Interactive web-based learning modules prior to general medicine advanced pharmacy practice experiences.

PubMed

Isaacs, Alex N; Walton, Alison M; Nisly, Sarah A

2015-04-25

To implement and evaluate interactive web-based learning modules prior to advanced pharmacy practice experiences (APPEs) on inpatient general medicine. Three clinical web-based learning modules were developed for use prior to APPEs in 4 health care systems. The aim of the interactive modules was to strengthen baseline clinical knowledge before the APPE to enable the application of learned material through the delivery of patient care. For the primary endpoint, postassessment scores increased overall and for each individual module compared to preassessment scores. Postassessment scores were similar among the health care systems. The survey demonstrated positive student perceptions of this learning experience. Prior to inpatient general medicine APPEs, web-based learning enabled the standardization and assessment of baseline student knowledge across 4 health care systems.

Neural Mechanisms for Integrating Prior Knowledge and Likelihood in Value-Based Probabilistic Inference

PubMed Central

Ting, Chih-Chung; Yu, Chia-Chen; Maloney, Laurence T.

2015-01-01

In Bayesian decision theory, knowledge about the probabilities of possible outcomes is captured by a prior distribution and a likelihood function. The prior reflects past knowledge and the likelihood summarizes current sensory information. The two combined (integrated) form a posterior distribution that allows estimation of the probability of different possible outcomes. In this study, we investigated the neural mechanisms underlying Bayesian integration using a novel lottery decision task in which both prior knowledge and likelihood information about reward probability were systematically manipulated on a trial-by-trial basis. Consistent with Bayesian integration, as sample size increased, subjects tended to weigh likelihood information more compared with prior information. Using fMRI in humans, we found that the medial prefrontal cortex (mPFC) correlated with the mean of the posterior distribution, a statistic that reflects the integration of prior knowledge and likelihood of reward probability. Subsequent analysis revealed that both prior and likelihood information were represented in mPFC and that the neural representations of prior and likelihood in mPFC reflected changes in the behaviorally estimated weights assigned to these different sources of information in response to changes in the environment. Together, these results establish the role of mPFC in prior-likelihood integration and highlight its involvement in representing and integrating these distinct sources of information. PMID:25632152

Does prior domain-specific content knowledge influence students' recall of arguments surrounding interdisciplinary topics?

PubMed

Schmidt, Hiemke K; Rothgangel, Martin; Grube, Dietmar

2017-12-01

Awareness of various arguments can help interactants present opinions, stress points, and build counterarguments during discussions. At school, some topics are taught in a way that students learn to accumulate knowledge and gather arguments, and later employ them during debates. Prior knowledge may facilitate recalling information on well structured, fact-based topics, but does it facilitate recalling arguments during discussions on complex, interdisciplinary topics? We assessed the prior knowledge in domains related to a bioethical topic of 277 students from Germany (approximately 15 years old), their interest in the topic, and their general knowledge. The students read a text with arguments for and against prenatal diagnostics and tried to recall the arguments one week later and again six weeks later. Prior knowledge in various domains related to the topic individually and separately helped students recall the arguments. These relationships were independent of students' interest in the topic and their general knowledge. Copyright © 2017 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

The influence of prior knowledge on the retrieval-directed function of note taking in prior knowledge activation.

PubMed

Wetzels, Sandra A J; Kester, Liesbeth; van Merriënboer, Jeroen J G; Broers, Nick J

2011-06-01

Prior knowledge activation facilitates learning. Note taking during prior knowledge activation (i.e., note taking directed at retrieving information from memory) might facilitate the activation process by enabling learners to build an external representation of their prior knowledge. However, taking notes might be less effective in supporting prior knowledge activation if available prior knowledge is limited. This study investigates the effects of the retrieval-directed function of note taking depending on learners' level of prior knowledge. It is hypothesized that the effectiveness of note taking is influenced by the amount of prior knowledge learners already possess. Sixty-one high school students participated in this study. A prior knowledge test was used to ascertain differences in level of prior knowledge and assign participants to a low or a high prior knowledge group. A 2×2 factorial design was used to investigate the effects of note taking during prior knowledge activation (yes, no) depending on learners' level of prior knowledge (low, high) on mental effort, performance, and mental efficiency. Note taking during prior knowledge activation lowered mental effort and increased mental efficiency for high prior knowledge learners. For low prior knowledge learners, note taking had the opposite effect on mental effort and mental efficiency. The effects of the retrieval-directed function of note taking are influenced by learners' level of prior knowledge. Learners with high prior knowledge benefit from taking notes while activating prior knowledge, whereas note taking has no beneficial effects for learners with limited prior knowledge. ©2010 The British Psychological Society.

A Knowledge-Based Arrangement of Prototypical Neural Representation Prior to Experience Contributes to Selectivity in Upcoming Knowledge Acquisition.

PubMed

Kurashige, Hiroki; Yamashita, Yuichi; Hanakawa, Takashi; Honda, Manabu

2018-01-01

Knowledge acquisition is a process in which one actively selects a piece of information from the environment and assimilates it with prior knowledge. However, little is known about the neural mechanism underlying selectivity in knowledge acquisition. Here we executed a 2-day human experiment to investigate the involvement of characteristic spontaneous activity resembling a so-called "preplay" in selectivity in sentence comprehension, an instance of knowledge acquisition. On day 1, we presented 10 sentences (prior sentences) that were difficult to understand on their own. On the following day, we first measured the resting-state functional magnetic resonance imaging (fMRI). Then, we administered a sentence comprehension task using 20 new sentences (posterior sentences). The posterior sentences were also difficult to understand on their own, but some could be associated with prior sentences to facilitate their understanding. Next, we measured the posterior sentence-induced fMRI to identify the neural representation. From the resting-state fMRI, we extracted the appearances of activity patterns similar to the neural representations for posterior sentences. Importantly, the resting-state fMRI was measured before giving the posterior sentences, and thus such appearances could be considered as preplay-like or prototypical neural representations. We compared the intensities of such appearances with the understanding of posterior sentences. This gave a positive correlation between these two variables, but only if posterior sentences were associated with prior sentences. Additional analysis showed the contribution of the entorhinal cortex, rather than the hippocampus, to the correlation. The present study suggests that prior knowledge-based arrangement of neural activity before an experience contributes to the active selection of information to be learned. Such arrangement prior to an experience resembles preplay activity observed in the rodent brain. In terms of knowledge acquisition, the present study leads to a new view of the brain (or more precisely of the brain's knowledge) as an autopoietic system in which the brain (or knowledge) selects what it should learn by itself, arranges preplay-like activity as a position for the new information in advance, and actively reorganizes itself.

A Knowledge-Based Arrangement of Prototypical Neural Representation Prior to Experience Contributes to Selectivity in Upcoming Knowledge Acquisition

PubMed Central

Kurashige, Hiroki; Yamashita, Yuichi; Hanakawa, Takashi; Honda, Manabu

2018-01-01

Knowledge acquisition is a process in which one actively selects a piece of information from the environment and assimilates it with prior knowledge. However, little is known about the neural mechanism underlying selectivity in knowledge acquisition. Here we executed a 2-day human experiment to investigate the involvement of characteristic spontaneous activity resembling a so-called “preplay” in selectivity in sentence comprehension, an instance of knowledge acquisition. On day 1, we presented 10 sentences (prior sentences) that were difficult to understand on their own. On the following day, we first measured the resting-state functional magnetic resonance imaging (fMRI). Then, we administered a sentence comprehension task using 20 new sentences (posterior sentences). The posterior sentences were also difficult to understand on their own, but some could be associated with prior sentences to facilitate their understanding. Next, we measured the posterior sentence-induced fMRI to identify the neural representation. From the resting-state fMRI, we extracted the appearances of activity patterns similar to the neural representations for posterior sentences. Importantly, the resting-state fMRI was measured before giving the posterior sentences, and thus such appearances could be considered as preplay-like or prototypical neural representations. We compared the intensities of such appearances with the understanding of posterior sentences. This gave a positive correlation between these two variables, but only if posterior sentences were associated with prior sentences. Additional analysis showed the contribution of the entorhinal cortex, rather than the hippocampus, to the correlation. The present study suggests that prior knowledge-based arrangement of neural activity before an experience contributes to the active selection of information to be learned. Such arrangement prior to an experience resembles preplay activity observed in the rodent brain. In terms of knowledge acquisition, the present study leads to a new view of the brain (or more precisely of the brain’s knowledge) as an autopoietic system in which the brain (or knowledge) selects what it should learn by itself, arranges preplay-like activity as a position for the new information in advance, and actively reorganizes itself. PMID:29662446

A Study about Placement Support Using Semantic Similarity

ERIC Educational Resources Information Center

Katz, Marco; van Bruggen, Jan; Giesbers, Bas; Waterink, Wim; Eshuis, Jannes; Koper, Rob

2014-01-01

This paper discusses Latent Semantic Analysis (LSA) as a method for the assessment of prior learning. The Accreditation of Prior Learning (APL) is a procedure to offer learners an individualized curriculum based on their prior experiences and knowledge. The placement decisions in this process are based on the analysis of student material by domain…

The relation between prior knowledge and students' collaborative discovery learning processes

NASA Astrophysics Data System (ADS)

Gijlers, Hannie; de Jong, Ton

2005-03-01

In this study we investigate how prior knowledge influences knowledge development during collaborative discovery learning. Fifteen dyads of students (pre-university education, 15-16 years old) worked on a discovery learning task in the physics field of kinematics. The (face-to-face) communication between students was recorded and the interaction with the environment was logged. Based on students' individual judgments of the truth-value and testability of a series of domain-specific propositions, a detailed description of the knowledge configuration for each dyad was created before they entered the learning environment. Qualitative analyses of two dialogues illustrated that prior knowledge influences the discovery learning processes, and knowledge development in a pair of students. Assessments of student and dyad definitional (domain-specific) knowledge, generic (mathematical and graph) knowledge, and generic (discovery) skills were related to the students' dialogue in different discovery learning processes. Results show that a high level of definitional prior knowledge is positively related to the proportion of communication regarding the interpretation of results. Heterogeneity with respect to generic prior knowledge was positively related to the number of utterances made in the discovery process categories hypotheses generation and experimentation. Results of the qualitative analyses indicated that collaboration between extremely heterogeneous dyads is difficult when the high achiever is not willing to scaffold information and work in the low achiever's zone of proximal development.

Students' inductive reasoning skills and the relevance of prior knowledge: an exploratory study with a computer-based training course on the topic of acne vulgaris.

PubMed

Horn-Ritzinger, Sabine; Bernhardt, Johannes; Horn, Michael; Smolle, Josef

2011-04-01

The importance of inductive instruction in medical education is increasingly growing. Little is known about the relevance of prior knowledge regarding students' inductive reasoning abilities. The purpose is to evaluate this inductive teaching method as a means of fostering higher levels of learning and to explore how individual differences in prior knowledge (high [HPK] vs. low [LPK]) contribute to students' inductive reasoning skills. Twenty-six LPK and 18 HPK students could train twice with an interactive computer-based training object to discover the underlying concept before doing the final comprehension check. Students had a median of 76.9% of correct answers in the first, 90.9% in the second training, and answered 92% of the final assessment questions correctly. More important, 86% of all students succeeded with inductive learning, among them 83% of the HPK students and 89% of the LPK students. Prior knowledge did not predict performance on overall comprehension. This inductive instructional strategy fostered students' deep approaches to learning in a time-effective way.

Prior Knowledge Guides Speech Segregation in Human Auditory Cortex.

PubMed

Wang, Yuanye; Zhang, Jianfeng; Zou, Jiajie; Luo, Huan; Ding, Nai

2018-05-18

Segregating concurrent sound streams is a computationally challenging task that requires integrating bottom-up acoustic cues (e.g. pitch) and top-down prior knowledge about sound streams. In a multi-talker environment, the brain can segregate different speakers in about 100 ms in auditory cortex. Here, we used magnetoencephalographic (MEG) recordings to investigate the temporal and spatial signature of how the brain utilizes prior knowledge to segregate 2 speech streams from the same speaker, which can hardly be separated based on bottom-up acoustic cues. In a primed condition, the participants know the target speech stream in advance while in an unprimed condition no such prior knowledge is available. Neural encoding of each speech stream is characterized by the MEG responses tracking the speech envelope. We demonstrate that an effect in bilateral superior temporal gyrus and superior temporal sulcus is much stronger in the primed condition than in the unprimed condition. Priming effects are observed at about 100 ms latency and last more than 600 ms. Interestingly, prior knowledge about the target stream facilitates speech segregation by mainly suppressing the neural tracking of the non-target speech stream. In sum, prior knowledge leads to reliable speech segregation in auditory cortex, even in the absence of reliable bottom-up speech segregation cue.

Fuzzy-based propagation of prior knowledge to improve large-scale image analysis pipelines

PubMed Central

Mikut, Ralf

2017-01-01

Many automatically analyzable scientific questions are well-posed and a variety of information about expected outcomes is available a priori. Although often neglected, this prior knowledge can be systematically exploited to make automated analysis operations sensitive to a desired phenomenon or to evaluate extracted content with respect to this prior knowledge. For instance, the performance of processing operators can be greatly enhanced by a more focused detection strategy and by direct information about the ambiguity inherent in the extracted data. We present a new concept that increases the result quality awareness of image analysis operators by estimating and distributing the degree of uncertainty involved in their output based on prior knowledge. This allows the use of simple processing operators that are suitable for analyzing large-scale spatiotemporal (3D+t) microscopy images without compromising result quality. On the foundation of fuzzy set theory, we transform available prior knowledge into a mathematical representation and extensively use it to enhance the result quality of various processing operators. These concepts are illustrated on a typical bioimage analysis pipeline comprised of seed point detection, segmentation, multiview fusion and tracking. The functionality of the proposed approach is further validated on a comprehensive simulated 3D+t benchmark data set that mimics embryonic development and on large-scale light-sheet microscopy data of a zebrafish embryo. The general concept introduced in this contribution represents a new approach to efficiently exploit prior knowledge to improve the result quality of image analysis pipelines. The generality of the concept makes it applicable to practically any field with processing strategies that are arranged as linear pipelines. The automated analysis of terabyte-scale microscopy data will especially benefit from sophisticated and efficient algorithms that enable a quantitative and fast readout. PMID:29095927

Feedback Both Helps and Hinders Learning: The Causal Role of Prior Knowledge

ERIC Educational Resources Information Center

Fyfe, Emily R.; Rittle-Johnson, Bethany

2016-01-01

Feedback can be a powerful learning tool, but its effects vary widely. Research has suggested that learners' prior knowledge may moderate the effects of feedback; however, no causal link has been established. In Experiment 1, we randomly assigned elementary school children (N = 108) to a condition based on a crossing of 2 factors: induced strategy…

The Effect of Prior Knowledge and Feedback Type Design on Student Achievement and Satisfaction in Introductory Accounting

ERIC Educational Resources Information Center

Campbell, Donald P.

2013-01-01

This study investigated the effect of student prior knowledge and feedback type on student achievement and satisfaction in an introductory managerial accounting course using computer-based formative assessment tools. The study involved a redesign of the existing Job Order Costing unit using the ADDIE model of instructional design. The…

Gradient-based reliability maps for ACM-based segmentation of hippocampus.

PubMed

Zarpalas, Dimitrios; Gkontra, Polyxeni; Daras, Petros; Maglaveras, Nicos

2014-04-01

Automatic segmentation of deep brain structures, such as the hippocampus (HC), in MR images has attracted considerable scientific attention due to the widespread use of MRI and to the principal role of some structures in various mental disorders. In this literature, there exists a substantial amount of work relying on deformable models incorporating prior knowledge about structures' anatomy and shape information. However, shape priors capture global shape characteristics and thus fail to model boundaries of varying properties; HC boundaries present rich, poor, and missing gradient regions. On top of that, shape prior knowledge is blended with image information in the evolution process, through global weighting of the two terms, again neglecting the spatially varying boundary properties, causing segmentation faults. An innovative method is hereby presented that aims to achieve highly accurate HC segmentation in MR images, based on the modeling of boundary properties at each anatomical location and the inclusion of appropriate image information for each of those, within an active contour model framework. Hence, blending of image information and prior knowledge is based on a local weighting map, which mixes gradient information, regional and whole brain statistical information with a multi-atlas-based spatial distribution map of the structure's labels. Experimental results on three different datasets demonstrate the efficacy and accuracy of the proposed method.

Knowledge Modeling in Prior Art Search

NASA Astrophysics Data System (ADS)

Graf, Erik; Frommholz, Ingo; Lalmas, Mounia; van Rijsbergen, Keith

This study explores the benefits of integrating knowledge representations in prior art patent retrieval. Key to the introduced approach is the utilization of human judgment available in the form of classifications assigned to patent documents. The paper first outlines in detail how a methodology for the extraction of knowledge from such an hierarchical classification system can be established. Further potential ways of integrating this knowledge with existing Information Retrieval paradigms in a scalable and flexible manner are investigated. Finally based on these integration strategies the effectiveness in terms of recall and precision is evaluated in the context of a prior art search task for European patents. As a result of this evaluation it can be established that in general the proposed knowledge expansion techniques are particularly beneficial to recall and, with respect to optimizing field retrieval settings, further result in significant precision gains.

Integrating clinicians, knowledge and data: expert-based cooperative analysis in healthcare decision support

PubMed Central

2010-01-01

Background Decision support in health systems is a highly difficult task, due to the inherent complexity of the process and structures involved. Method This paper introduces a new hybrid methodology Expert-based Cooperative Analysis (EbCA), which incorporates explicit prior expert knowledge in data analysis methods, and elicits implicit or tacit expert knowledge (IK) to improve decision support in healthcare systems. EbCA has been applied to two different case studies, showing its usability and versatility: 1) Bench-marking of small mental health areas based on technical efficiency estimated by EbCA-Data Envelopment Analysis (EbCA-DEA), and 2) Case-mix of schizophrenia based on functional dependency using Clustering Based on Rules (ClBR). In both cases comparisons towards classical procedures using qualitative explicit prior knowledge were made. Bayesian predictive validity measures were used for comparison with expert panels results. Overall agreement was tested by Intraclass Correlation Coefficient in case "1" and kappa in both cases. Results EbCA is a new methodology composed by 6 steps:. 1) Data collection and data preparation; 2) acquisition of "Prior Expert Knowledge" (PEK) and design of the "Prior Knowledge Base" (PKB); 3) PKB-guided analysis; 4) support-interpretation tools to evaluate results and detect inconsistencies (here Implicit Knowledg -IK- might be elicited); 5) incorporation of elicited IK in PKB and repeat till a satisfactory solution; 6) post-processing results for decision support. EbCA has been useful for incorporating PEK in two different analysis methods (DEA and Clustering), applied respectively to assess technical efficiency of small mental health areas and for case-mix of schizophrenia based on functional dependency. Differences in results obtained with classical approaches were mainly related to the IK which could be elicited by using EbCA and had major implications for the decision making in both cases. Discussion This paper presents EbCA and shows the convenience of completing classical data analysis with PEK as a mean to extract relevant knowledge in complex health domains. One of the major benefits of EbCA is iterative elicitation of IK.. Both explicit and tacit or implicit expert knowledge are critical to guide the scientific analysis of very complex decisional problems as those found in health system research. PMID:20920289

Integrating clinicians, knowledge and data: expert-based cooperative analysis in healthcare decision support.

PubMed

Gibert, Karina; García-Alonso, Carlos; Salvador-Carulla, Luis

2010-09-30

Decision support in health systems is a highly difficult task, due to the inherent complexity of the process and structures involved. This paper introduces a new hybrid methodology Expert-based Cooperative Analysis (EbCA), which incorporates explicit prior expert knowledge in data analysis methods, and elicits implicit or tacit expert knowledge (IK) to improve decision support in healthcare systems. EbCA has been applied to two different case studies, showing its usability and versatility: 1) Bench-marking of small mental health areas based on technical efficiency estimated by EbCA-Data Envelopment Analysis (EbCA-DEA), and 2) Case-mix of schizophrenia based on functional dependency using Clustering Based on Rules (ClBR). In both cases comparisons towards classical procedures using qualitative explicit prior knowledge were made. Bayesian predictive validity measures were used for comparison with expert panels results. Overall agreement was tested by Intraclass Correlation Coefficient in case "1" and kappa in both cases. EbCA is a new methodology composed by 6 steps:. 1) Data collection and data preparation; 2) acquisition of "Prior Expert Knowledge" (PEK) and design of the "Prior Knowledge Base" (PKB); 3) PKB-guided analysis; 4) support-interpretation tools to evaluate results and detect inconsistencies (here Implicit Knowledg -IK- might be elicited); 5) incorporation of elicited IK in PKB and repeat till a satisfactory solution; 6) post-processing results for decision support. EbCA has been useful for incorporating PEK in two different analysis methods (DEA and Clustering), applied respectively to assess technical efficiency of small mental health areas and for case-mix of schizophrenia based on functional dependency. Differences in results obtained with classical approaches were mainly related to the IK which could be elicited by using EbCA and had major implications for the decision making in both cases. This paper presents EbCA and shows the convenience of completing classical data analysis with PEK as a mean to extract relevant knowledge in complex health domains. One of the major benefits of EbCA is iterative elicitation of IK.. Both explicit and tacit or implicit expert knowledge are critical to guide the scientific analysis of very complex decisional problems as those found in health system research.

Comfort and experience with online learning: trends over nine years and associations with knowledge.

PubMed

Cook, David A; Thompson, Warren G

2014-07-01

Some evidence suggests that attitude toward computer-based instruction is an important determinant of success in online learning. We sought to determine how comfort using computers and perceptions of prior online learning experiences have changed over the past decade, and how these associate with learning outcomes. Each year from 2003-2011 we conducted a prospective trial of online learning. As part of each year's study, we asked medicine residents about their comfort using computers and if their previous experiences with online learning were favorable. We assessed knowledge using a multiple-choice test. We used regression to analyze associations and changes over time. 371 internal medicine and family medicine residents participated. Neither comfort with computers nor perceptions of prior online learning experiences showed a significant change across years (p > 0.61), with mean comfort rating 3.96 (maximum 5 = very comfortable) and mean experience rating 4.42 (maximum 6 = strongly agree [favorable]). Comfort showed no significant association with knowledge scores (p = 0.39) but perceptions of prior experiences did, with a 1.56% rise in knowledge score for a 1-point rise in experience score (p = 0.02). Correlations among comfort, perceptions of prior experiences, and number of prior experiences were all small and not statistically significant. Comfort with computers and perceptions of prior experience with online learning remained stable over nine years. Prior good experiences (but not comfort with computers) demonstrated a modest association with knowledge outcomes, suggesting that prior course satisfaction may influence subsequent learning.

Polite Web-Based Intelligent Tutors: Can They Improve Learning in Classrooms?

ERIC Educational Resources Information Center

McLaren, Bruce M.; DeLeeuw, Krista E.; Mayer, Richard E.

2011-01-01

Should an intelligent software tutor be polite, in an effort to motivate and cajole students to learn, or should it use more direct language? If it should be polite, under what conditions? In a series of studies in different contexts (e.g., lab versus classroom) with a variety of students (e.g., low prior knowledge versus high prior knowledge),…

Relevant Prior Knowledge Moderates the Effect of Elaboration during Small Group Discussion on Academic Achievement

ERIC Educational Resources Information Center

Van Blankenstein, Floris M.; Dolmans, Diana H. J. M.; Van der Vleuten, Cees P. M.; Schmidt, Henk G.

2013-01-01

This study set out to test whether relevant prior knowledge would moderate a positive effect on academic achievement of elaboration during small-group discussion. In a 2 × 2 experimental design, 66 undergraduate students observed a video showing a small-group problem-based discussion about thunder and lightning. In the video, a teacher asked…

Knowledge-based nonuniform sampling in multidimensional NMR.

PubMed

Schuyler, Adam D; Maciejewski, Mark W; Arthanari, Haribabu; Hoch, Jeffrey C

2011-07-01

The full resolution afforded by high-field magnets is rarely realized in the indirect dimensions of multidimensional NMR experiments because of the time cost of uniformly sampling to long evolution times. Emerging methods utilizing nonuniform sampling (NUS) enable high resolution along indirect dimensions by sampling long evolution times without sampling at every multiple of the Nyquist sampling interval. While the earliest NUS approaches matched the decay of sampling density to the decay of the signal envelope, recent approaches based on coupled evolution times attempt to optimize sampling by choosing projection angles that increase the likelihood of resolving closely-spaced resonances. These approaches employ knowledge about chemical shifts to predict optimal projection angles, whereas prior applications of tailored sampling employed only knowledge of the decay rate. In this work we adapt the matched filter approach as a general strategy for knowledge-based nonuniform sampling that can exploit prior knowledge about chemical shifts and is not restricted to sampling projections. Based on several measures of performance, we find that exponentially weighted random sampling (envelope matched sampling) performs better than shift-based sampling (beat matched sampling). While shift-based sampling can yield small advantages in sensitivity, the gains are generally outweighed by diminished robustness. Our observation that more robust sampling schemes are only slightly less sensitive than schemes highly optimized using prior knowledge about chemical shifts has broad implications for any multidimensional NMR study employing NUS. The results derived from simulated data are demonstrated with a sample application to PfPMT, the phosphoethanolamine methyltransferase of the human malaria parasite Plasmodium falciparum.

Measuring Knowledge Elaboration Based on a Computer-Assisted Knowledge Map Analytical Approach to Collaborative Learning

ERIC Educational Resources Information Center

Zheng, Lanqin; Huang, Ronghuai; Hwang, Gwo-Jen; Yang, Kaicheng

2015-01-01

The purpose of this study is to quantitatively measure the level of knowledge elaboration and explore the relationships between prior knowledge of a group, group performance, and knowledge elaboration in collaborative learning. Two experiments were conducted to investigate the level of knowledge elaboration. The collaborative learning objective in…

Prior Knowledge Facilitates Mutual Gaze Convergence and Head Nodding Synchrony in Face-to-face Communication

PubMed Central

Thepsoonthorn, C.; Yokozuka, T.; Miura, S.; Ogawa, K.; Miyake, Y.

2016-01-01

As prior knowledge is claimed to be an essential key to achieve effective education, we are interested in exploring whether prior knowledge enhances communication effectiveness. To demonstrate the effects of prior knowledge, mutual gaze convergence and head nodding synchrony are observed as indicators of communication effectiveness. We conducted an experiment on lecture task between lecturer and student under 2 conditions: prior knowledge and non-prior knowledge. The students in prior knowledge condition were provided the basic information about the lecture content and were assessed their understanding by the experimenter before starting the lecture while the students in non-prior knowledge had none. The result shows that the interaction in prior knowledge condition establishes significantly higher mutual gaze convergence (t(15.03) = 6.72, p < 0.0001; α = 0.05, n = 20) and head nodding synchrony (t(16.67) = 1.83, p = 0.04; α = 0.05, n = 19) compared to non-prior knowledge condition. This study reveals that prior knowledge facilitates mutual gaze convergence and head nodding synchrony. Furthermore, the interaction with and without prior knowledge can be evaluated by measuring or observing mutual gaze convergence and head nodding synchrony. PMID:27910902

Prior Knowledge Facilitates Mutual Gaze Convergence and Head Nodding Synchrony in Face-to-face Communication.

