer timescales.

  12. Physics faculty beliefs and values about the teaching and learning of problem solving. II. Procedures for measurement and analysis

    NASA Astrophysics Data System (ADS)

    Henderson, Charles; Yerushalmi, Edit; Kuo, Vince H.; Heller, Kenneth; Heller, Patricia

    2007-12-01

    To identify and describe the basis upon which instructors make curricular and pedagogical decisions, we have developed an artifact-based interview and an analysis technique based on multilayered concept maps. The policy capturing technique used in the interview asks instructors to make judgments about concrete instructional artifacts similar to those they likely encounter in their teaching environment. The analysis procedure alternatively employs both an a priori systems view analysis and an emergent categorization to construct a multilayered concept map, which is a hierarchically arranged set of concept maps where child maps include more details than parent maps. Although our goal was to develop a model of physics faculty beliefs about the teaching and learning of problem solving in the context of an introductory calculus-based physics course, the techniques described here are applicable to a variety of situations in which instructors make decisions that influence teaching and learning.

  13. Ventral striatal activity links adversity and reward processing in children.

    PubMed

    Kamkar, Niki H; Lewis, Daniel J; van den Bos, Wouter; Morton, J Bruce

    2017-08-01

    Adversity impacts many aspects of psychological and physical development including reward-based learning and decision-making. Mechanisms relating adversity and reward processing in children, however, remain unclear. Here, we show that adversity is associated with potentiated learning from positive outcomes and impulsive decision-making, but unrelated to learning from negative outcomes. We then show via functional magnetic resonance imaging that the link between adversity and reward processing is partially mediated by differences in ventral striatal response to rewards. The findings suggest that early-life adversity is associated with alterations in the brain's sensitivity to rewards accounting, in part, for the link between adversity and altered reward processing in children. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  14. Intelligent deflection routing in buffer-less networks.

    PubMed

    Haeri, Soroush; Trajković, Ljiljana

    2015-02-01

    Deflection routing is employed to ameliorate packet loss caused by contention in buffer-less architectures such as optical burst-switched networks. The main goal of deflection routing is to successfully deflect a packet based only on a limited knowledge that network nodes possess about their environment. In this paper, we present a framework that introduces intelligence to deflection routing (iDef). iDef decouples the design of the signaling infrastructure from the underlying learning algorithm. It consists of a signaling and a decision-making module. Signaling module implements a feedback management protocol while the decision-making module implements a reinforcement learning algorithm. We also propose several learning-based deflection routing protocols, implement them in iDef using the ns-3 network simulator, and compare their performance.

  15. Fronto-temporal white matter connectivity predicts reversal learning errors

    PubMed Central

    Alm, Kylie H.; Rolheiser, Tyler; Mohamed, Feroze B.; Olson, Ingrid R.

    2015-01-01

    Each day, we make hundreds of decisions. In some instances, these decisions are guided by our innate needs; in other instances they are guided by memory. Probabilistic reversal learning tasks exemplify the close relationship between decision making and memory, as subjects are exposed to repeated pairings of a stimulus choice with a reward or punishment outcome. After stimulus–outcome associations have been learned, the associated reward contingencies are reversed, and participants are not immediately aware of this reversal. Individual differences in the tendency to choose the previously rewarded stimulus reveal differences in the tendency to make poorly considered, inflexible choices. Lesion studies have strongly linked reversal learning performance to the functioning of the orbitofrontal cortex, the hippocampus, and in some instances, the amygdala. Here, we asked whether individual differences in the microstructure of the uncinate fasciculus, a white matter tract that connects anterior and medial temporal lobe regions to the orbitofrontal cortex, predict reversal learning performance. Diffusion tensor imaging and behavioral paradigms were used to examine this relationship in 33 healthy young adults. The results of tractography revealed a significant negative relationship between reversal learning performance and uncinate axial diffusivity, but no such relationship was demonstrated in a control tract, the inferior longitudinal fasciculus. Our findings suggest that the uncinate might serve to integrate associations stored in the anterior and medial temporal lobes with expectations about expected value based on feedback history, computed in the orbitofrontal cortex. PMID:26150776

  16. Influence of negative affect on decision making in women with restrictive and binge-purge type anorexia nervosa.

    PubMed

    Danner, Unna N; Sternheim, Lot; Bijsterbosch, Jojanneke M; Dingemans, Alexandra E; Evers, Catharine; van Elburg, Annemarie A

    2016-05-30

    The present study aims to examine the influence of negative affect on decision making in women with anorexia nervosa (AN) compared to healthy control women and, secondly, to assess differences between the restrictive (ANR) and binge-purge (ANBP) subtypes. One hundred four women (32 with ANR, 32 with ANBP, and 40 healthy controls) participated. All women were asked to watch either a negative or a control film fragment, both followed by the Bechara Gambling Task (BGT). Before and after the fragments negative affect was measured. Additionally, relevant characteristics (e.g., overall depressive symptoms) were assessed. Differences in negative affect did not influence decision making performance. Independent of affective state, decision making was found to be impaired in women with ANBP (no learning effect on the BGT), but not in women with ANR. These findings highlight the importance of considering different AN subtypes when examining decision making processes. However, the role of negative affect on decision making remains uncertain. Since other affect related factors such as affect dysregulation may also play a role, future studies on decision making in AN should take the role of affect into account. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  17. Neural and neurochemical basis of reinforcement-guided decision making.

    PubMed

    Khani, Abbas; Rainer, Gregor

    2016-08-01

    Decision making is an adaptive behavior that takes into account several internal and external input variables and leads to the choice of a course of action over other available and often competing alternatives. While it has been studied in diverse fields ranging from mathematics, economics, ecology, and ethology to psychology and neuroscience, recent cross talk among perspectives from different fields has yielded novel descriptions of decision processes. Reinforcement-guided decision making models are based on economic and reinforcement learning theories, and their focus is on the maximization of acquired benefit over a defined period of time. Studies based on reinforcement-guided decision making have implicated a large network of neural circuits across the brain. This network includes a wide range of cortical (e.g., orbitofrontal cortex and anterior cingulate cortex) and subcortical (e.g., nucleus accumbens and subthalamic nucleus) brain areas and uses several neurotransmitter systems (e.g., dopaminergic and serotonergic systems) to communicate and process decision-related information. This review discusses distinct as well as overlapping contributions of these networks and neurotransmitter systems to the processing of decision making. We end the review by touching on neural circuitry and neuromodulatory regulation of exploratory decision making. Copyright © 2016 the American Physiological Society.

  18. Learning relative values in the striatum induces violations of normative decision making

    PubMed Central

    Klein, Tilmann A.; Ullsperger, Markus; Jocham, Gerhard

    2017-01-01

    To decide optimally between available options, organisms need to learn the values associated with these options. Reinforcement learning models offer a powerful explanation of how these values are learnt from experience. However, human choices often violate normative principles. We suggest that seemingly counterintuitive decisions may arise as a natural consequence of the learning mechanisms deployed by humans. Here, using fMRI and a novel behavioural task, we show that, when suddenly switched to novel choice contexts, participants’ choices are incongruent with values learnt by standard learning algorithms. Instead, behaviour is compatible with the decisions of an agent learning how good an option is relative to an option with which it had previously been paired. Striatal activity exhibits the characteristics of a prediction error used to update such relative option values. Our data suggest that choices can be biased by a tendency to learn option values with reference to the available alternatives. PMID:28631734

  19. Does training with 3D videos improve decision-making in team invasion sports?

    PubMed

    Hohmann, Tanja; Obelöer, Hilke; Schlapkohl, Nele; Raab, Markus

    2016-01-01

    We examined the effectiveness of video-based decision training in national youth handball teams. Extending previous research, we tested in Study 1 whether a three-dimensional (3D) video training group would outperform a two-dimensional (2D) group. In Study 2, a 3D training group was compared to a control group and a group trained with a traditional tactic board. In both studies, training duration was 6 weeks. Performance was measured in a pre- to post-retention design. The tests consisted of a decision-making task measuring quality of decisions (first and best option) and decision time (time for first and best option). The results of Study 1 showed learning effects and revealed that the 3D video group made faster first-option choices than the 2D group, but differences in the quality of options were not pronounced. The results of Study 2 revealed learning effects for both training groups compared to the control group, and faster choices in the 3D group compared to both other groups. Together, the results show that 3D video training is the most useful tool for improving choices in handball, but only in reference to decision time and not decision quality. We discuss the usefulness of a 3D video tool for training of decision-making skills outside the laboratory or gym.

  20. Maximization of Learning Speed Due to Neuronal Redundancy in Reinforcement Learning

    NASA Astrophysics Data System (ADS)

    Takiyama, Ken

    2016-11-01

    Adaptable neural activity contributes to the flexibility of human behavior, which is optimized in situations such as motor learning and decision making. Although learning signals in motor learning and decision making are low-dimensional, neural activity, which is very high dimensional, must be modified to achieve optimal performance based on the low-dimensional signal, resulting in a severe credit-assignment problem. Despite this problem, the human brain contains a vast number of neurons, leaving an open question: what is the functional significance of the huge number of neurons? Here, I address this question by analyzing a redundant neural network with a reinforcement-learning algorithm in which the numbers of neurons and output units are N and M, respectively. Because many combinations of neural activity can generate the same output under the condition of N ≫ M, I refer to the index N - M as neuronal redundancy. Although greater neuronal redundancy makes the credit-assignment problem more severe, I demonstrate that a greater degree of neuronal redundancy facilitates learning speed. Thus, in an apparent contradiction of the credit-assignment problem, I propose the hypothesis that a functional role of a huge number of neurons or a huge degree of neuronal redundancy is to facilitate learning speed.

  1. Creating a Powerful Learning Environment with Networked Mobile Learning Devices

    ERIC Educational Resources Information Center

    Crawford, Valerie M.

    2007-01-01

    Highly mobile devices can make important information available to teachers in real-time, anywhere in the classroom, and in the form of easy-to-read graphical displays that support classroom decision making. By supporting such important teaching activities, we can create a high-performance classroom that supports teachers and the art of teaching,…

  2. Web-Based Distance Learning: Substitute or Alternative to the Traditional Classroom--Making the Delivery Method Decision

    ERIC Educational Resources Information Center

    Hunt, David Marshall

    2005-01-01

    When a distance learning program administrator makes the critical choice of delivery methods, she/he needs to consider factors such as program developer centrism, international experience, cultural similarity, and desired level of control which will all be elaborated on in this article. The aim of this manuscript is to assist international…

  3. Adaptation pathways: ecoregion and land ownership influences on climate adaptation decision-making in forest management

    Treesearch

    Todd A. Ontl; Chris Swanston; Leslie A. Brandt; Patricia R. Butler; Anthony W. D’Amato; Stephen D. Handler; Maria K. Janowiak; P. Danielle Shannon

    2018-01-01

    Climate adaptation planning and implementation are likely to increase rapidly within the forest sector not only as climate continues to change but also as we intentionally learn from real-world examples. We sought to better understand how adaptation is being incorporated in land management decision-making across diverse land ownership types in the Midwest by evaluating...

