Temperament and problem solving in a population of adolescent guide dogs.

PubMed

Bray, Emily E; Sammel, Mary D; Seyfarth, Robert M; Serpell, James A; Cheney, Dorothy L

2017-09-01

It is often assumed that measures of temperament within individuals are more correlated to one another than to measures of problem solving. However, the exact relationship between temperament and problem-solving tasks remains unclear because large-scale studies have typically focused on each independently. To explore this relationship, we tested 119 prospective adolescent guide dogs on a battery of 11 temperament and problem-solving tasks. We then summarized the data using both confirmatory factor analysis and exploratory principal components analysis. Results of confirmatory analysis revealed that a priori separation of tests as measuring either temperament or problem solving led to weak results, poor model fit, some construct validity, and no predictive validity. In contrast, results of exploratory analysis were best summarized by principal components that mixed temperament and problem-solving traits. These components had both construct and predictive validity (i.e., association with success in the guide dog training program). We conclude that there is complex interplay between tasks of "temperament" and "problem solving" and that the study of both together will be more informative than approaches that consider either in isolation.

Goals and everyday problem solving: examining the link between age-related goals and problem-solving strategy use.

PubMed

Hoppmann, Christiane A; Coats, Abby Heckman; Blanchard-Fields, Fredda

2008-07-01

Qualitative interviews on family and financial problems from 332 adolescents, young, middle-aged, and older adults, demonstrated that developmentally relevant goals predicted problem-solving strategy use over and above problem domain. Four focal goals concerned autonomy, generativity, maintaining good relationships with others, and changing another person. We examined both self- and other-focused problem-solving strategies. Autonomy goals were associated with self-focused instrumental problem solving and generative goals were related to other-focused instrumental problem solving in family and financial problems. Goals of changing another person were related to other-focused instrumental problem solving in the family domain only. The match between goals and strategies, an indicator of problem-solving adaptiveness, showed that young individuals displayed the greatest match between autonomy goals and self-focused problem solving, whereas older adults showed a greater match between generative goals and other-focused problem solving. Findings speak to the importance of considering goals in investigations of age-related differences in everyday problem solving.

Perceived problem solving, stress, and health among college students.

PubMed

Largo-Wight, Erin; Peterson, P Michael; Chen, W William

2005-01-01

To study the relationships among perceived problem solving, stress, and physical health. The Perceived Stress Questionnaire (PSQ), Personal Problem solving Inventory (PSI), and a stress-related physical health symptoms checklist were used to measure perceived stress, problem solving, and health among undergraduate college students (N = 232). Perceived problem-solving ability predicted self-reported physical health symptoms (R2 = .12; P < .001) and perceived stress (R2 = .19; P < .001). Perceived problem solving was a stronger predictor of physical health and perceived stress than were physical activity, alcohol consumption, or social support. Implications for college health promotion are discussed.

Phylogenetic prediction of Alternaria leaf blight resistance in wild and cultivated species of carrots (Daucus, Apiaceae)

USDA-ARS?s Scientific Manuscript database

Plant scientists make inferences and predictions from phylogenetic trees to solve scientific problems. Crop losses due to disease damage is an important problem that many plant breeders would like to solve, so the ability to predict traits like disease resistance from phylogenetic trees derived from...

How Can We Improve Problem Solving in Undergraduate Biology? Applying Lessons from 30 Years of Physics Education Research

PubMed Central

Hoskinson, A.-M.; Caballero, M. D.; Knight, J. K.

2013-01-01

If students are to successfully grapple with authentic, complex biological problems as scientists and citizens, they need practice solving such problems during their undergraduate years. Physics education researchers have investigated student problem solving for the past three decades. Although physics and biology problems differ in structure and content, the instructional purposes align closely: explaining patterns and processes in the natural world and making predictions about physical and biological systems. In this paper, we discuss how research-supported approaches developed by physics education researchers can be adopted by biologists to enhance student problem-solving skills. First, we compare the problems that biology students are typically asked to solve with authentic, complex problems. We then describe the development of research-validated physics curricula emphasizing process skills in problem solving. We show that solving authentic, complex biology problems requires many of the same skills that practicing physicists and biologists use in representing problems, seeking relationships, making predictions, and verifying or checking solutions. We assert that acquiring these skills can help biology students become competent problem solvers. Finally, we propose how biology scholars can apply lessons from physics education in their classrooms and inspire new studies in biology education research. PMID:23737623

Spontaneous gestures influence strategy choices in problem solving.

PubMed

Alibali, Martha W; Spencer, Robert C; Knox, Lucy; Kita, Sotaro

2011-09-01

Do gestures merely reflect problem-solving processes, or do they play a functional role in problem solving? We hypothesized that gestures highlight and structure perceptual-motor information, and thereby make such information more likely to be used in problem solving. Participants in two experiments solved problems requiring the prediction of gear movement, either with gesture allowed or with gesture prohibited. Such problems can be correctly solved using either a perceptual-motor strategy (simulation of gear movements) or an abstract strategy (the parity strategy). Participants in the gesture-allowed condition were more likely to use perceptual-motor strategies than were participants in the gesture-prohibited condition. Gesture promoted use of perceptual-motor strategies both for participants who talked aloud while solving the problems (Experiment 1) and for participants who solved the problems silently (Experiment 2). Thus, spontaneous gestures influence strategy choices in problem solving.

Emotion dysregulation, problem-solving, and hopelessness.

PubMed

Vatan, Sevginar; Lester, David; Gunn, John F

2014-04-01

A sample of 87 Turkish undergraduate students was administered scales to measure hopelessness, problem-solving skills, emotion dysregulation, and psychiatric symptoms. All of the scores from these scales were strongly associated. In a multiple regression, hopelessness scores were predicted by poor problem-solving skills and emotion dysregulation.

Innovation and problem solving: a review of common mechanisms.

PubMed

Griffin, Andrea S; Guez, David

2014-11-01

Behavioural innovations have become central to our thinking about how animals adjust to changing environments. It is now well established that animals vary in their ability to innovate, but understanding why remains a challenge. This is because innovations are rare, so studying innovation requires alternative experimental assays that create opportunities for animals to express their ability to invent new behaviours, or use pre-existing ones in new contexts. Problem solving of extractive foraging tasks has been put forward as a suitable experimental assay. We review the rapidly expanding literature on problem solving of extractive foraging tasks in order to better understand to what extent the processes underpinning problem solving, and the factors influencing problem solving, are in line with those predicted, and found, to underpin and influence innovation in the wild. Our aim is to determine whether problem solving can be used as an experimental proxy of innovation. We find that in most respects, problem solving is determined by the same underpinning mechanisms, and is influenced by the same factors, as those predicted to underpin, and to influence, innovation. We conclude that problem solving is a valid experimental assay for studying innovation, propose a conceptual model of problem solving in which motor diversity plays a more central role than has been considered to date, and provide recommendations for future research using problem solving to investigate innovation. This article is part of a Special Issue entitled: Cognition in the wild. Copyright © 2014 Elsevier B.V. All rights reserved.

Learning to Predict Combinatorial Structures

NASA Astrophysics Data System (ADS)

Vembu, Shankar

2009-12-01

The major challenge in designing a discriminative learning algorithm for predicting structured data is to address the computational issues arising from the exponential size of the output space. Existing algorithms make different assumptions to ensure efficient, polynomial time estimation of model parameters. For several combinatorial structures, including cycles, partially ordered sets, permutations and other graph classes, these assumptions do not hold. In this thesis, we address the problem of designing learning algorithms for predicting combinatorial structures by introducing two new assumptions: (i) The first assumption is that a particular counting problem can be solved efficiently. The consequence is a generalisation of the classical ridge regression for structured prediction. (ii) The second assumption is that a particular sampling problem can be solved efficiently. The consequence is a new technique for designing and analysing probabilistic structured prediction models. These results can be applied to solve several complex learning problems including but not limited to multi-label classification, multi-category hierarchical classification, and label ranking.

Working Memory Components and Problem-Solving Accuracy: Are There Multiple Pathways?

ERIC Educational Resources Information Center

Swanson, H. Lee; Fung, Wenson

2016-01-01

This study determined the working memory (WM) components (executive, phonological short-term memory [STM], and visual-spatial sketchpad) that best predicted mathematical word problem-solving accuracy in elementary schoolchildren (N = 392). The battery of tests administered to assess mediators between WM and problem-solving included measures of…

Cognitive Predictors of Everyday Problem Solving across the Lifespan.

PubMed

Chen, Xi; Hertzog, Christopher; Park, Denise C

2017-01-01

An important aspect of successful aging is maintaining the ability to solve everyday problems encountered in daily life. The limited evidence today suggests that everyday problem solving ability increases from young adulthood to middle age, but decreases in older age. The present study examined age differences in the relative contributions of fluid and crystallized abilities to solving problems on the Everyday Problems Test (EPT). We hypothesized that due to diminishing fluid resources available with advanced age, crystallized knowledge would become increasingly important in predicting everyday problem solving with greater age. Two hundred and twenty-one healthy adults from the Dallas Lifespan Brain Study, aged 24-93 years, completed a cognitive battery that included measures of fluid ability (i.e., processing speed, working memory, inductive reasoning) and crystallized ability (i.e., multiple measures of vocabulary). These measures were used to predict performance on EPT. Everyday problem solving showed an increase in performance from young to early middle age, with performance beginning to decrease at about age of 50 years. As hypothesized, fluid ability was the primary predictor of performance on everyday problem solving for young adults, but with increasing age, crystallized ability became the dominant predictor. This study provides evidence that everyday problem solving ability differs with age, and, more importantly, that the processes underlying it differ with age as well. The findings indicate that older adults increasingly rely on knowledge to support everyday problem solving, whereas young adults rely almost exclusively on fluid intelligence. © 2017 S. Karger AG, Basel.

The Strengthening Families Program 10-14: influence on parent and youth problem-solving skill.

PubMed

Semeniuk, Y; Brown, R L; Riesch, S K; Zywicki, M; Hopper, J; Henriques, J B

2010-06-01

The aim of this paper is to report the results of a preliminary examination of the efficacy of the Strengthening Families Program (SFP) 10-14 in improving parent and youth problem-solving skill. The Hypotheses in this paper include: (1) youth and parents who participated in SFP would have lower mean scores immediately (T2) and 6 months (T3) post intervention on indicators of hostile and negative problem-solving strategies; (2) higher mean scores on positive problem-solving strategies; and (3) youth who participated in SFP would have higher mean scores at T2 and at T3 on indicators of individual problem solving and problem-solving efficacy than youth in the comparison group. The dyads were recruited from elementary schools that had been stratified for race and assigned randomly to intervention or comparison conditions. Mean age of youth was 11 years (SD = 1.04). Fifty-seven dyads (34-intervention&23-control) were videotaped discussing a frequently occurring problem. The videotapes were analysed using the Iowa Family Interaction Rating Scale (IFIRS) and data were analysed using Dyadic Assessment Intervention Model. Most mean scores on the IFIRS did not change. One score changed as predicted: youth hostility decreased at T3. Two scores changed contrary to prediction: parent hostility increased T3 and parent positive problem solving decreased at T2. SFP demonstrated questionable efficacy for problem-solving skill in this study.

Analyzing Log Files to Predict Students' Problem Solving Performance in a Computer-Based Physics Tutor

ERIC Educational Resources Information Center

Lee, Young-Jin

2015-01-01

This study investigates whether information saved in the log files of a computer-based tutor can be used to predict the problem solving performance of students. The log files of a computer-based physics tutoring environment called Andes Physics Tutor was analyzed to build a logistic regression model that predicted success and failure of students'…

Suicidality, Problem-Solving Skills, Attachment Style, and Hopelessness in Turkish Students

ERIC Educational Resources Information Center

Zeyrek, Emek Yuce; Gencoz, Faruk; Bergman, Yoav; Lester, David

2009-01-01

Among 180 Turkish university students, the probability of suicide was strongly predicted by both hopelessness and deficiencies in problem solving. In addition, for women, unhealthy attachment styles (preoccupied and dismissing) also predicted suicidality. The clinical implications of these findings are that psychotherapists should focus on helping…

Modeling Students' Problem Solving Performance in the Computer-Based Mathematics Learning Environment

ERIC Educational Resources Information Center

Lee, Young-Jin

2017-01-01

Purpose: The purpose of this paper is to develop a quantitative model of problem solving performance of students in the computer-based mathematics learning environment. Design/methodology/approach: Regularized logistic regression was used to create a quantitative model of problem solving performance of students that predicts whether students can…

The Effect of Communication Skills and Interpersonal Problem Solving Skills on Social Self-Efficacy

ERIC Educational Resources Information Center

Erozkan, Atilgan

2013-01-01

The purpose of this study was to examine communication skills, interpersonal problem solving skills, and social self-efficacy perception of adolescents and the predictive role of communication skills and interpersonal problem solving skills on social self-efficacy. This study is a quantitative and relational study aimed at examining the…

The Effects of Labels on Learning Subgoals for Solving Problems.

ERIC Educational Resources Information Center

Catrambone, Richard

This study, involving 65 undergraduates at the Georgia Institute of Technology (Atlanta); explores a scheme for representing problem-solving knowledge and predicting transfer as a function of problem-solving subgoals acquired from examples. A subgoal is an unknown entity (numerical or conceptual) that needs to be found in order to achieve a higher…

Visual Attention for Solving Multiple-Choice Science Problem: An Eye-Tracking Analysis

ERIC Educational Resources Information Center

Tsai, Meng-Jung; Hou, Huei-Tse; Lai, Meng-Lung; Liu, Wan-Yi; Yang, Fang-Ying

2012-01-01

This study employed an eye-tracking technique to examine students' visual attention when solving a multiple-choice science problem. Six university students participated in a problem-solving task to predict occurrences of landslide hazards from four images representing four combinations of four factors. Participants' responses and visual attention…

Evolutionary Dynamic Multiobjective Optimization Via Kalman Filter Prediction.

PubMed

Muruganantham, Arrchana; Tan, Kay Chen; Vadakkepat, Prahlad

2016-12-01

Evolutionary algorithms are effective in solving static multiobjective optimization problems resulting in the emergence of a number of state-of-the-art multiobjective evolutionary algorithms (MOEAs). Nevertheless, the interest in applying them to solve dynamic multiobjective optimization problems has only been tepid. Benchmark problems, appropriate performance metrics, as well as efficient algorithms are required to further the research in this field. One or more objectives may change with time in dynamic optimization problems. The optimization algorithm must be able to track the moving optima efficiently. A prediction model can learn the patterns from past experience and predict future changes. In this paper, a new dynamic MOEA using Kalman filter (KF) predictions in decision space is proposed to solve the aforementioned problems. The predictions help to guide the search toward the changed optima, thereby accelerating convergence. A scoring scheme is devised to hybridize the KF prediction with a random reinitialization method. Experimental results and performance comparisons with other state-of-the-art algorithms demonstrate that the proposed algorithm is capable of significantly improving the dynamic optimization performance.

Cognitive Predictors of Everyday Problem Solving across the Lifespan

PubMed Central

Chen, Xi; Hertzog, Christopher; Park, Denise C.

2017-01-01

Background An important aspect of successful aging is maintaining the ability to solve everyday problems encountered in daily life. The limited evidence today suggests that everyday problem solving ability increases from young adulthood to middle age, but decreases in older age. Objectives The present study examined age differences in the relative contributions of fluid and crystallized abilities to solving problems on the Everyday Problems Test (EPT; [1]). We hypothesized that due to diminishing fluid resources available with advanced age, crystallized knowledge would become increasingly important in predicting everyday problem solving with greater age. Method Two hundred and twenty-one healthy adults from the Dallas Lifespan Brain Study, aged 24–93 years, completed a cognitive battery that included measures of fluid ability (i.e., processing speed, working memory, inductive reasoning) and crystallized ability (i.e., multiple measures of vocabulary). These measures were used to predict performance on the Everyday Problems Test. Results Everyday problem solving showed an increase in performance from young to early middle age, with performance beginning to decrease at about age of fifty. As hypothesized, fluid ability was the primary predictor of performance on everyday problem solving for young adults, but with increasing age, crystallized ability became the dominant predictor. Conclusion This study provides evidence that everyday problem solving ability differs with age, and, more importantly, that the processes underlying it differ with age as well. The findings indicate that older adults increasingly rely on knowledge to support everyday problem solving, whereas young adults rely almost exclusively on fluid intelligence. PMID:28273664

Revising explanatory models to accommodate anomalous genetic phenomena: Problem solving in the context of discovery

NASA Astrophysics Data System (ADS)

Hafner, Robert; Stewart, Jim

Past problem-solving research has provided a basis for helping students structure their knowledge and apply appropriate problem-solving strategies to solve problems for which their knowledge (or mental models) of scientific phenomena is adequate (model-using problem solving). This research examines how problem solving in the domain of Mendelian genetics proceeds in situations where solvers' mental models are insufficient to solve problems at hand (model-revising problem solving). Such situations require solvers to use existing models to recognize anomalous data and to revise those models to accommodate the data. The study was conducted in the context of 9-week high school genetics course and addressed: the heuristics charactenstic of successful model-revising problem solving: the nature of the model revisions, made by students as well as the nature of model development across problem types; and the basis upon which solvers decide that a revised model is sufficient (that t has both predictive and explanatory power).

Social problem-solving deficits and hopelessness, depression, and suicidal risk in college students and psychiatric inpatients.

PubMed

D'Zurilla, T J; Chang, E C; Nottingham, E J; Faccini, L

1998-12-01

The Social Problem-Solving Inventory-Revised was used to examine the relations between problem-solving abilities and hopelessness, depression, and suicidal risk in three different samples: undergraduate college students, general psychiatric inpatients, and suicidal psychiatric inpatients. A similar pattern of results was found in both college students and psychiatric patients: a negative problem orientation was most highly correlated with all three criterion variables, followed by either a positive problem orientation or an avoidance problem-solving style. Rational problem-solving skills emerged as an important predictor variable in the suicidal psychiatric sample. Support was found for a prediction model of suicidal risk that includes problem-solving deficits and hopelessness, with partial support being found for including depression in the model as well.

Primary School Text Comprehension Predicts Mathematical Word Problem-Solving Skills in Secondary School

ERIC Educational Resources Information Center

Björn, Piia Maria; Aunola, Kaisa; Nurmi, Jari-Erik

2016-01-01

This longitudinal study aimed to investigate the extent to which primary school text comprehension predicts mathematical word problem-solving skills in secondary school among Finnish students. The participants were 224 fourth graders (9-10 years old at the baseline). The children's text-reading fluency, text comprehension and basic calculation…

The Roles of Negative Career Thinking and Career Problem-Solving Self-Efficacy in Career Exploratory Behavior

ERIC Educational Resources Information Center

Bullock-Yowell, Emily; Katz, Sheba P.; Reardon, Robert C.; Peterson, Gary W.

2012-01-01

The respective roles of social cognitive career theory and cognitive information processing in career exploratory behavior were analyzed. A verified path model shows cognitive information processing theory's negative career thoughts inversely predict social cognitive career theory's career problem-solving self-efficacy, which predicts career…

Validity of the MicroDYN Approach: Complex Problem Solving Predicts School Grades beyond Working Memory Capacity

ERIC Educational Resources Information Center

Schweizer, Fabian; Wustenberg, Sascha; Greiff, Samuel

2013-01-01

This study examines the validity of the complex problem solving (CPS) test MicroDYN by investigating a) the relation between its dimensions--rule identification (exploration strategy), rule knowledge (acquired knowledge), rule application (control performance)--and working memory capacity (WMC), and b) whether CPS predicts school grades in…

Validation of Predictive Relationship of Creative Problem-Solving Attrubutes with Math Creativity

ERIC Educational Resources Information Center

Pham, Linh Hung

2014-01-01

This study was designed to investigate the predictive relationships of creative problem-solving attributes, which comprise divergent thinking, convergent thinking, motivation, general and domain knowledge and skills, and environment, with mathematical creativity of sixth grade students in Thai Nguyen City, Viet Nam. The study also aims to revise…

Collective Problem-Solving: The Role of Self-Efficacy, Skill, and Prior Knowledge

ERIC Educational Resources Information Center

Geifman, Dorit; Raban, Daphne R.

2015-01-01

Self-efficacy is essential to learning but what happens when learning is done as a result of a collective process? What is the role of individual self-efficacy in collective problem solving? This research examines the manifestation of self-efficacy in prediction markets that are configured as collective problem-solving platforms and whether…

Analysis of Social Problem Solving and Social Self-Efficacy in Prospective Teachers

ERIC Educational Resources Information Center

Erozkan, Atilgan

2014-01-01

The purpose of this study is to investigate the relationship between social problem solving and social selfefficacy and the predictive role of social problem solving skills with social self-efficacy. The sample consists of 706 prospective teachers (362 female and 344 male) who are majoring in different fields at Mugla Sitki Kocman University's…

Rosetta Structure Prediction as a Tool for Solving Difficult Molecular Replacement Problems.

PubMed

DiMaio, Frank

2017-01-01

Molecular replacement (MR), a method for solving the crystallographic phase problem using phases derived from a model of the target structure, has proven extremely valuable, accounting for the vast majority of structures solved by X-ray crystallography. However, when the resolution of data is low, or the starting model is very dissimilar to the target protein, solving structures via molecular replacement may be very challenging. In recent years, protein structure prediction methodology has emerged as a powerful tool in model building and model refinement for difficult molecular replacement problems. This chapter describes some of the tools available in Rosetta for model building and model refinement specifically geared toward difficult molecular replacement cases.

Racism-related stress, Africultural coping, and religious problem-solving among African Americans.

PubMed

Lewis-Coles, Ma'at E Lyris; Constantine, Madonna G

2006-07-01

This study explored the extent to which three types of racism-related stress (i.e., individual, institutional, and cultural) would predict the use of specific Africultural coping strategies (i.e., cognitive/emotional debriefing, spiritual-centered, collective, and ritual-centered coping) and religious problem-solving styles (i.e., self-directing, deferring, and collaborative) in a sample of 284 African American men and women. The authors found that higher institutional racism-related stress was associated with greater use of cognitive/emotional debriefing, spiritual-centered, and collective coping in African American women. Findings also indicated that higher cultural racism-related stress was predictive of lower use of self-directing religious problem-solving in African American women. Moreover, higher perceived cultural racism-related stress was related to greater use of collective coping strategies in African American men. Individual racism-related stress was not predictive of any forms of Africultural coping strategies or religious problem-solving. Implications of the findings are discussed.

Goal specificity and knowledge acquisition in statistics problem solving: evidence for attentional focus.

PubMed

Trumpower, David L; Goldsmith, Timothy E; Guynn, Melissa J

2004-12-01

Solving training problems with nonspecific goals (NG; i.e., solving for all possible unknown values) often results in better transfer than solving training problems with standard goals (SG; i.e., solving for one particular unknown value). In this study, we evaluated an attentional focus explanation of the goal specificity effect. According to the attentional focus view, solving NG problems causes attention to be directed to local relations among successive problem states, whereas solving SG problems causes attention to be directed to relations between the various problem states and the goal state. Attention to the former is thought to enhance structural knowledge about the problem domain and thus promote transfer. Results supported this view because structurally different transfer problems were solved faster following NG training than following SG training. Moreover, structural knowledge representations revealed more links depicting local relations following NG training and more links to the training goal following SG training. As predicted, these effects were obtained only by domain novices.

How do Rumination and Social Problem Solving Intensify Depression? A Longitudinal Study.

PubMed

Hasegawa, Akira; Kunisato, Yoshihiko; Morimoto, Hiroshi; Nishimura, Haruki; Matsuda, Yuko

2018-01-01

In order to examine how rumination and social problem solving intensify depression, the present study investigated longitudinal associations among each dimension of rumination and social problem solving and evaluated aspects of these constructs that predicted subsequent depression. A three-wave longitudinal study, with an interval of 4 weeks between waves, was conducted. Japanese university students completed the Beck Depression Inventory-Second Edition, Ruminative Responses Scale, Social Problem-Solving Inventory-Revised Short Version, and Interpersonal Stress Event Scale on three occasions 4 weeks apart ( n  = 284 at Time 1, 198 at Time 2, 165 at Time 3). Linear mixed models were analyzed to test whether each variable predicted subsequent depression, rumination, and each dimension of social problem solving. Rumination and negative problem orientation demonstrated a mutually enhancing relationship. Because these two variables were not associated with interpersonal conflict during the subsequent 4 weeks, rumination and negative problem orientation appear to strengthen each other without environmental change. Rumination and impulsivity/carelessness style were associated with subsequent depressive symptoms, after controlling for the effect of initial depression. Because rumination and impulsivity/carelessness style were not concurrently and longitudinally associated with each other, rumination and impulsive/careless problem solving style appear to be independent processes that serve to intensify depression.

Lesion mapping of social problem solving

PubMed Central

Colom, Roberto; Paul, Erick J.; Chau, Aileen; Solomon, Jeffrey; Grafman, Jordan H.

2014-01-01

Accumulating neuroscience evidence indicates that human intelligence is supported by a distributed network of frontal and parietal regions that enable complex, goal-directed behaviour. However, the contributions of this network to social aspects of intellectual function remain to be well characterized. Here, we report a human lesion study (n = 144) that investigates the neural bases of social problem solving (measured by the Everyday Problem Solving Inventory) and examine the degree to which individual differences in performance are predicted by a broad spectrum of psychological variables, including psychometric intelligence (measured by the Wechsler Adult Intelligence Scale), emotional intelligence (measured by the Mayer, Salovey, Caruso Emotional Intelligence Test), and personality traits (measured by the Neuroticism-Extraversion-Openness Personality Inventory). Scores for each variable were obtained, followed by voxel-based lesion–symptom mapping. Stepwise regression analyses revealed that working memory, processing speed, and emotional intelligence predict individual differences in everyday problem solving. A targeted analysis of specific everyday problem solving domains (involving friends, home management, consumerism, work, information management, and family) revealed psychological variables that selectively contribute to each. Lesion mapping results indicated that social problem solving, psychometric intelligence, and emotional intelligence are supported by a shared network of frontal, temporal, and parietal regions, including white matter association tracts that bind these areas into a coordinated system. The results support an integrative framework for understanding social intelligence and make specific recommendations for the application of the Everyday Problem Solving Inventory to the study of social problem solving in health and disease. PMID:25070511

A life history approach to delineating how harsh environments and hawk temperament traits differentially shape children's problem-solving skills.

PubMed

Suor, Jennifer H; Sturge-Apple, Melissa L; Davies, Patrick T; Cicchetti, Dante

2017-08-01

Harsh environments are known to predict deficits in children's cognitive abilities. Life history theory approaches challenge this interpretation, proposing stressed children's cognition becomes specialized to solve problems in fitness-enhancing ways. The goal of this study was to examine associations between early environmental harshness and children's problem-solving outcomes across tasks varying in ecological relevance. In addition, we utilize an evolutionary model of temperament toward further specifying whether hawk temperament traits moderate these associations. Two hundred and one mother-child dyads participated in a prospective multimethod study when children were 2 and 4 years old. At age 2, environmental harshness was assessed via maternal report of earned income and observations of maternal disengagement during a parent-child interaction task. Children's hawk temperament traits were assessed from a series of unfamiliar episodes. At age 4, children's reward-oriented and visual problem-solving were measured. Path analyses revealed early environmental harshness and children's hawk temperament traits predicted worse visual problem-solving. Results showed a significant two-way interaction between children's hawk temperament traits and environmental harshness on reward-oriented problem-solving. Simple slope analyses revealed the effect of environmental harshness on reward-oriented problem-solving was specific to children with higher levels of hawk traits. Results suggest early experiences of environmental harshness and child hawk temperament traits shape children's trajectories of problem-solving in an environment-fitting manner. © 2017 Association for Child and Adolescent Mental Health.

Investigation of Problem-Solving and Problem-Posing Abilities of Seventh-Grade Students

ERIC Educational Resources Information Center

Arikan, Elif Esra; Ünal, Hasan

2015-01-01

This study aims to examine the effect of multiple problem-solving skills on the problem-posing abilities of gifted and non-gifted students and to assess whether the possession of such skills can predict giftedness or affect problem-posing abilities. Participants' metaphorical images of problem posing were also explored. Participants were 20 gifted…

Decomposing intuitive components in a conceptual problem solving task.

PubMed

Reber, Rolf; Ruch-Monachon, Marie-Antoinette; Perrig, Walter J

2007-06-01

Research into intuitive problem solving has shown that objective closeness of participants' hypotheses were closer to the accurate solution than their subjective ratings of closeness. After separating conceptually intuitive problem solving from the solutions of rational incremental tasks and of sudden insight tasks, we replicated this finding by using more precise measures in a conceptual problem-solving task. In a second study, we distinguished performance level, processing style, implicit knowledge and subjective feeling of closeness to the solution within the problem-solving task and examined the relationships of these different components with measures of intelligence and personality. Verbal intelligence correlated with performance level in problem solving, but not with processing style and implicit knowledge. Faith in intuition, openness to experience, and conscientiousness correlated with processing style, but not with implicit knowledge. These findings suggest that one needs to decompose processing style and intuitive components in problem solving to make predictions on effects of intelligence and personality measures.

Analogy as a strategy for supporting complex problem solving under uncertainty.

PubMed

Chan, Joel; Paletz, Susannah B F; Schunn, Christian D

2012-11-01

Complex problem solving in naturalistic environments is fraught with uncertainty, which has significant impacts on problem-solving behavior. Thus, theories of human problem solving should include accounts of the cognitive strategies people bring to bear to deal with uncertainty during problem solving. In this article, we present evidence that analogy is one such strategy. Using statistical analyses of the temporal dynamics between analogy and expressed uncertainty in the naturalistic problem-solving conversations among scientists on the Mars Rover Mission, we show that spikes in expressed uncertainty reliably predict analogy use (Study 1) and that expressed uncertainty reduces to baseline levels following analogy use (Study 2). In addition, in Study 3, we show with qualitative analyses that this relationship between uncertainty and analogy is not due to miscommunication-related uncertainty but, rather, is primarily concentrated on substantive problem-solving issues. Finally, we discuss a hypothesis about how analogy might serve as an uncertainty reduction strategy in naturalistic complex problem solving.

Problem-solving style and multicultural personality dispositions: a study of construct validity.

PubMed

Houtz, John C; Ponterotto, Joseph G; Burger, Claudia; Marino, Cherylynn

2010-06-01

This exploratory study examined the relationship between problem-solving styles and multicultural personality dispositions among 91 graduate students enrolled in an urban university located in the northeast United States. Problem-solving style was assessed with the three dimensions of the VIEW: an Assessment of Problem Solving Style. Multicultural personality was assessed with the five-factor Multicultural Personality Questionnaire (MPQ); its factors of Cultural Empathy, Open-mindedness, Social Initiative, and Flexibility correlated significantly with Explorer and External problem-solving styles, as predicted. The Emotional Stability subscale also correlated significantly with scores on Explorer style, suggesting that individuals who prefer "thinking in new directions" in problem solving are more likely to report remaining calm under stressful situations. Collectively, study results provided additional evidence of construct validity for the VIEW.

Social Problem Solving and Depressive Symptoms Over Time: A Randomized Clinical Trial of Cognitive Behavioral Analysis System of Psychotherapy, Brief Supportive Psychotherapy, and Pharmacotherapy

PubMed Central

Klein, Daniel N.; Leon, Andrew C.; Li, Chunshan; D’Zurilla, Thomas J.; Black, Sarah R.; Vivian, Dina; Dowling, Frank; Arnow, Bruce A.; Manber, Rachel; Markowitz, John C.; Kocsis, James H.

2011-01-01

Objective Depression is associated with poor social problem-solving, and psychotherapies that focus on problem-solving skills are efficacious in treating depression. We examined the associations between treatment, social problem solving, and depression in a randomized clinical trial testing the efficacy of psychotherapy augmentation for chronically depressed patients who failed to fully respond to an initial trial of pharmacotherapy (Kocsis et al., 2009). Method Participants with chronic depression (n = 491) received Cognitive Behavioral Analysis System of Psychotherapy (CBASP), which emphasizes interpersonal problem-solving, plus medication; Brief Supportive Psychotherapy (BSP) plus medication; or medication alone for 12 weeks. Results CBASP plus pharmacotherapy was associated with significantly greater improvement in social problem solving than BSP plus pharmacotherapy, and a trend for greater improvement in problem solving than pharmacotherapy alone. In addition, change in social problem solving predicted subsequent change in depressive symptoms over time. However, the magnitude of the associations between changes in social problem solving and subsequent depressive symptoms did not differ across treatment conditions. Conclusions It does not appear that improved social problem solving is a mechanism that uniquely distinguishes CBASP from other treatment approaches. PMID:21500885

Predicting Academic Success of Junior Secondary School Students in Mathematics through Cognitive Style and Problem Solving Technique

ERIC Educational Resources Information Center

Badru, Ademola K.

2015-01-01

This study examined the prediction of academic success of Junior secondary school mathematics students using their cognitive style and problem solving technique. A descriptive survey of correlation type was adopted for this study. A purposive sampling procedure was used to select five Public Junior secondary schools in Ijebu-Ode local government…

The Complex Route to Success: Complex Problem-Solving Skills in the Prediction of University Success

ERIC Educational Resources Information Center

Stadler, Matthias J.; Becker, Nicolas; Greiff, Samuel; Spinath, Frank M.

2016-01-01

Successful completion of a university degree is a complex matter. Based on considerations regarding the demands of acquiring a university degree, the aim of this paper was to investigate the utility of complex problem-solving (CPS) skills in the prediction of objective and subjective university success (SUS). The key finding of this study was that…

Active and passive problem solving: moderating role in the relation between depressive symptoms and future suicidal ideation varies by suicide attempt history.

PubMed

Quiñones, Victoria; Jurska, Justyna; Fener, Eileen; Miranda, Regina

2015-04-01

Research suggests that being unable to generate solutions to problems in times of distress may contribute to suicidal thoughts and behavior, and that depression is associated with problem-solving deficits. This study examined active and passive problem solving as moderators of the association between depressive symptoms and future suicidal ideation among suicide attempters and nonattempters. Young adults (n = 324, 73% female, mean age = 19, standard deviation = 2.22) with (n = 78) and without (n = 246) a suicide attempt history completed a problem-solving task, self-report measures of hopelessness, depression, and suicidal ideation at baseline, and a self-report measure of suicidal ideation at 6-month follow-up. Passive problem solving was higher among suicide attempters but did not moderate the association between depressive symptoms and future suicidal ideation. Among attempters, active problem solving buffered against depressive symptoms in predicting future suicidal ideation. Suicide prevention should foster active problem solving, especially among suicide attempters. © 2015 Wiley Periodicals, Inc.

Active and Passive Problem Solving: Moderating Role in the Relation between Depressive Symptoms and Future Suicidal Ideation Varies by Suicide Attempt History

PubMed Central

Quiñones, Victoria; Jurska, Justyna; Fener, Eileen; Miranda, Regina

2016-01-01

Objective Research suggests that being unable to generate solutions to problems in times of distress may contribute to suicidal thoughts and behavior, and that depression is associated with problem solving deficits. This study examined active and passive problem solving as moderators of the association between depressive symptoms and future suicidal ideation (SI) among suicide attempters and non-attempters. Method Young adults (n = 324, 73% female, Mage = 19, SD = 2.22) with (n = 78) and without (n = 246) a suicide attempt history completed a problem-solving task, self-report measures of hopelessness, depression, and SI at baseline, and also completed a self-report measure of SI at 6-month follow-up. Results Passive problem solving was higher among suicide attempters but did not moderate the association between depressive symptoms and future SI. Among attempters, active problem solving buffered against depressive symptoms in predicting future SI. Conclusions Suicide prevention should foster active problem solving, especially among suicide attempters. PMID:25760651

The relation of locus-of-control orientation and task structure to problem-solving performance of sixth-grade student pairs

NASA Astrophysics Data System (ADS)

Main, June Dewey; Budd Rowe, Mary

This study investigated the relationship of locus-of-control orientations and task structure to the science problem-solving performance of 100 same-sex, sixth-grade student pairs. Pairs performed a four-variable problem-solving task, racing cylinders down a ramp in a series of trials to determine the 3 fastest of 18 different cylinders. The task was completed in one of two treatment conditions: the structured condition with moderate cuing and the unstructured condition with minimal cuing. Pairs completed an after-task assessment, predicting the results of proposed cylinder races, to measure the ability to understand and apply task concepts. Overall conclusions were: (1) There was no relationship between locus-of-control orientation and effectiveness of problem-solving strategy; (2) internality was significantly related to higher accuracy on task solutions and on after-task predictions; (3) there was no significant relationship between task structure and effectiveness of problem-solving strategy; (4) solutions to the task were more accurate in the unstructured task condition; (5) internality related to more accurate solutions in the unstructured task condition.

Mathematical learning disabilities and attention deficit and/or hyperactivity disorder: A study of the cognitive processes involved in arithmetic problem solving.

PubMed

Iglesias-Sarmiento, Valentín; Deaño, Manuel; Alfonso, Sonia; Conde, Ángeles

2017-02-01

The purpose of this study was to examine the contribution of cognitive functioning to arithmetic problem solving and to explore the cognitive profiles of children with attention deficit and/or hyperactivity disorder (ADHD) and with mathematical learning disabilities (MLD). The sample was made up of a total of 90 students of 4th, 5th, and 6th grade organized in three: ADHD (n=30), MLD (n=30) and typically achieving control (TA; n=30) group. Assessment was conducted in two sessions in which the PASS processes and arithmetic problem solving were evaluated. The ADHD group's performance in planning and attention was worse than that of the control group. Children with MLD obtained poorer results than the control group in planning and simultaneous and successive processing. Executive processes predicted arithmetic problem solving in the ADHD group whereas simultaneous processing was the unique predictor in the MLD sample. Children with ADHD and with MLD showed characteristic cognitive profiles. Groups' problem-solving performance can be predicted from their cognitive functioning. Copyright © 2016 Elsevier Ltd. All rights reserved.

Social problem-solving among adolescents treated for depression.

PubMed

Becker-Weidman, Emily G; Jacobs, Rachel H; Reinecke, Mark A; Silva, Susan G; March, John S

2010-01-01

Studies suggest that deficits in social problem-solving may be associated with increased risk of depression and suicidality in children and adolescents. It is unclear, however, which specific dimensions of social problem-solving are related to depression and suicidality among youth. Moreover, rational problem-solving strategies and problem-solving motivation may moderate or predict change in depression and suicidality among children and adolescents receiving treatment. The effect of social problem-solving on acute treatment outcomes were explored in a randomized controlled trial of 439 clinically depressed adolescents enrolled in the Treatment for Adolescents with Depression Study (TADS). Measures included the Children's Depression Rating Scale-Revised (CDRS-R), the Suicidal Ideation Questionnaire--Grades 7-9 (SIQ-Jr), and the Social Problem-Solving Inventory-Revised (SPSI-R). A random coefficients regression model was conducted to examine main and interaction effects of treatment and SPSI-R subscale scores on outcomes during the 12-week acute treatment stage. Negative problem orientation, positive problem orientation, and avoidant problem-solving style were non-specific predictors of depression severity. In terms of suicidality, avoidant problem-solving style and impulsiveness/carelessness style were predictors, whereas negative problem orientation and positive problem orientation were moderators of treatment outcome. Implications of these findings, limitations, and directions for future research are discussed. Copyright 2009 Elsevier Ltd. All rights reserved.

Spatial Visualization in Physics Problem Solving

ERIC Educational Resources Information Center

Kozhevnikov, Maria; Motes, Michael A.; Hegarty, Mary

2007-01-01

Three studies were conducted to examine the relation of spatial visualization to solving kinematics problems that involved either predicting the two-dimensional motion of an object, translating from one frame of reference to another, or interpreting kinematics graphs. In Study 1, 60 physics-naive students were administered kinematics problems and…

Do clients' problem-solving appraisals predict career counseling outcomes or vice versa? A reanalysis of Heppner, et al.

PubMed

Lee, Dong-Gwi; Park, Hyun-Joo; Heppner, Mary J

2009-12-01

Using Heppner, et al.'s data from 2004, this study tested career counseling clients in the United States on problem-solving appraisal scores and career-related variables. A cross-lagged panel design with structural equation modeling was used. Results supported the link between clients' precounseling problem-solving appraisal scores and career outcome. This finding held for career decision-making, but not for vocational identity. The study provided further support for Heppner, et al.'s findings, highlighting the influential role of clients' problem-solving appraisals in advancing their career decision-making processes.

Personal and parental problem drinking: effects on problem-solving performance and self-appraisal.

PubMed

Slavkin, S L; Heimberg, R G; Winning, C D; McCaffrey, R J

1992-01-01

This study examined the problem-solving performances and self-appraisals of problem-solving ability of college-age subjects with and without parental history of problem drinking. Contrary to our predictions, children of problem drinkers (COPDs) were rated as somewhat more effective in their problem-solving skills than non-COPDs, undermining prevailing assumptions about offspring from alcoholic households. While this difference was not large and was qualified by other variables, subjects' own alcohol abuse did exert a detrimental effect on problem-solving performance, regardless of parental history of problem drinking. However, a different pattern was evident for problem-solving self-appraisals. Alcohol-abusing non-COPDs saw themselves as effective problem-solvers while alcohol-abusing COPDs appraised themselves as poor problem-solvers. In addition, the self-appraisals of alcohol-abusing COPDs were consistent with objective ratings of solution effectiveness (i.e., they were both negative) while alcohol-abusing non-COPDs were overly positive in their appraisals, opposing the judgments of trained raters. This finding suggests that the relationship between personal alcohol abuse and self-appraised problem-solving abilities may differ as a function of parental history of problem drinking. Limitations on the generalizability of findings are addressed.

Early in-session cognitive-emotional problem-solving predicts 12-month outcomes in depression with personality disorder.

PubMed

McCarthy, Kye L; Mergenthaler, Erhard; Grenyer, Brin F S

2014-01-01

Therapist-patient verbalizations reveal complex cognitive-emotional linguistic data. How these variables contribute to change requires further research. Emotional-cognitive text analysis using the Ulm cycles model software was applied to transcripts of the third session of psychotherapy for 20 patients with depression and personality disorder. Results showed that connecting cycle sequences of problem-solving in the third hour predicted 12-month clinical outcomes. Therapist-patient dyads most improved spent significantly more time early in session in connecting cycles, whilst the least improved moved into connecting cycles late in session. For this particular sample, it was clear that positive emotional problem-solving in therapy was beneficial.

Behavioral flexibility and problem solving in an invasive bird.

PubMed

Logan, Corina J

2016-01-01

Behavioral flexibility is considered an important trait for adapting to environmental change, but it is unclear what it is, how it works, and whether it is a problem solving ability. I investigated behavioral flexibility and problem solving experimentally in great-tailed grackles, an invasive bird species and thus a likely candidate for possessing behavioral flexibility. Grackles demonstrated behavioral flexibility in two contexts, the Aesop's Fable paradigm and a color association test. Contrary to predictions, behavioral flexibility did not correlate across contexts. Four out of 6 grackles exhibited efficient problem solving abilities, but problem solving efficiency did not appear to be directly linked with behavioral flexibility. Problem solving speed also did not significantly correlate with reversal learning scores, indicating that faster learners were not the most flexible. These results reveal how little we know about behavioral flexibility, and provide an immense opportunity for future research to explore how individuals and species can use behavior to react to changing environments.

Problem-Solving Attitudes and Gender as Predictors of Academic Achievement in Mathematics and Science for Canadian and Finnish Students in the PISA 2012 Assessment

ERIC Educational Resources Information Center

Cutumisu, Maria; Bulut, Okan

2017-01-01

This study aims to understand the predictive role of attitudes towards problem solving, such as perseverance and openness for problem solving, as well as of gender and country for Canadian and Finnish students' academic achievement in mathematics and science. We examined the data of students from Canada (n = 21,544) and Finland (n = 8,829) who…

Lesion mapping of social problem solving.

PubMed

Barbey, Aron K; Colom, Roberto; Paul, Erick J; Chau, Aileen; Solomon, Jeffrey; Grafman, Jordan H

2014-10-01

Accumulating neuroscience evidence indicates that human intelligence is supported by a distributed network of frontal and parietal regions that enable complex, goal-directed behaviour. However, the contributions of this network to social aspects of intellectual function remain to be well characterized. Here, we report a human lesion study (n = 144) that investigates the neural bases of social problem solving (measured by the Everyday Problem Solving Inventory) and examine the degree to which individual differences in performance are predicted by a broad spectrum of psychological variables, including psychometric intelligence (measured by the Wechsler Adult Intelligence Scale), emotional intelligence (measured by the Mayer, Salovey, Caruso Emotional Intelligence Test), and personality traits (measured by the Neuroticism-Extraversion-Openness Personality Inventory). Scores for each variable were obtained, followed by voxel-based lesion-symptom mapping. Stepwise regression analyses revealed that working memory, processing speed, and emotional intelligence predict individual differences in everyday problem solving. A targeted analysis of specific everyday problem solving domains (involving friends, home management, consumerism, work, information management, and family) revealed psychological variables that selectively contribute to each. Lesion mapping results indicated that social problem solving, psychometric intelligence, and emotional intelligence are supported by a shared network of frontal, temporal, and parietal regions, including white matter association tracts that bind these areas into a coordinated system. The results support an integrative framework for understanding social intelligence and make specific recommendations for the application of the Everyday Problem Solving Inventory to the study of social problem solving in health and disease. © The Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Testing bidirectional associations among emotion regulation strategies and substance use: a daily diary study.

PubMed

Weiss, Nicole H; Bold, Krysten W; Sullivan, Tami P; Armeli, Stephen; Tennen, Howard

2017-04-01

Alcohol and marijuana are widely used among college students. Emotion regulation strategies have been linked to alcohol and marijuana use, but little attention has been devoted to modeling the directionality of these associations. The aims of the current study were to test whether (a) daytime use of emotion regulation strategies influences the likelihood of evening substance use and (b) evening substance use influences the likelihood of next-day use of emotion regulation strategies. Longitudinal daily diary data were collected for 30 days via on-line surveys. Northeastern United States. A total of 1640 college students (mean age = 19.2 years, 54% female, 80% European American) were recruited each semester between Spring 2008 and Spring 2012. Daily diaries assessed emotion regulation strategies (distraction, reappraisal, problem-solving, avoidance) and substance use (any drinking, heavy drinking, marijuana use, co-use of any drinking/heavy drinking and marijuana). Covariates included gender, age, race/ethnicity, fraternity/sorority involvement and baseline depression. Daytime distraction [odds ratio (OR) = 0.95], reappraisal (OR = 0.95) and problem-solving (OR = 0.94) predicted lower odds of evening marijuana use (P-values < 0.02). Evening heavy drinking (OR = 0.90) and marijuana use (OR = 0.89) predicted lower odds of next-day problem-solving, with heavy drinking also predicting higher odds (OR = 1.08) of next-day avoidance and marijuana use also predicting higher odds (OR = 1.08) of next-day reappraisal (P-values < 0.03). There appear to be reciprocal relations among emotion regulation strategies and substance use: greater daytime use of distraction, reappraisal, and problem solving predicts lower evening substance use, while higher evening substance use predicts higher next-day avoidance and reappraisal but lower next-day problem-solving. © 2016 Society for the Study of Addiction.

Clusters of Behaviors and Beliefs Predicting Adolescent Depression: Implications for Prevention

PubMed Central

Paunesku, David; Ellis, Justin; Fogel, Joshua; Kuwabara, Sachiko A; Gollan, Jackie; Gladstone, Tracy; Reinecke, Mark; Van Voorhees, Benjamin W.

2009-01-01

OBJECTIVE Risk factors for various disorders are known to cluster. However, the factor structure for behaviors and beliefs predicting depressive disorder in adolescents is not known. Knowledge of this structure can facilitate prevention planning. METHODS We used the National Longitudinal Study of Adolescent Health (AddHealth) data set to conduct an exploratory factor analysis to identify clusters of behaviors/experiences predicting the onset of major depressive disorder (MDD) at 1-year follow-up (N=4,791). RESULTS Four factors were identified: family/interpersonal relations, self-emancipation, avoidant problem solving/low self-worth, and religious activity. Strong family/interpersonal relations were the most significantly protective against depression at one year follow-up. Avoidant problem solving/low self-worth was not predictive of MDD on its own, but significantly amplified the risks associated with delinquency. CONCLUSION Depression prevention interventions should consider giving family relationships a more central role in their efforts. Programs teaching problem solving skills may be most appropriate for reducing MDD risk in delinquent youth. PMID:20502621

Generating optimal control simulations of musculoskeletal movement using OpenSim and MATLAB.

PubMed

Lee, Leng-Feng; Umberger, Brian R

2016-01-01

Computer modeling, simulation and optimization are powerful tools that have seen increased use in biomechanics research. Dynamic optimizations can be categorized as either data-tracking or predictive problems. The data-tracking approach has been used extensively to address human movement problems of clinical relevance. The predictive approach also holds great promise, but has seen limited use in clinical applications. Enhanced software tools would facilitate the application of predictive musculoskeletal simulations to clinically-relevant research. The open-source software OpenSim provides tools for generating tracking simulations but not predictive simulations. However, OpenSim includes an extensive application programming interface that permits extending its capabilities with scripting languages such as MATLAB. In the work presented here, we combine the computational tools provided by MATLAB with the musculoskeletal modeling capabilities of OpenSim to create a framework for generating predictive simulations of musculoskeletal movement based on direct collocation optimal control techniques. In many cases, the direct collocation approach can be used to solve optimal control problems considerably faster than traditional shooting methods. Cyclical and discrete movement problems were solved using a simple 1 degree of freedom musculoskeletal model and a model of the human lower limb, respectively. The problems could be solved in reasonable amounts of time (several seconds to 1-2 hours) using the open-source IPOPT solver. The problems could also be solved using the fmincon solver that is included with MATLAB, but the computation times were excessively long for all but the smallest of problems. The performance advantage for IPOPT was derived primarily by exploiting sparsity in the constraints Jacobian. The framework presented here provides a powerful and flexible approach for generating optimal control simulations of musculoskeletal movement using OpenSim and MATLAB. This should allow researchers to more readily use predictive simulation as a tool to address clinical conditions that limit human mobility.

Generating optimal control simulations of musculoskeletal movement using OpenSim and MATLAB

PubMed Central

Lee, Leng-Feng

2016-01-01

Computer modeling, simulation and optimization are powerful tools that have seen increased use in biomechanics research. Dynamic optimizations can be categorized as either data-tracking or predictive problems. The data-tracking approach has been used extensively to address human movement problems of clinical relevance. The predictive approach also holds great promise, but has seen limited use in clinical applications. Enhanced software tools would facilitate the application of predictive musculoskeletal simulations to clinically-relevant research. The open-source software OpenSim provides tools for generating tracking simulations but not predictive simulations. However, OpenSim includes an extensive application programming interface that permits extending its capabilities with scripting languages such as MATLAB. In the work presented here, we combine the computational tools provided by MATLAB with the musculoskeletal modeling capabilities of OpenSim to create a framework for generating predictive simulations of musculoskeletal movement based on direct collocation optimal control techniques. In many cases, the direct collocation approach can be used to solve optimal control problems considerably faster than traditional shooting methods. Cyclical and discrete movement problems were solved using a simple 1 degree of freedom musculoskeletal model and a model of the human lower limb, respectively. The problems could be solved in reasonable amounts of time (several seconds to 1–2 hours) using the open-source IPOPT solver. The problems could also be solved using the fmincon solver that is included with MATLAB, but the computation times were excessively long for all but the smallest of problems. The performance advantage for IPOPT was derived primarily by exploiting sparsity in the constraints Jacobian. The framework presented here provides a powerful and flexible approach for generating optimal control simulations of musculoskeletal movement using OpenSim and MATLAB. This should allow researchers to more readily use predictive simulation as a tool to address clinical conditions that limit human mobility. PMID:26835184

Prediction of Backbreak in Open Pit Blasting by Adaptive Neuro-Fuzzy Inference System / Prognozowanie Spękań Skał Przy Pracach Strzałowych W Kopalniach Odkrywkowych Przy Użyciu Metod Neuronowych I Wnioskowania Rozmytego (Anfis) Zastosowanych W Modelu Adaptywnym

NASA Astrophysics Data System (ADS)

Bazzazi, Abbas Aghajani; Esmaeili, Mohammad

2012-12-01

Adaptive neuro-fuzzy inference system (ANFIS) is powerful model in solving complex problems. Since ANFIS has the potential of solving nonlinear problem and can easily achieve the input-output mapping, it is perfect to be used for solving the predicting problem. Backbreak is one of the undesirable effects of blasting operations causing instability in mine walls, falling down the machinery, improper fragmentation and reduction in efficiency of drilling. In this paper, ANFIS was applied to predict backbreak in Sangan iron mine of Iran. The performance of the model was assessed through the root mean squared error (RMSE), the variance account for (VAF) and the correlation coefficient (R2) computed from the measured of backbreak and model-predicted values of the dependent variables. The RMSE, VAF, R2 indices were calculated 0.6, 0.94 and 0.95 for ANFIS model. As results, these indices revealed that the ANFIS model has very good prediction performance.

Spatial visualization in physics problem solving.

PubMed

Kozhevnikov, Maria; Motes, Michael A; Hegarty, Mary

2007-07-08

Three studies were conducted to examine the relation of spatial visualization to solving kinematics problems that involved either predicting the two-dimensional motion of an object, translating from one frame of reference to another, or interpreting kinematics graphs. In Study 1, 60 physics-naíve students were administered kinematics problems and spatial visualization ability tests. In Study 2, 17 (8 high- and 9 low-spatial ability) additional students completed think-aloud protocols while they solved the kinematics problems. In Study 3, the eye movements of fifteen (9 high- and 6 low-spatial ability) students were recorded while the students solved kinematics problems. In contrast to high-spatial students, most low-spatial students did not combine two motion vectors, were unable to switch frames of reference, and tended to interpret graphs literally. The results of the study suggest an important relationship between spatial visualization ability and solving kinematics problems with multiple spatial parameters. 2007 Cognitive Science Society, Inc.