PubMed

Thepsoonthorn, C; Yokozuka, T; Miura, S; Ogawa, K; Miyake, Y

2016-12-02

As prior knowledge is claimed to be an essential key to achieve effective education, we are interested in exploring whether prior knowledge enhances communication effectiveness. To demonstrate the effects of prior knowledge, mutual gaze convergence and head nodding synchrony are observed as indicators of communication effectiveness. We conducted an experiment on lecture task between lecturer and student under 2 conditions: prior knowledge and non-prior knowledge. The students in prior knowledge condition were provided the basic information about the lecture content and were assessed their understanding by the experimenter before starting the lecture while the students in non-prior knowledge had none. The result shows that the interaction in prior knowledge condition establishes significantly higher mutual gaze convergence (t(15.03) = 6.72, p < 0.0001; α = 0.05, n = 20) and head nodding synchrony (t(16.67) = 1.83, p = 0.04; α = 0.05, n = 19) compared to non-prior knowledge condition. This study reveals that prior knowledge facilitates mutual gaze convergence and head nodding synchrony. Furthermore, the interaction with and without prior knowledge can be evaluated by measuring or observing mutual gaze convergence and head nodding synchrony.

The effects of activating prior topic and metacognitive knowledge on text comprehension scores.

PubMed

Kostons, Danny; van der Werf, Greetje

2015-09-01

Research on prior knowledge activation has consistently shown that activating learners' prior knowledge has beneficial effects on learning. If learners activate their prior knowledge, this activated knowledge serves as a framework for establishing relationships between the knowledge they already possess and new information provided to them. Thus far, prior knowledge activation has dealt primarily with topic knowledge in specific domains. Students, however, likely also possess at least some metacognitive knowledge useful in those domains, which, when activated, should aid in the deployment of helpful strategies during reading. In this study, we investigated the effects of both prior topic knowledge activation (PTKA) and prior metacognitive knowledge activation (PMKA) on text comprehension scores. Eighty-eight students in primary education were randomly distributed amongst the conditions of the 2 × 2 (PTKA yes/no × PMKA yes/no) designed experiment. Results show that activating prior metacognitive knowledge had a beneficial effect on text comprehension, whereas activating prior topic knowledge, after correcting for the amount of prior knowledge, did not. Most studies deal with explicit instruction of metacognitive knowledge, but our results show that this may not be necessary, specifically in the case of students who already have some metacognitive knowledge. However, existing metacognitive knowledge needs to be activated in order for students to make better use of this knowledge. © 2015 The British Psychological Society.

The Effectiveness of Worked Examples Associated with Presentation Format and Prior Knowledge: A Web-Based Experiment

ERIC Educational Resources Information Center

Hsiao, E-Ling

2010-01-01

The aim of this study is to explore whether presentation format and prior knowledge affect the effectiveness of worked examples. The experiment was conducted through a specially designed online instrument. A 2X2X3 factorial before-and-after design was conducted. Three-way ANOVA was employed for data analysis. The result showed first, that prior…

A knowledge-based system for patient image pre-fetching in heterogeneous database environments--modeling, design, and evaluation.

PubMed

Wei, C P; Hu, P J; Sheng, O R

2001-03-01

When performing primary reading on a newly taken radiological examination, a radiologist often needs to reference relevant prior images of the same patient for confirmation or comparison purposes. Support of such image references is of clinical importance and may have significant effects on radiologists' examination reading efficiency, service quality, and work satisfaction. To effectively support such image reference needs, we proposed and developed a knowledge-based patient image pre-fetching system, addressing several challenging requirements of the application that include representation and learning of image reference heuristics and management of data-intensive knowledge inferencing. Moreover, the system demands an extensible and maintainable architecture design capable of effectively adapting to a dynamic environment characterized by heterogeneous and autonomous data source systems. In this paper, we developed a synthesized object-oriented entity- relationship model, a conceptual model appropriate for representing radiologists' prior image reference heuristics that are heuristic oriented and data intensive. We detailed the system architecture and design of the knowledge-based patient image pre-fetching system. Our architecture design is based on a client-mediator-server framework, capable of coping with a dynamic environment characterized by distributed, heterogeneous, and highly autonomous data source systems. To adapt to changes in radiologists' patient prior image reference heuristics, ID3-based multidecision-tree induction and CN2-based multidecision induction learning techniques were developed and evaluated. Experimentally, we examined effects of the pre-fetching system we created on radiologists' examination readings. Preliminary results show that the knowledge-based patient image pre-fetching system more accurately supports radiologists' patient prior image reference needs than the current practice adopted at the study site and that radiologists may become more efficient, consultatively effective, and better satisfied when supported by the pre-fetching system than when relying on the study site's pre-fetching practice.

The Influence of the Knowledge Base on the Development of Mnemonic Strategies.

ERIC Educational Resources Information Center

Ornstein, Peter A.; Naus, Mary J.

A dominant theme in cognitive psychology is that prior knowledge in long-term memory has a strong influence on an individual's cognitive processing. Citing numerous memory studies with children, knowledge base effects are presented as part of a broader picture of memory development. Using the sort/recall procedure (asking subjects to group sets of…

Findings from TIMSS 2007: What Drives Utilization of Inquiry-Based Science Instruction?

ERIC Educational Resources Information Center

Kuzhabekova, Aliya

2015-01-01

Prior research has shown that greatest student achievement in sciences is attributed to "inquiry-based instructional approach", in which the goal of science teaching is nurturing attitudes and skills necessary for independent quest for scientific knowledge. While prior research has clearly demonstrated positive instructional effects of…

Comfort and experience with online learning: trends over nine years and associations with knowledge

PubMed Central

2014-01-01

Background Some evidence suggests that attitude toward computer-based instruction is an important determinant of success in online learning. We sought to determine how comfort using computers and perceptions of prior online learning experiences have changed over the past decade, and how these associate with learning outcomes. Methods Each year from 2003–2011 we conducted a prospective trial of online learning. As part of each year’s study, we asked medicine residents about their comfort using computers and if their previous experiences with online learning were favorable. We assessed knowledge using a multiple-choice test. We used regression to analyze associations and changes over time. Results 371 internal medicine and family medicine residents participated. Neither comfort with computers nor perceptions of prior online learning experiences showed a significant change across years (p > 0.61), with mean comfort rating 3.96 (maximum 5 = very comfortable) and mean experience rating 4.42 (maximum 6 = strongly agree [favorable]). Comfort showed no significant association with knowledge scores (p = 0.39) but perceptions of prior experiences did, with a 1.56% rise in knowledge score for a 1-point rise in experience score (p = 0.02). Correlations among comfort, perceptions of prior experiences, and number of prior experiences were all small and not statistically significant. Conclusions Comfort with computers and perceptions of prior experience with online learning remained stable over nine years. Prior good experiences (but not comfort with computers) demonstrated a modest association with knowledge outcomes, suggesting that prior course satisfaction may influence subsequent learning. PMID:24985690

Profiles of Inconsistent Knowledge in Children's Pathways of Conceptual Change

ERIC Educational Resources Information Center

Schneider, Michael; Hardy, Ilonca

2013-01-01

Conceptual change requires learners to restructure parts of their conceptual knowledge base. Prior research has identified the fragmentation and the integration of knowledge as 2 important component processes of knowledge restructuring but remains unclear as to their relative importance and the time of their occurrence during development. Previous…

The Influence of Prior Knowledge on the Retrieval-Directed Function of Note Taking in Prior Knowledge Activation

ERIC Educational Resources Information Center

Wetzels, Sandra A. J.; Kester, Liesbeth; van Merrienboer, Jeroen J. G.; Broers, Nick J.

2011-01-01

Background: Prior knowledge activation facilitates learning. Note taking during prior knowledge activation (i.e., note taking directed at retrieving information from memory) might facilitate the activation process by enabling learners to build an external representation of their prior knowledge. However, taking notes might be less effective in…

Track Everything: Limiting Prior Knowledge in Online Multi-Object Recognition.

PubMed

Wong, Sebastien C; Stamatescu, Victor; Gatt, Adam; Kearney, David; Lee, Ivan; McDonnell, Mark D

2017-10-01

This paper addresses the problem of online tracking and classification of multiple objects in an image sequence. Our proposed solution is to first track all objects in the scene without relying on object-specific prior knowledge, which in other systems can take the form of hand-crafted features or user-based track initialization. We then classify the tracked objects with a fast-learning image classifier, that is based on a shallow convolutional neural network architecture and demonstrate that object recognition improves when this is combined with object state information from the tracking algorithm. We argue that by transferring the use of prior knowledge from the detection and tracking stages to the classification stage, we can design a robust, general purpose object recognition system with the ability to detect and track a variety of object types. We describe our biologically inspired implementation, which adaptively learns the shape and motion of tracked objects, and apply it to the Neovision2 Tower benchmark data set, which contains multiple object types. An experimental evaluation demonstrates that our approach is competitive with the state-of-the-art video object recognition systems that do make use of object-specific prior knowledge in detection and tracking, while providing additional practical advantages by virtue of its generality.

Creating Illusions of Knowledge: Learning Errors that Contradict Prior Knowledge

ERIC Educational Resources Information Center

Fazio, Lisa K.; Barber, Sarah J.; Rajaram, Suparna; Ornstein, Peter A.; Marsh, Elizabeth J.

2013-01-01

Most people know that the Pacific is the largest ocean on Earth and that Edison invented the light bulb. Our question is whether this knowledge is stable, or if people will incorporate errors into their knowledge bases, even if they have the correct knowledge stored in memory. To test this, we asked participants general-knowledge questions 2 weeks…

Methods and systems for detecting abnormal digital traffic

DOEpatents

Goranson, Craig A [Kennewick, WA; Burnette, John R [Kennewick, WA

2011-03-22

Aspects of the present invention encompass methods and systems for detecting abnormal digital traffic by assigning characterizations of network behaviors according to knowledge nodes and calculating a confidence value based on the characterizations from at least one knowledge node and on weighting factors associated with the knowledge nodes. The knowledge nodes include a characterization model based on prior network information. At least one of the knowledge nodes should not be based on fixed thresholds or signatures. The confidence value includes a quantification of the degree of confidence that the network behaviors constitute abnormal network traffic.

Integrating biological knowledge into variable selection: an empirical Bayes approach with an application in cancer biology

PubMed Central

2012-01-01

Background An important question in the analysis of biochemical data is that of identifying subsets of molecular variables that may jointly influence a biological response. Statistical variable selection methods have been widely used for this purpose. In many settings, it may be important to incorporate ancillary biological information concerning the variables of interest. Pathway and network maps are one example of a source of such information. However, although ancillary information is increasingly available, it is not always clear how it should be used nor how it should be weighted in relation to primary data. Results We put forward an approach in which biological knowledge is incorporated using informative prior distributions over variable subsets, with prior information selected and weighted in an automated, objective manner using an empirical Bayes formulation. We employ continuous, linear models with interaction terms and exploit biochemically-motivated sparsity constraints to permit exact inference. We show an example of priors for pathway- and network-based information and illustrate our proposed method on both synthetic response data and by an application to cancer drug response data. Comparisons are also made to alternative Bayesian and frequentist penalised-likelihood methods for incorporating network-based information. Conclusions The empirical Bayes method proposed here can aid prior elicitation for Bayesian variable selection studies and help to guard against mis-specification of priors. Empirical Bayes, together with the proposed pathway-based priors, results in an approach with a competitive variable selection performance. In addition, the overall procedure is fast, deterministic, and has very few user-set parameters, yet is capable of capturing interplay between molecular players. The approach presented is general and readily applicable in any setting with multiple sources of biological prior knowledge. PMID:22578440

New Knowledge Derived from Learned Knowledge: Functional-Anatomic Correlates of Stimulus Equivalence

ERIC Educational Resources Information Center

Schlund, Michael W.; Hoehn-Saric, Rudolf; Cataldo, Michael F.

2007-01-01

Forming new knowledge based on knowledge established through prior learning is a central feature of higher cognition that is captured in research on stimulus equivalence (SE). Numerous SE investigations show that reinforcing behavior under control of distinct sets of arbitrary conditional relations gives rise to stimulus control by new, "derived"…

Prediction of Slot Shape and Slot Size for Improving the Performance of Microstrip Antennas Using Knowledge-Based Neural Networks.

PubMed

Khan, Taimoor; De, Asok

2014-01-01

In the last decade, artificial neural networks have become very popular techniques for computing different performance parameters of microstrip antennas. The proposed work illustrates a knowledge-based neural networks model for predicting the appropriate shape and accurate size of the slot introduced on the radiating patch for achieving desired level of resonance, gain, directivity, antenna efficiency, and radiation efficiency for dual-frequency operation. By incorporating prior knowledge in neural model, the number of required training patterns is drastically reduced. Further, the neural model incorporated with prior knowledge can be used for predicting response in extrapolation region beyond the training patterns region. For validation, a prototype is also fabricated and its performance parameters are measured. A very good agreement is attained between measured, simulated, and predicted results.

Prediction of Slot Shape and Slot Size for Improving the Performance of Microstrip Antennas Using Knowledge-Based Neural Networks

PubMed Central

De, Asok

2014-01-01

In the last decade, artificial neural networks have become very popular techniques for computing different performance parameters of microstrip antennas. The proposed work illustrates a knowledge-based neural networks model for predicting the appropriate shape and accurate size of the slot introduced on the radiating patch for achieving desired level of resonance, gain, directivity, antenna efficiency, and radiation efficiency for dual-frequency operation. By incorporating prior knowledge in neural model, the number of required training patterns is drastically reduced. Further, the neural model incorporated with prior knowledge can be used for predicting response in extrapolation region beyond the training patterns region. For validation, a prototype is also fabricated and its performance parameters are measured. A very good agreement is attained between measured, simulated, and predicted results. PMID:27382616

Fault diagnosis of sensor networked structures with multiple faults using a virtual beam based approach

NASA Astrophysics Data System (ADS)

Wang, H.; Jing, X. J.

2017-07-01

This paper presents a virtual beam based approach suitable for conducting diagnosis of multiple faults in complex structures with limited prior knowledge of the faults involved. The "virtual beam", a recently-proposed concept for fault detection in complex structures, is applied, which consists of a chain of sensors representing a vibration energy transmission path embedded in the complex structure. Statistical tests and adaptive threshold are particularly adopted for fault detection due to limited prior knowledge of normal operational conditions and fault conditions. To isolate the multiple faults within a specific structure or substructure of a more complex one, a 'biased running' strategy is developed and embedded within the bacterial-based optimization method to construct effective virtual beams and thus to improve the accuracy of localization. The proposed method is easy and efficient to implement for multiple fault localization with limited prior knowledge of normal conditions and faults. With extensive experimental results, it is validated that the proposed method can localize both single fault and multiple faults more effectively than the classical trust index subtract on negative add on positive (TI-SNAP) method.

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

Mendell, Mark J.

This report briefly summarizes, based on recent review articles and selected more recent research reports, current scientific knowledge on two topics: assessing unhealthy levels of indoor D/M in homes and remediating home dampness-related problems to protect health. Based on a comparison of current scientific knowledge to that required to support effective, evidence-based, health-protective policies on home D/M, gaps in knowledge are highlighted, prior questions and research questions specified, and necessary research activities and approaches recommended.

Classroom Action Research on Formative Assessment in a Context-Based Chemistry Course

ERIC Educational Resources Information Center

Vogelzang, Johannes; Admiraal, Wilfried F.

2017-01-01

Context-based science courses stimulate students to reconstruct the information presented by connecting to their prior knowledge and experiences. However, students need support. Formative assessments inform both teacher and students about students' knowledge deficiencies and misconceptions and how students can be supported. Research on formative…

An empirical Bayes approach to network recovery using external knowledge.

PubMed

Kpogbezan, Gino B; van der Vaart, Aad W; van Wieringen, Wessel N; Leday, Gwenaël G R; van de Wiel, Mark A

2017-09-01

Reconstruction of a high-dimensional network may benefit substantially from the inclusion of prior knowledge on the network topology. In the case of gene interaction networks such knowledge may come for instance from pathway repositories like KEGG, or be inferred from data of a pilot study. The Bayesian framework provides a natural means of including such prior knowledge. Based on a Bayesian Simultaneous Equation Model, we develop an appealing Empirical Bayes (EB) procedure that automatically assesses the agreement of the used prior knowledge with the data at hand. We use variational Bayes method for posterior densities approximation and compare its accuracy with that of Gibbs sampling strategy. Our method is computationally fast, and can outperform known competitors. In a simulation study, we show that accurate prior data can greatly improve the reconstruction of the network, but need not harm the reconstruction if wrong. We demonstrate the benefits of the method in an analysis of gene expression data from GEO. In particular, the edges of the recovered network have superior reproducibility (compared to that of competitors) over resampled versions of the data. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Metal Artifact Reduction in X-ray Computed Tomography Using Computer-Aided Design Data of Implants as Prior Information.

PubMed

Ruth, Veikko; Kolditz, Daniel; Steiding, Christian; Kalender, Willi A

2017-06-01

The performance of metal artifact reduction (MAR) methods in x-ray computed tomography (CT) suffers from incorrect identification of metallic implants in the artifact-affected volumetric images. The aim of this study was to investigate potential improvements of state-of-the-art MAR methods by using prior information on geometry and material of the implant. The influence of a novel prior knowledge-based segmentation (PS) compared with threshold-based segmentation (TS) on 2 MAR methods (linear interpolation [LI] and normalized-MAR [NORMAR]) was investigated. The segmentation is the initial step of both MAR methods. Prior knowledge-based segmentation uses 3-dimensional registered computer-aided design (CAD) data as prior knowledge to estimate the correct position and orientation of the metallic objects. Threshold-based segmentation uses an adaptive threshold to identify metal. Subsequently, for LI and NORMAR, the selected voxels are projected into the raw data domain to mark metal areas. Attenuation values in these areas are replaced by different interpolation schemes followed by a second reconstruction. Finally, the previously selected metal voxels are replaced by the metal voxels determined by PS or TS in the initial reconstruction. First, we investigated in an elaborate phantom study if the knowledge of the exact implant shape extracted from the CAD data provided by the manufacturer of the implant can improve the MAR result. Second, the leg of a human cadaver was scanned using a clinical CT system before and after the implantation of an artificial knee joint. The results were compared regarding segmentation accuracy, CT number accuracy, and the restoration of distorted structures. The use of PS improved the efficacy of LI and NORMAR compared with TS. Artifacts caused by insufficient segmentation were reduced, and additional information was made available within the projection data. The estimation of the implant shape was more exact and not dependent on a threshold value. Consequently, the visibility of structures was improved when comparing the new approach to the standard method. This was further confirmed by improved CT value accuracy and reduced image noise. The PS approach based on prior implant information provides image quality which is superior to TS-based MAR, especially when the shape of the metallic implant is complex. The new approach can be useful for improving MAR methods and dose calculations within radiation therapy based on the MAR corrected CT images.

Identification of Boolean Network Models From Time Series Data Incorporating Prior Knowledge.

PubMed

Leifeld, Thomas; Zhang, Zhihua; Zhang, Ping

2018-01-01

Motivation: Mathematical models take an important place in science and engineering. A model can help scientists to explain dynamic behavior of a system and to understand the functionality of system components. Since length of a time series and number of replicates is limited by the cost of experiments, Boolean networks as a structurally simple and parameter-free logical model for gene regulatory networks have attracted interests of many scientists. In order to fit into the biological contexts and to lower the data requirements, biological prior knowledge is taken into consideration during the inference procedure. In the literature, the existing identification approaches can only deal with a subset of possible types of prior knowledge. Results: We propose a new approach to identify Boolean networks from time series data incorporating prior knowledge, such as partial network structure, canalizing property, positive and negative unateness. Using vector form of Boolean variables and applying a generalized matrix multiplication called the semi-tensor product (STP), each Boolean function can be equivalently converted into a matrix expression. Based on this, the identification problem is reformulated as an integer linear programming problem to reveal the system matrix of Boolean model in a computationally efficient way, whose dynamics are consistent with the important dynamics captured in the data. By using prior knowledge the number of candidate functions can be reduced during the inference. Hence, identification incorporating prior knowledge is especially suitable for the case of small size time series data and data without sufficient stimuli. The proposed approach is illustrated with the help of a biological model of the network of oxidative stress response. Conclusions: The combination of efficient reformulation of the identification problem with the possibility to incorporate various types of prior knowledge enables the application of computational model inference to systems with limited amount of time series data. The general applicability of this methodological approach makes it suitable for a variety of biological systems and of general interest for biological and medical research.

The critical success factors and impact of prior knowledge to nursing students when transferring nursing knowledge during nursing clinical practise.

PubMed

Tsai, Ming-Tien; Tsai, Ling-Long

2005-11-01

Nursing practise plays an important role in transferring nursing knowledge to nursing students. From the related literature review, prior knowledge will affect how learners gain new knowledge. There has been no direct examination of the prior knowledge interaction effect on students' performance and its influence on nursing students when evaluating the knowledge transfer success factors. This study explores (1) the critical success factors in transferring nursing knowledge, (2) the impact of prior knowledge when evaluating the success factors for transferring nursing knowledge. This research utilizes in-depth interviews to probe the initial success factor phase. A total of 422 valid questionnaires were conducted by the authors. The data were analysed by comparing the mean score and t-test between two groups. Seventeen critical success factors were identified by the two groups of students. Twelve items were selected to examine the diversity in the two groups. Students with prior knowledge were more independent than the other group. They also preferred self-directed learning over students without prior knowledge. Students who did not have prior knowledge were eager to take every opportunity to gain experience and more readily adopted new knowledge.

The Effects of Prior Knowledge and Instruction on Understanding Image Formation.

ERIC Educational Resources Information Center

Galili, Igal; And Others

1993-01-01

Reports a study (n=27) concerning the knowledge about image formation exhibited by students following instruction in geometrical optics in an activity-based college physics course for prospective elementary teachers. Student diagrams and verbal comments indicate their knowledge can be described as an intermediate state: a hybridization of…

Mitigating Information Overload: The Impact of Context-Based Approach to the Design of Tools for Intelligence Analysts

DTIC Science & Technology

2008-03-01

amount of arriving data, extract actionable information, and integrate it with prior knowledge. Add to that the pressures of today’s fusion center...information, and integrate it with prior knowledge. Add to that the pressures of today’s fusion center climate and it becomes clear that analysts, police... fusion centers, including specifics about how these problems manifest at the Illinois State Police (ISP) Statewide Terrorism and Intelligence Center

An Operational Approach for Building Learning Environments Supporting Cognitive Flexibility

ERIC Educational Resources Information Center

Chieu, Vu Minh

2007-01-01

Constructivism is a learning theory that states that people learn by actively constructing their own knowledge, based on prior knowledge. A significant number of ICT-based constructivist learning systems have been proposed in recent years. According to our analysis, those systems exhibit only a few constructivist principles, and a critical problem…

Indications of Knowledge Retention in the Transition to Higher Education

ERIC Educational Resources Information Center

Jones, Harriet; Black, Beth; Green, Jon; Langton, Phil; Rutherford, Stephen; Scott, Jon; Brown, Sally

2015-01-01

First year undergraduate courses in higher education tend to be designed based on assumptions of students' prior knowledge. Almost 600 undergraduates at five UK universities, studying biological sciences, were given an MCQ test in their first week at university, based on biology A-level (pre-university examination) core criteria. Results…

Predicting Mycobacterium tuberculosis Complex Clades Using Knowledge-Based Bayesian Networks

PubMed Central

Bennett, Kristin P.

2014-01-01

We develop a novel approach for incorporating expert rules into Bayesian networks for classification of Mycobacterium tuberculosis complex (MTBC) clades. The proposed knowledge-based Bayesian network (KBBN) treats sets of expert rules as prior distributions on the classes. Unlike prior knowledge-based support vector machine approaches which require rules expressed as polyhedral sets, KBBN directly incorporates the rules without any modification. KBBN uses data to refine rule-based classifiers when the rule set is incomplete or ambiguous. We develop a predictive KBBN model for 69 MTBC clades found in the SITVIT international collection. We validate the approach using two testbeds that model knowledge of the MTBC obtained from two different experts and large DNA fingerprint databases to predict MTBC genetic clades and sublineages. These models represent strains of MTBC using high-throughput biomarkers called spacer oligonucleotide types (spoligotypes), since these are routinely gathered from MTBC isolates of tuberculosis (TB) patients. Results show that incorporating rules into problems can drastically increase classification accuracy if data alone are insufficient. The SITVIT KBBN is publicly available for use on the World Wide Web. PMID:24864238

Effects of Prior Knowledge on Memory: Implications for Education

ERIC Educational Resources Information Center

Shing, Yee Lee; Brod, Garvin

2016-01-01

The encoding, consolidation, and retrieval of events and facts form the basis for acquiring new skills and knowledge. Prior knowledge can enhance those memory processes considerably and thus foster knowledge acquisition. But prior knowledge can also hinder knowledge acquisition, in particular when the to-be-learned information is inconsistent with…

The Effects of Prior Knowledge Activation on Free Recall and Study Time Allocation.

ERIC Educational Resources Information Center

Machiels-Bongaerts, Maureen; And Others

The effects of mobilizing prior knowledge on information processing were studied. Two hypotheses, the cognitive set-point hypothesis and the selective attention hypothesis, try to account for the facilitation effects of prior knowledge activation. These hypotheses predict different recall patterns as a result of mobilizing prior knowledge. In…

Deepening Understanding of Prior Knowledge: What Diverse First-Generation College Students in the U.S. Can Teach Us

ERIC Educational Resources Information Center

Castillo-Montoya, Milagros

2017-01-01

Educational research indicates that teachers revealing and utilizing students' prior knowledge supports students' academic learning. Yet, the variation in students' prior knowledge is not fully known. To better understand students' prior knowledge, I drew on sociocultural learning theories to examine racially and ethnically diverse college…

Knowledge of Algebra for Teaching: A Framework of Knowledge and Practices

ERIC Educational Resources Information Center

McCrory, Raven; Floden, Robert; Ferrini-Mundy, Joan; Reckase, Mark D.; Senk, Sharon L.