  4. College Teaching: Integrating Knowledge Acquisition, Decision-Making Skills, and a Love for John Dewey.

    ERIC Educational Resources Information Center

    Woolever, Roberta

    This paper describes an undergraduate course for non-education majors which emphasizes rational decision making as advocated by John Dewey. The course, offered in 1976 by the School of Education at the University of North Carolina at Chapel Hill, had three instructional goals. These were to (1) provide students an opportunity to learn about…

  5. Role-Playing in a Consumption Context: An Experiential Learning Activity Focused on the Consumer Decision-Making Process

    ERIC Educational Resources Information Center

    Thomas, Veronica L.; Magnotta, Sarah R.; Chang, Hua; Steffes, Erin

    2018-01-01

    Instructors are faced with the challenge of teaching a significant amount of material covering a wide variety of topics in a Principles of Marketing course. In order to present the critical consumer decision-making process concept in a meaningful way while remaining mindful of time constraints, we propose a semi-structured classroom activity that…

  6. Faculty Perceptions of Shared Decision Making and the Principal's Leadership Behaviors in Secondary Schools in a Large Urban District

    ERIC Educational Resources Information Center

    Leech, Don; Fulton, Charles Ray

    2008-01-01

    The traditional roles of teachers and principals have changed and improved organizational teamwork is fostered by all members of the learning community assuming decision making roles. Toward this end, the purpose of this correlational study was to explore the relationship between teachers' perceptions of the leadership behaviors of secondary…

  7. Systems Thinking, Decision Making: What Is Known and What Needs to Be Learned

    ERIC Educational Resources Information Center

    Dawidowicz, Paula M.

    2010-01-01

    The understanding and use of systems has been studied in numerous environments, particularly among leadership and management. However, as yet it is unclear what people at large know about systems thinking, where they gained their knowledge, or how important the role they perceive it to have in their decision making processes. Through a mixed model…

  8. Making Meaningful Decisions about Time, Workload and Pedagogy in the Digital Age: The Course Resource Appraisal Model

    ERIC Educational Resources Information Center

    Kennedy, Eileen; Laurillard, Diana; Horan, Bernard; Charlton, Patricia

    2015-01-01

    This article reports on a design-based research project to create a modelling tool to analyse the costs and learning benefits involved in different modes of study. The Course Resource Appraisal Model (CRAM) provides accurate cost-benefit information so that institutions are able to make more meaningful decisions about which kind of…

  9. Developing and Testing an Online Tool for Teaching GIS Concepts Applied to Spatial Decision-Making

    ERIC Educational Resources Information Center

    Carver, Steve; Evans, Andy; Kingston, Richard

    2004-01-01

    The development and testing of a Web-based GIS e-learning resource is described. This focuses on the application of GIS for siting a nuclear waste disposal facility and the associated principles of spatial decision-making using Boolean and weighted overlay methods. Initial student experiences in using the system are analysed as part of a research…

  10. Graduate Education in Risk Analysis for Food, Agriculture, and Veterinary Medicine: Challenges and Opportunities

    ERIC Educational Resources Information Center

    Correia, Ana-Paula; Wolt, Jeffrey D.

    2010-01-01

    The notion of risk in relation to food and food production has heightened the need to educate students to effectively deal with risk in relation to decision making from a science-based perspective. Curricula and related materials were developed and adopted to support graduate learning opportunities in risk analysis and decision making as applied…

  11. Rough Set Based Splitting Criterion for Binary Decision Tree Classifiers

    DTIC Science & Technology

    2006-09-26

    Alata O. Fernandez-Maloigne C., and Ferrie J.C. (2001). Unsupervised Algorithm for the Segmentation of Three-Dimensional Magnetic Resonance Brain ...instinctual and learned responses in the brain , causing it to make decisions based on patterns in the stimuli. Using this deceptively simple process...2001. [2] Bohn C. (1997). An Incremental Unsupervised Learning Scheme for Function Approximation. In: Proceedings of the 1997 IEEE International

  12. Decision Making and Reward in Frontal Cortex

    PubMed Central

    Kennerley, Steven W.; Walton, Mark E.

    2011-01-01

    Patients with damage to the prefrontal cortex (PFC)—especially the ventral and medial parts of PFC—often show a marked inability to make choices that meet their needs and goals. These decision-making impairments often reflect both a deficit in learning concerning the consequences of a choice, as well as deficits in the ability to adapt future choices based on experienced value of the current choice. Thus, areas of PFC must support some value computations that are necessary for optimal choice. However, recent frameworks of decision making have highlighted that optimal and adaptive decision making does not simply rest on a single computation, but a number of different value computations may be necessary. Using this framework as a guide, we summarize evidence from both lesion studies and single-neuron physiology for the representation of different value computations across PFC areas. PMID:21534649

  13. Stress enhances model-free reinforcement learning only after negative outcome

    PubMed Central

    Lee, Daeyeol

    2017-01-01

    Previous studies found that stress shifts behavioral control by promoting habits while decreasing goal-directed behaviors during reward-based decision-making. It is, however, unclear how stress disrupts the relative contribution of the two systems controlling reward-seeking behavior, i.e. model-free (or habit) and model-based (or goal-directed). Here, we investigated whether stress biases the contribution of model-free and model-based reinforcement learning processes differently depending on the valence of outcome, and whether stress alters the learning rate, i.e., how quickly information from the new environment is incorporated into choices. Participants were randomly assigned to either a stress or a control condition, and performed a two-stage Markov decision-making task in which the reward probabilities underwent periodic reversals without notice. We found that stress increased the contribution of model-free reinforcement learning only after negative outcome. Furthermore, stress decreased the learning rate. The results suggest that stress diminishes one’s ability to make adaptive choices in multiple aspects of reinforcement learning. This finding has implications for understanding how stress facilitates maladaptive habits, such as addictive behavior, and other dysfunctional behaviors associated with stress in clinical and educational contexts. PMID:28723943

  14. Stress enhances model-free reinforcement learning only after negative outcome.

    PubMed

    Park, Heyeon; Lee, Daeyeol; Chey, Jeanyung

    2017-01-01

    Previous studies found that stress shifts behavioral control by promoting habits while decreasing goal-directed behaviors during reward-based decision-making. It is, however, unclear how stress disrupts the relative contribution of the two systems controlling reward-seeking behavior, i.e. model-free (or habit) and model-based (or goal-directed). Here, we investigated whether stress biases the contribution of model-free and model-based reinforcement learning processes differently depending on the valence of outcome, and whether stress alters the learning rate, i.e., how quickly information from the new environment is incorporated into choices. Participants were randomly assigned to either a stress or a control condition, and performed a two-stage Markov decision-making task in which the reward probabilities underwent periodic reversals without notice. We found that stress increased the contribution of model-free reinforcement learning only after negative outcome. Furthermore, stress decreased the learning rate. The results suggest that stress diminishes one's ability to make adaptive choices in multiple aspects of reinforcement learning. This finding has implications for understanding how stress facilitates maladaptive habits, such as addictive behavior, and other dysfunctional behaviors associated with stress in clinical and educational contexts.

  15. Student decisions about lecture attendance: do electronic course materials matter?

    PubMed

    Billings-Gagliardi, Susan; Mazor, Kathleen M

    2007-10-01

    This study explored whether first-year medical students make deliberate decisions about attending nonrequired lectures. If so, it sought to identify factors that influence these decisions, specifically addressing the potential impact of electronic materials. Medical students who completed first-year studies between 2004 and 2006 responded to an open-ended survey question about their own lecture-attendance decisions. Responses were coded to capture major themes. Students' ratings of the electronic materials were also examined. Most respondents made deliberate attendance decisions. Decisions were influenced by previous experiences with the lecturer, predictions of what would occur during the session itself, personal learning preferences, and learning needs at that particular time, with the overriding goal of maximizing learning. Access to electronic materials did not influence students' choices. Fears that the increasing availability of technology-enhanced educational materials has a negative impact on lecture attendance seem unfounded.

  16. Rapid e-Learning Tools Selection Process for Cognitive and Psychomotor Learning Objectives

    ERIC Educational Resources Information Center

    Ku, David Tawei; Huang, Yung-Hsin

    2012-01-01

    This study developed a decision making process for the selection of rapid e-learning tools that could match different learning domains. With the development of the Internet, the speed of information updates has become faster than ever. E-learning has rapidly become the mainstream for corporate training and academic instruction. In order to reduce…

  17. Learning Analytics: Insights into the Natural Learning Behavior of Our Students

    ERIC Educational Resources Information Center

    Becker, Bernd

    2013-01-01

    The migration from traditional classrooms to online learning environments is in full effect. In the midst of these changes, a new approach to learning analytics needs to be considered. Learning analytics refers to the process of collecting and studying usage data in order to make instructional decisions that will support student success. In…

  18. Lifelong Learning in Action: Transforming Education in the 21st Century.

    ERIC Educational Resources Information Center

    Longworth, Norman

    This book presents key concepts in lifelong learning and case studies illustrating the impact of lifelong learning on schools throughout the world. The following are among the topics discussed in the book's 22 chapters: (1) the principle that learning is for the people; (2) educational decision making; (3) learning ownership and motivation; (4)…

  19. Decision Making: from Neuroscience to Psychiatry

    PubMed Central

    Lee, Daeyeol

    2013-01-01

    Adaptive behaviors increase the likelihood of survival and reproduction and improve the quality of life. However, it is often difficult to identify optimal behaviors in real life due to the complexity of the decision maker’s environment and social dynamics. As a result, although many different brain areas and circuits are involved in decision making, evolutionary and learning solutions adopted by individual decision makers sometimes produce suboptimal outcomes. Although these problems are exacerbated in numerous neurological and psychiatric disorders, their underlying neurobiological causes remain incompletely understood. In this review, theoretical frameworks in economics and machine learning and their applications in recent behavioral and neurobiological studies are summarized. Examples of such applications in clinical domains are also discussed for substance abuse, Parkinson’s disease, attention-deficit/hyperactivity disorder, schizophrenia, mood disorders, and autism. Findings from these studies have begun to lay the foundations necessary to improve diagnostics and treatment for various neurological and psychiatric disorders. PMID:23622061

  20. Examining key design decisions involved in developing a serious game for child sexual abuse prevention.

    PubMed

    Stieler-Hunt, Colleen; Jones, Christian M; Rolfe, Ben; Pozzebon, Kay

    2014-01-01

    This paper presents a case study of the key decisions made in the design of Orbit, a child sexual abuse prevention computer game targeted at school students between 8 and 10 years of age. Key decisions include providing supported delivery for the target age group, featuring adults in the program, not over-sanitizing game content, having a focus on building healthy self-concept of players, making the game engaging and relatable for all players and evaluating the program. This case study has implications for the design of Serious Games more generally, including that research should underpin game design decisions, game designers should consider ways of bridging the game to real life, the learning that arises from the game should go beyond rote-learning, designers should consider how the player can make the game-world their own and comprehensive evaluations of Serious Games should be undertaken.

  1. Behavioral and Neural Adaptation in Approach Behavior.

    PubMed

    Wang, Shuo; Falvello, Virginia; Porter, Jenny; Said, Christopher P; Todorov, Alexander

    2018-06-01

    People often make approachability decisions based on perceived facial trustworthiness. However, it remains unclear how people learn trustworthiness from a population of faces and whether this learning influences their approachability decisions. Here we investigated the neural underpinning of approach behavior and tested two important hypotheses: whether the amygdala adapts to different trustworthiness ranges and whether the amygdala is modulated by task instructions and evaluative goals. We showed that participants adapted to the stimulus range of perceived trustworthiness when making approach decisions and that these decisions were further modulated by the social context. The right amygdala showed both linear response and quadratic response to trustworthiness level, as observed in prior studies. Notably, the amygdala's response to trustworthiness was not modulated by stimulus range or social context, a possible neural dynamic adaptation. Together, our data have revealed a robust behavioral adaptation to different trustworthiness ranges as well as a neural substrate underlying approach behavior based on perceived facial trustworthiness.