Effect of Tutorial Giving on The Topic of Special Theory of Relativity in Modern Physics Course Towards Students’ Problem-Solving Ability

NASA Astrophysics Data System (ADS)

Hartatiek; Yudyanto; Haryoto, Dwi

2017-05-01

A Special Theory of Relativity handbook has been successfully arranged to guide students tutorial activity in the Modern Physics course. The low of students’ problem-solving ability was overcome by giving the tutorial in addition to the lecture class. It was done due to the limited time in the class during the course to have students do some exercises for their problem-solving ability. The explicit problem-solving based tutorial handbook was written by emphasizing to this 5 problem-solving strategies: (1) focus on the problem, (2) picture the physical facts, (3) plan the solution, (4) solve the problem, and (5) check the result. This research and development (R&D) consisted of 3 main steps: (1) preliminary study, (2) draft I. product development, and (3) product validation. The developed draft product was validated by experts to measure the feasibility of the material and predict the effect of the tutorial giving by means of questionnaires with scale 1 to 4. The students problem-solving ability in Special Theory of Relativity showed very good qualification. It implied that the tutorial giving with the help of tutorial handbook increased students problem-solving ability. The empirical test revealed that the developed handbook was significantly affected in improving students’ mastery concept and problem-solving ability. Both students’ mastery concept and problem-solving ability were in middle category with gain of 0.31 and 0.41, respectively.

The large area crop inventory experiment: An experiment to demonstrate how space-age technology can contribute to solving critical problems here on earth

NASA Technical Reports Server (NTRS)

1977-01-01

The large area crop inventory experiment is being developed to predict crop production through satellite photographs. This experiment demonstrates how space age technology can contribute to solving practical problems of agriculture management.

The Emotional Dimensions of the Problem-Solving Process.

ERIC Educational Resources Information Center

Hill, Barbara; And Others

1979-01-01

Predictable affective responses are evoked during each phase of a group or organizational problem-solving process. With the needs assessment phase come hope and energy; with goal-setting, confusion and dissatisfaction; with action planning, involvement and accomplishment; with implementation, "stage fright" and joy; with evaluation, pride or…

Behavioral flexibility and problem solving in an invasive bird

PubMed Central

2016-01-01

Behavioral flexibility is considered an important trait for adapting to environmental change, but it is unclear what it is, how it works, and whether it is a problem solving ability. I investigated behavioral flexibility and problem solving experimentally in great-tailed grackles, an invasive bird species and thus a likely candidate for possessing behavioral flexibility. Grackles demonstrated behavioral flexibility in two contexts, the Aesop’s Fable paradigm and a color association test. Contrary to predictions, behavioral flexibility did not correlate across contexts. Four out of 6 grackles exhibited efficient problem solving abilities, but problem solving efficiency did not appear to be directly linked with behavioral flexibility. Problem solving speed also did not significantly correlate with reversal learning scores, indicating that faster learners were not the most flexible. These results reveal how little we know about behavioral flexibility, and provide an immense opportunity for future research to explore how individuals and species can use behavior to react to changing environments. PMID:27168984

[Evolution of methodical approaches to solve problem of evaluating and predicting the thermal status of cosmonauts in the real flight].

PubMed

Kuznets, E I; Bobrov, A F; Bekreneva, L N; Mikhailova, L I; Utekhin, B A; Pruzhinina, T I; Iakovleva, E V; Chadov, V I

1996-01-01

The problem of evaluating and predicting the thermal status of a cosmonaut in the long-term space mission is a pressing one and remains to be solved. The previous studies indicated that the best plan to be followed is to evaluate the thermal status of a cosmonaut during his egress into outer space with the use of the procedure of parotid thermometry of the mean body temperature.

Incremental planning to control a blackboard-based problem solver

NASA Technical Reports Server (NTRS)

Durfee, E. H.; Lesser, V. R.

1987-01-01

To control problem solving activity, a planner must resolve uncertainty about which specific long-term goals (solutions) to pursue and about which sequences of actions will best achieve those goals. A planner is described that abstracts the problem solving state to recognize possible competing and compatible solutions and to roughly predict the importance and expense of developing these solutions. With this information, the planner plans sequences of problem solving activities that most efficiently resolve its uncertainty about which of the possible solutions to work toward. The planner only details actions for the near future because the results of these actions will influence how (and whether) a plan should be pursued. As problem solving proceeds, the planner adds new details to the plan incrementally, and monitors and repairs the plan to insure it achieves its goals whenever possible. Through experiments, researchers illustrate how these new mechanisms significantly improve problem solving decisions and reduce overall computation. They briefly discuss current research directions, including how these mechanisms can improve a problem solver's real-time response and can enhance cooperation in a distributed problem solving network.

Physical activity problem-solving inventory for adolescents: development and initial validation.

PubMed

Thompson, Debbe; Bhatt, Riddhi; Watson, Kathy

2013-08-01

Youth encounter physical activity barriers, often called problems. The purpose of problem solving is to generate solutions to overcome the barriers. Enhancing problem-solving ability may enable youth to be more physically active. Therefore, a method for reliably assessing physical activity problem-solving ability is needed. The purpose of this research was to report the development and initial validation of the physical activity problem-solving inventory for adolescents (PAPSIA). Qualitative and quantitative procedures were used. The social problem-solving inventory for adolescents guided the development of the PAPSIA scale. Youth (14- to 17-year-olds) were recruited using standard procedures, such as distributing flyers in the community and to organizations likely to be attended by adolescents. Cognitive interviews were conducted in person. Adolescents completed pen and paper versions of the questionnaire and/or scales assessing social desirability, self-reported physical activity, and physical activity self-efficacy. An expert panel review, cognitive interviews, and a pilot study (n = 129) established content validity. Construct, concurrent, and predictive validity were also established (n = 520 youth). PAPSIA is a promising measure for assessing youth physical activity problem-solving ability. Future research will assess its validity with objectively measured physical activity.

Cognitive functioning and social problem-solving skills in schizophrenia.

PubMed

Hatashita-Wong, Michi; Smith, Thomas E; Silverstein, Steven M; Hull, James W; Willson, Deborah F

2002-05-01

This study examined the relationships between symptoms, cognitive functioning, and social skill deficits in schizophrenia. Few studies have incorporated measures of cognitive functioning and symptoms in predictive models for social problem solving. For our study, 44 participants were recruited from consecutive outpatient admissions. Neuropsychological tests were given to assess cognitive function, and social problem solving was assessed using structured vignettes designed to evoke the participant's ability to generate, evaluate, and apply solutions to social problems. A sequential model-fitting method of analysis was used to incorporate social problem solving, symptom presentation, and cognitive impairment into linear regression models. Predictor variables were drawn from demographic, cognitive, and symptom domains. Because this method of analysis was exploratory and not intended as hierarchical modelling, no a priori hypotheses were proposed. Participants with higher scores on tests of cognitive flexibility were better able to generate accurate, appropriate, and relevant responses to the social problem-solving vignettes. The results suggest that cognitive flexibility is a potentially important mediating factor in social problem-solving competence. While other factors are related to social problem-solving skill, this study supports the importance of cognition and understanding how it relates to the complex and multifaceted nature of social functioning.

Interaction Network Estimation: Predicting Problem-Solving Diversity in Interactive Environments

ERIC Educational Resources Information Center

Eagle, Michael; Hicks, Drew; Barnes, Tiffany

2015-01-01

Intelligent tutoring systems and computer aided learning environments aimed at developing problem solving produce large amounts of transactional data which make it a challenge for both researchers and educators to understand how students work within the environment. Researchers have modeled student-tutor interactions using complex networks in…

Coping among Nonclinical College-Age Children of Alcoholics.

ERIC Educational Resources Information Center

Wright, Deborah M.; Heppner, P. Paul

1991-01-01

Compared 40 adult children of alcoholics (ACAs) to 40 non-ACAs on problem-solving appraisal, perceived social support, shame, suicidal ideation, and substance use; examined gender differences among ACAs; explored relations between problem-solving appraisal, perceived social support, and shame in predicting suicidal ideation and substance use. ACAs…

Sciencewise: Discovering Scientific Process through Problem Solving. Book 2.

ERIC Educational Resources Information Center

Holley, Dennis

This book of activities uses problem solving to help students develop the basic science process skills of observing, predicting, designing/experimenting, eliminating, and drawing conclusions. The activities are divided into two sections: Dynamo Demos and Creative Challenges. The teacher-led Dynamo Demos help students to develop science process…

Sciencewise: Discovering Scientific Process through Problem Solving. Book 1.

ERIC Educational Resources Information Center

Holley, Dennis

This book of activities uses problem solving to help students develop the basic science process skills of observing, predicting, designing/experimenting, eliminating, and drawing conclusions. The activities are divided into two sections: Dynamo Demos and Creative Challenges. The teacher-led Dynamo Demos help students to develop science process…

Exploring the relationship between work-related rumination, sleep quality, and work-related fatigue.

PubMed

Querstret, Dawn; Cropley, Mark

2012-07-01

This study examined the association among three conceptualizations of work-related rumination (affective rumination, problem-solving pondering, and detachment) with sleep quality and work-related fatigue. It was hypothesized that affective rumination and poor sleep quality would be associated with increased fatigue and that problem-solving pondering and detachment would be associated with decreased fatigue. The mediating effect of sleep quality on the relationship between work-related rumination and fatigue was also tested. An online questionnaire was completed by a heterogeneous sample of 719 adult workers in diverse occupations. The following variables were entered as predictors in a regression model: affective rumination, problem-solving pondering, detachment, and sleep quality. The dependent variables were chronic work-related fatigue (CF) and acute work-related fatigue (AF). Affective rumination was the strongest predictor of increased CF and AF. Problem-solving pondering was a significant predictor of decreased CF and AF. Poor sleep quality was predictive of increased CF and AF. Detachment was significantly negatively predictive for AF. Sleep quality partially mediated the relationship between affective rumination and fatigue and between problem-solving pondering and fatigue. Work-related affective rumination appears more detrimental to an individual's ability to recover from work than problem-solving pondering. In the context of identifying mechanisms by which demands at work are translated into ill-health, this appears to be a key finding and suggests that it is the type of work-related rumination, not rumination per se, that is important.

Intuitive Feelings of Warmth and Confidence in Insight and Noninsight Problem Solving of Magic Tricks.

PubMed

Hedne, Mikael R; Norman, Elisabeth; Metcalfe, Janet

2016-01-01

The focus of the current study is on intuitive feelings of insight during problem solving and the extent to which such feelings are predictive of successful problem solving. We report the results from an experiment (N = 51) that applied a procedure where the to-be-solved problems were 32 short (15 s) video recordings of magic tricks. The procedure included metacognitive ratings similar to the "warmth ratings" previously used by Metcalfe and colleagues, as well as confidence ratings. At regular intervals during problem solving, participants indicated the perceived closeness to the correct solution. Participants also indicated directly whether each problem was solved by insight or not. Problems that people claimed were solved by insight were characterized by higher accuracy and higher confidence than noninsight solutions. There was no difference between the two types of solution in warmth ratings, however. Confidence ratings were more strongly associated with solution accuracy for noninsight than insight trials. Moreover, for insight trials the participants were more likely to repeat their incorrect solutions on a subsequent recognition test. The results have implications for understanding people's metacognitive awareness of the cognitive processes involved in problem solving. They also have general implications for our understanding of how intuition and insight are related.

Intuitive Feelings of Warmth and Confidence in Insight and Noninsight Problem Solving of Magic Tricks

PubMed Central

Hedne, Mikael R.; Norman, Elisabeth; Metcalfe, Janet

2016-01-01

The focus of the current study is on intuitive feelings of insight during problem solving and the extent to which such feelings are predictive of successful problem solving. We report the results from an experiment (N = 51) that applied a procedure where the to-be-solved problems were 32 short (15 s) video recordings of magic tricks. The procedure included metacognitive ratings similar to the “warmth ratings” previously used by Metcalfe and colleagues, as well as confidence ratings. At regular intervals during problem solving, participants indicated the perceived closeness to the correct solution. Participants also indicated directly whether each problem was solved by insight or not. Problems that people claimed were solved by insight were characterized by higher accuracy and higher confidence than noninsight solutions. There was no difference between the two types of solution in warmth ratings, however. Confidence ratings were more strongly associated with solution accuracy for noninsight than insight trials. Moreover, for insight trials the participants were more likely to repeat their incorrect solutions on a subsequent recognition test. The results have implications for understanding people's metacognitive awareness of the cognitive processes involved in problem solving. They also have general implications for our understanding of how intuition and insight are related. PMID:27630598

Can I cut the Gordian tnok? The impact of pronounceability, actual solvability, and length on intuitive problem assessments of anagrams.

PubMed

Topolinski, Sascha; Bakhtiari, Giti; Erle, Thorsten M

2016-01-01

When assessing a problem, many cues can be used to predict solvability and solving effort. Some of these cues, however, can be misleading. The present approach shows that a feature of a problem that is actually related to solving difficulty is used as a cue for solving ease when assessing the problem in the first place. For anagrams, it is an established effect that easy-to-pronounce anagrams (e.g., NOGAL) take more time to being solved than hard-to-pronounce anagrams (e.g., HNWEI). However, when assessing an anagram in the first place, individuals use the feature of pronounceability to predict solving ease, because pronounceability is an instantiation of the general mechanism of processing fluency. Participants (total N=536) received short and long anagrams and nonanagrams and judged solvability and solving ease intuitively without actually solving the items. Easy-to-pronounce letter strings were more frequently judged as being solvable than hard-to-pronounce letters strings (Experiment 1), and were estimated to require less effort (Experiments 2, 4-7) and time to be solved (Experiment 3). This effect was robust for short and long items, anagrams and nonanagrams, and presentation timings from 4 down to 0.5s, and affected novices and experts alike. Spontaneous solutions did not mediate this effect. Participants were sensitive to actual solvability even for long anagrams (6-11 letters long) presented only for 500 ms. Copyright © 2015 Elsevier B.V. All rights reserved.

Development of Mastery during Adolescence: The Role of Family Problem Solving*

PubMed Central

Conger, Katherine Jewsbury; Williams, Shannon Tierney; Little, Wendy M.; Masyn, Katherine E.; Shebloski, Barbara

2009-01-01

A sense of mastery is an important component of psychological health and well-being across the life-span; however, relatively little is known about the development of mastery during childhood and adolescence. Utilizing prospective, longitudinal data from 444 adolescent sibling pairs and their parents, our conceptual model proposes that family SES in the form of parental education promotes effective family problem solving which, in turn, fosters adolescent mastery. Results show: (1) a significant increase in mastery for younger and older siblings, (2) parental education promoted effective problem solving between parents and adolescents and between siblings but not between the parents themselves, and (3) all forms of effective family problem solving predicted greater adolescent mastery. Parental education had a direct effect on adolescent mastery as well as the hypothesized indirect effect through problem solving effectiveness, suggesting both a social structural and social process influence on the development of mastery during adolescence. PMID:19413137

Development of mastery during adolescence: the role of family problem-solving.

PubMed

Conger, Katherine Jewsbury; Williams, Shannon Tierney; Little, Wendy M; Masyn, Katherine E; Shebloski, Barbara

2009-03-01

A sense of mastery is an important component of psychological health and wellbeing across the life-span; however relatively little is known about the development of mastery during childhood and adolescence. Utilizing prospective, longitudinal data from 444 adolescent sibling pairs and their parents, our conceptual model proposes that family socioeconomic status (SES) in the form of parental education promotes effective family problem-solving, which, in turn, fosters adolescent mastery. Results show: (1) a significant increase in mastery for younger and older siblings, (2) parental education promoted effective problem-solving between parents and adolescents and between siblings but not between the parents themselves, and (3) all forms of effective family problem-solving predicted greater adolescent mastery. Parental education had a direct effect on adolescent mastery as well as the hypothesized indirect effect through problem-solving effectiveness, suggesting both a social structural and social process influence on the development of mastery during adolescence.

Predicting Development of Mathematical Word Problem Solving Across the Intermediate Grades

PubMed Central

Tolar, Tammy D.; Fuchs, Lynn; Cirino, Paul T.; Fuchs, Douglas; Hamlett, Carol L.; Fletcher, Jack M.

2012-01-01

This study addressed predictors of the development of word problem solving (WPS) across the intermediate grades. At beginning of 3rd grade, 4 cohorts of students (N = 261) were measured on computation, language, nonverbal reasoning skills, and attentive behavior and were assessed 4 times from beginning of 3rd through end of 5th grade on 2 measures of WPS at low and high levels of complexity. Language skills were related to initial performance at both levels of complexity and did not predict growth at either level. Computational skills had an effect on initial performance in low- but not high-complexity problems and did not predict growth at either level of complexity. Attentive behavior did not predict initial performance but did predict growth in low-complexity, whereas it predicted initial performance but not growth for high-complexity problems. Nonverbal reasoning predicted initial performance and growth for low-complexity WPS, but only growth for high-complexity WPS. This evidence suggests that although mathematical structure is fixed, different cognitive resources may act as limiting factors in WPS development when the WPS context is varied. PMID:23325985

A Monte-Carlo game theoretic approach for Multi-Criteria Decision Making under uncertainty

NASA Astrophysics Data System (ADS)

Madani, Kaveh; Lund, Jay R.

2011-05-01

Game theory provides a useful framework for studying Multi-Criteria Decision Making problems. This paper suggests modeling Multi-Criteria Decision Making problems as strategic games and solving them using non-cooperative game theory concepts. The suggested method can be used to prescribe non-dominated solutions and also can be used as a method to predict the outcome of a decision making problem. Non-cooperative stability definitions for solving the games allow consideration of non-cooperative behaviors, often neglected by other methods which assume perfect cooperation among decision makers. To deal with the uncertainty in input variables a Monte-Carlo Game Theory (MCGT) approach is suggested which maps the stochastic problem into many deterministic strategic games. The games are solved using non-cooperative stability definitions and the results include possible effects of uncertainty in input variables on outcomes. The method can handle multi-criteria multi-decision-maker problems with uncertainty. The suggested method does not require criteria weighting, developing a compound decision objective, and accurate quantitative (cardinal) information as it simplifies the decision analysis by solving problems based on qualitative (ordinal) information, reducing the computational burden substantially. The MCGT method is applied to analyze California's Sacramento-San Joaquin Delta problem. The suggested method provides insights, identifies non-dominated alternatives, and predicts likely decision outcomes.

Dysfunctional attitudes and poor problem solving skills predict hopelessness in major depression.

PubMed

Cannon, B; Mulroy, R; Otto, M W; Rosenbaum, J F; Fava, M; Nierenberg, A A

1999-09-01

Hopelessness is a significant predictor of suicidality, but not all depressed patients feel hopeless. If clinicians can predict hopelessness, they may be able to identify those patients at risk of suicide and focus interventions on factors associated with hopelessness. In this study, we examined potential predictors of hopelessness in a sample of depressed outpatients. In this study, we examined potential demographic, diagnostic, and symptom predictors of hopelessness in a sample of 138 medication-free outpatients (73 women and 65 men) with a primary diagnosis of major depression. The significance of predictors was evaluated in both simple and multiple regression analyses. Consistent with previous studies, we found no significant associations between demographic and diagnostic variables and greater hopelessness. Hopelessness was significantly associated with greater depression severity, poor problem solving abilities as assessed by the Problem Solving Inventory, and each of two measures of dysfunctional cognitions (the Dysfunctional Attitudes Scale and the Cognitions Questionnaire). In a stepwise multiple regression equation, however, only dysfunctional cognitions and poor problem solving offered non-redundant prediction of hopelessness scores, and accounted for 20% of the variance in these scores. This study is based on depressed patients entering into an outpatient treatment protocol. All analyses were correlational in nature, and no causal links can be concluded. Our findings, identifying clinical correlates of hopelessness, provide clinicians with potential additional targets for assessment and treatment of suicidal risk. In particular, clinical attention to dysfunctional attitudes and problem solving skills may be important for further reduction of hopelessness and perhaps suicidal risk.

Dispositional Predictors of Problem Solving in the Field of Office Work

ERIC Educational Resources Information Center

Rausch, Andreas

2017-01-01

It was investigated how domain-specific knowledge, fluid intelligence, vocational interest and work-related self-efficacy predicted domain-specific problem-solving performance in the field of office work. The participants included 100 German VET (vocational education and training) students nearing the end of a 3-year apprenticeship program as an…

Influence of Family Processes, Motivation, and Beliefs about Intelligence on Creative Problem Solving of Scientifically Talented Individuals

ERIC Educational Resources Information Center

Cho, Seokhee; Lin, Chia-Yi

2011-01-01

Predictive relationships among perceived family processes, intrinsic and extrinsic motivation, incremental beliefs about intelligence, confidence in intelligence, and creative problem-solving practices in mathematics and science were examined. Participants were 733 scientifically talented Korean students in fourth through twelfth grades as well as…

Determining the Exchangeability of Concept Map and Problem-Solving Essay Scores

ERIC Educational Resources Information Center

Hollenbeck, Keith; Twyman, Todd; Tindal, Gerald

2006-01-01

This study investigated the score exchangeability of concept maps with problem-solving essays. Of interest was whether sixth-grade students' concept maps predicted their scores on essay responses that used concept map content. Concept maps were hypothesized to be alternatives to performance assessments for content-area domain knowledge in science.…

Schizotypy and Performance on an Insight Problem-Solving Task: The Contribution of Persecutory Ideation.

PubMed

Cosgrave, Jan; Haines, Ross; Golodetz, Stuart; Claridge, Gordon; Wulff, Katharina; van Heugten-van der Kloet, Dalena

2018-01-01

Insight problem solving is thought to underpin creative thought as it incorporates both divergent (generating multiple ideas and solutions) and convergent (arriving at the optimal solution) thinking approaches. The current literature on schizotypy and creativity is mixed and requires clarification. An alternate approach was employed by designing an exploratory web-based study using only correlates of schizotypal traits (paranoia, dissociation, cognitive failures, fantasy proneness, and unusual sleep experiences) and examining which (if any) predicted optimal performance on an insight problem-solving task. One hundred and twenty-one participants were recruited online from the general population and completed the number reduction task. The discovery of the hidden rule (HR) was used as a measure of insight. Multivariate logistic regression analyses highlighted persecutory ideation to best predict the discovery of the HR (OR = 1.05; 95% CI 1.01-1.10, p = 0.017), with a one-point increase in persecutory ideas corresponding to the participant being 5% more likely to discover the HR. This result suggests that persecutory ideation, above other schizotypy correlates, may be involved in insight problem solving.

Individual differences in children's innovative problem-solving are not predicted by divergent thinking or executive functions

PubMed Central

2016-01-01

Recent studies of children's tool innovation have revealed that there is variation in children's success in middle-childhood. In two individual differences studies, we sought to identify personal characteristics that might predict success on an innovation task. In Study 1, we found that although measures of divergent thinking were related to each other they did not predict innovation success. In Study 2, we measured executive functioning including: inhibition, working memory, attentional flexibility and ill-structured problem-solving. None of these measures predicted innovation, but, innovation was predicted by children's performance on a receptive vocabulary scale that may function as a proxy for general intelligence. We did not find evidence that children's innovation was predicted by specific personal characteristics. PMID:26926280

The impact of perceived self-efficacy on mental time travel and social problem solving.

PubMed

Brown, Adam D; Dorfman, Michelle L; Marmar, Charles R; Bryant, Richard A

2012-03-01

Current models of autobiographical memory suggest that self-identity guides autobiographical memory retrieval. Further, the capacity to recall the past and imagine one's self in the future (mental time travel) can influence social problem solving. We examined whether manipulating self-identity, through an induction task in which students were led to believe they possessed high or low self-efficacy, impacted episodic specificity and content of retrieved and imagined events, as well as social problem solving. Compared to individuals in the low self efficacy group, individuals in the high self efficacy group generated past and future events with greater (a) specificity, (b) positive words, and (c) self-efficacious statements, and also performed better on social problem solving indices. A lack of episodic detail for future events predicted poorer performance on social problem solving tasks. Strategies that increase perceived self-efficacy may help individuals to selectively construct a past and future that aids in negotiating social problems. Copyright © 2011 Elsevier Inc. All rights reserved.

Problem-solving and mental health outcomes of women and children in the wake of intimate partner violence.

PubMed

Maddoux, John; Symes, Lene; McFarlane, Judith; Koci, Anne; Gilroy, Heidi; Fredland, Nina

2014-01-01

The environmental stress of intimate partner violence is common and often results in mental health problems of depression, anxiety, and PTSD for women and behavioral dysfunctions for their children. Problem-solving skills can serve to mitigate or accentuate the environmental stress of violence and associated impact on mental health. To better understand the relationship between problem-solving skills and mental health of abused women with children, a cross-sectional predictive analysis of 285 abused women who used justice or shelter services was completed. The women were asked about social problem-solving, and mental health symptoms of depression, anxiety, and PTSD as well as behavioral functioning of their children. Higher negative problem-solving scores were associated with significantly (P < 0.001) greater odds of having clinically significant levels of PTSD, anxiety, depression, and somatization for the woman and significantly (P < 0.001) greater odds of her child having borderline or clinically significant levels of both internalizing and externalizing behaviors. A predominately negative problem-solving approach was strongly associated with poorer outcomes for both mothers and children in the aftermath of the environmental stress of abuse. Interventions addressing problem-solving ability may be beneficial in increasing abused women's abilities to navigate the daily stressors of life following abuse.

School Violence: To What Extent Do Perceptions of Problem Solving Skills Protect Adolescents?

ERIC Educational Resources Information Center

Turkum, Ayse Sibel

2011-01-01

This study examined whether adolescents' perceptions of problem solving skills differ according to their sex, experiences of exposure to violence, age and grade, and the variables predicting their experiences of exposure to violence. Data were collected from 600(298 females, 302 males) 14-19 year-old students attending various types of high…

Junior High School Physics: Using a Qualitative Strategy for Successful Problem Solving

ERIC Educational Resources Information Center

Mualem, Roni; Eylon, Bat Sheva

2010-01-01

Students at the junior high school (JHS) level often cannot use their knowledge of physics for explaining and predicting phenomena. We claim that this difficulty stems from the fact that explanations are multi-step reasoning tasks, and students often lack the qualitative problem-solving strategies needed to guide them. This article describes a new…

Social Problem Solving in High-Risk Mother-Child Dyads: An Intergenerational Study

ERIC Educational Resources Information Center

Martin, Julie P.; Stack, Dale M.; Serbin, Lisa A.; Schwartzman, Alex E.; Ledingham, Jane

2012-01-01

This study examined the contribution of maternal childhood histories of aggression and social withdrawal to the prediction of mother-child social problem solving in the next generation. Fifty-seven women (M = 37.32 years), previously rated (on a version of the pupil evaluation inventory) by their peers during childhood on measures of aggression…

A Life History Approach to Delineating How Harsh Environments and Hawk Temperament Traits Differentially Shape Children's Problem-Solving Skills

ERIC Educational Resources Information Center

Suor, Jennifer H.; Sturge-Apple, Melissa L.; Davies, Patrick T.; Cicchetti, Dante

2017-01-01

Harsh environments are known to predict deficits in children's cognitive abilities. Life history theory approaches challenge this interpretation, proposing stressed children's cognition becomes specialized to solve problems in fitness-enhancing ways. The goal of this study was to examine associations between early environmental harshness and…

Motion-based prediction is sufficient to solve the aperture problem

PubMed Central

Perrinet, Laurent U; Masson, Guillaume S

2012-01-01

In low-level sensory systems, it is still unclear how the noisy information collected locally by neurons may give rise to a coherent global percept. This is well demonstrated for the detection of motion in the aperture problem: as luminance of an elongated line is symmetrical along its axis, tangential velocity is ambiguous when measured locally. Here, we develop the hypothesis that motion-based predictive coding is sufficient to infer global motion. Our implementation is based on a context-dependent diffusion of a probabilistic representation of motion. We observe in simulations a progressive solution to the aperture problem similar to physiology and behavior. We demonstrate that this solution is the result of two underlying mechanisms. First, we demonstrate the formation of a tracking behavior favoring temporally coherent features independently of their texture. Second, we observe that incoherent features are explained away while coherent information diffuses progressively to the global scale. Most previous models included ad-hoc mechanisms such as end-stopped cells or a selection layer to track specific luminance-based features as necessary conditions to solve the aperture problem. Here, we have proved that motion-based predictive coding, as it is implemented in this functional model, is sufficient to solve the aperture problem. This solution may give insights in the role of prediction underlying a large class of sensory computations. PMID:22734489

Hamster Math: Authentic Experiences in Data Collection.

ERIC Educational Resources Information Center

Jorgensen, Beth

1996-01-01

Describes the data collection and interpretation project of primary grade students involving predicting, graphing, estimating, measuring, number problem construction, problem solving, and probability. (MKR)

Associations between conceptual reasoning, problem solving, and adaptive ability in high-functioning autism.

PubMed

Williams, Diane L; Mazefsky, Carla A; Walker, Jon D; Minshew, Nancy J; Goldstein, Gerald

2014-11-01

Abstract thinking is generally highly correlated with problem-solving ability which is predictive of better adaptive functioning. Measures of conceptual reasoning, an ecologically-valid laboratory measure of problem-solving, and a report measure of adaptive functioning in the natural environment, were administered to children and adults with and without autism. The individuals with autism had weaker conceptual reasoning ability than individuals with typical development of similar age and cognitive ability. For the autism group, their flexible thinking scores were significantly correlated with laboratory measures of strategy formation and rule shifting and with reported overall adaptive behavior but not socialization scores. Therefore, in autism, flexibility of thought is potentially more important for adaptive functioning in the natural environment than conceptual reasoning or problem-solving.

Numerical study of signal propagation in corrugated coaxial cables

DOE PAGES

Li, Jichun; Machorro, Eric A.; Shields, Sidney

2017-01-01

Our article focuses on high-fidelity modeling of signal propagation in corrugated coaxial cables. Taking advantage of the axisymmetry, the authors reduce the 3-D problem to a 2-D problem by solving time-dependent Maxwell's equations in cylindrical coordinates.They then develop a nodal discontinuous Galerkin method for solving their model equations. We prove stability and error analysis for the semi-discrete scheme. We we present our numerical results, we demonstrate that our algorithm not only converges as our theoretical analysis predicts, but it is also very effective in solving a variety of signal propagation problems in practical corrugated coaxial cables.

Better without (lateral) frontal cortex? Insight problems solved by frontal patients.

PubMed

Reverberi, Carlo; Toraldo, Alessio; D'Agostini, Serena; Skrap, Miran

2005-12-01

A recently proposed theory on frontal lobe functions claims that the prefrontal cortex, particularly its dorso-lateral aspect, is crucial in defining a set of responses suitable for a particular task, and biasing these for selection. This activity is carried out for virtually any kind of non-routine tasks, without distinction of content. The aim of this study is to test the prediction of Frith's 'sculpting the response space' hypothesis by means of an 'insight' problem-solving task, namely the matchstick arithmetic task. Starting from Knoblich et al.'s interpretation for the failure of healthy controls to solve the matchstick problem, and Frith's theory on the role of dorsolateral frontal cortex, we derived the counterintuitive prediction that patients with focal damage to the lateral frontal cortex should perform better than a group of healthy participants on this rather difficult task. We administered the matchstick task to 35 patients (aged 26-65 years) with a single focal brain lesion as determined by a CT or an MRI scan, and to 23 healthy participants (aged 34-62 years). The findings seemed in line with theoretical predictions. While only 43% of healthy participants could solve the most difficult matchstick problems ('type C'), 82% of lateral frontal patients did so (Fisher's exact test, P < 0.05). In conclusion, the combination of Frith's and Knoblich et al.'s theories was corroborated.

The Power of a "Maverick" in Collaborative Problem Solving: An Experimental Investigation of Individual Perspective-Taking Within a Group.

PubMed

Hayashi, Yugo

2018-05-01

Integrating different perspectives is a sophisticated strategy for developing constructive interactions in collaborative problem solving. However, cognitive aspects such as individuals' knowledge and bias often obscure group consensus and produce conflict. This study investigated collaborative problem solving, focusing on a group member interacting with another member having a different perspective (a "maverick"). It was predicted that mavericks might mitigate disadvantages and facilitate perspective taking during problem solving. Thus, 344 university students participated in two laboratory-based experiments by engaging in a simple rule-discovery task that raised conflicts among perspectives. They interacted with virtual partners whose conversations were controlled by multiple conversational agents. Results show that when participants interacted with a maverick during the task, they were able to take others' perspectives and integrate different perspectives to solve the problem. Moreover, when participants interacted in groups with a positive mood, groups with a maverick outperformed groups having several perspectives. Copyright © 2018 Cognitive Science Society, Inc.

Family-Peer Linkages for Children with Intellectual Disability and Children with Learning Disabilities.

PubMed

Floyd, Frank J; Olsen, Darren L

2017-09-01

Family interactions are potential contexts for children with intellectual and learning disabilities to develop skillful social behaviors needed to relate effectively with peers. This study examined problem solving interactions within families of elementary school-age children (7-11 years) with intellectual disability (n = 37), specific learning disabilities (n =48), and without disabilities (n = 22). After accounting for group differences in children's behaviors and peer acceptance, across all groups, mothers' behaviors that encouraged egalitarian problem solving predicted more engaged and skillful problem solving by the children. However, mothers' controlling, directive behaviors predicted fewer of these behaviors by the children. Fathers' behaviors had mixed associations with the children's actions, possibly because they were reactive to children's unengaged and negative behaviors. For the children, greater involvement, more facilitative behaviors, and less negativity with their families were associated with greater acceptance from their peers, supporting family-peer linkages for children at risk for peer rejection.

The relationship between everyday problem solving and inconsistency in reaction time in older adults.

PubMed

Burton, Catherine L; Strauss, Esther; Hultsch, David F; Hunter, Michael A

2009-09-01

The purpose of the present study was to investigate whether inconsistency in reaction time (RT) is predictive of older adults' ability to solve everyday problems. A sample of 304 community dwelling non-demented older adults, ranging in age from 62 to 92, completed a measure of everyday problem solving, the Everyday Problems Test (EPT). Inconsistency in latencies across trials was assessed on four RT tasks. Performance on the EPT was found to vary according to age and cognitive status. Both mean latencies and inconsistency were significantly associated with EPT performance, such that slower and more inconsistent RTs were associated with poorer everyday problem solving abilities. Even after accounting for age, education, and mean level of performance, inconsistency in reaction time continued to account for a significant proportion of the variance in EPT scores. These findings suggest that indicators of inconsistency in RT may be of functional relevance.

Improving insight and non-insight problem solving with brief interventions.

PubMed

Wen, Ming-Ching; Butler, Laurie T; Koutstaal, Wilma

2013-02-01

Developing brief training interventions that benefit different forms of problem solving is challenging. In earlier research, Chrysikou (2006) showed that engaging in a task requiring generation of alternative uses of common objects improved subsequent insight problem solving. These benefits were attributed to a form of implicit transfer of processing involving enhanced construction of impromptu, on-the-spot or 'ad hoc' goal-directed categorizations of the problem elements. Following this, it is predicted that the alternative uses exercise should benefit abilities that govern goal-directed behaviour, such as fluid intelligence and executive functions. Similarly, an indirect intervention - self-affirmation (SA) - that has been shown to enhance cognitive and executive performance after self-regulation challenge and when under stereotype threat, may also increase adaptive goal-directed thinking and likewise should bolster problem-solving performance. In Experiment 1, brief single-session interventions, involving either alternative uses generation or SA, significantly enhanced both subsequent insight and visual-spatial fluid reasoning problem solving. In Experiment 2, we replicated the finding of benefits of both alternative uses generation and SA on subsequent insight problem-solving performance, and demonstrated that the underlying mechanism likely involves improved executive functioning. Even brief cognitive- and social-psychological interventions may substantially bolster different types of problem solving and may exert largely similar facilitatory effects on goal-directed behaviours. © 2012 The British Psychological Society.

More than Just Fun and Games: The Longitudinal Relationships between Strategic Video Games, Self-Reported Problem Solving Skills, and Academic Grades

ERIC Educational Resources Information Center

Adachi, Paul J. C.; Willoughby, Teena

2013-01-01

Some researchers have proposed that video games possess good learning principles and may promote problem solving skills. Empirical research regarding this relationship, however, is limited. The goal of the presented study was to examine whether strategic video game play (i.e., role playing and strategy games) predicted self-reported problem…

Linking Complex Problem Solving and General Mental Ability to Career Advancement: Does a Transversal Skill Reveal Incremental Predictive Validity?

ERIC Educational Resources Information Center

Mainert, Jakob; Kretzschmar, André; Neubert, Jonas C.; Greiff, Samuel

2015-01-01

Transversal skills, such as complex problem solving (CPS) are viewed as central twenty-first-century skills. Recent empirical findings have already supported the importance of CPS for early academic advancement. We wanted to determine whether CPS could also contribute to the understanding of career advancement later in life. Towards this end, we…

Within Your Control? When Problem Solving May Be Most Helpful.

PubMed

Sarfan, Laurel D; Gooch, Peter; Clerkin, Elise M

2017-08-01

Emotion regulation strategies have been conceptualized as adaptive or maladaptive, but recent evidence suggests emotion regulation outcomes may be context-dependent. The present study tested whether the adaptiveness of a putatively adaptive emotion regulation strategy-problem solving-varied across contexts of high and low controllability. The present study also tested rumination, suggested to be one of the most putatively maladaptive strategies, which was expected to be associated with negative outcomes regardless of context. Participants completed an in vivo speech task, in which they were randomly assigned to a controllable ( n = 65) or an uncontrollable ( n = 63) condition. Using moderation analyses, we tested whether controllability interacted with emotion regulation use to predict negative affect, avoidance, and perception of performance. Partially consistent with hypotheses, problem solving was associated with certain positive outcomes (i.e., reduced behavioral avoidance) in the controllable (vs. uncontrollable) condition. Consistent with predictions, rumination was associated with negative outcomes (i.e., desired avoidance, negative affect, negative perception of performance) in both conditions. Overall, findings partially support contextual models of emotion regulation, insofar as the data suggest that the effects of problem solving may be more adaptive in controllable contexts for certain outcomes, whereas rumination may be maladaptive regardless of context.

The Main and Interactive Effects of Maternal Interpersonal Emotion Regulation and Negative Affect on Adolescent Girls' Borderline Personality Disorder Symptoms.

PubMed

Dixon-Gordon, Katherine L; Whalen, Diana J; Scott, Lori N; Cummins, Nicole D; Stepp, Stephanie D

2016-06-01

The transaction of adolescent's expressed negative affect and parental interpersonal emotion regulation are theoretically implicated in the development of borderline personality disorder (BPD). Although problem solving and support/validation are interpersonal strategies that foster emotion regulation, little is known about whether these strategies are associated with less BPD severity among adolescents. Adolescent girls (age 16; N = 74) and their mothers completed a conflict discussion task, and maternal problem solving, support/validation, and girls' negative affect were coded. Girls' BPD symptoms were assessed at four time points. A 3-way interaction of girls' negative affect, problem solving, and support/validation indicated that girls' negative affect was only associated with BPD severity in the context of low maternal support/validation and high maternal problem solving. These variables did not predict changes in BPD symptoms over time. Although high negative affect is a risk for BPD severity in adolescent girls, maternal interpersonal emotion regulation strategies moderate this link. Whereas maternal problem solving coupled with low support/validation is associated with a stronger negative affect-BPD relation, maternal problem solving paired with high support/validation is associated with an attenuated relationship.

The Main and Interactive Effects of Maternal Interpersonal Emotion Regulation and Negative Affect on Adolescent Girls’ Borderline Personality Disorder Symptoms

PubMed Central

Whalen, Diana J.; Scott, Lori N.; Cummins, Nicole D.; Stepp, Stephanie D.

2015-01-01

The transaction of adolescent’s expressed negative affect and parental interpersonal emotion regulation are theoretically implicated in the development of borderline personality disorder (BPD). Although problem solving and support/validation are interpersonal strategies that foster emotion regulation, little is known about whether these strategies are associated with less BPD severity among adolescents. Adolescent girls (age 16; N = 74) and their mothers completed a conflict discussion task, and maternal problem solving, support/validation, and girls’ negative affect were coded. Girls’ BPD symptoms were assessed at four time points. A 3-way interaction of girls’ negative affect, problem solving, and support/validation indicated that girls’ negative affect was only associated with BPD severity in the context of low maternal support/validation and high maternal problem solving. These variables did not predict changes in BPD symptoms over time. Although high negative affect is a risk for BPD severity in adolescent girls, maternal interpersonal emotion regulation strategies moderate this link. Whereas maternal problem solving coupled with low support/validation is associated with a stronger negative affect-BPD relation, maternal problem solving paired with high support/validation is associated with an attenuated relationship. PMID:27185969

Life stress, social support, and problem-solving skills predictive of depressive symptoms, hopelessness, and suicide ideation in an Asian student population: a test of a model.

PubMed

Yang, B; Clum, G A

1994-01-01

The present study tested both a stress-problem-solving model and a stress-social support model in the etiology of depressive symptoms, hopelessness, and suicide ideation for a group of Asian international students in the United States. Problem-solving skills and social support were hypothesized as two mediators between life stress and depressive symptoms, hopelessness, and suicide ideation. The results from a series of stepwise regression analyses and a path analysis support the hypotheses, indicating that these models generalized to a sample of Asian international students. The roles of social support and problem-solving skills in depressive symptoms and hopelessness are discussed. The results also suggest that hopelessness may serve as a cognitive factor directly affecting depressive symptoms and indirectly affecting suicide ideation.

Evaluation of POE and instructor-led problem-solving approaches integrated into force and motion lecture classes using a model analysis technique

NASA Astrophysics Data System (ADS)

Rakkapao, S.; Pengpan, T.; Srikeaw, S.; Prasitpong, S.

2014-01-01

This study aims to investigate the use of the predict-observe-explain (POE) approach integrated into large lecture classes on forces and motion. It is compared to the instructor-led problem-solving method using model analysis. The samples are science (SC, N = 420) and engineering (EN, N = 434) freshmen, from Prince of Songkla University, Thailand. Research findings from the force and motion conceptual evaluation indicate that the multimedia-supported POE method promotes students’ learning better than the problem-solving method, in particular for the velocity and acceleration concepts. There is a small shift of the students’ model states after the problem-solving instruction. Moreover, by using model analysis instructors are able to investigate students’ misconceptions and evaluate teaching methods. It benefits instructors in organizing subsequent instructional materials.

Do social support, stigma, and social problem-solving skills predict depressive symptoms in people living with HIV? A mediation analysis.

PubMed

White, Worawan; Grant, Joan S; Pryor, Erica R; Keltner, Norman L; Vance, David E; Raper, James L

2012-01-01

Social support, stigma, and social problem solving may be mediators of the relationship between sign and symptom severity and depressive symptoms in people living with HIV (PLWH). However, no published studies have examined these individual variables as mediators in PLWH. This cross-sectional, correlational study of 150 PLWH examined whether social support, stigma, and social problem solving were mediators of the relationship between HIV-related sign and symptom severity and depressive symptoms. Participants completed self-report questionnaires during their visits at two HIV outpatient clinics in the Southeastern United States. Using multiple regression analyses as a part of mediation testing, social support, stigma, and social problem solving were found to be partial mediators of the relationship between sign and symptom severity and depressive symptoms, considered individually and as a set.

An investigation of meaningful understanding and effectiveness of the implementation of Piagetian and Ausubelian theories in physics instruction

NASA Astrophysics Data System (ADS)

Williams, Karen Ann

One section of college students (N = 25) enrolled in an algebra-based physics course was selected for a Piagetian-based learning cycle (LC) treatment while a second section (N = 25) studied in an Ausubelian-based meaningful verbal reception learning treatment (MVRL). This study examined the students' overall (concept + problem solving + mental model) meaningful understanding of force, density/Archimedes Principle, and heat. Also examined were students' meaningful understanding as measured by conceptual questions, problems, and mental models. In addition, students' learning orientations were examined. There were no significant posttest differences between the LC and MVRL groups for students' meaningful understanding or learning orientation. Piagetian and Ausubelian theories explain meaningful understanding for each treatment. Students from each treatment increased their meaningful understanding. However, neither group altered their learning orientation. The results of meaningful understanding as measured by conceptual questions, problem solving, and mental models were mixed. Differences were attributed to the weaknesses and strengths of each treatment. This research also examined four variables (treatment, reasoning ability, learning orientation, and prior knowledge) to find which best predicted students' overall meaningful understanding of physics concepts. None of these variables were significant predictors at the.05 level. However, when the same variables were used to predict students' specific understanding (i.e. concept, problem solving, or mental model understanding), the results were mixed. For forces and density/Archimedes Principle, prior knowledge and reasoning ability significantly predicted students' conceptual understanding. For heat, however, reasoning ability was the only significant predictor of concept understanding. Reasoning ability and treatment were significant predictors of students' problem solving for heat and forces. For density/Archimedes Principle, treatment was the only significant predictor of students' problem solving. None of the variables were significant predictors of mental model understanding. This research suggested that Piaget and Ausubel used different terminology to describe learning yet these theories are similar. Further research is needed to validate this premise and validate the blending of the two theories.

Problem-solving style and adaptation in breast cancer survivors: a prospective analysis.

PubMed

Heppner, P Paul; Armer, Jane M; Mallinckrodt, Brent

2009-06-01

Emotional care of the breast cancer patient is not well understood; this lack of understanding results in both a high cost to the patient, as well as the health care system. This study examined the role of problem-solving style as a predictor of emotional distress, adjustment to breast cancer, and physical function immediately post-surgery and 12 months later. The sample consisted of 121 women diagnosed with breast cancer and undergoing surgery as a primary treatment. The survivors completed a measure of problem-solving style and three outcome measures immediately post-surgery, as well as at 1 year later. There was a 95.6% retention rate at 1 year. Multiple hierarchical regressions revealed, after controlling for patient demographics and stage of cancer, that problem-solving style (particularly personal control) was associated with emotional distress, adjustment to chronic illness, and physical function immediately following surgical intervention. In addition, a more positive problem-solving style was associated with less emotional distress, but not a better adaptation to a chronic illness or physical functioning 12 months later; the Personal Control again was the best single predictor of the emotional distress, adding 10% of the variance in predicting this outcome. The utility of post-surgery assessment may help identify those in need for problem-solving training to improve these outcomes at 1 year. Future studies need to determine the impact of interventions tailored to levels of problem-solving styles in cancer survivors over time. Understanding the role of problem solving style in breast cancer survivors deserves attention as it is associated with emotional distress immediately and one year after medical intervention. Problem-solving style should be evaluated early, and interventions established for those most at risk for emotional distress.

The Influence of Self-Efficacy Beliefs and Metacognitive Prompting on Genetics Problem Solving Ability among High School Students in Kenya

NASA Astrophysics Data System (ADS)

Aurah, Catherine Muhonja

Within the framework of social cognitive theory, the influence of self-efficacy beliefs and metacognitive prompting on genetics problem solving ability among high school students in Kenya was examined through a mixed methods research design. A quasi-experimental study, supplemented by focus group interviews, was conducted to investigate both the outcomes and the processes of students' genetics problem-solving ability. Focus group interviews substantiated and supported findings from the quantitative instruments. The study was conducted in 17 high schools in Western Province, Kenya. A total of 2,138 high school students were purposively sampled. A sub-sample of 48 students participated in focus group interviews to understand their perspectives and experiences during the study so as to corroborate the quantitative data. Quantitative data were analyzed through descriptive statistics, zero-order correlations, 2 x 2 factorial ANOVA,, and sequential hierarchical multiple regressions. Qualitative data were transcribed, coded, and reported thematically. Results revealed metacognitive prompts had significant positive effects on student problem-solving ability independent of gender. Self-efficacy and metacognitive prompting significantly predicted genetics problem-solving ability. Gender differences were revealed, with girls outperforming boys on the genetics problem-solving test. Furthermore, self-efficacy moderated the relationship between metacognitive prompting and genetics problem-solving ability. This study established a foundation for instructional methods for biology teachers and recommendations are made for implementing metacognitive prompting in a problem-based learning environment in high schools and science teacher education programs in Kenya.

Personality and problem-solving in common mynas (Acridotheres tristis).

PubMed

Lermite, Françoise; Peneaux, Chloé; Griffin, Andrea S

2017-01-01

Animals show consistent individual differences in behaviour across time and/or contexts. Recently, it has been suggested that proactive personality types might also exhibit fast cognitive styles. The speed with which individuals sample environmental cues is one way in which correlations between personality and cognition might arise. Here, we measured a collection of behavioural traits (competitiveness, neophobia, neophilia, task-directed motivation and exploration) in common mynas (Acridotheres tristis) and measured their relationship with problem solving. We predicted that fast solving mynas would interact with (i.e. sample) the problem solving task at higher rates, but also be more competitive, less neophobic, more neophilic, and more exploratory. Mynas that were faster to solve a novel foraging problem were no more competitive around food and no more inclined to take risks. Unexpectedly, these fast-solving mynas had higher rates of interactions with the task, but also displayed lower levels of exploration. It is possible that a negative relation between problem solving and spatial exploration arose as a consequence of how inter-individual variation in exploration was quantified. We discuss the need for greater consensus on how to measure exploratory behaviour before we can advance our understanding of relationships between cognition and personality more effectively. Copyright © 2016 Elsevier B.V. All rights reserved.

Social factors predictive of social integration for adults with brain injury.

PubMed

Batchos, Elisabeth; Easton, Amanda; Haak, Christopher; Ditchman, Nicole

2018-08-01

Individuals with acquired brain injury (ABI) may not only struggle with physical and cognitive impairments, but may also face challenges reintegrating into the community socially. Research has demonstrated that following ABI, individuals' social networks tend to dwindle, support may decline, and isolation increases. This study examined factors impacting social integration in a community-based sample of 102 individuals with ABI. Potential predictors included emotional support, instrumental support, problem solving confidence, and approach-avoidance style (AAS) of problem solving, while controlling for age, gender, education, and time since injury. Hierarchical regression was used to analyze whether these factors were predictive of social integration. The final model accounted for 33% of the variance in social integration outcomes. Results demonstrated that emotional support was initially a significant predictor; however, when controlling for emotional support the variance in social integration was better accounted for by social problem solving - specifically, AAS. A follow-up mediation analysis indicated that the relationship between social problem solving (specifically, AAS) and social integration was partially mediated by emotional support. This suggests that for individuals with ABI, a tendency to approach rather than avoid social problem solving issues is a significant predictor for social integration both directly and indirectly through its association with emotional social support. Implications for Rehabilitation Both instrumental and emotional social support should be assessed in patients with acquired brain injury (ABI), ensuring that emotional needs are met in addition to the more obvious instrumental needs. Barriers to problem solving for people with ABI may limit optimal social integration; thus, assessment and intervention aimed at increasing AAS are recommended. To enhance the social integration outcomes of people with brain injury, strength-based psychosocial rehabilitation should optimally balance an individual's abilities with areas requiring compensation, focusing on how to approach rather than avoid problems as well as strategies to cultivate emotional social support.

Numerical formulation for the prediction of solid/liquid change of a binary alloy

NASA Technical Reports Server (NTRS)

Schneider, G. E.; Tiwari, S. N.

1990-01-01

A computational model is presented for the prediction of solid/liquid phase change energy transport including the influence of free convection fluid flow in the liquid phase region. The computational model considers the velocity components of all non-liquid phase change material control volumes to be zero but fully solves the coupled mass-momentum problem within the liquid region. The thermal energy model includes the entire domain and uses an enthalpy like model and a recently developed method for handling the phase change interface nonlinearity. Convergence studies are performed and comparisons made with experimental data for two different problem specifications. The convergence studies indicate that grid independence was achieved and the comparison with experimental data indicates excellent quantitative prediction of the melt fraction evolution. Qualitative data is also provided in the form of velocity vector diagrams and isotherm plots for selected times in the evolution of both problems. The computational costs incurred are quite low by comparison with previous efforts on solving these problems.

Complex collaborative problem-solving processes in mission control.

PubMed

Fiore, Stephen M; Wiltshire, Travis J; Oglesby, James M; O'Keefe, William S; Salas, Eduardo

2014-04-01

NASA's Mission Control Center (MCC) is responsible for control of the International Space Station (ISS), which includes responding to problems that obstruct the functioning of the ISS and that may pose a threat to the health and well-being of the flight crew. These problems are often complex, requiring individuals, teams, and multiteam systems, to work collaboratively. Research is warranted to examine individual and collaborative problem-solving processes in this context. Specifically, focus is placed on how Mission Control personnel-each with their own skills and responsibilities-exchange information to gain a shared understanding of the problem. The Macrocognition in Teams Model describes the processes that individuals and teams undertake in order to solve problems and may be applicable to Mission Control teams. Semistructured interviews centering on a recent complex problem were conducted with seven MCC professionals. In order to assess collaborative problem-solving processes in MCC with those predicted by the Macrocognition in Teams Model, a coding scheme was developed to analyze the interview transcriptions. Findings are supported with excerpts from participant transcriptions and suggest that team knowledge-building processes accounted for approximately 50% of all coded data and are essential for successful collaborative problem solving in mission control. Support for the internalized and externalized team knowledge was also found (19% and 20%, respectively). The Macrocognition in Teams Model was shown to be a useful depiction of collaborative problem solving in mission control and further research with this as a guiding framework is warranted.

On the Role of Situational Stressors in the Disruption of Global Neural Network Stability during Problem Solving.

PubMed

Liu, Mengting; Amey, Rachel C; Forbes, Chad E

2017-12-01

When individuals are placed in stressful situations, they are likely to exhibit deficits in cognitive capacity over and above situational demands. Despite this, individuals may still persevere and ultimately succeed in these situations. Little is known, however, about neural network properties that instantiate success or failure in both neutral and stressful situations, particularly with respect to regions integral for problem-solving processes that are necessary for optimal performance on more complex tasks. In this study, we outline how hidden Markov modeling based on multivoxel pattern analysis can be used to quantify unique brain states underlying complex network interactions that yield either successful or unsuccessful problem solving in more neutral or stressful situations. We provide evidence that brain network stability and states underlying synchronous interactions in regions integral for problem-solving processes are key predictors of whether individuals succeed or fail in stressful situations. Findings also suggested that individuals utilize discriminate neural patterns in successfully solving problems in stressful or neutral situations. Findings overall highlight how hidden Markov modeling can provide myriad possibilities for quantifying and better understanding the role of global network interactions in the problem-solving process and how the said interactions predict success or failure in different contexts.

Children's externalizing and internalizing symptoms over time: the role of individual differences in patterns of RSA responding.

PubMed

Hinnant, James Benjamin; El-Sheikh, Mona

2009-11-01

We examined associations between basal respiratory sinus arrhythmia (RSA) in conjunction with RSA regulation with the hypothesis that their interaction would explain unique variability in children's prospective adjustment 2 years later. Participants were 176 children (98 girls; 78 boys) in middle childhood. RSA regulation was assessed through social and problem-solving challenges. Parents reported on children's internalizing and externalizing symptoms. Interactions between RSA baseline and regulation to the social stressor predicted children's later internalizing symptoms. Interactions between RSA baseline and responding to the problem-solving stressor predicted children's externalizing symptoms. The highest levels of internalizing symptoms were predicted for children with both lower basal RSA and higher RSA suppression. The highest levels of externalizing symptoms were predicted for children who demonstrated lower basal RSA in conjunction with RSA augmentation. Findings highlight the importance of the contemporaneous consideration of basal RSA and RSA regulation in the prediction of developmental psychopathology symptomology.