2012-01-01

Defining what teachers need to know to teach algebra successfully is important for informing teacher preparation and professional development efforts. Based on prior research, analysis of video, interviews with teachers, and analysis of textbooks, we define categories of knowledge and practices of teaching for understanding and assessing teachers'…

Main Road Extraction from ZY-3 Grayscale Imagery Based on Directional Mathematical Morphology and VGI Prior Knowledge in Urban Areas

PubMed Central

Liu, Bo; Wu, Huayi; Wang, Yandong; Liu, Wenming

2015-01-01

Main road features extracted from remotely sensed imagery play an important role in many civilian and military applications, such as updating Geographic Information System (GIS) databases, urban structure analysis, spatial data matching and road navigation. Current methods for road feature extraction from high-resolution imagery are typically based on threshold value segmentation. It is difficult however, to completely separate road features from the background. We present a new method for extracting main roads from high-resolution grayscale imagery based on directional mathematical morphology and prior knowledge obtained from the Volunteered Geographic Information found in the OpenStreetMap. The two salient steps in this strategy are: (1) using directional mathematical morphology to enhance the contrast between roads and non-roads; (2) using OpenStreetMap roads as prior knowledge to segment the remotely sensed imagery. Experiments were conducted on two ZiYuan-3 images and one QuickBird high-resolution grayscale image to compare our proposed method to other commonly used techniques for road feature extraction. The results demonstrated the validity and better performance of the proposed method for urban main road feature extraction. PMID:26397832

Use of Elaborative Interrogation to Help Students Acquire Information Consistent with Prior Knowledge and Information Inconsistent with Prior Knowledge.

ERIC Educational Resources Information Center

Woloshyn, Vera E.; And Others

1994-01-01

Thirty-two factual statements, half consistent and half not consistent with subjects' prior knowledge, were processed by 140 sixth and seventh graders. Half were directed to use elaborative interrogation (using prior knowledge) to answer why each statement was true. Across all memory measures, elaborative interrogation subjects performed better…

Brief Report: Teachers' Awareness of the Relationship between Prior Knowledge and New Learning

ERIC Educational Resources Information Center

Journal for Research in Mathematics Education, 2016

2016-01-01

The author examined the degree to which experienced teachers are aware of the relationship between prior knowledge and new learning. Interviews with teachers revealed that they were explicitly aware of when students made connections between prior knowledge and new learning, when they applied their prior knowledge to new contexts, and when they…

"Dare I Ask?": Eliciting Prior Knowledge and Its Implications for Teaching and Learning

ERIC Educational Resources Information Center

Dávila, Liv Thorstensson

2015-01-01

This article examines high school teachers' engagement of newcomer English learner students' prior knowledge. Three central research questions guided this study: 1) To what extent do teachers function as mediators of their students' prior knowledge? 2) What goes into teachers' thinking about how and when to elicit prior knowledge? and 3) How do…

Enhancing students’ mathematical representation and selfefficacy through situation-based learning assisted by geometer’s sketchpad program

NASA Astrophysics Data System (ADS)

Sowanto; Kusumah, Y. S.

2018-05-01

This research was conducted based on the problem of a lack of students’ mathematical representation ability as well as self-efficacy in accomplishing mathematical tasks. To overcome this problem, this research used situation-based learning (SBL) assisted by geometer’s sketchpad program (GSP). This research investigated students’ improvement of mathematical representation ability who were taught under situation-based learning (SBL) assisted by geometer’s sketchpad program (GSP) and regular method that viewed from the whole students’ prior knowledge (high, average, and low level). In addition, this research investigated the difference of students’ self-efficacy after learning was given. This research belongs to quasi experiment research using non-equivalent control group design with purposive sampling. The result of this research showed that students’ enhancement in their mathematical representation ability taught under SBL assisted by GSP was better than the regular method. Also, there was no interaction between learning methods and students prior knowledge in student’ enhancement of mathematical representation ability. There was significant difference of students’ enhancement of mathematical representation ability taught under SBL assisted by GSP viewed from students’ prior knowledge. Furthermore, there was no significant difference in terms of self-efficacy between those who were taught by SBL assisted by GSP with the regular method.

Individual Differences in Learning Entrepreneurship and Their Implications for Web-Based Instruction in E-Business and E-Commerce.

ERIC Educational Resources Information Center

Foster, Jonathan; Lin, Angela

2003-01-01

Discusses results from a survey of graduates following a module in e-business and e-commerce at the University of Sheffield that suggest differences in prior knowledge and cultural background impact students' acquisition of domain knowledge and intellectual and information research skills. Considers implications for Web-based instruction.…

Connecting Learning: Brain-Based Strategies for Linking Prior Knowledge in the Library Media Center

ERIC Educational Resources Information Center

Vanderbilt, Kathi L.

2005-01-01

The brain is a complex organ and learning is a complex process. While there is not complete agreement among researchers about brain-based learning and its direct connection to neuroscience, knowledge about the brain as well as the examination of cognitive psychology, anthropology, professional experience, and educational research can provide…

Building dynamical models from data and prior knowledge: the case of the first period-doubling bifurcation.

PubMed

Aguirre, Luis Antonio; Furtado, Edgar Campos

2007-10-01

This paper reviews some aspects of nonlinear model building from data with (gray box) and without (black box) prior knowledge. The model class is very important because it determines two aspects of the final model, namely (i) the type of nonlinearity that can be accurately approximated and (ii) the type of prior knowledge that can be taken into account. Such features are usually in conflict when it comes to choosing the model class. The problem of model structure selection is also reviewed. It is argued that such a problem is philosophically different depending on the model class and it is suggested that the choice of model class should be performed based on the type of a priori available. A procedure is proposed to build polynomial models from data on a Poincaré section and prior knowledge about the first period-doubling bifurcation, for which the normal form is also polynomial. The final models approximate dynamical data in a least-squares sense and, by design, present the first period-doubling bifurcation at a specified value of parameters. The procedure is illustrated by means of simulated examples.

Using Genetic Programming with Prior Formula Knowledge to Solve Symbolic Regression Problem.

PubMed

Lu, Qiang; Ren, Jun; Wang, Zhiguang

2016-01-01

A researcher can infer mathematical expressions of functions quickly by using his professional knowledge (called Prior Knowledge). But the results he finds may be biased and restricted to his research field due to limitation of his knowledge. In contrast, Genetic Programming method can discover fitted mathematical expressions from the huge search space through running evolutionary algorithms. And its results can be generalized to accommodate different fields of knowledge. However, since GP has to search a huge space, its speed of finding the results is rather slow. Therefore, in this paper, a framework of connection between Prior Formula Knowledge and GP (PFK-GP) is proposed to reduce the space of GP searching. The PFK is built based on the Deep Belief Network (DBN) which can identify candidate formulas that are consistent with the features of experimental data. By using these candidate formulas as the seed of a randomly generated population, PFK-GP finds the right formulas quickly by exploring the search space of data features. We have compared PFK-GP with Pareto GP on regression of eight benchmark problems. The experimental results confirm that the PFK-GP can reduce the search space and obtain the significant improvement in the quality of SR.

Predictive top-down integration of prior knowledge during speech perception.

PubMed

Sohoglu, Ediz; Peelle, Jonathan E; Carlyon, Robert P; Davis, Matthew H

2012-06-20

A striking feature of human perception is that our subjective experience depends not only on sensory information from the environment but also on our prior knowledge or expectations. The precise mechanisms by which sensory information and prior knowledge are integrated remain unclear, with longstanding disagreement concerning whether integration is strictly feedforward or whether higher-level knowledge influences sensory processing through feedback connections. Here we used concurrent EEG and MEG recordings to determine how sensory information and prior knowledge are integrated in the brain during speech perception. We manipulated listeners' prior knowledge of speech content by presenting matching, mismatching, or neutral written text before a degraded (noise-vocoded) spoken word. When speech conformed to prior knowledge, subjective perceptual clarity was enhanced. This enhancement in clarity was associated with a spatiotemporal profile of brain activity uniquely consistent with a feedback process: activity in the inferior frontal gyrus was modulated by prior knowledge before activity in lower-level sensory regions of the superior temporal gyrus. In parallel, we parametrically varied the level of speech degradation, and therefore the amount of sensory detail, so that changes in neural responses attributable to sensory information and prior knowledge could be directly compared. Although sensory detail and prior knowledge both enhanced speech clarity, they had an opposite influence on the evoked response in the superior temporal gyrus. We argue that these data are best explained within the framework of predictive coding in which sensory activity is compared with top-down predictions and only unexplained activity propagated through the cortical hierarchy.

Fostering Upper Secondary Students' Ability to Engage in Practices of Scientific Investigation: a Comparative Analysis of an Explicit and an Implicit Instructional Approach

NASA Astrophysics Data System (ADS)

Vorholzer, Andreas; von Aufschnaiter, Claudia; Boone, William J.

2018-02-01

Inquiry-based teaching is considered as contributing to content-related, procedural, and epistemic learning goals of science education. In this study, a quasi-experimental research design was utilized to investigate to what extent embedding inquiry activities in an explicit and an implicit instructional approach fosters students' ability to engage in three practices of scientific investigation (POSI): (1) formulating questions and hypotheses, (2) planning investigations, (3) analyzing and interpreting data. Both approaches were implemented in a classroom-based intervention conducted in a German upper secondary school (N = 222). Students' procedural knowledge of the three POSI was assessed with a paper-pencil test prior and post to the intervention, their content knowledge and dispositional factors (e.g., cognitive abilities) were gathered once. Results show that not only explicit but also implicit instruction fosters students' knowledge of POSI. While overall explicit instruction was found to be more effective, the findings indicate that the effectiveness depends considerably on the practice addressed. Moreover, findings suggest that both approaches were equally beneficial for all students regardless of their prior content knowledge and their prior procedural knowledge of POSI. Potential conditions for the success of explicit and implicit approaches as well as implications for instruction on POSI in science classrooms and for future research are discussed.

Cognitive Demand Differences in Causal Inferences: Characters' Plans Are More Difficult to Comprehend than Physical Causation

ERIC Educational Resources Information Center

Shears, Connie; Miller, Vanessa; Ball, Megan; Hawkins, Amanda; Griggs, Janna; Varner, Andria

2007-01-01

Readers may draw knowledge-based inferences to connect sentences in text differently depending on the knowledge domain being accessed. Most prior research has focused on the direction of the causal explanation (predictive vs. backward) without regard to the knowledge domain drawn on to support comprehension. We suggest that less cognitive effort…

Smoothing Spline ANOVA Decomposition of Arbitrary Splines: An Application to Eye Movements in Reading

PubMed Central

Matuschek, Hannes; Kliegl, Reinhold; Holschneider, Matthias

2015-01-01

The Smoothing Spline ANOVA (SS-ANOVA) requires a specialized construction of basis and penalty terms in order to incorporate prior knowledge about the data to be fitted. Typically, one resorts to the most general approach using tensor product splines. This implies severe constraints on the correlation structure, i.e. the assumption of isotropy of smoothness can not be incorporated in general. This may increase the variance of the spline fit, especially if only a relatively small set of observations are given. In this article, we propose an alternative method that allows to incorporate prior knowledge without the need to construct specialized bases and penalties, allowing the researcher to choose the spline basis and penalty according to the prior knowledge of the observations rather than choosing them according to the analysis to be done. The two approaches are compared with an artificial example and with analyses of fixation durations during reading. PMID:25816246

Use of prior knowledge for the analysis of high-throughput transcriptomics and metabolomics data

PubMed Central

2014-01-01

Background High-throughput omics technologies have enabled the measurement of many genes or metabolites simultaneously. The resulting high dimensional experimental data poses significant challenges to transcriptomics and metabolomics data analysis methods, which may lead to spurious instead of biologically relevant results. One strategy to improve the results is the incorporation of prior biological knowledge in the analysis. This strategy is used to reduce the solution space and/or to focus the analysis on biological meaningful regions. In this article, we review a selection of these methods used in transcriptomics and metabolomics. We combine the reviewed methods in three groups based on the underlying mathematical model: exploratory methods, supervised methods and estimation of the covariance matrix. We discuss which prior knowledge has been used, how it is incorporated and how it modifies the mathematical properties of the underlying methods. PMID:25033193

The Impact of Concept Mapping on the Process of Problem-Based Learning

ERIC Educational Resources Information Center

Zwaal, Wichard; Otting, Hans

2012-01-01

A concept map is a graphical tool to activate and elaborate on prior knowledge, to support problem solving, promote conceptual thinking and understanding, and to organize and memorize knowledge. The aim of this study is to determine if the use of concept mapping (CM) in a problem-based learning (PBL) curriculum enhances the PBL process. The paper…

Characterizing Solution Concepts in Games Using Knowledge Based Programs

DTIC Science & Technology

2007-01-01

rationalizable strategies [ Bernheim , 1984; Pearce, 1984]. Using a characterization due to Halpern [2006], we can show that if their prior is described...knowledge of rationality. Games and Economic Behavior, 8:6–19, 1995. [ Bernheim , 1984] B. D. Bernheim . Rationalizable strategic behavior. Econometrica, 52

Relations among conceptual knowledge, procedural knowledge, and procedural flexibility in two samples differing in prior knowledge.

PubMed

Schneider, Michael; Rittle-Johnson, Bethany; Star, Jon R

2011-11-01

Competence in many domains rests on children developing conceptual and procedural knowledge, as well as procedural flexibility. However, research on the developmental relations between these different types of knowledge has yielded unclear results, in part because little attention has been paid to the validity of the measures or to the effects of prior knowledge on the relations. To overcome these problems, we modeled the three constructs in the domain of equation solving as latent factors and tested (a) whether the predictive relations between conceptual and procedural knowledge were bidirectional, (b) whether these interrelations were moderated by prior knowledge, and (c) how both constructs contributed to procedural flexibility. We analyzed data from 2 measurement points each from two samples (Ns = 228 and 304) of middle school students who differed in prior knowledge. Conceptual and procedural knowledge had stable bidirectional relations that were not moderated by prior knowledge. Both kinds of knowledge contributed independently to procedural flexibility. The results demonstrate how changes in complex knowledge structures contribute to competence development.

A Research Agenda on Assessing and Remediating Home Dampness and Mold to Reduce Dampness-Related Health Effects

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

Mendell, Mark J.

2015-06-01

This report briefly summarizes, based on recent review articles and selected more recent research reports, current scientific knowledge on two topics: assessing unhealthy levels of indoor D/M in homes and remediating home dampness-related problems to protect health. Based on a comparison of current scientific knowledge to that required to support effective, evidence-based, health-protective policies on home D/M, gaps in knowledge are highlighted, prior questions and research questions specified, and necessary research activities and approaches recommended.

The Influence of Prior Knowledge on Memory: A Developmental Cognitive Neuroscience Perspective

PubMed Central

Brod, Garvin; Werkle-Bergner, Markus; Shing, Yee Lee

2013-01-01

Across ontogenetic development, individuals gather manifold experiences during which they detect regularities in their environment and thereby accumulate knowledge. This knowledge is used to guide behavior, make predictions, and acquire further new knowledge. In this review, we discuss the influence of prior knowledge on memory from both the psychology and the emerging cognitive neuroscience literature and provide a developmental perspective on this topic. Recent neuroscience findings point to a prominent role of the medial prefrontal cortex (mPFC) and of the hippocampus (HC) in the emergence of prior knowledge and in its application during the processes of successful memory encoding, consolidation, and retrieval. We take the lateral PFC into consideration as well and discuss changes in both medial and lateral PFC and HC across development and postulate how these may be related to the development of the use of prior knowledge for remembering. For future direction, we argue that, to measure age differential effects of prior knowledge on memory, it is necessary to distinguish the availability of prior knowledge from its accessibility and use. PMID:24115923

When generating answers benefits arithmetic skill: the importance of prior knowledge.

PubMed

Rittle-Johnson, Bethany; Kmicikewycz, Alexander Oleksij

2008-09-01

People remember information better if they generate the information while studying rather than read the information. However, prior research has not investigated whether this generation effect extends to related but unstudied items and has not been conducted in classroom settings. We compared third graders' success on studied and unstudied multiplication problems after they spent a class period generating answers to problems or reading the answers from a calculator. The effect of condition interacted with prior knowledge. Students with low prior knowledge had higher accuracy in the generate condition, but as prior knowledge increased, the advantage of generating answers decreased. The benefits of generating answers may extend to unstudied items and to classroom settings, but only for learners with low prior knowledge.

Trust from the past: Bayesian Personalized Ranking based Link Prediction in Knowledge Graphs

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

Zhang, Baichuan; Choudhury, Sutanay; Al-Hasan, Mohammad

2016-02-01

Estimating the confidence for a link is a critical task for Knowledge Graph construction. Link prediction, or predicting the likelihood of a link in a knowledge graph based on prior state is a key research direction within this area. We propose a Latent Feature Embedding based link recommendation model for prediction task and utilize Bayesian Personalized Ranking based optimization technique for learning models for each predicate. Experimental results on large-scale knowledge bases such as YAGO2 show that our approach achieves substantially higher performance than several state-of-art approaches. Furthermore, we also study the performance of the link prediction algorithm in termsmore » of topological properties of the Knowledge Graph and present a linear regression model to reason about its expected level of accuracy.« less

Semantically-based priors and nuanced knowledge core for Big Data, Social AI, and language understanding.

PubMed

Olsher, Daniel

2014-10-01

Noise-resistant and nuanced, COGBASE makes 10 million pieces of commonsense data and a host of novel reasoning algorithms available via a family of semantically-driven prior probability distributions. Machine learning, Big Data, natural language understanding/processing, and social AI can draw on COGBASE to determine lexical semantics, infer goals and interests, simulate emotion and affect, calculate document gists and topic models, and link commonsense knowledge to domain models and social, spatial, cultural, and psychological data. COGBASE is especially ideal for social Big Data, which tends to involve highly implicit contexts, cognitive artifacts, difficult-to-parse texts, and deep domain knowledge dependencies. Copyright © 2014 Elsevier Ltd. All rights reserved.

Novel joint TOA/RSSI-based WCE location tracking method without prior knowledge of biological human body tissues.

PubMed

Ito, Takahiro; Anzai, Daisuke; Jianqing Wang

2014-01-01

This paper proposes a novel joint time of arrival (TOA)/received signal strength indicator (RSSI)-based wireless capsule endoscope (WCE) location tracking method without prior knowledge of biological human tissues. Generally, TOA-based localization can achieve much higher localization accuracy than other radio frequency-based localization techniques, whereas wireless signals transmitted from a WCE pass through various kinds of human body tissues, as a result, the propagation velocity inside a human body should be different from one in free space. Because the variation of propagation velocity is mainly affected by the relative permittivity of human body tissues, instead of pre-measurement for the relative permittivity in advance, we simultaneously estimate not only the WCE location but also the relative permittivity information. For this purpose, this paper first derives the relative permittivity estimation model with measured RSSI information. Then, we pay attention to a particle filter algorithm with the TOA-based localization and the RSSI-based relative permittivity estimation. Our computer simulation results demonstrates that the proposed tracking methods with the particle filter can accomplish an excellent localization accuracy of around 2 mm without prior information of the relative permittivity of the human body tissues.

Knowledge-based IMRT treatment planning for prostate cancer.

PubMed

Chanyavanich, Vorakarn; Das, Shiva K; Lee, William R; Lo, Joseph Y

2011-05-01

To demonstrate the feasibility of using a knowledge base of prior treatment plans to generate new prostate intensity modulated radiation therapy (IMRT) plans. Each new case would be matched against others in the knowledge base. Once the best match is identified, that clinically approved plan is used to generate the new plan. A database of 100 prostate IMRT treatment plans was assembled into an information-theoretic system. An algorithm based on mutual information was implemented to identify similar patient cases by matching 2D beam's eye view projections of contours. Ten randomly selected query cases were each matched with the most similar case from the database of prior clinically approved plans. Treatment parameters from the matched case were used to develop new treatment plans. A comparison of the differences in the dose-volume histograms between the new and the original treatment plans were analyzed. On average, the new knowledge-based plan is capable of achieving very comparable planning target volume coverage as the original plan, to within 2% as evaluated for D98, D95, and D1. Similarly, the dose to the rectum and dose to the bladder are also comparable to the original plan. For the rectum, the mean and standard deviation of the dose percentage differences for D20, D30, and D50 are 1.8% +/- 8.5%, -2.5% +/- 13.9%, and -13.9% +/- 23.6%, respectively. For the bladder, the mean and standard deviation of the dose percentage differences for D20, D30, and D50 are -5.9% +/- 10.8%, -12.2% +/- 14.6%, and -24.9% +/- 21.2%, respectively. A negative percentage difference indicates that the new plan has greater dose sparing as compared to the original plan. The authors demonstrate a knowledge-based approach of using prior clinically approved treatment plans to generate clinically acceptable treatment plans of high quality. This semiautomated approach has the potential to improve the efficiency of the treatment planning process while ensuring that high quality plans are developed.

A schema theory analysis of students' think aloud protocols in an STS biology context

NASA Astrophysics Data System (ADS)

Quinlan, Catherine Louise

This dissertation study is a conglomerate of the fields of Science Education and Applied Cognitive Psychology. The goal of this study is to determine what organizational features and knowledge representation patterns high school students exhibit over time for issues pertinent to science and society. Participants are thirteen tenth grade students in a diverse suburban-urban classroom in a northeastern state. Students' think alouds are recorded, pre-, post-, and late-post treatment. Treatment consists of instruction in three Science, Technology, and Society (STS) biology issues, namely the human genome project, nutrition and health, and stem cell research. Coding and analyses are performed using Marshall's knowledge representations---identification knowledge, elaboration knowledge, planning knowledge, and execution knowledge, as well as qualitative research analysis methods. Schema theory, information processing theory, and other applied cognitive theory provide a framework in which to understand and explain students' schema descriptions and progressions over time. The results show that students display five organizational features in their identification and elaboration knowledge. Students also fall into one of four categories according to if they display prior schema or no prior schema, and their orientation "for" or "against," some of the issues. Students with prior schema and orientation "against" display the most robust schema descriptions and schema progressions. Those with no prior schemas and orientation "against" show very modest schema progressions best characterized by their keyword searches. This study shows the importance in considering not only students' integrated schemas but also their individual schemes. A role for the use of a more schema-based instruction that scaffolds student learning is implicated.

The Effects of the Timing of Isolated FFI on the Explicit Knowledge and Written Accuracy of Learners with Different Prior Knowledge of the Linguistic Target

ERIC Educational Resources Information Center

Shintani, Natsuko

2017-01-01

This study examines the effects of the timing of explicit instruction (EI) on grammatical accuracy. A total of 123 learners were divided into two groups: those with some productive knowledge of past-counterfactual conditionals (+Prior Knowledge) and those without such knowledge (-Prior Knowledge). Each group was divided into four conditions. Two…

Active Prior Tactile Knowledge Transfer for Learning Tactual Properties of New Objects

PubMed Central

Feng, Di

2018-01-01

Reusing the tactile knowledge of some previously-explored objects (prior objects) helps us to easily recognize the tactual properties of new objects. In this paper, we enable a robotic arm equipped with multi-modal artificial skin, like humans, to actively transfer the prior tactile exploratory action experiences when it learns the detailed physical properties of new objects. These experiences, or prior tactile knowledge, are built by the feature observations that the robot perceives from multiple sensory modalities, when it applies the pressing, sliding, and static contact movements on objects with different action parameters. We call our method Active Prior Tactile Knowledge Transfer (APTKT), and systematically evaluated its performance by several experiments. Results show that the robot improved the discrimination accuracy by around 10% when it used only one training sample with the feature observations of prior objects. By further incorporating the predictions from the observation models of prior objects as auxiliary features, our method improved the discrimination accuracy by over 20%. The results also show that the proposed method is robust against transferring irrelevant prior tactile knowledge (negative knowledge transfer). PMID:29466300

Influences of Source - Item Contingency and Schematic Knowledge on Source Monitoring: Tests of the Probability-Matching Account

PubMed Central

Bayen, Ute J.; Kuhlmann, Beatrice G.

2010-01-01

The authors investigated conditions under which judgments in source-monitoring tasks are influenced by prior schematic knowledge. According to a probability-matching account of source guessing (Spaniol & Bayen, 2002), when people do not remember the source of information, they match source guessing probabilities to the perceived contingency between sources and item types. When they do not have a representation of a contingency, they base their guesses on prior schematic knowledge. The authors provide support for this account in two experiments with sources presenting information that was expected for one source and somewhat unexpected for another. Schema-relevant information about the sources was provided at the time of encoding. When contingency perception was impeded by dividing attention, participants showed schema-based guessing (Experiment 1). Manipulating source - item contingency also affected guessing (Experiment 2). When this contingency was schema-inconsistent, it superseded schema-based expectations and led to schema-inconsistent guessing. PMID:21603251

Drift-Free Position Estimation of Periodic or Quasi-Periodic Motion Using Inertial Sensors

PubMed Central

Latt, Win Tun; Veluvolu, Kalyana Chakravarthy; Ang, Wei Tech

2011-01-01

Position sensing with inertial sensors such as accelerometers and gyroscopes usually requires other aided sensors or prior knowledge of motion characteristics to remove position drift resulting from integration of acceleration or velocity so as to obtain accurate position estimation. A method based on analytical integration has previously been developed to obtain accurate position estimate of periodic or quasi-periodic motion from inertial sensors using prior knowledge of the motion but without using aided sensors. In this paper, a new method is proposed which employs linear filtering stage coupled with adaptive filtering stage to remove drift and attenuation. The prior knowledge of the motion the proposed method requires is only approximate band of frequencies of the motion. Existing adaptive filtering methods based on Fourier series such as weighted-frequency Fourier linear combiner (WFLC), and band-limited multiple Fourier linear combiner (BMFLC) are modified to combine with the proposed method. To validate and compare the performance of the proposed method with the method based on analytical integration, simulation study is performed using periodic signals as well as real physiological tremor data, and real-time experiments are conducted using an ADXL-203 accelerometer. Results demonstrate that the performance of the proposed method outperforms the existing analytical integration method. PMID:22163935

Automatic Detection of Student Mental Models during Prior Knowledge Activation in MetaTutor

ERIC Educational Resources Information Center

Rus, Vasile; Lintean, Mihai; Azevedo, Roger

2009-01-01

This paper presents several methods to automatically detecting students' mental models in MetaTutor, an intelligent tutoring system that teaches students self-regulatory processes during learning of complex science topics. In particular, we focus on detecting students' mental models based on student-generated paragraphs during prior knowledge…

Mathematical learning models that depend on prior knowledge and instructional strategies

NASA Astrophysics Data System (ADS)

Pritchard, David E.; Lee, Young-Jin; Bao, Lei

2008-06-01

We present mathematical learning models—predictions of student’s knowledge vs amount of instruction—that are based on assumptions motivated by various theories of learning: tabula rasa, constructivist, and tutoring. These models predict the improvement (on the post-test) as a function of the pretest score due to intervening instruction and also depend on the type of instruction. We introduce a connectedness model whose connectedness parameter measures the degree to which the rate of learning is proportional to prior knowledge. Over a wide range of pretest scores on standard tests of introductory physics concepts, it fits high-quality data nearly within error. We suggest that data from MIT have low connectedness (indicating memory-based learning) because the test used the same context and representation as the instruction and that more connected data from the University of Minnesota resulted from instruction in a different representation from the test.