  2. Examining key design decisions involved in developing a serious game for child sexual abuse prevention

    PubMed Central

    Stieler-Hunt, Colleen; Jones, Christian M.; Rolfe, Ben; Pozzebon, Kay

    2014-01-01

    This paper presents a case study of the key decisions made in the design of Orbit, a child sexual abuse prevention computer game targeted at school students between 8 and 10 years of age. Key decisions include providing supported delivery for the target age group, featuring adults in the program, not over-sanitizing game content, having a focus on building healthy self-concept of players, making the game engaging and relatable for all players and evaluating the program. This case study has implications for the design of Serious Games more generally, including that research should underpin game design decisions, game designers should consider ways of bridging the game to real life, the learning that arises from the game should go beyond rote-learning, designers should consider how the player can make the game-world their own and comprehensive evaluations of Serious Games should be undertaken. PMID:24550880

  3. Coping with Constraints: Reflecting on Responsibilities.

    ERIC Educational Resources Information Center

    Johnson, Nancy J.

    2001-01-01

    Discusses common threads found in the four articles written by teachers in this themed journal issue on coping with mandated curriculum. Discusses the teachers' commitment to professional responsibility expressed as their responsibility to: learn about learning, demonstrate how learning works, make the best teaching decisions possible, remain…

  4. Utilizing a Micro in the Accounting Classroom.

    ERIC Educational Resources Information Center

    Wolverton, L. Craig

    1982-01-01

    The author discusses how to select microcomputer software for an accounting program and what types of instructional modes to use. The following modes are examined: problem solving, decision making, automated accounting functions, learning new accounting concepts, reinforcing concepts already learned, developing independent learning skills, and…

  5. The effect of subjective awareness measures on performance in artificial grammar learning task.

    PubMed

    Ivanchei, Ivan I; Moroshkina, Nadezhda V

    2018-01-01

    Systematic research into implicit learning requires well-developed awareness-measurement techniques. Recently, trial-by-trial measures have been widely used. However, they can increase complexity of a study because they are an additional experimental variable. We tested the effects of these measures on performance in artificial grammar learning study. Four groups of participants were assigned to different awareness measures conditions: confidence ratings, post-decision wagering, decision strategy attribution or none. Decision-strategy-attribution participants demonstrated better grammar learning and longer response times compared to controls. They also exhibited a conservative bias. Grammaticality by itself was a stronger predictor of strings endorsement in decision-strategy-attribution group compared to other groups. Confidence ratings and post-decision wagering only affected the response times. These results were supported by an additional experiment that used a balanced chunk strength design. We conclude that a decision-strategy-attribution procedure may force participants to adopt an analytical decision-making strategy and rely mostly on conscious knowledge of artificial grammar. Copyright © 2017 Elsevier Inc. All rights reserved.

  6. Exploring the oxygen supply and demand framework as a learning tool in undergraduate nursing education.

    PubMed

    Gillespie, Mary; Shackell, Eileen

    2017-11-01

    In nursing education, physiological concepts are typically presented within a body 'systems' framework yet learners are often challenged to apply this knowledge in the holistic and functional manner needed for effective clinical decision-making and safe patient care. A nursing faculty addressed this learning challenge by developing an advanced organizer as a conceptual and integrative learning tool to support learners in diverse learning environments and practice settings. A mixed methods research study was conducted that explored the effectiveness of the Oxygen Supply and Demand Framework as a learning tool in undergraduate nursing education. A pretest/post-test assessment and reflective journal were used to gather data. Findings indicated the Oxygen Supply and Demand Framework guided the development of pattern recognition and thinking processes and supported knowledge development, knowledge application and clinical decision-making. The Oxygen Supply and Demand Framework supports undergraduate students learning to provide safe and effective nursing care. Copyright © 2017 Elsevier Ltd. All rights reserved.

  7. Designing Science Learning in the First Years of Schooling. An Intervention Study with Sequenced Learning Material on the Topic of "Floating and Sinking"

    ERIC Educational Resources Information Center

    Leuchter, Miriam; Saalbach, Henrik; Hardy, Ilonca

    2014-01-01

    Research on learning and instruction of science has shown that learning environments applied in preschool and primary school rarely makes use of structured learning materials in problem-based environments although these are decisive quality features for promoting conceptual change and scientific reasoning within early science learning. We thus…

  8. Assessment "as" Learning: Blurring the Boundaries of Assessment and Learning for Theory, Policy and Practice

    ERIC Educational Resources Information Center

    Dann, Ruth

    2014-01-01

    This paper explores assessment and learning in a way that blurs their boundaries. The notion of assessment "as" learning (AaL) is offered as an aspect of formative assessment (assessment for learning). It considers how pupils self-regulate their own learning, and in so doing make complex decisions about how they use feedback and engage…

  9. Error affect inoculation for a complex decision-making task.

    PubMed

    Tabernero, Carmen; Wood, Robert E

    2009-05-01

    Individuals bring knowledge, implicit theories, and goal orientations to group meetings. Group decisions arise out of the exchange of these orientations. This research explores how a trainee's exploratory and deliberate process (an incremental theory and learning goal orientation) impacts the effectiveness of individual and group decision-making processes. The effectiveness of this training program is compared with another program that included error affect inoculation (EAI). Subjects were 40 Spanish Policemen in a training course. They were distributed in two training conditions for an individual and group decision-making task. In one condition, individuals received the Self-Guided Exploration plus Deliberation Process instructions, which emphasised exploring the options and testing hypotheses. In the other condition, individuals also received instructions based on Error Affect Inoculation (EAI), which emphasised positive affective reactions to errors and mistakes when making decisions. Results show that the quality of decisions increases when the groups share their reasoning. The AIE intervention promotes sharing information, flexible initial viewpoints, and improving the quality of group decisions. Implications and future directions are discussed.

  10. Considering a Voice of the Body for Adult Transformative Learning Theory

    ERIC Educational Resources Information Center

    Boleyn, Elizabeth C.

    2013-01-01

    Unknowingly, much of the population of the Western World are thinking machines who live and learn isolated from somatic experiences. They distrust their bodies in the learning process and are stuck living out unquestioned realities of embodied socioculturalism and rationalism which guide decision making, learning and ways of being. Considering a…

  11. Inter-Judge Agreement in Classifying Students as Learning Disabled.

    ERIC Educational Resources Information Center

    Epps, Susan; And Others

    Eighteen judges with backgrounds in assessment, decision making, and learning disabilities were asked to use an array of information to differentiate learning disabled (LD) and non-learning disabled students. Each judge was provided with forms containing information on 42 test or subtest scores of 50 school-identified LD students and 49 non-LD…

  12. Preserved complex emotion-based learning in amnesia.

    PubMed

    Turnbull, Oliver H; Evans, Cathryn E Y

    2006-01-01

    An important role for emotion in decision-making has recently been highlighted by disruptions in problem solving abilities after lesion to the frontal lobes. Such complex decision-making skills appear to be based on a class of memory ability (emotion-based learning) that may be anatomically independent of hippocampally mediated episodic memory systems. There have long been reports of intact emotion-based learning in amnesia, arguably dating back to the classic report of Claparede. However, all such accounts relate to relatively simple patterns of emotional valence learning, rather than the more complex contingency patterns of emotional experience, which characterise everyday life. A patient, SL, who had a profound anterograde amnesia following posterior cerebral artery infarction, performed a measure of complex emotion-based learning (the Iowa Gambling Task) on three separate occasions. Despite his severe episodic memory impairment, he showed normal levels of performance on the Gambling Task, at levels comparable or better than controls-including learning that persisted across substantial periods of time (weeks). Thus, emotion-based learning systems appear able to encode, and sustain, more sophisticated patterns of valence learning than have previously been reported.

  13. Effects of emotional preferences on value-based decision making are mediated by mentalizing not reward networks

    PubMed Central

    Evans, Simon; Fleming, Stephen M.; Dolan, Raymond J.; Averbeck, Bruno B.

    2012-01-01

    Real-world decision-making often involves social considerations. Consequently, the social value of stimuli can induce preferences in choice behavior. However, it is unknown how financial and social values are integrated in the brain. Here, we investigated how smiling and angry face stimuli interacted with financial reward feedback in a stochastically-rewarded decision-making task. Subjects reliably preferred the smiling faces despite equivalent reward feedback, demonstrating a socially driven bias. We fit a Bayesian reinforcement learning model to factor the effects of financial rewards and emotion preferences in individual subjects, and regressed model predictions on the trial-by-trial fMRI signal. Activity in the sub-callosal cingulate and the ventral striatum, both involved in reward learning, correlated with financial reward feedback, whereas the differential contribution of social value activated dorsal temporo-parietal junction and dorsal anterior cingulate cortex, previously proposed as components of a mentalizing network. We conclude that the impact of social stimuli on value-based decision processes is mediated by effects in brain regions partially separable from classical reward circuitry. PMID:20946058

  14. Cognitive influences on self-care decision making in persons with heart failure.

    PubMed

    Dickson, Victoria V; Tkacs, Nancy; Riegel, Barbara

    2007-09-01

    Despite advances in management, heart failure is associated with high rates of hospitalization, poor quality of life, and early death. Education intended to improve patients' abilities to care for themselves is an integral component of disease management programs. True self-care requires that patients make decisions about symptoms, but the cognitive deficits documented in 30% to 50% of the heart failure population may make daily decision making challenging. After describing heart failure self-care as a naturalistic decision making process, we explore cognitive deficits known to exist in persons with heart failure. Problems in heart failure self-care are analyzed in relation to neural alterations associated with heart failure. As a neural process, decision making has been traced to regions of the prefrontal cortex, the same areas that are affected by ischemia, infarction, and hypoxemia in heart failure. Resulting deficits in memory, attention, and executive function may impair the perception and interpretation of early symptoms and reasoning and, thereby, delay early treatment implementation. There is compelling evidence that the neural processes critical to decision making are located in the same structures that are affected by heart failure. Because self-care requires the cognitive ability to learn, perceive, interpret, and respond, research is needed to discern how neural deficits affects these abilities, decision-making, and self-care behaviors.

  15. Two Dimensions of an Inquiry Stance toward Student-Learning Data

    ERIC Educational Resources Information Center

    Nelson, Tamara Holmlund; Slavit, David; Deuel, Angie

    2012-01-01

    Background/Context: Schools and districts are increasingly emphasizing evidence-based decision making as a means for improving teaching and learning. In response, professional development efforts have shifted toward situated, sustained activities that involve groups of teachers in reflective inquiry about student learning data, instructional…

  16. Manual and computer-aided materials selection for industrial production: An exercise in decision making

    NASA Technical Reports Server (NTRS)

    Bates, Seth P.

    1990-01-01

    Students are introduced to methods and concepts for systematic selection and evaluation of materials which are to be used to manufacture specific products in industry. For this laboratory exercise, students are asked to work in groups to identify and describe a product, then to proceed through the process to select a list of three candidates to make the item from. The exercise draws on knowledge of mechanical, physical, and chemical properties, common materials test techniques, and resource management skills in finding and assessing property data. A very important part of the exercise is the students' introduction to decision making algorithms, and learning how to apply them to a complex decision making process.