Application of Direct Parallel Methods to Reconstruction and Forecasting Problems

NASA Astrophysics Data System (ADS)

Song, Changgeun

Many important physical processes in nature are represented by partial differential equations. Numerical weather prediction in particular, requires vast computational resources. We investigate the significance of parallel processing technology to the real world problem of atmospheric prediction. In this paper we consider the classic problem of decomposing the observed wind field into the irrotational and nondivergent components. Recognizing the fact that on a limited domain this problem has a non-unique solution, Lynch (1989) described eight different ways to accomplish the decomposition. One set of elliptic equations is associated with the decomposition--this determines the initial nondivergent state for the forecast model. It is shown that the entire decomposition problem can be solved in a fraction of a second using multi-vector processor such as ALLIANT FX/8. Secondly, the barotropic model is used to track hurricanes. Also, one set of elliptic equations is solved to recover the streamfunction from the forecasted vorticity. A 72 h prediction of Elena is made while it is in the Gulf of Mexico. During this time the hurricane executes a dramatic re-curvature that is captured by the model. Furthermore, an improvement in the track prediction results when a simple assimilation strategy is used. This technique makes use of the wind fields in the 24 h period immediately preceding the initial time for the prediction. In this particular application, solutions to systems of elliptic equations are the center of the computational mechanics. We demonstrate that direct, parallel methods based on accelerated block cyclic reduction (BCR) significantly reduce the computational time required to solve the elliptic equations germane to the decomposition, the forecast and adjoint assimilation.

Much ado about aha!: Insight problem solving is strongly related to working memory capacity and reasoning ability.

PubMed

Chuderski, Adam; Jastrzębski, Jan

2018-02-01

A battery comprising 4 fluid reasoning tests as well as 13 working memory (WM) tasks that involved storage, recall, updating, binding, and executive control, was applied to 318 adults in order to evaluate the true relationship of reasoning ability and WM capacity (WMC) to insight problem solving, measured using 40 verbal, spatial, math, matchstick, and remote associates problems (insight problems). WMC predicted 51.8% of variance in insight problem solving and virtually explained its almost isomorphic link to reasoning ability (84.6% of shared variance). The strong link between WMC and insight pertained generally to most WM tasks and insight problems, was identical for problems solved with and without reported insight, was linear throughout the ability levels, and was not mediated by age, motivation, anxiety, psychoticism, and openness to experience. In contrast to popular views on the sudden and holistic nature of insight, the solving of insight problems results primarily from typical operations carried out by the basic WM mechanisms that are responsible for the maintenance, retrieval, transformation, and control of information in the broad range of intellectual tasks (including fluid reasoning). Little above and beyond WM is unique about insight. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Predicting outcome of Internet-based treatment for depressive symptoms.

PubMed

Warmerdam, Lisanne; Van Straten, Annemieke; Twisk, Jos; Cuijpers, Pim

2013-01-01

In this study we explored predictors and moderators of response to Internet-based cognitive behavioral therapy (CBT) and Internet-based problem-solving therapy (PST) for depressive symptoms. The sample consisted of 263 participants with moderate to severe depressive symptoms. Of those, 88 were randomized to CBT, 88 to PST and 87 to a waiting list control condition. Outcomes were improvement and clinically significant change in depressive symptoms after 8 weeks. Higher baseline depression and higher education predicted improvement, while higher education, less avoidance behavior and decreased rational problem-solving skills predicted clinically significant change across all groups. No variables were found that differentially predicted outcome between Internet-based CBT and Internet-based PST. More research is needed with sufficient power to investigate predictors and moderators of response to reveal for whom Internet-based therapy is best suited.

Math and numeracy in young adults with spina bifida and hydrocephalus.

PubMed

Dennis, Maureen; Barnes, Marcia

2002-01-01

The developmental stability of poor math skill was studied in 31 young adults with spina bifida and hydrocephalus (SBH), a neurodevelopmental disorder involving malformations of the brain and spinal cord. Longitudinally, individuals with poor math problem solving as children grew into adults with poor problem solving and limited functional numeracy. As a group, young adults with SBH had poor computation accuracy, computation speed, problem solving, a ndfunctional numeracy. Computation accuracy was related to a supporting cognitive system (working memory for numbers), and functional numeracy was related to one medical history variable (number of lifetime shunt revisions). Adult functional numeracy, but not functional literacy, was predictive of higher levels of social, personal, and community independence.

Testing a model of depression among Thai adolescents.

PubMed

Vatanasin, Duangjai; Thapinta, Darawan; Thompson, Elaine Adams; Thungjaroenkul, Petsunee

2012-11-01

This predictive correlational study was designed to test a comprehensive model of depression for Thai adolescents. This sample included 800 high school students in Chiang Mai, Thailand. Data were collected using self-reported measures of depression, negative automatic thoughts, effective social problem solving, ineffective social problem solving, rumination, parental care, parental overprotection, and negative life events. Structural equation modeling revealed that negative automatic thoughts, effective and ineffective social problem solving mediated the effects of rumination, negative life events, and parental care and overprotection on adolescent depression. These findings provide new knowledge about identified factors and the mechanisms of their influence on depression among Thai adolescents, which are appropriate for targeting preventive interventions. © 2012 Wiley Periodicals, Inc.

Improving local clustering based top-L link prediction methods via asymmetric link clustering information

NASA Astrophysics Data System (ADS)

Wu, Zhihao; Lin, Youfang; Zhao, Yiji; Yan, Hongyan

2018-02-01

Networks can represent a wide range of complex systems, such as social, biological and technological systems. Link prediction is one of the most important problems in network analysis, and has attracted much research interest recently. Many link prediction methods have been proposed to solve this problem with various techniques. We can note that clustering information plays an important role in solving the link prediction problem. In previous literatures, we find node clustering coefficient appears frequently in many link prediction methods. However, node clustering coefficient is limited to describe the role of a common-neighbor in different local networks, because it cannot distinguish different clustering abilities of a node to different node pairs. In this paper, we shift our focus from nodes to links, and propose the concept of asymmetric link clustering (ALC) coefficient. Further, we improve three node clustering based link prediction methods via the concept of ALC. The experimental results demonstrate that ALC-based methods outperform node clustering based methods, especially achieving remarkable improvements on food web, hamster friendship and Internet networks. Besides, comparing with other methods, the performance of ALC-based methods are very stable in both globalized and personalized top-L link prediction tasks.

Systems Training for Emotional Predictability and Problem Solving (STEPPS) group treatment for offenders with borderline personality disorder.

PubMed

Black, Donald W; Blum, Nancee; McCormick, Brett; Allen, Jeff

2013-02-01

Systems Training for Emotional Predictability and Problem Solving (STEPPS) is a manual-based group treatment of persons with borderline personality disorder (BPD). We report results from a study of offenders supervised by the Iowa Department of Corrections. Seventy-seven offenders participated in STEPPS groups. The offenders experienced clinically significant improvement in BPD-related symptoms (d = 1.30), mood, and negative affectivity. Suicidal behaviors and disciplinary infractions were reduced. Baseline severity was inversely associated with improvement. The offenders indicated satisfaction with STEPPS. We conclude that STEPPS can be successfully integrated into the care of offenders with BPD in prison and community corrections settings.

The Co-Development of Skill at and Preference for Use of Retrieval-Based Processes for Solving Addition Problems: Individual and Sex Differences from First to Sixth Grade

PubMed Central

Bailey, Drew H.; Littlefield, Andrew; Geary, David C.

2012-01-01

The ability to retrieve basic arithmetic facts from long-term memory contributes to individual and perhaps sex differences in mathematics achievement. The current study tracked the co-development of preference for using retrieval over other strategies to solve single-digit addition problems, independent of accuracy, and skilled use of retrieval (i.e., accuracy and RT) from first to sixth grade, inclusive (n = 311). Accurate retrieval in first grade was related to working memory capacity and intelligence and predicted a preference for retrieval in second grade. In later grades, the relation between skill and preference changed such that preference in one grade predicted accuracy and RT in the next, as RT and accuracy continued to predict future gains in preference. In comparison to girls, boys had a consistent preference for retrieval over other strategies and had faster retrieval speeds, but the sex difference in retrieval accuracy varied across grades. Results indicate ability influences early skilled retrieval but both practice and skill influence each other in a feedback loop later in development, and provide insights into the source of the sex difference in problem solving approaches. PMID:22704036

A Message Passing Approach to Side Chain Positioning with Applications in Protein Docking Refinement *

PubMed Central

Moghadasi, Mohammad; Kozakov, Dima; Mamonov, Artem B.; Vakili, Pirooz; Vajda, Sandor; Paschalidis, Ioannis Ch.

2013-01-01

We introduce a message-passing algorithm to solve the Side Chain Positioning (SCP) problem. SCP is a crucial component of protein docking refinement, which is a key step of an important class of problems in computational structural biology called protein docking. We model SCP as a combinatorial optimization problem and formulate it as a Maximum Weighted Independent Set (MWIS) problem. We then employ a modified and convergent belief-propagation algorithm to solve a relaxation of MWIS and develop randomized estimation heuristics that use the relaxed solution to obtain an effective MWIS feasible solution. Using a benchmark set of protein complexes we demonstrate that our approach leads to more accurate docking predictions compared to a baseline algorithm that does not solve the SCP. PMID:23515575

Brain size predicts problem-solving ability in mammalian carnivores

PubMed Central

Benson-Amram, Sarah; Dantzer, Ben; Stricker, Gregory; Swanson, Eli M.; Holekamp, Kay E.

2016-01-01

Despite considerable interest in the forces shaping the relationship between brain size and cognitive abilities, it remains controversial whether larger-brained animals are, indeed, better problem-solvers. Recently, several comparative studies have revealed correlations between brain size and traits thought to require advanced cognitive abilities, such as innovation, behavioral flexibility, invasion success, and self-control. However, the general assumption that animals with larger brains have superior cognitive abilities has been heavily criticized, primarily because of the lack of experimental support for it. Here, we designed an experiment to inquire whether specific neuroanatomical or socioecological measures predict success at solving a novel technical problem among species in the mammalian order Carnivora. We presented puzzle boxes, baited with food and scaled to accommodate body size, to members of 39 carnivore species from nine families housed in multiple North American zoos. We found that species with larger brains relative to their body mass were more successful at opening the boxes. In a subset of species, we also used virtual brain endocasts to measure volumes of four gross brain regions and show that some of these regions improve model prediction of success at opening the boxes when included with total brain size and body mass. Socioecological variables, including measures of social complexity and manual dexterity, failed to predict success at opening the boxes. Our results, thus, fail to support the social brain hypothesis but provide important empirical support for the relationship between relative brain size and the ability to solve this novel technical problem. PMID:26811470

Brain size predicts problem-solving ability in mammalian carnivores.

PubMed

Benson-Amram, Sarah; Dantzer, Ben; Stricker, Gregory; Swanson, Eli M; Holekamp, Kay E

2016-03-01

Despite considerable interest in the forces shaping the relationship between brain size and cognitive abilities, it remains controversial whether larger-brained animals are, indeed, better problem-solvers. Recently, several comparative studies have revealed correlations between brain size and traits thought to require advanced cognitive abilities, such as innovation, behavioral flexibility, invasion success, and self-control. However, the general assumption that animals with larger brains have superior cognitive abilities has been heavily criticized, primarily because of the lack of experimental support for it. Here, we designed an experiment to inquire whether specific neuroanatomical or socioecological measures predict success at solving a novel technical problem among species in the mammalian order Carnivora. We presented puzzle boxes, baited with food and scaled to accommodate body size, to members of 39 carnivore species from nine families housed in multiple North American zoos. We found that species with larger brains relative to their body mass were more successful at opening the boxes. In a subset of species, we also used virtual brain endocasts to measure volumes of four gross brain regions and show that some of these regions improve model prediction of success at opening the boxes when included with total brain size and body mass. Socioecological variables, including measures of social complexity and manual dexterity, failed to predict success at opening the boxes. Our results, thus, fail to support the social brain hypothesis but provide important empirical support for the relationship between relative brain size and the ability to solve this novel technical problem.

A problem with problem solving: motivational traits, but not cognition, predict success on novel operant foraging tasks.

PubMed

van Horik, Jayden O; Madden, Joah R

2016-04-01

Rates of innovative foraging behaviours and success on problem-solving tasks are often used to assay differences in cognition, both within and across species. Yet the cognitive features of some problem-solving tasks can be unclear. As such, explanations that attribute cognitive mechanisms to individual variation in problem-solving performance have revealed conflicting results. We investigated individual consistency in problem-solving performances in captive-reared pheasant chicks, Phasianus colchicus , and addressed whether success depends on cognitive processes, such as trial-and-error associative learning, or whether performances may be driven solely via noncognitive motivational mechanisms, revealed through subjects' willingness to approach, engage with and persist in their interactions with an apparatus, or via physiological traits such as body condition. While subjects' participation and success were consistent within the same problems and across similar tasks, their performances were inconsistent across different types of task. Moreover, subjects' latencies to approach each test apparatus and their attempts to access the reward were not repeatable across trials. Successful individuals did not improve their performances with experience, nor were they consistent in their techniques in repeated presentations of a task. However, individuals that were highly motivated to enter the experimental chamber were more likely to participate. Successful individuals were also faster to approach each test apparatus and more persistent in their attempts to solve the tasks than unsuccessful individuals. Our findings therefore suggest that individual differences in problem-solving success can arise from inherent motivational differences alone and hence be achieved without inferring more complex cognitive processes.

A problem with problem solving: motivational traits, but not cognition, predict success on novel operant foraging tasks

PubMed Central

van Horik, Jayden O.; Madden, Joah R.

2016-01-01

Rates of innovative foraging behaviours and success on problem-solving tasks are often used to assay differences in cognition, both within and across species. Yet the cognitive features of some problem-solving tasks can be unclear. As such, explanations that attribute cognitive mechanisms to individual variation in problem-solving performance have revealed conflicting results. We investigated individual consistency in problem-solving performances in captive-reared pheasant chicks, Phasianus colchicus, and addressed whether success depends on cognitive processes, such as trial-and-error associative learning, or whether performances may be driven solely via noncognitive motivational mechanisms, revealed through subjects' willingness to approach, engage with and persist in their interactions with an apparatus, or via physiological traits such as body condition. While subjects' participation and success were consistent within the same problems and across similar tasks, their performances were inconsistent across different types of task. Moreover, subjects' latencies to approach each test apparatus and their attempts to access the reward were not repeatable across trials. Successful individuals did not improve their performances with experience, nor were they consistent in their techniques in repeated presentations of a task. However, individuals that were highly motivated to enter the experimental chamber were more likely to participate. Successful individuals were also faster to approach each test apparatus and more persistent in their attempts to solve the tasks than unsuccessful individuals. Our findings therefore suggest that individual differences in problem-solving success can arise from inherent motivational differences alone and hence be achieved without inferring more complex cognitive processes. PMID:27122637

In Search of Insight.

ERIC Educational Resources Information Center

Kaplan, Craig A.; Simon, Herbert A.

1990-01-01

Attaining the insight needed to solve the Mutilated Checkerboard problem, which requires discovery of an effective problem representation (EPR), is described. Performance on insight problems can be predicted from the availability of generators and constraints in the search for an EPR. Data for 23 undergraduates were analyzed. (TJH)

A geostatistical approach to the change-of-support problem and variable-support data fusion in spatial analysis

NASA Astrophysics Data System (ADS)

Wang, Jun; Wang, Yang; Zeng, Hui

2016-01-01

A key issue to address in synthesizing spatial data with variable-support in spatial analysis and modeling is the change-of-support problem. We present an approach for solving the change-of-support and variable-support data fusion problems. This approach is based on geostatistical inverse modeling that explicitly accounts for differences in spatial support. The inverse model is applied here to produce both the best predictions of a target support and prediction uncertainties, based on one or more measurements, while honoring measurements. Spatial data covering large geographic areas often exhibit spatial nonstationarity and can lead to computational challenge due to the large data size. We developed a local-window geostatistical inverse modeling approach to accommodate these issues of spatial nonstationarity and alleviate computational burden. We conducted experiments using synthetic and real-world raster data. Synthetic data were generated and aggregated to multiple supports and downscaled back to the original support to analyze the accuracy of spatial predictions and the correctness of prediction uncertainties. Similar experiments were conducted for real-world raster data. Real-world data with variable-support were statistically fused to produce single-support predictions and associated uncertainties. The modeling results demonstrate that geostatistical inverse modeling can produce accurate predictions and associated prediction uncertainties. It is shown that the local-window geostatistical inverse modeling approach suggested offers a practical way to solve the well-known change-of-support problem and variable-support data fusion problem in spatial analysis and modeling.

Cognitive Predictors of Achievement Growth in Mathematics: A Five Year Longitudinal Study

PubMed Central

Geary, David C.

2011-01-01

The study's goal was to identify the beginning of first grade quantitative competencies that predict mathematics achievement start point and growth through fifth grade. Measures of number, counting, and arithmetic competencies were administered in early first grade and used to predict mathematics achievement through fifth (n = 177), while controlling for intelligence, working memory, and processing speed. Multilevel models revealed intelligence, processing speed, and the central executive component of working memory predicted achievement or achievement growth in mathematics and, as a contrast domain, word reading. The phonological loop was uniquely predictive of word reading and the visuospatial sketch pad of mathematics. Early fluency in processing and manipulating numerical set size and Arabic numerals, accurate use of sophisticated counting procedures for solving addition problems, and accuracy in making placements on a mathematical number line were uniquely predictive of mathematics achievement. Use of memory-based processes to solve addition problems predicted mathematics and reading achievement but in different ways. The results identify the early quantitative competencies that uniquely contribute to mathematics learning. PMID:21942667

Application of Artificial Neural Network to Predict the use of Runway at Juanda International Airport

NASA Astrophysics Data System (ADS)

Putra, J. C. P.; Safrilah

2017-06-01

Artificial neural network approaches are useful to solve many complicated problems. It solves a number of problems in various areas such as engineering, medicine, business, manufacturing, etc. This paper presents an application of artificial neural network to predict a runway capacity at Juanda International Airport. An artificial neural network model of backpropagation and multi-layer perceptron is adopted to this research to learning process of runway capacity at Juanda International Airport. The results indicate that the training data is successfully recognizing the certain pattern of runway use at Juanda International Airport. Whereas, testing data indicate vice versa. Finally, it can be concluded that the approach of uniformity data and network architecture is the critical part to determine the accuracy of prediction results.

The relationship between two-dimensional self-esteem and problem solving style in an anorexic inpatient sample.

PubMed

Paterson, Gillian; Power, Kevin; Yellowlees, Alex; Park, Katy; Taylor, Louise

2007-01-01

Research examining cognitive and behavioural determinants of anorexia is currently lacking. This has implications for the success of treatment programmes for anorexics, particularly, given the high reported dropout rates. This study examines two-dimensional self-esteem (comprising of self-competence and self-liking) and social problem-solving in an anorexic population and predicts that self-esteem will mediate the relationship between problem-solving and eating pathology by facilitating/inhibiting use of faulty/effective strategies. Twenty-seven anorexic inpatients and 62 controls completed measures of social problem solving and two-dimensional self-esteem. Anorexics scored significantly higher than the non-clinical group on measures of eating pathology, negative problem orientation, impulsivity/carelessness and avoidance and significantly lower on positive problem orientation and both self-esteem components. In the clinical sample, disordered eating correlated significantly with self-competence, negative problem-orientation and avoidance. Associations between disordered eating and problem solving lost significance when self-esteem was controlled in the clinical group only. Self-competence was found to be the main predictor of eating pathology in the clinical sample while self-liking, impulsivity and negative and positive problem orientation were main predictors in the non-clinical sample. Findings support the two-dimensional self-esteem theory with self-competence only being relevant to the anorexic population and support the hypothesis that self-esteem mediates the relationship between disordered eating and problem solving ability in an anorexic sample. Treatment implications include support for programmes emphasising increasing self-appraisal and self-efficacy. 2006 John Wiley & Sons, Ltd and Eating Disorders Association

Prediction of Sound Waves Propagating Through a Nozzle Without/With a Shock Wave Using the Space-Time CE/SE Method

NASA Technical Reports Server (NTRS)

Wang, Xiao-Yen; Chang, Sin-Chung; Jorgenson, Philip C. E.

2000-01-01

The benchmark problems in Category 1 (Internal Propagation) of the third Computational Aeroacoustics (CAA) Work-shop sponsored by NASA Glenn Research Center are solved using the space-time conservation element and solution element (CE/SE) method. The first problem addresses the propagation of sound waves through a nearly choked transonic nozzle. The second one concerns shock-sound interaction in a supersonic nozzle. A quasi one-dimension CE/SE Euler solver for a nonuniform mesh is developed and employed to solve both problems. Numerical solutions are compared with the analytical solution for both problems. It is demonstrated that the CE/SE method is capable of solving aeroacoustic problems with/without shock waves in a simple way. Furthermore, the simple nonreflecting boundary condition used in the CE/SE method which is not based on the characteristic theory works very well.

Social problem solving in chronic pain: An integrative model of coping predicts mental health in chronic pain patients.

PubMed

Suso-Ribera, Carlos; Camacho-Guerrero, Laura; McCracken, Lance M; Maydeu-Olivares, Alberto; Gallardo-Pujol, David

2016-06-01

Despite several models of coping have been proposed in chronic pain, research is not integrative and has not yet identified a reliable set of beneficial coping strategies. We intend to offer a comprehensive view of coping using the social problem-solving model. Participants were 369 chronic pain patients (63.78% women; mean age 58.89 years; standard deviation = 15.12 years). Correlation analyses and the structural equation model for mental health revealed potentially beneficial and harmful problem-solving components. This integrative perspective on general coping could be used to promote changes in the way patients deal with stressful conditions other than pain. © The Author(s) 2014.

Cognitive correlates of serious suicidal ideation in a community sample of adolescents.

PubMed

Labelle, Réal; Breton, Jean-Jacques; Pouliot, Louise; Dufresne, Marie-Josée; Berthiaume, Claude

2013-03-05

Studies indicate that a dysfunctional attributional style, problem-solving deficits and hopelessness place youths at risk of developing suicidal thoughts and engaging in suicidal behaviour. However, in the realm of suicidality in adolescent, no study has examined the linkages between these three cognitive variables and suicidal ideation in non-clinical samples while taking into account the moderating role of gender on the relationships and controlling for depression. In this community study of 712 adolescents 14-18 years of age, through a multivariate approach, the interaction between the cognitive variables, depression and gender was examined with depression controlled in the analyses. Problem-solving deficits and hopelessness proved predictive of such ideation whether or not depressive symptoms were controlled in the analyses. Negative problem orientation/avoidant style was more predictive of ideation in boys than in girls. On the other hand, hopelessness was more predictive for girls than boys. Results were based on a convenience community sample of adolescents and a cross-sectional survey. Results suggest that a unique explanatory model of the suicide process in adolescence that fails to take account of gender would be ill informed. Suicide prevention strategies should be differentiated according to gender with a stronger emphasis in hopelessness in female adolescents, and problem-solving deficits in male adolescents. Copyright © 2012 Elsevier B.V. All rights reserved.

Probabilities and predictions: modeling the development of scientific problem-solving skills.

PubMed

Stevens, Ron; Johnson, David F; Soller, Amy

2005-01-01

The IMMEX (Interactive Multi-Media Exercises) Web-based problem set platform enables the online delivery of complex, multimedia simulations, the rapid collection of student performance data, and has already been used in several genetic simulations. The next step is the use of these data to understand and improve student learning in a formative manner. This article describes the development of probabilistic models of undergraduate student problem solving in molecular genetics that detailed the spectrum of strategies students used when problem solving, and how the strategic approaches evolved with experience. The actions of 776 university sophomore biology majors from three molecular biology lecture courses were recorded and analyzed. Each of six simulations were first grouped by artificial neural network clustering to provide individual performance measures, and then sequences of these performances were probabilistically modeled by hidden Markov modeling to provide measures of progress. The models showed that students with different initial problem-solving abilities choose different strategies. Initial and final strategies varied across different sections of the same course and were not strongly correlated with other achievement measures. In contrast to previous studies, we observed no significant gender differences. We suggest that instructor interventions based on early student performances with these simulations may assist students to recognize effective and efficient problem-solving strategies and enhance learning.

Solving Assembly Sequence Planning using Angle Modulated Simulated Kalman Filter

NASA Astrophysics Data System (ADS)

Mustapa, Ainizar; Yusof, Zulkifli Md.; Adam, Asrul; Muhammad, Badaruddin; Ibrahim, Zuwairie

2018-03-01

This paper presents an implementation of Simulated Kalman Filter (SKF) algorithm for optimizing an Assembly Sequence Planning (ASP) problem. The SKF search strategy contains three simple steps; predict-measure-estimate. The main objective of the ASP is to determine the sequence of component installation to shorten assembly time or save assembly costs. Initially, permutation sequence is generated to represent each agent. Each agent is then subjected to a precedence matrix constraint to produce feasible assembly sequence. Next, the Angle Modulated SKF (AMSKF) is proposed for solving ASP problem. The main idea of the angle modulated approach in solving combinatorial optimization problem is to use a function, g(x), to create a continuous signal. The performance of the proposed AMSKF is compared against previous works in solving ASP by applying BGSA, BPSO, and MSPSO. Using a case study of ASP, the results show that AMSKF outperformed all the algorithms in obtaining the best solution.

The relationship between mathematical problem-solving skills and self-regulated learning through homework behaviours, motivation, and metacognition

NASA Astrophysics Data System (ADS)

Çiğdem Özcan, Zeynep

2016-04-01

Studies highlight that using appropriate strategies during problem solving is important to improve problem-solving skills and draw attention to the fact that using these skills is an important part of students' self-regulated learning ability. Studies on this matter view the self-regulated learning ability as key to improving problem-solving skills. The aim of this study is to investigate the relationship between mathematical problem-solving skills and the three dimensions of self-regulated learning (motivation, metacognition, and behaviour), and whether this relationship is of a predictive nature. The sample of this study consists of 323 students from two public secondary schools in Istanbul. In this study, the mathematics homework behaviour scale was administered to measure students' homework behaviours. For metacognition measurements, the mathematics metacognition skills test for students was administered to measure offline mathematical metacognitive skills, and the metacognitive experience scale was used to measure the online mathematical metacognitive experience. The internal and external motivational scales used in the Programme for International Student Assessment (PISA) test were administered to measure motivation. A hierarchic regression analysis was conducted to determine the relationship between the dependent and independent variables in the study. Based on the findings, a model was formed in which 24% of the total variance in students' mathematical problem-solving skills is explained by the three sub-dimensions of the self-regulated learning model: internal motivation (13%), willingness to do homework (7%), and post-problem retrospective metacognitive experience (4%).

Estimation and Compression over Large Alphabets

ERIC Educational Resources Information Center

Acharya, Jayadev

2014-01-01

Compression, estimation, and prediction are basic problems in Information theory, statistics and machine learning. These problems have been extensively studied in all these fields, though the primary focus in a large portion of the work has been on understanding and solving the problems in the asymptotic regime, "i.e." the alphabet size…

Child and Family Predictors of Therapy Outcome for Children with Behavioral and Emotional Problems

ERIC Educational Resources Information Center

Hemphill, Sheryl A.; Littlefield, Lyn

2006-01-01

This study investigated the characteristics of 106 children primarily referred for externalizing behavior problems and their families, and assessed the prediction of treatment outcome following a standardized short-term, cognitive behavioral group program. "Exploring Together" comprised a children's group (anger management, problem-solving and…

Neural imaging to track mental states while using an intelligent tutoring system.

PubMed

Anderson, John R; Betts, Shawn; Ferris, Jennifer L; Fincham, Jon M

2010-04-13

Hemodynamic measures of brain activity can be used to interpret a student's mental state when they are interacting with an intelligent tutoring system. Functional magnetic resonance imaging (fMRI) data were collected while students worked with a tutoring system that taught an algebra isomorph. A cognitive model predicted the distribution of solution times from measures of problem complexity. Separately, a linear discriminant analysis used fMRI data to predict whether or not students were engaged in problem solving. A hidden Markov algorithm merged these two sources of information to predict the mental states of students during problem-solving episodes. The algorithm was trained on data from 1 day of interaction and tested with data from a later day. In terms of predicting what state a student was in during a 2-s period, the algorithm achieved 87% accuracy on the training data and 83% accuracy on the test data. The results illustrate the importance of integrating the bottom-up information from imaging data with the top-down information from a cognitive model.

A Physics-Based Engineering Methodology for Calculating Soft Error Rates of Bulk CMOS and SiGe Heterojunction Bipolar Transistor Integrated Circuits

NASA Astrophysics Data System (ADS)

Fulkerson, David E.

2010-02-01

This paper describes a new methodology for characterizing the electrical behavior and soft error rate (SER) of CMOS and SiGe HBT integrated circuits that are struck by ions. A typical engineering design problem is to calculate the SER of a critical path that commonly includes several circuits such as an input buffer, several logic gates, logic storage, clock tree circuitry, and an output buffer. Using multiple 3D TCAD simulations to solve this problem is too costly and time-consuming for general engineering use. The new and simple methodology handles the problem with ease by simple SPICE simulations. The methodology accurately predicts the measured threshold linear energy transfer (LET) of a bulk CMOS SRAM. It solves for circuit currents and voltage spikes that are close to those predicted by expensive 3D TCAD simulations. It accurately predicts the measured event cross-section vs. LET curve of an experimental SiGe HBT flip-flop. The experimental cross section vs. frequency behavior and other subtle effects are also accurately predicted.

A postprocessing method in the HMC framework for predicting gene function based on biological instrumental data

NASA Astrophysics Data System (ADS)

Feng, Shou; Fu, Ping; Zheng, Wenbin

2018-03-01

Predicting gene function based on biological instrumental data is a complicated and challenging hierarchical multi-label classification (HMC) problem. When using local approach methods to solve this problem, a preliminary results processing method is usually needed. This paper proposed a novel preliminary results processing method called the nodes interaction method. The nodes interaction method revises the preliminary results and guarantees that the predictions are consistent with the hierarchy constraint. This method exploits the label dependency and considers the hierarchical interaction between nodes when making decisions based on the Bayesian network in its first phase. In the second phase, this method further adjusts the results according to the hierarchy constraint. Implementing the nodes interaction method in the HMC framework also enhances the HMC performance for solving the gene function prediction problem based on the Gene Ontology (GO), the hierarchy of which is a directed acyclic graph that is more difficult to tackle. The experimental results validate the promising performance of the proposed method compared to state-of-the-art methods on eight benchmark yeast data sets annotated by the GO.

Analytic Formulation and Numerical Implementation of an Acoustic Pressure Gradient Prediction

NASA Technical Reports Server (NTRS)

Lee, Seongkyu; Brentner, Kenneth S.; Farassat, F.; Morris, Philip J.

2008-01-01

Two new analytical formulations of the acoustic pressure gradient have been developed and implemented in the PSU-WOPWOP rotor noise prediction code. The pressure gradient can be used to solve the boundary condition for scattering problems and it is a key aspect to solve acoustic scattering problems. The first formulation is derived from the gradient of the Ffowcs Williams-Hawkings (FW-H) equation. This formulation has a form involving the observer time differentiation outside the integrals. In the second formulation, the time differentiation is taken inside the integrals analytically. This formulation avoids the numerical time differentiation with respect to the observer time, which is computationally more efficient. The acoustic pressure gradient predicted by these new formulations is validated through comparison with available exact solutions for a stationary and moving monopole sources. The agreement between the predictions and exact solutions is excellent. The formulations are applied to the rotor noise problems for two model rotors. A purely numerical approach is compared with the analytical formulations. The agreement between the analytical formulations and the numerical method is excellent for both stationary and moving observer cases.

Using Deep Learning Model for Meteorological Satellite Cloud Image Prediction

NASA Astrophysics Data System (ADS)

Su, X.

2017-12-01

A satellite cloud image contains much weather information such as precipitation information. Short-time cloud movement forecast is important for precipitation forecast and is the primary means for typhoon monitoring. The traditional methods are mostly using the cloud feature matching and linear extrapolation to predict the cloud movement, which makes that the nonstationary process such as inversion and deformation during the movement of the cloud is basically not considered. It is still a hard task to predict cloud movement timely and correctly. As deep learning model could perform well in learning spatiotemporal features, to meet this challenge, we could regard cloud image prediction as a spatiotemporal sequence forecasting problem and introduce deep learning model to solve this problem. In this research, we use a variant of Gated-Recurrent-Unit(GRU) that has convolutional structures to deal with spatiotemporal features and build an end-to-end model to solve this forecast problem. In this model, both the input and output are spatiotemporal sequences. Compared to Convolutional LSTM(ConvLSTM) model, this model has lower amount of parameters. We imply this model on GOES satellite data and the model perform well.

Predicting Phenotypes from Genetic Crosses: A Mathematical Concept to Help Struggling Biology Students

ERIC Educational Resources Information Center

Baurhoo, Neerusha; Darwish, Shireef

2012-01-01

Predicting phenotypic outcomes from genetic crosses is often very difficult for biology students, especially those with learning disabilities. With our mathematical concept, struggling students in inclusive biology classrooms are now better equipped to solve genetic problems and predict phenotypes, because of improved understanding of dominance…

Using Problematizing Ability to Predict Student Performance in a First Course in Computer Programming

ERIC Educational Resources Information Center

Schuyler, Stanley TenEyck

2008-01-01

Problem solving can be thought of in two phases: the first phase is problem formulation and the second solution development. Problem formulation is the process of identifying a problem or opportunity in a situation. Problem Formulation Ability, or PFA, is the ability to perform this process. This research investigated a method to assess PFA and…

Role of beliefs and emotions in numerical problem solving in university physics education

NASA Astrophysics Data System (ADS)

Bodin, Madelen; Winberg, Mikael

2012-06-01

Numerical problem solving in classical mechanics in university physics education offers a learning situation where students have many possibilities of control and creativity. In this study, expertlike beliefs about physics and learning physics together with prior knowledge were the most important predictors of the quality of performance of a task with many degrees of freedom. Feelings corresponding to control and concentration, i.e., emotions that are expected to trigger students’ intrinsic motivation, were also important in predicting performance. Unexpectedly, intrinsic motivation, as indicated by enjoyment and interest, together with students’ personal interest and utility value beliefs did not predict performance. This indicates that although a certain degree of enjoyment is probably necessary, motivated behavior is rather regulated by integration and identification of expertlike beliefs about learning and are more strongly associated with concentration and control during learning and, ultimately, with high performance. The results suggest that the development of students’ epistemological beliefs is important for students’ ability to learn from realistic problem-solving situations with many degrees of freedom in physics education.

Research on the Wire Network Signal Prediction Based on the Improved NNARX Model

NASA Astrophysics Data System (ADS)

Zhang, Zipeng; Fan, Tao; Wang, Shuqing

It is difficult to obtain accurately the wire net signal of power system's high voltage power transmission lines in the process of monitoring and repairing. In order to solve this problem, the signal measured in remote substation or laboratory is employed to make multipoint prediction to gain the needed data. But, the obtained power grid frequency signal is delay. In order to solve the problem, an improved NNARX network which can predict frequency signal based on multi-point data collected by remote substation PMU is describes in this paper. As the error curved surface of the NNARX network is more complicated, this paper uses L-M algorithm to train the network. The result of the simulation shows that the NNARX network has preferable predication performance which provides accurate real time data for field testing and maintenance.

Is self-generated thought a means of social problem solving?

PubMed Central

Ruby, Florence J. M.; Smallwood, Jonathan; Sackur, Jerome; Singer, Tania

2013-01-01

Appropriate social problem solving constitutes a critical skill for individuals and may rely on processes important for self-generated thought (SGT). The aim of the current study was to investigate the link between SGT and social problem solving. Using the Means-End Problem Solving task (MEPS), we assessed participants' abilities to resolve daily social problems in terms of overall efficiency and number of relevant means they provided to reach the given solution. Participants also performed a non-demanding choice reaction time task (CRT) and a moderately-demanding working memory task (WM) as a context in which to measure their SGT (assessed via thought sampling). We found that although overall SGT was associated with lower MEPS efficiency, it was also associated with higher relevant means, perhaps because both depend on the capacity to generate cognition that is independent from the hear and now. The specific content of SGT did not differentially predict individual differences in social problem solving, suggesting that the relationship may depend on SGT regardless of its content. In addition, we also found that performance at the WM but not the CRT was linked to overall better MEPS performance, suggesting that individuals good at social processing are also distinguished by their capacity to constrain attention to an external task. Our results provide novel evidence that the capacity for SGT is implicated in the process by which solutions to social problems are generated, although optimal problem solving may be achieved by individuals who display a suitable balance between SGT and cognition derived from perceptual input. PMID:24391621

HEAP: Heat Energy Analysis Program, a computer model simulating solar receivers. [solving the heat transfer problem

NASA Technical Reports Server (NTRS)

Lansing, F. L.

1979-01-01

A computer program which can distinguish between different receiver designs, and predict transient performance under variable solar flux, or ambient temperatures, etc. has a basic structure that fits a general heat transfer problem, but with specific features that are custom-made for solar receivers. The code is written in MBASIC computer language. The methodology followed in solving the heat transfer problem is explained. A program flow chart, an explanation of input and output tables, and an example of the simulation of a cavity-type solar receiver are included.

Computational inverse methods of heat source in fatigue damage problems

NASA Astrophysics Data System (ADS)

Chen, Aizhou; Li, Yuan; Yan, Bo

2018-04-01

Fatigue dissipation energy is the research focus in field of fatigue damage at present. It is a new idea to solve the problem of calculating fatigue dissipation energy by introducing inverse method of heat source into parameter identification of fatigue dissipation energy model. This paper introduces the research advances on computational inverse method of heat source and regularization technique to solve inverse problem, as well as the existing heat source solution method in fatigue process, prospects inverse method of heat source applying in fatigue damage field, lays the foundation for further improving the effectiveness of fatigue dissipation energy rapid prediction.

Dynamic Assessment of Algebraic Learning in Predicting Third Graders’ Development of Mathematical Problem Solving

PubMed Central

Fuchs, Lynn S.; Compton, Donald L.; Fuchs, Douglas; Hollenbeck, Kurstin N.; Craddock, Caitlin F.; Hamlett, Carol L.

2008-01-01

Dynamic assessment (DA) involves helping students learn a task and indexing responsiveness to that instruction as a measure of learning potential. The purpose of this study was to explore the utility of a DA of algebraic learning in predicting 3rd graders’ development of mathematics problem solving. In the fall, 122 3rd-grade students were assessed on language, nonverbal reasoning, attentive behavior, calculations, word-problem skill, and DA. On the basis of random assignment, students received 16 weeks of validated instruction on word problems or received 16 weeks of conventional instruction on word problems. Then, students were assessed on word-problem measures proximal and distal to instruction. Structural equation measurement models showed that DA measured a distinct dimension of pretreatment ability and that proximal and distal word-problem measures were needed to account for outcome. Structural equation modeling showed that instruction (conventional vs. validated) was sufficient to account for math word-problem outcome proximal to instruction; by contrast, language, pretreatment math skill, and DA were needed to forecast learning on word-problem outcomes more distal to instruction. Findings are discussed in terms of responsiveness-to-intervention models for preventing and identifying learning disabilities. PMID:19884957

Solving a novel confinement problem by spartaeine salticids that are predisposed to solve problems in the context of predation.

PubMed

Cross, Fiona R; Jackson, Robert R

2015-03-01

Intricate predatory strategies are widespread in the salticid subfamily Spartaeinae. The hypothesis we consider here is that the spartaeine species that are proficient at solving prey-capture problems are also proficient at solving novel problems. We used nine species from this subfamily in our experiments. Eight of these species (two Brettus, one Cocalus, three Cyrba, two Portia) are known for specialized invasion of other spiders' webs and for actively choosing other spiders as preferred prey ('araneophagy'). Except for Cocalus, these species also use trial and error to derive web-based signals with which they gain dynamic fine control of the resident spider's behaviour ('aggressive mimicry').The ninth species, Paracyrba wanlessi, is not araneophagic and instead specializes at preying on mosquitoes. We presented these nine species with a novel confinement problem that could be solved by trial and error. The test spider began each trial on an island in a tray of water, with an atoll surrounding the island. From the island, the spider could choose between two potential escape tactics (leap or swim), but we decided at random before the trial which tactic would fail and which tactic would achieve partial success. Our findings show that the seven aggressive-mimic species are proficient at solving the confinement problem by repeating 'correct' choices and by switching to the alternative tactic after making an 'incorrect' choice. However, as predicted, there was no evidence of C. gibbosus or P. wanlessi, the two non-aggressive-mimic species, solving the confinement problem. We discuss these findings in the context of an often-made distinction between domain-specific and domain-general cognition.

Protein Structure Prediction with Evolutionary Algorithms

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

Hart, W.E.; Krasnogor, N.; Pelta, D.A.

1999-02-08

Evolutionary algorithms have been successfully applied to a variety of molecular structure prediction problems. In this paper we reconsider the design of genetic algorithms that have been applied to a simple protein structure prediction problem. Our analysis considers the impact of several algorithmic factors for this problem: the confirmational representation, the energy formulation and the way in which infeasible conformations are penalized, Further we empirically evaluated the impact of these factors on a small set of polymer sequences. Our analysis leads to specific recommendations for both GAs as well as other heuristic methods for solving PSP on the HP model.

Handling a Small Dataset Problem in Prediction Model by employ Artificial Data Generation Approach: A Review

NASA Astrophysics Data System (ADS)

Lateh, Masitah Abdul; Kamilah Muda, Azah; Yusof, Zeratul Izzah Mohd; Azilah Muda, Noor; Sanusi Azmi, Mohd

2017-09-01

The emerging era of big data for past few years has led to large and complex data which needed faster and better decision making. However, the small dataset problems still arise in a certain area which causes analysis and decision are hard to make. In order to build a prediction model, a large sample is required as a training sample of the model. Small dataset is insufficient to produce an accurate prediction model. This paper will review an artificial data generation approach as one of the solution to solve the small dataset problem.

Sandia National Laboratories analysis code data base

NASA Astrophysics Data System (ADS)

Peterson, C. W.

1994-11-01

Sandia National Laboratories' mission is to solve important problems in the areas of national defense, energy security, environmental integrity, and industrial technology. The laboratories' strategy for accomplishing this mission is to conduct research to provide an understanding of the important physical phenomena underlying any problem, and then to construct validated computational models of the phenomena which can be used as tools to solve the problem. In the course of implementing this strategy, Sandia's technical staff has produced a wide variety of numerical problem-solving tools which they use regularly in the design, analysis, performance prediction, and optimization of Sandia components, systems, and manufacturing processes. This report provides the relevant technical and accessibility data on the numerical codes used at Sandia, including information on the technical competency or capability area that each code addresses, code 'ownership' and release status, and references describing the physical models and numerical implementation.

Qualitative Differences in Real-Time Solution of Standardized Figural Analogies.

ERIC Educational Resources Information Center

Schiano, Diane J.; And Others

Performance on standardized figural analogy tests is considered highly predictive of academic success. While information-processing models of analogy solution attribute performance differences to quantitative differences in processing parameters, the problem-solving literature suggests that qualitative differences in problem representation and…

The Use of Factorial Forecasting to Predict Public Response

ERIC Educational Resources Information Center

Weiss, David J.

2012-01-01

Policies that call for members of the public to change their behavior fail if people don't change; predictions of whether the requisite changes will take place are needed prior to implementation. I propose to solve the prediction problem with Factorial Forecasting, a version of functional measurement methodology that employs group designs. Aspects…

Manage Your Life Online (MYLO): a pilot trial of a conversational computer-based intervention for problem solving in a student sample.

PubMed

Gaffney, Hannah; Mansell, Warren; Edwards, Rachel; Wright, Jason

2014-11-01

Computerized self-help that has an interactive, conversational format holds several advantages, such as flexibility across presenting problems and ease of use. We designed a new program called MYLO that utilizes the principles of METHOD of Levels (MOL) therapy--based upon Perceptual Control Theory (PCT). We tested the efficacy of MYLO, tested whether the psychological change mechanisms described by PCT mediated its efficacy, and evaluated effects of client expectancy. Forty-eight student participants were randomly assigned to MYLO or a comparison program ELIZA. Participants discussed a problem they were currently experiencing with their assigned program and completed measures of distress, resolution and expectancy preintervention, postintervention and at 2-week follow-up. MYLO and ELIZA were associated with reductions in distress, depression, anxiety and stress. MYLO was considered more helpful and led to greater problem resolution. The psychological change processes predicted higher ratings of MYLO's helpfulness and reductions in distress. Positive expectancies towards computer-based problem solving correlated with MYLO's perceived helpfulness and greater problem resolution, and this was partly mediated by the psychological change processes identified. The findings provide provisional support for the acceptability of the MYLO program in a non-clinical sample although its efficacy as an innovative computer-based aid to problem solving remains unclear. Nevertheless, the findings provide tentative early support for the mechanisms of psychological change identified within PCT and highlight the importance of client expectations on predicting engagement in computer-based self-help.

Software Design Challenges in Time Series Prediction Systems Using Parallel Implementation of Artificial Neural Networks.

PubMed

Manikandan, Narayanan; Subha, Srinivasan

2016-01-01

Software development life cycle has been characterized by destructive disconnects between activities like planning, analysis, design, and programming. Particularly software developed with prediction based results is always a big challenge for designers. Time series data forecasting like currency exchange, stock prices, and weather report are some of the areas where an extensive research is going on for the last three decades. In the initial days, the problems with financial analysis and prediction were solved by statistical models and methods. For the last two decades, a large number of Artificial Neural Networks based learning models have been proposed to solve the problems of financial data and get accurate results in prediction of the future trends and prices. This paper addressed some architectural design related issues for performance improvement through vectorising the strengths of multivariate econometric time series models and Artificial Neural Networks. It provides an adaptive approach for predicting exchange rates and it can be called hybrid methodology for predicting exchange rates. This framework is tested for finding the accuracy and performance of parallel algorithms used.

Software Design Challenges in Time Series Prediction Systems Using Parallel Implementation of Artificial Neural Networks

PubMed Central

Manikandan, Narayanan; Subha, Srinivasan

2016-01-01

Software development life cycle has been characterized by destructive disconnects between activities like planning, analysis, design, and programming. Particularly software developed with prediction based results is always a big challenge for designers. Time series data forecasting like currency exchange, stock prices, and weather report are some of the areas where an extensive research is going on for the last three decades. In the initial days, the problems with financial analysis and prediction were solved by statistical models and methods. For the last two decades, a large number of Artificial Neural Networks based learning models have been proposed to solve the problems of financial data and get accurate results in prediction of the future trends and prices. This paper addressed some architectural design related issues for performance improvement through vectorising the strengths of multivariate econometric time series models and Artificial Neural Networks. It provides an adaptive approach for predicting exchange rates and it can be called hybrid methodology for predicting exchange rates. This framework is tested for finding the accuracy and performance of parallel algorithms used. PMID:26881271

Intuitive reasoning about abstract and familiar physics problems

NASA Technical Reports Server (NTRS)

Kaiser, Mary Kister; Jonides, John; Alexander, Joanne

1986-01-01

Previous research has demonstrated that many people have misconceptions about basic properties of motion. Two experiments examined whether people are more likely to produce dynamically correct predictions about basic motion problems involving situations with which they are familiar, and whether solving such problems enhances performance on a subsequent abstract problem. In experiment 1, college students were asked to predict the trajectories of objects exiting a curved tube. Subjects were more accurate on the familiar version of the problem, and there was no evidence of transfer to the abstract problem. In experiment 2, two familiar problems were provided in an attempt to enhance subjects' tendency to extract the general structure of the problems. Once again, they gave more correct responses to the familiar problems but failed to generalize to the abstract problem. Formal physics training was associated with correct predictions for the abstract problem but was unrelated to performance on the familiar problems.

Model-Based Prognostics of Hybrid Systems

NASA Technical Reports Server (NTRS)

Daigle, Matthew; Roychoudhury, Indranil; Bregon, Anibal

2015-01-01

Model-based prognostics has become a popular approach to solving the prognostics problem. However, almost all work has focused on prognostics of systems with continuous dynamics. In this paper, we extend the model-based prognostics framework to hybrid systems models that combine both continuous and discrete dynamics. In general, most systems are hybrid in nature, including those that combine physical processes with software. We generalize the model-based prognostics formulation to hybrid systems, and describe the challenges involved. We present a general approach for modeling hybrid systems, and overview methods for solving estimation and prediction in hybrid systems. As a case study, we consider the problem of conflict (i.e., loss of separation) prediction in the National Airspace System, in which the aircraft models are hybrid dynamical systems.

Integrated identification, modeling and control with applications

NASA Astrophysics Data System (ADS)

Shi, Guojun

This thesis deals with the integration of system design, identification, modeling and control. In particular, six interdisciplinary engineering problems are addressed and investigated. Theoretical results are established and applied to structural vibration reduction and engine control problems. First, the data-based LQG control problem is formulated and solved. It is shown that a state space model is not necessary to solve this problem; rather a finite sequence from the impulse response is the only model data required to synthesize an optimal controller. The new theory avoids unnecessary reliance on a model, required in the conventional design procedure. The infinite horizon model predictive control problem is addressed for multivariable systems. The basic properties of the receding horizon implementation strategy is investigated and the complete framework for solving the problem is established. The new theory allows the accommodation of hard input constraints and time delays. The developed control algorithms guarantee the closed loop stability. A closed loop identification and infinite horizon model predictive control design procedure is established for engine speed regulation. The developed algorithms are tested on the Cummins Engine Simulator and desired results are obtained. A finite signal-to-noise ratio model is considered for noise signals. An information quality index is introduced which measures the essential information precision required for stabilization. The problems of minimum variance control and covariance control are formulated and investigated. Convergent algorithms are developed for solving the problems of interest. The problem of the integrated passive and active control design is addressed in order to improve the overall system performance. A design algorithm is developed, which simultaneously finds: (i) the optimal values of the stiffness and damping ratios for the structure, and (ii) an optimal output variance constrained stabilizing controller such that the active control energy is minimized. A weighted q-Markov COVER method is introduced for identification with measurement noise. The result is use to develop an iterative closed loop identification/control design algorithm. The effectiveness of the algorithm is illustrated by experimental results.

Problem-Solving Phase Transitions During Team Collaboration.

PubMed

Wiltshire, Travis J; Butner, Jonathan E; Fiore, Stephen M

2018-01-01

Multiple theories of problem-solving hypothesize that there are distinct qualitative phases exhibited during effective problem-solving. However, limited research has attempted to identify when transitions between phases occur. We integrate theory on collaborative problem-solving (CPS) with dynamical systems theory suggesting that when a system is undergoing a phase transition it should exhibit a peak in entropy and that entropy levels should also relate to team performance. Communications from 40 teams that collaborated on a complex problem were coded for occurrence of problem-solving processes. We applied a sliding window entropy technique to each team's communications and specified criteria for (a) identifying data points that qualify as peaks and (b) determining which peaks were robust. We used multilevel modeling, and provide a qualitative example, to evaluate whether phases exhibit distinct distributions of communication processes. We also tested whether there was a relationship between entropy values at transition points and CPS performance. We found that a proportion of entropy peaks was robust and that the relative occurrence of communication codes varied significantly across phases. Peaks in entropy thus corresponded to qualitative shifts in teams' CPS communications, providing empirical evidence that teams exhibit phase transitions during CPS. Also, lower average levels of entropy at the phase transition points predicted better CPS performance. We specify future directions to improve understanding of phase transitions during CPS, and collaborative cognition, more broadly. Copyright © 2017 Cognitive Science Society, Inc.

Tailoring Configuration to User’s Tasks under Uncertainty

DTIC Science & Technology

2008-04-28

CARISMA is the problem being solved. CARISMA applies microeconom- ics and game theory to make runtime decisions about allocating scarce resources among...scarce resources, these applications are running on be- half of one user. Thus, our problem has no game theoretic aspects. 2.2 Task Oriented...prediction tool [15] is based on the RPS tool and allows prediction of bandwidth online . There is additional evidence (see, for example [49

Predictors of hopelessness among clinically depressed youth.

PubMed

Becker-Weidman, Emily G; Reinecke, Mark A; Jacobs, Rachel H; Martinovich, Zoran; Silva, Susan G; March, John S

2009-05-01

Factors that distinguish depressed individuals who become hopeless from those who do not are poorly understood. In this study, predictors of hopelessness were examined in a sample of 439 clinically depressed adolescents participating in the Treatment for Adolescents with Depression Study (TADS). The total score of the Beck Hopelessness Scale (BHS) was used to assess hopelessness at baseline. Multiple regression and logistic regression analyses were conducted to evaluate the extent to which variables were associated with hopelessness and determine which cluster of measures best predicted clinically significantly hopelessness. Hopelessness was associated with greater depression severity, poor social problem-solving, cognitive distortions, and family conflict. View of self, view of the world, internal attributional style, need for social approval, positive problem-solving orientation, and family problems consistently emerged as the best predictors of hopelessness in depressed youth. Cognitive and familial factors predict those depressed youth who have high levels of hopelessness.

Predictive analysis and data mining among the employment of fresh graduate students in HEI

NASA Astrophysics Data System (ADS)

Rahman, Nor Azziaty Abdul; Tan, Kian Lam; Lim, Chen Kim

2017-10-01

Management of higher education have a problem in producing 100% of graduates who can meet the needs of industry while industry is also facing the problem of finding skilled graduates who suit their needs partly due to the lack of an effective method in assessing problem solving skills as well as weaknesses in the assessment of problem-solving skills. The purpose of this paper is to propose a suitable classification model that can be used in making prediction and assessment of the attributes of the student's dataset to meet the selection criteria of work demanded by the industry of the graduates in the academic field. Supervised and unsupervised Machine Learning Algorithms were used in this research where; K-Nearest Neighbor, Naïve Bayes, Decision Tree, Neural Network, Logistic Regression and Support Vector Machine. The proposed model will help the university management to make a better long-term plans for producing graduates who are skilled, knowledgeable and fulfill the industry needs as well.