Prior knowledge based mining functional modules from Yeast PPI networks with gene ontology

PubMed Central

2010-01-01

Background In the literature, there are fruitful algorithmic approaches for identification functional modules in protein-protein interactions (PPI) networks. Because of accumulation of large-scale interaction data on multiple organisms and non-recording interaction data in the existing PPI database, it is still emergent to design novel computational techniques that can be able to correctly and scalably analyze interaction data sets. Indeed there are a number of large scale biological data sets providing indirect evidence for protein-protein interaction relationships. Results The main aim of this paper is to present a prior knowledge based mining strategy to identify functional modules from PPI networks with the aid of Gene Ontology. Higher similarity value in Gene Ontology means that two gene products are more functionally related to each other, so it is better to group such gene products into one functional module. We study (i) to encode the functional pairs into the existing PPI networks; and (ii) to use these functional pairs as pairwise constraints to supervise the existing functional module identification algorithms. Topology-based modularity metric and complex annotation in MIPs will be used to evaluate the identified functional modules by these two approaches. Conclusions The experimental results on Yeast PPI networks and GO have shown that the prior knowledge based learning methods perform better than the existing algorithms. PMID:21172053

Knowledge Structures of Entering Computer Networking Students and Their Instructors

ERIC Educational Resources Information Center

DiCerbo, Kristen E.

2007-01-01

Students bring prior knowledge to their learning experiences. This prior knowledge is known to affect how students encode and later retrieve new information learned. Teachers and content developers can use information about students' prior knowledge to create more effective lessons and materials. In many content areas, particularly the sciences,…

Nudging toward Inquiry: Awakening and Building upon Prior Knowledge

ERIC Educational Resources Information Center

Fontichiaro, Kristin, Comp.

2010-01-01

"Prior knowledge" (sometimes called schema or background knowledge) is information one already knows that helps him/her make sense of new information. New learning builds on existing prior knowledge. In traditional reporting-style research projects, students bypass this crucial step and plow right into answer-finding. It's no wonder that many…

Mind wandering during film comprehension: The role of prior knowledge and situational interest.

PubMed

Kopp, Kristopher; Mills, Caitlin; D'Mello, Sidney

2016-06-01

This study assessed the occurrence and factors that influence mind wandering (MW) in the domain of film comprehension. The cascading model of inattention assumes that a stronger mental representation (i.e., a situation model) during comprehension results in less MW. Accordingly, a suppression hypothesis suggests that MW would decrease as a function of having the knowledge of the plot of a film prior to viewing, because the prior-knowledge would help to strengthen the situation model during comprehension. Furthermore, an interest-moderation hypothesis would predict that the suppression effect of prior-knowledge would only emerge when there was interest in viewing the film. In the current experiment, 108 participants either read a short story that depicted the plot (i.e., prior-knowledge condition) or read an unrelated story of equal length (control condition) prior to viewing the short film (32.5 minutes) entitled The Red Balloon. Participants self-reported their interest in viewing the film immediately before the film was presented. MW was tracked using a self-report method targeting instances of MW with metacognitive awareness. Participants in the prior-knowledge condition reported less MW compared with the control condition, thereby supporting the suppression hypothesis. MW also decreased over the duration of the film, but only for those with prior-knowledge of the film. Finally, prior-knowledge effects on MW were only observed when interest was average or high, but not when interest was low.

Engaging Physician Learners Through a Web-Based Platform: Individualized End-of-Life Education.

PubMed

Bergman, Jonathan; Ballon-Landa, Eric; Lerman, Steven E; Kwan, Lorna; Bennett, Carol J; Litwin, Mark S

2016-09-01

Web-based modules provide a convenient and low-cost education platform, yet should be carefully designed to ensure that learners are actively engaged. In order to improve attitudes and knowledge in end-of-life (EOL) care, we developed a web-based educational module that employed hyperlinks to allow users access to auxiliary resources: clinical guidelines and seminal research papers. Participants took pre-test evaluations of attitudes and knowledge regarding EOL care prior to accessing the educational module, and a post-test evaluation following the module intervention. We recorded the type of hyperlinks (guideline or paper) accessed by learners, and stratified participants into groups based on link type accessed (none, either, or both). We used demographic and educational data to develop a multivariate mixed-effects regression analysis to develop adjusted predictions of attitudes and knowledge. 114 individuals participated. The majority had some professional exposure to EOL care (prior instruction 62%; EOL referral 53%; EOL discussion 56%), though most had no family (68%) or personal experience (51%). On bivariate analysis, non-partnered (p = .04), medical student training level (p = .03), prior palliative care referral (p = .02), having a family member (p = .02) and personal experience of EOL care (p < .01) were all associated with linking to auxiliary resources via hyperlinks. When adjusting for confounders, β coefficient estimates and least squares estimation demonstrated that participants clicking on both hyperlink types were more likely to score higher on all knowledge and attitude items, and demonstrate increased score improvements. Auxiliary resources accessible by hyperlink are an effective adjunct to web-based learning in end-of-life care. © The Author(s) 2015.

Television-based health promotion in general practice waiting rooms in London: a cross-sectional study evaluating patients' knowledge and intentions to access dental services.

PubMed

Jawad, Mohammed; Ingram, Sam; Choudhury, Imran; Airebamen, Anne; Christodoulou, Kostakis; Wilson Sharma, Amanda

2016-07-20

This study aimed to evaluate whether television-based dental health promotion initiatives in General Practice waiting rooms would increase patients' knowledge of and intentions to seek dental services. This cross-sectional survey of 2,345 patients attending 49 General Practices in Brent, northwest London, evaluated the 'Life Channel' - a series of six brief health promotion advertisements, including one dental health promotion advertisement, displayed over ten minutes on television in General Practice waiting rooms. Primary outcome measures were a self-reported gain in the knowledge to contact a National Health Service (NHS) and emergency dentist, and an intention to seek dental services, attributed to viewing the Life Channel. Among the 1,088 patients who did not know how to contact an NHS dentist prior to the survey, and the 1,247 patients who did not know how to contact an emergency dentist prior to the survey, 48.0 % (95 % CI 45.0-51.0 %) and 35.1 % (95 % CI 32.4-37.8 %) attributed the Life Channel to educating them how to do so, respectively. Among the 1,605 patients who did not have any intention to contact a dentist prior to the survey, 15.2 % (95 % CI 13.4-17.0 %) attributed the Life Channel to creating such an intention. We report adjusted odds ratios on sociodemographic disparities in this evaluation. Television-based dental health promotion may significantly increase knowledge of and intention to seek dental services in this sample in London. Television-based dental health promotion may appeal more to certain population groups. More research is needed to identify longer term outcomes of television-based health promotion.

Conceptual change strategies in teaching genetics

NASA Astrophysics Data System (ADS)

Batzli, Laura Elizabeth

The purpose of this study was to evaluate the effectiveness of utilizing conceptual change strategies when teaching high school genetics. The study examined the effects of structuring instruction to provide students with cognitive situations which promote conceptual change, specifically instruction was structured to elicit students' prior knowledge. The goal of the study was that the students would not only be able to solve genetics problems and define basic terminology but they would also have constructed more scientific schemas of the actual processes involved in inheritance. This study is based on the constructivist theory of learning and conceptual change research which suggest that students are actively involved in the process of relating new information to prior knowledge as they construct new knowledge. Two sections of biology II classes received inquiry based instruction and participated in structured cooperative learning groups. However, the unique difference in the treatment group's instruction was the use of structured thought time and the resulting social interaction between the students. The treatment group students' instructional design allowed students to socially construct their cognitive knowledge after elicitation of their prior knowledge. In contrast, the instructional design for the control group students allowed them to socially construct their cognitive knowledge of genetics without the individually structured thought time. The results indicated that the conceptual change strategies with individually structured thought time improved the students' scientific mastery of genetics concepts and they maintained fewer post instructional alternative conceptions. Although all students gained the ability to correctly solve genetics problems, the treatment group students were able to explain the processes involved in terms of meiosis. The treatment group students were also able to better apply their knowledge to novel genetic situations. The implications for genetics instruction from these results were discussed.

Family Child Care Learning Environments: Caregiver Knowledge and Practices Related to Early Literacy and Mathematics

ERIC Educational Resources Information Center

Phillips, Beth M.; Morse, Erika E.

2011-01-01

This paper presents findings from a stratified-random survey of family child care providers' backgrounds, caregiving environments, practices, attitudes, and knowledge related to language, literacy, and mathematics development for preschool children. Descriptive results are consistent with prior studies suggesting that home-based providers are…

Assessing the Previous Economic Knowledge of Beginning Students in Germany: Implications for Teaching Economics in Basic Courses

ERIC Educational Resources Information Center

Happ, Roland; Förster, Manuel; Zlatkin-Troitschanskaia, Olga; Carstensen, Vivian

2016-01-01

Study-related prior knowledge plays a decisive role in business and economics degree courses. Prior knowledge has a significant influence on knowledge acquisition in higher education, and teachers need information on it to plan their introductory courses accordingly. Very few studies have been conducted of first-year students' prior economic…

Prior Knowledge Base of Constellations and Bright Stars among Non-Science Majoring Undergraduates and 14-15 Year Old Students

ERIC Educational Resources Information Center

Hintz, Eric G.; Hintz, Maureen L.; Lawler, M. Jeannette

2015-01-01

As part of an effort to improve students' knowledge of constellations and bright stars in an introductory level descriptive astronomy survey course, we measured the baseline knowledge that students bring to the class and how their score evolve over the course of the semester. This baseline is needed by the broader astronomy education research…

Explanation and Prior Knowledge Interact to Guide Learning

ERIC Educational Resources Information Center

Williams, Joseph J.; Lombrozo, Tania

2013-01-01

How do explaining and prior knowledge contribute to learning? Four experiments explored the relationship between explanation and prior knowledge in category learning. The experiments independently manipulated whether participants were prompted to explain the category membership of study observations and whether category labels were informative in…

Sequential Probability Ratio Test for Collision Avoidance Maneuver Decisions

NASA Technical Reports Server (NTRS)

Carpenter, J. Russell; Markley, F. Landis

2010-01-01

When facing a conjunction between space objects, decision makers must chose whether to maneuver for collision avoidance or not. We apply a well-known decision procedure, the sequential probability ratio test, to this problem. We propose two approaches to the problem solution, one based on a frequentist method, and the other on a Bayesian method. The frequentist method does not require any prior knowledge concerning the conjunction, while the Bayesian method assumes knowledge of prior probability densities. Our results show that both methods achieve desired missed detection rates, but the frequentist method's false alarm performance is inferior to the Bayesian method's

The Second Prototype of the Development of a Technological Pedagogical Content Knowledge Based Instructional Design Model: An Implementation Study in a Technology Integration Course

ERIC Educational Resources Information Center

Lee, Chia-Jung; Kim, ChanMin

2014-01-01

This study presents a refined technological pedagogical content knowledge (also known as TPACK) based instructional design model, which was revised using findings from the implementation study of a prior model. The refined model was applied in a technology integration course with 38 preservice teachers. A case study approach was used in this…

The Importance of Prior Knowledge.

ERIC Educational Resources Information Center

Cleary, Linda Miller

1989-01-01

Recounts a college English teacher's experience of reading and rereading Noam Chomsky, building up a greater store of prior knowledge. Argues that Frank Smith provides a theory for the importance of prior knowledge and Chomsky's work provided a personal example with which to interpret and integrate that theory. (RS)

Risk of future cardiovascular disease in women with prior preeclampsia: a focus group study.

PubMed

Seely, Ellen W; Rich-Edwards, Janet; Lui, Janet; Nicklas, Jacinda M; Saxena, Aditi; Tsigas, Eleni; Levkoff, Sue E

2013-12-21

A history of preeclampsia is a risk factor for the future development of hypertension and cardiovascular disease (CVD). The objective of this study was to assess, in women with prior preeclampsia, the level of knowledge regarding the link between preeclampsia and CVD, motivators for and barriers to lifestyle change and interest in a lifestyle modification program to decrease CVD risk following a pregnancy complicated by preeclampsia. Twenty women with a history of preeclampsia participated in 5 phone-based focus groups. Focus groups were recorded, transcribed, and analyzed. Qualitative content analysis was used to identify common themes across focus groups. Consensus was reached on a representative set of themes describing the data. Women with prior preeclampsia were in general unaware of the link between preeclampsia and future CVD but eager to learn about this link and motivated to achieve a healthy lifestyle. Major perceived barriers to lifestyle change were lack of time, cost of healthy foods and family responsibilities. Perceived facilitators included knowledge of the link between preeclampsia and CVD, a desire to stay healthy, and creating a healthy home for their children. Women with prior preeclampsia were interested in the idea of a web-based program focused on lifestyle strategies to decrease CVD risk in women. Women with prior preeclampsia were eager to learn about the link between preeclampsia and CVD and to take steps to reduce CVD risk. A web-based program to help women with prior preeclampsia adopt a healthy lifestyle may be an appropriate strategy for this population.

Mathematical Learning Models that Depend on Prior Knowledge and Instructional Strategies

ERIC Educational Resources Information Center

Pritchard, David E.; Lee, Young-Jin; Bao, Lei

2008-01-01

We present mathematical learning models--predictions of student's knowledge vs amount of instruction--that are based on assumptions motivated by various theories of learning: tabula rasa, constructivist, and tutoring. These models predict the improvement (on the post-test) as a function of the pretest score due to intervening instruction and also…

Epistemic Metacognition in Context: Evaluating and Learning Online Information

ERIC Educational Resources Information Center

Mason, Lucia; Boldrin, Angela; Ariasi, Nicola

2010-01-01

This study examined epistemic metacognition as a reflective activity about knowledge and knowing in the context of online information searching on the Web, and whether it was related to prior knowledge on the topic, study approach, and domain-specific beliefs about science. In addition, we investigated whether Internet-based learning was…

The Role of Structure in Learning Non-Euclidean Geometry

ERIC Educational Resources Information Center

Asmuth, Jennifer A.

2009-01-01

How do people learn novel mathematical information that contradicts prior knowledge? The focus of this thesis is the role of structure in the acquisition of knowledge about hyperbolic geometry, a non-Euclidean geometry. In a series of three experiments, I contrast a more holistic structure--training based on closed figures--with a mathematically…

Exploring expectation effects in EMDR: does prior treatment knowledge affect the degrading effects of eye movements on memories?

PubMed Central

Littel, Marianne; van Schie, Kevin; van den Hout, Marcel A.

2017-01-01

ABSTRACT Background: Eye movement desensitization and reprocessing (EMDR) is an effective psychological treatment for posttraumatic stress disorder. Recalling a memory while simultaneously making eye movements (EM) decreases a memory’s vividness and/or emotionality. It has been argued that non-specific factors, such as treatment expectancy and experimental demand, may contribute to the EMDR’s effectiveness. Objective: The present study was designed to test whether expectations about the working mechanism of EMDR would alter the memory attenuating effects of EM. Two experiments were conducted. In Experiment 1, we examined the effects of pre-existing (non-manipulated) knowledge of EMDR in participants with and without prior knowledge. In Experiment 2, we experimentally manipulated prior knowledge by providing participants without prior knowledge with correct or incorrect information about EMDR’s working mechanism. Method: Participants in both experiments recalled two aversive, autobiographical memories during brief sets of EM (Recall+EM) or keeping eyes stationary (Recall Only). Before and after the intervention, participants scored their memories on vividness and emotionality. A Bayesian approach was used to compare two competing hypotheses on the effects of (existing/given) prior knowledge: (1) Prior (correct) knowledge increases the effects of Recall+EM vs. Recall Only, vs. (2) prior knowledge does not affect the effects of Recall+EM. Results: Recall+EM caused greater reductions in memory vividness and emotionality than Recall Only in all groups, including the incorrect information group. In Experiment 1, both hypotheses were supported by the data: prior knowledge boosted the effects of EM, but only modestly. In Experiment 2, the second hypothesis was clearly supported over the first: providing knowledge of the underlying mechanism of EMDR did not alter the effects of EM. Conclusions: Recall+EM appears to be quite robust against the effects of prior expectations. As Recall+EM is the core component of EMDR, expectancy effects probably contribute little to the effectiveness of EMDR treatment. PMID:29038685

Calculus Instructors' Responses to Prior Knowledge Errors

ERIC Educational Resources Information Center

Talley, Jana Renee

2009-01-01

This study investigates the responses to prior knowledge errors that Calculus I instructors make when assessing students. Prior knowledge is operationalized as any skill or understanding that a student needs to successfully navigate through a Calculus I course. A two part qualitative study consisting of student exams and instructor interviews was…

Signaling Text-Picture Relations in Multimedia Learning: The Influence of Prior Knowledge

ERIC Educational Resources Information Center

Richter, Juliane; Scheiter, Katharina; Eitel, Alexander

2018-01-01

Multimedia integration signals highlight correspondences between text and pictures with the aim of supporting learning from multimedia. A recent meta-analysis revealed that only learners with low domain-specific prior knowledge benefit from multimedia integration signals. To more thoroughly investigate the influence of prior knowledge on the…

Menarche: Prior Knowledge and Experience.

ERIC Educational Resources Information Center

Skandhan, K. P.; And Others

1988-01-01

Recorded menstruation information among 305 young women in India, assessing the differences between those who did and did not have knowledge of menstruation prior to menarche. Those with prior knowledge considered menarche to be a normal physiological function and had a higher rate of regularity, lower rate of dysmenorrhea, and earlier onset of…

Preparing learners with partly incorrect intuitive prior knowledge for learning

PubMed Central

Ohst, Andrea; Fondu, Béatrice M. E.; Glogger, Inga; Nückles, Matthias; Renkl, Alexander

2014-01-01

Learners sometimes have incoherent and fragmented intuitive prior knowledge that is (partly) “incompatible” with the to-be-learned contents. Such knowledge in pieces can cause conceptual disorientation and cognitive overload while learning. We hypothesized that a pre-training intervention providing a generalized schema as a structuring framework for such knowledge in pieces would support (re)organizing-processes of prior knowledge and thus reduce unnecessary cognitive load during subsequent learning. Fifty-six student teachers participated in the experiment. A framework group underwent a pre-training intervention providing a generalized, categorical schema for categorizing primary learning strategies and related but different strategies as a cognitive framework for (re-)organizing their prior knowledge. Our control group received comparable factual information but no framework. Afterwards, all participants learned about primary learning strategies. The framework group claimed to possess higher levels of interest and self-efficacy, achieved higher learning outcomes, and learned more efficiently. Hence, providing a categorical framework can help overcome the barrier of incorrect prior knowledge in pieces. PMID:25071638

In silico model-based inference: a contemporary approach for hypothesis testing in network biology

PubMed Central

Klinke, David J.

2014-01-01

Inductive inference plays a central role in the study of biological systems where one aims to increase their understanding of the system by reasoning backwards from uncertain observations to identify causal relationships among components of the system. These causal relationships are postulated from prior knowledge as a hypothesis or simply a model. Experiments are designed to test the model. Inferential statistics are used to establish a level of confidence in how well our postulated model explains the acquired data. This iterative process, commonly referred to as the scientific method, either improves our confidence in a model or suggests that we revisit our prior knowledge to develop a new model. Advances in technology impact how we use prior knowledge and data to formulate models of biological networks and how we observe cellular behavior. However, the approach for model-based inference has remained largely unchanged since Fisher, Neyman and Pearson developed the ideas in the early 1900’s that gave rise to what is now known as classical statistical hypothesis (model) testing. Here, I will summarize conventional methods for model-based inference and suggest a contemporary approach to aid in our quest to discover how cells dynamically interpret and transmit information for therapeutic aims that integrates ideas drawn from high performance computing, Bayesian statistics, and chemical kinetics. PMID:25139179

In silico model-based inference: a contemporary approach for hypothesis testing in network biology.

PubMed

Klinke, David J

2014-01-01

Inductive inference plays a central role in the study of biological systems where one aims to increase their understanding of the system by reasoning backwards from uncertain observations to identify causal relationships among components of the system. These causal relationships are postulated from prior knowledge as a hypothesis or simply a model. Experiments are designed to test the model. Inferential statistics are used to establish a level of confidence in how well our postulated model explains the acquired data. This iterative process, commonly referred to as the scientific method, either improves our confidence in a model or suggests that we revisit our prior knowledge to develop a new model. Advances in technology impact how we use prior knowledge and data to formulate models of biological networks and how we observe cellular behavior. However, the approach for model-based inference has remained largely unchanged since Fisher, Neyman and Pearson developed the ideas in the early 1900s that gave rise to what is now known as classical statistical hypothesis (model) testing. Here, I will summarize conventional methods for model-based inference and suggest a contemporary approach to aid in our quest to discover how cells dynamically interpret and transmit information for therapeutic aims that integrates ideas drawn from high performance computing, Bayesian statistics, and chemical kinetics. © 2014 American Institute of Chemical Engineers.

Accurate identification of RNA editing sites from primitive sequence with deep neural networks.

PubMed

Ouyang, Zhangyi; Liu, Feng; Zhao, Chenghui; Ren, Chao; An, Gaole; Mei, Chuan; Bo, Xiaochen; Shu, Wenjie

2018-04-16

RNA editing is a post-transcriptional RNA sequence alteration. Current methods have identified editing sites and facilitated research but require sufficient genomic annotations and prior-knowledge-based filtering steps, resulting in a cumbersome, time-consuming identification process. Moreover, these methods have limited generalizability and applicability in species with insufficient genomic annotations or in conditions of limited prior knowledge. We developed DeepRed, a deep learning-based method that identifies RNA editing from primitive RNA sequences without prior-knowledge-based filtering steps or genomic annotations. DeepRed achieved 98.1% and 97.9% area under the curve (AUC) in training and test sets, respectively. We further validated DeepRed using experimentally verified U87 cell RNA-seq data, achieving 97.9% positive predictive value (PPV). We demonstrated that DeepRed offers better prediction accuracy and computational efficiency than current methods with large-scale, mass RNA-seq data. We used DeepRed to assess the impact of multiple factors on editing identification with RNA-seq data from the Association of Biomolecular Resource Facilities and Sequencing Quality Control projects. We explored developmental RNA editing pattern changes during human early embryogenesis and evolutionary patterns in Drosophila species and the primate lineage using DeepRed. Our work illustrates DeepRed's state-of-the-art performance; it may decipher the hidden principles behind RNA editing, making editing detection convenient and effective.

A cautionary note on Bayesian estimation of population size by removal sampling with diffuse priors.

PubMed

Bord, Séverine; Bioche, Christèle; Druilhet, Pierre

2018-05-01

We consider the problem of estimating a population size by removal sampling when the sampling rate is unknown. Bayesian methods are now widespread and allow to include prior knowledge in the analysis. However, we show that Bayes estimates based on default improper priors lead to improper posteriors or infinite estimates. Similarly, weakly informative priors give unstable estimators that are sensitive to the choice of hyperparameters. By examining the likelihood, we show that population size estimates can be stabilized by penalizing small values of the sampling rate or large value of the population size. Based on theoretical results and simulation studies, we propose some recommendations on the choice of the prior. Then, we applied our results to real datasets. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Prior knowledge driven Granger causality analysis on gene regulatory network discovery

DOE PAGES

Yao, Shun; Yoo, Shinjae; Yu, Dantong

2015-08-28

Our study focuses on discovering gene regulatory networks from time series gene expression data using the Granger causality (GC) model. However, the number of available time points (T) usually is much smaller than the number of target genes (n) in biological datasets. The widely applied pairwise GC model (PGC) and other regularization strategies can lead to a significant number of false identifications when n>>T. In this study, we proposed a new method, viz., CGC-2SPR (CGC using two-step prior Ridge regularization) to resolve the problem by incorporating prior biological knowledge about a target gene data set. In our simulation experiments, themore » propose new methodology CGC-2SPR showed significant performance improvement in terms of accuracy over other widely used GC modeling (PGC, Ridge and Lasso) and MI-based (MRNET and ARACNE) methods. In addition, we applied CGC-2SPR to a real biological dataset, i.e., the yeast metabolic cycle, and discovered more true positive edges with CGC-2SPR than with the other existing methods. In our research, we noticed a “ 1+1>2” effect when we combined prior knowledge and gene expression data to discover regulatory networks. Based on causality networks, we made a functional prediction that the Abm1 gene (its functions previously were unknown) might be related to the yeast’s responses to different levels of glucose. In conclusion, our research improves causality modeling by combining heterogeneous knowledge, which is well aligned with the future direction in system biology. Furthermore, we proposed a method of Monte Carlo significance estimation (MCSE) to calculate the edge significances which provide statistical meanings to the discovered causality networks. All of our data and source codes will be available under the link https://bitbucket.org/dtyu/granger-causality/wiki/Home.« less

Spotting Books and Countries: New Approaches to Estimating and Conceptualizing Prior Intelligence

ERIC Educational Resources Information Center

Scott, Kirsten M.; de Wit, Isabella; Deary, Ian J.

2006-01-01

We aimed to design alternative estimates of pre-morbid/prior intelligence to the National Adult Reading Test (NART) and the Spot-the-Word (STW) in order to tap non-vocabulary based knowledge stores. The rationale for the development of the new tests was that more cognitively able individuals acquire and retain more "singular facts" from their…

Prior knowledge-based approach for associating ...

EPA Pesticide Factsheets

Evaluating the potential human health and/or ecological risks associated with exposures to complex chemical mixtures in the ambient environment is one of the central challenges of chemical safety assessment and environmental protection. There is a need for approaches that can help to integrate chemical monitoring and bio-effects data to evaluate risks associated with chemicals present in the environment. We used prior knowledge about chemical-gene interactions to develop a knowledge assembly model for detected chemicals at five locations near two wastewater treatment plants. The assembly model was used to generate hypotheses about the biological impacts of the chemicals at each location. The hypotheses were tested using empirical hepatic gene expression data from fathead minnows exposed for 12 d at each location. Empirical gene expression data was also mapped to the assembly models to statistically evaluate the likelihood of a chemical contributing to the observed biological responses. The prior knowledge approach was able reasonably hypothesize the biological impacts at one site but not the other. Chemicals most likely contributing to the observed biological responses were identified at each location. Despite limitations to the approach, knowledge assembly models have strong potential for associating chemical occurrence with potential biological effects and providing a foundation for hypothesis generation to guide research and/or monitoring efforts relat

How to achieve synergy between medical education and cognitive neuroscience? An exercise on prior knowledge in understanding.

PubMed

Ruiter, Dirk J; van Kesteren, Marlieke T R; Fernandez, Guillen

2012-05-01

A major challenge in contemporary research is how to connect medical education and cognitive neuroscience and achieve synergy between these domains. Based on this starting point we discuss how this may result in a common language about learning, more educationally focused scientific inquiry, and multidisciplinary research projects. As the topic of prior knowledge in understanding plays a strategic role in both medical education and cognitive neuroscience it is used as a central element in our discussion. A critical condition for the acquisition of new knowledge is the existence of prior knowledge, which can be built in a mental model or schema. Formation of schemas is a central event in student-centered active learning, by which mental models are constructed and reconstructed. These theoretical considerations from cognitive psychology foster scientific discussions that may lead to salient issues and questions for research with cognitive neuroscience. Cognitive neuroscience attempts to understand how knowledge, insight and experience are established in the brain and to clarify their neural correlates. Recently, evidence has been obtained that new information processed by the hippocampus can be consolidated into a stable, neocortical network more rapidly if this new information fits readily into a schema. Opportunities for medical education and medical education research can be created in a fruitful dialogue within an educational multidisciplinary platform. In this synergetic setting many questions can be raised by educational scholars interested in evidence-based education that may be highly relevant for integrative research and the further development of medical education.