  17. A review of clinical decision making: models and current research.

    PubMed

    Banning, Maggi

    2008-01-01

    The aim of this paper was to review the current literature clinical decision-making models and the educational application of models to clinical practice. This was achieved by exploring the function and related research of the three available models of clinical decision making: information-processing model, the intuitive-humanist model and the clinical decision-making model. Clinical decision making is a unique process that involves the interplay between knowledge of pre-existing pathological conditions, explicit patient information, nursing care and experiential learning. Historically, two models of clinical decision making are recognized from the literature; the information-processing model and the intuitive-humanist model. The usefulness and application of both models has been examined in relation the provision of nursing care and care related outcomes. More recently a third model of clinical decision making has been proposed. This new multidimensional model contains elements of the information-processing model but also examines patient specific elements that are necessary for cue and pattern recognition. Literature review. Evaluation of the literature generated from MEDLINE, CINAHL, OVID, PUBMED and EBESCO systems and the Internet from 1980 to November 2005. The characteristics of the three models of decision making were identified and the related research discussed. Three approaches to clinical decision making were identified, each having its own attributes and uses. The most recent addition to the clinical decision making is a theoretical, multidimensional model which was developed through an evaluation of current literature and the assessment of a limited number of research studies that focused on the clinical decision-making skills of inexperienced nurses in pseudoclinical settings. The components of this model and the relative merits to clinical practice are discussed. It is proposed that clinical decision making improves as the nurse gains experience of nursing patients within a specific speciality and with experience, nurses gain a sense of saliency in relation to decision making. Experienced nurses may use all three forms of clinical decision making both independently and concurrently to solve nursing-related problems. It is suggested that O'Neill's clinical decision-making model could be tested by educators and experienced nurses to assess the efficacy of this hybrid approach to decision making.

  18. The child brain computes and utilizes internalized maternal choices

    PubMed Central

    Lim, Seung-Lark; Cherry, J. Bradley C.; Davis, Ann M.; Balakrishnan, S. N.; Ha, Oh-Ryeong; Bruce, Jared M.; Bruce, Amanda S.

    2016-01-01

    As children grow, they gradually learn how to make decisions independently. However, decisions like choosing healthy but less-tasty foods can be challenging for children whose self-regulation and executive cognitive functions are still maturing. We propose a computational decision-making process in which children estimate their mother's choices for them as well as their individual food preferences. By employing functional magnetic resonance imaging during real food choices, we find that the ventromedial prefrontal cortex (vmPFC) encodes children's own preferences and the left dorsolateral prefrontal cortex (dlPFC) encodes the projected mom's choices for them at the time of children's choice. Also, the left dlPFC region shows an inhibitory functional connectivity with the vmPFC at the time of children's own choice. Our study suggests that in part, children utilize their perceived caregiver's choices when making choices for themselves, which may serve as an external regulator of decision-making, leading to optimal healthy decisions. PMID:27218420

  19. Dissociation between dorsal and ventral hippocampal theta oscillations during decision-making.

    PubMed

    Schmidt, Brandy; Hinman, James R; Jacobson, Tara K; Szkudlarek, Emily; Argraves, Melissa; Escabí, Monty A; Markus, Etan J

    2013-04-03

    Hippocampal theta oscillations are postulated to support mnemonic processes in humans and rodents. Theta oscillations facilitate encoding and spatial navigation, but to date, it has been difficult to dissociate the effects of volitional movement from the cognitive demands of a task. Therefore, we examined whether volitional movement or cognitive demands exerted a greater modulating factor over theta oscillations during decision-making. Given the anatomical, electrophysiological, and functional dissociations along the dorsal-ventral axis, theta oscillations were simultaneously recorded in the dorsal and ventral hippocampus in rats trained to switch between place and motor-response strategies. Stark differences in theta characteristics were found between the dorsal and ventral hippocampus in frequency, power, and coherence. Theta power increased in the dorsal, but decreased in the ventral hippocampus, during the decision-making epoch. Interestingly, the relationship between running speed and theta power was uncoupled during the decision-making epoch, a phenomenon limited to the dorsal hippocampus. Theta frequency increased in both the dorsal and ventral hippocampus during the decision epoch, although this effect was greater in the dorsal hippocampus. Despite these differences, ventral hippocampal theta was responsive to the navigation task; theta frequency, power, and coherence were all affected by cognitive demands. Theta coherence increased within the dorsal hippocampus during the decision-making epoch on all three tasks. However, coherence selectively increased throughout the hippocampus (dorsal to ventral) on the task with new hippocampal learning. Interestingly, most results were consistent across tasks, regardless of hippocampal-dependent learning. These data indicate increased integration and cooperation throughout the hippocampus during information processing.

  20. An investigation of the role of some person and situation variables in multiple cue probability learning.

    PubMed

    Bayindir, Mustafa; Bolger, Fergus; Say, Bilge

    2016-07-19

    Making decisions using judgements of multiple non-deterministic indicators is an important task, both in everyday and professional life. Learning of such decision making has often been studied as the mapping of stimuli (cues) to an environmental variable (criterion); however, little attention has been paid to the effects of situation-by-person interactions on this learning. Accordingly, we manipulated cue and feedback presentation mode (graphic or numeric) and task difficulty, and measured individual differences in working memory capacity (WMC). We predicted that graphic presentation, fewer cues, and elevated WMC would facilitate learning, and that person and task characteristics would interact such that presentation mode compatible with the decision maker's cognitive capability (enhanced visual or verbal WMC) would assist learning, particularly for more difficult tasks. We found our predicted main effects, but no significant interactions, except that those with greater WMC benefited to a larger extent with graphic than with numeric presentation, regardless of which type of working memory was enhanced or number of cues. Our findings suggest that the conclusions of past research based predominantly on tasks using numeric presentation need to be reevaluated and cast light on how working memory helps us learn multiple cue-criterion relationships, with implications for dual-process theories of cognition.

  1. The role of risk aversion in non-conscious decision making.

    PubMed

    Wang, Shuo; Krajbich, Ian; Adolphs, Ralph; Tsuchiya, Naotsugu

    2012-01-01

    To what extent can people choose advantageously without knowing why they are making those choices? This hotly debated question has capitalized on the Iowa Gambling Task (IGT), in which people often learn to choose advantageously without appearing to know why. However, because the IGT is unconstrained in many respects, this finding remains debated and other interpretations are possible (e.g., risk aversion, ambiguity aversion, limits of working memory, or insensitivity to reward/punishment can explain the finding of the IGT). Here we devised an improved variant of the IGT in which the deck-payoff contingency switches after subjects repeatedly choose from a good deck, offering the statistical power of repeated within-subject measures based on learning the reward contingencies associated with each deck. We found that participants exhibited low confidence in their choices, as probed with post-decision wagering, despite high accuracy in selecting advantageous decks in the task, which is putative evidence for non-conscious decision making. However, such a behavioral dissociation could also be explained by risk aversion, a tendency to avoid risky decisions under uncertainty. By explicitly measuring risk aversion for each individual, we predicted subjects' post-decision wagering using Bayesian modeling. We found that risk aversion indeed does play a role, but that it did not explain the entire effect. Moreover, independently measured risk aversion was uncorrelated with risk aversion exhibited during our version of the IGT, raising the possibility that the latter risk aversion may be non-conscious. Our findings support the idea that people can make optimal choices without being fully aware of the basis of their decision. We suggest that non-conscious decision making may be mediated by emotional feelings of risk that are based on mechanisms distinct from those that support cognitive assessment of risk.

  2. The Role of Risk Aversion in Non-Conscious Decision Making

    PubMed Central

    Wang, Shuo; Krajbich, Ian; Adolphs, Ralph; Tsuchiya, Naotsugu

    2012-01-01

    To what extent can people choose advantageously without knowing why they are making those choices? This hotly debated question has capitalized on the Iowa Gambling Task (IGT), in which people often learn to choose advantageously without appearing to know why. However, because the IGT is unconstrained in many respects, this finding remains debated and other interpretations are possible (e.g., risk aversion, ambiguity aversion, limits of working memory, or insensitivity to reward/punishment can explain the finding of the IGT). Here we devised an improved variant of the IGT in which the deck-payoff contingency switches after subjects repeatedly choose from a good deck, offering the statistical power of repeated within-subject measures based on learning the reward contingencies associated with each deck. We found that participants exhibited low confidence in their choices, as probed with post-decision wagering, despite high accuracy in selecting advantageous decks in the task, which is putative evidence for non-conscious decision making. However, such a behavioral dissociation could also be explained by risk aversion, a tendency to avoid risky decisions under uncertainty. By explicitly measuring risk aversion for each individual, we predicted subjects’ post-decision wagering using Bayesian modeling. We found that risk aversion indeed does play a role, but that it did not explain the entire effect. Moreover, independently measured risk aversion was uncorrelated with risk aversion exhibited during our version of the IGT, raising the possibility that the latter risk aversion may be non-conscious. Our findings support the idea that people can make optimal choices without being fully aware of the basis of their decision. We suggest that non-conscious decision making may be mediated by emotional feelings of risk that are based on mechanisms distinct from those that support cognitive assessment of risk. PMID:22375133

  3. What do decision makers learn from public forums on climate-related hazards and resilience?

    NASA Astrophysics Data System (ADS)

    Weller, N.; Farooque, M.; Sittenfeld, D.

    2017-12-01

    Public engagement around climate resilience efforts can foster learning for both public audiences and decision makers. On the one hand, public audiences learn about environmental hazards and strategies to increase community resilience through effective public engagement. On the other, decision makers and scientists learn about community members' values and priorities and their relation to environmental hazards and resilience strategies. Evidence from other public engagement efforts involving decision makers suggests that decision maker involvement results in reflection by officials on their own values, capacities, and roles. However, few public engagement exercises evaluate impacts on decision makers. As part of the Science Center Public Forums project, which aims to conduct public forums in eight cities across the country on resiliency to drought, heat, extreme precipitation, and sea level rise, we sought to 1) build partnerships with local decision makers and scientists around public forums and 2) explore how decision makers and scientists interacted with the planning and undertaking of those public forums. We held workshops with decision makers and scientists to inform forum content and identify local resilience issues. We will conduct interviews with local decision makers regarding their involvement in forum planning, their reflections and takeaways from the forum itself, and their perspectives on the value of public engagement for policy making. We will present our model of engagement with decision makers, initial findings from interviews, and lessons learned from connecting decision makers and scientists to public engagement efforts.

  4. Integrated Cognitive Architectures For Robust Decision Making

    DTIC Science & Technology

    2010-09-20

    groups differed significantly from the other three [W(5) > 5, p > 0.13, uncorrected]. Performance by Condition It is useful to look at the average...the research that pursues integrated theories of human cognition, two approaches have become particularly influencial : ACT-R and Leabra. ACT-R...a wide range of tasks involving attention, learning, memory, problem solving, decision making, and language processing. Under the pressure of

  5. Family Decision-Making Style, Peer Group Affiliation and Prior Academic Achievement as Predictors of the Academic Achievement of African American Students

    ERIC Educational Resources Information Center

    Engerman, Kimarie

    2006-01-01

    A study analyzed family decision-making style, peer group affiliation, and academic achievement in 10th grade as predictors of academic achievement of African American students in 12th grade. Findings indicated that though peer groups were known to influence academic performance, affiliation with learning oriented peers in 10th grade did not…

  6. The Development and Validation of a Tool to Measure Self-Confidence and Anxiety in Nursing Students While Making Clinical Decisions

    ERIC Educational Resources Information Center

    White, Krista Alaine

    2011-01-01

    Clinical decision making (CDM) is a cornerstone skill for nurses. Self-confidence and anxiety are two affective influences that impact the learning and adeptness of CDM. Currently, no instruments exist that measure perceived self-confidence and anxiety level of undergraduate nursing students related to CDM. The purpose of this research was to…

  7. How Parents and Teachers Are Helping To Create Better Environments for Learning. Energy-Smart Building Choices.

    ERIC Educational Resources Information Center

    Department of Energy, Washington, DC.