Retrosynthetic Reaction Prediction Using Neural Sequence-to-Sequence Models

PubMed Central

2017-01-01

We describe a fully data driven model that learns to perform a retrosynthetic reaction prediction task, which is treated as a sequence-to-sequence mapping problem. The end-to-end trained model has an encoder–decoder architecture that consists of two recurrent neural networks, which has previously shown great success in solving other sequence-to-sequence prediction tasks such as machine translation. The model is trained on 50,000 experimental reaction examples from the United States patent literature, which span 10 broad reaction types that are commonly used by medicinal chemists. We find that our model performs comparably with a rule-based expert system baseline model, and also overcomes certain limitations associated with rule-based expert systems and with any machine learning approach that contains a rule-based expert system component. Our model provides an important first step toward solving the challenging problem of computational retrosynthetic analysis. PMID:29104927

Understanding the Equals Sign as a Gateway to Algebraic Thinking

ERIC Educational Resources Information Center

Matthews, Percival G.; Rittle-Johnson, Bethany; Taylor, Roger S.; McEldoon, Katherine L.

2010-01-01

In this study, the authors wanted to examine whether success on items testing basic equivalence knowledge, such as the meaning of the equal sign and ability to solve problems such as 3 + 5 = 4 + _, predicted success on items testing more advanced algebraic thinking (i.e. principles of equality and solving equations that use letter variables). This…

Psychometric properties of the Social Problem Solving Inventory-Revised Short-Form in a South African population.

PubMed

Sorsdahl, Katherine; Stein, Dan J; Myers, Bronwyn

2017-04-01

The Social Problem Solving Inventory-Revised Short-Form (SPSI-R:SF) has been used in several countries to identify problem-solving deficits among clinical and general populations in order to guide cognitive-behavioural interventions. Yet, very few studies have evaluated its psychometric properties. Three language versions of the questionnaire were administered to a general population sample comprising 1000 participants (771 English-, 178 Afrikaans- and 101 Xhosa-speakers). Of these participants, 210 were randomly selected to establish test-retest reliability (70 in each language). Principal component analysis was performed to examine the applicability of the factor structure of the original questionnaire to the South African data. Supplementary psychometric analyses were performed, including internal consistency and test-retest reliability. Collectively, results provide initial evidence of the reliability and validity of the SPSI-R:SF for the assessment of problem solving deficits in South Africa. Further studies that explore how the Afrikaans language version of the SPSI-R:SF can be improved and that establish the predictive validity of scores on the SPSI-R:SF are needed. © 2015 International Union of Psychological Science.

Working with low back pain: problem-solving orientation and function.

PubMed

Shaw, W S; Feuerstein, M; Haufler, A J; Berkowitz, S M; Lopez, M S

2001-08-01

A number of ergonomic, workplace and individual psychosocial factors and health behaviors have been associated with the onset, exacerbation and/or maintenance of low back pain (LBP). The functional impact of these factors may be influenced by how a worker approaches problems in general. The present study was conducted to determine whether problem-solving orientation was associated with physical and mental health outcomes in fully employed workers (soldiers) reporting a history of LBP in the past year. The sample consisted of 475 soldiers (446 male, 29 female; mean age 24.5 years) who worked in jobs identified as high risk for LBP-related disability and reported LBP symptoms in the past 12 months. The Social Problem-Solving Inventory and the Standard Form-12 (SF-12) were completed by all subjects. Hierarchical multiple regression analyses were used to predict the SF-12 physical health summary scale from interactions of LBP symptoms with each of five problem-solving subscales. Low scores on positive problem-solving orientation (F(1,457)=4.49), and high scores on impulsivity/carelessness (F(1,457)=9.11) were associated with a steeper gradient in functional loss related to LBP. Among those with a longer history of low-grade LBP, an avoidant approach to problem-solving was also associated with a steeper gradient of functional loss (three-way interaction; F(1,458)=4.58). These results suggest that the prolonged impact of LBP on daily function may be reduced by assisting affected workers to conceptualize LBP as a problem that can be overcome and using strategies that promote taking an active role in reducing risks for LBP. Secondary prevention efforts may be improved by addressing these factors.

Reinforcement learning in computer vision

NASA Astrophysics Data System (ADS)

Bernstein, A. V.; Burnaev, E. V.

2018-04-01

Nowadays, machine learning has become one of the basic technologies used in solving various computer vision tasks such as feature detection, image segmentation, object recognition and tracking. In many applications, various complex systems such as robots are equipped with visual sensors from which they learn state of surrounding environment by solving corresponding computer vision tasks. Solutions of these tasks are used for making decisions about possible future actions. It is not surprising that when solving computer vision tasks we should take into account special aspects of their subsequent application in model-based predictive control. Reinforcement learning is one of modern machine learning technologies in which learning is carried out through interaction with the environment. In recent years, Reinforcement learning has been used both for solving such applied tasks as processing and analysis of visual information, and for solving specific computer vision problems such as filtering, extracting image features, localizing objects in scenes, and many others. The paper describes shortly the Reinforcement learning technology and its use for solving computer vision problems.

Clinical and Cognitive Characteristics Associated with Mathematics Problem Solving in Adolescents with Autism Spectrum Disorder.

PubMed

Oswald, Tasha M; Beck, Jonathan S; Iosif, Ana-Maria; McCauley, James B; Gilhooly, Leslie J; Matter, John C; Solomon, Marjorie

2016-04-01

Mathematics achievement in autism spectrum disorder (ASD) has been understudied. However, the ability to solve applied math problems is associated with academic achievement, everyday problem-solving abilities, and vocational outcomes. The paucity of research on math achievement in ASD may be partly explained by the widely-held belief that most individuals with ASD are mathematically gifted, despite emerging evidence to the contrary. The purpose of the study was twofold: to assess the relative proportions of youth with ASD who demonstrate giftedness versus disability on applied math problems, and to examine which cognitive (i.e., perceptual reasoning, verbal ability, working memory) and clinical (i.e., test anxiety) characteristics best predict achievement on applied math problems in ASD relative to typically developing peers. Twenty-seven high-functioning adolescents with ASD and 27 age- and Full Scale IQ-matched typically developing controls were assessed on standardized measures of math problem solving, perceptual reasoning, verbal ability, and test anxiety. Results indicated that 22% of the ASD sample evidenced a mathematics learning disability, while only 4% exhibited mathematical giftedness. The parsimonious linear regression model revealed that the strongest predictor of math problem solving was perceptual reasoning, followed by verbal ability and test anxiety, then diagnosis of ASD. These results inform our theories of math ability in ASD and highlight possible targets of intervention for students with ASD struggling with mathematics. © 2015 International Society for Autism Research, Wiley Periodicals, Inc.

A Research Methodology for Studying What Makes Some Problems Difficult to Solve

ERIC Educational Resources Information Center

Gulacar, Ozcan; Fynewever, Herb

2010-01-01

We present a quantitative model for predicting the level of difficulty subjects will experience with specific problems. The model explicitly accounts for the number of subproblems a problem can be broken into and the difficultly of each subproblem. Although the model builds on previously published models, it is uniquely suited for blending with…

Applications of an exponential finite difference technique

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

Handschuh, R.F.; Keith, T.G. Jr.

1988-07-01

An exponential finite difference scheme first presented by Bhattacharya for one dimensional unsteady heat conduction problems in Cartesian coordinates was extended. The finite difference algorithm developed was used to solve the unsteady diffusion equation in one dimensional cylindrical coordinates and was applied to two and three dimensional conduction problems in Cartesian coordinates. Heat conduction involving variable thermal conductivity was also investigated. The method was used to solve nonlinear partial differential equations in one and two dimensional Cartesian coordinates. Predicted results are compared to exact solutions where available or to results obtained by other numerical methods.

Robust distributed model predictive control of linear systems with structured time-varying uncertainties

NASA Astrophysics Data System (ADS)

Zhang, Langwen; Xie, Wei; Wang, Jingcheng

2017-11-01

In this work, synthesis of robust distributed model predictive control (MPC) is presented for a class of linear systems subject to structured time-varying uncertainties. By decomposing a global system into smaller dimensional subsystems, a set of distributed MPC controllers, instead of a centralised controller, are designed. To ensure the robust stability of the closed-loop system with respect to model uncertainties, distributed state feedback laws are obtained by solving a min-max optimisation problem. The design of robust distributed MPC is then transformed into solving a minimisation optimisation problem with linear matrix inequality constraints. An iterative online algorithm with adjustable maximum iteration is proposed to coordinate the distributed controllers to achieve a global performance. The simulation results show the effectiveness of the proposed robust distributed MPC algorithm.

Adaptive Memory: Ancestral Priorities and the Mnemonic Value of Survival Processing

ERIC Educational Resources Information Center

Nairne, James S.; Pandeirada, Josefa N. S.

2010-01-01

Evolutionary psychologists often propose that humans carry around "stone-age" brains, along with a toolkit of cognitive adaptations designed originally to solve hunter-gatherer problems. This perspective predicts that optimal cognitive performance might sometimes be induced by ancestrally-based problems, those present in ancestral environments,…

Differences in problem-solving between canid populations: Do domestication and lifetime experience affect persistence?

PubMed

Brubaker, Lauren; Dasgupta, Sandipan; Bhattacharjee, Debottam; Bhadra, Anindita; Udell, Monique A R

2017-07-01

Past research has suggested that a variety of factors, phylogenetic and ontogenetic, play a role in how canines behave during problem-solving tasks and the degree to which the presence of a human influences their problem-solving behaviour. While comparisons between socialized wolves and domestic dogs have commonly been used to tease apart these predictive factors, in many cases a single dog population, often pets, have been used for these comparisons. Less is understood about how different populations of dogs may behave when compared with wolves, or with each other, during an independent problem-solving task. This experiment compared the independent persistence of four populations of canines (two groups of pet domestic dogs, a group of free-ranging domestic dogs, and human-socialized wolves) on an independent problem-solving task in the presence of an on looking human. Results showed that wolves persisted the most at the task while free-ranging dogs persisted the least. Free-ranging dogs gazed at the human experimenter for the longest durations during the task. While further research is needed to understand why these differences exist, this study demonstrates that dogs, even those living outside human homes as scavengers, show comparatively low levels of persistence when confronted with a solvable task in the presence of a human as well as significantly greater duration of human-directed gaze when compared with wolves.

Multiobjective optimization of temporal processes.

PubMed

Song, Zhe; Kusiak, Andrew

2010-06-01

This paper presents a dynamic predictive-optimization framework of a nonlinear temporal process. Data-mining (DM) and evolutionary strategy algorithms are integrated in the framework for solving the optimization model. DM algorithms learn dynamic equations from the process data. An evolutionary strategy algorithm is then applied to solve the optimization problem guided by the knowledge extracted by the DM algorithm. The concept presented in this paper is illustrated with the data from a power plant, where the goal is to maximize the boiler efficiency and minimize the limestone consumption. This multiobjective optimization problem can be either transformed into a single-objective optimization problem through preference aggregation approaches or into a Pareto-optimal optimization problem. The computational results have shown the effectiveness of the proposed optimization framework.

Newtonian semiclassical gravity in three ontological quantum theories that solve the measurement problem: Formalisms and empirical predictions

NASA Astrophysics Data System (ADS)

Derakhshani, Maaneli

In this thesis, we consider the implications of solving the quantum measurement problem for the Newtonian description of semiclassical gravity. First we review the formalism of the Newtonian description of semiclassical gravity based on standard quantum mechanics---the Schroedinger-Newton theory---and two well-established predictions that come out of it, namely, gravitational 'cat states' and gravitationally-induced wavepacket collapse. Then we review three quantum theories with 'primitive ontologies' that are well-known known to solve the measurement problem---Schroedinger's many worlds theory, the GRW collapse theory with matter density ontology, and Nelson's stochastic mechanics. We extend the formalisms of these three quantum theories to Newtonian models of semiclassical gravity and evaluate their implications for gravitational cat states and gravitational wavepacket collapse. We find that (1) Newtonian semiclassical gravity based on Schroedinger's many worlds theory is mathematically equivalent to the Schroedinger-Newton theory and makes the same predictions; (2) Newtonian semiclassical gravity based on the GRW theory differs from Schroedinger-Newton only in the use of a stochastic collapse law, but this law allows it to suppress gravitational cat states so as not to be in contradiction with experiment, while allowing for gravitational wavepacket collapse to happen as well; (3) Newtonian semiclassical gravity based on Nelson's stochastic mechanics differs significantly from Schroedinger-Newton, and does not predict gravitational cat states nor gravitational wavepacket collapse. Considering that gravitational cat states are experimentally ruled out, but gravitational wavepacket collapse is testable in the near future, this implies that only the latter two are viable theories of Newtonian semiclassical gravity and that they can be experimentally tested against each other in future molecular interferometry experiments that are anticipated to be capable of testing the gravitational wavepacket collapse prediction.

Best candidates for cognitive treatment of illness perceptions in chronic low back pain: results of a theory-driven predictor study.

PubMed

Siemonsma, Petra C; Stuvie, Ilse; Roorda, Leo D; Vollebregt, Joke A; Lankhorst, Gustaaf J; Lettinga, Ant T

2011-04-01

The aim of this study was to identify treatment-specific predictors of the effectiveness of a method of evidence-based treatment: cognitive treatment of illness perceptions. This study focuses on what treatment works for whom, whereas most prognostic studies focusing on chronic non-specific low back pain rehabilitation aim to reduce the heterogeneity of the population of patients who are suitable for rehabilitation treatment in general. Three treatment-specific predictors were studied in patients with chronic non-specific low back pain receiving cognitive treatment of illness perceptions: a rational approach to problem-solving, discussion skills and verbal skills. Hierarchical linear regression analysis was used to assess their predictive value. Short-term changes in physical activity, measured with the Patient-Specific Functioning List, were the outcome measure for cognitive treatment of illness perceptions effect. A total of 156 patients with chronic non-specific low back pain participated in the study. Rational problem-solving was found to be a significant predictor for the change in physical activity. Discussion skills and verbal skills were non-significant. Rational problem-solving explained 3.9% of the total variance. The rational problem-solving scale results are encouraging, because chronic non-specific low back pain problems are complex by nature and can be influenced by a variety of factors. A minimum score of 44 points on the rational problem-solving scale may assist clinicians in selecting the most appropriate candidates for cognitive treatment of illness perceptions.

Optimistic expectations in early marriage: a resource or vulnerability for adaptive relationship functioning?

PubMed

Neff, Lisa A; Geers, Andrew L

2013-07-01

Do optimistic expectations facilitate or hinder adaptive responses to relationship challenges? Traditionally, optimism has been characterized as a resource that encourages positive coping efforts within relationships. Yet, some work suggests optimism can be a liability, as expecting the best may prevent individuals from taking proactive steps when confronted with difficulties. To reconcile these perspectives, the current article argues that greater attention must be given to the way in which optimistic expectancies are conceptualized. Whereas generalized dispositional optimism may predict constructive responses to relationship difficulties, more focused relationship-specific forms of optimism may predict poor coping responses. A multi-method, longitudinal study of newly married couples confirmed that spouses higher in dispositional optimism (a) reported engaging in more positive problem-solving behaviors on days in which they experienced greater relationship conflict, (b) were observed to display more constructive problem-solving behaviors when discussing important marital issues with their partner in the lab, and (c) experienced fewer declines in marital well-being over the 1st year of marriage. Conversely, spouses higher in relationship-specific optimism (a) reported engaging in fewer constructive problem-solving behaviors on high conflict days, (b) were observed to exhibit worse problem-solving behaviors in the lab-particularly when discussing marital issues of greater importance-and (c) experienced steeper declines in marital well-being over time. All findings held controlling for self-esteem and neuroticism. Together, results suggest that whereas global forms of optimism may represent a relationship asset, specific forms of optimism can place couples at risk for marital deterioration. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Missile Guidance Law Based on Robust Model Predictive Control Using Neural-Network Optimization.

PubMed

Li, Zhijun; Xia, Yuanqing; Su, Chun-Yi; Deng, Jun; Fu, Jun; He, Wei

2015-08-01

In this brief, the utilization of robust model-based predictive control is investigated for the problem of missile interception. Treating the target acceleration as a bounded disturbance, novel guidance law using model predictive control is developed by incorporating missile inside constraints. The combined model predictive approach could be transformed as a constrained quadratic programming (QP) problem, which may be solved using a linear variational inequality-based primal-dual neural network over a finite receding horizon. Online solutions to multiple parametric QP problems are used so that constrained optimal control decisions can be made in real time. Simulation studies are conducted to illustrate the effectiveness and performance of the proposed guidance control law for missile interception.

Hippocampal-neocortical functional reorganization underlies children's cognitive development

PubMed Central

Qin, Shaozheng; Cho, Soohyun; Chen, Tianwen; Rosenberg-Lee, Miriam; Geary, David C.; Menon, Vinod

2014-01-01

The importance of the hippocampal system for rapid learning and memory is well recognized, but its contributions to a cardinal feature of children's cognitive development – the transition from procedure-based to memory-based problem solving strategies – are unknown. Here we show that the hippocampal system is pivotal to this strategic transition. Longitudinal fMRI in children, ages 7 to 9, revealed that the transition from use of counting to memory-based retrieval parallels increased hippocampal and decreased prefrontal-parietal engagement during arithmetic problem solving. Critically, longitudinal improvements in retrieval strategy use were predicted by increased hippocampal-neocortical functional connectivity. Beyond childhood, retrieval strategy use continued to improve through adolescence into adulthood, and was associated with decreased activation but more stable inter-problem representations in the hippocampus. Our findings provide novel insights into the dynamic role of the hippocampus in the maturation of memory-based problem solving, and establish a critical link between hippocampal-neocortical reorganization and children's cognitive development. PMID:25129076

Wolves, dogs, rearing and reinforcement: complex interactions underlying species differences in training and problem-solving performance.

PubMed

Frank, Harry

2011-11-01

Frank and Frank et al. (1982-1987) administered a series of age-graded training and problem-solving tasks to samples of Eastern timber wolf (C. lupus lycaon) and Alaskan Malamute (C. familiaris) pups to test Frank's (Zeitschrift für Tierpsychologie 53:389-399, 1980) model of the evolution of information processing under conditions of natural and artificial selection. Results confirmed the model's prediction that wolves should perform better than dogs on problem-solving tasks and that dogs should perform better than wolves on training tasks. Further data collected at the University of Connecticut in 1983 revealed a more complex and refined picture, indicating that species differences can be mediated by a number of factors influencing wolf performance, including socialization regimen (hand-rearing vs. mother-rearing), interactive effects of socialization on the efficacy of both rewards and punishments, and the flexibility to select learning strategies that experimenters might not anticipate.

The emergence of the Activity Reduces Conflict Associated Strain (ARCAS) model: a test of a conditional mediation model of workplace conflict and employee strain.

PubMed

Dijkstra, Maria T M; Beersma, Bianca; Cornelissen, Roosmarijn A W M

2012-07-01

To test and extend the emerging Activity Reduces Conflict-Associated Strain (ARCAS) model, we predicted that the relationship between task conflict and employee strain would be weakened to the extent that people experience high organization-based self-esteem (OBSE). A survey among Dutch employees demonstrated that, consistent with the model, the conflict-employee strain relationship was weaker the higher employees' OBSE and the more they engaged in active problem-solving conflict management. Our data also revealed that higher levels of OBSE were related to more problem-solving conflict management. Moreover, consistent with the ARCAS model, we could confirm a conditional mediation model in which organization-based self-esteem through its relationship with problem-solving conflict management weakened the relationship between task conflict and employee strain. Potential applications of the results are discussed.

Cooperative airframe/propulsion control for supersonic cruise aircraft

NASA Technical Reports Server (NTRS)

Schweikhard, W. G.; Berry, D. T.

1974-01-01

Interactions between propulsion systems and flight controls have emerged as a major control problem on supersonic cruise aircraft. This paper describes the nature and causes of these interactions and the approaches to predicting and solving the problem. Integration of propulsion and flight control systems appears to be the most promising solution if the interaction effects can be adequately predicted early in the vehicle design. Significant performance, stability, and control improvements may be realized from a cooperative control system.

Schizophrenia, narrative, and neurocognition: The utility of life-stories in understanding social problem-solving skills.

PubMed

Moe, Aubrey M; Breitborde, Nicholas J K; Bourassa, Kyle J; Gallagher, Colin J; Shakeel, Mohammed K; Docherty, Nancy M

2018-06-01

Schizophrenia researchers have focused on phenomenological aspects of the disorder to better understand its underlying nature. In particular, development of personal narratives-that is, the complexity with which people form, organize, and articulate their "life stories"-has recently been investigated in individuals with schizophrenia. However, less is known about how aspects of narrative relate to indicators of neurocognitive and social functioning. The objective of the present study was to investigate the association of linguistic complexity of life-story narratives to measures of cognitive and social problem-solving abilities among people with schizophrenia. Thirty-two individuals with a diagnosis of schizophrenia completed a research battery consisting of clinical interviews, a life-story narrative, neurocognitive testing, and a measure assessing multiple aspects of social problem solving. Narrative interviews were assessed for linguistic complexity using computerized technology. The results indicate differential relationships of linguistic complexity and neurocognition to domains of social problem-solving skills. More specifically, although neurocognition predicted how well one could both describe and enact a solution to a social problem, linguistic complexity alone was associated with accurately recognizing that a social problem had occurred. In addition, linguistic complexity appears to be a cognitive factor that is discernible from other broader measures of neurocognition. Linguistic complexity may be more relevant in understanding earlier steps of the social problem-solving process than more traditional, broad measures of cognition, and thus is relevant in conceptualizing treatment targets. These findings also support the relevance of developing narrative-focused psychotherapies. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Fictitious domain method for fully resolved reacting gas-solid flow simulation

NASA Astrophysics Data System (ADS)

Zhang, Longhui; Liu, Kai; You, Changfu

2015-10-01

Fully resolved simulation (FRS) for gas-solid multiphase flow considers solid objects as finite sized regions in flow fields and their behaviours are predicted by solving equations in both fluid and solid regions directly. Fixed mesh numerical methods, such as fictitious domain method, are preferred in solving FRS problems and have been widely researched. However, for reacting gas-solid flows no suitable fictitious domain numerical method has been developed. This work presents a new fictitious domain finite element method for FRS of reacting particulate flows. Low Mach number reacting flow governing equations are solved sequentially on a regular background mesh. Particles are immersed in the mesh and driven by their surface forces and torques integrated on immersed interfaces. Additional treatments on energy and surface reactions are developed. Several numerical test cases validated the method and a burning carbon particles array falling simulation proved the capability for solving moving reacting particle cluster problems.

Gravity with free initial conditions: A solution to the cosmological constant problem testable by CMB B -mode polarization

NASA Astrophysics Data System (ADS)

Totani, Tomonori

2017-10-01

In standard general relativity the universe cannot be started with arbitrary initial conditions, because four of the ten components of the Einstein's field equations (EFE) are constraints on initial conditions. In the previous work it was proposed to extend the gravity theory to allow free initial conditions, with a motivation to solve the cosmological constant problem. This was done by setting four constraints on metric variations in the action principle, which is reasonable because the gravity's physical degrees of freedom are at most six. However, there are two problems about this theory; the three constraints in addition to the unimodular condition were introduced without clear physical meanings, and the flat Minkowski spacetime is unstable against perturbations. Here a new set of gravitational field equations is derived by replacing the three constraints with new ones requiring that geodesic paths remain geodesic against metric variations. The instability problem is then naturally solved. Implications for the cosmological constant Λ are unchanged; the theory converges into EFE with nonzero Λ by inflation, but Λ varies on scales much larger than the present Hubble horizon. Then galaxies are formed only in small Λ regions, and the cosmological constant problem is solved by the anthropic argument. Because of the increased degrees of freedom in metric dynamics, the theory predicts new non-oscillatory modes of metric anisotropy generated by quantum fluctuation during inflation, and CMB B -mode polarization would be observed differently from the standard predictions by general relativity.

Adolescents' and Best Friend's Depressive Symptoms and Conflict Management: Intraindividual and Interpersonal Processes Over Time.

PubMed

Boersma-van Dam, Elise; Hale, Bill; Koot, Hans; Meeus, Wim; Branje, Susan

2016-12-12

This 6-year longitudinal study examined the relation between 3 conflict management styles (i.e., problem solving, conflict engagement, and compliance) and depressive symptoms in adolescent-best friend relationships. Participants were 479 Dutch adolescents and their best friend who reported annually on depressive symptoms and conflict management styles toward each other. Bidirectional effects between conflict management styles and depressive symptoms were studied both within adolescents (intraindividual) and between adolescent best friends (interpersonal). A positive interpersonal effect of depressive symptoms of one dyad member on depressive symptoms of the other member was found. Similarly, higher positive problem solving and conflict engagement of one dyad member predicted respectively higher problem solving and conflict engagement of the other dyad member. Adolescents who reported more depressive symptoms reported more conflict engagement and compliance over time. In addition, for boys, higher levels of depressive symptoms of one dyad member were related to more problem solving by the other member over time. The current study contributed to the literature by showing that depressive symptoms and conflict management are related constructs in adolescents and that both intrapersonal and interpersonal processes contribute to this relation.

Calculation and word problem-solving skills in primary grades - Impact of cognitive abilities and longitudinal interrelations with task-persistent behaviour.

PubMed

Jõgi, Anna-Liisa; Kikas, Eve

2016-06-01

Primary school math skills form a basis for academic success down the road. Different math skills have different antecedents and there is a reason to believe that more complex math tasks require better self-regulation. The study aimed to investigate longitudinal interrelations of calculation and problem-solving skills, and task-persistent behaviour in Grade 1 and Grade 3, and the effect of non-verbal intelligence, linguistic abilities, and executive functioning on math skills and task persistence. Participants were 864 students (52.3% boys) from 33 different schools in Estonia. Students were tested twice - at the end of Grade1 and at the end of Grade 3. Calculation and problem-solving skills, and teacher-rated task-persistent behaviour were measured at both time points. Non-verbal intelligence, linguistic abilities, and executive functioning were measured in Grade 1. Cross-lagged structural equation modelling indicated that calculation skills depend on previous math skills and linguistic abilities, while problem-solving skills require also non-verbal intelligence, executive functioning, and task persistence. Task-persistent behaviour in Grade 3 was predicted by previous problem-solving skills, linguistic abilities, and executive functioning. Gender and mother's educational level were added as covariates. The findings indicate that math skills and self-regulation are strongly related in primary grades and that solving complex tasks requires executive functioning and task persistence from children. Findings support the idea that instructional practices might benefit from supporting self-regulation in order to gain domain-specific, complex skill achievement. © 2015 The British Psychological Society.

Modifications of the PCPT method for HJB equations

NASA Astrophysics Data System (ADS)

Kossaczký, I.; Ehrhardt, M.; Günther, M.

2016-10-01

In this paper we will revisit the modification of the piecewise constant policy timestepping (PCPT) method for solving Hamilton-Jacobi-Bellman (HJB) equations. This modification is called piecewise predicted policy timestepping (PPPT) method and if properly used, it may be significantly faster. We will quickly recapitulate the algorithms of PCPT, PPPT methods and of the classical implicit method and apply them on a passport option pricing problem with non-standard payoff. We will present modifications needed to solve this problem effectively with the PPPT method and compare the performance with the PCPT method and the classical implicit method.

The min-conflicts heuristic: Experimental and theoretical results

NASA Technical Reports Server (NTRS)

Minton, Steven; Philips, Andrew B.; Johnston, Mark D.; Laird, Philip

1991-01-01

This paper describes a simple heuristic method for solving large-scale constraint satisfaction and scheduling problems. Given an initial assignment for the variables in a problem, the method operates by searching through the space of possible repairs. The search is guided by an ordering heuristic, the min-conflicts heuristic, that attempts to minimize the number of constraint violations after each step. We demonstrate empirically that the method performs orders of magnitude better than traditional backtracking techniques on certain standard problems. For example, the one million queens problem can be solved rapidly using our approach. We also describe practical scheduling applications where the method has been successfully applied. A theoretical analysis is presented to explain why the method works so well on certain types of problems and to predict when it is likely to be most effective.

Predicting flow at work: investigating the activities and job characteristics that predict flow states at work.

PubMed

Nielsen, Karina; Cleal, Bryan

2010-04-01

Flow (a state of consciousness where people become totally immersed in an activity and enjoy it intensely) has been identified as a desirable state with positive effects for employee well-being and innovation at work. Flow has been studied using both questionnaires and Experience Sampling Method (ESM). In this study, we used a newly developed 9-item flow scale in an ESM study combined with a questionnaire to examine the predictors of flow at two levels: the activities (brainstorming, planning, problem solving and evaluation) associated with transient flow states and the more stable job characteristics (role clarity, influence and cognitive demands). Participants were 58 line managers from two companies in Denmark; a private accountancy firm and a public elder care organization. We found that line managers in elder care experienced flow more often than accountancy line managers, and activities such as planning, problem solving, and evaluation predicted transient flow states. The more stable job characteristics included in this study were not, however, found to predict flow at work. Copyright 2010 APA, all rights reserved.

Distributed Method to Optimal Profile Descent

NASA Astrophysics Data System (ADS)

Kim, Geun I.

Current ground automation tools for Optimal Profile Descent (OPD) procedures utilize path stretching and speed profile change to maintain proper merging and spacing requirements at high traffic terminal area. However, low predictability of aircraft's vertical profile and path deviation during decent add uncertainty to computing estimated time of arrival, a key information that enables the ground control center to manage airspace traffic effectively. This paper uses an OPD procedure that is based on a constant flight path angle to increase the predictability of the vertical profile and defines an OPD optimization problem that uses both path stretching and speed profile change while largely maintaining the original OPD procedure. This problem minimizes the cumulative cost of performing OPD procedures for a group of aircraft by assigning a time cost function to each aircraft and a separation cost function to a pair of aircraft. The OPD optimization problem is then solved in a decentralized manner using dual decomposition techniques under inter-aircraft ADS-B mechanism. This method divides the optimization problem into more manageable sub-problems which are then distributed to the group of aircraft. Each aircraft solves its assigned sub-problem and communicate the solutions to other aircraft in an iterative process until an optimal solution is achieved thus decentralizing the computation of the optimization problem.

An Integrated Model of Suicidal Ideation in Transcultural Populations of Chinese Adolescents.

PubMed

Leung, Cyrus L K; Kwok, Sylvia Y C L; Ling, Chloe C Y

2016-07-01

This study tested the model of suicidal ideation, incorporating family and personal factors to predict suicidal ideation with hopelessness as a mediating factor in the Hong Kong sample, to a sample in Shanghai. Using MGSEM, the study aims to investigate the personal correlates and the family correlates of suicidal ideation in Hong Kong and Shanghai adolescents. We integrated the family ecological and diathesis-stress-hopelessness models of suicidal ideation in connecting the correlates. A cross-sectional design was used. The full model achieved metric invariance and partial path-loading invariance. Family functioning and social problem solving negatively predicted hopelessness or suicidal ideation in both the Hong Kong and Shanghai adolescents. The results supported an integrative approach in facilitating parent-adolescent communication and strengthening family functioning, and reducing the use of negative social problem-solving styles in adolescent suicide prevention.

A framework for qualitative reasoning about solid objects

NASA Technical Reports Server (NTRS)

Davis, E.

1987-01-01

Predicting the behavior of a qualitatively described system of solid objects requires a combination of geometrical, temporal, and physical reasoning. Methods based upon formulating and solving differential equations are not adequate for robust prediction, since the behavior of a system over extended time may be much simpler than its behavior over local time. A first-order logic, in which one can state simple physical problems and derive their solution deductively, without recourse to solving the differential equations, is discussed. This logic is substantially more expressive and powerful than any previous AI representational system in this domain.

Living Well with Living Wills: Application of Protection Motivation Theory to Living Wills Among Older Caucasian and African American Adults

PubMed Central

ALLEN, REBECCA S.; PHILLIPS, LAURA L.; PEKMEZI, DOROTHY; CROWTHER, MARTHA R.; PRENTICE-DUNN, STEVEN

2009-01-01

Using protection motivation theory, we examined racial differences in intent to complete a living will, rational problem solving (e.g., information seeking), and maladaptive coping responses (i.e., wishful thinking) to a health crisis. Sixty healthy, older adults without living wills responded to written vignettes, including information about living wills as an effective coping mechanism to avoid a health crisis. Use of adaptive coping responses predicted intent to execute a living will. A significant race-by-threat interaction predicted use of rational problem solving, with Caucasians more likely to seek information in response to perceived threat in comparison with African Americans. A significant race-by-adaptive-coping interaction predicted maladaptive coping, indicating that Caucasians were more variable in their maladaptive responses. The effectiveness of health care messages regarding living wills for older adults may be enhanced by focusing on racial differences in response to perceived health threat and perceived adaptive coping information. PMID:19337566

Living Well with Living Wills: Application of Protection Motivation Theory to Living Wills Among Older Caucasian and African American Adults.

PubMed

Allen, Rebecca S; Phillips, Laura L; Pekmezi, Dorothy; Crowther, Martha R; Prentice-Dunn, Steven

2009-01-01

Using protection motivation theory, we examined racial differences in intent to complete a living will, rational problem solving (e.g., information seeking), and maladaptive coping responses (i.e., wishful thinking) to a health crisis. Sixty healthy, older adults without living wills responded to written vignettes, including information about living wills as an effective coping mechanism to avoid a health crisis. Use of adaptive coping responses predicted intent to execute a living will. A significant race-by-threat interaction predicted use of rational problem solving, with Caucasians more likely to seek information in response to perceived threat in comparison with African Americans. A significant race-by-adaptive-coping interaction predicted maladaptive coping, indicating that Caucasians were more variable in their maladaptive responses. The effectiveness of health care messages regarding living wills for older adults may be enhanced by focusing on racial differences in response to perceived health threat and perceived adaptive coping information.

Predictors of response to Systems Training for Emotional Predictability and Problem Solving (STEPPS) for borderline personality disorder: an exploratory study.

PubMed

Black, D W; Allen, J; St John, D; Pfohl, B; McCormick, B; Blum, N

2009-07-01

Few predictors of treatment outcome or early discontinuation have been identified in persons with borderline personality disorder (BPD). The aim of the study was to examine the relationship between baseline clinical variables and treatment response and early discontinuation in a randomized controlled trial of System Training for Emotional Predictability and Problem Solving, a new cognitive group treatment. Improvement was rated using the Zanarini Rating Scale for BPD, the Clinical Global Impression Scale, the Global Assessment Scale and the Beck Depression Inventory. Subjects were assessed during the 20 week trial and a 1-year follow-up. Higher baseline severity was associated with greater improvement in global functioning and BPD-related symptoms. Higher impulsivity was predictive of early discontinuation. Optimal improvement was associated with attending > or = 15 sessions. Subjects likely to improve have the more severe BPD symptoms at baseline, while high levels of impulsivity are associated with early discontinuation.

The nonlinear dynamics of family problem solving in adolescence: the predictive validity of a peaceful resolution attractor.

PubMed

Dishion, Thomas J; Forgatch, Marion; Van Ryzin, Mark; Winter, Charlotte

2012-07-01

In this study we examined the videotaped family interactions of a community sample of adolescents and their parents. Youths were assessed in early to late adolescence on their levels of antisocial behavior. At age 16-17, youths and their parents were videotaped interacting while completing a variety of tasks, including family problem solving. The interactions were coded and compared for three developmental patterns of antisocial behavior: early onset, persistent; adolescence onset; and typically developing. The mean duration of conflict bouts was the only interaction pattern that discriminated the 3 groups. In the prediction of future antisocial behavior, parent and youth reports of transition entropy and conflict resolution interacted to account for antisocial behavior at age 18-19. Families with low entropy and peaceful resolutions predicted low levels of youth antisocial behavior at age 18-19. These findings suggest the need to study both attractors and repellers to understand family dynamics associated with health and social and emotional development.

The Nonlinear Dynamics of Family Problem Solving in Adolescence: The Predictive Validity of a Peaceful Resolution Attractor

PubMed Central

Dishion, Thomas J.; Forgatch, Marion; Van Ryzin, Mark; Winter, Charlotte

2012-01-01

In this study we examined the videotaped family interactions of a community sample of adolescents and their parents. Youths were assessed in early to late adolescence on their levels of antisocial behavior. At age 16–17, youths and their parents were videotaped interacting while completing a variety of tasks, including family problem solving. The interactions were coded and compared for 3 developmental patterns of antisocial behavior: early onset, persistent; adolescence onset; and typically developing. The mean duration of conflict bouts was the only interaction pattern that discriminated the 3 groups. In the prediction of future antisocial behavior, parent and youth reports of transition entropy and conflict resolution interacted to account for antisocial behavior at age 18–19. Families with low entropy and peaceful resolutions predicted low levels of youth antisocial behavior at age 18–19. These findings suggest the need to study both attractors and repellers to understand family dynamics associated with health and social and emotional development. PMID:22695152

Perm State University HPC-hardware and software services: capabilities for aircraft engine aeroacoustics problems solving

NASA Astrophysics Data System (ADS)

Demenev, A. G.

2018-02-01

The present work is devoted to analyze high-performance computing (HPC) infrastructure capabilities for aircraft engine aeroacoustics problems solving at Perm State University. We explore here the ability to develop new computational aeroacoustics methods/solvers for computer-aided engineering (CAE) systems to handle complicated industrial problems of engine noise prediction. Leading aircraft engine engineering company, including “UEC-Aviadvigatel” JSC (our industrial partners in Perm, Russia), require that methods/solvers to optimize geometry of aircraft engine for fan noise reduction. We analysed Perm State University HPC-hardware resources and software services to use efficiently. The performed results demonstrate that Perm State University HPC-infrastructure are mature enough to face out industrial-like problems of development CAE-system with HPC-method and CFD-solvers.

Predicting the Future as Bayesian Inference: People Combine Prior Knowledge with Observations when Estimating Duration and Extent

ERIC Educational Resources Information Center

Griffiths, Thomas L.; Tenenbaum, Joshua B.

2011-01-01

Predicting the future is a basic problem that people have to solve every day and a component of planning, decision making, memory, and causal reasoning. In this article, we present 5 experiments testing a Bayesian model of predicting the duration or extent of phenomena from their current state. This Bayesian model indicates how people should…

Reduction of the dimension of neural network models in problems of pattern recognition and forecasting

NASA Astrophysics Data System (ADS)

Nasertdinova, A. D.; Bochkarev, V. V.

2017-11-01

Deep neural networks with a large number of parameters are a powerful tool for solving problems of pattern recognition, prediction and classification. Nevertheless, overfitting remains a serious problem in the use of such networks. A method of solving the problem of overfitting is proposed in this article. This method is based on reducing the number of independent parameters of a neural network model using the principal component analysis, and can be implemented using existing libraries of neural computing. The algorithm was tested on the problem of recognition of handwritten symbols from the MNIST database, as well as on the task of predicting time series (rows of the average monthly number of sunspots and series of the Lorentz system were used). It is shown that the application of the principal component analysis enables reducing the number of parameters of the neural network model when the results are good. The average error rate for the recognition of handwritten figures from the MNIST database was 1.12% (which is comparable to the results obtained using the "Deep training" methods), while the number of parameters of the neural network can be reduced to 130 times.

Cognition-emotion interactions: patterns of change and implications for math problem solving

PubMed Central

Trezise, Kelly; Reeve, Robert A.

2014-01-01

Surprisingly little is known about whether relationships between cognitive and emotional states remain stable or change over time, or how different patterns of stability and/or change in the relationships affect problem solving abilities. Nevertheless, cross-sectional studies show that anxiety/worry may reduce working memory (WM) resources, and the ability to minimize the effects anxiety/worry is higher in individuals with greater WM capacity. To investigate the patterns of stability and/or change in cognition-emotion relations over time and their implications for problem solving, 126 14-year-olds’ algebraic WM and worry levels were assessed twice in a single day before completing an algebraic math problem solving test. We used latent transition analysis to identify stability/change in cognition-emotion relations, which yielded a six subgroup solution. Subgroups varied in WM capacity, worry, and stability/change relationships. Among the subgroups, we identified a high WM/low worry subgroup that remained stable over time and a high WM/high worry, and a moderate WM/low worry subgroup that changed to low WM subgroups over time. Patterns of stability/change in subgroup membership predicted algebraic test results. The stable high WM/low worry subgroup performed best and the low WM capacity-high worry “unstable across time” subgroup performed worst. The findings highlight the importance of assessing variations in cognition-emotion relationships over time (rather than assessing cognition or emotion states alone) to account for differences in problem solving abilities. PMID:25132830

Model Prediction Results for 2007 Ultrasonic Benchmark Problems

NASA Astrophysics Data System (ADS)

Kim, Hak-Joon; Song, Sung-Jin

2008-02-01

The World Federation of NDE Centers (WFNDEC) has addressed two types of problems for the 2007 ultrasonic benchmark problems: prediction of side-drilled hole responses with 45° and 60° refracted shear waves, and effects of surface curvatures on the ultrasonic responses of flat-bottomed hole. To solve this year's ultrasonic benchmark problems, we applied multi-Gaussian beam models for calculation of ultrasonic beam fields and the Kirchhoff approximation and the separation of variables method for calculation of far-field scattering amplitudes of flat-bottomed holes and side-drilled holes respectively In this paper, we present comparison results of model predictions to experiments for side-drilled holes and discuss effect of interface curvatures on ultrasonic responses by comparison of peak-to-peak amplitudes of flat-bottomed hole responses with different sizes and interface curvatures.

Closed loop problems in biomechanics. Part II--an optimization approach.

PubMed

Vaughan, C L; Hay, J G; Andrews, J G

1982-01-01

A closed loop problem in biomechanics may be defined as a problem in which there are one or more closed loops formed by the human body in contact with itself or with an external system. Under certain conditions the problem is indeterminate--the unknown forces and torques outnumber the equations. Force transducing devices, which would help solve this problem, have serious drawbacks, and existing methods are inaccurate and non-general. The purposes of the present paper are (1) to develop a general procedure for solving closed loop problems; (2) to illustrate the application of the procedure; and (3) to examine the validity of the procedure. A mathematical optimization approach is applied to the solution of three different closed loop problems--walking up stairs, vertical jumping and cartwheeling. The following conclusions are drawn: (1) the method described is reasonably successful for predicting horizontal and vertical reaction forces at the distal segments although problems exist for predicting the points of application of these forces; (2) the results provide some support for the notion that the human neuromuscular mechanism attempts to minimize the joint torques and thus, to a certain degree, the amount of muscular effort; (3) in the validation procedure it is desirable to have a force device for each of the distal segments in contact with a fixed external system; and (4) the method is sufficiently general to be applied to all classes of closed loop problems.

Learning to forget: continual prediction with LSTM.

PubMed

Gers, F A; Schmidhuber, J; Cummins, F

2000-10-01

Long short-term memory (LSTM; Hochreiter & Schmidhuber, 1997) can solve numerous tasks not solvable by previous learning algorithms for recurrent neural networks (RNNs). We identify a weakness of LSTM networks processing continual input streams that are not a priori segmented into subsequences with explicitly marked ends at which the network's internal state could be reset. Without resets, the state may grow indefinitely and eventually cause the network to break down. Our remedy is a novel, adaptive "forget gate" that enables an LSTM cell to learn to reset itself at appropriate times, thus releasing internal resources. We review illustrative benchmark problems on which standard LSTM outperforms other RNN algorithms. All algorithms (including LSTM) fail to solve continual versions of these problems. LSTM with forget gates, however, easily solves them, and in an elegant way.

Observed Parenting Behavior with Teens: Measurement Invariance and Predictive Validity Across Race

PubMed Central

Skinner, Martie L.; MacKenzie, Elizabeth P.; Haggerty, Kevin P.; Hill, Karl G.; Roberson, Kendra C.

2011-01-01

Previous reports supporting measurement equality between European American and African American families have often focused on self-reported risk factors or observed parent behavior with young children. This study examines equality of measurement of observer ratings of parenting behavior with adolescents during structured tasks; mean levels of observed parenting; and predictive validity of teen self-reports of antisocial behaviors and beliefs using a sample of 163 African American and 168 European American families. Multiple-group confirmatory factor analyses supported measurement invariance across ethnic groups for 4 measures of observed parenting behavior: prosocial rewards, psychological costs, antisocial rewards, and problem solving. Some mean-level differences were found: African American parents exhibited lower levels of prosocial rewards, higher levels of psychological costs, and lower problem solving when compared to European Americans. No significant mean difference was found in rewards for antisocial behavior. Multigroup structural equation models suggested comparable relationships across race (predictive validity) between parenting constructs and youth antisocial constructs (i.e., drug initiation, positive drug attitudes, antisocial attitudes, problem behaviors) in all but one of the tested relationships. This study adds to existing evidence that family-based interventions targeting parenting behaviors can be generalized to African American families. PMID:21787057

Prediction of Sea Surface Temperature Using Long Short-Term Memory

NASA Astrophysics Data System (ADS)

Zhang, Qin; Wang, Hui; Dong, Junyu; Zhong, Guoqiang; Sun, Xin

2017-10-01

This letter adopts long short-term memory(LSTM) to predict sea surface temperature(SST), which is the first attempt, to our knowledge, to use recurrent neural network to solve the problem of SST prediction, and to make one week and one month daily prediction. We formulate the SST prediction problem as a time series regression problem. LSTM is a special kind of recurrent neural network, which introduces gate mechanism into vanilla RNN to prevent the vanished or exploding gradient problem. It has strong ability to model the temporal relationship of time series data and can handle the long-term dependency problem well. The proposed network architecture is composed of two kinds of layers: LSTM layer and full-connected dense layer. LSTM layer is utilized to model the time series relationship. Full-connected layer is utilized to map the output of LSTM layer to a final prediction. We explore the optimal setting of this architecture by experiments and report the accuracy of coastal seas of China to confirm the effectiveness of the proposed method. In addition, we also show its online updated characteristics.

Effects of topiramate on language functions in newly diagnosed pediatric epileptic patients.

PubMed

Kim, Sun Jun; Kim, Moon Yeon; Choi, Yoon Mi; Song, Mi Kyoung

2014-09-01

The aim of this study was to characterize the effects of topiramate on language functions in newly diagnosed pediatric epileptic patients. Thirty-eight newly diagnosed epileptic patients were assessed using standard language tests. Data were collected before and after beginning topiramate during which time a monotherapy treatment regimen was maintained. Language tests included the Test of Language Problem Solving Abilities, a Korean version of the Peabody Picture Vocabulary Test. We used language tests in the Korean version because all the patients were spoken Korean exclusively in their families. All the language parameters of Test of Language Problem Solving Abilities worsened after initiation of topiramate (determine cause, 13.2 ± 4.8 to 11.2 ± 4.3; problem solving, 14.8 ± 6.0 to 12.8 ± 5.0; predicting, 9.8 ± 3.6 to 8.8 ± 4.6). Patients given topiramate exhibited a shortened mean length of utterance in words during response (determine cause, 4.8 ± 0.9 to 4.3 ± 0.7; making inference, 4.5 ± 0.8 to 4.1 ± 1.1; predicting, 5.2 ± 1.0 to 4.7 ± 0.6; P < 0.05), provided ambiguous answers during the testing, exhibited difficulty in selecting appropriate words, took more time to provide answers, and used incorrect grammar. However, there were no statistically significant changes in the receptive language of patients after taking topiramate (95.4 ± 20.4 to 100.8 ± 19.1). Our data suggest that topiramate may have negative effects on problem-solving abilities in children. We recommend performing language tests should be considered in children being treated with topiramate. Copyright © 2014 Elsevier Inc. All rights reserved.

Self-Regulation and Executive Functioning as Related to Survival in Motor Neuron Disease: Preliminary Findings.

PubMed

Garcia-Willingham, Natasha E; Roach, Abbey R; Kasarskis, Edward J; Segerstrom, Suzanne C

2018-05-16

Disease progression varies widely among patients with motor neuron disease (MND). Patients with MND and coexisting dementia have shorter survival. However, implications of mild cognitive and behavioral difficulties are unclear. The present study examined the relative contribution of executive functioning and self-regulation difficulties on survival over a 6-year period among patients with MND, who scored largely within normal limits on cognitive and behavioral indices. Patients with MND (N=37, age=59.97±11.57, 46% female) completed the Wisconsin Card Sorting Task (WCST) as an executive functioning perseveration index. The Behavior Rating Inventory of Executive Functions (BRIEF-A) was used as a behavioral measure of self-regulation in two subdomains self-regulatory behavior (Behavioral Regulation) and self-regulatory problem-solving (Metacognition). Cox proportional hazard regression analyses were used. In total, 23 patients died during follow-up. In Cox proportional hazard regressions adjusted for a priori covariates, each 10-point T-score increment in patient-reported BRIEF-A self-regulatory behavior and problem-solving difficulties increased mortality risk by 94% and103%, respectively (adjusted HR=1.94, 95% CI [1.07, 3.52]; adjusted HR=2.03, 95% CI [1.19, 3.48]). In sensitivity analyses, patient-reported self-regulatory problem-solving remained significant independent of disease severity and a priori covariates (adjusted HR=1.68, 95% CI [1.01, 2.78], though the predictive value of self-regulatory behavior was attenuated in adjusted models (HR=1.67, 95% CI [0.85, 3.27). Caregiver-reported BRIEF-A ratings of patients and WCST perseverative errors did not significantly predict survival. Preliminary evidence suggests patient-reported self-regulatory problem-solving difficulties indicate poorer prognosis in MND. Further research is needed to uncover mechanisms that negatively affect patient survival.

Probabilities and Predictions: Modeling the Development of Scientific Problem-Solving Skills

ERIC Educational Resources Information Center

Stevens, Ron; Johnson, David F.; Soller, Amy

2005-01-01

The IMMEX (Interactive Multi-Media Exercises) Web-based problem set platform enables the online delivery of complex, multimedia simulations, the rapid collection of student performance data, and has already been used in several genetic simulations. The next step is the use of these data to understand and improve student learning in a formative…

Heat-Energy Analysis for Solar Receivers

NASA Technical Reports Server (NTRS)

Lansing, F. L.

1982-01-01

Heat-energy analysis program (HEAP) solves general heat-transfer problems, with some specific features that are "custom made" for analyzing solar receivers. Can be utilized not only to predict receiver performance under varying solar flux, ambient temperature and local heat-transfer rates but also to detect locations of hotspots and metallurgical difficulties and to predict performance sensitivity of neighboring component parameters.

The Minimal Control Principle Predicts Strategy Shifts in the Abstract Decision Making Task

ERIC Educational Resources Information Center

Taatgen, Niels A.

2011-01-01

The minimal control principle (Taatgen, 2007) predicts that people strive for problem-solving strategies that require as few internal control states as possible. In an experiment with the Abstract Decision Making task (ADM task; Joslyn & Hunt, 1998) the reward structure was manipulated to make either a low-control strategy or a high-strategy…

Contingencies in Mother-Child Teaching Interactions and Behavioral Regulation and Dysregulation in Early Childhood

ERIC Educational Resources Information Center

Lunkenheimer, Erika S.; Kemp, Christine J.; Albrecht, Erin C.

2013-01-01

Predictable patterns in early parent-child interactions may help lay the foundation for how children learn to self-regulate. The present study examined contingencies between maternal teaching and directives and child compliance in mother-child problem-solving interactions at age 3.5 and whether they predicted children's behavioral regulation and…

Fan noise prediction assessment

NASA Technical Reports Server (NTRS)

Bent, Paul H.

1995-01-01

This report is an evaluation of two techniques for predicting the fan noise radiation from engine nacelles. The first is a relatively computational intensive finite element technique. The code is named ARC, an abbreviation of Acoustic Radiation Code, and was developed by Eversman. This is actually a suite of software that first generates a grid around the nacelle, then solves for the potential flowfield, and finally solves the acoustic radiation problem. The second approach is an analytical technique requiring minimal computational effort. This is termed the cutoff ratio technique and was developed by Rice. Details of the duct geometry, such as the hub-to-tip ratio and Mach number of the flow in the duct, and modal content of the duct noise are required for proper prediction.

Analysis of problem solving on project based learning with resource based learning approach computer-aided program

NASA Astrophysics Data System (ADS)

Kuncoro, K. S.; Junaedi, I.; Dwijanto

2018-03-01

This study aimed to reveal the effectiveness of Project Based Learning with Resource Based Learning approach computer-aided program and analyzed problem-solving abilities in terms of problem-solving steps based on Polya stages. The research method used was mixed method with sequential explanatory design. The subject of this research was the students of math semester 4. The results showed that the S-TPS (Strong Top Problem Solving) and W-TPS (Weak Top Problem Solving) had good problem-solving abilities in each problem-solving indicator. The problem-solving ability of S-MPS (Strong Middle Problem Solving) and (Weak Middle Problem Solving) in each indicator was good. The subject of S-BPS (Strong Bottom Problem Solving) had a difficulty in solving the problem with computer program, less precise in writing the final conclusion and could not reflect the problem-solving process using Polya’s step. While the Subject of W-BPS (Weak Bottom Problem Solving) had not been able to meet almost all the indicators of problem-solving. The subject of W-BPS could not precisely made the initial table of completion so that the completion phase with Polya’s step was constrained.

Research at USAFA 2011

DTIC Science & Technology

2011-01-01

field repair technique for enamel -coated steel used in reinforcing concrete structures. In addition to solving real problems, these efforts provide...projects are varied and range from designing and validating repairs, performing residual life analysis, augmenting the current crack growth prediction

Brain organization underlying superior mathematical abilities in children with autism.

PubMed

Iuculano, Teresa; Rosenberg-Lee, Miriam; Supekar, Kaustubh; Lynch, Charles J; Khouzam, Amirah; Phillips, Jennifer; Uddin, Lucina Q; Menon, Vinod

2014-02-01

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by social and communication deficits. While such deficits have been the focus of most research, recent evidence suggests that individuals with ASD may exhibit cognitive strengths in domains such as mathematics. Cognitive assessments and functional brain imaging were used to investigate mathematical abilities in 18 children with ASD and 18 age-, gender-, and IQ-matched typically developing (TD) children. Multivariate classification and regression analyses were used to investigate whether brain activity patterns during numerical problem solving were significantly different between the groups and predictive of individual mathematical abilities. Children with ASD showed better numerical problem solving abilities and relied on sophisticated decomposition strategies for single-digit addition problems more frequently than TD peers. Although children with ASD engaged similar brain areas as TD children, they showed different multivariate activation patterns related to arithmetic problem complexity in ventral temporal-occipital cortex, posterior parietal cortex, and medial temporal lobe. Furthermore, multivariate activation patterns in ventral temporal-occipital cortical areas typically associated with face processing predicted individual numerical problem solving abilities in children with ASD but not in TD children. Our study suggests that superior mathematical information processing in children with ASD is characterized by a unique pattern of brain organization and that cortical regions typically involved in perceptual expertise may be utilized in novel ways in ASD. Our findings of enhanced cognitive and neural resources for mathematics have critical implications for educational, professional, and social outcomes for individuals with this lifelong disorder. Copyright © 2014 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Trajectory control method of stratospheric airship based on the sliding mode control and prediction in wind field

NASA Astrophysics Data System (ADS)

Zhang, Jia-shi; Yang, Xi-xiang

2017-11-01

The stratospheric airship has the characteristics of large inertia, long time delay and large disturbance of wind field , so the trajectory control is very difficult .Build the lateral three degrees of freedom dynamic model which consider the wind interference , the dynamics equation is linearized by the small perturbation theory, propose a trajectory control method Combine with the sliding mode control and prediction, design the trajectory controller , takes the HAA airship as the reference to carry out simulation analysis. Results show that the improved sliding mode control with front-feedback method not only can solve well control problems of airship trajectory in wind field, but also can effectively improve the control accuracy of the traditional sliding mode control method, solved problems that using the traditional sliding mode control to control. It provides a useful reference for dynamic modeling and trajectory control of stratospheric airship.