Using Hypermedia: Effects of Prior Knowledge and Goal Strength.

ERIC Educational Resources Information Center

Last, David A.; O'Donnell, Angela M.; Kelly, Anthony E.

The influences of a student's prior knowledge and desired goal on the difficulties and benefits associated with using hypertext were examined in this study. Participants, 12 students from an undergraduate course in educational psychology, were assigned to either the low or high prior knowledge category. Within these two groups, subjects were…

The Role of Prior Knowledge in Learning from Analogies in Science Texts

ERIC Educational Resources Information Center

Braasch, Jason L. G.; Goldman, Susan R.

2010-01-01

Two experiments examined whether inconsistent effects of analogies in promoting new content learning from text are related to prior knowledge of the analogy "per se." In Experiment 1, college students who demonstrated little understanding of weather systems and different levels of prior knowledge (more vs. less) of an analogous everyday…

Learning gait of quadruped robot without prior knowledge of the environment

NASA Astrophysics Data System (ADS)

Xu, Tao; Chen, Qijun

2012-09-01

Walking is the basic skill of a legged robot, and one of the promising ways to improve the walking performance and its adaptation to environment changes is to let the robot learn its walking by itself. Currently, most of the walking learning methods are based on robot vision system or some external sensing equipment to estimate the walking performance of certain walking parameters, and therefore are usually only applicable under laboratory condition, where environment can be pre-defined. Inspired by the rhythmic swing movement during walking of legged animals and the behavior of their adjusting their walking gait on different walking surfaces, a concept of walking rhythmic pattern(WRP) is proposed to evaluate the walking specialty of legged robot, which is just based on the walking dynamics of the robot. Based on the onboard acceleration sensor data, a method to calculate WRP using power spectrum in frequency domain and diverse smooth filters is also presented. Since the evaluation of WRP is only based on the walking dynamics data of the robot's body, the proposed method doesn't require prior knowledge of environment and thus can be applied in unknown environment. A gait learning approach of legged robots based on WRP and evolution algorithm(EA) is introduced. By using the proposed approach, a quadruped robot can learn its locomotion by its onboard sensing in an unknown environment, where the robot has no prior knowledge about this place. The experimental result proves proportional relationship exits between WRP match score and walking performance of legged robot, which can be used to evaluate the walking performance in walking optimization under unknown environment.

Knowledge-Based Topic Model for Unsupervised Object Discovery and Localization.

PubMed

Niu, Zhenxing; Hua, Gang; Wang, Le; Gao, Xinbo

Unsupervised object discovery and localization is to discover some dominant object classes and localize all of object instances from a given image collection without any supervision. Previous work has attempted to tackle this problem with vanilla topic models, such as latent Dirichlet allocation (LDA). However, in those methods no prior knowledge for the given image collection is exploited to facilitate object discovery. On the other hand, the topic models used in those methods suffer from the topic coherence issue-some inferred topics do not have clear meaning, which limits the final performance of object discovery. In this paper, prior knowledge in terms of the so-called must-links are exploited from Web images on the Internet. Furthermore, a novel knowledge-based topic model, called LDA with mixture of Dirichlet trees, is proposed to incorporate the must-links into topic modeling for object discovery. In particular, to better deal with the polysemy phenomenon of visual words, the must-link is re-defined as that one must-link only constrains one or some topic(s) instead of all topics, which leads to significantly improved topic coherence. Moreover, the must-links are built and grouped with respect to specific object classes, thus the must-links in our approach are semantic-specific , which allows to more efficiently exploit discriminative prior knowledge from Web images. Extensive experiments validated the efficiency of our proposed approach on several data sets. It is shown that our method significantly improves topic coherence and outperforms the unsupervised methods for object discovery and localization. In addition, compared with discriminative methods, the naturally existing object classes in the given image collection can be subtly discovered, which makes our approach well suited for realistic applications of unsupervised object discovery.Unsupervised object discovery and localization is to discover some dominant object classes and localize all of object instances from a given image collection without any supervision. Previous work has attempted to tackle this problem with vanilla topic models, such as latent Dirichlet allocation (LDA). However, in those methods no prior knowledge for the given image collection is exploited to facilitate object discovery. On the other hand, the topic models used in those methods suffer from the topic coherence issue-some inferred topics do not have clear meaning, which limits the final performance of object discovery. In this paper, prior knowledge in terms of the so-called must-links are exploited from Web images on the Internet. Furthermore, a novel knowledge-based topic model, called LDA with mixture of Dirichlet trees, is proposed to incorporate the must-links into topic modeling for object discovery. In particular, to better deal with the polysemy phenomenon of visual words, the must-link is re-defined as that one must-link only constrains one or some topic(s) instead of all topics, which leads to significantly improved topic coherence. Moreover, the must-links are built and grouped with respect to specific object classes, thus the must-links in our approach are semantic-specific , which allows to more efficiently exploit discriminative prior knowledge from Web images. Extensive experiments validated the efficiency of our proposed approach on several data sets. It is shown that our method significantly improves topic coherence and outperforms the unsupervised methods for object discovery and localization. In addition, compared with discriminative methods, the naturally existing object classes in the given image collection can be subtly discovered, which makes our approach well suited for realistic applications of unsupervised object discovery.

Using expert knowledge for test linking.

PubMed

Bolsinova, Maria; Hoijtink, Herbert; Vermeulen, Jorine Adinda; Béguin, Anton

2017-12-01

Linking and equating procedures are used to make the results of different test forms comparable. In the cases where no assumption of random equivalent groups can be made some form of linking design is used. In practice the amount of data available to link the two tests is often very limited due to logistic and security reasons, which affects the precision of linking procedures. This study proposes to enhance the quality of linking procedures based on sparse data by using Bayesian methods which combine the information in the linking data with background information captured in informative prior distributions. We propose two methods for the elicitation of prior knowledge about the difference in difficulty of two tests from subject-matter experts and explain how these results can be used in the specification of priors. To illustrate the proposed methods and evaluate the quality of linking with and without informative priors, an empirical example of linking primary school mathematics tests is presented. The results suggest that informative priors can increase the precision of linking without decreasing the accuracy. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Incorporating prior knowledge induced from stochastic differential equations in the classification of stochastic observations.

PubMed

Zollanvari, Amin; Dougherty, Edward R

2016-12-01

In classification, prior knowledge is incorporated in a Bayesian framework by assuming that the feature-label distribution belongs to an uncertainty class of feature-label distributions governed by a prior distribution. A posterior distribution is then derived from the prior and the sample data. An optimal Bayesian classifier (OBC) minimizes the expected misclassification error relative to the posterior distribution. From an application perspective, prior construction is critical. The prior distribution is formed by mapping a set of mathematical relations among the features and labels, the prior knowledge, into a distribution governing the probability mass across the uncertainty class. In this paper, we consider prior knowledge in the form of stochastic differential equations (SDEs). We consider a vector SDE in integral form involving a drift vector and dispersion matrix. Having constructed the prior, we develop the optimal Bayesian classifier between two models and examine, via synthetic experiments, the effects of uncertainty in the drift vector and dispersion matrix. We apply the theory to a set of SDEs for the purpose of differentiating the evolutionary history between two species.

Automatic Detection of Student Mental Models Based on Natural Language Student Input during Metacognitive Skill Training

ERIC Educational Resources Information Center

Lintean, Mihai; Rus, Vasile; Azevedo, Roger

2012-01-01

This article describes the problem of detecting the student mental models, i.e. students' knowledge states, during the self-regulatory activity of prior knowledge activation in MetaTutor, an intelligent tutoring system that teaches students self-regulation skills while learning complex science topics. The article presents several approaches to…

A Web Browser Interface to Manage the Searching and Organizing of Information on the Web by Learners

ERIC Educational Resources Information Center

Li, Liang-Yi; Chen, Gwo-Dong

2010-01-01

Information Gathering is a knowledge construction process. Web learners make a plan for their Information Gathering task based on their prior knowledge. The plan is evolved with new information encountered and their mental model is constructed through continuously assimilating and accommodating new information gathered from different Web pages. In…

Promoting Uptake of the HPV Vaccine: The Knowledge and Views of School Staff

ERIC Educational Resources Information Center

Rose, Sally B.; Lanumata, Tolotea; Lawton, Beverley A.

2011-01-01

Background: School-based human papillomavirus (HPV)/cervical cancer vaccination programs have been implemented widely, but few studies have investigated the knowledge and views of school staff about this new vaccine. Methods: Prior to the introduction of the HPV vaccine in 2009, we surveyed staff at 14 socioeconomically diverse schools to assess…

Schema Theories as a Base for the Structural Representation of the Knowledge State.

ERIC Educational Resources Information Center

Dochy, F. J. R. C.; Bouwens, M. R. J.

From the view of schema-transfer theory, the use of schemata with their several functions gives an explanation for the facilitative effect of prior knowledge on learning processes. This report gives a theoretical exploration of the concept of schemata, underlying schema theories, and functions of schemata to indicate the importance of schema…

WE-F-BRB-00: New Developments in Knowledge-Based Treatment Planning and Automation

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

NONE

2015-06-15

Advancements in informatics in radiotherapy are opening up opportunities to improve our ability to assess treatment plans. Models on individualizing patient dose constraints from prior patient data and shape relationships have been extensively researched and are now making their way into commercial products. New developments in knowledge based treatment planning involve understanding the impact of the radiation dosimetry on the patient. Akin to radiobiology models that have driven intensity modulated radiotherapy optimization, toxicity and outcome predictions based on treatment plans and prior patient experiences may be the next step in knowledge based planning. In order to realize these predictions, itmore » is necessary to understand how the clinical information can be captured, structured and organized with ontologies and databases designed for recall. Large databases containing radiation dosimetry and outcomes present the opportunity to evaluate treatment plans against predictions of toxicity and disease response. Such evaluations can be based on dose volume histogram or even the full 3-dimensional dose distribution and its relation to the critical anatomy. This session will provide an understanding of ontologies and standard terminologies used to capture clinical knowledge into structured databases; How data can be organized and accessed to utilize the knowledge in planning; and examples of research and clinical efforts to incorporate that clinical knowledge into planning for improved care for our patients. Learning Objectives: Understand the role of standard terminologies, ontologies and data organization in oncology Understand methods to capture clinical toxicity and outcomes in a clinical setting Understand opportunities to learn from clinical data and its application to treatment planning Todd McNutt receives funding from Philips, Elekta and Toshiba for some of the work presented.« less

Improving Bayesian credibility intervals for classifier error rates using maximum entropy empirical priors.

PubMed

Gustafsson, Mats G; Wallman, Mikael; Wickenberg Bolin, Ulrika; Göransson, Hanna; Fryknäs, M; Andersson, Claes R; Isaksson, Anders

2010-06-01

Successful use of classifiers that learn to make decisions from a set of patient examples require robust methods for performance estimation. Recently many promising approaches for determination of an upper bound for the error rate of a single classifier have been reported but the Bayesian credibility interval (CI) obtained from a conventional holdout test still delivers one of the tightest bounds. The conventional Bayesian CI becomes unacceptably large in real world applications where the test set sizes are less than a few hundred. The source of this problem is that fact that the CI is determined exclusively by the result on the test examples. In other words, there is no information at all provided by the uniform prior density distribution employed which reflects complete lack of prior knowledge about the unknown error rate. Therefore, the aim of the study reported here was to study a maximum entropy (ME) based approach to improved prior knowledge and Bayesian CIs, demonstrating its relevance for biomedical research and clinical practice. It is demonstrated how a refined non-uniform prior density distribution can be obtained by means of the ME principle using empirical results from a few designs and tests using non-overlapping sets of examples. Experimental results show that ME based priors improve the CIs when employed to four quite different simulated and two real world data sets. An empirically derived ME prior seems promising for improving the Bayesian CI for the unknown error rate of a designed classifier. Copyright 2010 Elsevier B.V. All rights reserved.

The Effect of Prior Knowledge Activation on Text Recall: An Investigation of Two Conflicting Hypotheses.

ERIC Educational Resources Information Center

Machiels-Bongaerts, Maureen; And Others

Two hypotheses, the cognitive capacity hypothesis and the selective attention hypothesis, try to account for the facilitation effects of prior knowledge activation. They appear to be mutually exclusive since they predict different recall patterns as a result of prior knowledge activation. This study was designed to determine whether the two…

Understanding the Role of Prior Knowledge in a Multimedia Learning Application

ERIC Educational Resources Information Center

Rias, Riaza Mohd; Zaman, Halimah Badioze

2013-01-01

This study looked at the effects that individual differences in prior knowledge have on student understanding in learning with multimedia in a computer science subject. Students were identified as having either low or high prior knowledge from a series of questions asked in a survey conducted at the Faculty of Computer and Mathematical Sciences at…

Prior-based artifact correction (PBAC) in computed tomography

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

Heußer, Thorsten, E-mail: thorsten.heusser@dkfz-heidelberg.de; Brehm, Marcus; Ritschl, Ludwig

2014-02-15

Purpose: Image quality in computed tomography (CT) often suffers from artifacts which may reduce the diagnostic value of the image. In many cases, these artifacts result from missing or corrupt regions in the projection data, e.g., in the case of metal, truncation, and limited angle artifacts. The authors propose a generalized correction method for different kinds of artifacts resulting from missing or corrupt data by making use of available prior knowledge to perform data completion. Methods: The proposed prior-based artifact correction (PBAC) method requires prior knowledge in form of a planning CT of the same patient or in form ofmore » a CT scan of a different patient showing the same body region. In both cases, the prior image is registered to the patient image using a deformable transformation. The registered prior is forward projected and data completion of the patient projections is performed using smooth sinogram inpainting. The obtained projection data are used to reconstruct the corrected image. Results: The authors investigate metal and truncation artifacts in patient data sets acquired with a clinical CT and limited angle artifacts in an anthropomorphic head phantom data set acquired with a gantry-based flat detector CT device. In all cases, the corrected images obtained by PBAC are nearly artifact-free. Compared to conventional correction methods, PBAC achieves better artifact suppression while preserving the patient-specific anatomy at the same time. Further, the authors show that prominent anatomical details in the prior image seem to have only minor impact on the correction result. Conclusions: The results show that PBAC has the potential to effectively correct for metal, truncation, and limited angle artifacts if adequate prior data are available. Since the proposed method makes use of a generalized algorithm, PBAC may also be applicable to other artifacts resulting from missing or corrupt data.« less

Eye Care Quality and Accessibility Improvement in the Community (EQUALITY): impact of an eye health education program on patient knowledge about glaucoma and attitudes about eye care.

PubMed

Rhodes, Lindsay A; Huisingh, Carrie E; McGwin, Gerald; Mennemeyer, Stephen T; Bregantini, Mary; Patel, Nita; Saaddine, Jinan; Crews, John E; Girkin, Christopher A; Owsley, Cynthia

2016-01-01

To assess the impact of the education program of the Eye Care Quality and Accessibility Improvement in the Community (EQUALITY) telemedicine program on at-risk patients' knowledge about glaucoma and attitudes about eye care as well as to assess patient satisfaction with EQUALITY. New or existing patients presenting for a comprehensive eye exam (CEE) at one of two retail-based primary eye clinics were enrolled based on ≥1 of the following at-risk criteria for glaucoma: African Americans ≥40 years of age, Whites ≥50 years of age, diabetes, family history of glaucoma, and/or preexisting diagnosis of glaucoma. A total of 651 patients were enrolled. A questionnaire was administered prior to the patients' CEE and prior to the patients receiving any of the evidence-based eye health education program; a follow-up questionnaire was administered 2-4 weeks later by phone. Baseline and follow-up patient responses regarding knowledge about glaucoma and attitudes about eye care were compared using McNemar's test. Logistic regression models were used to assess the association of patient-level characteristics with improvement in knowledge and attitudes. Overall patient satisfaction was summarized. At follow-up, all patient responses in the knowledge and attitude domains significantly improved from baseline (P≤0.01 for all questions). Those who were unemployed (odds ratio =0.63, 95% confidence interval =0.42-0.95, P=0.026) or had lower education (odds ratio =0.55, 95% confidence interval =0.29-1.02, P=0.058) were less likely to improve their knowledge after adjusting for age, sex, race, and prior glaucoma diagnosis. This association was attenuated after further adjustment for other patient-level characteristics. Ninety-eight percent (n=501) of patients reported being likely to have a CEE within the next 2 years, whereas 63% (n=326) had a CEE in the previous 2 years. Patient satisfaction with EQUALITY was high (99%). Improved knowledge about glaucoma and a high intent to pursue eye care may lead to improved detection of early disease, thus lowering the risk of blindness.

Impact of educational outreach intervention on enhancing health care providers' knowledge about statin therapy prescribing in Malaysian patients with type 2 diabetes mellitus.

PubMed

Elnaem, Mohamed Hassan; Nik Mohamed, Mohamad Haniki; Zaman Huri, Hasniza; Azarisman, Shah M

2018-03-06

Previous research reported underutilization of statin therapy among patients with type 2 diabetes mellitus. Improving health care providers' awareness and understanding of the benefits and risks of statin treatment could be of assistance in optimizing the statin prescribing process. This study aimed to assess health care providers' knowledge related to statin therapy and the impact of educational outreach intervention based on the perceived knowledge. This was a cross-sectional study based on educational outreach intervention targeting physicians and pharmacists in 1 major tertiary hospital in the state of Pahang, Malaysia. Participants responded to a 12-item, validated questionnaire both prior to and after the outreach educational program. Two sessions were conducted separately for 2 cohorts of pharmacists and physicians. The knowledge scores prior to and after the educational intervention were calculated and compared using a paired-samples t-test. The response rate to both pre-and post-educational outreach questionnaires was 91% (40/44). Prior to the intervention, around 84% (n37) of the participants decided to initiate statin therapy for both pre-assessment clinical case scenarios; however, only 27% (n12) could state the clinical benefits of statin therapy. Forty-five percent (n20) could state the drug to drug interactions, and 52.3% (n23) could identify the statin therapy that can be given at any time day/evening. The educational outreach program increased participants' knowledge scores of 1.450 (95% CI, 0.918 to 1.982) point, P < .0005, which is statistically significant. Forty respondents (91%) were of the opinion that statin side effects are the most common cause of treatment discontinuation. This work demonstrated the impact of an educational outreach intervention on improving health care providers' knowledge and beliefs about statin therapy. This type of intervention is considered effective for short-term knowledge enhancement. Further research is needed to test the long-term efficacy of such intervention. © 2018 John Wiley & Sons, Ltd.

When does prior knowledge disproportionately benefit older adults’ memory?

PubMed Central

Badham, Stephen P.; Hay, Mhairi; Foxon, Natasha; Kaur, Kiran; Maylor, Elizabeth A.

2016-01-01

ABSTRACT Material consistent with knowledge/experience is generally more memorable than material inconsistent with knowledge/experience – an effect that can be more extreme in older adults. Four experiments investigated knowledge effects on memory with young and older adults. Memory for familiar and unfamiliar proverbs (Experiment 1) and for common and uncommon scenes (Experiment 2) showed similar knowledge effects across age groups. Memory for person-consistent and person-neutral actions (Experiment 3) showed a greater benefit of prior knowledge in older adults. For cued recall of related and unrelated word pairs (Experiment 4), older adults benefited more from prior knowledge only when it provided uniquely useful additional information beyond the episodic association itself. The current data and literature suggest that prior knowledge has the age-dissociable mnemonic properties of (1) improving memory for the episodes themselves (age invariant), and (2) providing conceptual information about the tasks/stimuli extrinsically to the actual episodic memory (particularly aiding older adults). PMID:26473767

Is an Illustration Always Worth Ten Thousand Words? Effects of Prior Knowledge, Learning Style and Multimedia Illustrations on Text Comprehension.

ERIC Educational Resources Information Center

Ollerenshaw, Alison; Aidman, Eugene; Kidd, Garry

1997-01-01

This study examined comprehension in four groups of undergraduates under text only, multimedia, and two diagram conditions of text supplementation. Results indicated that effects of text supplementation are mediated by prior knowledge and learning style: multimedia appears more beneficial to surface learners with little prior knowledge and makes…

Effects of Prior Knowledge in Mathematics on Learner-Interface Interactions in a Learning-by-Teaching Intelligent Tutoring System

ERIC Educational Resources Information Center

Bringula, Rex P.; Basa, Roselle S.; Dela Cruz, Cecilio; Rodrigo, Ma. Mercedes T.

2016-01-01

This study attempted to determine the influence of prior knowledge in mathematics of students on learner-interface interactions in a learning-by-teaching intelligent tutoring system. One hundred thirty-nine high school students answered a pretest (i.e., the prior knowledge in mathematics) and a posttest. In between the pretest and posttest, they…

The Effect of the States of Prior Knowledge on Question Answering.

ERIC Educational Resources Information Center

Holmes, Betty C.

A study was conducted to gain insight into the question answering abilities of good and poor readers by comparing how well they answered questions when their prior knowledge was at two different levels (high, low) and in four different states. These states of prior knowledge consisted of the ways in which answers to the questions were stored in…

Learning from Instructional Animations: How Does Prior Knowledge Mediate the Effect of Visual Cues?

ERIC Educational Resources Information Center

Arslan-Ari, I.

2018-01-01

The purpose of this study was to investigate the effects of cueing and prior knowledge on learning and mental effort of students studying an animation with narration. This study employed a 2 (no cueing vs. visual cueing) × 2 (low vs. high prior knowledge) between-subjects factorial design. The results revealed a significant interaction effect…

An oral health education programme based on the National Curriculum.

PubMed

Chapman, A; Copestake, S J; Duncan, K

2006-01-01

The aim of this study was to develop and evaluate a teaching programme based on the national curriculum for use in a primary school setting. National Curriculum guidelines were combined with oral health education messages to draw up lesson plans for teachers to deliver. A questionnaire was used to demonstrate children's oral health knowledge prior to the teaching programme, and at 1 and 7 weeks following the programme. The study took place in inner-city, state-run primary schools in Manchester and North London, UK. The subjects were children between the ages of 7 and 8 years from Manchester (n = 58) and North London (n = 30). The main outcome measure was change in knowledge attributable to a newly developed teaching programme. The children in Manchester had a higher level of knowledge prior to the teaching programme. Following the teaching programme, children in both schools showed a significant improvement in dental health knowledge (P < 0.001). Seven weeks later, the Manchester children showed no significant loss of knowledge (P < 0.001). The aims of the National Curriculum were easily integrated with oral health messages. A more widely available teaching resource, such as the one described in this study, would be useful to encourage the teaching profession to take on oral health education without more costly input from dental professionals.

Development of Bilingual Phonological Awareness in Spanish-Speaking English Language Learners: The Roles of Vocabulary, Letter Knowledge, and Prior Phonological Awareness

ERIC Educational Resources Information Center

Anthony, Jason L.; Solari, Emily J.; Williams, Jeffrey M.; Schoger, Kimberly D.; Zhang, Zhou; Branum-Martin, Lee; Francis, David J.

2009-01-01

Theories concerning the development of phonological awareness place special emphasis on lexical and orthographic knowledge. Given the large degree of variability in preschool classrooms that house Spanish-speaking English language learners (ELL), this study controlled for classroom effects by removing classroom means and covariances based on 158…

Knowledge, Attitudes, Beliefs, and Personal Practices regarding Colorectal Cancer Screening among Health Care Professionals in Rural Colorado: A Pilot Survey

ERIC Educational Resources Information Center

Rim, Sun Hee; Zittleman, Linda; Westfall, John M.; Overholser, Linda; Froshaug, Desiree; Coughlin, Steven S.

2009-01-01

Purpose: This study reports the baseline knowledge, attitudes, beliefs, and personal practices of health care professionals regarding colorectal cancer (CRC) screening in the High Plains Research Network (HPRN) of rural Colorado prior to a community-based educational intervention. It also examines the association between health care staff members'…

Predicting fifth-grade students' understanding of ecological science concepts with motivational and cognitive variables

NASA Astrophysics Data System (ADS)

Alao, Solomon

The need to identify factors that contribute to students' understanding of ecological concepts has been widely expressed in recent literature. The purpose of this study was to investigate the relationship between fifth grade students' prior knowledge, learning strategies, interest, and learning goals and their conceptual understanding of ecological science concepts. Subject were 72 students from three fifth grade classrooms located in a metropolitan area of the eastern United States. Students completed the goal commitment, interest, and strategy use questionnaire (GISQ), and a knowledge test designed to assess their prior knowledge and conceptual understanding of ecological science concepts. The learning goals scale assessed intentions to try to learn and understand ecological concepts. The interest scale assessed the feeling and value-related valences that students ascribed to science and ecological science concepts. The strategy use scale assessed the use of two cognitive strategies (monitoring and elaboration). The knowledge test assessed students' understanding of ecological concepts (the relationship between living organisms and their environment). Scores on all measures were examined for gender differences; no significant gender differences were observed. The motivational and cognitive variables contributed to students' understanding of ecological concepts. After accounting for interest, learning goals, and strategy use, prior knowledge accounted for 28% of the total variance in conceptual understanding. After accounting for prior knowledge, interest, learning goals, and strategy use explained 7%, 6%, and 4% of the total variance in conceptual understanding, respectively. More importantly, these variables were interrelated to each other and to conceptual understanding. After controlling for prior knowledge, learning goals, and strategy use, interest did not predict the variance in conceptual understanding. After controlling for prior knowledge, interest, and strategy use, learning goals did not predict the variance in conceptual understanding. And, after controlling for prior knowledge, interest, and learning goals, strategy use did not predict the variance in conceptual understanding. Results of this study indicated that prior knowledge, interest, learning goals, and strategy use should be included in theoretical models design to explain and to predict fifth grade students' understanding of ecological concepts. Results of this study further suggested that curriculum developers and science teachers need to take fifth grade students' prior knowledge of ecological concepts, interest in science and ecological concepts; intentions to learn and understand ecological concepts, and use of cognitive strategies into account when designing instructional contexts to support these students' understanding of ecological concepts.

Simulation Study of Effects of the Blind Deconvolution on Ultrasound Image

NASA Astrophysics Data System (ADS)

He, Xingwu; You, Junchen

2018-03-01

Ultrasonic image restoration is an essential subject in Medical Ultrasound Imaging. However, without enough and precise system knowledge, some traditional image restoration methods based on the system prior knowledge often fail to improve the image quality. In this paper, we use the simulated ultrasound image to find the effectiveness of the blind deconvolution method for ultrasound image restoration. Experimental results demonstrate that the blind deconvolution method can be applied to the ultrasound image restoration and achieve the satisfactory restoration results without the precise prior knowledge, compared with the traditional image restoration method. And with the inaccurate small initial PSF, the results shows blind deconvolution could improve the overall image quality of ultrasound images, like much better SNR and image resolution, and also show the time consumption of these methods. it has no significant increasing on GPU platform.