    This guide explores the contributions that parents and teachers can make to enhance energy choice decisions that affect the design and operation of educational facilities. It also examines how making the right choice can create better learning environments. The guide reveals how schools have turned energy improvements into powerful teaching tools;…

  8. Faculty Integration of Technology into Instruction and Students' Perceptions of Computer Technology to Improve Student Learning

    ERIC Educational Resources Information Center

    Keengwe, Jared

    2007-01-01

    There has been a remarkable improvement in access and rate of adoption of technology in higher education. Even so, reports indicate that faculty members are not integrating technology into instruction in ways that make a difference in student learning (Cuban, 2001; McCannon & Crews, 2000). To help faculty make informed decisions on student…

  9. Exploring Identities to Deepen Understanding of Urban High School Students' Sexual Health Decision-Making

    ERIC Educational Resources Information Center

    Brotman, Jennie S.; Mensah, Felicia Moore; Lesko, Nancy

    2010-01-01

    Sexual health is a controversial science topic that has received little attention in the field of science education, despite its direct relevance to students' lives and communities. Moreover, research from other fields indicates that a great deal remains to be learned about how to make school learning about sexual health influence the real-life…

  10. Procedural Decision-Making Experiences among Informational Technology Professionals at a Midwestern Fortune 500 Company

    ERIC Educational Resources Information Center

    McKee, Shari Turner

    2013-01-01

    Between 2002 and 2012, information technology (IT) procedural decisions related to technology, fraud, bias, greed, and misleading information increased cost by more than $44 billion. The purpose of this phenomenological study was to explore IT professionals' experiences of IT procedural decisions. The research questions were intended to learn from…

  11. Statistical learning and adaptive decision-making underlie human response time variability in inhibitory control.

    PubMed

    Ma, Ning; Yu, Angela J

    2015-01-01

    Response time (RT) is an oft-reported behavioral measure in psychological and neurocognitive experiments, but the high level of observed trial-to-trial variability in this measure has often limited its usefulness. Here, we combine computational modeling and psychophysics to examine the hypothesis that fluctuations in this noisy measure reflect dynamic computations in human statistical learning and corresponding cognitive adjustments. We present data from the stop-signal task (SST), in which subjects respond to a go stimulus on each trial, unless instructed not to by a subsequent, infrequently presented stop signal. We model across-trial learning of stop signal frequency, P(stop), and stop-signal onset time, SSD (stop-signal delay), with a Bayesian hidden Markov model, and within-trial decision-making with an optimal stochastic control model. The combined model predicts that RT should increase with both expected P(stop) and SSD. The human behavioral data (n = 20) bear out this prediction, showing P(stop) and SSD both to be significant, independent predictors of RT, with P(stop) being a more prominent predictor in 75% of the subjects, and SSD being more prominent in the remaining 25%. The results demonstrate that humans indeed readily internalize environmental statistics and adjust their cognitive/behavioral strategy accordingly, and that subtle patterns in RT variability can serve as a valuable tool for validating models of statistical learning and decision-making. More broadly, the modeling tools presented in this work can be generalized to a large body of behavioral paradigms, in order to extract insights about cognitive and neural processing from apparently quite noisy behavioral measures. We also discuss how this behaviorally validated model can then be used to conduct model-based analysis of neural data, in order to help identify specific brain areas for representing and encoding key computational quantities in learning and decision-making.

  12. Implications of Modeling Uncertainty for Water Quality Decision Making

    NASA Astrophysics Data System (ADS)

    Shabman, L.

    2002-05-01

    The report, National Academy of Sciences report, "Assessing the TMDL Approach to Water Quality Management" endorsed the "watershed" and "ambient water quality focused" approach" to water quality management called for in the TMDL program. The committee felt that available data and models were adequate to move such a program forward, if the EPA and all stakeholders better understood the nature of the scientific enterprise and its application to the TMDL program. Specifically, the report called for a greater acknowledgement of model prediction uncertinaity in making and implementing TMDL plans. To assure that such uncertinaity was addressed in water quality decision making the committee called for a commitment to "adaptive implementation" of water quality management plans. The committee found that the number and complexity of the interactions of multiple stressors, combined with model prediction uncertinaity means that we need to avoid the temptation to make assurances that specific actions will result in attainment of particular water quality standards. Until the work on solving a water quality problem begins, analysts and decision makers cannot be sure what the correct solutions are, or even what water quality goals a community should be seeking. In complex systems we need to act in order to learn; adaptive implementation is a concurrent process of action and learning. Learning requires (1) continued monitoring of the waterbody to determine how it responds to the actions taken and (2) carefully designed experiments in the watershed. If we do not design learning into what we attempt we are not doing adaptive implementation. Therefore, there needs to be an increased commitment to monitoring and experiments in watersheds that will lead to learning. This presentation will 1) explain the logic for adaptive implementation; 2) discuss the ways that water quality modelers could characterize and explain model uncertinaity to decision makers; 3) speculate on the implications of the adaptive implementation for setting of water quality standards, for design of watershed monitoring programs and for the regulatory rules governing the TMDL program implementation.

  13. Prioritising the relevant information for learning and decision making within orbital and ventromedial prefrontal cortex.

    PubMed

    Walton, Mark E; Chau, Bolton K H; Kennerley, Steven W

    2015-02-01

    Our environment and internal states are frequently complex, ambiguous and dynamic, meaning we need to have selection mechanisms to ensure we are basing our decisions on currently relevant information. Here, we review evidence that orbitofrontal (OFC) and ventromedial prefrontal cortex (VMPFC) play conserved, critical but distinct roles in this process. While OFC may use specific sensory associations to enhance task-relevant information, particularly in the context of learning, VMPFC plays a role in ensuring irrelevant information does not impinge on the decision in hand.

  14. Knowledge Co-production Strategies for Water Resources Modeling and Decision Making

    NASA Astrophysics Data System (ADS)

    Gober, P.

    2016-12-01

    The limited impact of scientific information on policy making and climate adaptation in North America has raised awareness of the need for new modeling strategies and knowledge transfer processes. This paper outlines the rationale for a new paradigm in water resources modeling and management, using examples from the USA and Canada. Principles include anticipatory modeling, complex system dynamics, decision making under uncertainty, visualization, capacity to represent and manipulate critical trade-offs, stakeholder engagement, local knowledge, context-specific activities, social learning, vulnerability analysis, iterative and collaborative modeling, and the concept of a boundary organization. In this framework, scientists and stakeholders are partners in the production and dissemination of knowledge for decision making, and local knowledge is fused with scientific observation and methodology. Discussion draws from experience in building long-term collaborative boundary organizations in Phoenix, Arizona in the USA and the Saskatchewan River Basin (SRB) in Canada. Examples of boundary spanning activities include the use of visualization, the concept of a decision theater, infrastructure to support social learning, social networks, and reciprocity, simulation modeling to explore "what if" scenarios of the future, surveys to elicit how water problems are framed by scientists and stakeholders, and humanistic activities (theatrical performances, art exhibitions, etc.) to draw attention to local water issues. The social processes surrounding model development and dissemination are at least as important as modeling assumptions, procedures, and results in determining whether scientific knowledge will be used effectively for water resources decision making.

  15. Multi-Objective Reinforcement Learning for Cognitive Radio-Based Satellite Communications

    NASA Technical Reports Server (NTRS)

    Ferreira, Paulo Victor R.; Paffenroth, Randy; Wyglinski, Alexander M.; Hackett, Timothy M.; Bilen, Sven G.; Reinhart, Richard C.; Mortensen, Dale J.

    2016-01-01

    Previous research on cognitive radios has addressed the performance of various machine-learning and optimization techniques for decision making of terrestrial link properties. In this paper, we present our recent investigations with respect to reinforcement learning that potentially can be employed by future cognitive radios installed onboard satellite communications systems specifically tasked with radio resource management. This work analyzes the performance of learning, reasoning, and decision making while considering multiple objectives for time-varying communications channels, as well as different cross-layer requirements. Based on the urgent demand for increased bandwidth, which is being addressed by the next generation of high-throughput satellites, the performance of cognitive radio is assessed considering links between a geostationary satellite and a fixed ground station operating at Ka-band (26 GHz). Simulation results show multiple objective performance improvements of more than 3.5 times for clear sky conditions and 6.8 times for rain conditions.

  16. Alterations in choice behavior by manipulations of world model.

    PubMed

    Green, C S; Benson, C; Kersten, D; Schrater, P

    2010-09-14

    How to compute initially unknown reward values makes up one of the key problems in reinforcement learning theory, with two basic approaches being used. Model-free algorithms rely on the accumulation of substantial amounts of experience to compute the value of actions, whereas in model-based learning, the agent seeks to learn the generative process for outcomes from which the value of actions can be predicted. Here we show that (i) "probability matching"-a consistent example of suboptimal choice behavior seen in humans-occurs in an optimal Bayesian model-based learner using a max decision rule that is initialized with ecologically plausible, but incorrect beliefs about the generative process for outcomes and (ii) human behavior can be strongly and predictably altered by the presence of cues suggestive of various generative processes, despite statistically identical outcome generation. These results suggest human decision making is rational and model based and not consistent with model-free learning.

  17. Alterations in choice behavior by manipulations of world model

    PubMed Central

    Green, C. S.; Benson, C.; Kersten, D.; Schrater, P.

    2010-01-01

    How to compute initially unknown reward values makes up one of the key problems in reinforcement learning theory, with two basic approaches being used. Model-free algorithms rely on the accumulation of substantial amounts of experience to compute the value of actions, whereas in model-based learning, the agent seeks to learn the generative process for outcomes from which the value of actions can be predicted. Here we show that (i) “probability matching”—a consistent example of suboptimal choice behavior seen in humans—occurs in an optimal Bayesian model-based learner using a max decision rule that is initialized with ecologically plausible, but incorrect beliefs about the generative process for outcomes and (ii) human behavior can be strongly and predictably altered by the presence of cues suggestive of various generative processes, despite statistically identical outcome generation. These results suggest human decision making is rational and model based and not consistent with model-free learning. PMID:20805507

  18. Hypermedia or Hyperchaos: Using HyperCard to Teach Medical Decision Making

    PubMed Central

    Smith, W.R.; Hahn, J.S.

    1989-01-01

    HyperCard presents an uncoventional instructional environment for educators and students, in that it is nonlinear, nonsequential, and it provides innumerable choices of learning paths to learners. The danger of this environment is that it may frustrate learners whose cognitive and learning styles do not match this environment. Leaners who prefer guided learning rather than independent exploration may become distracted or disoriented by this environment, lost in “hyperspace.” In the context of medical education, these ill-matched styles may produce some physicians who have not mastered skills essential to the practice of medicine. The authors have sought to develop a HyperCard learning environment consisting of related programs that teach medical decision making. The environment allows total learner control until the learner demonstrates a need for guidance in order to achieve the essential objectives of the program. A discussion follows of the implications of hypermedia for instructional design and medical education.