Category 3: Sound Generation by Interacting with a Gust

NASA Technical Reports Server (NTRS)

Scott, James R.

2004-01-01

The cascade-gust interaction problem is solved employing a time-domain approach. The purpose of this problem is to test the ability of a CFD/CAA code to accurately predict the unsteady aerodynamic and aeroacoustic response of a single airfoil to a two-dimensional, periodic vortical gust.Nonlinear time dependent Euler equations are solved using higher order spatial differencing and time marching techniques. The solutions indicate the generation and propagation of expected mode orders for the given configuration and flow conditions. The blade passing frequency (BPF) is cut off for this cascade while higher harmonic, 2BPF and 3BPF, modes are cut on.

Swarm intelligence metaheuristics for enhanced data analysis and optimization.

PubMed

Hanrahan, Grady

2011-09-21

The swarm intelligence (SI) computing paradigm has proven itself as a comprehensive means of solving complicated analytical chemistry problems by emulating biologically-inspired processes. As global optimum search metaheuristics, associated algorithms have been widely used in training neural networks, function optimization, prediction and classification, and in a variety of process-based analytical applications. The goal of this review is to provide readers with critical insight into the utility of swarm intelligence tools as methods for solving complex chemical problems. Consideration will be given to algorithm development, ease of implementation and model performance, detailing subsequent influences on a number of application areas in the analytical, bioanalytical and detection sciences.

Alternative theoretical method for motion of a sand-filled funnel experiment

NASA Astrophysics Data System (ADS)

Byrd, David; White, Gary

2001-11-01

In "Motion of a Sand-Filled Funnel," Peter Sullivan and Anna McLoon described how to use numerical methods and a Microsoft Excel spreadsheet to predict the motion of a variant of Atwood's machine with variable mass. They wrote for noncalculus-based physics classes, but we solve the same problem using the methods of calculus. Our method highlights the less-familiar but more accurate version of Newton's second law, ∑F =dp/dt. This can help introductory physics students understand a broader definition of Newton's second law and enhance their calculus skills. It also teaches students how to solve a variable-mass problem.

Managing stress: the influence of gender, age and emotion regulation on coping among university students in Botswana

PubMed Central

Monteiro, Nicole M.; Balogun, Shyngle K.; Oratile, Kutlo N.

2014-01-01

This study focused on the influence of gender, age and emotion regulation on coping strategies among university students in Botswana. Sixty-four males and 64 females, ranging in age from 18 to 29 years completed the Difficulty in Emotion Regulation Scale and the Coping Strategy Inventory. Female students used wishful thinking and problem-focused disengagement more than male students; however, there were no other significant gender differences in coping strategies. Older students were more likely to use problem-solving, cognitive restructuring and express emotion coping strategies. In addition, problems in emotion regulation significantly predicted problem-and emotion-focused engagement, problem- and emotion-focused disengagement and coping strategies. There was a unique finding that non-acceptance of emotional responses, a type of emotion suppression, was positively correlated with problem solving, cognitive restructuring, expressing emotion, social support, problem avoidance and wishful thinking coping strategies. Cultural context and implications for student well-being and university support are discussed. PMID:24910491

Working memory facilitates insight instead of hindering it: Comment on DeCaro, Van Stockum, and Wieth (2016).

PubMed

Chuderski, Adam; Jastrzębski, Jan

2017-12-01

The "nothing-special" account of insight predicts positive correlations of insight problem solving and working memory capacity (WMC), whereas the "special-process" account expects no, or even negative, correlations. In the latter vein, DeCaro, Van Stockum Jr., and Wieth (2016) have recently reported weak negative WMC correlations with 2 constraint relaxation matchstick problems and 3 insight problems, and thus they claim that WM hinders insight. Here, we report on 3 studies that investigated WMC and various matchstick and classical problems (including 1 study that precisely replicated DeCaro et al.'s procedure). All 3 studies yielded moderate positive correlations of WMC with both the constraint relaxation and the classical problems. WMC explained 10% variance in problem solving, no matter what problems were used or how they were applied. Thus, DeCaro et al.'s claim that WM hinders insight is unwarranted. The opposite is true: WM facilitates insight. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

An approach to quantum-computational hydrologic inverse analysis

DOE PAGES

O'Malley, Daniel

2018-05-02

Making predictions about flow and transport in an aquifer requires knowledge of the heterogeneous properties of the aquifer such as permeability. Computational methods for inverse analysis are commonly used to infer these properties from quantities that are more readily observable such as hydraulic head. We present a method for computational inverse analysis that utilizes a type of quantum computer called a quantum annealer. While quantum computing is in an early stage compared to classical computing, we demonstrate that it is sufficiently developed that it can be used to solve certain subsurface flow problems. We utilize a D-Wave 2X quantum annealermore » to solve 1D and 2D hydrologic inverse problems that, while small by modern standards, are similar in size and sometimes larger than hydrologic inverse problems that were solved with early classical computers. Our results and the rapid progress being made with quantum computing hardware indicate that the era of quantum-computational hydrology may not be too far in the future.« less

An approach to quantum-computational hydrologic inverse analysis.

PubMed

O'Malley, Daniel

2018-05-02

Making predictions about flow and transport in an aquifer requires knowledge of the heterogeneous properties of the aquifer such as permeability. Computational methods for inverse analysis are commonly used to infer these properties from quantities that are more readily observable such as hydraulic head. We present a method for computational inverse analysis that utilizes a type of quantum computer called a quantum annealer. While quantum computing is in an early stage compared to classical computing, we demonstrate that it is sufficiently developed that it can be used to solve certain subsurface flow problems. We utilize a D-Wave 2X quantum annealer to solve 1D and 2D hydrologic inverse problems that, while small by modern standards, are similar in size and sometimes larger than hydrologic inverse problems that were solved with early classical computers. Our results and the rapid progress being made with quantum computing hardware indicate that the era of quantum-computational hydrology may not be too far in the future.

Problem solving, contention, and struggle: how siblings resolve a conflict of interests.

PubMed

Ram, A; Ross, H S

2001-01-01

In a laboratory setting, 48 sibling dyads age 4 and 6 or 6 and 8 years negotiated the division of six toys. Findings revealed that, in general, children reached divisions while using a preponderance of constructive problem-solving strategies, rather than contentious tactics. The degree of conflict of interests and the quality of sibling relationships predicted the children's use of problem-solving and contentious negotiation strategies, and was related to the types of resolutions achieved. Dyads experiencing low conflict of interests resolved their differences quickly. High conflict of interests coupled with positive relationships and constructive negotiation resulted in longer negotiations and creative, agreeable resolutions. High conflict of interests coupled with more negative relationships and destructive negotiations resulted in children's failures to reach agreement. Developmental differences indicated that older siblings within the pairs took the lead in negotiation, and benefited slightly more from the divisions. Furthermore, children in older dyads were more sophisticated and other oriented in their negotiations.

Hippocampal-neocortical functional reorganization underlies children's cognitive development.

PubMed

Qin, Shaozheng; Cho, Soohyun; Chen, Tianwen; Rosenberg-Lee, Miriam; Geary, David C; Menon, Vinod

2014-09-01

The importance of the hippocampal system for rapid learning and memory is well recognized, but its contributions to a cardinal feature of children's cognitive development-the transition from procedure-based to memory-based problem-solving strategies-are unknown. Here we show that the hippocampal system is pivotal to this strategic transition. Longitudinal functional magnetic resonance imaging (fMRI) in 7-9-year-old children revealed that the transition from use of counting to memory-based retrieval parallels increased hippocampal and decreased prefrontal-parietal engagement during arithmetic problem solving. Longitudinal improvements in retrieval-strategy use were predicted by increased hippocampal-neocortical functional connectivity. Beyond childhood, retrieval-strategy use continued to improve through adolescence into adulthood and was associated with decreased activation but more stable interproblem representations in the hippocampus. Our findings provide insights into the dynamic role of the hippocampus in the maturation of memory-based problem solving and establish a critical link between hippocampal-neocortical reorganization and children's cognitive development.

An approach to quantum-computational hydrologic inverse analysis

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

O'Malley, Daniel

Making predictions about flow and transport in an aquifer requires knowledge of the heterogeneous properties of the aquifer such as permeability. Computational methods for inverse analysis are commonly used to infer these properties from quantities that are more readily observable such as hydraulic head. We present a method for computational inverse analysis that utilizes a type of quantum computer called a quantum annealer. While quantum computing is in an early stage compared to classical computing, we demonstrate that it is sufficiently developed that it can be used to solve certain subsurface flow problems. We utilize a D-Wave 2X quantum annealermore » to solve 1D and 2D hydrologic inverse problems that, while small by modern standards, are similar in size and sometimes larger than hydrologic inverse problems that were solved with early classical computers. Our results and the rapid progress being made with quantum computing hardware indicate that the era of quantum-computational hydrology may not be too far in the future.« less

Tracking children's mental states while solving algebra equations.

PubMed

Anderson, John R; Betts, Shawn; Ferris, Jennifer L; Fincham, Jon M

2012-11-01

Behavioral and function magnetic resonance imagery (fMRI) data were combined to infer the mental states of students as they interacted with an intelligent tutoring system. Sixteen children interacted with a computer tutor for solving linear equations over a six-day period (days 0-5), with days 1 and 5 occurring in an fMRI scanner. Hidden Markov model algorithms combined a model of student behavior with multi-voxel imaging pattern data to predict the mental states of students. We separately assessed the algorithms' ability to predict which step in a problem-solving sequence was performed and whether the step was performed correctly. For day 1, the data patterns of other students were used to predict the mental states of a target student. These predictions were improved on day 5 by adding information about the target student's behavioral and imaging data from day 1. Successful tracking of mental states depended on using the combination of a behavioral model and multi-voxel pattern analysis, illustrating the effectiveness of an integrated approach to tracking the cognition of individuals in real time as they perform complex tasks. Copyright © 2011 Wiley Periodicals, Inc.

Experimental Matching of Instances to Heuristics for Constraint Satisfaction Problems.

PubMed

Moreno-Scott, Jorge Humberto; Ortiz-Bayliss, José Carlos; Terashima-Marín, Hugo; Conant-Pablos, Santiago Enrique

2016-01-01

Constraint satisfaction problems are of special interest for the artificial intelligence and operations research community due to their many applications. Although heuristics involved in solving these problems have largely been studied in the past, little is known about the relation between instances and the respective performance of the heuristics used to solve them. This paper focuses on both the exploration of the instance space to identify relations between instances and good performing heuristics and how to use such relations to improve the search. Firstly, the document describes a methodology to explore the instance space of constraint satisfaction problems and evaluate the corresponding performance of six variable ordering heuristics for such instances in order to find regions on the instance space where some heuristics outperform the others. Analyzing such regions favors the understanding of how these heuristics work and contribute to their improvement. Secondly, we use the information gathered from the first stage to predict the most suitable heuristic to use according to the features of the instance currently being solved. This approach proved to be competitive when compared against the heuristics applied in isolation on both randomly generated and structured instances of constraint satisfaction problems.

Experimental Matching of Instances to Heuristics for Constraint Satisfaction Problems

PubMed Central

Moreno-Scott, Jorge Humberto; Ortiz-Bayliss, José Carlos; Terashima-Marín, Hugo; Conant-Pablos, Santiago Enrique

2016-01-01

Constraint satisfaction problems are of special interest for the artificial intelligence and operations research community due to their many applications. Although heuristics involved in solving these problems have largely been studied in the past, little is known about the relation between instances and the respective performance of the heuristics used to solve them. This paper focuses on both the exploration of the instance space to identify relations between instances and good performing heuristics and how to use such relations to improve the search. Firstly, the document describes a methodology to explore the instance space of constraint satisfaction problems and evaluate the corresponding performance of six variable ordering heuristics for such instances in order to find regions on the instance space where some heuristics outperform the others. Analyzing such regions favors the understanding of how these heuristics work and contribute to their improvement. Secondly, we use the information gathered from the first stage to predict the most suitable heuristic to use according to the features of the instance currently being solved. This approach proved to be competitive when compared against the heuristics applied in isolation on both randomly generated and structured instances of constraint satisfaction problems. PMID:26949383

A Simple Label Switching Algorithm for Semisupervised Structural SVMs.

PubMed

Balamurugan, P; Shevade, Shirish; Sundararajan, S

2015-10-01

In structured output learning, obtaining labeled data for real-world applications is usually costly, while unlabeled examples are available in abundance. Semisupervised structured classification deals with a small number of labeled examples and a large number of unlabeled structured data. In this work, we consider semisupervised structural support vector machines with domain constraints. The optimization problem, which in general is not convex, contains the loss terms associated with the labeled and unlabeled examples, along with the domain constraints. We propose a simple optimization approach that alternates between solving a supervised learning problem and a constraint matching problem. Solving the constraint matching problem is difficult for structured prediction, and we propose an efficient and effective label switching method to solve it. The alternating optimization is carried out within a deterministic annealing framework, which helps in effective constraint matching and avoiding poor local minima, which are not very useful. The algorithm is simple and easy to implement. Further, it is suitable for any structured output learning problem where exact inference is available. Experiments on benchmark sequence labeling data sets and a natural language parsing data set show that the proposed approach, though simple, achieves comparable generalization performance.

Impact of Cognitive Abilities and Prior Knowledge on Complex Problem Solving Performance - Empirical Results and a Plea for Ecologically Valid Microworlds.

PubMed

Süß, Heinz-Martin; Kretzschmar, André

2018-01-01

The original aim of complex problem solving (CPS) research was to bring the cognitive demands of complex real-life problems into the lab in order to investigate problem solving behavior and performance under controlled conditions. Up until now, the validity of psychometric intelligence constructs has been scrutinized with regard to its importance for CPS performance. At the same time, different CPS measurement approaches competing for the title of the best way to assess CPS have been developed. In the first part of the paper, we investigate the predictability of CPS performance on the basis of the Berlin Intelligence Structure Model and Cattell's investment theory as well as an elaborated knowledge taxonomy. In the first study, 137 students managed a simulated shirt factory ( Tailorshop ; i.e., a complex real life-oriented system) twice, while in the second study, 152 students completed a forestry scenario ( FSYS ; i.e., a complex artificial world system). The results indicate that reasoning - specifically numerical reasoning (Studies 1 and 2) and figural reasoning (Study 2) - are the only relevant predictors among the intelligence constructs. We discuss the results with reference to the Brunswik symmetry principle. Path models suggest that reasoning and prior knowledge influence problem solving performance in the Tailorshop scenario mainly indirectly. In addition, different types of system-specific knowledge independently contribute to predicting CPS performance. The results of Study 2 indicate that working memory capacity, assessed as an additional predictor, has no incremental validity beyond reasoning. We conclude that (1) cognitive abilities and prior knowledge are substantial predictors of CPS performance, and (2) in contrast to former and recent interpretations, there is insufficient evidence to consider CPS a unique ability construct. In the second part of the paper, we discuss our results in light of recent CPS research, which predominantly utilizes the minimally complex systems (MCS) measurement approach. We suggest ecologically valid microworlds as an indispensable tool for future CPS research and applications.

Development of a Preventive HIV Vaccine Requires Solving Inverse Problems Which Is Unattainable by Rational Vaccine Design

PubMed Central

Van Regenmortel, Marc H. V.

2018-01-01

Hypotheses and theories are essential constituents of the scientific method. Many vaccinologists are unaware that the problems they try to solve are mostly inverse problems that consist in imagining what could bring about a desired outcome. An inverse problem starts with the result and tries to guess what are the multiple causes that could have produced it. Compared to the usual direct scientific problems that start with the causes and derive or calculate the results using deductive reasoning and known mechanisms, solving an inverse problem uses a less reliable inductive approach and requires the development of a theoretical model that may have different solutions or none at all. Unsuccessful attempts to solve inverse problems in HIV vaccinology by reductionist methods, systems biology and structure-based reverse vaccinology are described. The popular strategy known as rational vaccine design is unable to solve the multiple inverse problems faced by HIV vaccine developers. The term “rational” is derived from “rational drug design” which uses the 3D structure of a biological target for designing molecules that will selectively bind to it and inhibit its biological activity. In vaccine design, however, the word “rational” simply means that the investigator is concentrating on parts of the system for which molecular information is available. The economist and Nobel laureate Herbert Simon introduced the concept of “bounded rationality” to explain why the complexity of the world economic system makes it impossible, for instance, to predict an event like the financial crash of 2007–2008. Humans always operate under unavoidable constraints such as insufficient information, a limited capacity to process huge amounts of data and a limited amount of time available to reach a decision. Such limitations always prevent us from achieving the complete understanding and optimization of a complex system that would be needed to achieve a truly rational design process. This is why the complexity of the human immune system prevents us from rationally designing an HIV vaccine by solving inverse problems. PMID:29387066

Toward Solving the Problem of Problem Solving: An Analysis Framework

ERIC Educational Resources Information Center

Roesler, Rebecca A.

2016-01-01

Teaching is replete with problem solving. Problem solving as a skill, however, is seldom addressed directly within music teacher education curricula, and research in music education has not examined problem solving systematically. A framework detailing problem-solving component skills would provide a needed foundation. I observed problem solving…

The functional implications of motor, cognitive, psychiatric, and social problem-solving states in Huntington's disease.

PubMed

Van Liew, Charles; Gluhm, Shea; Goldstein, Jody; Cronan, Terry A; Corey-Bloom, Jody

2013-01-01

Huntington's disease (HD) is a genetic, neurodegenerative disorder characterized by motor, cognitive, and psychiatric dysfunction. In HD, the inability to solve problems successfully affects not only disease coping, but also interpersonal relationships, judgment, and independent living. The aim of the present study was to examine social problem-solving (SPS) in well-characterized HD and at-risk (AR) individuals and to examine its unique and conjoint effects with motor, cognitive, and psychiatric states on functional ratings. Sixty-three participants, 31 HD and 32 gene-positive AR, were included in the study. Participants completed the Social Problem-Solving Inventory-Revised: Long (SPSI-R:L), a 52-item, reliable, standardized measure of SPS. Items are aggregated under five scales (Positive, Negative, and Rational Problem-Solving; Impulsivity/Carelessness and Avoidance Styles). Participants also completed the Unified Huntington's Disease Rating Scale functional, behavioral, and cognitive assessments, as well as additional neuropsychological examinations and the Symptom Checklist-90-Revised (SCL-90R). A structural equation model was used to examine the effects of motor, cognitive, psychiatric, and SPS states on functionality. The multifactor structural model fit well descriptively. Cognitive and motor states uniquely and significantly predicted function in HD; however, neither psychiatric nor SPS states did. SPS was, however, significantly related to motor, cognitive, and psychiatric states, suggesting that it may bridge the correlative gap between psychiatric and cognitive states in HD. SPS may be worth assessing in conjunction with the standard gamut of clinical assessments in HD. Suggestions for future research and implications for patients, families, caregivers, and clinicians are discussed.

High school students' understanding and problem solving in population genetics

NASA Astrophysics Data System (ADS)

Soderberg, Patti D.

This study is an investigation of student understanding of population genetics and how students developed, used and revised conceptual models to solve problems. The students in this study participated in three rounds of problem solving. The first round involved the use of a population genetics model to predict the number of carriers in a population. The second round required them to revise their model of simple dominance population genetics to make inferences about populations containing three phenotype variations. The third round of problem solving required the students to revise their model of population genetics to explain anomalous data where the proportions of males and females with a trait varied significantly. As the students solved problems, they were involved in basic scientific processes as they observed population phenomena, constructed explanatory models to explain the data they observed, and attempted to persuade their peers as to the adequacy of their models. In this study, the students produced new knowledge about the genetics of a trait in a population through the revision and use of explanatory population genetics models using reasoning that was similar to what scientists do. The students learned, used and revised a model of Hardy-Weinberg equilibrium to generate and test hypotheses about the genetics of phenotypes given only population data. Students were also interviewed prior to and following instruction. This study suggests that a commonly held intuitive belief about the predominance of a dominant variation in populations is resistant to change, despite instruction and interferes with a student's ability to understand Hardy-Weinberg equilibrium and microevolution.

Efficient Computation of Info-Gap Robustness for Finite Element Models

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

Stull, Christopher J.; Hemez, Francois M.; Williams, Brian J.

2012-07-05

A recent research effort at LANL proposed info-gap decision theory as a framework by which to measure the predictive maturity of numerical models. Info-gap theory explores the trade-offs between accuracy, that is, the extent to which predictions reproduce the physical measurements, and robustness, that is, the extent to which predictions are insensitive to modeling assumptions. Both accuracy and robustness are necessary to demonstrate predictive maturity. However, conducting an info-gap analysis can present a formidable challenge, from the standpoint of the required computational resources. This is because a robustness function requires the resolution of multiple optimization problems. This report offers anmore » alternative, adjoint methodology to assess the info-gap robustness of Ax = b-like numerical models solved for a solution x. Two situations that can arise in structural analysis and design are briefly described and contextualized within the info-gap decision theory framework. The treatments of the info-gap problems, using the adjoint methodology are outlined in detail, and the latter problem is solved for four separate finite element models. As compared to statistical sampling, the proposed methodology offers highly accurate approximations of info-gap robustness functions for the finite element models considered in the report, at a small fraction of the computational cost. It is noted that this report considers only linear systems; a natural follow-on study would extend the methodologies described herein to include nonlinear systems.« less

Pasta Predation.

ERIC Educational Resources Information Center

Waugh, Michael L.

1986-01-01

Presents a predator-prey simulation which involves students in collecting data, solving problems, and making predictions on the evolution of prey populations. Provides directives on how to perform the chi-square test and also includes an Applesoft BASK program that performs the calculations. (ML)

ORES - Objective Referenced Evaluation in Science.

ERIC Educational Resources Information Center

Shaw, Terry

Science process skills considered important in making decisions and solving problems include: observing, classifying, measuring, using numbers, using space/time relationships, communicating, predicting, inferring, manipulating variables, making operational definitions, forming hypotheses, interpreting data, and experimenting. This 60-item test,…

Predicting Correctness of Problem Solving from Low-Level Log Data in Intelligent Tutoring Systems

ERIC Educational Resources Information Center

Cetintas, Suleyman; Si, Luo; Xin, Yan Ping; Hord, Casey

2009-01-01

This paper proposes a learning based method that can automatically determine how likely a student is to give a correct answer to a problem in an intelligent tutoring system. Only log files that record students' actions with the system are used to train the model, therefore the modeling process doesn't require expert knowledge for identifying…

Landfill gas control at military installations. Final report

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

Shafer, R.A.; Renta-Babb, A.; Bandy, J.T.

1984-01-01

This report provides information useful to Army personnel responsible for recognizing and solving potential problems from gas generated by landfills. Information is provided on recognizing and gauging the magnitude of landfill gas problems; selecting appropriate gas control strategies, procedures, and equipment; use of computer modeling to predict gas production and migration and the success of gas control devices; and safety considerations.

Young Adolescents' Metacognition and Domain Knowledge as Predictors of Hypothesis-Development Performance in a Computer-Supported Context

ERIC Educational Resources Information Center

Kim, Hye Jeong; Pedersen, Susan

2010-01-01

Recently, the importance of ill-structured problem-solving in real-world contexts has become a focus of educational research. Particularly, the hypothesis-development process has been examined as one of the keys to developing a high-quality solution in a problem context. The authors of this study examined predictive relations between young…

No Solutions: Resisting Certainty in Water Supply Management

NASA Astrophysics Data System (ADS)

Cockerill, K.; Armstrong, M.; Richter, J.; Okie, J. G.

2017-12-01

Although most scholars and water managers implicitly understand that managing water resources is an ongoing need, both popular and academic literature routinely use the words `solution' and `solve' in discussing water management concerns. The word `solution' reflects a quest for certainty, stability, permanence. A focus on `solving' creates a simplistic expectation that some person or institution is responsible for implementing a solution and that once `solved' the issue no longer requires attention. The reality, however, is water management is a wicked problem, meaning it is amorphous, involves multiple definitions, is embedded in complex systems, and hence is intractable. By definition, wicked problems defy solution. Our interdisciplinary project integrates research from across a broad spectrum of biological, physical, and social sciences. We find that framing a problem in terms of `solving' affects how people think, feel, behave toward the problem. Further, our work suggests that the prevalence of solution- based language has simultaneously generated expectations that science / scientists can predict and control biophysical systems and that science is not to be trusted because it has failed to deliver on previous promises to permanently `solve' events like floods or droughts. Hydrologic systems, are, of course highly uncertain. Hence, reiterating a simplistic insistence on `solving' water management concerns may result in decreased public attention to or support for more complex policy discussions that could provide long-term management strategies. Using the language of `solutions' with expectations of certainty sets hydrologic researchers and water managers up to fail. Managing water is a social responsibility and it will require consistent attention in the future, just as it has throughout human history. Scientists have a key role to play in explaining how various hydrologic systems function, but they should not be expected to `solve' pressing water management needs. Rather, reconsidering the language used to frame water management concerns can help us recognize our own culpability in creating water problems and our responsibility in continuously managing this most essential resource.

Problem-Solving Appraisal and the Prediction of Depression during Pregnancy and in the Postpartum Period.

ERIC Educational Resources Information Center

Elliott, Timothy R.; And Others

1996-01-01

Tested hypothesis that higher levels of positive affect and lower levels of negative affect would predict depression during pregnancy and in the postpartum period. Analysis of 100 women indicated that women at risk for depression during pregnancy and in the postpartum period may exhibit heightened negative moods and a dearth of positive affective…

Ventral striatal prediction error signaling is associated with dopamine synthesis capacity and fluid intelligence

PubMed Central

Schlagenhauf, Florian; Rapp, Michael A.; Huys, Quentin J. M.; Beck, Anne; Wüstenberg, Torsten; Deserno, Lorenz; Buchholz, Hans-Georg; Kalbitzer, Jan; Buchert, Ralph; Kienast, Thorsten; Cumming, Paul; Plotkin, Michail; Kumakura, Yoshitaka; Grace, Anthony A.; Dolan, Raymond J.; Heinz, Andreas

2013-01-01

Fluid intelligence represents the capacity for flexible problem solving and rapid behavioral adaptation. Rewards drive flexible behavioral adaptation, in part via a teaching signal expressed as reward prediction errors in the ventral striatum, which has been associated with phasic dopamine release in animal studies. We examined a sample of 28 healthy male adults using multimodal imaging and biological parametric mapping with 1) functional magnetic resonance imaging during a reversal learning task and 2) in a subsample of 17 subjects also with positron emission tomography using 6-[18F]fluoro-L-DOPA to assess dopamine synthesis capacity. Fluid intelligence was measured using a battery of nine standard neuropsychological tests. Ventral striatal BOLD correlates of reward prediction errors were positively correlated with fluid intelligence and, in the right ventral striatum, also inversely correlated with dopamine synthesis capacity (FDOPA Kinapp). When exploring aspects of fluid intelligence, we observed that prediction error signaling correlates with complex attention and reasoning. These findings indicate that individual differences in the capacity for flexible problem solving may be driven by ventral striatal activation during reward-related learning, which in turn proved to be inversely associated with ventral striatal dopamine synthesis capacity. PMID:22344813

Resources in Technology: Problem-Solving.

ERIC Educational Resources Information Center

Technology Teacher, 1986

1986-01-01

This instructional module examines a key function of science and technology: problem solving. It studies the meaning of problem solving, looks at techniques for problem solving, examines case studies that exemplify the problem-solving approach, presents problems for the reader to solve, and provides a student self-quiz. (Author/CT)

Solving geosteering inverse problems by stochastic Hybrid Monte Carlo method

DOE PAGES

Shen, Qiuyang; Wu, Xuqing; Chen, Jiefu; ...

2017-11-20

The inverse problems arise in almost all fields of science where the real-world parameters are extracted from a set of measured data. The geosteering inversion plays an essential role in the accurate prediction of oncoming strata as well as a reliable guidance to adjust the borehole position on the fly to reach one or more geological targets. This mathematical treatment is not easy to solve, which requires finding an optimum solution among a large solution space, especially when the problem is non-linear and non-convex. Nowadays, a new generation of logging-while-drilling (LWD) tools has emerged on the market. The so-called azimuthalmore » resistivity LWD tools have azimuthal sensitivity and a large depth of investigation. Hence, the associated inverse problems become much more difficult since the earth model to be inverted will have more detailed structures. The conventional deterministic methods are incapable to solve such a complicated inverse problem, where they suffer from the local minimum trap. Alternatively, stochastic optimizations are in general better at finding global optimal solutions and handling uncertainty quantification. In this article, we investigate the Hybrid Monte Carlo (HMC) based statistical inversion approach and suggest that HMC based inference is more efficient in dealing with the increased complexity and uncertainty faced by the geosteering problems.« less

Psychological resilience in young and older adults.

PubMed

Gooding, P A; Hurst, A; Johnson, J; Tarrier, N

2012-03-01

The goal of the current study was to investigate psychological resilience in the older adults (>64 years) compared with that of the young ones (<26 years). Questionnaire measures of depression, hopelessness, general health and resilience were administered to the participants. The resilience measure comprised three sub-scales of social support, emotional regulation and problem solving. The older adults were the more resilient group especially with respect to emotional regulation ability and problem solving. The young ones had more resilience related to social support. Poor perceptions of general health and low energy levels predicted low levels of resilience regardless of age. Low hopelessness scores also predicted greater resilience in both groups. Experiencing higher levels of mental illness and physical dysfunction predicted high resilience scores especially for the social support resilience scale in the older adults. The negative effects of depression on resilience related to emotional regulation were countered by low hopelessness but only in the young adults. These results highlight the importance of maintaining resilience-related coping skills in both young and older adults but indicate that different psychological processes underlie resilience across the lifespan. Copyright © 2011 John Wiley & Sons, Ltd.

Dynamics of representational change: entropy, action, and cognition.

PubMed

Stephen, Damian G; Dixon, James A; Isenhower, Robert W

2009-12-01

Explaining how the cognitive system can create new structures has been a major challenge for cognitive science. Self-organization from the theory of nonlinear dynamics offers an account of this remarkable phenomenon. Two studies provide an initial test of the hypothesis that the emergence of new cognitive structure follows the same universal principles as emergence in other domains (e.g., fluids, lasers). In both studies, participants initially solved gear-system problems by manually tracing the force across a system of gears. Subsequently, they discovered that the gears form an alternating sequence, thereby demonstrating a new cognitive structure. In both studies, dynamical analyses of action during problem solving predicted the spontaneous emergence of the new cognitive structure. Study 1 showed that a peak in entropy, followed by negentropy, key indicators of self-organization, predicted discovery of alternation. Study 2 replicated these effects, and showed that increasing environmental entropy accelerated discovery, a classic prediction from dynamics. Additional analyses based on the relationship between phase transitions and power-law behavior provide converging evidence. The studies provide an initial demonstration of the emergence of cognitive structure through self-organization.

A Cognitive Analysis of Students’ Mathematical Problem Solving Ability on Geometry

NASA Astrophysics Data System (ADS)

Rusyda, N. A.; Kusnandi, K.; Suhendra, S.

2017-09-01

The purpose of this research is to analyze of mathematical problem solving ability of students in one of secondary school on geometry. This research was conducted by using quantitative approach with descriptive method. Population in this research was all students of that school and the sample was twenty five students that was chosen by purposive sampling technique. Data of mathematical problem solving were collected through essay test. The results showed the percentage of achievement of mathematical problem solving indicators of students were: 1) solve closed mathematical problems with context in math was 50%; 2) solve the closed mathematical problems with the context beyond mathematics was 24%; 3) solving open mathematical problems with contexts in mathematics was 35%; And 4) solving open mathematical problems with contexts outside mathematics was 44%. Based on the percentage, it can be concluded that the level of achievement of mathematical problem solving ability in geometry still low. This is because students are not used to solving problems that measure mathematical problem solving ability, weaknesses remember previous knowledge, and lack of problem solving framework. So the students’ ability of mathematical problems solving need to be improved with implement appropriate learning strategy.

Individual differences in working memory and reasoning-remembering relationships in solving class-inclusion problems.

PubMed

Howe, M L; Rabinowitz, F M; Powell, T L

1998-09-01

In the present experiment, we evaluated the effects of individual differences in reading span and variation in memory demands on class-inclusion performance. One hundred twenty college students whose reading spans ranged from low to medium to high (as indexed by a computerized version of the Daneman and Carpenter [1980] reading-span task) solved 48 class-inclusion problems. Half of the subjects had the solution information available when the problems were presented; the other half performed a detection task between solution information and problem presentation. The results from both standard statistical analyses and from a mathematical model indicated that differences in reading span and memory load had predictable, similar effects. Specifically, the sophistication of reasoning strategies declined when memory demands increased or when reading spans decreased. Surprisingly, these effects were primarily additive. The results were interpreted in terms of global resource models and findings from the developmental literature.

Predicting flight delay based on multiple linear regression

NASA Astrophysics Data System (ADS)

Ding, Yi

2017-08-01

Delay of flight has been regarded as one of the toughest difficulties in aviation control. How to establish an effective model to handle the delay prediction problem is a significant work. To solve the problem that the flight delay is difficult to predict, this study proposes a method to model the arriving flights and a multiple linear regression algorithm to predict delay, comparing with Naive-Bayes and C4.5 approach. Experiments based on a realistic dataset of domestic airports show that the accuracy of the proposed model approximates 80%, which is further improved than the Naive-Bayes and C4.5 approach approaches. The result testing shows that this method is convenient for calculation, and also can predict the flight delays effectively. It can provide decision basis for airport authorities.

Predicting the evolution of spreading on complex networks

PubMed Central

Chen, Duan-Bing; Xiao, Rui; Zeng, An

2014-01-01

Due to the wide applications, spreading processes on complex networks have been intensively studied. However, one of the most fundamental problems has not yet been well addressed: predicting the evolution of spreading based on a given snapshot of the propagation on networks. With this problem solved, one can accelerate or slow down the spreading in advance if the predicted propagation result is narrower or wider than expected. In this paper, we propose an iterative algorithm to estimate the infection probability of the spreading process and then apply it to a mean-field approach to predict the spreading coverage. The validation of the method is performed in both artificial and real networks. The results show that our method is accurate in both infection probability estimation and spreading coverage prediction. PMID:25130862

An improved stochastic fractal search algorithm for 3D protein structure prediction.

PubMed

Zhou, Changjun; Sun, Chuan; Wang, Bin; Wang, Xiaojun

2018-05-03

Protein structure prediction (PSP) is a significant area for biological information research, disease treatment, and drug development and so on. In this paper, three-dimensional structures of proteins are predicted based on the known amino acid sequences, and the structure prediction problem is transformed into a typical NP problem by an AB off-lattice model. This work applies a novel improved Stochastic Fractal Search algorithm (ISFS) to solve the problem. The Stochastic Fractal Search algorithm (SFS) is an effective evolutionary algorithm that performs well in exploring the search space but falls into local minimums sometimes. In order to avoid the weakness, Lvy flight and internal feedback information are introduced in ISFS. In the experimental process, simulations are conducted by ISFS algorithm on Fibonacci sequences and real peptide sequences. Experimental results prove that the ISFS performs more efficiently and robust in terms of finding the global minimum and avoiding getting stuck in local minimums.

Advanced Methods for Determining Prediction Uncertainty in Model-Based Prognostics with Application to Planetary Rovers

NASA Technical Reports Server (NTRS)

Daigle, Matthew J.; Sankararaman, Shankar

2013-01-01

Prognostics is centered on predicting the time of and time until adverse events in components, subsystems, and systems. It typically involves both a state estimation phase, in which the current health state of a system is identified, and a prediction phase, in which the state is projected forward in time. Since prognostics is mainly a prediction problem, prognostic approaches cannot avoid uncertainty, which arises due to several sources. Prognostics algorithms must both characterize this uncertainty and incorporate it into the predictions so that informed decisions can be made about the system. In this paper, we describe three methods to solve these problems, including Monte Carlo-, unscented transform-, and first-order reliability-based methods. Using a planetary rover as a case study, we demonstrate and compare the different methods in simulation for battery end-of-discharge prediction.

Concurrent validity and clinical usefulness of several individually administered tests of children's social-emotional cognition.

PubMed

McKown, Clark

2007-03-01

In this study, the validity of 5 tests of children's social-emotional cognition, defined as their encoding, memory, and interpretation of social information, was tested. Participants were 126 clinic-referred children between the ages of 5 and 17. All 5 tests were evaluated in terms of their (a) concurrent validity, (b) incremental validity, and (c) clinical usefulness in predicting social functioning. Tests included measures of nonverbal sensitivity, social language, and social problem solving. Criterion measures included parent and teacher report of social functioning. Analyses support the concurrent validity of all measures, and the incremental validity and clinical usefulness of tests of pragmatic language and problem solving.

A test of the circumvention-of-limits hypothesis in scientific problem solving: the case of geological bedrock mapping.

PubMed

Hambrick, David Z; Libarkin, Julie C; Petcovic, Heather L; Baker, Kathleen M; Elkins, Joe; Callahan, Caitlin N; Turner, Sheldon P; Rench, Tara A; Ladue, Nicole D

2012-08-01

Sources of individual differences in scientific problem solving were investigated. Participants representing a wide range of experience in geology completed tests of visuospatial ability and geological knowledge, and performed a geological bedrock mapping task, in which they attempted to infer the geological structure of an area in the Tobacco Root Mountains of Montana. A Visuospatial Ability × Geological Knowledge interaction was found, such that visuospatial ability positively predicted mapping performance at low, but not high, levels of geological knowledge. This finding suggests that high levels of domain knowledge may sometimes enable circumvention of performance limitations associated with cognitive abilities. (PsycINFO Database Record (c) 2012 APA, all rights reserved).

Problem-solving variability in older spouses: how is it linked to problem-, person-, and couple-characteristics?

PubMed

Hoppmann, Christiane A; Blanchard-Fields, Fredda

2011-09-01

Problem-solving does not take place in isolation and often involves social others such as spouses. Using repeated daily life assessments from 98 older spouses (M age = 72 years; M marriage length = 42 years), the present study examined theoretical notions from social-contextual models of coping regarding (a) the origins of problem-solving variability and (b) associations between problem-solving and specific problem-, person-, and couple- characteristics. Multilevel models indicate that the lion's share of variability in everyday problem-solving is located at the level of the problem situation. Importantly, participants reported more proactive emotion regulation and collaborative problem-solving for social than nonsocial problems. We also found person-specific consistencies in problem-solving. That is, older spouses high in Neuroticism reported more problems across the study period as well as less instrumental problem-solving and more passive emotion regulation than older spouses low in Neuroticism. Contrary to expectations, relationship satisfaction was unrelated to problem-solving in the present sample. Results are in line with the stress and coping literature in demonstrating that everyday problem-solving is a dynamic process that has to be viewed in the broader context in which it occurs. Our findings also complement previous laboratory-based work on everyday problem-solving by underscoring the benefits of examining everyday problem-solving as it unfolds in spouses' own environment.

Resource Letter RPS-1: Research in problem solving

NASA Astrophysics Data System (ADS)

Hsu, Leonardo; Brewe, Eric; Foster, Thomas M.; Harper, Kathleen A.

2004-09-01

This Resource Letter provides a guide to the literature on research in problem solving, especially in physics. The references were compiled with two audiences in mind: physicists who are (or might become) engaged in research on problem solving, and physics instructors who are interested in using research results to improve their students' learning of problem solving. In addition to general references, journal articles and books are cited for the following topics: cognitive aspects of problem solving, expert-novice problem-solver characteristics, problem solving in mathematics, alternative problem types, curricular interventions, and the use of computers in problem solving.

Frnakenstein: multiple target inverse RNA folding.

PubMed

Lyngsø, Rune B; Anderson, James W J; Sizikova, Elena; Badugu, Amarendra; Hyland, Tomas; Hein, Jotun

2012-10-09

RNA secondary structure prediction, or folding, is a classic problem in bioinformatics: given a sequence of nucleotides, the aim is to predict the base pairs formed in its three dimensional conformation. The inverse problem of designing a sequence folding into a particular target structure has only more recently received notable interest. With a growing appreciation and understanding of the functional and structural properties of RNA motifs, and a growing interest in utilising biomolecules in nano-scale designs, the interest in the inverse RNA folding problem is bound to increase. However, whereas the RNA folding problem from an algorithmic viewpoint has an elegant and efficient solution, the inverse RNA folding problem appears to be hard. In this paper we present a genetic algorithm approach to solve the inverse folding problem. The main aims of the development was to address the hitherto mostly ignored extension of solving the inverse folding problem, the multi-target inverse folding problem, while simultaneously designing a method with superior performance when measured on the quality of designed sequences. The genetic algorithm has been implemented as a Python program called Frnakenstein. It was benchmarked against four existing methods and several data sets totalling 769 real and predicted single structure targets, and on 292 two structure targets. It performed as well as or better at finding sequences which folded in silico into the target structure than all existing methods, without the heavy bias towards CG base pairs that was observed for all other top performing methods. On the two structure targets it also performed well, generating a perfect design for about 80% of the targets. Our method illustrates that successful designs for the inverse RNA folding problem does not necessarily have to rely on heavy biases in base pair and unpaired base distributions. The design problem seems to become more difficult on larger structures when the target structures are real structures, while no deterioration was observed for predicted structures. Design for two structure targets is considerably more difficult, but far from impossible, demonstrating the feasibility of automated design of artificial riboswitches. The Python implementation is available at http://www.stats.ox.ac.uk/research/genome/software/frnakenstein.

Frnakenstein: multiple target inverse RNA folding

PubMed Central

2012-01-01

Background RNA secondary structure prediction, or folding, is a classic problem in bioinformatics: given a sequence of nucleotides, the aim is to predict the base pairs formed in its three dimensional conformation. The inverse problem of designing a sequence folding into a particular target structure has only more recently received notable interest. With a growing appreciation and understanding of the functional and structural properties of RNA motifs, and a growing interest in utilising biomolecules in nano-scale designs, the interest in the inverse RNA folding problem is bound to increase. However, whereas the RNA folding problem from an algorithmic viewpoint has an elegant and efficient solution, the inverse RNA folding problem appears to be hard. Results In this paper we present a genetic algorithm approach to solve the inverse folding problem. The main aims of the development was to address the hitherto mostly ignored extension of solving the inverse folding problem, the multi-target inverse folding problem, while simultaneously designing a method with superior performance when measured on the quality of designed sequences. The genetic algorithm has been implemented as a Python program called Frnakenstein. It was benchmarked against four existing methods and several data sets totalling 769 real and predicted single structure targets, and on 292 two structure targets. It performed as well as or better at finding sequences which folded in silico into the target structure than all existing methods, without the heavy bias towards CG base pairs that was observed for all other top performing methods. On the two structure targets it also performed well, generating a perfect design for about 80% of the targets. Conclusions Our method illustrates that successful designs for the inverse RNA folding problem does not necessarily have to rely on heavy biases in base pair and unpaired base distributions. The design problem seems to become more difficult on larger structures when the target structures are real structures, while no deterioration was observed for predicted structures. Design for two structure targets is considerably more difficult, but far from impossible, demonstrating the feasibility of automated design of artificial riboswitches. The Python implementation is available at http://www.stats.ox.ac.uk/research/genome/software/frnakenstein. PMID:23043260

Benjamin Banneker and the Law of Sines

ERIC Educational Resources Information Center

Mahoney, John F.

2005-01-01

Benjamin Banneker, a self-taught mathematician, surveyor and astronomer published annual almanacs containing his astronomical observations and predictions. Banneker who also used logarithms to apply the Law of Sines believed that the method used to solve a mathematical problem depends on the tools available.

Issues in the Empirical Study of Private Speech: A Response to Frawley and Lantolf's Commentary.

ERIC Educational Resources Information Center

Diaz, Rafael M.

1986-01-01

Responds to W. Frawley's and J. Lantolf's comments on the Frauenglass and Diaz study concerning the interaction between private speech and cognition. Argues that Vygotsky's theory predicts a positive effect on children's problem solving activity. (HOD)

Examining adherence to components of cognitive-behavioral therapy for youth anxiety after training and consultation.

PubMed

Edmunds, Julie M; Brodman, Douglas M; Ringle, Vanesa A; Read, Kendra L; Kendall, Philip C; Beidas, Rinad S

2017-02-01

The present study examined 115 service providers' adherence to components of cognitive-behavioral therapy (CBT) for youth anxiety prior to training, post workshop training, and after three months of weekly consultation. Adherence was measured using a role-play with a trained actor. We examined differences in individual adherence to CBT components across time and the relationship between number of consultation sessions attended and adherence ratings following consultation. Findings indicated that somatic arousal identification and relaxation were the most used treatment components prior to training. Adherence to all components of CBT increased following workshop training, except the usage of problem-solving. Adherence to problem-solving, positive reinforcement, the identification of anxious self-talk, and the creation of coping thoughts increased following consultation but usage of problem-solving remained low compared to other treatment components. Overall adherence remained less than optimal at the final measurement point. Number of consultation sessions attended predicted post-consultation adherence to identification of somatic arousal, identification of anxious self-talk, and positive reinforcement. Implications include tailoring future training based on baseline levels of adherence and spending more time during training and consultation on underutilized CBT components, such as problem-solving. Limitations of the present study, including how adherence was measured, are discussed. This study adds to the implementation science literature by providing more nuanced information on changes in adherence over the course of training and consultation of service providers.

Cognitive reserve as a moderator of responsiveness to an online problem-solving intervention for adolescents with complicated mild to severe traumatic brain injury

PubMed Central

Karver, Christine L.; Wade, Shari L.; Cassedy, Amy; Taylor, H. Gerry; Brown, Tanya M.; Kirkwood, Michael W.; Stancin, Terry

2013-01-01

Children and adolescents with traumatic brain injury (TBI) often experience behavior difficulties that may arise from problem-solving deficits and impaired self-regulation. However, little is known about the relationship of neurocognitive ability to post-TBI behavioral recovery. To address this question, we examined whether verbal intelligence, as estimated by Vocabulary scores from the Wechsler Abbreviated Scale of Intelligence, predicted improvements in behavior and executive functioning following a problem-solving intervention for adolescents with TBI. 132 adolescents with complicated mild to serve TBI were randomly assigned to a 6 month web-based problem-solving intervention (CAPS; n = 65) or to an internet resource comparison (IRC; n = 67) group. Vocabulary moderated the association between treatment group and improvements in meta-cognitive abilities. Examination of the mean estimates indicated that for those with lower Vocabulary scores, pre-intervention Metacognition Index scores from the Behavior Rating Inventory of Executive Function (BRIEF) did not differ between the groups, but post-intervention scores were significantly lower (more improved) for those in the CAPS group. These findings suggest that low verbal intelligence was associated with greater improvements in executive functioning following the CAPS intervention and that verbal intelligence may have an important role in response to intervention for TBI. Understanding predictors of responsiveness to interventions allows clinicians to tailor treatments to individuals, thus improving efficacy. PMID:23710617

Improved method for predicting protein fold patterns with ensemble classifiers.

PubMed

Chen, W; Liu, X; Huang, Y; Jiang, Y; Zou, Q; Lin, C

2012-01-27

Protein folding is recognized as a critical problem in the field of biophysics in the 21st century. Predicting protein-folding patterns is challenging due to the complex structure of proteins. In an attempt to solve this problem, we employed ensemble classifiers to improve prediction accuracy. In our experiments, 188-dimensional features were extracted based on the composition and physical-chemical property of proteins and 20-dimensional features were selected using a coupled position-specific scoring matrix. Compared with traditional prediction methods, these methods were superior in terms of prediction accuracy. The 188-dimensional feature-based method achieved 71.2% accuracy in five cross-validations. The accuracy rose to 77% when we used a 20-dimensional feature vector. These methods were used on recent data, with 54.2% accuracy. Source codes and dataset, together with web server and software tools for prediction, are available at: http://datamining.xmu.edu.cn/main/~cwc/ProteinPredict.html.

Individual differences in spontaneous analogical transfer.

PubMed

Kubricht, James R; Lu, Hongjing; Holyoak, Keith J

2017-05-01

Research on analogical problem solving has shown that people often fail to spontaneously notice the relevance of a semantically remote source analog when solving a target problem, although they are able to form mappings and derive inferences when given a hint to recall the source. Relatively little work has investigated possible individual differences that predict spontaneous transfer, or how such differences may interact with interventions that facilitate transfer. In this study, fluid intelligence was measured for participants in an analogical problem-solving task, using an abridged version of the Raven's Progressive Matrices (RPM) test. In two experiments, we systematically compared the effect of augmenting verbal descriptions of the source with animations or static diagrams. Solution rates to Duncker's radiation problem were measured across varying source presentation conditions, and participants' understanding of the relevant source material was assessed. The pattern of transfer was best fit by a moderated mediation model: the positive impact of fluid intelligence on spontaneous transfer was mediated by its influence on source comprehension; however, this path was in turn modulated by provision of a supplemental animation via its influence on comprehension of the source. Animated source depictions were most beneficial in facilitating spontaneous transfer for those participants with low scores on the fluid intelligence measure.

Individual differences in mathematical competence predict parietal brain activation during mental calculation.

PubMed

Grabner, Roland H; Ansari, Daniel; Reishofer, Gernot; Stern, Elsbeth; Ebner, Franz; Neuper, Christa

2007-11-01

Functional neuroimaging studies have revealed that parietal brain circuits subserve arithmetic problem solving and that their recruitment dynamically changes as a function of training and development. The present study investigated whether the brain activation during mental calculation is also modulated by individual differences in mathematical competence. Twenty-five adult students were selected from a larger pool based on their performance on standardized tests of intelligence and arithmetic and divided into groups of individuals with relatively lower and higher mathematical competence. These groups did not differ in their non-numerical intelligence or age. In an fMRI block-design, participants had to verify the correctness of single-digit and multi-digit multiplication problems. Analyses revealed that the individuals with higher mathematical competence displayed stronger activation of the left angular gyrus while solving both types of arithmetic problems. Additional correlational analyses corroborated the association between individual differences in mathematical competence and angular gyrus activation, even when variability in task performance was controlled for. These findings demonstrate that the recruitment of the left angular gyrus during arithmetic problem solving underlies individual differences in mathematical ability and suggests a stronger reliance on automatic, language-mediated processes in more competent individuals.

Students’ difficulties in probabilistic problem-solving

NASA Astrophysics Data System (ADS)

Arum, D. P.; Kusmayadi, T. A.; Pramudya, I.

2018-03-01

There are many errors can be identified when students solving mathematics problems, particularly in solving the probabilistic problem. This present study aims to investigate students’ difficulties in solving the probabilistic problem. It focuses on analyzing and describing students errors during solving the problem. This research used the qualitative method with case study strategy. The subjects in this research involve ten students of 9th grade that were selected by purposive sampling. Data in this research involve students’ probabilistic problem-solving result and recorded interview regarding students’ difficulties in solving the problem. Those data were analyzed descriptively using Miles and Huberman steps. The results show that students have difficulties in solving the probabilistic problem and can be divided into three categories. First difficulties relate to students’ difficulties in understanding the probabilistic problem. Second, students’ difficulties in choosing and using appropriate strategies for solving the problem. Third, students’ difficulties with the computational process in solving the problem. Based on the result seems that students still have difficulties in solving the probabilistic problem. It means that students have not able to use their knowledge and ability for responding probabilistic problem yet. Therefore, it is important for mathematics teachers to plan probabilistic learning which could optimize students probabilistic thinking ability.

Brains, brawn and sociality: a hyaena’s tale

PubMed Central

Holekamp, Kay E.; Dantzer, Ben; Stricker, Gregory; Shaw Yoshida, Kathryn C.; Benson-Amram, Sarah

2015-01-01

Theoretically intelligence should evolve to help animals solve specific types of problems posed by the environment, but it remains unclear how environmental complexity or novelty facilitates the evolutionary enhancement of cognitive abilities, or whether domain-general intelligence can evolve in response to domain-specific selection pressures. The social complexity hypothesis, which posits that intelligence evolved to cope with the labile behaviour of conspecific group-mates, has been strongly supported by work on the sociocognitive abilities of primates and other animals. Here we review the remarkable convergence in social complexity between cercopithecine primates and spotted hyaenas, and describe our tests of predictions of the social complexity hypothesis in regard to both cognition and brain size in hyaenas. Behavioural data indicate that there has been remarkable convergence between primates and hyaenas with respect to their abilities in the domain of social cognition. Furthermore, within the family Hyaenidae, our data suggest that social complexity might have contributed to enlargement of the frontal cortex. However, social complexity failed to predict either brain volume or frontal cortex volume in a larger array of mammalian carnivores. To address the question of whether or not social complexity might be able to explain the evolution of domain-general intelligence as well as social cognition in particular, we presented simple puzzle boxes, baited with food and scaled to accommodate body size, to members of 39 carnivore species housed in zoos and found that species with larger brains relative to their body mass were more innovative and more successful at opening the boxes. However, social complexity failed to predict success in solving this problem. Overall our work suggests that, although social complexity enhances social cognition, there are no unambiguous causal links between social complexity and either brain size or performance in problem-solving tasks outside the social domain in mammalian carnivores. PMID:26160980

Can False Memories Prime Problem Solutions for Healthy Older Adults and those with Alzheimer 's Disease?

PubMed

Akhtar, Shazia; Howe, Mark L; Hoepstine, Kedron

2018-06-05

Recent research has shown that false memories can have a positive consequence on human cognition in both children and young adults. The present experiment investigated whether false memories could have similar positive effects by priming solutions to insight-based problems in healthy older adults and people with Alzheimer's disease. Participants were asked to solve compound remote associate task (CRAT) problems, half of which had been preceded by the presentation of Deese/Roediger-McDermott (DRM) lists whose critical lures were also the solutions to those problems. The results showed that regardless of cognitive ability, when the critical lure was falsely recognized, CRAT problems were solved more often and reliably faster than problems that were not primed by a DRM list. When the critical lure was not falsely recognized, CRAT problem solution rates and times were no different from when there was no DRM priming. These findings are consistent with predictions from theories of associative activation and demonstrate the importance of automatic spreading activation processes in memory across the lifespan.