An Optimization-Based Framework for the Transformation of Incomplete Biological Knowledge into a Probabilistic Structure and Its Application to the Utilization of Gene/Protein Signaling Pathways in Discrete Phenotype Classification.

PubMed

Esfahani, Mohammad Shahrokh; Dougherty, Edward R

2015-01-01

Phenotype classification via genomic data is hampered by small sample sizes that negatively impact classifier design. Utilization of prior biological knowledge in conjunction with training data can improve both classifier design and error estimation via the construction of the optimal Bayesian classifier. In the genomic setting, gene/protein signaling pathways provide a key source of biological knowledge. Although these pathways are neither complete, nor regulatory, with no timing associated with them, they are capable of constraining the set of possible models representing the underlying interaction between molecules. The aim of this paper is to provide a framework and the mathematical tools to transform signaling pathways to prior probabilities governing uncertainty classes of feature-label distributions used in classifier design. Structural motifs extracted from the signaling pathways are mapped to a set of constraints on a prior probability on a Multinomial distribution. Being the conjugate prior for the Multinomial distribution, we propose optimization paradigms to estimate the parameters of a Dirichlet distribution in the Bayesian setting. The performance of the proposed methods is tested on two widely studied pathways: mammalian cell cycle and a p53 pathway model.

Collaborative filtering to improve navigation of large radiology knowledge resources.

PubMed

Kahn, Charles E

2005-06-01

Collaborative filtering is a knowledge-discovery technique that can help guide readers to items of potential interest based on the experience of prior users. This study sought to determine the impact of collaborative filtering on navigation of a large, Web-based radiology knowledge resource. Collaborative filtering was applied to a collection of 1,168 radiology hypertext documents available via the Internet. An item-based collaborative filtering algorithm identified each document's six most closely related documents based on 248,304 page views in an 18-day period. Documents were amended to include links to their related documents, and use was analyzed over the next 5 days. The mean number of documents viewed per visit increased from 1.57 to 1.74 (P < 0.0001). Collaborative filtering can increase a radiology information resource's utilization and can improve its usefulness and ease of navigation. The technique holds promise for improving navigation of large Internet-based radiology knowledge resources.

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

Zhu, Yitan; Xu, Yanxun; Helseth, Donald L.

Background: Genetic interactions play a critical role in cancer development. Existing knowledge about cancer genetic interactions is incomplete, especially lacking evidences derived from large-scale cancer genomics data. The Cancer Genome Atlas (TCGA) produces multimodal measurements across genomics and features of thousands of tumors, which provide an unprecedented opportunity to investigate the interplays of genes in cancer. Methods: We introduce Zodiac, a computational tool and resource to integrate existing knowledge about cancer genetic interactions with new information contained in TCGA data. It is an evolution of existing knowledge by treating it as a prior graph, integrating it with a likelihood modelmore » derived by Bayesian graphical model based on TCGA data, and producing a posterior graph as updated and data-enhanced knowledge. In short, Zodiac realizes “Prior interaction map + TCGA data → Posterior interaction map.” Results: Zodiac provides molecular interactions for about 200 million pairs of genes. All the results are generated from a big-data analysis and organized into a comprehensive database allowing customized search. In addition, Zodiac provides data processing and analysis tools that allow users to customize the prior networks and update the genetic pathways of their interest. Zodiac is publicly available at www.compgenome.org/ZODIAC. Conclusions: Zodiac recapitulates and extends existing knowledge of molecular interactions in cancer. It can be used to explore novel gene-gene interactions, transcriptional regulation, and other types of molecular interplays in cancer.« less

WE-F-BRB-01: The Power of Ontologies and Standardized Terminologies for Capturing Clinical Knowledge

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

Gabriel, P.

2015-06-15

Advancements in informatics in radiotherapy are opening up opportunities to improve our ability to assess treatment plans. Models on individualizing patient dose constraints from prior patient data and shape relationships have been extensively researched and are now making their way into commercial products. New developments in knowledge based treatment planning involve understanding the impact of the radiation dosimetry on the patient. Akin to radiobiology models that have driven intensity modulated radiotherapy optimization, toxicity and outcome predictions based on treatment plans and prior patient experiences may be the next step in knowledge based planning. In order to realize these predictions, itmore » is necessary to understand how the clinical information can be captured, structured and organized with ontologies and databases designed for recall. Large databases containing radiation dosimetry and outcomes present the opportunity to evaluate treatment plans against predictions of toxicity and disease response. Such evaluations can be based on dose volume histogram or even the full 3-dimensional dose distribution and its relation to the critical anatomy. This session will provide an understanding of ontologies and standard terminologies used to capture clinical knowledge into structured databases; How data can be organized and accessed to utilize the knowledge in planning; and examples of research and clinical efforts to incorporate that clinical knowledge into planning for improved care for our patients. Learning Objectives: Understand the role of standard terminologies, ontologies and data organization in oncology Understand methods to capture clinical toxicity and outcomes in a clinical setting Understand opportunities to learn from clinical data and its application to treatment planning Todd McNutt receives funding from Philips, Elekta and Toshiba for some of the work presented.« less

Prior knowledge guided active modules identification: an integrated multi-objective approach.

PubMed

Chen, Weiqi; Liu, Jing; He, Shan

2017-03-14

Active module, defined as an area in biological network that shows striking changes in molecular activity or phenotypic signatures, is important to reveal dynamic and process-specific information that is correlated with cellular or disease states. A prior information guided active module identification approach is proposed to detect modules that are both active and enriched by prior knowledge. We formulate the active module identification problem as a multi-objective optimisation problem, which consists two conflicting objective functions of maximising the coverage of known biological pathways and the activity of the active module simultaneously. Network is constructed from protein-protein interaction database. A beta-uniform-mixture model is used to estimate the distribution of p-values and generate scores for activity measurement from microarray data. A multi-objective evolutionary algorithm is used to search for Pareto optimal solutions. We also incorporate a novel constraints based on algebraic connectivity to ensure the connectedness of the identified active modules. Application of proposed algorithm on a small yeast molecular network shows that it can identify modules with high activities and with more cross-talk nodes between related functional groups. The Pareto solutions generated by the algorithm provides solutions with different trade-off between prior knowledge and novel information from data. The approach is then applied on microarray data from diclofenac-treated yeast cells to build network and identify modules to elucidate the molecular mechanisms of diclofenac toxicity and resistance. Gene ontology analysis is applied to the identified modules for biological interpretation. Integrating knowledge of functional groups into the identification of active module is an effective method and provides a flexible control of balance between pure data-driven method and prior information guidance.

Integration of prior knowledge into dense image matching for video surveillance

NASA Astrophysics Data System (ADS)

Menze, M.; Heipke, C.

2014-08-01

Three-dimensional information from dense image matching is a valuable input for a broad range of vision applications. While reliable approaches exist for dedicated stereo setups they do not easily generalize to more challenging camera configurations. In the context of video surveillance the typically large spatial extent of the region of interest and repetitive structures in the scene render the application of dense image matching a challenging task. In this paper we present an approach that derives strong prior knowledge from a planar approximation of the scene. This information is integrated into a graph-cut based image matching framework that treats the assignment of optimal disparity values as a labelling task. Introducing the planar prior heavily reduces ambiguities together with the search space and increases computational efficiency. The results provide a proof of concept of the proposed approach. It allows the reconstruction of dense point clouds in more general surveillance camera setups with wider stereo baselines.

Stochastic formulation of patient positioning using linac-mounted cone beam imaging with prior knowledge

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

Hoegele, W.; Loeschel, R.; Dobler, B.

2011-02-15

Purpose: In this work, a novel stochastic framework for patient positioning based on linac-mounted CB projections is introduced. Based on this formulation, the most probable shifts and rotations of the patient are estimated, incorporating interfractional deformations of patient anatomy and other uncertainties associated with patient setup. Methods: The target position is assumed to be defined by and is stochastically determined from positions of various features such as anatomical landmarks or markers in CB projections, i.e., radiographs acquired with a CB-CT system. The patient positioning problem of finding the target location from CB projections is posed as an inverse problem withmore » prior knowledge and is solved using a Bayesian maximum a posteriori (MAP) approach. The prior knowledge is three-fold and includes the accuracy of an initial patient setup (such as in-room laser and skin marks), the plasticity of the body (relative shifts between target and features), and the feature detection error in CB projections (which may vary depending on specific detection algorithm and feature type). For this purpose, MAP estimators are derived and a procedure of using them in clinical practice is outlined. Furthermore, a rule of thumb is theoretically derived, relating basic parameters of the prior knowledge (initial setup accuracy, plasticity of the body, and number of features) and the parameters of CB data acquisition (number of projections and accuracy of feature detection) to the expected estimation accuracy. Results: MAP estimation can be applied to arbitrary features and detection algorithms. However, to experimentally demonstrate its applicability and to perform the validation of the algorithm, a water-equivalent, deformable phantom with features represented by six 1 mm chrome balls were utilized. These features were detected in the cone beam projections (XVI, Elekta Synergy) by a local threshold method for demonstration purposes only. The accuracy of estimation (strongly varying for different plasticity parameters of the body) agreed with the rule of thumb formula. Moreover, based on this rule of thumb formula, about 20 projections for 6 detectable features seem to be sufficient for a target estimation accuracy of 0.2 cm, even for relatively large feature detection errors with standard deviation of 0.5 cm and spatial displacements of the features with standard deviation of 0.5 cm. Conclusions: The authors have introduced a general MAP-based patient setup algorithm accounting for different sources of uncertainties, which are utilized as the prior knowledge in a transparent way. This new framework can be further utilized for different clinical sites, as well as theoretical developments in the field of patient positioning for radiotherapy.« less

Novel keyword co-occurrence network-based methods to foster systematic reviews of scientific literature.

PubMed

Radhakrishnan, Srinivasan; Erbis, Serkan; Isaacs, Jacqueline A; Kamarthi, Sagar

2017-01-01

Systematic reviews of scientific literature are important for mapping the existing state of research and highlighting further growth channels in a field of study, but systematic reviews are inherently tedious, time consuming, and manual in nature. In recent years, keyword co-occurrence networks (KCNs) are exploited for knowledge mapping. In a KCN, each keyword is represented as a node and each co-occurrence of a pair of words is represented as a link. The number of times that a pair of words co-occurs in multiple articles constitutes the weight of the link connecting the pair. The network constructed in this manner represents cumulative knowledge of a domain and helps to uncover meaningful knowledge components and insights based on the patterns and strength of links between keywords that appear in the literature. In this work, we propose a KCN-based approach that can be implemented prior to undertaking a systematic review to guide and accelerate the review process. The novelty of this method lies in the new metrics used for statistical analysis of a KCN that differ from those typically used for KCN analysis. The approach is demonstrated through its application to nano-related Environmental, Health, and Safety (EHS) risk literature. The KCN approach identified the knowledge components, knowledge structure, and research trends that match with those discovered through a traditional systematic review of the nanoEHS field. Because KCN-based analyses can be conducted more quickly to explore a vast amount of literature, this method can provide a knowledge map and insights prior to undertaking a rigorous traditional systematic review. This two-step approach can significantly reduce the effort and time required for a traditional systematic literature review. The proposed KCN-based pre-systematic review method is universal. It can be applied to any scientific field of study to prepare a knowledge map.

Novel keyword co-occurrence network-based methods to foster systematic reviews of scientific literature

PubMed Central

Isaacs, Jacqueline A.

2017-01-01

Systematic reviews of scientific literature are important for mapping the existing state of research and highlighting further growth channels in a field of study, but systematic reviews are inherently tedious, time consuming, and manual in nature. In recent years, keyword co-occurrence networks (KCNs) are exploited for knowledge mapping. In a KCN, each keyword is represented as a node and each co-occurrence of a pair of words is represented as a link. The number of times that a pair of words co-occurs in multiple articles constitutes the weight of the link connecting the pair. The network constructed in this manner represents cumulative knowledge of a domain and helps to uncover meaningful knowledge components and insights based on the patterns and strength of links between keywords that appear in the literature. In this work, we propose a KCN-based approach that can be implemented prior to undertaking a systematic review to guide and accelerate the review process. The novelty of this method lies in the new metrics used for statistical analysis of a KCN that differ from those typically used for KCN analysis. The approach is demonstrated through its application to nano-related Environmental, Health, and Safety (EHS) risk literature. The KCN approach identified the knowledge components, knowledge structure, and research trends that match with those discovered through a traditional systematic review of the nanoEHS field. Because KCN-based analyses can be conducted more quickly to explore a vast amount of literature, this method can provide a knowledge map and insights prior to undertaking a rigorous traditional systematic review. This two-step approach can significantly reduce the effort and time required for a traditional systematic literature review. The proposed KCN-based pre-systematic review method is universal. It can be applied to any scientific field of study to prepare a knowledge map. PMID:28328983

Bayesian hierarchical functional data analysis via contaminated informative priors.

PubMed

Scarpa, Bruno; Dunson, David B

2009-09-01

A variety of flexible approaches have been proposed for functional data analysis, allowing both the mean curve and the distribution about the mean to be unknown. Such methods are most useful when there is limited prior information. Motivated by applications to modeling of temperature curves in the menstrual cycle, this article proposes a flexible approach for incorporating prior information in semiparametric Bayesian analyses of hierarchical functional data. The proposed approach is based on specifying the distribution of functions as a mixture of a parametric hierarchical model and a nonparametric contamination. The parametric component is chosen based on prior knowledge, while the contamination is characterized as a functional Dirichlet process. In the motivating application, the contamination component allows unanticipated curve shapes in unhealthy menstrual cycles. Methods are developed for posterior computation, and the approach is applied to data from a European fecundability study.

Learners' strategies for reconstructing cognitive frameworks and navigating conceptual change from prior conception to consensual genetics knowledge

NASA Astrophysics Data System (ADS)

Parrott, Annette M.

Problem. Science teachers are charged with preparing students to become scientifically literate individuals. Teachers are given curriculum that specifies the knowledge that students should come away with; however, they are not necessarily aware of the knowledge with which the student arrives or how best to help them navigate between the two knowledge states. Educators must be aware, not only of where their students are conceptually, but how their students move from their prior knowledge and naive theories, to scientifically acceptable theories. The understanding of how students navigate this course has the potential to revolutionize educational practices. Methods. This study explored how five 9th grade biology students reconstructed their cognitive frameworks and navigated conceptual change from prior conception to consensual genetics knowledge. The research questions investigated were: (1) how do students in the process of changing their naive science theories to accepted science theories describe their journey from prior knowledge to current conception, and (2) what are the methods that students utilize to bridge the gap between alternate and consensual science conceptions to effect conceptual change. Qualitative and quantitative methods were employed to gather and analyze the data. In depth, semi-structured interviews formed the primary data for probing the context and details of students' conceptual change experience. Primary interview data was coded by thematic analysis. Results and discussion. This study revealed information about students' perceived roles in learning, the role of articulation in the conceptual change process, and ways in which a community of learners aids conceptual change. It was ascertained that students see their role in learning primarily as repeating information until they could add that information to their knowledge. Students are more likely to consider challenges to their conceptual frameworks and be more motivated to become active participants in constructing their knowledge when they are working collaboratively with peers instead of receiving instruction from their teacher. Articulation was found to be instrumental in aiding learners in identifying their alternate conceptions as well as in revisiting, investigating and reconstructing their conceptual frameworks. Based on the assumptions generated, suggestions were offered to inform pedagogical practice in support of the conceptual change process.

Using texts in science education: cognitive processes and knowledge representation.

PubMed

van den Broek, Paul

2010-04-23

Texts form a powerful tool in teaching concepts and principles in science. How do readers extract information from a text, and what are the limitations in this process? Central to comprehension of and learning from a text is the construction of a coherent mental representation that integrates the textual information and relevant background knowledge. This representation engenders learning if it expands the reader's existing knowledge base or if it corrects misconceptions in this knowledge base. The Landscape Model captures the reading process and the influences of reader characteristics (such as working-memory capacity, reading goal, prior knowledge, and inferential skills) and text characteristics (such as content/structure of presented information, processing demands, and textual cues). The model suggests factors that can optimize--or jeopardize--learning science from text.

Schema-driven facilitation of new hierarchy learning in the transitive inference paradigm

PubMed Central

Kumaran, Dharshan

2013-01-01

Prior knowledge, in the form of a mental schema or framework, is viewed to facilitate the learning of new information in a range of experimental and everyday scenarios. Despite rising interest in the cognitive and neural mechanisms underlying schema-driven facilitation of new learning, few paradigms have been developed to examine this issue in humans. Here we develop a multiphase experimental scenario aimed at characterizing schema-based effects in the context of a paradigm that has been very widely used across species, the transitive inference task. We show that an associative schema, comprised of prior knowledge of the rank positions of familiar items in the hierarchy, has a marked effect on transitivity performance and the development of relational knowledge of the hierarchy that cannot be accounted for by more general changes in task strategy. Further, we show that participants are capable of deploying prior knowledge to successful effect under surprising conditions (i.e., when corrective feedback is totally absent), but only when the associative schema is robust. Finally, our results provide insights into the cognitive mechanisms underlying such schema-driven effects, and suggest that new hierarchy learning in the transitive inference task can occur through a contextual transfer mechanism that exploits the structure of associative experiences. PMID:23782509

Schema-driven facilitation of new hierarchy learning in the transitive inference paradigm.

PubMed

Kumaran, Dharshan

2013-06-19

Prior knowledge, in the form of a mental schema or framework, is viewed to facilitate the learning of new information in a range of experimental and everyday scenarios. Despite rising interest in the cognitive and neural mechanisms underlying schema-driven facilitation of new learning, few paradigms have been developed to examine this issue in humans. Here we develop a multiphase experimental scenario aimed at characterizing schema-based effects in the context of a paradigm that has been very widely used across species, the transitive inference task. We show that an associative schema, comprised of prior knowledge of the rank positions of familiar items in the hierarchy, has a marked effect on transitivity performance and the development of relational knowledge of the hierarchy that cannot be accounted for by more general changes in task strategy. Further, we show that participants are capable of deploying prior knowledge to successful effect under surprising conditions (i.e., when corrective feedback is totally absent), but only when the associative schema is robust. Finally, our results provide insights into the cognitive mechanisms underlying such schema-driven effects, and suggest that new hierarchy learning in the transitive inference task can occur through a contextual transfer mechanism that exploits the structure of associative experiences.

Report of the Aircraft Systems/Flight Test Workshop Held at East Point, Georgia on 8-17 November 1977.

DTIC Science & Technology

1977-11-01

prior knowledge to decrease the amount of manpower and time required to evaluate the second package, but in principle, each STC package must be...techniques. Our knowledge of the problems, hazards, and pitfalls in the use of these techniques is very limited. Background: We do not have sufficient...prediction techniques, and what recommendations we would like to make, based on the limited knowledge we currently have. I would really like to spend another

A Conceptual Framework for Web-Based Learning Design

ERIC Educational Resources Information Center

Alomyan, Hesham

2017-01-01

The purpose of this paper is to provide a coherent framework to present the relationship between individual differences and web-based learning. Two individual difference factors have been identified for investigation within the present paper: Cognitive style and prior knowledge. The importance of individual differences is reviewed and previous…

Effectiveness of MMORPG-Based Instruction in Elementary English Education in Korea

ERIC Educational Resources Information Center

Suh, S.; Kim, S. W.; Kim, N. J.

2010-01-01

This study investigated the effectiveness of massive multiplayer online role-playing game (MMORPG)-based (massive multiplayer online role-playing game) instruction in elementary English education. The effectiveness of the MMORPG program was compared with face-to-face instruction and the independent variables (gender, prior knowledge, motivation…

Nudging toward Inquiry: Strategies for Searching for and Finding Great Information

ERIC Educational Resources Information Center

Fontichiaro, Kristin, Comp.

2010-01-01

Inquiry does not replace information literacy; rather, it encompasses it. Inquiry-based learning invites school librarians to step into all aspects of instructional planning, from activating prior knowledge straight through to reflection. Libraries pursuing inquiry-based instruction are building on the bedrock of information literacy, not starting…

Computer-Based Imaginary Sciences and Research on Concept Acquisition.

ERIC Educational Resources Information Center

Allen, Brockenbrough S.

To control for interactions in learning research due to subjects' prior knowledge of the instructional material presented, an imaginary curriculum was presented with a computer assisted technique based on Carl Berieter's imaginary science of Xenograde systems. The curriculum consisted of a classification system for ten conceptual classes of…

Elapsed decision time affects the weighting of prior probability in a perceptual decision task

PubMed Central

Hanks, Timothy D.; Mazurek, Mark E.; Kiani, Roozbeh; Hopp, Elizabeth; Shadlen, Michael N.

2012-01-01

Decisions are often based on a combination of new evidence with prior knowledge of the probable best choice. Optimal combination requires knowledge about the reliability of evidence, but in many realistic situations, this is unknown. Here we propose and test a novel theory: the brain exploits elapsed time during decision formation to combine sensory evidence with prior probability. Elapsed time is useful because (i) decisions that linger tend to arise from less reliable evidence, and (ii) the expected accuracy at a given decision time depends on the reliability of the evidence gathered up to that point. These regularities allow the brain to combine prior information with sensory evidence by weighting the latter in accordance with reliability. To test this theory, we manipulated the prior probability of the rewarded choice while subjects performed a reaction-time discrimination of motion direction using a range of stimulus reliabilities that varied from trial to trial. The theory explains the effect of prior probability on choice and reaction time over a wide range of stimulus strengths. We found that prior probability was incorporated into the decision process as a dynamic bias signal that increases as a function of decision time. This bias signal depends on the speed-accuracy setting of human subjects, and it is reflected in the firing rates of neurons in the lateral intraparietal cortex (LIP) of rhesus monkeys performing this task. PMID:21525274

Elapsed decision time affects the weighting of prior probability in a perceptual decision task.

PubMed

Hanks, Timothy D; Mazurek, Mark E; Kiani, Roozbeh; Hopp, Elisabeth; Shadlen, Michael N

2011-04-27

Decisions are often based on a combination of new evidence with prior knowledge of the probable best choice. Optimal combination requires knowledge about the reliability of evidence, but in many realistic situations, this is unknown. Here we propose and test a novel theory: the brain exploits elapsed time during decision formation to combine sensory evidence with prior probability. Elapsed time is useful because (1) decisions that linger tend to arise from less reliable evidence, and (2) the expected accuracy at a given decision time depends on the reliability of the evidence gathered up to that point. These regularities allow the brain to combine prior information with sensory evidence by weighting the latter in accordance with reliability. To test this theory, we manipulated the prior probability of the rewarded choice while subjects performed a reaction-time discrimination of motion direction using a range of stimulus reliabilities that varied from trial to trial. The theory explains the effect of prior probability on choice and reaction time over a wide range of stimulus strengths. We found that prior probability was incorporated into the decision process as a dynamic bias signal that increases as a function of decision time. This bias signal depends on the speed-accuracy setting of human subjects, and it is reflected in the firing rates of neurons in the lateral intraparietal area (LIP) of rhesus monkeys performing this task.

Contribution of prior semantic knowledge to new episodic learning in amnesia.

PubMed

Kan, Irene P; Alexander, Michael P; Verfaellie, Mieke

2009-05-01

We evaluated whether prior semantic knowledge would enhance episodic learning in amnesia. Subjects studied prices that are either congruent or incongruent with prior price knowledge for grocery and household items and then performed a forced-choice recognition test for the studied prices. Consistent with a previous report, healthy controls' performance was enhanced by price knowledge congruency; however, only a subset of amnesic patients experienced the same benefit. Whereas patients with relatively intact semantic systems, as measured by an anatomical measure (i.e., lesion involvement of anterior and lateral temporal lobes), experienced a significant congruency benefit, patients with compromised semantic systems did not experience a congruency benefit. Our findings suggest that when prior knowledge structures are intact, they can support acquisition of new episodic information by providing frameworks into which such information can be incorporated.

Using Content Acquisition Podcasts to Improve Teacher Candidate Knowledge of Curriculum-Based Measurement

ERIC Educational Resources Information Center

Kennedy, Michael J.; Wagner, Dana; Stegall, Joanna; Lembke, Erica; Miciak, Jeremy; Alves, Kat D.; Brown, Tiara; Driver, Melissa K.; Hirsch, Shanna Eisner

2016-01-01

Given the significant literature supporting the use of curriculum-based measurement (CBM) for data-based decision making, it is critical that teacher candidates learn about it prior to student teaching and entry into the field as full-time teachers. The authors of this study used a content acquisition podcast (CAP), a multimedia-based…

A Natural Language Interface Concordant with a Knowledge Base.

PubMed

Han, Yong-Jin; Park, Seong-Bae; Park, Se-Young

2016-01-01

The discordance between expressions interpretable by a natural language interface (NLI) system and those answerable by a knowledge base is a critical problem in the field of NLIs. In order to solve this discordance problem, this paper proposes a method to translate natural language questions into formal queries that can be generated from a graph-based knowledge base. The proposed method considers a subgraph of a knowledge base as a formal query. Thus, all formal queries corresponding to a concept or a predicate in the knowledge base can be generated prior to query time and all possible natural language expressions corresponding to each formal query can also be collected in advance. A natural language expression has a one-to-one mapping with a formal query. Hence, a natural language question is translated into a formal query by matching the question with the most appropriate natural language expression. If the confidence of this matching is not sufficiently high the proposed method rejects the question and does not answer it. Multipredicate queries are processed by regarding them as a set of collected expressions. The experimental results show that the proposed method thoroughly handles answerable questions from the knowledge base and rejects unanswerable ones effectively.

Pathway-based analyses.

PubMed

Kent, Jack W

2016-02-03

New technologies for acquisition of genomic data, while offering unprecedented opportunities for genetic discovery, also impose severe burdens of interpretation and penalties for multiple testing. The Pathway-based Analyses Group of the Genetic Analysis Workshop 19 (GAW19) sought reduction of multiple-testing burden through various approaches to aggregation of highdimensional data in pathways informed by prior biological knowledge. Experimental methods testedincluded the use of "synthetic pathways" (random sets of genes) to estimate power and false-positive error rate of methods applied to simulated data; data reduction via independent components analysis, single-nucleotide polymorphism (SNP)-SNP interaction, and use of gene sets to estimate genetic similarity; and general assessment of the efficacy of prior biological knowledge to reduce the dimensionality of complex genomic data. The work of this group explored several promising approaches to managing high-dimensional data, with the caveat that these methods are necessarily constrained by the quality of external bioinformatic annotation.

Knowledge-based image processing for on-off type DNA microarray

NASA Astrophysics Data System (ADS)

Kim, Jong D.; Kim, Seo K.; Cho, Jeong S.; Kim, Jongwon

2002-06-01

This paper addresses the image processing technique for discriminating whether the probes are hybrized with target DNA in the Human Papilloma Virus (HPV) DNA Chip designed for genotyping HPV. In addition to the probes, the HPV DNA chip has markers that always react with the sample DNA. The positions of probe-dots in the final scanned image are fixed relative to the marker-dot locations with a small variation according to the accuracy of the dotter and the scanner. The probes are duplicated 4 times for the diagnostic stability. The prior knowledges such as the maker relative distance and the duplication information of probes is integrated into the template matching technique with the normalized correlation measure. Results show that the employment of both of the prior knowledges is to simply average the template matching measures over the positions of the markers and probes. The eventual proposed scheme yields stable marker locating and probe classification.