  19. Combining MLC and SVM Classifiers for Learning Based Decision Making: Analysis and Evaluations

    PubMed Central

    Zhang, Yi; Ren, Jinchang; Jiang, Jianmin

    2015-01-01

    Maximum likelihood classifier (MLC) and support vector machines (SVM) are two commonly used approaches in machine learning. MLC is based on Bayesian theory in estimating parameters of a probabilistic model, whilst SVM is an optimization based nonparametric method in this context. Recently, it is found that SVM in some cases is equivalent to MLC in probabilistically modeling the learning process. In this paper, MLC and SVM are combined in learning and classification, which helps to yield probabilistic output for SVM and facilitate soft decision making. In total four groups of data are used for evaluations, covering sonar, vehicle, breast cancer, and DNA sequences. The data samples are characterized in terms of Gaussian/non-Gaussian distributed and balanced/unbalanced samples which are then further used for performance assessment in comparing the SVM and the combined SVM-MLC classifier. Interesting results are reported to indicate how the combined classifier may work under various conditions. PMID:26089862

  20. Combining MLC and SVM Classifiers for Learning Based Decision Making: Analysis and Evaluations.

    PubMed

    Zhang, Yi; Ren, Jinchang; Jiang, Jianmin

    2015-01-01

    Maximum likelihood classifier (MLC) and support vector machines (SVM) are two commonly used approaches in machine learning. MLC is based on Bayesian theory in estimating parameters of a probabilistic model, whilst SVM is an optimization based nonparametric method in this context. Recently, it is found that SVM in some cases is equivalent to MLC in probabilistically modeling the learning process. In this paper, MLC and SVM are combined in learning and classification, which helps to yield probabilistic output for SVM and facilitate soft decision making. In total four groups of data are used for evaluations, covering sonar, vehicle, breast cancer, and DNA sequences. The data samples are characterized in terms of Gaussian/non-Gaussian distributed and balanced/unbalanced samples which are then further used for performance assessment in comparing the SVM and the combined SVM-MLC classifier. Interesting results are reported to indicate how the combined classifier may work under various conditions.

  1. Multi-Objective Reinforcement Learning for Cognitive Radio Based Satellite Communications

    NASA Technical Reports Server (NTRS)

    Ferreira, Paulo; Paffenroth, Randy; Wyglinski, Alexander; Hackett, Timothy; Bilen, Sven; Reinhart, Richard; Mortensen, Dale John

    2016-01-01

    Previous research on cognitive radios has addressed the performance of various machine learning and optimization techniques for decision making of terrestrial link properties. In this paper, we present our recent investigations with respect to reinforcement learning that potentially can be employed by future cognitive radios installed onboard satellite communications systems specifically tasked with radio resource management. This work analyzes the performance of learning, reasoning, and decision making while considering multiple objectives for time-varying communications channels, as well as different crosslayer requirements. Based on the urgent demand for increased bandwidth, which is being addressed by the next generation of high-throughput satellites, the performance of cognitive radio is assessed considering links between a geostationary satellite and a fixed ground station operating at Ka-band (26 GHz). Simulation results show multiple objective performance improvements of more than 3:5 times for clear sky conditions and 6:8 times for rain conditions.

  2. Forum: The Lecture and Student Learning. Sound Decision Making about the Lecture's Role in the College Classroom

    ERIC Educational Resources Information Center

    Waldeck, Jennifer H.; Weimer, Maryellen

    2017-01-01

    College instructors use lecture and its current counterpoint--active learning--widely and often rely on both strategies, but the question of which best promotes student learning has become a debate that ignores the fact that learning can result from both. Students still listen to and learn from lectures. They pass exams, obtain degrees, and…

  3. 11.2 YIP Human In the Loop Statistical RelationalLearners

    DTIC Science & Technology

    2017-10-23

    learning formalisms including inverse reinforcement learning [4] and statistical relational learning [7, 5, 8]. We have also applied our algorithms in...one introduced for label preferences. 4 Figure 2: Active Advice Seeking for Inverse Reinforcement Learning. active advice seeking is in selecting the...learning tasks. 1.2.1 Sequential Decision-Making Our previous work on advice for inverse reinforcement learning (IRL) defined advice as action

  4. Decision-making impairments in the context of intact reward sensitivity in schizophrenia.

    PubMed

    Heerey, Erin A; Bell-Warren, Kimberly R; Gold, James M

    2008-07-01

    Deficits in motivated behavior and decision-making figure prominently in the behavioral syndrome that characterizes schizophrenia and are difficult both to treat and to understand. One explanation for these deficits is that schizophrenia decreases sensitivity to rewards in the environment. An alternate explanation is that sensitivity to rewards is intact but that poor integration of affective with cognitive information impairs the ability to use this information to guide behavior. We tested reward sensitivity with a modified version of an existing signal detection task with asymmetric reinforcement and decision-making with a probabilistic decision-making task in 40 participants with schizophrenia and 26 healthy participants. Results showed normal sensitivity to reward in participants with schizophrenia but differences in choice patterns on the decision-making task. A logistic regression model of the decision-making data showed that participants with schizophrenia differed from healthy participants in the ability to weigh potential outcomes, specifically potential losses, when choosing between competing response options. Deficits in working memory ability accounted for group differences in ability to use potential outcomes during decision-making. These results suggest that the implicit mechanisms that drive reward-based learning are surprisingly intact in schizophrenia but that poor ability to integrate cognitive and affective information when calculating the value of possible choices might hamper the ability to use such information during explicit decision-making.

  5. Taking on the doctor role in whole-task simulation.

    PubMed

    Bartlett, Maggie; Gay, Simon P; Kinston, Ruth; McKinley, Robert

    2018-06-01

    Untimed simulated primary care consultations focusing on safe and effective clinical outcomes were first introduced into undergraduate medical education in Otago, New Zealand, in 2004. We extended this concept and included a secondary care version for final-year students. We offer students opportunities to manage entire consultations, which include making and implementing clinical decisions with simulated patients (SPs). Formative feedback is given by SPs on the achievement of pre-determined outcomes and by faculty members on clinical decision making, medical record keeping and case presentation. We explored students' perceptions of the educational value of the sessions using post-session questionnaires (n = 194) and focus groups (n = 36 participants overall). Students are offered opportunities to manage entire consultations with simulated patients RESULTS: Students perceived that the sessions were useful, enjoyable and relevant to early postgraduate practice. They identified useful learning in time management, communication, decision making, prescribing and managing uncertainty. Students identified gaps in their knowledge and recognised that they had been offered opportunities to develop decision-making skills by having to take responsibility for whole consultations and all the decisions included within them. Most students reported positive impacts on learning, although a small minority reported negative impacts on their perceptions of their ability to cope as a junior doctor. These simulated consultation sessions appear to lead to the effective learning of a range of skills that students need in order to work as junior doctors. Facilitators leading such sessions must be alert to the possibility of educational harm arising from such simulations, and the need to address this during the debriefing. © 2017 John Wiley & Sons Ltd and The Association for the Study of Medical Education.

  6. Physician Perspectives on Decision Making for Treatment of Pediatric Sleep-Disordered Breathing.

    PubMed

    Boss, Emily F; Links, Anne R; Saxton, Ron; Cheng, Tina L; Beach, Mary Catherine

    2017-10-01

    Sleep-disordered breathing (SDB) is prevalent in children and most commonly treated by surgery with adenotonsillectomy. We aimed to learn physician perspectives of social and communication factors that influence decision making for treatment of pediatric SDB. Purposive sampling identified 10 physician key informants across disciplines and practice settings, who participated in semistructured interviews regarding SDB care experiences and communication with parents. Interviews were analyzed using directed qualitative content analysis. Physicians provided a variety of perspectives on decision making for treatment that fell into 3 overarching themes: approach to surgery and alternatives, communication and decision making with families, and sociocultural factors/barriers to care. Perspectives were moderately heterogeneous, suggesting that individual social and relational elements may significantly influence how physicians refer patients and recommend treatment, and how parents choose surgery for this prevalent condition. These findings will inform development of culturally competent communication strategies and support tools to enhance shared decision making for physicians treating children with SDB.

  7. On-line social decision making and antisocial behavior: some essential but neglected issues.

    PubMed

    Fontaine, Reid Griffith

    2008-01-01

    The last quarter century has witnessed considerable progress in the scientific study of social information processing (SIP) and aggressive behavior in children. SIP research has shown that social decision making in youth is particularly predictive of antisocial behavior, especially as children enter and progress through adolescence. In furtherance of this research, more sophisticated, elaborate models of on-line social decision making have been developed, by which various domains of evaluative judgment are hypothesized to account for both responsive decision making and behavior, as well as self-initiated, instrumental functioning. However, discussions of these models have neglected a number of key issues. In particular, the roles of nonconscious cognitive factors, learning and development, impulsivity and behavioral disinhibition, emotion, and other internal and external factors (e.g., pharmacological influences and audience effects) have been largely absent from scholarly writings. In response, this article introduces discussion of these factors and reviews their possible roles in on-line social decision making and antisocial behavior in youth.

  8. Difficulties of Diabetic Patients in Learning about Their Illness.

    ERIC Educational Resources Information Center

    Bonnet, Caroline; Gagnayre, Remi; d'Ivernois, Jean Francois

    2001-01-01

    Examines the difficulties experienced by diabetic patients in learning about their illness. Diabetic people (N=138) were questioned by means of a closed answer questionnaire. Results reveal that patients easily acquired manual skills, yet numerous learning difficulties were associated with the skills required to solve problems and make decisions,…

  9. Social and Emotional Learning Hikes Interest and Resiliency

    ERIC Educational Resources Information Center

    Beland, Kathy

    2007-01-01

    Social Emotional Learning (SEL) is the process by which people develop the skills to recognize and manage emotions, form positive relationships, solve problems that arise, motivate themselves to accomplish a goal, make responsible decisions, and avoid risky behavior. The Collaborative for Social and Emotional Learning (CASEL), at the University of…

  10. Adapting Cooperative Learning and Embedding It into Holistic Language Usage.

    ERIC Educational Resources Information Center

    Bailey, Dora L.; Ginnetti, Philip

    Class collaboration and small group composition illustrate the embedding of cooperative learning theory in whole language classroom events. Through this experience all students participate in active learning. The teacher has a weighty role in decision making, setting of the lesson, assigning roles, and monitoring segments of cooperative learning…

  11. Dig That Site: Exploring Archaeology, History, and Civilization on the Internet.

    ERIC Educational Resources Information Center

    Garfield, Gary M.; McDonough, Suzanne

    This book combines the excitement of the Internet with conventional learning resources to explore early civilizations and cultures. This approach encourages independent student research, problem solving, and decision making while bringing together the fascination of archaeology with the Internet and hands-on learning activities. Students learn the…

  12. From Telling, to Teaching, towards Learning: A New Approach to Nitrogen Fertility Management of Cereals in Northern Australia.

    ERIC Educational Resources Information Center

    Lawrence, David; Cawley, Scott

    1999-01-01

    An agricultural extension workshop on nitrogen use was evaluated by 75% of Australian farmers participating. Use of action learning and adult learning principles helped make the issues presented meaningful and influenced 67% of the respondents' fertilizer decisions. (SK)

  13. Learning Partnerships in Rural Early Childhood Settings.

    ERIC Educational Resources Information Center

    Coombe, Kennece; Lubawy, Joy

    2002-01-01

    A study examined the value of six theoretical aspects of learning communities in rural New South Wales (Australia) preschools. Surveys of nine preschool directors indicated that they recognized the value of shared decision making, reflection, and delegating power, and that open communication was necessary for developing a learning environment…

  14. Learning about Health

    ERIC Educational Resources Information Center

    Geertshuis, Susan; Cooper-Thomas, Helena

    2011-01-01

    This paper examines the extent of patients' health-related learning from a range of sources and aims to identify psycho-cognitive variables that predict learning. Using a survey design, we found that people higher in perceived health competence were lower in anxiety and took a more logical approach to decision making. Low perceived health…

  15. Designing the Learning Context in School for Talent Development

    ERIC Educational Resources Information Center

    Hertzog, Nancy B.