Development of a problem solving evaluation instrument; untangling of specific problem solving assets

NASA Astrophysics Data System (ADS)

Adams, Wendy Kristine

The purpose of my research was to produce a problem solving evaluation tool for physics. To do this it was necessary to gain a thorough understanding of how students solve problems. Although physics educators highly value problem solving and have put extensive effort into understanding successful problem solving, there is currently no efficient way to evaluate problem solving skill. Attempts have been made in the past; however, knowledge of the principles required to solve the subject problem are so absolutely critical that they completely overshadow any other skills students may use when solving a problem. The work presented here is unique because the evaluation tool removes the requirement that the student already have a grasp of physics concepts. It is also unique because I picked a wide range of people and picked a wide range of tasks for evaluation. This is an important design feature that helps make things emerge more clearly. This dissertation includes an extensive literature review of problem solving in physics, math, education and cognitive science as well as descriptions of studies involving student use of interactive computer simulations, the design and validation of a beliefs about physics survey and finally the design of the problem solving evaluation tool. I have successfully developed and validated a problem solving evaluation tool that identifies 44 separate assets (skills) necessary for solving problems. Rigorous validation studies, including work with an independent interviewer, show these assets identified by this content-free evaluation tool are the same assets that students use to solve problems in mechanics and quantum mechanics. Understanding this set of component assets will help teachers and researchers address problem solving within the classroom.

Age differences in everyday problem-solving effectiveness: older adults select more effective strategies for interpersonal problems.

PubMed

Blanchard-Fields, Fredda; Mienaltowski, Andrew; Seay, Renee Baldi

2007-01-01

Using the Everyday Problem Solving Inventory of Cornelius and Caspi, we examined differences in problem-solving strategy endorsement and effectiveness in two domains of everyday functioning (instrumental or interpersonal, and a mixture of the two domains) and for four strategies (avoidance-denial, passive dependence, planful problem solving, and cognitive analysis). Consistent with past research, our research showed that older adults were more problem focused than young adults in their approach to solving instrumental problems, whereas older adults selected more avoidant-denial strategies than young adults when solving interpersonal problems. Overall, older adults were also more effective than young adults when solving everyday problems, in particular for interpersonal problems.

Too upset to think: the interplay of borderline personality features, negative emotions, and social problem solving in the laboratory.

PubMed

Dixon-Gordon, Katherine L; Chapman, Alexander L; Lovasz, Nathalie; Walters, Kris

2011-10-01

Borderline personality disorder (BPD) is associated with poor social problem solving and problems with emotion regulation. In this study, the social problem-solving performance of undergraduates with high (n = 26), mid (n = 32), or low (n = 29) levels of BPD features was assessed with the Social Problem-Solving Inventory-Revised and using the means-ends problem-solving procedure before and after a social rejection stressor. The high-BP group, but not the low-BP group, showed a significant reduction in relevant solutions to social problems and more inappropriate solutions following the negative emotion induction. Increases in self-reported negative emotions during the emotion induction mediated the relationship between BP features and reductions in social problem-solving performance. In addition, the high-BP group demonstrated trait deficits in social problem solving on the Social Problem-Solving Inventory-Revised. These findings suggest that future research must examine social problem solving under differing emotional conditions, and that clinical interventions to improve social problem solving among persons with BP features should focus on responses to emotional contexts.

Refined genetic algorithm -- Economic dispatch example

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

Sheble, G.B.; Brittig, K.

1995-02-01

A genetic-based algorithm is used to solve an economic dispatch (ED) problem. The algorithm utilizes payoff information of perspective solutions to evaluate optimality. Thus, the constraints of classical LaGrangian techniques on unit curves are eliminated. Using an economic dispatch problem as a basis for comparison, several different techniques which enhance program efficiency and accuracy, such as mutation prediction, elitism, interval approximation and penalty factors, are explored. Two unique genetic algorithms are also compared. The results are verified for a sample problem using a classical technique.

An Investigation of Secondary Teachers’ Understanding and Belief on Mathematical Problem Solving

NASA Astrophysics Data System (ADS)

Yuli Eko Siswono, Tatag; Wachidul Kohar, Ahmad; Kurniasari, Ika; Puji Astuti, Yuliani

2016-02-01

Weaknesses on problem solving of Indonesian students as reported by recent international surveys give rise to questions on how Indonesian teachers bring out idea of problem solving in mathematics lesson. An explorative study was undertaken to investigate how secondary teachers who teach mathematics at junior high school level understand and show belief toward mathematical problem solving. Participants were teachers from four cities in East Java province comprising 45 state teachers and 25 private teachers. Data was obtained through questionnaires and written test. The results of this study point out that the teachers understand pedagogical problem solving knowledge well as indicated by high score of observed teachers‘ responses showing understanding on problem solving as instruction as well as implementation of problem solving in teaching practice. However, they less understand on problem solving content knowledge such as problem solving strategies and meaning of problem itself. Regarding teacher's difficulties, teachers admitted to most frequently fail in (1) determining a precise mathematical model or strategies when carrying out problem solving steps which is supported by data of test result that revealed transformation error as the most frequently observed errors in teachers’ work and (2) choosing suitable real situation when designing context-based problem solving task. Meanwhile, analysis of teacher's beliefs on problem solving shows that teachers tend to view both mathematics and how students should learn mathematics as body static perspective, while they tend to believe to apply idea of problem solving as dynamic approach when teaching mathematics.

The Impact of Teacher Training on Creative Writing and Problem-Solving Using Futuristic Scenarios for Creative Problem Solving and Creative Problem Solving Programs

ERIC Educational Resources Information Center

Hayel Al-Srour, Nadia; Al-Ali, Safa M.; Al-Oweidi, Alia

2016-01-01

The present study aims to detect the impact of teacher training on creative writing and problem-solving using both Futuristic scenarios program to solve problems creatively, and creative problem solving. To achieve the objectives of the study, the sample was divided into two groups, the first consist of 20 teachers, and 23 teachers to second…

Leadership emergence in engineering design teams.

PubMed

Guastello, Stephen J

2011-01-01

Leaders emerge from leaderless groups as part of a more complex emerging social structure. Several studies have shown that the emerging structure is aptly described by a swallowtail catastrophe model where the control parameters differ depending on whether creative problem solving, production, coordination-intensive, or emergency management groups are involved. The present study explored creative problem solving further where the participants were engaged in real-world tasks extending over several months rather than short laboratory tasks. Participants were engineering students who were organized into groups of to people who designed, built, and tested a prototype product that would solve a real-world problem. At the th week of work they completed a questionnaire indicating who was most like the leader of their group, second most like the leader, along with other questions about individuals' contributions to the group process. Results showed that the swallowtail model (R = .) exhibited a strong advantage over the linear alternative model (R = .) for predicting leadership emergence. The three control variables were control of the task, creative contributions to the group's work, and facilitating the creative contributions of others.

Water Rockets and Indirect Measurement.

ERIC Educational Resources Information Center

Inman, Duane

1997-01-01

Describes an activity that teaches a number of scientific concepts including indirect measurement, Newton's third law of motion, manipulating and controlling variables, and the scientific method of inquiry. Uses process skills such as observation, inference, prediction, mensuration, and communication as well as problem solving and higher-order…

Designing Effective Supports for Causal Reasoning

ERIC Educational Resources Information Center

Jonassen, David H.; Ionas, Ioan Gelu

2008-01-01

Causal reasoning represents one of the most basic and important cognitive processes that underpin all higher-order activities, such as conceptual understanding and problem solving. Hume called causality the "cement of the universe" [Hume (1739/2000). Causal reasoning is required for making predictions, drawing implications and…

The Adversary System in Low-Level Soviet Economic Decisionmaking.

DTIC Science & Technology

1984-08-01

34- ° .. 78 - capital or a few countertrade agreements, will solve their problems for them. This is markedly different from the overall Soviet pattern...currency countertrade practice, the considerations of this Note would permit further refinement of predictions of Soviet economic decisionmaking that

Mathematic and the Quest for Fundamental Principles of Biology

DTIC Science & Technology

2017-05-05

stochasticity as part of the process, rather than as extrinsic noise. In some sense, like all organisms, we must continually solve inverse problems...predictions that could not be made before, ideally while simultaneously elucidating new mechanisms and proposing new experiments. The meeting concluded with

Problem-solving skills in high school biology: The effectiveness of the IMMEX problem-solving assessment software

NASA Astrophysics Data System (ADS)

Palacio-Cayetano, Joycelin

"Problem-solving through reflective thinking should be both the method and valuable outcome of science instruction in America's schools" proclaimed John Dewey (Gabel, 1995). If the development of problem-solving is a primary goal of science education, more problem-solving opportunities must be an integral part of K-16 education. To examine the effective use of technology in developing and assessing problem-solving skills, a problem-solving authoring, learning, and assessment software, the UCLA IMMEX Program-Interactive Multimedia Exercises-was investigated. This study was a twenty-week quasi-experimental study that was implemented as a control-group time series design among 120 tenth grade students. Both the experimental group (n = 60) and the control group (n = 60) participated in a problem-based learning curriculum; however, the experimental group received regular intensive experiences with IMMEX problem-solving and the control group did not. Problem-solving pretest and posttest were administered to all students. The instruments used were a 35-item Processes of Biological Inquiry Test and an IMMEX problem-solving assessment test, True Roots. Students who participated in the IMMEX Program achieved significant (p <.05) gains in problem-solving skills on both problem-solving assessment instruments. This study provided evidence that IMMEX software is highly efficient in evaluating salient elements of problem-solving. Outputs of students' problem-solving strategies revealed that unsuccessful problem solvers primarily used the following four strategies: (1) no data search strategy, students simply guessed; (2) limited data search strategy leading to insufficient data and premature closing; (3) irrelevant data search strategy, students focus in areas bearing no substantive data; and (4) extensive data search strategy with inadequate integration and analysis. On the contrary, successful problem solvers used the following strategies; (1) focused search strategy coupled with the ability to fill in knowledge gaps by accessing the appropriate resources; (2) targeted search strategy coupled with high level of analytical and integration skills; and (3) focused search strategy coupled with superior discrimination, analytical, and integration skills. The strategies of students who were successful and unsuccessful solving IMMEX problems were consistent with those of expert and novice problem solvers identified in the literature on problem-solving.

Systems Training for Emotional Predictability and Problem Solving Program and Emotion Dysregulation: A Pilot Study.

PubMed

Boccalon, Silvia; Alesiani, Roberta; Giarolli, Laura; Fossati, Andrea

2017-03-01

The aim of this study was to assess the observed changes on emotion dysregulation obtained through the Systems Training for Emotional Predictability and Problem Solving (STEPPS) program. The sample is composed of 24 subjects with a personality disorder with borderline features. All participants filled out the Difficulties in Emotion Regulation Scale (DERS). There was a significant decrease in the DERS total score at the end of the treatment and at 6-month follow-up. Friedman test showed a significant decrease in suicide attempts and hospitalizations over time. The analysis of the DERS subscales showed that "goals" and "impulse" were the two dimensions on which the treatment acted and the changes were stable over time. STEPPS is associated with an improvement in emotion regulation and a reduction in the number of hospitalizations and suicide attempts. The treatment seems to act on the behavioral dimensions of emotion dysregulation like the ability to control impulsive behaviors and to achieve goals.

A randomized controlled trial of a Dutch version of systems training for emotional predictability and problem solving for borderline personality disorder.

PubMed

Bos, Elisabeth H; van Wel, E Bas; Appelo, Martin T; Verbraak, Marc J P M

2010-04-01

Systems Training for Emotional Predictability and Problem Solving (STEPPS) is a group treatment for persons with borderline personality disorder (BPD) that is relatively easy to implement. We investigated the efficacy of a Dutch version of this treatment (VERS). Seventy-nine DSM-IV BPD patients were randomly assigned to STEPPS plus an adjunctive individual therapy, or to treatment as usual. Assessments took place before and after the intervention, and at a 6-month follow-up. STEPPS recipients showed a significantly greater reduction in general psychiatric and BPD-specific symptomatology than subjects assigned to treatment as usual; these differences remained significant at follow-up. STEPPS also led to greater improvement in quality of life, especially at follow-up. No differences in impulsive or parasuicidal behavior were observed. Effect sizes for the differences between the treatments were moderate to large. The results suggest that the brief STEPPS program combined with limited individual therapy can improve BPD-treatment in a number of ways.

A numerical solution of Duffing's equations including the prediction of jump phenomena

NASA Technical Reports Server (NTRS)

Moyer, E. T., Jr.; Ghasghai-Abdi, E.

1987-01-01

Numerical methodology for the solution of Duffing's differential equation is presented. Algorithms for the prediction of multiple equilibrium solutions and jump phenomena are developed. In addition, a filtering algorithm for producing steady state solutions is presented. The problem of a rigidly clamped circular plate subjected to cosinusoidal pressure loading is solved using the developed algorithms (the plate is assumed to be in the geometrically nonlinear range). The results accurately predict regions of solution multiplicity and jump phenomena.

fRMSDPred: Predicting Local RMSD Between Structural Fragments Using Sequence Information

DTIC Science & Technology

2007-04-04

machine learning approaches for estimating the RMSD value of a pair of protein fragments. These estimated fragment-level RMSD values can be used to construct the alignment, assess the quality of an alignment, and identify high-quality alignment segments. We present algorithms to solve this fragment-level RMSD prediction problem using a supervised learning framework based on support vector regression and classification that incorporates protein profiles, predicted secondary structure, effective information encoding schemes, and novel second-order pairwise exponential kernel

Pre-Service Class Teacher' Ability in Solving Mathematical Problems and Skills in Solving Daily Problems

ERIC Educational Resources Information Center

Aljaberi, Nahil M.; Gheith, Eman

2016-01-01

This study aims to investigate the ability of pre-service class teacher at University of Petrain solving mathematical problems using Polya's Techniques, their level of problem solving skills in daily-life issues. The study also investigates the correlation between their ability to solve mathematical problems and their level of problem solving…

An evaluation of scanpath-comparison and machine-learning classification algorithms used to study the dynamics of analogy making.

PubMed

French, Robert M; Glady, Yannick; Thibaut, Jean-Pierre

2017-08-01

In recent years, eyetracking has begun to be used to study the dynamics of analogy making. Numerous scanpath-comparison algorithms and machine-learning techniques are available that can be applied to the raw eyetracking data. We show how scanpath-comparison algorithms, combined with multidimensional scaling and a classification algorithm, can be used to resolve an outstanding question in analogy making-namely, whether or not children's and adults' strategies in solving analogy problems are different. (They are.) We show which of these scanpath-comparison algorithms is best suited to the kinds of analogy problems that have formed the basis of much analogy-making research over the years. Furthermore, we use machine-learning classification algorithms to examine the item-to-item saccade vectors making up these scanpaths. We show which of these algorithms best predicts, from very early on in a trial, on the basis of the frequency of various item-to-item saccades, whether a child or an adult is doing the problem. This type of analysis can also be used to predict, on the basis of the item-to-item saccade dynamics in the first third of a trial, whether or not a problem will be solved correctly.

The Association between Motivation, Affect, and Self-regulated Learning When Solving Problems.

PubMed

Baars, Martine; Wijnia, Lisette; Paas, Fred

2017-01-01

Self-regulated learning (SRL) skills are essential for learning during school years, particularly in complex problem-solving domains, such as biology and math. Although a lot of studies have focused on the cognitive resources that are needed for learning to solve problems in a self-regulated way, affective and motivational resources have received much less research attention. The current study investigated the relation between affect (i.e., Positive Affect and Negative Affect Scale), motivation (i.e., autonomous and controlled motivation), mental effort, SRL skills, and problem-solving performance when learning to solve biology problems in a self-regulated online learning environment. In the learning phase, secondary education students studied video-modeling examples of how to solve hereditary problems, solved hereditary problems which they chose themselves from a set of problems with different complexity levels (i.e., five levels). In the posttest, students solved hereditary problems, self-assessed their performance, and chose a next problem from the set of problems but did not solve these problems. The results from this study showed that negative affect, inaccurate self-assessments during the posttest, and higher perceptions of mental effort during the posttest were negatively associated with problem-solving performance after learning in a self-regulated way.

Prediction of protein-protein interaction network using a multi-objective optimization approach.

PubMed

Chowdhury, Archana; Rakshit, Pratyusha; Konar, Amit

2016-06-01

Protein-Protein Interactions (PPIs) are very important as they coordinate almost all cellular processes. This paper attempts to formulate PPI prediction problem in a multi-objective optimization framework. The scoring functions for the trial solution deal with simultaneous maximization of functional similarity, strength of the domain interaction profiles, and the number of common neighbors of the proteins predicted to be interacting. The above optimization problem is solved using the proposed Firefly Algorithm with Nondominated Sorting. Experiments undertaken reveal that the proposed PPI prediction technique outperforms existing methods, including gene ontology-based Relative Specific Similarity, multi-domain-based Domain Cohesion Coupling method, domain-based Random Decision Forest method, Bagging with REP Tree, and evolutionary/swarm algorithm-based approaches, with respect to sensitivity, specificity, and F1 score.

Hybrid robust predictive optimization method of power system dispatch

DOEpatents

Chandra, Ramu Sharat [Niskayuna, NY; Liu, Yan [Ballston Lake, NY; Bose, Sumit [Niskayuna, NY; de Bedout, Juan Manuel [West Glenville, NY

2011-08-02

A method of power system dispatch control solves power system dispatch problems by integrating a larger variety of generation, load and storage assets, including without limitation, combined heat and power (CHP) units, renewable generation with forecasting, controllable loads, electric, thermal and water energy storage. The method employs a predictive algorithm to dynamically schedule different assets in order to achieve global optimization and maintain the system normal operation.

Identifying Future Scientists: Predicting Persistence into Research Training

PubMed Central

2007-01-01

This study used semistructured interviews and grounded theory to look for characteristics among college undergraduates that predicted persistence into Ph.D. and M.D./Ph.D. training. Participants in the summer undergraduate and postbaccalaureate research programs at the Mayo Clinic College of Medicine were interviewed at the start, near the end, and 8–12 months after their research experience. Of more than 200 themes considered, five characteristics predicted those students who went on to Ph.D. and M.D./Ph.D. training or to M.D. training intending to do research: 1) Curiosity to discover the unknown, 2) Enjoyment of problem solving, 3) A high level of independence, 4) The desire to help others indirectly through research, and 5) A flexible, minimally structured approach to the future. Web-based surveys with different students confirmed the high frequency of curiosity and/or problem solving as the primary reason students planned research careers. No evidence was found for differences among men, women, and minority and nonminority students. Although these results seem logical compared with successful scientists, their constancy, predictive capabilities, and sharp contrast to students who chose clinical medicine were striking. These results provide important insights into selection and motivation of potential biomedical scientists and the early experiences that will motivate them toward research careers. PMID:18056303

Numerical and experimental study of expiratory flow in the case of major upper airway obstructions with fluid structure interaction

NASA Astrophysics Data System (ADS)

Chouly, F.; van Hirtum, A.; Lagrée, P.-Y.; Pelorson, X.; Payan, Y.

2008-02-01

This study deals with the numerical prediction and experimental description of the flow-induced deformation in a rapidly convergent divergent geometry which stands for a simplified tongue, in interaction with an expiratory airflow. An original in vitro experimental model is proposed, which allows measurement of the deformation of the artificial tongue, in condition of major initial airway obstruction. The experimental model accounts for asymmetries in geometry and tissue properties which are two major physiological upper airway characteristics. The numerical method for prediction of the fluid structure interaction is described. The theory of linear elasticity in small deformations has been chosen to compute the mechanical behaviour of the tongue. The main features of the flow are taken into account using a boundary layer theory. The overall numerical method entails finite element solving of the solid problem and finite differences solving of the fluid problem. First, the numerical method predicts the deformation of the tongue with an overall error of the order of 20%, which can be seen as a preliminary successful validation of the theory and simulations. Moreover, expiratory flow limitation is predicted in this configuration. As a result, both the physical and numerical models could be useful to understand this phenomenon reported in heavy snorers and apneic patients during sleep.

Identifying future scientists: predicting persistence into research training.

PubMed

McGee, Richard; Keller, Jill L

2007-01-01

This study used semistructured interviews and grounded theory to look for characteristics among college undergraduates that predicted persistence into Ph.D. and M.D./Ph.D. training. Participants in the summer undergraduate and postbaccalaureate research programs at the Mayo Clinic College of Medicine were interviewed at the start, near the end, and 8-12 months after their research experience. Of more than 200 themes considered, five characteristics predicted those students who went on to Ph.D. and M.D./Ph.D. training or to M.D. training intending to do research: 1) Curiosity to discover the unknown, 2) Enjoyment of problem solving, 3) A high level of independence, 4) The desire to help others indirectly through research, and 5) A flexible, minimally structured approach to the future. Web-based surveys with different students confirmed the high frequency of curiosity and/or problem solving as the primary reason students planned research careers. No evidence was found for differences among men, women, and minority and nonminority students. Although these results seem logical compared with successful scientists, their constancy, predictive capabilities, and sharp contrast to students who chose clinical medicine were striking. These results provide important insights into selection and motivation of potential biomedical scientists and the early experiences that will motivate them toward research careers.

Questioning and reading goals: information-seeking questions asked on scientific texts read under different task conditions.

PubMed

Ishiwa, Koto; Sanjosé, Vicente; Otero, José

2013-09-01

A number of studies report that few questions are asked in classrooms and that many of them are shallow questions. This study investigates the way in which reading goals determine questioning on scientific texts. Reading goals were manipulated through two different tasks: reading for understanding versus reading to solve a problem. A total of 183 university students. In the first and third questioning experiments, the participants read two short texts. Students in one condition were instructed to understand the texts, whereas in the alternative condition they had to read texts to solve a problem. Students were instructed to write down any questions they might have about the texts. The questions were categorized according to the type of underlying obstacle: associative, explanatory, or predictive. The second experiment used a think-aloud methodology to identify the mental representations generated by the students. The two questioning experiments show that the questions asked depend on the reading goals. Significantly more explanation questions were asked in the understanding condition than in the problem-solving condition. Also, the two conditions were found to have a different influence on the generation of association and explanation questions. Very few prediction questions were asked in either condition. The think-aloud experiment revealed that the mental representations attempted by readers under the two conditions were indeed different. In conclusion, the experiments showed that, given a certain textual input, readers' questions depend on the reading goals associated with tasks. © 2012 The British Psychological Society.

Extraction of a group-pair relation: problem-solving relation from web-board documents.

PubMed

Pechsiri, Chaveevan; Piriyakul, Rapepun

2016-01-01

This paper aims to extract a group-pair relation as a Problem-Solving relation, for example a DiseaseSymptom-Treatment relation and a CarProblem-Repair relation, between two event-explanation groups, a problem-concept group as a symptom/CarProblem-concept group and a solving-concept group as a treatment-concept/repair concept group from hospital-web-board and car-repair-guru-web-board documents. The Problem-Solving relation (particularly Symptom-Treatment relation) including the graphical representation benefits non-professional persons by supporting knowledge of primarily solving problems. The research contains three problems: how to identify an EDU (an Elementary Discourse Unit, which is a simple sentence) with the event concept of either a problem or a solution; how to determine a problem-concept EDU boundary and a solving-concept EDU boundary as two event-explanation groups, and how to determine the Problem-Solving relation between these two event-explanation groups. Therefore, we apply word co-occurrence to identify a problem-concept EDU and a solving-concept EDU, and machine-learning techniques to solve a problem-concept EDU boundary and a solving-concept EDU boundary. We propose using k-mean and Naïve Bayes to determine the Problem-Solving relation between the two event-explanation groups involved with clustering features. In contrast to previous works, the proposed approach enables group-pair relation extraction with high accuracy.

Students’ Mathematical Problem-Solving Abilities Through The Application of Learning Models Problem Based Learning

NASA Astrophysics Data System (ADS)

Nasution, M. L.; Yerizon, Y.; Gusmiyanti, R.

2018-04-01

One of the purpose mathematic learning is to develop problem solving abilities. Problem solving is obtained through experience in questioning non-routine. Improving students’ mathematical problem-solving abilities required an appropriate strategy in learning activities one of them is models problem based learning (PBL). Thus, the purpose of this research is to determine whether the problem solving abilities of mathematical students’ who learn to use PBL better than on the ability of students’ mathematical problem solving by applying conventional learning. This research included quasi experiment with static group design and population is students class XI MIA SMAN 1 Lubuk Alung. Class experiment in the class XI MIA 5 and class control in the class XI MIA 6. The instrument of final test students’ mathematical problem solving used essay form. The result of data final test in analyzed with t-test. The result is students’ mathematical problem solving abilities with PBL better then on the ability of students’ mathematical problem solving by applying conventional learning. It’s seen from the high percentage achieved by the group of students who learn to use PBL for each indicator of students’ mathematical problem solving.

Using a general problem-solving strategy to promote transfer.

PubMed

Youssef-Shalala, Amina; Ayres, Paul; Schubert, Carina; Sweller, John

2014-09-01

Cognitive load theory was used to hypothesize that a general problem-solving strategy based on a make-as-many-moves-as-possible heuristic could facilitate problem solutions for transfer problems. In four experiments, school students were required to learn about a topic through practice with a general problem-solving strategy, through a conventional problem solving strategy or by studying worked examples. In Experiments 1 and 2 using junior high school students learning geometry, low knowledge students in the general problem-solving group scored significantly higher on near or far transfer tests than the conventional problem-solving group. In Experiment 3, an advantage for a general problem-solving group over a group presented worked examples was obtained on far transfer tests using the same curriculum materials, again presented to junior high school students. No differences between conditions were found in Experiments 1, 2, or 3 using test problems similar to the acquisition problems. Experiment 4 used senior high school students studying economics and found the general problem-solving group scored significantly higher than the conventional problem-solving group on both similar and transfer tests. It was concluded that the general problem-solving strategy was helpful for novices, but not for students that had access to domain-specific knowledge. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Parent-Teacher Communication about Children with Autism Spectrum Disorder: An Examination of Collaborative Problem-Solving

PubMed Central

Azad, Gazi F.; Kim, Mina; Marcus, Steven C.; Mandell, David S.; Sheridan, Susan M.

2016-01-01

Effective parent-teacher communication involves problem-solving concerns about students. Few studies have examined problem solving interactions between parents and teachers of children with autism spectrum disorder (ASD), with a particular focus on identifying communication barriers and strategies for improving them. This study examined the problem-solving behaviors of parents and teachers of children with ASD. Participants included 18 teachers and 39 parents of children with ASD. Parent-teacher dyads were prompted to discuss and provide a solution for a problem that a student experienced at home and at school. Parents and teachers also reported on their problem-solving behaviors. Results showed that parents and teachers displayed limited use of the core elements of problem-solving. Teachers displayed more problem-solving behaviors than parents. Both groups reported engaging in more problem-solving behaviors than they were observed to display during their discussions. Our findings suggest that teacher and parent training programs should include collaborative approaches to problem-solving. PMID:28392604

Parent-Teacher Communication about Children with Autism Spectrum Disorder: An Examination of Collaborative Problem-Solving.

PubMed

Azad, Gazi F; Kim, Mina; Marcus, Steven C; Mandell, David S; Sheridan, Susan M

2016-12-01

Effective parent-teacher communication involves problem-solving concerns about students. Few studies have examined problem solving interactions between parents and teachers of children with autism spectrum disorder (ASD), with a particular focus on identifying communication barriers and strategies for improving them. This study examined the problem-solving behaviors of parents and teachers of children with ASD. Participants included 18 teachers and 39 parents of children with ASD. Parent-teacher dyads were prompted to discuss and provide a solution for a problem that a student experienced at home and at school. Parents and teachers also reported on their problem-solving behaviors. Results showed that parents and teachers displayed limited use of the core elements of problem-solving. Teachers displayed more problem-solving behaviors than parents. Both groups reported engaging in more problem-solving behaviors than they were observed to display during their discussions. Our findings suggest that teacher and parent training programs should include collaborative approaches to problem-solving.

Errors analysis of problem solving using the Newman stage after applying cooperative learning of TTW type

NASA Astrophysics Data System (ADS)

Rr Chusnul, C.; Mardiyana, S., Dewi Retno

2017-12-01

Problem solving is the basis of mathematics learning. Problem solving teaches us to clarify an issue coherently in order to avoid misunderstanding information. Sometimes there may be mistakes in problem solving due to misunderstanding the issue, choosing a wrong concept or misapplied concept. The problem-solving test was carried out after students were given treatment on learning by using cooperative learning of TTW type. The purpose of this study was to elucidate student problem regarding to problem solving errors after learning by using cooperative learning of TTW type. Newman stages were used to identify problem solving errors in this study. The new research used a descriptive method to find out problem solving errors in students. The subject in this study were students of Vocational Senior High School (SMK) in 10th grade. Test and interview was conducted for data collection. Thus, the results of this study suggested problem solving errors in students after learning by using cooperative learning of TTW type for Newman stages.

Rejection Sensitivity and Depression: Indirect Effects Through Problem Solving.

PubMed

Kraines, Morganne A; Wells, Tony T

2017-01-01

Rejection sensitivity (RS) and deficits in social problem solving are risk factors for depression. Despite their relationship to depression and the potential connection between them, no studies have examined RS and social problem solving together in the context of depression. As such, we examined RS, five facets of social problem solving, and symptoms of depression in a young adult sample. A total of 180 participants completed measures of RS, social problem solving, and depressive symptoms. We used bootstrapping to examine the indirect effect of RS on depressive symptoms through problem solving. RS was positively associated with depressive symptoms. A negative problem orientation, impulsive/careless style, and avoidance style of social problem solving were positively associated with depressive symptoms, and a positive problem orientation was negatively associated with depressive symptoms. RS demonstrated an indirect effect on depressive symptoms through two social problem-solving facets: the tendency to view problems as threats to one's well-being and an avoidance problem-solving style characterized by procrastination, passivity, or overdependence on others. These results are consistent with prior research that found a positive association between RS and depression symptoms, but this is the first study to implicate specific problem-solving deficits in the relationship between RS and depression. Our results suggest that depressive symptoms in high RS individuals may result from viewing problems as threats and taking an avoidant, rather than proactive, approach to dealing with problems. These findings may have implications for problem-solving interventions for rejection sensitive individuals.

The Cyclic Nature of Problem Solving: An Emergent Multidimensional Problem-Solving Framework

ERIC Educational Resources Information Center

Carlson, Marilyn P.; Bloom, Irene

2005-01-01

This paper describes the problem-solving behaviors of 12 mathematicians as they completed four mathematical tasks. The emergent problem-solving framework draws on the large body of research, as grounded by and modified in response to our close observations of these mathematicians. The resulting "Multidimensional Problem-Solving Framework" has four…

Mathematical Problem Solving: A Review of the Literature.

ERIC Educational Resources Information Center

Funkhouser, Charles

The major perspectives on problem solving of the twentieth century are reviewed--associationism, Gestalt psychology, and cognitive science. The results of the review on teaching problem solving and the uses of computers to teach problem solving are included. Four major issues related to the teaching of problem solving are discussed: (1)…

Teaching Problem Solving Skills to Elementary Age Students with Autism

ERIC Educational Resources Information Center

Cote, Debra L.; Jones, Vita L.; Barnett, Crystal; Pavelek, Karin; Nguyen, Hoang; Sparks, Shannon L.

2014-01-01

Students with disabilities need problem-solving skills to promote their success in solving the problems of daily life. The research into problem-solving instruction has been limited for students with autism. Using a problem-solving intervention and the Self Determined Learning Model of Instruction, three elementary age students with autism were…

Learning problem-solving skills in a distance education physics course

NASA Astrophysics Data System (ADS)

Rampho, G. J.; Ramorola, M. Z.

2017-10-01

In this paper we present the results of a study on the effectiveness of combinations of delivery modes of distance education in learning problem-solving skills in a distance education introductory physics course. A problem-solving instruction with the explicit teaching of a problem-solving strategy and worked-out examples were implemented in the course. The study used the ex post facto research design with stratified sampling to investigate the effect of the learning of a problem-solving strategy on the problem-solving performance. The number of problems attempted and the mean frequency of using a strategy in solving problems in the three course presentation modes were compared. The finding of the study indicated that combining the different course presentation modes had no statistically significant effect in the learning of problem-solving skills in the distance education course.

Lemonade's the Name, Simulation's the Game.

ERIC Educational Resources Information Center

Friel, Susan

1983-01-01

Provides a detailed description of Lemonade, a business game designed to introduce elementary and secondary students to the basics of business; i.e., problem solving strategies, hypothesis formulation and testing, trend analysis, prediction, comparative analysis, and effects of such factors as advertising and climatic conditions on sales and…

The Sky Is the Limit.

ERIC Educational Resources Information Center

Learning, 1994

1994-01-01

Pullout pages provide suggestions for teaching elementary students at all levels about the wonders of human ingenuity. The suggestions help students see that great ideas come from the need to solve real-life problems and that one great idea leads to another, so current inventions help predict future inventions. (SM)

Predicting Conflict Management Based on Organizational Commitment and Selected Demographic Variables

ERIC Educational Resources Information Center

Balay, Refik

2007-01-01

The purpose of this study is to investigate the relationship between different levels of organizational commitment (compliance, identification, internalization) of teachers and their different conflict management strategies (compromising, problem solving, forcing, yielding, avoiding). Based on a questionnaire survey of 418 teachers, this study…

Analysis of strong-interaction dynamic stall for laminar flow on airfoils

NASA Technical Reports Server (NTRS)

Gibeling, H. J.; Shamroth, S. J.; Eiseman, P. R.

1978-01-01

A compressible Navier-Stokes solution procedure is applied to the flow about an isolated airfoil. Two major problem areas were investigated. The first area is that of developing a coordinate system and an initial step in this direction has been taken. An airfoil coordinate system obtained from specification of discrete data points developed and the heat conduction equation has been solved in this system. Efforts required to allow the Navier-Stokes equations to be solved in this system are discussed. The second problem area is that of obtaining flow field solutions. Solutions for the flow about a circular cylinder and an isolated airfoil are presented. In the former case, the prediction is shown to be in good agreement with data.

Multitask SVM learning for remote sensing data classification

NASA Astrophysics Data System (ADS)

Leiva-Murillo, Jose M.; Gómez-Chova, Luis; Camps-Valls, Gustavo

2010-10-01

Many remote sensing data processing problems are inherently constituted by several tasks that can be solved either individually or jointly. For instance, each image in a multitemporal classification setting could be taken as an individual task but relation to previous acquisitions should be properly considered. In such problems, different modalities of the data (temporal, spatial, angular) gives rise to changes between the training and test distributions, which constitutes a difficult learning problem known as covariate shift. Multitask learning methods aim at jointly solving a set of prediction problems in an efficient way by sharing information across tasks. This paper presents a novel kernel method for multitask learning in remote sensing data classification. The proposed method alleviates the dataset shift problem by imposing cross-information in the classifiers through matrix regularization. We consider the support vector machine (SVM) as core learner and two regularization schemes are introduced: 1) the Euclidean distance of the predictors in the Hilbert space; and 2) the inclusion of relational operators between tasks. Experiments are conducted in the challenging remote sensing problems of cloud screening from multispectral MERIS images and for landmine detection.

Impact of Cognitive Abilities and Prior Knowledge on Complex Problem Solving Performance – Empirical Results and a Plea for Ecologically Valid Microworlds

PubMed Central

Süß, Heinz-Martin; Kretzschmar, André

2018-01-01

The original aim of complex problem solving (CPS) research was to bring the cognitive demands of complex real-life problems into the lab in order to investigate problem solving behavior and performance under controlled conditions. Up until now, the validity of psychometric intelligence constructs has been scrutinized with regard to its importance for CPS performance. At the same time, different CPS measurement approaches competing for the title of the best way to assess CPS have been developed. In the first part of the paper, we investigate the predictability of CPS performance on the basis of the Berlin Intelligence Structure Model and Cattell’s investment theory as well as an elaborated knowledge taxonomy. In the first study, 137 students managed a simulated shirt factory (Tailorshop; i.e., a complex real life-oriented system) twice, while in the second study, 152 students completed a forestry scenario (FSYS; i.e., a complex artificial world system). The results indicate that reasoning – specifically numerical reasoning (Studies 1 and 2) and figural reasoning (Study 2) – are the only relevant predictors among the intelligence constructs. We discuss the results with reference to the Brunswik symmetry principle. Path models suggest that reasoning and prior knowledge influence problem solving performance in the Tailorshop scenario mainly indirectly. In addition, different types of system-specific knowledge independently contribute to predicting CPS performance. The results of Study 2 indicate that working memory capacity, assessed as an additional predictor, has no incremental validity beyond reasoning. We conclude that (1) cognitive abilities and prior knowledge are substantial predictors of CPS performance, and (2) in contrast to former and recent interpretations, there is insufficient evidence to consider CPS a unique ability construct. In the second part of the paper, we discuss our results in light of recent CPS research, which predominantly utilizes the minimally complex systems (MCS) measurement approach. We suggest ecologically valid microworlds as an indispensable tool for future CPS research and applications. PMID:29867627

Goal-directed tail use in Colombian spider monkeys (Ateles fusciceps rufiventris) is highly lateralized.

PubMed

Nelson, Eliza L; Kendall, Giulianna A

2018-02-01

Behavioral laterality refers to a bias in the use of one side of the body over the other and is commonly studied in paired organs (e.g., hands, feet, eyes, antennae). Less common are reports of laterality in unpaired organs (e.g., trunk, tongue, tail). The goal of the current study was to examine tail use biases across different tasks in the Colombian spider monkey ( Ateles fusciceps rufiventris ) for the first time (N = 14). We hypothesized that task context and task complexity influence tail laterality in spider monkeys, and we predicted that monkeys would exhibit strong preferences for using the tail for manipulation to solve out-of-reach feeding problems, but not for using the tail at rest. Our results show that a subset of spider monkeys solved each of the experimental problems through goal-directed tail use (N = 7). However, some tasks were more difficult than others, given the number of monkeys who solved the tasks. Our results supported our predictions regarding laterality in tail use and only partially replicated prior work on tail use preferences in Geoffroy's spider monkeys ( Ateles geoffroyi ). Overall, skilled tail use, but not resting tail use, was highly lateralized in Colombian spider monkeys. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Relationship Functioning Moderates the Association Between Depressive Symptoms and Life Stressors

PubMed Central

Trombello, Joseph M.; Schoebi, Dominik; Bradbury, Thomas N.

2017-01-01

Data from 172 newlywed couples were collected over the first 4 years of marriage to test how behaviors demonstrated during marital interactions moderate associations between depressive symptoms and subsequent life stressors. Depressive symptoms and behaviors coded from problem-solving and social support interactions were analyzed as predictors of nonmarital stressors that were interpersonal and dependent on the participant's actions. Behavioral codes were found to moderate 3 of 16 symptom-to-life event associations for husbands. Husbands' reports of more depressive symptoms predicted greater levels of stress when husbands' positive affect and hard negative affect during problem-solving were relatively infrequent and when wives made frequent displays of positive behaviors during husbands' support topics. These effects remained after controlling for marital satisfaction. For wives, behavioral moderators did not interact with depressive symptoms to predict changes in stress, but marital satisfaction consistently interacted with depressive symptoms to predict future stressors beyond interpersonal behaviors. Specifically, for wives, stress generation was more evident when relationship satisfaction was low than when it was high. Our results, though different for men and women, suggest that relationship functioning can alter associations between depressive symptoms and life stress in the early years of marriage. PMID:21355647

The Association between Motivation, Affect, and Self-regulated Learning When Solving Problems

PubMed Central

Baars, Martine; Wijnia, Lisette; Paas, Fred

2017-01-01

Self-regulated learning (SRL) skills are essential for learning during school years, particularly in complex problem-solving domains, such as biology and math. Although a lot of studies have focused on the cognitive resources that are needed for learning to solve problems in a self-regulated way, affective and motivational resources have received much less research attention. The current study investigated the relation between affect (i.e., Positive Affect and Negative Affect Scale), motivation (i.e., autonomous and controlled motivation), mental effort, SRL skills, and problem-solving performance when learning to solve biology problems in a self-regulated online learning environment. In the learning phase, secondary education students studied video-modeling examples of how to solve hereditary problems, solved hereditary problems which they chose themselves from a set of problems with different complexity levels (i.e., five levels). In the posttest, students solved hereditary problems, self-assessed their performance, and chose a next problem from the set of problems but did not solve these problems. The results from this study showed that negative affect, inaccurate self-assessments during the posttest, and higher perceptions of mental effort during the posttest were negatively associated with problem-solving performance after learning in a self-regulated way. PMID:28848467

An experience sampling study of learning, affect, and the demands control support model.

PubMed

Daniels, Kevin; Boocock, Grahame; Glover, Jane; Holland, Julie; Hartley, Ruth

2009-07-01

The demands control support model (R. A. Karasek & T. Theorell, 1990) indicates that job control and social support enable workers to engage in problem solving. In turn, problem solving is thought to influence learning and well-being (e.g., anxious affect, activated pleasant affect). Two samples (N = 78, N = 106) provided data up to 4 times per day for up to 5 working days. The extent to which job control was used for problem solving was assessed by measuring the extent to which participants changed aspects of their work activities to solve problems. The extent to which social support was used to solve problems was assessed by measuring the extent to which participants discussed problems to solve problems. Learning mediated the relationship between changing aspects of work activities to solve problems and activated pleasant affect. Learning also mediated the relationship between discussing problems to solve problems and activated pleasant affect. The findings indicated that how individuals use control and support to respond to problem-solving demands is associated with organizational and individual phenomena, such as learning and affective well-being.

What Does (and Doesn't) Make Analogical Problem Solving Easy? A Complexity-Theoretic Perspective

ERIC Educational Resources Information Center

Wareham, Todd; Evans, Patricia; van Rooij, Iris

2011-01-01

Solving new problems can be made easier if one can build on experiences with other problems one has already successfully solved. The ability to exploit earlier problem-solving experiences in solving new problems seems to require several cognitive sub-abilities. Minimally, one needs to be able to retrieve relevant knowledge of earlier solved…

Synthesizing Huber's Problem Solving and Kolb's Learning Cycle: A Balanced Approach to Technical Problem Solving

ERIC Educational Resources Information Center

Kamis, Arnold; Khan, Beverly K.

2009-01-01

How do we model and improve technical problem solving, such as network subnetting? This paper reports an experimental study that tested several hypotheses derived from Kolb's experiential learning cycle and Huber's problem solving model. As subjects solved a network subnetting problem, they mapped their mental processes according to Huber's…

Generalization of Social Skills: Strategies and Results of a Training Program in Problem Solving Skills.

ERIC Educational Resources Information Center

Paraschiv, Irina; Olley, J. Gregory

This paper describes the "Problem Solving for Life" training program which trains adolescents and adults with mental retardation in skills for solving social problems. The program requires group participants to solve social problems by practicing two prerequisite skills (relaxation and positive self-statements) and four problem solving steps: (1)…

Young Children's Analogical Problem Solving: Gaining Insights from Video Displays

ERIC Educational Resources Information Center

Chen, Zhe; Siegler, Robert S.

2013-01-01

This study examined how toddlers gain insights from source video displays and use the insights to solve analogous problems. Two- to 2.5-year-olds viewed a source video illustrating a problem-solving strategy and then attempted to solve analogous problems. Older but not younger toddlers extracted the problem-solving strategy depicted in the video…

Investigating Problem-Solving Perseverance Using Lesson Study

ERIC Educational Resources Information Center

Bieda, Kristen N.; Huhn, Craig

2017-01-01

Problem solving has long been a focus of research and curriculum reform (Kilpatrick 1985; Lester 1994; NCTM 1989, 2000; CCSSI 2010). The importance of problem solving is not new, but the Common Core introduced the idea of making sense of problems and persevering in solving them (CCSSI 2010, p. 6) as an aspect of problem solving. Perseverance is…

Separation of ion types in tandem mass spectrometry data interpretation -- a graph-theoretic approach.

PubMed

Yan, Bo; Pan, Chongle; Olman, Victor N; Hettich, Robert L; Xu, Ying

2004-01-01

Mass spectrometry is one of the most popular analytical techniques for identification of individual proteins in a protein mixture, one of the basic problems in proteomics. It identifies a protein through identifying its unique mass spectral pattern. While the problem is theoretically solvable, it remains a challenging problem computationally. One of the key challenges comes from the difficulty in distinguishing the N- and C-terminus ions, mostly b- and y-ions respectively. In this paper, we present a graph algorithm for solving the problem of separating bfrom y-ions in a set of mass spectra. We represent each spectral peak as a node and consider two types of edges: a type-1 edge connects two peaks possibly of the same ion types and a type-2 edge connects two peaks possibly of different ion types, predicted based on local information. The ion-separation problem is then formulated and solved as a graph partition problem, which is to partition the graph into three subgraphs, namely b-, y-ions and others respectively, so to maximize the total weight of type-1 edges while minimizing the total weight of type-2 edges within each subgraph. We have developed a dynamic programming algorithm for rigorously solving this graph partition problem and implemented it as a computer program PRIME. We have tested PRIME on 18 data sets of high accurate FT-ICR tandem mass spectra and found that it achieved ~90% accuracy for separation of b- and y- ions.

Simultaneous Co-Clustering and Classification in Customers Insight

NASA Astrophysics Data System (ADS)

Anggistia, M.; Saefuddin, A.; Sartono, B.

2017-04-01

Building predictive model based on the heterogeneous dataset may yield many problems, such as less precise in parameter and prediction accuracy. Such problem can be solved by segmenting the data into relatively homogeneous groups and then build a predictive model for each cluster. The advantage of using this strategy usually gives result in simpler models, more interpretable, and more actionable without any loss in accuracy and reliability. This work concerns on marketing data set which recorded a customer behaviour across products. There are some variables describing customer and product as attributes. The basic idea of this approach is to combine co-clustering and classification simultaneously. The objective of this research is to analyse the customer across product characteristics, so the marketing strategy implemented precisely.

HMMBinder: DNA-Binding Protein Prediction Using HMM Profile Based Features.

PubMed

Zaman, Rianon; Chowdhury, Shahana Yasmin; Rashid, Mahmood A; Sharma, Alok; Dehzangi, Abdollah; Shatabda, Swakkhar

2017-01-01

DNA-binding proteins often play important role in various processes within the cell. Over the last decade, a wide range of classification algorithms and feature extraction techniques have been used to solve this problem. In this paper, we propose a novel DNA-binding protein prediction method called HMMBinder. HMMBinder uses monogram and bigram features extracted from the HMM profiles of the protein sequences. To the best of our knowledge, this is the first application of HMM profile based features for the DNA-binding protein prediction problem. We applied Support Vector Machines (SVM) as a classification technique in HMMBinder. Our method was tested on standard benchmark datasets. We experimentally show that our method outperforms the state-of-the-art methods found in the literature.

Problem-solving deficits in Iranian people with borderline personality disorder.

PubMed

Akbari Dehaghi, Ashraf; Kaviani, Hossein; Tamanaeefar, Shima

2014-01-01

Interventions for people suffering from borderline personality disorder (BPD), such as dialectical behavior therapy, often include a problem-solving component. However, there is an absence of published studies examining the problem-solving abilities of this client group in Iran. The study compared inpatients and outpatients with BPD and a control group on problem-solving capabilities in an Iranian sample. It was hypothesized that patients with BPD would have more deficiencies in this area. Fifteen patients with BPD were compared to 15 healthy participants. Means-ends problem-solving task (MEPS) was used to measure problem-solving skills in both groups. BPD group reported less effective strategies in solving problems as opposed to the healthy group. Compared to the control group, participants with BPD provided empirical support for the use of problem-solving interventions with people suffering from BPD. The findings supported the idea that a problem-solving intervention can be efficiently applied either as a stand-alone therapy or in conjunction with other available psychotherapies to treat people with BPD.

Impulsivity as a mediator in the relationship between problem solving and suicidal ideation.

PubMed

Gonzalez, Vivian M; Neander, Lucía L

2018-03-15

This study examined whether three facets of impulsivity previously shown to be associated with suicidal ideation and attempts (negative urgency, lack of premeditation, and lack of perseverance) help to account for the established association between problem solving deficits and suicidal ideation. Emerging adult college student drinkers with a history of at least passive suicidal ideation (N = 387) completed measures of problem solving, impulsivity, and suicidal ideation. A path analysis was conducted to examine the mediating role of impulsivity variables in the association between problem solving (rational problem solving, positive and negative problem orientation, and avoidance style) and suicidal ideation. Direct and indirect associations through impulsivity, particularly negative urgency, were found between problem solving and severity of suicidal ideation. Interventions aimed at teaching problem solving skills, as well as self-efficacy and optimism for solving life problems, may help to reduce impulsivity and suicidal ideation. © 2018 Wiley Periodicals, Inc.

Dynamic motion planning of 3D human locomotion using gradient-based optimization.

PubMed

Kim, Hyung Joo; Wang, Qian; Rahmatalla, Salam; Swan, Colby C; Arora, Jasbir S; Abdel-Malek, Karim; Assouline, Jose G

2008-06-01

Since humans can walk with an infinite variety of postures and limb movements, there is no unique solution to the modeling problem to predict human gait motions. Accordingly, we test herein the hypothesis that the redundancy of human walking mechanisms makes solving for human joint profiles and force time histories an indeterminate problem best solved by inverse dynamics and optimization methods. A new optimization-based human-modeling framework is thus described for predicting three-dimensional human gait motions on level and inclined planes. The basic unknowns in the framework are the joint motion time histories of a 25-degree-of-freedom human model and its six global degrees of freedom. The joint motion histories are calculated by minimizing an objective function such as deviation of the trunk from upright posture that relates to the human model's performance. A variety of important constraints are imposed on the optimization problem, including (1) satisfaction of dynamic equilibrium equations by requiring the model's zero moment point (ZMP) to lie within the instantaneous geometrical base of support, (2) foot collision avoidance, (3) limits on ground-foot friction, and (4) vanishing yawing moment. Analytical forms of objective and constraint functions are presented and discussed for the proposed human-modeling framework in which the resulting optimization problems are solved using gradient-based mathematical programming techniques. When the framework is applied to the modeling of bipedal locomotion on level and inclined planes, acyclic human walking motions that are smooth and realistic as opposed to less natural robotic motions are obtained. The aspects of the modeling framework requiring further investigation and refinement, as well as potential applications of the framework in biomechanics, are discussed.

Improving mathematical problem solving skills through visual media

NASA Astrophysics Data System (ADS)

Widodo, S. A.; Darhim; Ikhwanudin, T.

2018-01-01

The purpose of this article was to find out the enhancement of students’ mathematical problem solving by using visual learning media. The ability to solve mathematical problems is the ability possessed by students to solve problems encountered, one of the problem-solving model of Polya. This preliminary study was not to make a model, but it only took a conceptual approach by comparing the various literature of problem-solving skills by linking visual learning media. The results of the study indicated that the use of learning media had not been appropriated so that the ability to solve mathematical problems was not optimal. The inappropriateness of media use was due to the instructional media that was not adapted to the characteristics of the learners. Suggestions that can be given is the need to develop visual media to increase the ability to solve problems.

The Relationship between Students' Problem Posing and Problem Solving Abilities and Beliefs: A Small-Scale Study with Chinese Elementary School Children

ERIC Educational Resources Information Center

Limin, Chen; Van Dooren, Wim; Verschaffel, Lieven

2013-01-01

The goal of the present study is to investigate the relationship between pupils' problem posing and problem solving abilities, their beliefs about problem posing and problem solving, and their general mathematics abilities, in a Chinese context. Five instruments, i.e., a problem posing test, a problem solving test, a problem posing questionnaire,…

An Investigation of the Effects on Students' Attitudes, Beliefs, and Abilities in Problem Solving and Mathematics after One Year of a Systematic Approach to the Learning of Problem Solving.

ERIC Educational Resources Information Center

Higgins, Karen M.

This study investigated the effects of Oregon's Lane County "Problem Solving in Mathematics" (PSM) materials on middle-school students' attitudes, beliefs, and abilities in problem solving and mathematics. The instructional approach advocated in PSM includes: the direct teaching of five problem-solving skills, weekly challenge problems,…

The role of nonverbal cognitive ability in the association of adverse life events with dysfunctional attitudes and hopelessness in adolescence.

PubMed

Flouri, Eirini; Panourgia, Constantina

2012-10-01

The aim of this study was to test whether nonverbal cognitive ability buffers the effect of life stress (number of adverse life events in the last year) on diatheses for depression. It was expected that, as problem-solving aptitude, nonverbal cognitive ability would moderate the effect of life stress on those diatheses (such as dysfunctional attitudes) that are depressogenic because they represent deficits in information-processing or problem-solving skills, but not on diatheses (such as hopelessness) that are depressogenic because they represent deficits in motivation or effort to apply problem-solving skills. The sample included 558 10- to 19-year-olds from a state secondary school in London. Nonverbal cognitive ability was negatively associated with both dysfunctional attitudes and hopelessness. As expected, nonverbal cognitive ability moderated the association between life adversity and dysfunctional attitudes. However, hopelessness was not related to life stress, and therefore, there was no life stress effect for nonverbal cognitive ability to moderate. This study adds to knowledge about the association between problem-solving ability and depressogenic diatheses. By identifying life stress as a risk factor for dysfunctional attitudes but not hopelessness, it highlights the importance of considering outcome specificity in models predicting adolescent outcomes from adverse life events. Importantly for practice, it suggests that an emphasis on recent life adversity will likely underestimate the true level of hopelessness among adolescents. Copyright © 2012 Elsevier Inc. All rights reserved.

Application of the Digital Image Technology in the Visual Monitoring and Prediction of Shuttering Construction Safety

NASA Astrophysics Data System (ADS)

Ummin, Okumura; Tian, Han; Zhu, Haiyu; Liu, Fuqiang

2018-03-01

Construction safety has always been the first priority in construction process. The common safety problem is the instability of the template support. In order to solve this problem, the digital image measurement technology has been contrived to support real-time monitoring system which can be triggered if the deformation value exceed the specified range. Thus the economic loss could be reduced to the lowest level.

A Systems Engineering Survey of Artificial Intelligence and Smart Sensor Networks in a Network-Centric Environment

DTIC Science & Technology

2009-09-01

problems, to better model the problem solving of computer systems. This research brought about the intertwining of AI and cognitive psychology . Much of...where symbol sequences are sequential intelligent states of the network, and must be classified as normal, abnormal , or unknown. These symbols...is associated with abnormal behavior; and abcbc is associated with unknown behavior, as it fits no known behavior. Predicted outcomes from

The future of computing--new architectures and new technologies.