Selective influence of prior allocentric knowledge on the kinesthetic learning of a path.

PubMed

Lafon, Matthieu; Vidal, Manuel; Berthoz, Alain

2009-04-01

Spatial cognition studies have described two main cognitive strategies involved in the memorization of traveled paths in human navigation. One of these strategies uses the action-based memory (egocentric) of the traveled route or paths, which involves kinesthetic memory, optic flow, and episodic memory, whereas the other strategy privileges a survey memory of cartographic type (allocentric). Most studies have dealt with these two strategies separately, but none has tried to show the interaction between them in spite of the fact that we commonly use a map to imagine our journey and then proceed using egocentric navigation. An interesting question is therefore: how does prior allocentric knowledge of the environment affect the egocentric, purely kinesthetic navigation processes involved in human navigation? We designed an experiment in which blindfolded subjects had first to walk and memorize a path with kinesthetic cues only. They had previously been shown a map of the path, which was either correct or distorted (consistent shrinking or growing). The latter transformations were studied in order to observe what influence a distorted prior knowledge could have on spatial mechanisms. After having completed the first learning travel along the path, they had to perform several spatial tasks during the testing phase: (1) pointing towards the origin and (2) to specific points encountered along the path, (3) a free locomotor reproduction, and (4) a drawing of the memorized path. The results showed that prior cartographic knowledge influences the paths drawn and the spatial inference capacity, whereas neither locomotor reproduction nor spatial updating was disturbed. Our results strongly support the notion that (1) there are two independent neural bases underlying these mechanisms: a map-like representation allowing allocentric spatial inferences, and a kinesthetic memory of self-motion in space; and (2) a common use of, or a switching between, these two strategies is possible. Nevertheless, allocentric representations can emerge from the experience of kinesthetic cues alone.

Intrinsic Bayesian Active Contours for Extraction of Object Boundaries in Images

PubMed Central

Srivastava, Anuj

2010-01-01

We present a framework for incorporating prior information about high-probability shapes in the process of contour extraction and object recognition in images. Here one studies shapes as elements of an infinite-dimensional, non-linear quotient space, and statistics of shapes are defined and computed intrinsically using differential geometry of this shape space. Prior models on shapes are constructed using probability distributions on tangent bundles of shape spaces. Similar to the past work on active contours, where curves are driven by vector fields based on image gradients and roughness penalties, we incorporate the prior shape knowledge in the form of vector fields on curves. Through experimental results, we demonstrate the use of prior shape models in the estimation of object boundaries, and their success in handling partial obscuration and missing data. Furthermore, we describe the use of this framework in shape-based object recognition or classification. PMID:21076692

Marginally specified priors for non-parametric Bayesian estimation

PubMed Central

Kessler, David C.; Hoff, Peter D.; Dunson, David B.

2014-01-01

Summary Prior specification for non-parametric Bayesian inference involves the difficult task of quantifying prior knowledge about a parameter of high, often infinite, dimension. A statistician is unlikely to have informed opinions about all aspects of such a parameter but will have real information about functionals of the parameter, such as the population mean or variance. The paper proposes a new framework for non-parametric Bayes inference in which the prior distribution for a possibly infinite dimensional parameter is decomposed into two parts: an informative prior on a finite set of functionals, and a non-parametric conditional prior for the parameter given the functionals. Such priors can be easily constructed from standard non-parametric prior distributions in common use and inherit the large support of the standard priors on which they are based. Additionally, posterior approximations under these informative priors can generally be made via minor adjustments to existing Markov chain approximation algorithms for standard non-parametric prior distributions. We illustrate the use of such priors in the context of multivariate density estimation using Dirichlet process mixture models, and in the modelling of high dimensional sparse contingency tables. PMID:25663813

Knowledge discovery about quality of life changes of spinal cord injury patients: clustering based on rules by states.

PubMed

Gibert, Karina; García-Rudolph, Alejandro; Curcoll, Lluïsa; Soler, Dolors; Pla, Laura; Tormos, José María

2009-01-01

In this paper, an integral Knowledge Discovery Methodology, named Clustering based on rules by States, which incorporates artificial intelligence (AI) and statistical methods as well as interpretation-oriented tools, is used for extracting knowledge patterns about the evolution over time of the Quality of Life (QoL) of patients with Spinal Cord Injury. The methodology incorporates the interaction with experts as a crucial element with the clustering methodology to guarantee usefulness of the results. Four typical patterns are discovered by taking into account prior expert knowledge. Several hypotheses are elaborated about the reasons for psychological distress or decreases in QoL of patients over time. The knowledge discovery from data (KDD) approach turns out, once again, to be a suitable formal framework for handling multidimensional complexity of the health domains.

7 CFR 275.2 - State agency responsibilities.

Code of Federal Regulations, 2014 CFR

2014-01-01

...: (i) Data collection through management evaluation (ME) reviews and quality control (QC) reviews; (ii... knowledge of either the household or the decision under review. Where there is prior knowledge, the reviewer must disqualify her/himself. Prior knowledge is defined as having: (1) Taken any part in the decision...

7 CFR 275.2 - State agency responsibilities.

Code of Federal Regulations, 2011 CFR

2011-01-01

...: (i) Data collection through management evaluation (ME) reviews and quality control (QC) reviews; (ii... knowledge of either the household or the decision under review. Where there is prior knowledge, the reviewer must disqualify her/himself. Prior knowledge is defined as having: (1) Taken any part in the decision...

7 CFR 275.2 - State agency responsibilities.

Code of Federal Regulations, 2013 CFR

2013-01-01

...: (i) Data collection through management evaluation (ME) reviews and quality control (QC) reviews; (ii... knowledge of either the household or the decision under review. Where there is prior knowledge, the reviewer must disqualify her/himself. Prior knowledge is defined as having: (1) Taken any part in the decision...

7 CFR 275.2 - State agency responsibilities.

Code of Federal Regulations, 2012 CFR

2012-01-01

...: (i) Data collection through management evaluation (ME) reviews and quality control (QC) reviews; (ii... knowledge of either the household or the decision under review. Where there is prior knowledge, the reviewer must disqualify her/himself. Prior knowledge is defined as having: (1) Taken any part in the decision...

7 CFR 275.2 - State agency responsibilities.

Code of Federal Regulations, 2010 CFR

2010-01-01

...: (i) Data collection through management evaluation (ME) reviews and quality control (QC) reviews; (ii... knowledge of either the household or the decision under review. Where there is prior knowledge, the reviewer must disqualify her/himself. Prior knowledge is defined as having: (1) Taken any part in the decision...

The Design and Assessment of a Hypermedia Course on Semiconductor Manufacturing.

ERIC Educational Resources Information Center

Schank, Patrick K.; Rowe, Lawrence A.

1993-01-01

Describes the design and evaluation of a multimedia course on integrated circuit manufacturing that was developed at the University of California at Berkeley using IC-HIP (Integrated Circuit-Hypermedia in PICASSO), a hypermedia-based instructional system. Learning effects based on prior knowledge, methods of navigation, and other factors are…

RC-MAPS: Bridging the Comprehension Gap in EAP Reading

ERIC Educational Resources Information Center

Sterzik, Angela Meyer; Fraser, Carol

2012-01-01

In academic environments, reading is assigned not simply to transmit information; students are required to take the information, and based on the task set by the instructor, assess, analyze, and critique it on the basis of personal experiences, prior knowledge, and other readings (Grabe, 2009). Thus text-based comprehension (Kintsch, 1998) alone…

Eye Care Quality and Accessibility Improvement in the Community (EQUALITY): impact of an eye health education program on patient knowledge about glaucoma and attitudes about eye care

PubMed Central

Rhodes, Lindsay A; Huisingh, Carrie E; McGwin, Gerald; Mennemeyer, Stephen T; Bregantini, Mary; Patel, Nita; Saaddine, Jinan; Crews, John E; Girkin, Christopher A; Owsley, Cynthia

2016-01-01

Purpose To assess the impact of the education program of the Eye Care Quality and Accessibility Improvement in the Community (EQUALITY) telemedicine program on at-risk patients’ knowledge about glaucoma and attitudes about eye care as well as to assess patient satisfaction with EQUALITY. Patients and methods New or existing patients presenting for a comprehensive eye exam (CEE) at one of two retail-based primary eye clinics were enrolled based on ≥1 of the following at-risk criteria for glaucoma: African Americans ≥40 years of age, Whites ≥50 years of age, diabetes, family history of glaucoma, and/or preexisting diagnosis of glaucoma. A total of 651 patients were enrolled. A questionnaire was administered prior to the patients’ CEE and prior to the patients receiving any of the evidence-based eye health education program; a follow-up questionnaire was administered 2–4 weeks later by phone. Baseline and follow-up patient responses regarding knowledge about glaucoma and attitudes about eye care were compared using McNemar’s test. Logistic regression models were used to assess the association of patient-level characteristics with improvement in knowledge and attitudes. Overall patient satisfaction was summarized. Results At follow-up, all patient responses in the knowledge and attitude domains significantly improved from baseline (P≤0.01 for all questions). Those who were unemployed (odds ratio =0.63, 95% confidence interval =0.42–0.95, P=0.026) or had lower education (odds ratio =0.55, 95% confidence interval =0.29–1.02, P=0.058) were less likely to improve their knowledge after adjusting for age, sex, race, and prior glaucoma diagnosis. This association was attenuated after further adjustment for other patient-level characteristics. Ninety-eight percent (n=501) of patients reported being likely to have a CEE within the next 2 years, whereas 63% (n=326) had a CEE in the previous 2 years. Patient satisfaction with EQUALITY was high (99%). Conclusion Improved knowledge about glaucoma and a high intent to pursue eye care may lead to improved detection of early disease, thus lowering the risk of blindness. PMID:27274329

Assessing the Impact of a Semester-Long Course in Agricultural Mechanics on Pre-Service Agricultural Education Teachers' Importance, Confidence, and Knowledge of Welding

ERIC Educational Resources Information Center

Leiby, Brian L.; Robinson, J. Shane; Key, James P.

2013-01-01

This study sought to assess the perceptions of Oklahoma pre-service agricultural education teachers regarding the importance of identified welding skills standards and their confidence to teach them, based on a semester-long course on metals and welding. This study also sought to determine pre-service teachers' knowledge of welding prior to and at…

Comparison of three instructional strategies in food and nutrition education: developing a diet plan for a diabetic case

NASA Astrophysics Data System (ADS)

Darabi, Aubteen; Pourafshar, Shirin; Suryavanshi, Rinki; `Logan'Arrington, Thomas

2016-05-01

This study examines the performance of dietitians-in-training on developing a diet plan for a diabetic patient either independently or after peer discussion. Participants (n = 58) from an undergraduate program in food and nutrition were divided into two groups based on their prior knowledge before being randomly assigned into three conditions: (1) peer discussion with just-in-time information (JIT information), (2) peer discussion without JIT information), and (3) independent performers. The learners' performance in the three conditions was analyzed. The results presented here describe the role of prior knowledge and JIT information across the conditions and the interaction of the two factors as well as the instructional implications of the findings.

Processing Waveform-Based NDE

NASA Technical Reports Server (NTRS)

Roth, Donald J (Inventor)

2011-01-01

A computer implemented process for simultaneously measuring the velocity of terahertz electromagnetic radiation in a dielectric material sample without prior knowledge of the thickness of the sample and for measuring the thickness of a material sample using terahertz electromagnetic radiation in a material sample without prior knowledge of the velocity of the terahertz electromagnetic radiation in the sample is disclosed and claimed. Utilizing interactive software the process evaluates, in a plurality of locations, the sample for microstructural variations and for thickness variations and maps the microstructural and thickness variations by location. A thin sheet of dielectric material may be used on top of the sample to create a dielectric mismatch. The approximate focal point of the radiation source (transceiver) is initially determined for good measurements.

Discovery learning model with geogebra assisted for improvement mathematical visual thinking ability

NASA Astrophysics Data System (ADS)

Juandi, D.; Priatna, N.

2018-05-01

The main goal of this study is to improve the mathematical visual thinking ability of high school student through implementation the Discovery Learning Model with Geogebra Assisted. This objective can be achieved through study used quasi-experimental method, with non-random pretest-posttest control design. The sample subject of this research consist of 62 senior school student grade XI in one of school in Bandung district. The required data will be collected through documentation, observation, written tests, interviews, daily journals, and student worksheets. The results of this study are: 1) Improvement students Mathematical Visual Thinking Ability who obtain learning with applied the Discovery Learning Model with Geogebra assisted is significantly higher than students who obtain conventional learning; 2) There is a difference in the improvement of students’ Mathematical Visual Thinking ability between groups based on prior knowledge mathematical abilities (high, medium, and low) who obtained the treatment. 3) The Mathematical Visual Thinking Ability improvement of the high group is significantly higher than in the medium and low groups. 4) The quality of improvement ability of high and low prior knowledge is moderate category, in while the quality of improvement ability in the high category achieved by student with medium prior knowledge.

WE-F-BRB-02: Setting the Stage for Incorporation of Toxicity Measures in Treatment Plan Assessments

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

Mayo, C.

2015-06-15

Advancements in informatics in radiotherapy are opening up opportunities to improve our ability to assess treatment plans. Models on individualizing patient dose constraints from prior patient data and shape relationships have been extensively researched and are now making their way into commercial products. New developments in knowledge based treatment planning involve understanding the impact of the radiation dosimetry on the patient. Akin to radiobiology models that have driven intensity modulated radiotherapy optimization, toxicity and outcome predictions based on treatment plans and prior patient experiences may be the next step in knowledge based planning. In order to realize these predictions, itmore » is necessary to understand how the clinical information can be captured, structured and organized with ontologies and databases designed for recall. Large databases containing radiation dosimetry and outcomes present the opportunity to evaluate treatment plans against predictions of toxicity and disease response. Such evaluations can be based on dose volume histogram or even the full 3-dimensional dose distribution and its relation to the critical anatomy. This session will provide an understanding of ontologies and standard terminologies used to capture clinical knowledge into structured databases; How data can be organized and accessed to utilize the knowledge in planning; and examples of research and clinical efforts to incorporate that clinical knowledge into planning for improved care for our patients. Learning Objectives: Understand the role of standard terminologies, ontologies and data organization in oncology Understand methods to capture clinical toxicity and outcomes in a clinical setting Understand opportunities to learn from clinical data and its application to treatment planning Todd McNutt receives funding from Philips, Elekta and Toshiba for some of the work presented.« less

WE-F-BRB-03: Inclusion of Data-Driven Risk Predictions in Radiation Treatment Planning in the Context of a Local Level Learning Health System

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

McNutt, T.

Advancements in informatics in radiotherapy are opening up opportunities to improve our ability to assess treatment plans. Models on individualizing patient dose constraints from prior patient data and shape relationships have been extensively researched and are now making their way into commercial products. New developments in knowledge based treatment planning involve understanding the impact of the radiation dosimetry on the patient. Akin to radiobiology models that have driven intensity modulated radiotherapy optimization, toxicity and outcome predictions based on treatment plans and prior patient experiences may be the next step in knowledge based planning. In order to realize these predictions, itmore » is necessary to understand how the clinical information can be captured, structured and organized with ontologies and databases designed for recall. Large databases containing radiation dosimetry and outcomes present the opportunity to evaluate treatment plans against predictions of toxicity and disease response. Such evaluations can be based on dose volume histogram or even the full 3-dimensional dose distribution and its relation to the critical anatomy. This session will provide an understanding of ontologies and standard terminologies used to capture clinical knowledge into structured databases; How data can be organized and accessed to utilize the knowledge in planning; and examples of research and clinical efforts to incorporate that clinical knowledge into planning for improved care for our patients. Learning Objectives: Understand the role of standard terminologies, ontologies and data organization in oncology Understand methods to capture clinical toxicity and outcomes in a clinical setting Understand opportunities to learn from clinical data and its application to treatment planning Todd McNutt receives funding from Philips, Elekta and Toshiba for some of the work presented.« less

Self-Explanation in the Domain of Statistics: An Expertise Reversal Effect

ERIC Educational Resources Information Center

Leppink, Jimmie; Broers, Nick J.; Imbos, Tjaart; van der Vleuten, Cees P. M.; Berger, Martijn P. F.

2012-01-01

This study investigated the effects of four instructional methods on cognitive load, propositional knowledge, and conceptual understanding of statistics, for low prior knowledge students and for high prior knowledge students. The instructional methods were (1) a reading-only control condition, (2) answering open-ended questions, (3) answering…

Conceptualising GP teachers' knowledge: a pedagogical content knowledge perspective.

PubMed

Cantillon, Peter; de Grave, Willem

2012-05-01

Most teacher development initiatives focus on enhancing knowledge of teaching (pedagogy), whilst largely ignoring other important features of teacher knowledge such as subject matter knowledge and awareness of the learning context. Furthermore, teachers' ability to learn from faculty development interventions is limited by their existing (often implicit) pedagogical knowledge and beliefs. Pedagogical content knowledge (PCK) represents a model of teacher knowledge incorporating what they know about subject matter, pedagogy and context. PCK can be used to explore teachers' prior knowledge and to structure faculty development programmes so that they take account of a broader range of teachers' knowledge. We set out to examine the application of a PCK model in a general practice education setting. This study is part of a larger study that employed a mixed method approach (concept mapping, phenomenological interviews and video-stimulated recall) to explore features of GP teachers' subject matter knowledge, pedagogical knowledge and knowledge of the learning environment in the context of a general practice tutorial. This paper presents data on GP teachers' pedagogical and context knowledge. There was considerable overlap between different GP teachers' knowledge and beliefs about learners and the clinical learning environment (i.e. knowledge of context). The teachers' beliefs about learners were largely based on assumptions derived from their own student experiences. There were stark differences, however, between teachers in terms of pedagogical knowledge, particularly in terms of their teaching orientations (i.e. transmission or facilitation orientation) and this was manifest in their teaching behaviours. PCK represents a useful model for conceptualising clinical teacher prior knowledge in three domains, namely subject matter, learning context and pedagogy. It can and should be used as a simple guiding framework by faculty developers to inform the design and delivery of their faculty development programmes.

Effect of an Education Presentation On the Knowledge and Awareness of Urinary Tract Infection among Non-Licensed and Licensed Health Care Workers in Long-Term Care Facilities.

PubMed

Freeman-Jobson, Jennifer H; Rogers, Jamie L; Ward-Smith, Peggy

2016-01-01

This article presents the findings of a pre-test, post-test quality improvement project that describes the change in knowledge from prior to and following an evidence-based education presentation. The presentation addressed the clinical symptoms, diagnostic processes, interventions, and responsibilities of licensed and unlicensed health care workers employed in long-term care facilities related to prevention and detection of non-catheter-related urinary tract infections. Results indicate that the education presentation improved knowledge in specific.

Advances in Pediatric Cardiology Boot Camp: Boot Camp Training Promotes Fellowship Readiness and Enables Retention of Knowledge.

PubMed

Ceresnak, Scott R; Axelrod, David M; Sacks, Loren D; Motonaga, Kara S; Johnson, Emily R; Krawczeski, Catherine D

2017-03-01

We previously demonstrated that a pediatric cardiology boot camp can improve knowledge acquisition and decrease anxiety for trainees. We sought to determine if boot camp participants entered fellowship with a knowledge advantage over fellows who did not attend and if there was moderate-term retention of that knowledge. A 2-day training program was provided for incoming pediatric cardiology fellows from eight fellowship programs in April 2016. Hands-on, immersive experiences and simulations were provided in all major areas of pediatric cardiology. Knowledge-based examinations were completed by each participant prior to boot camp (PRE), immediately post-training (POST), and prior to the start of fellowship in June 2016 (F/U). A control group of fellows who did not attend boot camp also completed an examination prior to fellowship (CTRL). Comparisons of scores were made for individual participants and between participants and controls. A total of 16 participants and 16 control subjects were included. Baseline exam scores were similar between participants and controls (PRE 47 ± 11% vs. CTRL 52 ± 10%; p = 0.22). Participants' knowledge improved with boot camp training (PRE 47 ± 11% vs. POST 70 ± 8%; p < 0.001) and there was excellent moderate-term retention of the information taught at boot camp (PRE 47 ± 11% vs. F/U 71 ± 8%; p < 0.001). Testing done at the beginning of fellowship demonstrated significantly better scores in participants versus controls (F/U 71 ± 8% vs. CTRL 52 ± 10%; p < 0.001). Boot camp participants demonstrated a significant improvement in basic cardiology knowledge after the training program and had excellent moderate-term retention of that knowledge. Participants began fellowship with a larger fund of knowledge than those fellows who did not attend.

Effects of prior information on decoding degraded speech: an fMRI study.

PubMed

Clos, Mareike; Langner, Robert; Meyer, Martin; Oechslin, Mathias S; Zilles, Karl; Eickhoff, Simon B

2014-01-01

Expectations and prior knowledge are thought to support the perceptual analysis of incoming sensory stimuli, as proposed by the predictive-coding framework. The current fMRI study investigated the effect of prior information on brain activity during the decoding of degraded speech stimuli. When prior information enabled the comprehension of the degraded sentences, the left middle temporal gyrus and the left angular gyrus were activated, highlighting a role of these areas in meaning extraction. In contrast, the activation of the left inferior frontal gyrus (area 44/45) appeared to reflect the search for meaningful information in degraded speech material that could not be decoded because of mismatches with the prior information. Our results show that degraded sentences evoke instantaneously different percepts and activation patterns depending on the type of prior information, in line with prediction-based accounts of perception. Copyright © 2012 Wiley Periodicals, Inc.

Effectiveness of false correction strategy on science reading comprehension

NASA Astrophysics Data System (ADS)

Ghent, Cynthia Anne

False-correction reading strategy theoretically prompted college students to activate their prior knowledge when provided false statements linked to a portion of their biology textbook. This strategy is based in elaborative interrogation theory, which suggests that prompting readers to answer interrogatives about text students are reading increases their comprehension of that text. These interrogatives always asked "why" statements pulled from a text, one sentence in length, were "true." True statements in this study based on a text were converted by the experimenter into false statements, one sentence in length. Students were requested to rewrite each statement (n=12) on average every 200 words in a text as they were reading, converting each false statement into a true statement. These students outperformed other students requested to reread the same biology text twice (an established placebo-control strategy). These students, in turn, outperformed still other students reading an unrelated control text taken from the same textbook used only to establish a prior knowledge baseline for all students included in this study. Students participating in this study were enrolled students in an undergraduate introductory general biology course designed for non-majors. A three-group, posttest-only, randomized experimental control-group design was used to prevent pretest activation of students' prior knowledge thus increasing chances of producing evidence of false-correction effectiveness and to begin augmenting potential generalizability to science classrooms. Students' (n=357) general biology knowledge, verbal ability, and attempts to use the false correction strategy were collected and analyzed. Eight of the participants were interviewed by the researcher in a first attempt in this domain to collect data on participants' points of view about the strategy. The results of this study are not yet recommended for use in authentic school settings as further research is indicated.

Balancing the Role of Priors in Multi-Observer Segmentation Evaluation

PubMed Central

Huang, Xiaolei; Wang, Wei; Lopresti, Daniel; Long, Rodney; Antani, Sameer; Xue, Zhiyun; Thoma, George

2009-01-01

Comparison of a group of multiple observer segmentations is known to be a challenging problem. A good segmentation evaluation method would allow different segmentations not only to be compared, but to be combined to generate a “true” segmentation with higher consensus. Numerous multi-observer segmentation evaluation approaches have been proposed in the literature, and STAPLE in particular probabilistically estimates the true segmentation by optimal combination of observed segmentations and a prior model of the truth. An Expectation–Maximization (EM) algorithm, STAPLE’S convergence to the desired local minima depends on good initializations for the truth prior and the observer-performance prior. However, accurate modeling of the initial truth prior is nontrivial. Moreover, among the two priors, the truth prior always dominates so that in certain scenarios when meaningful observer-performance priors are available, STAPLE can not take advantage of that information. In this paper, we propose a Bayesian decision formulation of the problem that permits the two types of prior knowledge to be integrated in a complementary manner in four cases with differing application purposes: (1) with known truth prior; (2) with observer prior; (3) with neither truth prior nor observer prior; and (4) with both truth prior and observer prior. The third and fourth cases are not discussed (or effectively ignored) by STAPLE, and in our research we propose a new method to combine multiple-observer segmentations based on the maximum a posterior (MAP) principle, which respects the observer prior regardless of the availability of the truth prior. Based on the four scenarios, we have developed a web-based software application that implements the flexible segmentation evaluation framework for digitized uterine cervix images. Experiment results show that our framework has flexibility in effectively integrating different priors for multi-observer segmentation evaluation and it also generates results comparing favorably to those by the STAPLE algorithm and the Majority Vote Rule. PMID:20523759

Figure-ground segmentation based on class-independent shape priors

NASA Astrophysics Data System (ADS)

Li, Yang; Liu, Yang; Liu, Guojun; Guo, Maozu

2018-01-01

We propose a method to generate figure-ground segmentation by incorporating shape priors into the graph-cuts algorithm. Given an image, we first obtain a linear representation of an image and then apply directional chamfer matching to generate class-independent, nonparametric shape priors, which provide shape clues for the graph-cuts algorithm. We then enforce shape priors in a graph-cuts energy function to produce object segmentation. In contrast to previous segmentation methods, the proposed method shares shape knowledge for different semantic classes and does not require class-specific model training. Therefore, the approach obtains high-quality segmentation for objects. We experimentally validate that the proposed method outperforms previous approaches using the challenging PASCAL VOC 2010/2012 and Berkeley (BSD300) segmentation datasets.

The value of prior knowledge in machine learning of complex network systems.

PubMed

Ferranti, Dana; Krane, David; Craft, David

2017-11-15

Our overall goal is to develop machine-learning approaches based on genomics and other relevant accessible information for use in predicting how a patient will respond to a given proposed drug or treatment. Given the complexity of this problem, we begin by developing, testing and analyzing learning methods using data from simulated systems, which allows us access to a known ground truth. We examine the benefits of using prior system knowledge and investigate how learning accuracy depends on various system parameters as well as the amount of training data available. The simulations are based on Boolean networks-directed graphs with 0/1 node states and logical node update rules-which are the simplest computational systems that can mimic the dynamic behavior of cellular systems. Boolean networks can be generated and simulated at scale, have complex yet cyclical dynamics and as such provide a useful framework for developing machine-learning algorithms for modular and hierarchical networks such as biological systems in general and cancer in particular. We demonstrate that utilizing prior knowledge (in the form of network connectivity information), without detailed state equations, greatly increases the power of machine-learning algorithms to predict network steady-state node values ('phenotypes') and perturbation responses ('drug effects'). Links to codes and datasets here: https://gray.mgh.harvard.edu/people-directory/71-david-craft-phd. dcraft@broadinstitute.org. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Middle school students' knowledge of autism.