    2017-01-01

    This article explores the learning context for talent development in public schools. Total aspects of the environment from physical space, affective elements, and pedagogical approaches affect learning. How teachers believe and perceive their roles as teachers influence instructional design and decision making. In this article, the optimal…

  16. Teacher Professional Learning Communities: Going beyond Contrived Collegiality toward Challenging Debate and Collegial Learning and Professional Growth

    ERIC Educational Resources Information Center

    Owen, Susanne

    2014-01-01

    Professional learning community (PLC) is a current "buzz" term in business and educational contexts, seemingly referring to anything from decision making committees to regular meeting groups or collegial learning teams. This paper explores the concept of a PLC within three significantly innovative schools, based on an examination of the…

  17. Students' Motivations, Value, and Decision to Participate in Service-Learning at the National FFA Days of Service

    ERIC Educational Resources Information Center

    Roberts, Richie; Terry, Robert, Jr.; Brown, Nicholas R.; Ramsey, Jon W.

    2016-01-01

    As agricultural educators continue to seek methods of instruction to make learning impactful for students, service-learning has emerged as a desirable technique for meeting these educational objectives. A gap in the agricultural education literature exists, however, in terms of describing whether these learning experiences motivate students…

  18. How to Represent Adaptation in e-Learning with IMS Learning Design

    ERIC Educational Resources Information Center

    Burgos, Daniel; Tattersall, Colin; Koper, Rob

    2007-01-01

    Adaptation in e-learning has been an important research topic for the last few decades in computer-based education. In adaptivity the behaviour of the user triggers some actions in the system that guides the learning process. In adaptability, the user makes changes and takes decisions. Progressing from computer-based training and adaptive…

  19. STANFORD ARTIFICIAL INTELLIGENCE PROJECT.

    DTIC Science & Technology

    ARTIFICIAL INTELLIGENCE , GAME THEORY, DECISION MAKING, BIONICS, AUTOMATA, SPEECH RECOGNITION, GEOMETRIC FORMS, LEARNING MACHINES, MATHEMATICAL MODELS, PATTERN RECOGNITION, SERVOMECHANISMS, SIMULATION, BIBLIOGRAPHIES.

  20. Predicting species distributions for conservation decisions

    PubMed Central

    Guisan, Antoine; Tingley, Reid; Baumgartner, John B; Naujokaitis-Lewis, Ilona; Sutcliffe, Patricia R; Tulloch, Ayesha I T; Regan, Tracey J; Brotons, Lluis; McDonald-Madden, Eve; Mantyka-Pringle, Chrystal; Martin, Tara G; Rhodes, Jonathan R; Maggini, Ramona; Setterfield, Samantha A; Elith, Jane; Schwartz, Mark W; Wintle, Brendan A; Broennimann, Olivier; Austin, Mike; Ferrier, Simon; Kearney, Michael R; Possingham, Hugh P; Buckley, Yvonne M

    2013-01-01

    Species distribution models (SDMs) are increasingly proposed to support conservation decision making. However, evidence of SDMs supporting solutions for on-ground conservation problems is still scarce in the scientific literature. Here, we show that successful examples exist but are still largely hidden in the grey literature, and thus less accessible for analysis and learning. Furthermore, the decision framework within which SDMs are used is rarely made explicit. Using case studies from biological invasions, identification of critical habitats, reserve selection and translocation of endangered species, we propose that SDMs may be tailored to suit a range of decision-making contexts when used within a structured and transparent decision-making process. To construct appropriate SDMs to more effectively guide conservation actions, modellers need to better understand the decision process, and decision makers need to provide feedback to modellers regarding the actual use of SDMs to support conservation decisions. This could be facilitated by individuals or institutions playing the role of ‘translators’ between modellers and decision makers. We encourage species distribution modellers to get involved in real decision-making processes that will benefit from their technical input; this strategy has the potential to better bridge theory and practice, and contribute to improve both scientific knowledge and conservation outcomes. PMID:24134332

  1. Cost-benefit decision circuitry: proposed modulatory role for acetylcholine.

    PubMed

    Fobbs, Wambura C; Mizumori, Sheri J Y

    2014-01-01

    In order to select which action should be taken, an animal must weigh the costs and benefits of possible outcomes associate with each action. Such decisions, called cost-benefit decisions, likely involve several cognitive processes (including memory) and a vast neural circuitry. Rodent models have allowed research to begin to probe the neural basis of three forms of cost-benefit decision making: effort-, delay-, and risk-based decision making. In this review, we detail the current understanding of the functional circuits that subserve each form of decision making. We highlight the extensive literature by detailing the ability of dopamine to influence decisions by modulating structures within these circuits. Since acetylcholine projects to all of the same important structures, we propose several ways in which the cholinergic system may play a local modulatory role that will allow it to shape these behaviors. A greater understanding of the contribution of the cholinergic system to cost-benefit decisions will permit us to better link the decision and memory processes, and this will help us to better understand and/or treat individuals with deficits in a number of higher cognitive functions including decision making, learning, memory, and language. © 2014 Elsevier Inc. All rights reserved.

  2. Students academic performance based on behavior

    NASA Astrophysics Data System (ADS)

    Maulida, Juwita Dien; Kariyam

    2017-12-01

    Utilization of data in an information system that can be used for decision making that utilizes existing data warehouse to help dig useful information to make decisions correctly and accurately. Experience API (xAPI) is one of the enabling technologies for collecting data, so xAPI can be used as a data warehouse that can be used for various needs. One software application whose data is collected in xAPI is LMS. LMS is a software used in an electronic learning process that can handle all aspects of learning, by using LMS can also be known how the learning process and the aspects that can affect learning achievement. One of the aspects that can affect the learning achievement is the background of each student, which is not necessarily the student with a good background is an outstanding student or vice versa. Therefore, an action is needed to anticipate this problem. Prediction of student academic performance using Naive Bayes algorithm obtained accuracy of 67.7983% and error 32.2917%.

  3. The role of medial prefrontal cortex in memory and decision making.

    PubMed

    Euston, David R; Gruber, Aaron J; McNaughton, Bruce L

    2012-12-20

    Some have claimed that the medial prefrontal cortex (mPFC) mediates decision making. Others suggest mPFC is selectively involved in the retrieval of remote long-term memory. Yet others suggests mPFC supports memory and consolidation on time scales ranging from seconds to days. How can all these roles be reconciled? We propose that the function of the mPFC is to learn associations between context, locations, events, and corresponding adaptive responses, particularly emotional responses. Thus, the ubiquitous involvement of mPFC in both memory and decision making may be due to the fact that almost all such tasks entail the ability to recall the best action or emotional response to specific events in a particular place and time. An interaction between multiple memory systems may explain the changing importance of mPFC to different types of memories over time. In particular, mPFC likely relies on the hippocampus to support rapid learning and memory consolidation. Copyright © 2012 Elsevier Inc. All rights reserved.

  4. Adaptive Management: From More Talk to Real Action

    NASA Astrophysics Data System (ADS)

    Williams, Byron K.; Brown, Eleanor D.

    2014-02-01

    The challenges currently facing resource managers are large-scale and complex, and demand new approaches to balance development and conservation goals. One approach that shows considerable promise for addressing these challenges is adaptive management, which by now is broadly seen as a natural, intuitive, and potentially effective way to address decision-making in the face of uncertainties. Yet the concept of adaptive management continues to evolve, and its record of success remains limited. In this article, we present an operational framework for adaptive decision-making, and describe the challenges and opportunities in applying it to real-world problems. We discuss the key elements required for adaptive decision-making, and their integration into an iterative process that highlights and distinguishes technical and social learning. We illustrate the elements and processes of the framework with some successful on-the-ground examples of natural resource management. Finally, we address some of the difficulties in applying learning-based management, and finish with a discussion of future directions and strategic challenges.

  5. Do Children Who Experience Regret Make Better Decisions? A Developmental Study of the Behavioral Consequences of Regret

    PubMed Central

    O’Connor, Eimear; McCormack, Teresa; Feeney, Aidan

    2014-01-01

    Although regret is assumed to facilitate good decision making, there is little research directly addressing this assumption. Four experiments (N = 326) examined the relation between children's ability to experience regret and the quality of their subsequent decision making. In Experiment 1 regret and adaptive decision making showed the same developmental profile, with both first appearing at about 7 years. In Experiments 2a and 2b, children aged 6–7 who experienced regret decided adaptively more often than children who did not experience regret, and this held even when controlling for age and verbal ability. Experiment 3 ruled out a memory-based interpretation of these findings. These findings suggest that the experience of regret facilitates children's ability to learn rapidly from bad outcomes. PMID:24773388

  6. Decision-making based on emotional images.

    PubMed

    Katahira, Kentaro; Fujimura, Tomomi; Okanoya, Kazuo; Okada, Masato

    2011-01-01

    The emotional outcome of a choice affects subsequent decision making. While the relationship between decision making and emotion has attracted attention, studies on emotion and decision making have been independently developed. In this study, we investigated how the emotional valence of pictures, which was stochastically contingent on participants' choices, influenced subsequent decision making. In contrast to traditional value-based decision-making studies that used money or food as a reward, the "reward value" of the decision outcome, which guided the update of value for each choice, is unknown beforehand. To estimate the reward value of emotional pictures from participants' choice data, we used reinforcement learning models that have successfully been used in previous studies for modeling value-based decision making. Consequently, we found that the estimated reward value was asymmetric between positive and negative pictures. The negative reward value of negative pictures (relative to neutral pictures) was larger in magnitude than the positive reward value of positive pictures. This asymmetry was not observed in valence for an individual picture, which was rated by the participants regarding the emotion experienced upon viewing it. These results suggest that there may be a difference between experienced emotion and the effect of the experienced emotion on subsequent behavior. Our experimental and computational paradigm provides a novel way for quantifying how and what aspects of emotional events affect human behavior. The present study is a first step toward relating a large amount of knowledge in emotion science and in taking computational approaches to value-based decision making.

  7. A Decision-Making Tools Workshop

    DTIC Science & Technology

    1999-08-01

    California Polytechnic State University, San Luis Obispo, CA 47 Distributed Intelligent Agents Katia Sycara, Keith Decker, Anandeep Pannu , Mike...Anandeep Pannu and Katia Sycara. Learning text filtering preferences. In 1996 AAAI Symposium on Machine Learning and Information Access, 1996. [19] Anand

  8. Beyond negative valence: 2-week administration of a serotonergic antidepressant enhances both reward and effort learning signals

    PubMed Central

    Kolling, Nils; Nelissen, Natalie; Browning, Michael; Rushworth, Matthew F. S.; Harmer, Catherine J.

    2017-01-01

    To make good decisions, humans need to learn about and integrate different sources of appetitive and aversive information. While serotonin has been linked to value-based decision-making, its role in learning is less clear, with acute manipulations often producing inconsistent results. Here, we show that when the effects of a selective serotonin reuptake inhibitor (SSRI, citalopram) are studied over longer timescales, learning is robustly improved. We measured brain activity with functional magnetic resonance imaging (fMRI) in volunteers as they performed a concurrent appetitive (money) and aversive (effort) learning task. We found that 2 weeks of citalopram enhanced reward and effort learning signals in a widespread network of brain regions, including ventromedial prefrontal and anterior cingulate cortex. At a behavioral level, this was accompanied by more robust reward learning. This suggests that serotonin can modulate the ability to learn via a mechanism that is independent of stimulus valence. Such effects may partly underlie SSRIs’ impact in treating psychological illnesses. Our results highlight both a specific function in learning for serotonin and the importance of studying its role across longer timescales. PMID:28207733

  9. A typology of time-scale mismatches and behavioral interventions to diagnose and solve conservation problems

    USGS Publications Warehouse

    Wilson, Robyn S.; Hardisty, David J.; Epanchin-Niell, Rebecca S.; Runge, Michael C.; Cottingham, Kathryn L.; Urban, Dean L.; Maguire, Lynn A.; Hastings, Alan; Mumby, Peter J.; Peters, Debra P.C.