PubMed

Warren, P

2004-02-01

All modern computers are designed using the 'von Neumann' architecture and built using silicon transistor technology. Both architecture and technology have been remarkably successful. Yet there are a range of problems for which this conventional architecture is not particularly well adapted, and new architectures are being proposed to solve these problems, in particular based on insight from nature. Transistor technology has enjoyed 50 years of continuing progress. However, the laws of physics dictate that within a relatively short time period this progress will come to an end. New technologies, based on molecular and biological sciences as well as quantum physics, are vying to replace silicon, or at least coexist with it and extend its capability. The paper describes these novel architectures and technologies, places them in the context of the kinds of problems they might help to solve, and predicts their possible manner and time of adoption. Finally it describes some key questions and research problems associated with their use.

Coping with Treatment-Related Stress: Effects on Patient Adherence in Hemodialysis.

ERIC Educational Resources Information Center

Christensen, Alan J.; And Others

1995-01-01

Examines the relation of coping to adherence among 57 hemodialysis patients. As predicted, coping efforts involving planful problem solving were associated with more favorable adherence when used in response to stressors involving a relatively controllable aspect of the hemodialysis context. For less controllable stressors, coping efforts…

Understanding and Working with Non-Compliant and Aggressive Young Children

ERIC Educational Resources Information Center

Honig, Alice Sterling

2009-01-01

Interpersonal, familial, and situational risk factors that predict young children's aggression and non-compliance are explored. Here examples of specific techniques and provided to help teachers and parents effectively support children's early development of cooperative and prosocial behaviours as well as problem-solving skills in family and…

General Intelligence Predicts Reasoning Ability Even for Evolutionarily Familiar Content

ERIC Educational Resources Information Center

Kaufman, Scott Barry; DeYoung, Colin G.; Reis, Deidre L.; Gray, Jeremy R.

2011-01-01

The existence of general-purpose cognitive mechanisms related to intelligence, which appear to facilitate all forms of problem solving, conflicts with the strong modularity view of the mind espoused by some evolutionary psychologists. The current study assessed the contribution of general intelligence ("g") to explaining variation in…

Data Mining Algorithms for Classification of Complex Biomedical Data

ERIC Educational Resources Information Center

Lan, Liang

2012-01-01

In my dissertation, I will present my research which contributes to solve the following three open problems from biomedical informatics: (1) Multi-task approaches for microarray classification; (2) Multi-label classification of gene and protein prediction from multi-source biological data; (3) Spatial scan for movement data. In microarray…

A Case for a Process Approach: The Warwick Experience.

ERIC Educational Resources Information Center

Screen, P.

1988-01-01

Describes the cyclical nature of a problem-solving sequence produced from observing children involved in the process. Discusses the generic qualities of science: (1) observing; (2) inferring; (3) classifying; (4) predicting; (5) controlling variables; and (6) hypothesizing. Explains the processes in use and advantages of a process-led course. (RT)

Problems in air traffic management. V., Identification and potential aptitude test measures for selection of tower air traffic controller trainees.

DOT National Transportation Integrated Search

1965-07-01

A study of over 200 Terminal Air Traffic Control Specialists indicated that their training performance could be well predicted by a composite of four aptitude tests measuring: numerical ability, non-verbal abstract reasoning, ability to solve simplif...

The Contribution of Domain-Specific Knowledge in Predicting Students' Proportional Word Problem Solving Performance

ERIC Educational Resources Information Center

Jitendra, Asha K.; Lein, Amy E.; Star, Jon R.; Dupuis, Danielle N.

2013-01-01

Proportional thinking, which requires understanding fractions, ratios, and proportions, is an area of mathematics that is cognitively challenging for many children and adolescents (Fujimura, 2001; Lamon, 2007; Lobato, Ellis, Charles, & Zbiek, 2010; National Mathematics Advisory Panel [NMAP], 2008) and "transcends topical barriers in adult…

Analytic Cognitive Style Predicts Religious and Paranormal Belief

ERIC Educational Resources Information Center

Pennycook, Gordon; Cheyne, James Allan; Seli, Paul; Koehler, Derek J.; Fugelsang, Jonathan A.

2012-01-01

An analytic cognitive style denotes a propensity to set aside highly salient intuitions when engaging in problem solving. We assess the hypothesis that an analytic cognitive style is associated with a history of questioning, altering, and rejecting (i.e., unbelieving) supernatural claims, both religious and paranormal. In two studies, we examined…

The Information Society of the 1990s; Blue Sky and Green Pastures?

ERIC Educational Resources Information Center

Bearman, Toni Carbo

1987-01-01

Predicts how an information-intensive society in the next 10 years will affect the daily life of an individual. Trends described include renewed emphasis of problem solving, increased awareness of the importance of lifelong learning, greater economic challenges, and redirected attention to sociocultural concerns. (EM)

A comparative study of four major approaches to predicting ATES performance

NASA Astrophysics Data System (ADS)

Doughty, C.; Buscheck, T. A.; Bodvarsson, G. S.; Tsang, C. F.

1982-09-01

The International Energy Agency test problem involving Aquifer Thermal Energy Storage was solved using four approaches: the numerical model PF (formerly CCC), the simpler numerical model SFM, and two graphical characterization schemes. Each of the four techniques, with the advantages and disadvantages of each, are discussed.

Activities to Promote Critical Thinking. Classroom Practices in Teaching English, 1986.

ERIC Educational Resources Information Center

National Council of Teachers of English, Urbana, IL.

Intended to involve students in language and communication study in such a way that significant thinking occurs, this collection of teaching ideas outlines ways to teach literature and composition that engage the students in such thinking processes as inferring, sequencing, predicting, classifying, problem solving, and synthesizing. The activities…

Student’s scheme in solving mathematics problems

NASA Astrophysics Data System (ADS)

Setyaningsih, Nining; Juniati, Dwi; Suwarsono

2018-03-01

The purpose of this study was to investigate students’ scheme in solving mathematics problems. Scheme are data structures for representing the concepts stored in memory. In this study, we used it in solving mathematics problems, especially ratio and proportion topics. Scheme is related to problem solving that assumes that a system is developed in the human mind by acquiring a structure in which problem solving procedures are integrated with some concepts. The data were collected by interview and students’ written works. The results of this study revealed are students’ scheme in solving the problem of ratio and proportion as follows: (1) the content scheme, where students can describe the selected components of the problem according to their prior knowledge, (2) the formal scheme, where students can explain in construct a mental model based on components that have been selected from the problem and can use existing schemes to build planning steps, create something that will be used to solve problems and (3) the language scheme, where students can identify terms, or symbols of the components of the problem.Therefore, by using the different strategies to solve the problems, the students’ scheme in solving the ratio and proportion problems will also differ.

Factors of Problem-Solving Competency in a Virtual Chemistry Environment: The Role of Metacognitive Knowledge about Strategies

ERIC Educational Resources Information Center

Scherer, Ronny; Tiemann, Rudiger

2012-01-01

The ability to solve complex scientific problems is regarded as one of the key competencies in science education. Until now, research on problem solving focused on the relationship between analytical and complex problem solving, but rarely took into account the structure of problem-solving processes and metacognitive aspects. This paper,…

Same Old Problem, New Name? Alerting Students to the Nature of the Problem-Solving Process

ERIC Educational Resources Information Center

Yerushalmi, Edit; Magen, Esther

2006-01-01

Students frequently misconceive the process of problem-solving, expecting the linear process required for solving an exercise, rather than the convoluted search process required to solve a genuine problem. In this paper we present an activity designed to foster in students realization and appreciation of the nature of the problem-solving process,…

The Problem-Solving Process in Physics as Observed When Engineering Students at University Level Work in Groups

ERIC Educational Resources Information Center

Gustafsson, Peter; Jonsson, Gunnar; Enghag, Margareta

2015-01-01

The problem-solving process is investigated for five groups of students when solving context-rich problems in an introductory physics course included in an engineering programme. Through transcripts of their conversation, the paths in the problem-solving process have been traced and related to a general problem-solving model. All groups exhibit…

Implementing thinking aloud pair and Pólya problem solving strategies in fractions

NASA Astrophysics Data System (ADS)

Simpol, N. S. H.; Shahrill, M.; Li, H.-C.; Prahmana, R. C. I.

2017-12-01

This study implemented two pedagogical strategies, the Thinking Aloud Pair Problem Solving and Pólya’s Problem Solving, to support students’ learning of fractions. The participants were 51 students (ages 11-13) from two Year 7 classes in a government secondary school in Brunei Darussalam. A mixed method design was employed in the present study, with data collected from the pre- and post-tests, problem solving behaviour questionnaire and interviews. The study aimed to explore if there were differences in the students’ problem solving behaviour before and after the implementation of the problem solving strategies. Results from the Wilcoxon Signed Rank Test revealed a significant difference in the test results regarding student problem solving behaviour, z = -3.68, p = .000, with a higher mean score for the post-test (M = 95.5, SD = 13.8) than for the pre-test (M = 88.9, SD = 15.2). This implied that there was improvement in the students’ problem solving performance from the pre-test to the post-test. Results from the questionnaire showed that more than half of the students increased scores in all four stages of the Pólya’s problem solving strategy, which provided further evidence of the students’ improvement in problem solving.

Genetic influences on insight problem solving: the role of catechol-O-methyltransferase (COMT) gene polymorphisms

PubMed Central

Jiang, Weili; Shang, Siyuan; Su, Yanjie

2015-01-01

People may experience an “aha” moment, when suddenly realizing a solution of a puzzling problem. This experience is called insight problem solving. Several findings suggest that catecholamine-related genes may contribute to insight problem solving, among which the catechol-O-methyltransferase (COMT) gene is the most promising candidate. The current study examined 753 healthy individuals to determine the associations between 7 candidate single nucleotide polymorphisms on the COMT gene and insight problem-solving performance, while considering gender differences. The results showed that individuals carrying A allele of rs4680 or T allele of rs4633 scored significantly higher on insight problem-solving tasks, and the COMT gene rs5993883 combined with gender interacted with correct solutions of insight problems, specifically showing that this gene only influenced insight problem-solving performance in males. This study presents the first investigation of the genetic impact on insight problem solving and provides evidence that highlights the role that the COMT gene plays in insight problem solving. PMID:26528222

Genetic influences on insight problem solving: the role of catechol-O-methyltransferase (COMT) gene polymorphisms.

PubMed

Jiang, Weili; Shang, Siyuan; Su, Yanjie

2015-01-01

People may experience an "aha" moment, when suddenly realizing a solution of a puzzling problem. This experience is called insight problem solving. Several findings suggest that catecholamine-related genes may contribute to insight problem solving, among which the catechol-O-methyltransferase (COMT) gene is the most promising candidate. The current study examined 753 healthy individuals to determine the associations between 7 candidate single nucleotide polymorphisms on the COMT gene and insight problem-solving performance, while considering gender differences. The results showed that individuals carrying A allele of rs4680 or T allele of rs4633 scored significantly higher on insight problem-solving tasks, and the COMT gene rs5993883 combined with gender interacted with correct solutions of insight problems, specifically showing that this gene only influenced insight problem-solving performance in males. This study presents the first investigation of the genetic impact on insight problem solving and provides evidence that highlights the role that the COMT gene plays in insight problem solving.

Understanding Undergraduates’ Problem-Solving Processes †

PubMed Central

Nehm, Ross H.

2010-01-01

Fostering effective problem-solving skills is one of the most longstanding and widely agreed upon goals of biology education. Nevertheless, undergraduate biology educators have yet to leverage many major findings about problem-solving processes from the educational and cognitive science research literatures. This article highlights key facets of problem-solving processes and introduces methodologies that may be used to reveal how undergraduate students perceive and represent biological problems. Overall, successful problem-solving entails a keen sensitivity to problem contexts, disciplined internal representation or modeling of the problem, and the principled management and deployment of cognitive resources. Context recognition tasks, problem representation practice, and cognitive resource management receive remarkably little emphasis in the biology curriculum, despite their central roles in problem-solving success. PMID:23653710

Thinking Process of Naive Problem Solvers to Solve Mathematical Problems

ERIC Educational Resources Information Center

Mairing, Jackson Pasini

2017-01-01

Solving problems is not only a goal of mathematical learning. Students acquire ways of thinking, habits of persistence and curiosity, and confidence in unfamiliar situations by learning to solve problems. In fact, there were students who had difficulty in solving problems. The students were naive problem solvers. This research aimed to describe…

Teaching Problem Solving without Modeling through "Thinking Aloud Pair Problem Solving."

ERIC Educational Resources Information Center

Pestel, Beverly C.

1993-01-01

Reviews research relevant to the problem of unsatisfactory student problem-solving abilities and suggests a teaching strategy that addresses the issue. Author explains how she uses teaching aloud problem solving (TAPS) in college chemistry and presents evaluation data. Among the findings are that the TAPS class got fewer problems completely right,…

Social Problem Solving, Conduct Problems, and Callous-Unemotional Traits in Children

ERIC Educational Resources Information Center

Waschbusch, Daniel A.; Walsh, Trudi M.; Andrade, Brendan F.; King, Sara; Carrey, Normand J.

2007-01-01

This study examined the association between social problem solving, conduct problems (CP), and callous-unemotional (CU) traits in elementary age children. Participants were 53 children (40 boys and 13 girls) aged 7-12 years. Social problem solving was evaluated using the Social Problem Solving Test-Revised, which requires children to produce…

State dependent model predictive control for orbital rendezvous using pulse-width pulse-frequency modulated thrusters

NASA Astrophysics Data System (ADS)

Li, Peng; Zhu, Zheng H.; Meguid, S. A.

2016-07-01

This paper studies the pulse-width pulse-frequency modulation based trajectory planning for orbital rendezvous and proximity maneuvering near a non-cooperative spacecraft in an elliptical orbit. The problem is formulated by converting the continuous control input, output from the state dependent model predictive control, into a sequence of pulses of constant magnitude by controlling firing frequency and duration of constant-magnitude thrusters. The state dependent model predictive control is derived by minimizing the control error of states and control roughness of control input for a safe, smooth and fuel efficient approaching trajectory. The resulting nonlinear programming problem is converted into a series of quadratic programming problem and solved by numerical iteration using the receding horizon strategy. The numerical results show that the proposed state dependent model predictive control with the pulse-width pulse-frequency modulation is able to effectively generate optimized trajectories using equivalent control pulses for the proximity maneuvering with less energy consumption.

Computational structural mechanics for engine structures

NASA Technical Reports Server (NTRS)

Chamis, Christos C.

1988-01-01

The computational structural mechanics (CSM) program at Lewis encompasses the formulation and solution of structural mechanics problems and the development of integrated software systems to computationally simulate the performance, durability, and life of engine structures. It is structured to supplement, complement, and, whenever possible, replace costly experimental efforts. Specific objectives are to investigate unique advantages of parallel and multiprocessing for reformulating and solving structural mechanics and formulating and solving multidisciplinary mechanics and to develop integrated structural system computational simulators for predicting structural performance, evaluating newly developed methods, and identifying and prioritizing improved or missing methods.

Computational structural mechanics for engine structures

NASA Technical Reports Server (NTRS)

Chamis, Christos C.

1989-01-01

The computational structural mechanics (CSM) program at Lewis encompasses the formulation and solution of structural mechanics problems and the development of integrated software systems to computationally simulate the performance, durability, and life of engine structures. It is structured to supplement, complement, and, whenever possible, replace costly experimental efforts. Specific objectives are to investigate unique advantages of parallel and multiprocessing for reformulating and solving structural mechanics and formulating and solving multidisciplinary mechanics and to develop integrated structural system computational simulators for predicting structural performance, evaluating newly developed methods, and identifying and prioritizing improved or missing methods.

Neural Mechanisms of Credit Assignment in a Multicue Environment

PubMed Central

Kolling, Nils; Brown, Joshua W.; Rushworth, Matthew

2016-01-01

In complex environments, many potential cues can guide a decision or be assigned responsibility for the outcome of the decision. We know little, however, about how humans and animals select relevant information sources that should guide behavior. We show that subjects solve this relevance selection and credit assignment problem by selecting one cue and its association with a particular outcome as the main focus of a hypothesis. To do this, we examined learning while using a task design that allowed us to estimate the focus of each subject's hypotheses on a trial-by-trial basis. When a prediction is confirmed by the outcome, then credit for the outcome is assigned to that cue rather than an alternative. Activity in medial frontal cortex is associated with the assignment of credit to the cue that is the main focus of the hypothesis. However, when the outcome disconfirms a prediction, the focus shifts between cues, and the credit for the outcome is assigned to an alternative cue. This process of reselection for credit assignment to an alternative cue is associated with lateral orbitofrontal cortex. SIGNIFICANCE STATEMENT Learners should infer which features of environments are predictive of significant events, such as rewards. This “credit assignment” problem is particularly challenging when any of several cues might be predictive. We show that human subjects solve the credit assignment problem by implicitly “hypothesizing” which cue is relevant for predicting subsequent outcomes, and then credit is assigned according to this hypothesis. This process is associated with a distinctive pattern of activity in a part of medial frontal cortex. By contrast, when unexpected outcomes occur, hypotheses are redirected toward alternative cues, and this process is associated with activity in lateral orbitofrontal cortex. PMID:26818500

Personality, problem solving, and adolescent substance use.

PubMed

Jaffee, William B; D'Zurilla, Thomas J

2009-03-01

The major aim of this study was to examine the role of social problem solving in the relationship between personality and substance use in adolescents. Although a number of studies have identified a relationship between personality and substance use, the precise mechanism by which this occurs is not clear. We hypothesized that problem-solving skills could be one such mechanism. More specifically, we sought to determine whether problem solving mediates, moderates, or both mediates and moderates the relationship between different personality traits and substance use. Three hundred and seven adolescents were administered the Substance Use Profile Scale, the Social Problem-Solving Inventory-Revised, and the Personality Experiences Inventory to assess personality, social problem-solving ability, and substance use, respectively. Results showed that the dimension of rational problem solving (i.e., effective problem-solving skills) significantly mediated the relationship between hopelessness and lifetime alcohol and marijuana use. The theoretical and clinical implications of these results were discussed.

Enhancing chemistry problem-solving achievement using problem categorization

NASA Astrophysics Data System (ADS)

Bunce, Diane M.; Gabel, Dorothy L.; Samuel, John V.

The enhancement of chemistry students' skill in problem solving through problem categorization is the focus of this study. Twenty-four students in a freshman chemistry course for health professionals are taught how to solve problems using the explicit method of problem solving (EMPS) (Bunce & Heikkinen, 1986). The EMPS is an organized approach to problem analysis which includes encoding the information given in a problem (Given, Asked For), relating this to what is already in long-term memory (Recall), and planning a solution (Overall Plan) before a mathematical solution is attempted. In addition to the EMPS training, treatment students receive three 40-minute sessions following achievement tests in which they are taught how to categorize problems. Control students use this time to review the EMPS solutions of test questions. Although problem categorization is involved in one section of the EMPS (Recall), treatment students who received specific training in problem categorization demonstrate significantly higher achievement on combination problems (those problems requiring the use of more than one chemical topic for their solution) at (p = 0.01) than their counterparts. Significantly higher achievement for treatment students is also measured on an unannounced test (p = 0.02). Analysis of interview transcripts of both treatment and control students illustrates a Rolodex approach to problem solving employed by all students in this study. The Rolodex approach involves organizing equations used to solve problems on mental index cards and flipping through them, matching units given when a new problem is to be solved. A second phenomenon observed during student interviews is the absence of a link in the conceptual understanding of the chemical concepts involved in a problem and the problem-solving skills employed to correctly solve problems. This study shows that explicit training in categorization skills and the EMPS can lead to higher achievement in complex problem-solving situations (combination problems and unannounced test). However, such achievement may be limited by the lack of linkages between students' conceptual understanding and improved problem-solving skill.

Non-ambiguous recovery of Biot poroelastic parameters of cellular panels using ultrasonicwaves

NASA Astrophysics Data System (ADS)

Ogam, Erick; Fellah, Z. E. A.; Sebaa, Naima; Groby, J.-P.

2011-03-01

The inverse problem of the recovery of the poroelastic parameters of open-cell soft plastic foam panels is solved by employing transmitted ultrasonic waves (USW) and the Biot-Johnson-Koplik-Champoux-Allard (BJKCA) model. It is shown by constructing the objective functional given by the total square of the difference between predictions from the BJKCA interaction model and experimental data obtained with transmitted USW that the inverse problem is ill-posed, since the functional exhibits several local minima and maxima. In order to solve this problem, which is beyond the capability of most off-the-shelf iterative nonlinear least squares optimization algorithms (such as the Levenberg Marquadt or Nelder-Mead simplex methods), simple strategies are developed. The recovered acoustic parameters are compared with those obtained using simpler interaction models and a method employing asymptotic phase velocity of the transmitted USW. The retrieved elastic moduli are validated by solving an inverse vibration spectroscopy problem with data obtained from beam-like specimens cut from the panels using an equivalent solid elastodynamic model as estimator. The phase velocities are reconstructed using computed, measured resonance frequencies and a time-frequency decomposition of transient waves induced in the beam specimen. These confirm that the elastic parameters recovered using vibration are valid over the frequency range ofstudy.

Decision-Making and Problem-Solving Approaches in Pharmacy Education

PubMed Central

Martin, Lindsay C.; Holdford, David A.

2016-01-01

Domain 3 of the Center for the Advancement of Pharmacy Education (CAPE) 2013 Educational Outcomes recommends that pharmacy school curricula prepare students to be better problem solvers, but are silent on the type of problems they should be prepared to solve. We identified five basic approaches to problem solving in the curriculum at a pharmacy school: clinical, ethical, managerial, economic, and legal. These approaches were compared to determine a generic process that could be applied to all pharmacy decisions. Although there were similarities in the approaches, generic problem solving processes may not work for all problems. Successful problem solving requires identification of the problems faced and application of the right approach to the situation. We also advocate that the CAPE Outcomes make explicit the importance of different approaches to problem solving. Future pharmacists will need multiple approaches to problem solving to adapt to the complexity of health care. PMID:27170823

Decision-Making and Problem-Solving Approaches in Pharmacy Education.

PubMed

Martin, Lindsay C; Donohoe, Krista L; Holdford, David A

2016-04-25

Domain 3 of the Center for the Advancement of Pharmacy Education (CAPE) 2013 Educational Outcomes recommends that pharmacy school curricula prepare students to be better problem solvers, but are silent on the type of problems they should be prepared to solve. We identified five basic approaches to problem solving in the curriculum at a pharmacy school: clinical, ethical, managerial, economic, and legal. These approaches were compared to determine a generic process that could be applied to all pharmacy decisions. Although there were similarities in the approaches, generic problem solving processes may not work for all problems. Successful problem solving requires identification of the problems faced and application of the right approach to the situation. We also advocate that the CAPE Outcomes make explicit the importance of different approaches to problem solving. Future pharmacists will need multiple approaches to problem solving to adapt to the complexity of health care.

Social problem-solving in Chinese baccalaureate nursing students.

PubMed

Fang, Jinbo; Luo, Ying; Li, Yanhua; Huang, Wenxia

2016-11-01

To describe social problem solving in Chinese baccalaureate nursing students. A descriptive cross-sectional study was conducted with a cluster sample of 681 Chinese baccalaureate nursing students. The Chinese version of the Social Problem-Solving scale was used. Descriptive analyses, independent t-test and one-way analysis of variance were applied to analyze the data. The final year nursing students presented the highest scores of positive social problem-solving skills. Students with experiences of self-directed and problem-based learning presented significantly higher scores in Positive Problem Orientation subscale. The group with Critical thinking training experience, however, displayed higher negative problem solving scores compared with nonexperience group. Social problem solving abilities varied based upon teaching-learning strategies. Self-directed and problem-based learning may be recommended as effective way to improve social problem-solving ability. © 2016 Chinese Cochrane Center, West China Hospital of Sichuan University and John Wiley & Sons Australia, Ltd.

Problem Solving and Chemical Equilibrium: Successful versus Unsuccessful Performance.

ERIC Educational Resources Information Center

Camacho, Moises; Good, Ron

1989-01-01

Describes the problem-solving behaviors of experts and novices engaged in solving seven chemical equilibrium problems. Lists 27 behavioral tendencies of successful and unsuccessful problem solvers. Discusses several implications for a problem solving theory, think-aloud techniques, adequacy of the chemistry domain, and chemistry instruction.…

Worry and problem-solving skills and beliefs in primary school children.

PubMed

Parkinson, Monika; Creswell, Cathy

2011-03-01

To examine the association between worry and problem-solving skills and beliefs (confidence and perceived control) in primary school children. Children (8-11 years) were screened using the Penn State Worry Questionnaire for Children. High (N= 27) and low (N= 30) scorers completed measures of anxiety, problem-solving skills (generating alternative solutions to problems, planfulness, and effectiveness of solutions) and problem-solving beliefs (confidence and perceived control). High and low worry groups differed significantly on measures of anxiety and problem-solving beliefs (confidence and control) but not on problem-solving skills. Consistent with findings with adults, worry in children was associated with cognitive distortions, not skills deficits. Interventions for worried children may benefit from a focus on increasing positive problem-solving beliefs. ©2010 The British Psychological Society.

The effectiveness of problem-based learning on students’ problem solving ability in vector analysis course

NASA Astrophysics Data System (ADS)

Mushlihuddin, R.; Nurafifah; Irvan

2018-01-01

The student’s low ability in mathematics problem solving proved to the less effective of a learning process in the classroom. Effective learning was a learning that affects student’s math skills, one of which is problem-solving abilities. Problem-solving capability consisted of several stages: understanding the problem, planning the settlement, solving the problem as planned, re-examining the procedure and the outcome. The purpose of this research was to know: (1) was there any influence of PBL model in improving ability Problem solving of student math in a subject of vector analysis?; (2) was the PBL model effective in improving students’ mathematical problem-solving skills in vector analysis courses? This research was a quasi-experiment research. The data analysis techniques performed from the test stages of data description, a prerequisite test is the normality test, and hypothesis test using the ANCOVA test and Gain test. The results showed that: (1) there was an influence of PBL model in improving students’ math problem-solving abilities in vector analysis courses; (2) the PBL model was effective in improving students’ problem-solving skills in vector analysis courses with a medium category.

Novel applications of multitask learning and multiple output regression to multiple genetic trait prediction.

PubMed

He, Dan; Kuhn, David; Parida, Laxmi

2016-06-15

Given a set of biallelic molecular markers, such as SNPs, with genotype values encoded numerically on a collection of plant, animal or human samples, the goal of genetic trait prediction is to predict the quantitative trait values by simultaneously modeling all marker effects. Genetic trait prediction is usually represented as linear regression models. In many cases, for the same set of samples and markers, multiple traits are observed. Some of these traits might be correlated with each other. Therefore, modeling all the multiple traits together may improve the prediction accuracy. In this work, we view the multitrait prediction problem from a machine learning angle: as either a multitask learning problem or a multiple output regression problem, depending on whether different traits share the same genotype matrix or not. We then adapted multitask learning algorithms and multiple output regression algorithms to solve the multitrait prediction problem. We proposed a few strategies to improve the least square error of the prediction from these algorithms. Our experiments show that modeling multiple traits together could improve the prediction accuracy for correlated traits. The programs we used are either public or directly from the referred authors, such as MALSAR (http://www.public.asu.edu/~jye02/Software/MALSAR/) package. The Avocado data set has not been published yet and is available upon request. dhe@us.ibm.com. © The Author 2016. Published by Oxford University Press.

Effects of Training in Problem Solving on the Problem-Solving Abilities of Gifted Fourth Graders: A Comparison of the Future Problem Solving and Instrumental Enrichment Programs.

ERIC Educational Resources Information Center

Dufner, Hillrey A.; Alexander, Patricia A.

The differential effects of two different types of problem-solving training on the problem-solving abilities of gifted fourth graders were studied. Two successive classes of gifted fourth graders from Weslaco Independent School District (Texas) were pretested with the Coloured Progressive Matrices (CPM) and Thinking Creatively With Pictures…

Step by Step: Biology Undergraduates’ Problem-Solving Procedures during Multiple-Choice Assessment

PubMed Central

Prevost, Luanna B.; Lemons, Paula P.

2016-01-01

This study uses the theoretical framework of domain-specific problem solving to explore the procedures students use to solve multiple-choice problems about biology concepts. We designed several multiple-choice problems and administered them on four exams. We trained students to produce written descriptions of how they solved the problem, and this allowed us to systematically investigate their problem-solving procedures. We identified a range of procedures and organized them as domain general, domain specific, or hybrid. We also identified domain-general and domain-specific errors made by students during problem solving. We found that students use domain-general and hybrid procedures more frequently when solving lower-order problems than higher-order problems, while they use domain-specific procedures more frequently when solving higher-order problems. Additionally, the more domain-specific procedures students used, the higher the likelihood that they would answer the problem correctly, up to five procedures. However, if students used just one domain-general procedure, they were as likely to answer the problem correctly as if they had used two to five domain-general procedures. Our findings provide a categorization scheme and framework for additional research on biology problem solving and suggest several important implications for researchers and instructors. PMID:27909021

Contrast-enhanced spectral mammography in patients with MRI contraindications.

PubMed

Richter, Vivien; Hatterman, Valerie; Preibsch, Heike; Bahrs, Sonja D; Hahn, Markus; Nikolaou, Konstantin; Wiesinger, Benjamin

2017-01-01

Background Contrast-enhanced spectral mammography (CESM) is a novel breast imaging technique providing comparable diagnostic accuracy to breast magnetic resonance imaging (MRI). Purpose To show that CESM in patients with MRI contraindications is feasible, accurate, and useful as a problem-solving tool, and to highlight its limitations. Material and Methods A total of 118 patients with MRI contraindications were examined by CESM. Histology was obtained in 94 lesions and used as gold standard for diagnostic accuracy calculations. Imaging data were reviewed retrospectively for feasibility, accuracy, and technical problems. The diagnostic yield of CESM as a problem-solving tool and for therapy response evaluation was reviewed separately. Results CESM was more accurate than mammography (MG) for lesion categorization (r = 0.731, P < 0.0001 vs. r = 0.279, P = 0.006) and for lesion size estimation (r = 0.738 vs. r = 0.689, P < 0.0001). Negative predictive value of CESM was significantly higher than of MG (85.71% vs. 30.77%, P < 0.0001). When used for problem-solving, CESM changed patient management in 2/8 (25%) cases. Superposition artifacts and timing problems affected diagnostic utility in 3/118 (2.5%) patients. Conclusion CESM is a feasible and accurate alternative for patients with MRI contraindications, but it is necessary to be aware of the method's technical limitations.

A Novel Sensor Selection and Power Allocation Algorithm for Multiple-Target Tracking in an LPI Radar Network

PubMed Central

She, Ji; Wang, Fei; Zhou, Jianjiang

2016-01-01

Radar networks are proven to have numerous advantages over traditional monostatic and bistatic radar. With recent developments, radar networks have become an attractive platform due to their low probability of intercept (LPI) performance for target tracking. In this paper, a joint sensor selection and power allocation algorithm for multiple-target tracking in a radar network based on LPI is proposed. It is found that this algorithm can minimize the total transmitted power of a radar network on the basis of a predetermined mutual information (MI) threshold between the target impulse response and the reflected signal. The MI is required by the radar network system to estimate target parameters, and it can be calculated predictively with the estimation of target state. The optimization problem of sensor selection and power allocation, which contains two variables, is non-convex and it can be solved by separating power allocation problem from sensor selection problem. To be specific, the optimization problem of power allocation can be solved by using the bisection method for each sensor selection scheme. Also, the optimization problem of sensor selection can be solved by a lower complexity algorithm based on the allocated powers. According to the simulation results, it can be found that the proposed algorithm can effectively reduce the total transmitted power of a radar network, which can be conducive to improving LPI performance. PMID:28009819

Computing wave functions in multichannel collisions with non-local potentials using the R-matrix method

NASA Astrophysics Data System (ADS)

Bonitati, Joey; Slimmer, Ben; Li, Weichuan; Potel, Gregory; Nunes, Filomena

2017-09-01

The calculable form of the R-matrix method has been previously shown to be a useful tool in approximately solving the Schrodinger equation in nuclear scattering problems. We use this technique combined with the Gauss quadrature for the Lagrange-mesh method to efficiently solve for the wave functions of projectile nuclei in low energy collisions (1-100 MeV) involving an arbitrary number of channels. We include the local Woods-Saxon potential, the non-local potential of Perey and Buck, a Coulomb potential, and a coupling potential to computationally solve for the wave function of two nuclei at short distances. Object oriented programming is used to increase modularity, and parallel programming techniques are introduced to reduce computation time. We conclude that the R-matrix method is an effective method to predict the wave functions of nuclei in scattering problems involving both multiple channels and non-local potentials. Michigan State University iCER ACRES REU.

Disciplinary Foundations for Solving Interdisciplinary Scientific Problems

ERIC Educational Resources Information Center

Zhang, Dongmei; Shen, Ji

2015-01-01

Problem-solving has been one of the major strands in science education research. But much of the problem-solving research has been conducted on discipline-based contexts; little research has been done on how students, especially individuals, solve interdisciplinary problems. To understand how individuals reason about interdisciplinary problems, we…

Engineering students' experiences and perceptions of workplace problem solving

NASA Astrophysics Data System (ADS)

Pan, Rui

In this study, I interviewed 22 engineering Co-Op students about their workplace problem solving experiences and reflections and explored: 1) Of Co-Op students who experienced workplace problem solving, what are the different ways in which students experience workplace problem solving? 2) How do students perceive a) the differences between workplace problem solving and classroom problem solving and b) in what areas are they prepared by their college education to solve workplace problems? To answer my first research question, I analyzed data through the lens of phenomenography and I conducted thematic analysis to answer my second research question. The results of this study have implications for engineering education and engineering practice. Specifically, the results reveal the different ways students experience workplace problem solving, which provide engineering educators and practicing engineers a better understanding of the nature of workplace engineering. In addition, the results indicate that there is still a gap between classroom engineering and workplace engineering. For engineering educators who aspire to prepare students to be future engineers, it is imperative to design problem solving experiences that can better prepare students with workplace competency.

Problem-Solving Deficits in Iranian People with Borderline Personality Disorder

PubMed Central

Akbari Dehaghi, Ashraf; Kaviani, Hossein; Tamanaeefar, Shima

2014-01-01

Objective: Interventions for people suffering from borderline personality disorder (BPD), such as dialectical behavior therapy, often include a problem-solving component. However, there is an absence of published studies examining the problem-solving abilities of this client group in Iran. The study compared inpatients and outpatients with BPD and a control group on problem-solving capabilities in an Iranian sample. It was hypothesized that patients with BPD would have more deficiencies in this area. Methods: Fifteen patients with BPD were compared to 15 healthy participants. Means-ends problem-solving task (MEPS) was used to measure problem-solving skills in both groups. Results: BPD group reported less effective strategies in solving problems as opposed to the healthy group. Compared to the control group, participants with BPD provided empirical support for the use of problem-solving interventions with people suffering from BPD. Conclusions: The findings supported the idea that a problem-solving intervention can be efficiently applied either as a stand-alone therapy or in conjunction with other available psychotherapies to treat people with BPD. PMID:25798169

Enhancing memory and imagination improves problem solving among individuals with depression.

PubMed

McFarland, Craig P; Primosch, Mark; Maxson, Chelsey M; Stewart, Brandon T

2017-08-01

Recent work has revealed links between memory, imagination, and problem solving, and suggests that increasing access to detailed memories can lead to improved imagination and problem-solving performance. Depression is often associated with overgeneral memory and imagination, along with problem-solving deficits. In this study, we tested the hypothesis that an interview designed to elicit detailed recollections would enhance imagination and problem solving among both depressed and nondepressed participants. In a within-subjects design, participants completed a control interview or an episodic specificity induction prior to completing memory, imagination, and problem-solving tasks. Results revealed that compared to the control interview, the episodic specificity induction fostered increased detail generation in memory and imagination and more relevant steps on the problem-solving task among depressed and nondepressed participants. This study builds on previous work by demonstrating that a brief interview can enhance problem solving among individuals with depression and supports the notion that episodic memory plays a key role in problem solving. It should be noted, however, that the results of the interview are relatively short-lived.

Measuring Family Problem Solving: The Family Problem Solving Diary.

ERIC Educational Resources Information Center

Kieren, Dianne K.

The development and use of the family problem-solving diary are described. The diary is one of several indicators and measures of family problem-solving behavior. It provides a record of each person's perception of day-to-day family problems (what the problem concerns, what happened, who got involved, what those involved did, how the problem…

Problem-Solving After Traumatic Brain Injury in Adolescence: Associations With Functional Outcomes

PubMed Central

Wade, Shari L.; Cassedy, Amy E.; Fulks, Lauren E.; Taylor, H. Gerry; Stancin, Terry; Kirkwood, Michael W.; Yeates, Keith O.; Kurowski, Brad G.

2017-01-01

Objective To examine the association of problem-solving with functioning in youth with traumatic brain injury (TBI). Design Cross-sectional evaluation of pretreatment data from a randomized controlled trial. Setting Four children’s hospitals and 1 general hospital, with level 1 trauma units. Participants Youth, ages 11 to 18 years, who sustained moderate or severe TBI in the last 18 months (N=153). Main Outcome Measures Problem-solving skills were assessed using the Social Problem-Solving Inventory (SPSI) and the Dodge Social Information Processing Short Stories. Everyday functioning was assessed based on a structured clinical interview using the Child and Adolescent Functional Assessment Scale (CAFAS) and via adolescent ratings on the Youth Self Report (YSR). Correlations and multiple regression analyses were used to examine associations among measures. Results The TBI group endorsed lower levels of maladaptive problem-solving (negative problem orientation, careless/impulsive responding, and avoidant style) and lower levels of rational problem-solving, resulting in higher total problem-solving scores for the TBI group compared with a normative sample (P<.001). Dodge Social Information Processing Short Stories dimensions were correlated (r=.23–.37) with SPSI subscales in the anticipated direction. Although both maladaptive (P<.001) and adaptive (P=.006) problem-solving composites were associated with overall functioning on the CAFAS, only maladaptive problem-solving (P<.001) was related to the YSR total when outcomes were continuous. For the both CAFAS and YSR logistic models, maladaptive style was significantly associated with greater risk of impairment (P=.001). Conclusions Problem-solving after TBI differs from normative samples and is associated with functional impairments. The relation of problem-solving deficits after TBI with global functioning merits further investigation, with consideration of the potential effects of problem-solving interventions on functional outcomes. PMID:28389109

Problem-Solving After Traumatic Brain Injury in Adolescence: Associations With Functional Outcomes.

PubMed

Wade, Shari L; Cassedy, Amy E; Fulks, Lauren E; Taylor, H Gerry; Stancin, Terry; Kirkwood, Michael W; Yeates, Keith O; Kurowski, Brad G

2017-08-01

To examine the association of problem-solving with functioning in youth with traumatic brain injury (TBI). Cross-sectional evaluation of pretreatment data from a randomized controlled trial. Four children's hospitals and 1 general hospital, with level 1 trauma units. Youth, ages 11 to 18 years, who sustained moderate or severe TBI in the last 18 months (N=153). Problem-solving skills were assessed using the Social Problem-Solving Inventory (SPSI) and the Dodge Social Information Processing Short Stories. Everyday functioning was assessed based on a structured clinical interview using the Child and Adolescent Functional Assessment Scale (CAFAS) and via adolescent ratings on the Youth Self Report (YSR). Correlations and multiple regression analyses were used to examine associations among measures. The TBI group endorsed lower levels of maladaptive problem-solving (negative problem orientation, careless/impulsive responding, and avoidant style) and lower levels of rational problem-solving, resulting in higher total problem-solving scores for the TBI group compared with a normative sample (P<.001). Dodge Social Information Processing Short Stories dimensions were correlated (r=.23-.37) with SPSI subscales in the anticipated direction. Although both maladaptive (P<.001) and adaptive (P=.006) problem-solving composites were associated with overall functioning on the CAFAS, only maladaptive problem-solving (P<.001) was related to the YSR total when outcomes were continuous. For the both CAFAS and YSR logistic models, maladaptive style was significantly associated with greater risk of impairment (P=.001). Problem-solving after TBI differs from normative samples and is associated with functional impairments. The relation of problem-solving deficits after TBI with global functioning merits further investigation, with consideration of the potential effects of problem-solving interventions on functional outcomes. Copyright © 2017 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Use of Genetic Algorithms to solve Inverse Problems in Relativistic Hydrodynamics

NASA Astrophysics Data System (ADS)

Guzmán, F. S.; González, J. A.

2018-04-01

We present the use of Genetic Algorithms (GAs) as a strategy to solve inverse problems associated with models of relativistic hydrodynamics. The signal we consider to emulate an observation is the density of a relativistic gas, measured at a point where a shock is traveling. This shock is generated numerically out of a Riemann problem with mildly relativistic conditions. The inverse problem we propose is the prediction of the initial conditions of density, velocity and pressure of the Riemann problem that gave origin to that signal. For this we use the density, velocity and pressure of the gas at both sides of the discontinuity, as the six genes of an organism, initially with random values within a tolerance. We then prepare an initial population of N of these organisms and evolve them using methods based on GAs. In the end, the organism with the best fitness of each generation is compared to the signal and the process ends when the set of initial conditions of the organisms of a later generation fit the Signal within a tolerance.

New Ideas on the Design of the Web-Based Learning System Oriented to Problem Solving from the Perspective of Question Chain and Learning Community

ERIC Educational Resources Information Center

Zhang, Yin; Chu, Samuel K. W.

2016-01-01

In recent years, a number of models concerning problem solving systems have been put forward. However, many of them stress on technology and neglect the research of problem solving itself, especially the learning mechanism related to problem solving. In this paper, we analyze the learning mechanism of problem solving, and propose that when…

Problem-solving rubrics revisited: Attending to the blending of informal conceptual and formal mathematical reasoning

NASA Astrophysics Data System (ADS)

Hull, Michael M.; Kuo, Eric; Gupta, Ayush; Elby, Andrew

2013-06-01

Much research in engineering and physics education has focused on improving students’ problem-solving skills. This research has led to the development of step-by-step problem-solving strategies and grading rubrics to assess a student’s expertise in solving problems using these strategies. These rubrics value “communication” between the student’s qualitative description of the physical situation and the student’s formal mathematical descriptions (usually equations) at two points: when initially setting up the equations, and when evaluating the final mathematical answer for meaning and plausibility. We argue that (i) neither the rubrics nor the associated problem-solving strategies explicitly value this kind of communication during mathematical manipulations of the chosen equations, and (ii) such communication is an aspect of problem-solving expertise. To make this argument, we present a case study of two students, Alex and Pat, solving the same kinematics problem in clinical interviews. We argue that Pat’s solution, which connects manipulation of equations to their physical interpretation, is more expertlike than Alex’s solution, which uses equations more algorithmically. We then show that the types of problem-solving rubrics currently available do not discriminate between these two types of solutions. We conclude that problem-solving rubrics should be revised or repurposed to more accurately assess problem-solving expertise.

Examining Tasks that Facilitate the Experience of Incubation While Problem-Solving

ERIC Educational Resources Information Center

Both, Lilly; Needham, Douglas; Wood, Eileen

2004-01-01

The three studies presented here contrasted the problem-solving outcomes of university students when a break was provided or not provided during a problem-solving session. In addition, two studies explored the effect of providing hints (priming) and the placement of hints during the problem-solving session. First, the ability to solve a previously…

A Survey of Computational Intelligence Techniques in Protein Function Prediction

PubMed Central

Tiwari, Arvind Kumar; Srivastava, Rajeev

2014-01-01

During the past, there was a massive growth of knowledge of unknown proteins with the advancement of high throughput microarray technologies. Protein function prediction is the most challenging problem in bioinformatics. In the past, the homology based approaches were used to predict the protein function, but they failed when a new protein was different from the previous one. Therefore, to alleviate the problems associated with homology based traditional approaches, numerous computational intelligence techniques have been proposed in the recent past. This paper presents a state-of-the-art comprehensive review of various computational intelligence techniques for protein function predictions using sequence, structure, protein-protein interaction network, and gene expression data used in wide areas of applications such as prediction of DNA and RNA binding sites, subcellular localization, enzyme functions, signal peptides, catalytic residues, nuclear/G-protein coupled receptors, membrane proteins, and pathway analysis from gene expression datasets. This paper also summarizes the result obtained by many researchers to solve these problems by using computational intelligence techniques with appropriate datasets to improve the prediction performance. The summary shows that ensemble classifiers and integration of multiple heterogeneous data are useful for protein function prediction. PMID:25574395

The profile of students’ problem-solving skill in physics across interest program in the secondary school

NASA Astrophysics Data System (ADS)

Jua, S. K.; Sarwanto; Sukarmin

2018-05-01

Problem-solving skills are important skills in physics. However, according to some researchers, the problem-solving skill of Indonesian students’ problem in physics learning is categorized still low. The purpose of this study was to identify the profile of problem-solving skills of students who follow the across the interests program of physics. The subjects of the study were high school students of Social Sciences, grade X. The type of this research was descriptive research. The data which used to analyze the problem-solving skills were obtained through student questionnaires and the test results with impulse materials and collision. From the descriptive analysis results, the percentage of students’ problem-solving skill based on the test was 52.93% and indicators respectively. These results indicated that students’ problem-solving skill is categorized low.

A research strategy for the dynamic study of students' concepts and problem solving strategies using science software

NASA Astrophysics Data System (ADS)

Krajcik, Joseph S.; Simmons, Patricia E.; Lunetta, Vincent N.

Microcomputers and appropriate software have the potential to help students learn. They can also serve as appropriate media for investigating how students learn. In this article we describe a research strategy examining learning and behavior when students interacted with microcomputers and software. Results from two preliminary studies illustrate the strategy.A major feature of the strategy included recording students interacting with microcomputer software interfaced with a VCR. The VCR recorded the video output from a microcomputer and students' verbal commentary via microphone input. This technique allowed students' comments about their observations, perceptions, predictions, explanations, and decisions to be recorded simultaneously with their computer input and the display on the microcomputer monitor.The research strategy described can provide important information about cognitive and affective behaviors of students engaged in using instructional software. Research studies utilizing this strategy can enhance our understanding of how students develop and employ important concepts and scientific relationships, how students develop problem-solving skills and solve problems, and how they interact with instructional software. Results of such studies have important implications for teaching and for the design of instructional software.

Executive Functions Contribute Uniquely to Reading Competence in Minority Youth.

PubMed

Jacobson, Lisa A; Koriakin, Taylor; Lipkin, Paul; Boada, Richard; Frijters, Jan C; Lovett, Maureen W; Hill, Dina; Willcutt, Erik; Gottwald, Stephanie; Wolf, Maryanne; Bosson-Heenan, Joan; Gruen, Jeffrey R; Mahone, E Mark

Competent reading requires various skills beyond those for basic word reading (i.e., core language skills, rapid naming, phonological processing). Contributing "higher-level" or domain-general processes include information processing speed and executive functions (working memory, strategic problem solving, attentional switching). Research in this area has relied on largely Caucasian samples, with limited representation of children from racial or ethnic minority groups. This study examined contributions of executive skills to reading competence in 761 children of minority backgrounds. Hierarchical linear regressions examined unique contributions of executive functions (EF) to word reading, fluency, and comprehension. EF contributed uniquely to reading performance, over and above reading-related language skills; working memory contributed uniquely to all components of reading; while attentional switching, but not problem solving, contributed to isolated and contextual word reading and reading fluency. Problem solving uniquely predicted comprehension, suggesting that this skill may be especially important for reading comprehension in minority youth. Attentional switching may play a unique role in development of reading fluency in minority youth, perhaps as a result of the increased demand for switching between spoken versus written dialects. Findings have implications for educational and clinical practice with regard to reading instruction, remedial reading intervention, and assessment of individuals with reading difficulty.

The brain and the law.

PubMed Central

Chorvat, Terrence; McCabe, Kevin

2004-01-01

Much has been written about how law as an institution has developed to solve many problems that human societies face. Inherent in all of these explanations are models of how humans make decisions. This article discusses what current neuroscience research tells us about the mechanisms of human decision making of particular relevance to law. This research indicates that humans are both more capable of solving many problems than standard economic models predict, but also limited in ways those models ignore. This article discusses how law is both shaped by our cognitive processes and also shapes them. The article considers some of the implications of this research for improving our understanding of how our current legal regimes operate and how the law can be structured to take advantage of our neural mechanisms to improve social welfare. PMID:15590613

A New Problem-Posing Approach Based on Problem-Solving Strategy: Analyzing Pre-Service Primary School Teachers' Performance

ERIC Educational Resources Information Center

Kiliç, Çigdem

2017-01-01

This study examined pre-service primary school teachers' performance in posing problems that require knowledge of problem-solving strategies. Quantitative and qualitative methods were combined. The 120 participants were asked to pose a problem that could be solved by using the find-a-pattern a particular problem-solving strategy. After that,…

Case of Two Electrostatics Problems: Can Providing a Diagram Adversely Impact Introductory Physics Students' Problem Solving Performance?

ERIC Educational Resources Information Center

Maries, Alexandru; Singh, Chandralekha

2018-01-01

Drawing appropriate diagrams is a useful problem solving heuristic that can transform a problem into a representation that is easier to exploit for solving it. One major focus while helping introductory physics students learn effective problem solving is to help them understand that drawing diagrams can facilitate problem solution. We conducted an…

School Leaders' Problem Framing: A Sense-Making Approach to Problem-Solving Processes of Beginning School Leaders

ERIC Educational Resources Information Center

Sleegers, Peter; Wassink, Hartger; van Veen, Klaas; Imants, Jeroen

2009-01-01

In addition to cognitive research on school leaders' problem solving, this study focuses on the situated and personal nature of problem framing by combining insights from cognitive research on problem solving and sense-making theory. The study reports the results of a case study of two school leaders solving problems in their daily context by…

The Place of Problem Solving in Contemporary Mathematics Curriculum Documents

ERIC Educational Resources Information Center

Stacey, Kaye

2005-01-01

This paper reviews the presentation of problem solving and process aspects of mathematics in curriculum documents from Australia, UK, USA and Singapore. The place of problem solving in the documents is reviewed and contrasted, and illustrative problems from teachers' support materials are used to demonstrate how problem solving is now more often…

Translation among Symbolic Representations in Problem-Solving. Revised.

ERIC Educational Resources Information Center

Shavelson, Richard J.; And Others

This study investigated the relationships among the symbolic representation of problems given to students to solve, the mental representations they use to solve the problems, and the accuracy of their solutions. Twenty eleventh-grade science students were asked to think aloud as they solved problems on the ideal gas laws. The problems were…

Using Students' Representations Constructed during Problem Solving to Infer Conceptual Understanding

ERIC Educational Resources Information Center

Domin, Daniel; Bodner, George

2012-01-01

The differences in the types of representations constructed during successful and unsuccessful problem-solving episodes were investigated within the context of graduate students working on problems that involve concepts from 2D-NMR. Success at problem solving was established by having the participants solve five problems relating to material just…

Errors and Understanding: The Effects of Error-Management Training on Creative Problem-Solving

ERIC Educational Resources Information Center

Robledo, Issac C.; Hester, Kimberly S.; Peterson, David R.; Barrett, Jamie D.; Day, Eric A.; Hougen, Dean P.; Mumford, Michael D.

2012-01-01

People make errors in their creative problem-solving efforts. The intent of this article was to assess whether error-management training would improve performance on creative problem-solving tasks. Undergraduates were asked to solve an educational leadership problem known to call for creative thought where problem solutions were scored for…

Encouraging Sixth-Grade Students' Problem-Solving Performance by Teaching through Problem Solving

ERIC Educational Resources Information Center

Bostic, Jonathan D.; Pape, Stephen J.; Jacobbe, Tim

2016-01-01

This teaching experiment provided students with continuous engagement in a problem-solving based instructional approach during one mathematics unit. Three sections of sixth-grade mathematics were sampled from a school in Florida, U.S.A. and one section was randomly assigned to experience teaching through problem solving. Students' problem-solving…

King Oedipus and the Problem Solving Process.

ERIC Educational Resources Information Center

Borchardt, Donald A.

An analysis of the problem solving process reveals at least three options: (1) finding the cause, (2) solving the problem, and (3) anticipating potential problems. These methods may be illustrated by examining "Oedipus Tyrannus," a play in which a king attempts to deal with a problem that appears to be beyond his ability to solve, and…

Problem Solving with the Elementary Youngster.

ERIC Educational Resources Information Center

Swartz, Vicki

This paper explores research on problem solving and suggests a problem-solving approach to elementary school social studies, using a culture study of the ancient Egyptians and King Tut as a sample unit. The premise is that problem solving is particularly effective in dealing with problems which do not have one simple and correct answer but rather…

The needs analysis of learning Inventive Problem Solving for technical and vocational students

NASA Astrophysics Data System (ADS)

Sai'en, Shanty; Tze Kiong, Tee; Yunos, Jailani Md; Foong, Lee Ming; Heong, Yee Mei; Mohaffyza Mohamad, Mimi

2017-08-01

Malaysian Ministry of Education highlighted in their National Higher Education Strategic plan that higher education’s need to focus adopting 21st century skills in order to increase a graduate’s employability. Current research indicates that most graduate lack of problem solving skills to help them securing the job. Realising the important of this skill hence an alternative way suggested as an option for high institution’s student to solve their problem. This study was undertaken to measure the level of problem solving skills, identify the needs of learning inventive problem solving skills and the needs of developing an Inventive problem solving module. Using a questionnaire, the study sampled 132 students from Faculty of Technical and Vocational Education. Findings indicated that majority of the students fail to define what is an inventive problem and the root cause of a problem. They also unable to state the objectives and goal thus fail to solve the problem. As a result, the students agreed on the developing Inventive Problem Solving Module to assist them.

Automation and adaptation: Nurses' problem-solving behavior following the implementation of bar coded medication administration technology.

PubMed

Holden, Richard J; Rivera-Rodriguez, A Joy; Faye, Héléne; Scanlon, Matthew C; Karsh, Ben-Tzion

2013-08-01

The most common change facing nurses today is new technology, particularly bar coded medication administration technology (BCMA). However, there is a dearth of knowledge on how BCMA alters nursing work. This study investigated how BCMA technology affected nursing work, particularly nurses' operational problem-solving behavior. Cognitive systems engineering observations and interviews were conducted after the implementation of BCMA in three nursing units of a freestanding pediatric hospital. Problem-solving behavior, associated problems, and goals, were specifically defined and extracted from observed episodes of care. Three broad themes regarding BCMA's impact on problem solving were identified. First, BCMA allowed nurses to invent new problem-solving behavior to deal with pre-existing problems. Second, BCMA made it difficult or impossible to apply some problem-solving behaviors that were commonly used pre-BCMA, often requiring nurses to use potentially risky workarounds to achieve their goals. Third, BCMA created new problems that nurses were either able to solve using familiar or novel problem-solving behaviors, or unable to solve effectively. Results from this study shed light on hidden hazards and suggest three critical design needs: (1) ecologically valid design; (2) anticipatory control; and (3) basic usability. Principled studies of the actual nature of clinicians' work, including problem solving, are necessary to uncover hidden hazards and to inform health information technology design and redesign.