    2016-01-01

    Ecological systems often operate on time scales significantly longer or shorter than the time scales typical of human decision making, which causes substantial difficulty for conservation and management in socioecological systems. For example, invasive species may move faster than humans can diagnose problems and initiate solutions, and climate systems may exhibit long-term inertia and short-term fluctuations that obscure learning about the efficacy of management efforts in many ecological systems. We adopted a management-decision framework that distinguishes decision makers within public institutions from individual actors within the social system, calls attention to the ways socioecological systems respond to decision makers’ actions, and notes institutional learning that accrues from observing these responses. We used this framework, along with insights from bedeviling conservation problems, to create a typology that identifies problematic time-scale mismatches occurring between individual decision makers in public institutions and between individual actors in the social or ecological system. We also considered solutions that involve modifying human perception and behavior at the individual level as a means of resolving these problematic mismatches. The potential solutions are derived from the behavioral economics and psychology literature on temporal challenges in decision making, such as the human tendency to discount future outcomes at irrationally high rates. These solutions range from framing environmental decisions to enhance the salience of long-term consequences, to using structured decision processes that make time scales of actions and consequences more explicit, to structural solutions aimed at altering the consequences of short-sighted behavior to make it less appealing. Additional application of these tools and long-term evaluation measures that assess not just behavioral changes but also associated changes in ecological systems are needed.

  10. A typology of time-scale mismatches and behavioral interventions to diagnose and solve conservation problems.

    PubMed

    Wilson, Robyn S; Hardisty, David J; Epanchin-Niell, Rebecca S; Runge, Michael C; Cottingham, Kathryn L; Urban, Dean L; Maguire, Lynn A; Hastings, Alan; Mumby, Peter J; Peters, Debra P C

    2016-02-01

    Ecological systems often operate on time scales significantly longer or shorter than the time scales typical of human decision making, which causes substantial difficulty for conservation and management in socioecological systems. For example, invasive species may move faster than humans can diagnose problems and initiate solutions, and climate systems may exhibit long-term inertia and short-term fluctuations that obscure learning about the efficacy of management efforts in many ecological systems. We adopted a management-decision framework that distinguishes decision makers within public institutions from individual actors within the social system, calls attention to the ways socioecological systems respond to decision makers' actions, and notes institutional learning that accrues from observing these responses. We used this framework, along with insights from bedeviling conservation problems, to create a typology that identifies problematic time-scale mismatches occurring between individual decision makers in public institutions and between individual actors in the social or ecological system. We also considered solutions that involve modifying human perception and behavior at the individual level as a means of resolving these problematic mismatches. The potential solutions are derived from the behavioral economics and psychology literature on temporal challenges in decision making, such as the human tendency to discount future outcomes at irrationally high rates. These solutions range from framing environmental decisions to enhance the salience of long-term consequences, to using structured decision processes that make time scales of actions and consequences more explicit, to structural solutions aimed at altering the consequences of short-sighted behavior to make it less appealing. Additional application of these tools and long-term evaluation measures that assess not just behavioral changes but also associated changes in ecological systems are needed. © 2015 Society for Conservation Biology.

  11. An Instructional Management Guide to Cost Effective Decision Making,

    DTIC Science & Technology

    1974-01-01

    Journal , 1968, 34. United States Congress. To improve learning. Report by the Commission on Instructional Technology of the Commis- sion on Education...of cost-benefit analysis and cost-effectiveness analysis has been recognized in public and private education. It was reported by the Commission on...instructional decision-making, however, is a more formidable task. One difficulty is that although much has been reported on the advantages of

  12. Understanding Optimal Military Decision Making: Year 2 Progress Report

    DTIC Science & Technology

    2014-01-01

    measures. ARMY RELEVANCY AND MILITARY APPLICATION AREAS Objectively defining, measuring, and developing a means to assess military optimal decision making...has the potential to enhance training and refine procedures supporting more efficient learning and task accomplishment. Through the application of...26.79 (12.39) 7.94 (62.38) N/A = Not applicable ; as it is not possible to calculate this particular variable. Table 2. Descriptive statistics of

  13. Using Sanctioned Athletics Programs to Understand Stakeholders' Perceived Influence in Decisions at Major Research Universities

    ERIC Educational Resources Information Center

    Hirko, Scott

    2011-01-01

    This study set out to learn more about the perceived influence of stakeholders on academic decisions affecting intercollegiate athletics, with the intent that such knowledge would help provide useful implications for future leaders making decisions that impact unique student populations. As an area of research, the semi-autonomous unit of…

  14. In Light of the Limitations of Data-Driven Decision Making

    ERIC Educational Resources Information Center

    Loeb, Susanna

    2012-01-01

    Students' experiences and the opportunities they have to learn rest on the quality of education decisions made in each classroom, in each school, in each district, and in each state, federal legislature, and department of education. The role of research and scholarship more broadly in education finance and policy is to inform these decisions for…

  15. Patients with Parkinson's Disease Learn to Control Complex Systems via Procedural as Well as Non-Procedural Learning

    ERIC Educational Resources Information Center

    Osman, Magda; Wilkinson, Leonora; Beigi, Mazda; Castaneda, Cristina Sanchez; Jahanshahi, Marjan

    2008-01-01

    The striatum is considered to mediate some forms of procedural learning. Complex dynamic control (CDC) tasks involve an individual having to make a series of sequential decisions to achieve a specific outcome (e.g. learning to operate and control a car), and they involve procedural learning. The aim of this study was to test the hypothesis that…

  16. Flight School in the Virtual Environment: Capabilities and Risks of Executing a Simulations-Based Flight Training Program

    DTIC Science & Technology

    2012-05-17

    theories work together to explain learning in aviation—behavioral learning theory , cognitive learning theory , constructivism, experiential ...solve problems, and make decisions. Experiential learning theory incorporates both behavioral and cognitive theories .104 This theory harnesses the...34Evaluation of the Effectiveness of Flight School XXI," 7. 106 David A. Kolb , Experiential Learning : Experience as the Source of

  17. Identifying Non-Sustainable Courses of Action: A Prerequisite for Decision-Making in Education for Sustainable Development

    NASA Astrophysics Data System (ADS)

    Gresch, Helge; Bögeholz, Susanne

    2013-04-01

    Students are faced with a multitude of decisions as consumers and in societal debates. Because of the scarcity of resources, the destruction of ecosystems and social injustice in a globalized world, it is vital that students are able to identify non-sustainable courses of action when involved in decision-making. The application of decision-making strategies is one approach to enhancing the quality of decisions. Options that do not meet ecological, social or economic standards should be excluded using non-compensatory strategies whereas other tasks may require a complete trade-off of all the evidence, following a compensatory approach. To enhance decision-making competence, a computer-based intervention study was conducted that focused on the use of decision-making strategies. While the results of the summative evaluation are reported by Gresch et al. (International Journal of Science Education, 2011), in-depth analyses of process-related data collected during the information processing are presented in this paper to reveal insights into the mechanisms of the intervention. The quality of high school students' ( n = 120) metadecision skills when selecting a decision-making strategy was investigated using qualitative content analyses combined with inferential statistics. The results reveal that the students offered elaborate reflections on the sustainability of options. However, the characteristics that were declared non-sustainable differed among the students because societal norms and personal values were intertwined. One implication for education for sustainable development is that students are capable of reflecting on decision-making tasks and on corresponding favorable decision-making strategies at a metadecision level. From these results, we offer suggestions for improving learning environments and constructing test instruments for decision-making competence.

  18. Emergence of β-Band Oscillations in the Aged Rat Amygdala during Discrimination Learning and Decision Making Tasks

    PubMed Central

    Samson, Rachel D.; Duarte, Leroy; Venkatesh, Anu

    2017-01-01

    Abstract Older adults tend to use strategies that differ from those used by young adults to solve decision-making tasks. MRI experiments suggest that altered strategy use during aging can be accompanied by a change in extent of activation of a given brain region, inter-hemispheric bilateralization or added brain structures. It has been suggested that these changes reflect compensation for less effective networks to enable optimal performance. One way that communication can be influenced within and between brain networks is through oscillatory events that help structure and synchronize incoming and outgoing information. It is unknown how aging impacts local oscillatory activity within the basolateral complex of the amygdala (BLA). The present study recorded local field potentials (LFPs) and single units in old and young rats during the performance of tasks that involve discrimination learning and probabilistic decision making. We found task- and age-specific increases in power selectively within the β range (15–30 Hz). The increased β power occurred after lever presses, as old animals reached the goal location. Periods of high-power β developed over training days in the aged rats, and was greatest in early trials of a session. β Power was also greater after pressing for the large reward option. These data suggest that aging of BLA networks results in strengthened synchrony of β oscillations when older animals are learning or deciding between rewards of different size. Whether this increased synchrony reflects the neural basis of a compensatory strategy change of old animals in reward-based decision-making tasks, remains to be verified. PMID:29034315

  19. Neural correlates of decision making with explicit information about probabilities and incentives in elderly healthy subjects.

    PubMed

    Labudda, Kirsten; Woermann, Friedrich G; Mertens, Markus; Pohlmann-Eden, Bernd; Markowitsch, Hans J; Brand, Matthias

    2008-06-01

    Recent functional neuroimaging and lesion studies demonstrate the involvement of the orbitofrontal/ventromedial prefrontal cortex as a key structure in decision making processes. This region seems to be particularly crucial when contingencies between options and consequences are unknown but have to be learned by the use of feedback following previous decisions (decision making under ambiguity). However, little is known about the neural correlates of decision making under risk conditions in which information about probabilities and potential outcomes is given. In the present study, we used functional magnetic resonance imaging to measure blood-oxygenation-level-dependent (BOLD) responses in 12 subjects during a decision making task. This task provided explicit information about probabilities and associated potential incentives. The responses were compared to BOLD signals in a control condition without information about incentives. In contrast to previous decision making studies, we completely removed the outcome phase following a decision to exclude the potential influence of feedback previously received on current decisions. The results indicate that the integration of information about probabilities and incentives leads to activations within the dorsolateral prefrontal cortex, the posterior parietal lobe, the anterior cingulate and the right lingual gyrus. We assume that this pattern of activation is due to the involvement of executive functions, conflict detection mechanisms and arithmetic operations during the deliberation phase of decisional processes that are based on explicit information.

  20. Social modulation of decision-making: a cross-species review

    PubMed Central

    van den Bos, Ruud; Jolles, Jolle W.; Homberg, Judith R.

    2013-01-01

    Taking decisions plays a pivotal role in daily life and comprises a complex process of assessing and weighing short-term and long-term costs and benefits of competing actions. Decision-making has been shown to be affected by factors such as sex, age, genotype, and personality. Importantly, also the social environment affects decisions, both via social interactions (e.g., social learning, cooperation and competition) and social stress effects. Although everyone is aware of this social modulating role on daily life decisions, this has thus far only scarcely been investigated in human and animal studies. Furthermore, neuroscientific studies rarely discuss social influence on decision-making from a functional perspective such as done in behavioral ecology studies. Therefore, the first aim of this article is to review the available data of the influence of the social context on decision-making both from a causal and functional perspective, drawing on animal and human studies. Also, there is currently still a gap between decision-making in real life where influences of the social environment are extensive, and decision-making as measured in the laboratory, which is often done without any (deliberate) social influences. However, methods are being developed to bridge this gap. Therefore, the second aim of this review is to discuss these methods and ways in which this gap can be increasingly narrowed. We end this review by formulating future research questions. PMID:23805092

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