Automation and adaptation: Nurses’ problem-solving behavior following the implementation of bar coded medication administration technology

PubMed Central

Holden, Richard J.; Rivera-Rodriguez, A. Joy; Faye, Héléne; Scanlon, Matthew C.; Karsh, Ben-Tzion

2012-01-01

The most common change facing nurses today is new technology, particularly bar coded medication administration technology (BCMA). However, there is a dearth of knowledge on how BCMA alters nursing work. This study investigated how BCMA technology affected nursing work, particularly nurses’ operational problem-solving behavior. Cognitive systems engineering observations and interviews were conducted after the implementation of BCMA in three nursing units of a freestanding pediatric hospital. Problem-solving behavior, associated problems, and goals, were specifically defined and extracted from observed episodes of care. Three broad themes regarding BCMA’s impact on problem solving were identified. First, BCMA allowed nurses to invent new problem-solving behavior to deal with pre-existing problems. Second, BCMA made it difficult or impossible to apply some problem-solving behaviors that were commonly used pre-BCMA, often requiring nurses to use potentially risky workarounds to achieve their goals. Third, BCMA created new problems that nurses were either able to solve using familiar or novel problem-solving behaviors, or unable to solve effectively. Results from this study shed light on hidden hazards and suggest three critical design needs: (1) ecologically valid design; (2) anticipatory control; and (3) basic usability. Principled studies of the actual nature of clinicians’ work, including problem solving, are necessary to uncover hidden hazards and to inform health information technology design and redesign. PMID:24443642

Do problem-solving skills affect success in nursing process applications? An application among Turkish nursing students.

PubMed

Bayindir Çevik, Ayfer; Olgun, Nermin

2015-04-01

This study aimed to determine the relationship between problem-solving and nursing process application skills of nursing. This is a longitudinal and correlational study. The sample included 71 students. An information form, Problem-Solving Inventory, and nursing processes the students presented at the end of clinical courses were used for data collection. Although there was no significant relationship between problem-solving skills and nursing process grades, improving problem-solving skills increased successful grades. Problem-solving skills and nursing process skills can be concomitantly increased. Students were suggested to use critical thinking, practical approaches, and care plans, as well as revising nursing processes in order to improve their problem-solving skills and nursing process application skills. © 2014 NANDA International, Inc.

Modification of the nuclear landscape in the inverse problem framework using the generalized Bethe-Weizsäcker mass formula

NASA Astrophysics Data System (ADS)

Mavrodiev, S. Cht.; Deliyergiyev, M. A.

We formalized the nuclear mass problem in the inverse problem framework. This approach allows us to infer the underlying model parameters from experimental observation, rather than to predict the observations from the model parameters. The inverse problem was formulated for the numerically generalized semi-empirical mass formula of Bethe and von Weizsäcker. It was solved in a step-by-step way based on the AME2012 nuclear database. The established parametrization describes the measured nuclear masses of 2564 isotopes with a maximum deviation less than 2.6MeV, starting from the number of protons and number of neutrons equal to 1. The explicit form of unknown functions in the generalized mass formula was discovered in a step-by-step way using the modified least χ2 procedure, that realized in the algorithms which were developed by Lubomir Aleksandrov to solve the nonlinear systems of equations via the Gauss-Newton method, lets us to choose the better one between two functions with same χ2. In the obtained generalized model, the corrections to the binding energy depend on nine proton (2, 8, 14, 20, 28, 50, 82, 108, 124) and ten neutron (2, 8, 14, 20, 28, 50, 82, 124, 152, 202) magic numbers as well on the asymptotic boundaries of their influence. The obtained results were compared with the predictions of other models.

Adaptive adjustment of interval predictive control based on combined model and application in shell brand petroleum distillation tower

NASA Astrophysics Data System (ADS)

Sun, Chao; Zhang, Chunran; Gu, Xinfeng; Liu, Bin

2017-10-01

Constraints of the optimization objective are often unable to be met when predictive control is applied to industrial production process. Then, online predictive controller will not find a feasible solution or a global optimal solution. To solve this problem, based on Back Propagation-Auto Regressive with exogenous inputs (BP-ARX) combined control model, nonlinear programming method is used to discuss the feasibility of constrained predictive control, feasibility decision theorem of the optimization objective is proposed, and the solution method of soft constraint slack variables is given when the optimization objective is not feasible. Based on this, for the interval control requirements of the controlled variables, the slack variables that have been solved are introduced, the adaptive weighted interval predictive control algorithm is proposed, achieving adaptive regulation of the optimization objective and automatically adjust of the infeasible interval range, expanding the scope of the feasible region, and ensuring the feasibility of the interval optimization objective. Finally, feasibility and effectiveness of the algorithm is validated through the simulation comparative experiments.

Coping and sickness absence

PubMed Central

Schaufeli, Wilmar B.; van Dijk, Frank J. H.; Blonk, Roland W. B.

2007-01-01

Objectives The aim of this study is to examine the role of coping styles in sickness absence. In line with findings that contrast the reactive–passive focused strategies, problem-solving strategies are generally associated with positive results in terms of well-being and overall health outcomes; our hypothesis is that such strategies are positively related to a low frequency of sickness absence and with short lengths (total number of days absent) and durations (mean duration per spell). Methods Using a prospective design, employees’ (N = 3,628) responses on a self-report coping inventory are used to predict future registered sickness absence (i.e. frequency, length, duration, and median time before the onset of a new sick leave period). Results and conclusions In accordance with our hypothesis, and after adjustment for potential confounders, employees with an active problem-solving coping strategy are less likely to drop out because of sickness absence in terms of frequency, length (longer than 14 days), and duration (more than 7 days) of sickness absence. This positive effect is observed in the case of seeking social support only for the duration of sickness absence and in the case of palliative reaction only for the length and frequency of absence. In contrast, an avoidant coping style, representing a reactive–passive strategy, increases the likelihood of frequent absences significantly, as well as the length and duration of sickness absence. Expression of emotions, representing another reactive–passive strategy, has no effect on future sickness absenteeism. The median time before the onset of a new episode of absenteeism is significantly extended for active problem-solving and reduced for avoidance and for a palliative response. The results of the present study support the notion that problem-solving coping and reactive–passive strategies are inextricably connected to frequency, duration, length and onset of sickness absence. Especially, active problem-solving decreases the chance of future sickness absence. PMID:17701200

Coping and sickness absence.

PubMed

van Rhenen, Willem; Schaufeli, Wilmar B; van Dijk, Frank J H; Blonk, Roland W B

2008-02-01

The aim of this study is to examine the role of coping styles in sickness absence. In line with findings that contrast the reactive-passive focused strategies, problem-solving strategies are generally associated with positive results in terms of well-being and overall health outcomes; our hypothesis is that such strategies are positively related to a low frequency of sickness absence and with short lengths (total number of days absent) and durations (mean duration per spell). Using a prospective design, employees' (N = 3,628) responses on a self-report coping inventory are used to predict future registered sickness absence (i.e. frequency, length, duration, and median time before the onset of a new sick leave period). In accordance with our hypothesis, and after adjustment for potential confounders, employees with an active problem-solving coping strategy are less likely to drop out because of sickness absence in terms of frequency, length (longer than 14 days), and duration (more than 7 days) of sickness absence. This positive effect is observed in the case of seeking social support only for the duration of sickness absence and in the case of palliative reaction only for the length and frequency of absence. In contrast, an avoidant coping style, representing a reactive-passive strategy, increases the likelihood of frequent absences significantly, as well as the length and duration of sickness absence. Expression of emotions, representing another reactive-passive strategy, has no effect on future sickness absenteeism. The median time before the onset of a new episode of absenteeism is significantly extended for active problem-solving and reduced for avoidance and for a palliative response. The results of the present study support the notion that problem-solving coping and reactive-passive strategies are inextricably connected to frequency, duration, length and onset of sickness absence. Especially, active problem-solving decreases the chance of future sickness absence.

Modelling of the 10-micrometer natural laser emission from the mesospheres of Mars and Venus

NASA Technical Reports Server (NTRS)

Deming, D.; Mumma, M. J.

1983-01-01

The NLTE radiative transfer problem is solved to obtain the 00 deg 1 vibrational state population. This model successfully reproduces the existing center-to-limb observations, although higher spatial resolution observations are needed for a definitive test. The model also predicts total fluxes which are close to the observed values. The strength of the emission is predicted to be closely related to the instantaneous near-IR solar heating rate.

Modeling of the 10-micron natural laser emission from the mesospheres of Mars and Venus

NASA Technical Reports Server (NTRS)

Deming, D.; Mumma, M. J.

1983-01-01

The NLTE radiative transfer problem is solved to obtain the 00 deg 1 vibrational state population. This model successfully reproduces the existing center-to-limb observations, although higher spatial resolution observations are needed for a definitive test. The model also predicts total fluxes which are close to the observed values. The strength of the emission is predicted to be closely related to the instantaneous near-IR solar heating rate.

Predictive Simulations of Neuromuscular Coordination and Joint-Contact Loading in Human Gait.

PubMed

Lin, Yi-Chung; Walter, Jonathan P; Pandy, Marcus G

2018-04-18

We implemented direct collocation on a full-body neuromusculoskeletal model to calculate muscle forces, ground reaction forces and knee contact loading simultaneously for one cycle of human gait. A data-tracking collocation problem was solved for walking at the normal speed to establish the practicality of incorporating a 3D model of articular contact and a model of foot-ground interaction explicitly in a dynamic optimization simulation. The data-tracking solution then was used as an initial guess to solve predictive collocation problems, where novel patterns of movement were generated for walking at slow and fast speeds, independent of experimental data. The data-tracking solutions accurately reproduced joint motion, ground forces and knee contact loads measured for two total knee arthroplasty patients walking at their preferred speeds. RMS errors in joint kinematics were < 2.0° for rotations and < 0.3 cm for translations while errors in the model-computed ground-reaction and knee-contact forces were < 0.07 BW and < 0.4 BW, respectively. The predictive solutions were also consistent with joint kinematics, ground forces, knee contact loads and muscle activation patterns measured for slow and fast walking. The results demonstrate the feasibility of performing computationally-efficient, predictive, dynamic optimization simulations of movement using full-body, muscle-actuated models with realistic representations of joint function.

Collis-Romberg Mathematical Problem Solving Profiles.

ERIC Educational Resources Information Center

Collis, K. F.; Romberg, T. A.

Problem solving has become a focus of mathematics programs in Australia in recent years, necessitating the assessment of students' problem-solving abilities. This manual provides a problem-solving assessment and teaching resource package containing four elements: (1) profiles assessment items; (2) profiles diagnostic forms for recording individual…

Tracing for the problem-solving ability in advanced calculus class based on modification of SAVI model at Universitas Negeri Semarang

NASA Astrophysics Data System (ADS)

Pujiastuti, E.; Waluya, B.; Mulyono

2018-03-01

There were many ways of solving the problem offered by the experts. The author combines various ways of solving the problem as a form of novelty. Among the learning model that was expected to support the growth of problem-solving skills was SAVI. The purpose, to obtain trace results from the analysis of the problem-solving ability of students in the Dual Integral material. The research method was a qualitative approach. Its activities include tests was filled with mathematical connections, observation, interviews, FGD, and triangulation. The results were: (1) some students were still experiencing difficulties in solving the problems. (2) The application of modification of SAVI learning model effective in supporting the growth of problem-solving abilities. (3) The strength of the students related to solving the problem, there were two students in the excellent category, there were three students in right classes and one student in the medium group.

Flexibility in Mathematics Problem Solving Based on Adversity Quotient

NASA Astrophysics Data System (ADS)

Dina, N. A.; Amin, S. M.; Masriyah

2018-01-01

Flexibility is an ability which is needed in problem solving. One of the ways in problem solving is influenced by Adversity Quotient (AQ). AQ is the power of facing difficulties. There are three categories of AQ namely climber, camper, and quitter. This research is a descriptive research using qualitative approach. The aim of this research is to describe flexibility in mathematics problem solving based on Adversity Quotient. The subjects of this research are climber student, camper student, and quitter student. This research was started by giving Adversity Response Profile (ARP) questioner continued by giving problem solving task and interviews. The validity of data measurement was using time triangulation. The results of this research shows that climber student uses two strategies in solving problem and doesn’t have difficulty. The camper student uses two strategies in solving problem but has difficulty to finish the second strategies. The quitter student uses one strategy in solving problem and has difficulty to finish it.

Interference thinking in constructing students’ knowledge to solve mathematical problems

NASA Astrophysics Data System (ADS)

Jayanti, W. E.; Usodo, B.; Subanti, S.

2018-04-01

This research aims to describe interference thinking in constructing students’ knowledge to solve mathematical problems. Interference thinking in solving problems occurs when students have two concepts that interfere with each other’s concept. Construction of problem-solving can be traced using Piaget’s assimilation and accommodation framework, helping to know the students’ thinking structures in solving the problems. The method of this research was a qualitative method with case research strategy. The data in this research involving problem-solving result and transcripts of interviews about students’ errors in solving the problem. The results of this research focus only on the student who experience proactive interference, where student in solving a problem using old information to interfere with the ability to recall new information. The student who experience interference thinking in constructing their knowledge occurs when the students’ thinking structures in the assimilation and accommodation process are incomplete. However, after being given reflection to the student, then the students’ thinking process has reached equilibrium condition even though the result obtained remains wrong.

How preschool executive functioning predicts several aspects of math achievement in Grades 1 and 3: A longitudinal study.

PubMed

Viterbori, Paola; Usai, M Carmen; Traverso, Laura; De Franchis, Valentina

2015-12-01

This longitudinal study analyzes whether selected components of executive function (EF) measured during the preschool period predict several indices of math achievement in primary school. Six EF measures were assessed in a sample of 5-year-old children (N = 175). The math achievement of the same children was then tested in Grades 1 and 3 using both a composite math score and three single indices of written calculation, arithmetical facts, and problem solving. Using previous results obtained from the same sample of children, a confirmatory factor analysis examining the latent EF structure in kindergarten indicated that a two-factor model provided the best fit for the data. In this model, inhibition and working memory (WM)-flexibility were separate dimensions. A full structural equation model was then used to test the hypothesis that math achievement (the composite math score and single math scores) in Grades 1 and 3 could be explained by the two EF components comprising the kindergarten model. The results indicate that the WM-flexibility component measured during the preschool period substantially predicts mathematical achievement, especially in Grade 3. The math composite scores were predicted by the WM-flexibility factor at both grade levels. In Grade 3, both problem solving and arithmetical facts were predicted by the WM-flexibility component. The results empirically support interventions that target EF as an important component of early childhood mathematics education. Copyright © 2015 Elsevier Inc. All rights reserved.

A Structural Equation Model Explaining 8th Grade Students' Mathematics Achievements

ERIC Educational Resources Information Center

Yurt, Eyüp; Sünbül, Ali Murat

2014-01-01

The purpose of this study is to investigate, via a model, the explanatory and predictive relationships among the following variables: Mathematical Problem Solving and Reasoning Skills, Sources of Mathematics Self-Efficacy, Spatial Ability, and Mathematics Achievements of Secondary School 8th Grade Students. The sample group of the study, itself…

Realism, Instrumentalism, and Scientific Symbiosis: Psychological Theory as a Search for Truth and the Discovery of Solutions

ERIC Educational Resources Information Center

Cacioppo, John T.; Semin, Gun R.; Berntson, Gary G.

2004-01-01

Scientific realism holds that scientific theories are approximations of universal truths about reality, whereas scientific instrumentalism posits that scientific theories are intellectual structures that provide adequate predictions of what is observed and useful frameworks for answering questions and solving problems in a given domain. These…

Rockets: A Teacher's Guide with Activities in Science, Mathematics, and Technology. Grades K-12.

ERIC Educational Resources Information Center

Shearer, Deborah A.; Vogt, Gregory L.

This guide contains activities that emphasize hands-on involvement, prediction, data collection and interpretation, teamwork, and problem solving. It begins with background information on the history of rocketry, scientific principles, and practical rocketry. Following the background sections are a series of activities that demonstrate the basic…

Energy. Physical Science in Action. Teacher's Manual and Workbook.

ERIC Educational Resources Information Center

Sneider, Cary I.; Piccotto, Henri

The Science in Action series is designed to teach practical science concepts to special-needs students. It is intended to develop students' problem-solving skills by teaching them to observe, record, analyze, conclude, and predict. This document contains a student workbook which deals with basic principles of physical science. Six separate units…

Optimizing Partial Credit Algorithms to Predict Student Performance

ERIC Educational Resources Information Center

Ostrow, Korinn; Donnelly, Chistopher; Heffernan, Neil

2015-01-01

As adaptive tutoring systems grow increasingly popular for the completion of classwork and homework, it is crucial to assess the manner in which students are scored within these platforms. The majority of systems, including ASSISTments, return the binary correctness of a student's first attempt at solving each problem. Yet for many teachers,…

Decision support systems for plant disease and insect management in commercial nurseries in the Midwest: A perspective review

USDA-ARS?s Scientific Manuscript database

Decision-support systems (DDSs) are techniques that help decision makers utilize models to solve problems under complex and uncertain conditions. Predicting conditions that warrant intervention is a key tenet of the concept of integrated pest management (IPM) with the use of expert systems and pest ...

Children's Task Oriented Patterns in Early Childhood: A Latent Transition Analysis

ERIC Educational Resources Information Center

Wang, Feihong; Algina, James; Snyder, Patricia; Cox, Martha; Vernon-Feagans, Lynne; Cox, Martha; Blair, Clancy; Burchinal, Margaret; Burton, Linda; Crnic, Keith; Crouter, Ann; Garrett-Peters, Patricia; Greenberg, Mark; Lanza, Stephanie; Mills-Koonce, Roger; Werner, Emily; Willoughby, Michael

2017-01-01

We examined individual differences and predictions of children's patterns in behavioral, emotional and attentional efforts toward challenging puzzle tasks at 24 and 35 months using data from a large longitudinal rural representative sample. Using latent transition analysis, we found four distinct task-oriented patterns in problem-solving tasks…

Sound. Physical Science in Action. Teacher's Manual and Workbook.

ERIC Educational Resources Information Center

Chan, Janis Fisher; Friedland, Mary

The Science in Action series is designed to teach practical science concepts to special-needs students. It is intended to develop students' problem-solving skills by teaching them to observe, record, analyze, conclude, and predict. This document contains a student workbook which deals with basic principles of physical science. Six separate units…

The Research of the Personality Qualities of Future Educational Psychologists

ERIC Educational Resources Information Center

Dolgova, V. I.; Salamatov, A. A.; Potapova, M. V.; Yakovleva, N. O.

2016-01-01

In this article, the authors substantiate the existence of the personality qualities of future educational psychologists (PQFEP) that are, in fact, a sum of knowledge, skills, abilities, socially required qualities of personality allowing the psychologist to solve problems in all the fields of professional activities. A model of PQFEP predicts the…

Working Memory Facilitates Insight Instead of Hindering It: Comment on Decaro, Van Stockum, and Wieth (2016)

ERIC Educational Resources Information Center

Chuderski, Adam; Jastrzebski, Jan

2017-01-01

The "nothing-special" account of insight predicts positive correlations of insight problem solving and working memory capacity (WMC), whereas the "special-process" account expects no, or even negative, correlations. In the latter vein, DeCaro, Van Stockum Jr., and Wieth (2016) have recently reported weak negative WMC…

Animals. Life Science in Action. Teacher's Manual and Workbook.

ERIC Educational Resources Information Center

Roderman, Winifred Ho; Booth, Gerald

The Science in Action series is designed to teach practical science concepts to special-needs students. It is intended to develop students' problem-solving skills by teaching them to observe, record, analyze, conclude, and predict. This document contains a student workbook which deals with basic principles of life science. Six separate units…

SSL: A Theory of How People Learn to Select Strategies

ERIC Educational Resources Information Center

Rieskamp, Jorg; Otto, Philipp E.

2006-01-01

The assumption that people possess a repertoire of strategies to solve the inference problems they face has been raised repeatedly. However, a computational model specifying how people select strategies from their repertoire is still lacking. The proposed strategy selection learning (SSL) theory predicts a strategy selection process on the basis…

Dynamic Nature of Atoms and Molecules, Science (Experimental): 5316.06.

ERIC Educational Resources Information Center

Buffaloe, Jacquelin F.

This unit of instruction deals with the study of both physical and chemical systems in equilibrium. It provides the student with instruction that will enable him to predict products in solubility, acid-base, and oxidation-reduction reactions and to write and balance equations for these reactions and solve problems involving equilibria constants.…

A Question of Trust: Predictive Conditions for Adaptive and Technical Leadership in Educational Contexts

ERIC Educational Resources Information Center

Daly, Alan J.; Chrispeels, Janet

2008-01-01

Recent studies have suggested that educational leaders enacting a balance of technical and adaptive leadership have an effect on increasing student achievement. Technical leadership focuses on problem-solving or first-order changes within existing structures and paradigms. Adaptive leadership involves deep or second-order changes that alter…

Strategy Generalization across Orientation Tasks: Testing a Computational Cognitive Model

ERIC Educational Resources Information Center

Gunzelmann, Glenn

2008-01-01

Humans use their spatial information processing abilities flexibly to facilitate problem solving and decision making in a variety of tasks. This article explores the question of whether a general strategy can be adapted for performing two different spatial orientation tasks by testing the predictions of a computational cognitive model. Human…

Insightful problem solving and emulation in brown capuchin monkeys.

PubMed

Renner, Elizabeth; Abramo, Allison M; Karen Hambright, M; Phillips, Kimberley A

2017-05-01

We investigated problem solving abilities of capuchin monkeys via the "floating object problem," a task in which the subject must use creative problem solving to retrieve a favored food item from the bottom of a clear tube. Some great apes have solved this problem by adding water to raise the object to a level at which it can be easily grabbed. We presented seven capuchins with the task over eight trials (four "dry" and four "wet"). None of the subjects solved the task, indicating that no capuchin demonstrated insightful problem solving under these experimental conditions. We then investigated whether capuchins would emulate a solution to the task. Seven subjects observed a human model solve the problem by pouring water from a cup into the tube, which brought the object to the top of the tube, allowing the subject to retrieve it. Subjects were then allowed to interact freely with an unfilled tube containing the object in the presence of water and objects that could be used to solve the task. While most subjects were unable to solve the task after viewing a demonstrator solve it, one subject did so, but in a unique way. Our results are consistent with some previous results in great ape species and indicate that capuchins do not spontaneously solve the floating object problem via insight.

Real time optimal guidance of low-thrust spacecraft: an application of nonlinear model predictive control.

PubMed

Arrieta-Camacho, Juan José; Biegler, Lorenz T

2005-12-01

Real time optimal guidance is considered for a class of low thrust spacecraft. In particular, nonlinear model predictive control (NMPC) is utilized for computing the optimal control actions required to transfer a spacecraft from a low Earth orbit to a mission orbit. The NMPC methodology presented is able to cope with unmodeled disturbances. The dynamics of the transfer are modeled using a set of modified equinoctial elements because they do not exhibit singularities for zero inclination and zero eccentricity. The idea behind NMPC is the repeated solution of optimal control problems; at each time step, a new control action is computed. The optimal control problem is solved using a direct method-fully discretizing the equations of motion. The large scale nonlinear program resulting from the discretization procedure is solved using IPOPT--a primal-dual interior point algorithm. Stability and robustness characteristics of the NMPC algorithm are reviewed. A numerical example is presented that encourages further development of the proposed methodology: the transfer from low-Earth orbit to a molniya orbit.

Emotional Intelligence and cognitive abilities - associations and sex differences.

PubMed

Pardeller, Silvia; Frajo-Apor, Beatrice; Kemmler, Georg; Hofer, Alex

2017-09-01

In order to expand on previous research, this cross-sectional study investigated the relationship between Emotional Intelligence (EI) and cognitive abilities in healthy adults with a special focus on potential sex differences. EI was assessed by means of the Mayer-Salovey-Caruso-Emotional-Intelligence Test (MSCEIT), whereas cognitive abilities were investigated using the Brief Assessment of Cognition in Schizophrenia (BACS), which measures key aspects of cognitive functioning, i.e. verbal memory, working memory, motor speed, verbal fluency, attention and processing speed, and reasoning and problem solving. 137 subjects (65% female) with a mean age of 38.7 ± 11.8 years were included into the study. While males and females were comparable with regard to EI, men achieved significantly higher BACS composite scores and outperformed women in the BACS subscales motor speed, attention and processing speed, and reasoning and problem solving. Verbal fluency significantly predicted EI, whereas the MSCEIT subscale understanding emotions significantly predicted the BACS composite score. Our findings support previous research and emphasize the relevance of considering cognitive abilities when assessing ability EI in healthy individuals.

A structural model decomposition framework for systems health management

NASA Astrophysics Data System (ADS)

Roychoudhury, I.; Daigle, M.; Bregon, A.; Pulido, B.

Systems health management (SHM) is an important set of technologies aimed at increasing system safety and reliability by detecting, isolating, and identifying faults; and predicting when the system reaches end of life (EOL), so that appropriate fault mitigation and recovery actions can be taken. Model-based SHM approaches typically make use of global, monolithic system models for online analysis, which results in a loss of scalability and efficiency for large-scale systems. Improvement in scalability and efficiency can be achieved by decomposing the system model into smaller local submodels and operating on these submodels instead. In this paper, the global system model is analyzed offline and structurally decomposed into local submodels. We define a common model decomposition framework for extracting submodels from the global model. This framework is then used to develop algorithms for solving model decomposition problems for the design of three separate SHM technologies, namely, estimation (which is useful for fault detection and identification), fault isolation, and EOL prediction. We solve these model decomposition problems using a three-tank system as a case study.

The Academic Diligence Task (ADT): Assessing Individual Differences in Effort on Tedious but Important Schoolwork

PubMed Central

Galla, Brian M.; Plummer, Benjamin D.; White, Rachel E.; Meketon, David; D’Mello, Sidney K.; Duckworth, Angela L.

2014-01-01

The current study reports on the development and validation of the Academic Diligence Task (ADT), designed to assess the tendency to expend effort on academic tasks which are tedious in the moment but valued in the long-term. In this novel online task, students allocate their time between solving simple math problems (framed as beneficial for problem solving skills) and, alternatively, playing Tetris or watching entertaining videos. Using a large sample of high school seniors (N = 921), the ADT demonstrated convergent validity with self-report ratings of Big Five conscientiousness and its facets, self-control and grit, as well as discriminant validity from theoretically unrelated constructs, such as Big Five extraversion, openness, and emotional stability, test anxiety, life satisfaction, and positive and negative affect. The ADT also demonstrated incremental predictive validity for objectively measured GPA, standardized math and reading achievement test scores, high school graduation, and college enrollment, over and beyond demographics and intelligence. Collectively, findings suggest the feasibility of online behavioral measures to assess noncognitive individual differences that predict academic outcomes. PMID:25258470

The Academic Diligence Task (ADT): Assessing Individual Differences in Effort on Tedious but Important Schoolwork.

PubMed

Galla, Brian M; Plummer, Benjamin D; White, Rachel E; Meketon, David; D'Mello, Sidney K; Duckworth, Angela L

2014-10-01

The current study reports on the development and validation of the Academic Diligence Task (ADT), designed to assess the tendency to expend effort on academic tasks which are tedious in the moment but valued in the long-term. In this novel online task, students allocate their time between solving simple math problems (framed as beneficial for problem solving skills) and, alternatively, playing Tetris or watching entertaining videos. Using a large sample of high school seniors ( N = 921), the ADT demonstrated convergent validity with self-report ratings of Big Five conscientiousness and its facets, self-control and grit, as well as discriminant validity from theoretically unrelated constructs, such as Big Five extraversion, openness, and emotional stability, test anxiety, life satisfaction, and positive and negative affect. The ADT also demonstrated incremental predictive validity for objectively measured GPA, standardized math and reading achievement test scores, high school graduation, and college enrollment, over and beyond demographics and intelligence. Collectively, findings suggest the feasibility of online behavioral measures to assess noncognitive individual differences that predict academic outcomes.

A Structural Model Decomposition Framework for Systems Health Management

NASA Technical Reports Server (NTRS)

Roychoudhury, Indranil; Daigle, Matthew J.; Bregon, Anibal; Pulido, Belamino

2013-01-01

Systems health management (SHM) is an important set of technologies aimed at increasing system safety and reliability by detecting, isolating, and identifying faults; and predicting when the system reaches end of life (EOL), so that appropriate fault mitigation and recovery actions can be taken. Model-based SHM approaches typically make use of global, monolithic system models for online analysis, which results in a loss of scalability and efficiency for large-scale systems. Improvement in scalability and efficiency can be achieved by decomposing the system model into smaller local submodels and operating on these submodels instead. In this paper, the global system model is analyzed offline and structurally decomposed into local submodels. We define a common model decomposition framework for extracting submodels from the global model. This framework is then used to develop algorithms for solving model decomposition problems for the design of three separate SHM technologies, namely, estimation (which is useful for fault detection and identification), fault isolation, and EOL prediction. We solve these model decomposition problems using a three-tank system as a case study.

Analysis of Student Errors on Division of Fractions

NASA Astrophysics Data System (ADS)

Maelasari, E.; Jupri, A.

2017-02-01

This study aims to describe the type of student errors that typically occurs at the completion of the division arithmetic operations on fractions, and to describe the causes of students’ mistakes. This research used a descriptive qualitative method, and involved 22 fifth grade students at one particular elementary school in Kuningan, Indonesia. The results of this study showed that students’ error answers caused by students changing their way of thinking to solve multiplication and division operations on the same procedures, the changing of mix fractions to common fraction have made students confused, and students are careless in doing calculation. From student written work, in solving the fraction problems, we found that there is influence between the uses of learning methods and student response, and some of student responses beyond researchers’ prediction. We conclude that the teaching method is not only the important thing that must be prepared, but the teacher should also prepare about predictions of students’ answers to the problems that will be given in the learning process. This could be a reflection for teachers to be better and to achieve the expected learning goals.

The importance of understanding: Model space moderates goal specificity effects.

PubMed

Kistner, Saskia; Burns, Bruce D; Vollmeyer, Regina; Kortenkamp, Ulrich

2016-01-01

The three-space theory of problem solving predicts that the quality of a learner's model and the goal specificity of a task interact on knowledge acquisition. In Experiment 1 participants used a computer simulation of a lever system to learn about torques. They either had to test hypotheses (nonspecific goal), or to produce given values for variables (specific goal). In the good- but not in the poor-model condition they saw torque depicted as an area. Results revealed the predicted interaction. A nonspecific goal only resulted in better learning when a good model of torques was provided. In Experiment 2 participants learned to manipulate the inputs of a system to control its outputs. A nonspecific goal to explore the system helped performance when compared to a specific goal to reach certain values when participants were given a good model, but not when given a poor model that suggested the wrong hypothesis space. Our findings support the three-space theory. They emphasize the importance of understanding for problem solving and stress the need to study underlying processes.

Adolescents’ Functional Numeracy Is Predicted by Their School Entry Number System Knowledge

PubMed Central

Geary, David C.; Hoard, Mary K.; Nugent, Lara; Bailey, Drew H.

2013-01-01

One in five adults in the United States is functionally innumerate; they do not possess the mathematical competencies needed for many modern jobs. We administered functional numeracy measures used in studies of young adults’ employability and wages to 180 thirteen-year-olds. The adolescents began the study in kindergarten and participated in multiple assessments of intelligence, working memory, mathematical cognition, achievement, and in-class attentive behavior. Their number system knowledge at the beginning of first grade was defined by measures that assessed knowledge of the systematic relations among Arabic numerals and skill at using this knowledge to solve arithmetic problems. Early number system knowledge predicted functional numeracy more than six years later (ß = 0.195, p = .0014) controlling for intelligence, working memory, in-class attentive behavior, mathematical achievement, demographic and other factors, but skill at using counting procedures to solve arithmetic problems did not. In all, we identified specific beginning of schooling numerical knowledge that contributes to individual differences in adolescents’ functional numeracy and demonstrated that performance on mathematical achievement tests underestimates the importance of this early knowledge. PMID:23382934

Problem solving therapy - use and effectiveness in general practice.

PubMed

Pierce, David

2012-09-01

Problem solving therapy (PST) is one of the focused psychological strategies supported by Medicare for use by appropriately trained general practitioners. This article reviews the evidence base for PST and its use in the general practice setting. Problem solving therapy involves patients learning or reactivating problem solving skills. These skills can then be applied to specific life problems associated with psychological and somatic symptoms. Problem solving therapy is suitable for use in general practice for patients experiencing common mental health conditions and has been shown to be as effective in the treatment of depression as antidepressants. Problem solving therapy involves a series of sequential stages. The clinician assists the patient to develop new empowering skills, and then supports them to work through the stages of therapy to determine and implement the solution selected by the patient. Many experienced GPs will identify their own existing problem solving skills. Learning about PST may involve refining and focusing these skills.

Collection of solved problems in physics

NASA Astrophysics Data System (ADS)

Koupilová, ZdeÅka; Mandíková, Dana; Snětinová, Marie

2017-01-01

To solve physics problems is a key ability which students should reach during their physics education. Ten years ago we started to develop a Collection of fully solved problems. The structure of problems' solutions is specially designed to substitute tutor's help during lesson and encourage students to solve at least some parts of a problem independently. Nowadays the database contains about 770 fully solved problems in physics in Czech, more than 100 problems in Polish and more than 140 problems in English. Other problems are still being translated. Except for physics problems, the Collection has also a mathematical part, which contains more than 300 fully solved problems in mathematics. This paper follows the presentation of the Collection of solved problems from previous years and introduces a new interface of the Collection, its enhanced functionality, new topics, newly created interface for teachers, user feedback and plans for future development. The database is placed at the website of the Department of Physics Education, Faculty of Mathematics and Physics, Charles University in Prague, the links are: http://reseneulohy.cz/fyzika (Czech version); http://www.physicstasks.eu/ (English version).

Pre-service mathematics teachers’ ability in solving well-structured problem

NASA Astrophysics Data System (ADS)

Paradesa, R.

2018-01-01

This study aimed to describe the mathematical problem-solving ability of undergraduate students of mathematics education in solving the well-structured problem. The type of this study was qualitative descriptive. The subjects in this study were 100 undergraduate students of Mathematics Education at one of the private universities in Palembang city. The data in this study was collected through two test items with essay form. The results of this study showed that, from the first problem, only 8% students can solve it, but do not check back again to validate the process. Based on a scoring rubric that follows Polya strategy, their answer satisfied 2 4 2 0 patterns. But, from the second problem, 45% students satisfied it. This is because the second problem imitated from the example that was given in learning process. The average score of undergraduate students mathematical problem-solving ability in solving well-structured problems showed 56.00 with standard deviation was 13.22. It means that, from 0 - 100 scale, undergraduate students mathematical problem-solving ability can be categorized low. From this result, the conclusion was undergraduate students of mathematics education in Palembang still have a problem in solving mathematics well-structured problem.

An Investigation on Chinese Teachers' Realistic Problem Posing and Problem Solving Ability and Beliefs

ERIC Educational Resources Information Center

Chen, Limin; Van Dooren, Wim; Chen, Qi; Verschaffel, Lieven

2011-01-01

In the present study, which is a part of a research project about realistic word problem solving and problem posing in Chinese elementary schools, a problem solving and a problem posing test were administered to 128 pre-service and in-service elementary school teachers from Tianjin City in China, wherein the teachers were asked to solve 3…

Problem-solving skills and perceived stress among undergraduate students: The moderating role of hardiness.

PubMed

Abdollahi, Abbas; Abu Talib, Mansor; Carlbring, Per; Harvey, Richard; Yaacob, Siti Nor; Ismail, Zanariah

2016-06-01

This study was designed to examine the relationships between problem-solving skills, hardiness, and perceived stress and to test the moderating role of hardiness in the relationship between problem-solving skills and perceived stress among 500 undergraduates from Malaysian public universities. The analyses showed that undergraduates with poor problem-solving confidence, external personal control of emotion, and approach-avoidance style were more likely to report perceived stress. Hardiness moderated the relationships between problem-solving skills and perceived stress. These findings reinforce the importance of moderating role of hardiness as an influencing factor that explains how problem-solving skills affect perceived stress among undergraduates.

The Effects of Thinking Aloud Pair Problem Solving on High School Students' Chemistry Problem-Solving Performance and Verbal Interactions

NASA Astrophysics Data System (ADS)

Jeon, Kyungmoon; Huffman, Douglas; Noh, Taehee

2005-10-01

This study investigated the effects of a thinking aloud pair problem solving (TAPPS) approach on students' chemistry problem-solving performance and verbal interactions. A total of 85 eleventh grade students from three classes in a Korean high school were randomly assigned to one of three groups; either individually using a problem-solving strategy, using a problem-solving strategy with TAPPS, or the control group. After instruction, students' problem-solving performance was examined. The results showed that students in both the individual and TAPPS groups performed better than those in the control group on recalling the related law and mathematical execution, while students in the TAPPS group performed better than those in the other groups on conceptual knowledge. To investigate the verbal behaviors using TAPPS, verbal behaviors of solvers and listeners were classified into 8 categories. Listeners' verbal behavior of "agreeing" and "pointing out", and solvers' verbal behavior of "modifying" were positively related with listeners' problem-solving performance. There was, however, a negative correlation between listeners' use of "point out" and solvers' problem-solving performance. The educational implications of this study are discussed.

Pedagogy and/or technology: Making difference in improving students' problem solving skills

NASA Astrophysics Data System (ADS)

Hrepic, Zdeslav; Lodder, Katherine; Shaw, Kimberly A.

2013-01-01

Pen input computers combined with interactive software may have substantial potential for promoting active instructional methodologies and for facilitating students' problem solving ability. An excellent example is a study in which introductory physics students improved retention, conceptual understanding and problem solving abilities when one of three weekly lectures was replaced with group problem solving sessions facilitated with Tablet PCs and DyKnow software [1,2]. The research goal of the present study was to isolate the effect of the methodology itself (using additional time to teach problem solving) from that of the involved technology. In Fall 2011 we compared the performance of students taking the same introductory physics lecture course while enrolled in two separate problem-solving sections. One section used pen-based computing to facilitate group problem solving while the other section used low-tech methods for one third of the semester (covering Kinematics), and then traded technologies for the middle third of the term (covering Dynamics). Analysis of quiz, exam and standardized pre-post test results indicated no significant difference in scores of the two groups. Combining this result with those of previous studies implies primacy of pedagogy (collaborative problem solving itself) over technology for student learning in problem solving recitations.

Calculators and Strategies for Problem Solving in Grade Seven: An Implementation Program and Study. Report No. 83:3.

ERIC Educational Resources Information Center

Szetela, W.; Super, D.

A problem-solving program supplemented by calculators in one treatment group was conducted in 63 grade 7 classes with about 1350 students. Teachers were provided with problems correlated with textbooks, and instruction for teaching problem-solving strategies. School districts provided calculators and problem-solving materials. Pretest scores…

Assessing Student Written Problem Solutions: A Problem-Solving Rubric with Application to Introductory Physics

ERIC Educational Resources Information Center

Docktor, Jennifer L.; Dornfeld, Jay; Frodermann, Evan; Heller, Kenneth; Hsu, Leonardo; Jackson, Koblar Alan; Mason, Andrew; Ryan, Qing X.; Yang, Jie

2016-01-01

Problem solving is a complex process valuable in everyday life and crucial for learning in the STEM fields. To support the development of problem-solving skills it is important for researchers and curriculum developers to have practical tools that can measure the difference between novice and expert problem-solving performance in authentic…

Problem Solving: How Can We Help Students Overcome Cognitive Difficulties

ERIC Educational Resources Information Center

Cardellini, Liberato

2014-01-01

The traditional approach to teach problem solving usually consists in showing students the solutions of some example-problems and then in asking students to practice individually on solving a certain number of related problems. This approach does not ensure that students learn to solve problems and above all to think about the solution process in…

Step by Step: Biology Undergraduates' Problem-Solving Procedures during Multiple-Choice Assessment

ERIC Educational Resources Information Center

Prevost, Luanna B.; Lemons, Paula P.

2016-01-01

This study uses the theoretical framework of domain-specific problem solving to explore the procedures students use to solve multiple-choice problems about biology concepts. We designed several multiple-choice problems and administered them on four exams. We trained students to produce written descriptions of how they solved the problem, and this…

Analog Processor To Solve Optimization Problems

NASA Technical Reports Server (NTRS)

Duong, Tuan A.; Eberhardt, Silvio P.; Thakoor, Anil P.

1993-01-01

Proposed analog processor solves "traveling-salesman" problem, considered paradigm of global-optimization problems involving routing or allocation of resources. Includes electronic neural network and auxiliary circuitry based partly on concepts described in "Neural-Network Processor Would Allocate Resources" (NPO-17781) and "Neural Network Solves 'Traveling-Salesman' Problem" (NPO-17807). Processor based on highly parallel computing solves problem in significantly less time.

Computer Programming: A Medium for Teaching Problem Solving.

ERIC Educational Resources Information Center

Casey, Patrick J.

1997-01-01

Argues that including computer programming in the curriculum as a medium for instruction is a feasible alternative for teaching problem solving. Discusses the nature of problem solving; the problem-solving elements of discovery, motivation, practical learning situations and flexibility which are inherent in programming; capabilities of computer…

Perceived Problem Solving, Stress, and Health among College Students

ERIC Educational Resources Information Center

Largo-Wight, Erin; Peterson, P. Michael; Chen, W. William

2005-01-01

Objective: To study the relationships among perceived problem solving, stress, and physical health. Methods: The Perceived Stress Questionnaire (PSQ), Personal Problem solving Inventory (PSI), and a stress-related physical health symptoms checklist were used to measure perceived stress, problem solving, and health among undergraduate college…

THE CURRENT STATUS OF RESEARCH AND THEORY IN HUMAN PROBLEM SOLVING.

ERIC Educational Resources Information Center

DAVIS, GARY A.

PROBLEM-SOLVING THEORIES IN THREE AREAS - TRADITIONAL (STIMULUS-RESPONSE) LEARNING, COGNITIVE-GESTALT APPROACHES, AND COMPUTER AND MATHEMATICAL MODELS - WERE SUMMARIZED. RECENT EMPIRICAL STUDIES (1960-65) ON PROBLEM SOLVING WERE CATEGORIZED ACCORDING TO TYPE OF BEHAVIOR ELICITED BY PARTICULAR PROBLEM-SOLVING TASKS. ANAGRAM,…

Developing Creativity through Collaborative Problem Solving

ERIC Educational Resources Information Center

Albert, Lillie R.; Kim, Rina

2013-01-01

This paper discusses an alternative approach for developing problem solving experiences for students. The major argument is that students can develop their creativity by engaging in collaborative problem solving activities in which they apply a variety of mathematical methods creatively to solve problems. The argument is supported by: considering…

The effects of expected reward on creative problem solving.

PubMed

Cristofori, Irene; Salvi, Carola; Beeman, Mark; Grafman, Jordan

2018-06-12

Creative problem solving involves search processes, and it is known to be hard to motivate. Reward cues have been found to enhance performance across a range of tasks, even when cues are presented subliminally, without being consciously detected. It is uncertain whether motivational processes, such as reward, can influence problem solving. We tested the effect of supraliminal and subliminal reward on participant performance on problem solving that can be solved by deliberate analysis or by insight. Forty-one participants attempted to solve 100 compound remote associate problems. At the beginning of each problem, a potential reward cue (1 or 25 cents) was displayed, either subliminally (17 ms) or supraliminally (100 ms). Participants earned the displayed reward if they solved the problem correctly. Results showed that the higher subliminal reward increased the percentage of problems solved correctly overall. Second, we explored if subliminal rewards preferentially influenced solutions that were achieved via a sudden insight (mostly processed below awareness) or via a deliberate analysis. Participants solved more problems via insight following high subliminal reward when compared with low subliminal reward, and compared with high supraliminal reward, with no corresponding effect on analytic solving. Striatal dopamine (DA) is thought to influence motivation, reinforce behavior, and facilitate cognition. We speculate that subliminal rewards activate the striatal DA system, enhancing the kinds of automatic integrative processes that lead to more creative strategies for problem solving, without increasing the selectivity of attention, which could impede insight.

Find the Dimensions: Students Solving a Tiling Problem

ERIC Educational Resources Information Center

Obara, Samuel

2018-01-01

Students learn mathematics by solving problems. Mathematics textbooks are full of problems, and mathematics teachers use these problems to test students' understanding of mathematical concepts. This paper discusses how problem-solving skills can be fostered with a geometric tiling problem.

Energy Storage Sizing Taking Into Account Forecast Uncertainties and Receding Horizon Operation

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

Baker, Kyri; Hug, Gabriela; Li, Xin

Energy storage systems (ESS) have the potential to be very beneficial for applications such as reducing the ramping of generators, peak shaving, and balancing not only the variability introduced by renewable energy sources, but also the uncertainty introduced by errors in their forecasts. Optimal usage of storage may result in reduced generation costs and an increased use of renewable energy. However, optimally sizing these devices is a challenging problem. This paper aims to provide the tools to optimally size an ESS under the assumption that it will be operated under a model predictive control scheme and that the forecast ofmore » the renewable energy resources include prediction errors. A two-stage stochastic model predictive control is formulated and solved, where the optimal usage of the storage is simultaneously determined along with the optimal generation outputs and size of the storage. Wind forecast errors are taken into account in the optimization problem via probabilistic constraints for which an analytical form is derived. This allows for the stochastic optimization problem to be solved directly, without using sampling-based approaches, and sizing the storage to account not only for a wide range of potential scenarios, but also for a wide range of potential forecast errors. In the proposed formulation, we account for the fact that errors in the forecast affect how the device is operated later in the horizon and that a receding horizon scheme is used in operation to optimally use the available storage.« less

Performance of subjects with and without severe mental illness on a clinical test of problem solving.

PubMed

Marshall, R C; McGurk, S R; Karow, C M; Kairy, T J; Flashman, L A

2006-06-01

Severe mental illness is associated with impairments in executive functions, such as conceptual reasoning, planning, and strategic thinking all of which impact problem solving. The present study examined the utility of a novel assessment tool for problem solving, the Rapid Assessment of Problem Solving Test (RAPS) in persons with severe mental illness. Subjects were 47 outpatients with severe mental illness and an equal number healthy controls matched for age and gender. Results confirmed all hypotheses with respect to how subjects with severe mental illness would perform on the RAPS. Specifically, the severely mentally ill subjects (1) solved fewer problems on the RAPS, (2) when they did solve problems on the test, they did so far less efficiently than their healthy counterparts, and (3) the two groups differed markedly in the types of questions asked on the RAPS. The healthy control subjects tended to take a systematic, organized, but not always optimal approach to solving problems on the RAPS. The subjects with severe mental illness used some of the problem solving strategies of the healthy controls, but their performance was less consistent and tended to deteriorate when the complexity of the problem solving task increased. This was reflected by a high degree of guessing in lieu of asking constraint questions, particularly if a category-limited question was insufficient to continue the problem solving effort.

Effects of performance feedback and coaching on the problem-solving process: Improving the integrity of implementation and enhancing student outcomes

NASA Astrophysics Data System (ADS)

Lundahl, Allison A.

Schools implementing Response to Intervention (RtI) procedures frequently engage in team problem-solving processes to address the needs of students who require intensive and individualized services. Because the effectiveness of the problem-solving process will impact the overall success of RtI systems, the present study was designed to learn more about how to strengthen the integrity of the problem-solving process. Research suggests that school districts must ensure high quality training and ongoing support to enhance the effectiveness, acceptability, and sustainability of the problem-solving process within an RtI model; however, there is a dearth of research examining the effectiveness of methods to provide this training and support. Consequently, this study investigated the effects of performance feedback and coaching strategies on the integrity with which teams of educators conducted the problem-solving process in schools. In addition, the relationships between problem-solving integrity, teacher acceptability, and student outcomes were examined. Results suggested that the performance feedback increased problem-solving procedural integrity across two of the three participating schools. Conclusions about the effectiveness of the (a) coaching intervention and (b) interventions implemented in the third school were inconclusive. Regression analyses indicated that the integrity with which the teams conducted the problem-solving process was a significant predictor of student outcomes. However, the relationship between problem-solving procedural integrity and teacher acceptability was not statistically significant.

The Missing Curriculum in Physics Problem-Solving Education

NASA Astrophysics Data System (ADS)

Williams, Mobolaji

2018-05-01

Physics is often seen as an excellent introduction to science because it allows students to learn not only the laws governing the world around them, but also, through the problems students solve, a way of thinking which is conducive to solving problems outside of physics and even outside of science. In this article, we contest this latter idea and argue that in physics classes, students do not learn widely applicable problem-solving skills because physics education almost exclusively requires students to solve well-defined problems rather than the less-defined problems which better model problem solving outside of a formal class. Using personal, constructed, and the historical accounts of Schrödinger's development of the wave equation and Feynman's development of path integrals, we argue that what is missing in problem-solving education is practice in identifying gaps in knowledge and in framing these knowledge gaps as questions of the kind answerable using techniques students have learned. We discuss why these elements are typically not taught as part of the problem-solving curriculum and end with suggestions on how to incorporate these missing elements into physics classes.

Noticing relevant problem features: activating prior knowledge affects problem solving by guiding encoding

PubMed Central

Crooks, Noelle M.; Alibali, Martha W.

2013-01-01

This study investigated whether activating elements of prior knowledge can influence how problem solvers encode and solve simple mathematical equivalence problems (e.g., 3 + 4 + 5 = 3 + __). Past work has shown that such problems are difficult for elementary school students (McNeil and Alibali, 2000). One possible reason is that children's experiences in math classes may encourage them to think about equations in ways that are ultimately detrimental. Specifically, children learn a set of patterns that are potentially problematic (McNeil and Alibali, 2005a): the perceptual pattern that all equations follow an “operations = answer” format, the conceptual pattern that the equal sign means “calculate the total”, and the procedural pattern that the correct way to solve an equation is to perform all of the given operations on all of the given numbers. Upon viewing an equivalence problem, knowledge of these patterns may be reactivated, leading to incorrect problem solving. We hypothesized that these patterns may negatively affect problem solving by influencing what people encode about a problem. To test this hypothesis in children would require strengthening their misconceptions, and this could be detrimental to their mathematical development. Therefore, we tested this hypothesis in undergraduate participants. Participants completed either control tasks or tasks that activated their knowledge of the three patterns, and were then asked to reconstruct and solve a set of equivalence problems. Participants in the knowledge activation condition encoded the problems less well than control participants. They also made more errors in solving the problems, and their errors resembled the errors children make when solving equivalence problems. Moreover, encoding performance mediated the effect of knowledge activation on equivalence problem solving. Thus, one way in which experience may affect equivalence problem solving is by influencing what students encode about the equations. PMID:24324454

Conceptual and procedural knowledge community college students use when solving a complex science problem

NASA Astrophysics Data System (ADS)

Steen-Eibensteiner, Janice Lee

2006-07-01

A strong science knowledge base and problem solving skills have always been highly valued for employment in the science industry. Skills currently needed for employment include being able to problem solve (Overtoom, 2000). Academia also recognizes the need for effectively teaching students to apply problem solving skills in clinical settings. This thesis investigates how students solve complex science problems in an academic setting in order to inform the development of problem solving skills for the workplace. Students' use of problem solving skills in the form of learned concepts and procedural knowledge was studied as students completed a problem that might come up in real life. Students were taking a community college sophomore biology course, Human Anatomy & Physiology II. The problem topic was negative feedback inhibition of the thyroid and parathyroid glands. The research questions answered were (1) How well do community college students use a complex of conceptual knowledge when solving a complex science problem? (2) What conceptual knowledge are community college students using correctly, incorrectly, or not using when solving a complex science problem? (3) What problem solving procedural knowledge are community college students using successfully, unsuccessfully, or not using when solving a complex science problem? From the whole class the high academic level participants performed at a mean of 72% correct on chapter test questions which was a low average to fair grade of C-. The middle and low academic participants both failed (F) the test questions (37% and 30% respectively); 29% (9/31) of the students show only a fair performance while 71% (22/31) fail. From the subset sample population of 2 students each from the high, middle, and low academic levels selected from the whole class 35% (8/23) of the concepts were used effectively, 22% (5/23) marginally, and 43% (10/23) poorly. Only 1 concept was used incorrectly by 3/6 of the students and identified as a misconception. One of 21 (5%) problem-solving pathway characteristics was used effectively, 7 (33%) marginally, and 13 (62%) poorly. There were very few (0 to 4) problem-solving pathway characteristics used unsuccessfully most were simply not used.

Computational structural mechanics for engine structures

NASA Technical Reports Server (NTRS)

Chamis, C. C.

1989-01-01

The computational structural mechanics (CSM) program at Lewis encompasses: (1) fundamental aspects for formulating and solving structural mechanics problems, and (2) development of integrated software systems to computationally simulate the performance/durability/life of engine structures. It is structured to mainly supplement, complement, and whenever possible replace, costly experimental efforts which are unavoidable during engineering research and development programs. Specific objectives include: investigate unique advantages of parallel and multiprocesses for: reformulating/solving structural mechanics and formulating/solving multidisciplinary mechanics and develop integrated structural system computational simulators for: predicting structural performances, evaluating newly developed methods, and for identifying and prioritizing improved/missing methods needed. Herein the CSM program is summarized with emphasis on the Engine Structures Computational Simulator (ESCS). Typical results obtained using ESCS are described to illustrate its versatility.

Physics-of-Failure Approach to Prognostics

NASA Technical Reports Server (NTRS)

Kulkarni, Chetan S.

2017-01-01

As more and more electric vehicles emerge in our daily operation progressively, a very critical challenge lies in accurate prediction of the electrical components present in the system. In case of electric vehicles, computing remaining battery charge is safety-critical. In order to tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to predict the future state of the system, it is also required to possess knowledge of the current and future operations of the vehicle. In this presentation our approach to develop a system level health monitoring safety indicator for different electronic components is presented which runs estimation and prediction algorithms to determine state-of-charge and estimate remaining useful life of respective components. Given models of the current and future system behavior, the general approach of model-based prognostics can be employed as a solution to the prediction problem and further for decision making.