PubMed

Campbell, Jonathan M; Barger, Brian D

2011-06-01

Authors examined 1,015 middle school students' knowledge of autism using a single item of prior awareness and a 10-item Knowledge of Autism (KOA) scale. The KOA scale was designed to assess students' knowledge of the course, etiology, and symptoms associated with autism. Less than half of students (46.1%) reported having heard of autism; however, most students correctly responded that autism was a chronic condition that was not communicable. Students reporting prior awareness of autism scored higher on 9 of 10 KOA scale items when compared to their naïve counterparts. Prior awareness of autism and KOA scores also differed across schools. A more detailed understanding of developmental changes in students' knowledge of autism should improve peer educational interventions.

Relationship of prior knowledge and working engineers' learning preferences: implications for designing effective instruction

NASA Astrophysics Data System (ADS)

Baukal, Charles E.; Ausburn, Lynna J.

2017-05-01

Continuing engineering education (CEE) is important to ensure engineers maintain proficiency over the life of their careers. However, relatively few studies have examined designing effective training for working engineers. Research has indicated that both learner instructional preferences and prior knowledge can impact the learning process, but it has not established if these factors are interrelated. The study reported here considered relationships of prior knowledge and three aspects of learning preferences of working engineers at a manufacturing company: learning strategy choices, verbal-visual cognitive styles, and multimedia preferences. Prior knowledge was not found to be significantly related to engineers' learning preferences, indicating independence of effects of these variables on learning. The study also examined relationships of this finding to the Multimedia Cone of Abstraction and implications for its use as an instructional design tool for CEE.

The Relation between Prior Knowledge and Students' Collaborative Discovery Learning Processes

ERIC Educational Resources Information Center

Gijlers, Hannie; de Jong, Ton

2005-01-01

In this study we investigate how prior knowledge influences knowledge development during collaborative discovery learning. Fifteen dyads of students (pre-university education, 15-16 years old) worked on a discovery learning task in the physics field of kinematics. The (face-to-face) communication between students was recorded and the interaction…

Prior Knowledge and Story Processing: Integration, Selection, and Variation. Technical Report No. 138.

ERIC Educational Resources Information Center

Spiro, Rand J.

Psychological research concerning several aspects of the relationship between existing knowledge schemata and the processing of text is summarized in this report. The first section is concerned with dynamic processes of story understanding, with emphasis on the integration of information. The role of prior knowledge in accommodating parts of…

Preparation for College General Chemistry: More than Just a Matter of Content Knowledge Acquisition

ERIC Educational Resources Information Center

Cracolice, Mark S.; Busby, Brittany D.

2015-01-01

This study investigates the potential of five factors that may be predictive of success in college general chemistry courses: prior knowledge of common alternate conceptions, intelligence, scientific reasoning ability, proportional reasoning ability, and attitude toward chemistry. We found that both prior knowledge and scientific reasoning ability…

Third-Grade Students' Mental Models of Energy Expenditure during Exercise

ERIC Educational Resources Information Center

Pasco, Denis; Ennis, Catherine D.

2015-01-01

Background: Students' prior knowledge plays an important role in learning new knowledge. In physical education (PE) and physical activity settings, studies have confirmed the role of students' prior knowledge. According to Placek and Griffin, these studies demonstrate that: "our students are not empty balls waiting to be filled with knowledge…

Curriculum Weaving: Developing Creative Curricular Opportunities for Pre-Service Teachers and Elementary Students through Project-Based Learning

ERIC Educational Resources Information Center

DuBois, Alison Lynn; Keller, Tina Marie

2016-01-01

Curriculum Weaving uses multi-layered goal planning designed to activate the students' prior knowledge, connect the student to student competencies and encourage them to engage in professionally-based, project management activities that will cultivate effective professional in the field classroom teacher. The focus of weaving these elements…

A Web-Based Adaptive Tutor to Teach PCR Primer Design

ERIC Educational Resources Information Center

van Seters, Janneke R.; Wellink, Joan; Tramper, Johannes; Goedhart, Martin J.; Ossevoort, Miriam A.

2012-01-01

When students have varying prior knowledge, personalized instruction is desirable. One way to personalize instruction is by using adaptive e-learning to offer training of varying complexity. In this study, we developed a web-based adaptive tutor to teach PCR primer design: the PCR Tutor. We used part of the Taxonomy of Educational Objectives (the…

Validating College Course Placement Decisions Based on CLEP Exam Scores: CLEP Placement Validity Study Results. Statistical Report

ERIC Educational Resources Information Center

Godfrey, Kelly E.; Jagesic, Sanja

2016-01-01

The College-Level Examination Program® (CLEP®) is a computer-based prior-learning assessment that allows examinees the opportunity to demonstrate mastery of knowledge and skills necessary to earn postsecondary course credit in higher education. Currently, there are 33 exams in five subject areas: composition and literature, world languages,…

Bias in the physical examination of patients with lumbar radiculopathy

PubMed Central

2010-01-01

Background No prior studies have examined systematic bias in the musculoskeletal physical examination. The objective of this study was to assess the effects of bias due to prior knowledge of lumbar spine magnetic resonance imaging findings (MRI) on perceived diagnostic accuracy of the physical examination for lumbar radiculopathy. Methods This was a cross-sectional comparison of the performance characteristics of the physical examination with blinding to MRI results (the 'independent group') with performance in the situation where the physical examination was not blinded to MRI results (the 'non-independent group'). The reference standard was the final diagnostic impression of nerve root impingement by the examining physician. Subjects were recruited from a hospital-based outpatient specialty spine clinic. All adults age 18 and older presenting with lower extremity radiating pain of duration ≤ 12 weeks were evaluated for participation. 154 consecutively recruited subjects with lumbar disk herniation confirmed by lumbar spine MRI were included in this study. Sensitivities and specificities with 95% confidence intervals were calculated in the independent and non-independent groups for the four components of the radiculopathy examination: 1) provocative testing, 2) motor strength testing, 3) pinprick sensory testing, and 4) deep tendon reflex testing. Results The perceived sensitivity of sensory testing was higher with prior knowledge of MRI results (20% vs. 36%; p = 0.05). Sensitivities and specificities for exam components otherwise showed no statistically significant differences between groups. Conclusions Prior knowledge of lumbar MRI results may introduce bias into the pinprick sensory testing component of the physical examination for lumbar radiculopathy. No statistically significant effect of bias was seen for other components of the physical examination. The effect of bias due to prior knowledge of lumbar MRI results should be considered when an isolated sensory deficit on examination is used in medical decision-making. Further studies of bias should include surgical clinic populations and other common diagnoses including shoulder, knee and hip pathology. PMID:21118558

Bias in the physical examination of patients with lumbar radiculopathy.

PubMed

Suri, Pradeep; Hunter, David J; Katz, Jeffrey N; Li, Ling; Rainville, James

2010-11-30

No prior studies have examined systematic bias in the musculoskeletal physical examination. The objective of this study was to assess the effects of bias due to prior knowledge of lumbar spine magnetic resonance imaging findings (MRI) on perceived diagnostic accuracy of the physical examination for lumbar radiculopathy. This was a cross-sectional comparison of the performance characteristics of the physical examination with blinding to MRI results (the 'independent group') with performance in the situation where the physical examination was not blinded to MRI results (the 'non-independent group'). The reference standard was the final diagnostic impression of nerve root impingement by the examining physician. Subjects were recruited from a hospital-based outpatient specialty spine clinic. All adults age 18 and older presenting with lower extremity radiating pain of duration ≤ 12 weeks were evaluated for participation. 154 consecutively recruited subjects with lumbar disk herniation confirmed by lumbar spine MRI were included in this study. Sensitivities and specificities with 95% confidence intervals were calculated in the independent and non-independent groups for the four components of the radiculopathy examination: 1) provocative testing, 2) motor strength testing, 3) pinprick sensory testing, and 4) deep tendon reflex testing. The perceived sensitivity of sensory testing was higher with prior knowledge of MRI results (20% vs. 36%; p = 0.05). Sensitivities and specificities for exam components otherwise showed no statistically significant differences between groups. Prior knowledge of lumbar MRI results may introduce bias into the pinprick sensory testing component of the physical examination for lumbar radiculopathy. No statistically significant effect of bias was seen for other components of the physical examination. The effect of bias due to prior knowledge of lumbar MRI results should be considered when an isolated sensory deficit on examination is used in medical decision-making. Further studies of bias should include surgical clinic populations and other common diagnoses including shoulder, knee and hip pathology.

Mathematics understanding and anxiety in collaborative teaching

NASA Astrophysics Data System (ADS)

Ansari, B. I.; Wahyu, N.

2017-12-01

This study aims to examine students’ mathematical understanding and anxiety using collaborative teaching. The sample consists of 51 students in the 7th-grade of MTs N Jeureula, one of the Islamic public junior high schools in Jeureula, Aceh, Indonesia. A test of mathematics understanding was administered to the students twice during the period of two months. The result suggests that there is a significant increase in mathematical understanding in the pre-test and post-test. We categorized the students into the high, intermediate, and low level of prior mathematics knowledge. In the high-level prior knowledge, there is no difference of mathematical understanding between the experiment and control group. Meanwhile, in the intermediate and low level of prior knowledge, there is a significant difference of mathematical understanding between the experiment and control group. The mathematics anxiety is at an intermediate level in the experiment class and at a high level in the control group. There is no interaction between the learning model and the students’ prior knowledge towards the mathematical understanding, but there are interactions towards the mathematics anxiety. It indicates that the collaborative teaching model and the students’ prior knowledge do not simultaneously impacts on the mathematics understanding but the mathematics anxiety.

Developmental Change in the Influence of Domain-General Abilities and Domain-Specific Knowledge on Mathematics Achievement: An Eight-Year Longitudinal Study

PubMed Central

Geary, David C.; Nicholas, Alan; Li, Yaoran; Sun, Jianguo

2016-01-01

The contributions of domain-general abilities and domain-specific knowledge to subsequent mathematics achievement were longitudinally assessed (n = 167) through 8th grade. First grade intelligence and working memory and prior grade reading achievement indexed domain-general effects and domain-specific effects were indexed by prior grade mathematics achievement and mathematical cognition measures of prior grade number knowledge, addition skills, and fraction knowledge. Use of functional data analysis enabled grade-by-grade estimation of overall domain-general and domain-specific effects on subsequent mathematics achievement, the relative importance of individual domain-general and domain-specific variables on this achievement, and linear and non-linear across-grade estimates of these effects. The overall importance of domain-general abilities for subsequent achievement was stable across grades, with working memory emerging as the most important domain-general ability in later grades. The importance of prior mathematical competencies on subsequent mathematics achievement increased across grades, with number knowledge and arithmetic skills critical in all grades and fraction knowledge in later grades. Overall, domain-general abilities were more important than domain-specific knowledge for mathematics learning in early grades but general abilities and domain-specific knowledge were equally important in later grades. PMID:28781382

Hires and beyond

NASA Technical Reports Server (NTRS)

Fowler, John W.; Aumann, H. H.

1994-01-01

The High-Resolution image construction program (HiRes) used at IPAC is based on the Maximum Correlation Method. After HiRes intensity images are constructed from IRAS data, additional images are needed to aid in scientific interpretation. Some of the images that are available for this purpose show the fitting noise, estimates of the achieved resolution, and detector track maps. Two methods have been developed for creating color maps without discarding any more spatial information than absolutely necessary: the 'cross-band simulation' and 'prior-knowledge' methods. These maps are demonstrated using the survey observations of a 2 x 2 degree field centered on M31. Prior knowledge may also be used to achieve super-resolution and to suppress ringing around bright point sources observed against background emission. Tools to suppress noise spikes and for accelerating convergence are also described.

Hepatitis disease detection using Bayesian theory

NASA Astrophysics Data System (ADS)

Maseleno, Andino; Hidayati, Rohmah Zahroh

2017-02-01

This paper presents hepatitis disease diagnosis using a Bayesian theory for better understanding of the theory. In this research, we used a Bayesian theory for detecting hepatitis disease and displaying the result of diagnosis process. Bayesian algorithm theory is rediscovered and perfected by Laplace, the basic idea is using of the known prior probability and conditional probability density parameter, based on Bayes theorem to calculate the corresponding posterior probability, and then obtained the posterior probability to infer and make decisions. Bayesian methods combine existing knowledge, prior probabilities, with additional knowledge derived from new data, the likelihood function. The initial symptoms of hepatitis which include malaise, fever and headache. The probability of hepatitis given the presence of malaise, fever, and headache. The result revealed that a Bayesian theory has successfully identified the existence of hepatitis disease.

Prior schemata transfer as an account for assessing the intuitive use of new technology.

PubMed

Fischer, Sandrine; Itoh, Makoto; Inagaki, Toshiyuki

2015-01-01

New devices are considered intuitive when they allow users to transfer prior knowledge. Drawing upon fundamental psychology experiments that distinguish prior knowledge transfer from new schema induction, a procedure was specified for assessing intuitive use. This procedure was tested with 31 participants who, prior to using an on-board computer prototype, studied its screenshots in reading vs. schema induction conditions. Distinct patterns of transfer or induction resulted for features of the prototype whose functions were familiar or unfamiliar, respectively. Though moderated by participants' cognitive style, these findings demonstrated a means for quantitatively assessing transfer of prior knowledge as the operation that underlies intuitive use. Implications for interface evaluation and design, as well as potential improvements to the procedure, are discussed. Copyright © 2014 Elsevier Ltd and The Ergonomics Society. All rights reserved.

How Prior Knowledge and Colour Contrast Interfere Visual Search Processes in Novice Learners: An Eye Tracking Study

ERIC Educational Resources Information Center

Sonmez, Duygu; Altun, Arif; Mazman, Sacide Guzin

2012-01-01

This study investigates how prior content knowledge and prior exposure to microscope slides on the phases of mitosis effect students' visual search strategies and their ability to differentiate cells that are going through any phases of mitosis. Two different sets of microscope slide views were used for this purpose; with high and low colour…

Executive Functions as Moderators of the Worked Example Effect: When Shifting Is More Important than Working Memory Capacity

ERIC Educational Resources Information Center

Schwaighofer, Matthias; Bühner, Markus; Fischer, Frank

2016-01-01

Worked examples have proven to be effective for knowledge acquisition compared with problem solving, particularly when prior knowledge is low (e.g., Kalyuga, 2007). However, in addition to prior knowledge, executive functions and fluid intelligence might be potential moderators of the effectiveness of worked examples. The present study examines…

Effects of Activation of Prior Knowledge on the Recall of a Clinical Case.

ERIC Educational Resources Information Center

Schmidt, Henk G.; Boshuizen, Henny P. A.

A study investigated the known phenomenon of "intermediate effect" in which medical students with an intermediate amount of knowledge and experience demonstrate higher amounts of recall of the text of a medical case than either experienced clinicians or novices. In this study the amount of activation of prior knowledge was controlled by…

Effect of Altered Prior Knowledge on Passage Recall.

ERIC Educational Resources Information Center

Langer, Judith A.; Nicolich, Mark

A study was conducted to determine: (1) the relationships between prior knowledge and passage recall; (2) the effect of a prereading activity (PReP) on available knowledge; and (3) the effect of the PReP activity on total comprehension scores. The subjects were 161 sixth grade students from a middle class suburban Long Island, New York, public…

Does Teaching Experience Matter? Examining Biology Teachers' Prior Knowledge for Teaching in an Alternative Certification Program

ERIC Educational Resources Information Center

Friedrichsen, Patricia J.; Abell, Sandra K.; Pareja, Enrique M.; Brown, Patrick L.; Lankford, Deanna M.; Volkmann, Mark J.

2009-01-01

Alternative certification programs (ACPs) have been proposed as a viable way to address teacher shortages, yet we know little about how teacher knowledge develops within such programs. The purpose of this study was to investigate prior knowledge for teaching among students entering an ACP, comparing individuals with teaching experience to those…

The Importance of Prior Knowledge when Comparing Examples: Influences on Conceptual and Procedural Knowledge of Equation Solving

ERIC Educational Resources Information Center

Rittle-Johnson, Bethany; Star, Jon R.; Durkin, Kelley

2009-01-01

Comparing multiple examples typically supports learning and transfer in laboratory studies and is considered a key feature of high-quality mathematics instruction. This experimental study investigated the importance of prior knowledge in learning from comparison. Seventh- and 8th-grade students (N = 236) learned to solve equations by comparing…

Reverse engineering highlights potential principles of large gene regulatory network design and learning.

PubMed

Carré, Clément; Mas, André; Krouk, Gabriel

2017-01-01

Inferring transcriptional gene regulatory networks from transcriptomic datasets is a key challenge of systems biology, with potential impacts ranging from medicine to agronomy. There are several techniques used presently to experimentally assay transcription factors to target relationships, defining important information about real gene regulatory networks connections. These techniques include classical ChIP-seq, yeast one-hybrid, or more recently, DAP-seq or target technologies. These techniques are usually used to validate algorithm predictions. Here, we developed a reverse engineering approach based on mathematical and computer simulation to evaluate the impact that this prior knowledge on gene regulatory networks may have on training machine learning algorithms. First, we developed a gene regulatory networks-simulating engine called FRANK (Fast Randomizing Algorithm for Network Knowledge) that is able to simulate large gene regulatory networks (containing 10 4 genes) with characteristics of gene regulatory networks observed in vivo. FRANK also generates stable or oscillatory gene expression directly produced by the simulated gene regulatory networks. The development of FRANK leads to important general conclusions concerning the design of large and stable gene regulatory networks harboring scale free properties (built ex nihilo). In combination with supervised (accepting prior knowledge) support vector machine algorithm we (i) address biologically oriented questions concerning our capacity to accurately reconstruct gene regulatory networks and in particular we demonstrate that prior-knowledge structure is crucial for accurate learning, and (ii) draw conclusions to inform experimental design to performed learning able to solve gene regulatory networks in the future. By demonstrating that our predictions concerning the influence of the prior-knowledge structure on support vector machine learning capacity holds true on real data ( Escherichia coli K14 network reconstruction using network and transcriptomic data), we show that the formalism used to build FRANK can to some extent be a reasonable model for gene regulatory networks in real cells.

Bayes and blickets: Effects of knowledge on causal induction in children and adults

PubMed Central

Griffiths, Thomas L.; Sobel, David M.; Tenenbaum, Joshua B.; Gopnik, Alison

2011-01-01

People are adept at inferring novel causal relations, even from only a few observations. Prior knowledge about the probability of encountering causal relations of various types and the nature of the mechanisms relating causes and effects plays a crucial role in these inferences. We test a formal account of how this knowledge can be used and acquired, based on analyzing causal induction as Bayesian inference. Five studies explored the predictions of this account with adults and 4-year-olds, using tasks in which participants learned about the causal properties of a set of objects. The studies varied the two factors that our Bayesian approach predicted should be relevant to causal induction: the prior probability with which causal relations exist, and the assumption of a deterministic or a probabilistic relation between cause and effect. Adults’ judgments (Experiments 1, 2, and 4) were in close correspondence with the quantitative predictions of the model, and children’s judgments (Experiments 3 and 5) agreed qualitatively with this account. PMID:21972897

Specific previous experience affects perception of harmony and meter.

PubMed

Creel, Sarah C

2011-10-01

Prior knowledge shapes our experiences, but which prior knowledge shapes which experiences? This question is addressed in the domain of music perception. Three experiments were used to determine whether listeners activate specific musical memories during music listening. Each experiment provided listeners with one of two musical contexts that was presented simultaneously with a melody. After a listener was familiarized with melodies embedded in contexts, the listener heard melodies in isolation and judged the fit of a final harmonic or metrical probe event. The probe event matched either the familiar (but absent) context or an unfamiliar context. For both harmonic (Experiments 1 and 3) and metrical (Experiment 2) information, exposure to context shifted listeners' preferences toward a probe matching the context that they had been familiarized with. This suggests that listeners rapidly form specific musical memories without explicit instruction, which are then activated during music listening. These data pose an interesting challenge for models of music perception which implicitly assume that the listener's knowledge base is predominantly schematic or abstract.

What You Know Can Hurt You: Effects of Age and Prior Knowledge on the Accuracy of Judgments of Learning

PubMed Central

Toth, Jeffrey P.; Daniels, Karen A.; Solinger, Lisa A.

2011-01-01

How do aging and prior knowledge affect memory and metamemory? We explored this question in the context of a dual-process approach to Judgments of Learning (JOLs) which require people to predict their ability to remember information at a later time. Young and older adults (n's = 36, mean ages = 20.2 & 73.1) studied the names of actors that were famous in the 1950s or 1990s, providing a JOL for each. Recognition memory for studied and unstudied actors was then assessed using a Recollect/Know/No-Memory (R/K/N) judgment task. Results showed that prior knowledge increased recollection in both age groups such that older adults recollected significantly more 1950s actors than younger adults. Also, for both age groups and both decades, actors judged R at test garnered significantly higher JOLs at study than actors judged K or N. However, while the young showed benefits of prior knowledge on relative JOL accuracy, older adults did not, showing lower levels of JOL accuracy for 1950s actors despite having higher recollection for, and knowledge about, those actors. Overall, the data suggest that prior knowledge can be a double-edged sword, increasing the availability of details that can support later recollection, but also increasing non-diagnostic feelings of familiarity that can reduce the accuracy of memory predictions. PMID:21480715

Objective estimates based on experimental data and initial and final knowledge

NASA Technical Reports Server (NTRS)

Rosenbaum, B. M.

1972-01-01

An extension of the method of Jaynes, whereby least biased probability estimates are obtained, permits such estimates to be made which account for experimental data on hand as well as prior and posterior knowledge. These estimates can be made for both discrete and continuous sample spaces. The method allows a simple interpretation of Laplace's two rules: the principle of insufficient reason and the rule of succession. Several examples are analyzed by way of illustration.

Leveraging prior quantitative knowledge in guiding pediatric drug development: a case study.

PubMed

Jadhav, Pravin R; Zhang, Jialu; Gobburu, Jogarao V S

2009-01-01

The manuscript presents the FDA's focus on leveraging prior knowledge in designing informative pediatric trial through this case study. In developing written request for Drug X, an anti-hypertensive for immediate blood pressure (BP) control, the sponsor and FDA conducted clinical trial simulations (CTS) to design trial with proper sample size and support the choice of dose range. The objective was to effectively use prior knowledge from adult patients for drug X, pediatric data from Corlopam (approved for a similar indication) trial and general experience in developing anti-hypertensive agents. Different scenarios governing the exposure response relationship in the pediatric population were simulated to perturb model assumptions. The choice of scenarios was based on the past observation that pediatric population is less responsive and sensitive compared with adults. The conceptual framework presented here should serve as an example on how the industry and FDA scientists can collaborate in designing the pediatric exclusivity trial. Using CTS, inter-disciplinary scientists with the sponsor and FDA can objectively discuss the choice of dose range, sample size, endpoints and other design elements. These efforts are believed to yield plausible trial design, qrational dosing recommendations and useful labeling information in pediatrics. Published in 2009 by John Wiley & Sons, Ltd.

An Integrative Framework for Bayesian Variable Selection with Informative Priors for Identifying Genes and Pathways

PubMed Central

Ander, Bradley P.; Zhang, Xiaoshuai; Xue, Fuzhong; Sharp, Frank R.; Yang, Xiaowei

2013-01-01

The discovery of genetic or genomic markers plays a central role in the development of personalized medicine. A notable challenge exists when dealing with the high dimensionality of the data sets, as thousands of genes or millions of genetic variants are collected on a relatively small number of subjects. Traditional gene-wise selection methods using univariate analyses face difficulty to incorporate correlational, structural, or functional structures amongst the molecular measures. For microarray gene expression data, we first summarize solutions in dealing with ‘large p, small n’ problems, and then propose an integrative Bayesian variable selection (iBVS) framework for simultaneously identifying causal or marker genes and regulatory pathways. A novel partial least squares (PLS) g-prior for iBVS is developed to allow the incorporation of prior knowledge on gene-gene interactions or functional relationships. From the point view of systems biology, iBVS enables user to directly target the joint effects of multiple genes and pathways in a hierarchical modeling diagram to predict disease status or phenotype. The estimated posterior selection probabilities offer probabilitic and biological interpretations. Both simulated data and a set of microarray data in predicting stroke status are used in validating the performance of iBVS in a Probit model with binary outcomes. iBVS offers a general framework for effective discovery of various molecular biomarkers by combining data-based statistics and knowledge-based priors. Guidelines on making posterior inferences, determining Bayesian significance levels, and improving computational efficiencies are also discussed. PMID:23844055

An integrative framework for Bayesian variable selection with informative priors for identifying genes and pathways.

PubMed

Peng, Bin; Zhu, Dianwen; Ander, Bradley P; Zhang, Xiaoshuai; Xue, Fuzhong; Sharp, Frank R; Yang, Xiaowei

2013-01-01

The discovery of genetic or genomic markers plays a central role in the development of personalized medicine. A notable challenge exists when dealing with the high dimensionality of the data sets, as thousands of genes or millions of genetic variants are collected on a relatively small number of subjects. Traditional gene-wise selection methods using univariate analyses face difficulty to incorporate correlational, structural, or functional structures amongst the molecular measures. For microarray gene expression data, we first summarize solutions in dealing with 'large p, small n' problems, and then propose an integrative Bayesian variable selection (iBVS) framework for simultaneously identifying causal or marker genes and regulatory pathways. A novel partial least squares (PLS) g-prior for iBVS is developed to allow the incorporation of prior knowledge on gene-gene interactions or functional relationships. From the point view of systems biology, iBVS enables user to directly target the joint effects of multiple genes and pathways in a hierarchical modeling diagram to predict disease status or phenotype. The estimated posterior selection probabilities offer probabilitic and biological interpretations. Both simulated data and a set of microarray data in predicting stroke status are used in validating the performance of iBVS in a Probit model with binary outcomes. iBVS offers a general framework for effective discovery of various molecular biomarkers by combining data-based statistics and knowledge-based priors. Guidelines on making posterior inferences, determining Bayesian significance levels, and improving computational efficiencies are also discussed.

The impact of curiosity on learning during a school field trip to the zoo

NASA Astrophysics Data System (ADS)

Carlin, Kerry Ann

1999-11-01

This study was designed to examine (a) differences in cognitive learning as a result of a zoo field trip, (b) if the trip to the zoo had an impact on epistemic curiosity, (c) the role epistemic curiosity plays in learning, (d) the effect of gender, race, prior knowledge and prior visitation to the zoo on learning and epistemic curiosity, (e) participants' affect for the zoo animals, and (f) if prior visitation to the zoo contributes to prior knowledge. Ninety-six fourth and fifth grade children completed curiosity, cognitive, and affective written tests before and after a field trip to the Lowery Park Zoo in Tampa, Florida. The data showed that students were very curious about zoo animals. Dependent T-tests indicated no significant difference between pretest and posttest curiosity levels. The trip did not influence participants' curiosity levels. Multiple regression analysis was used to determine the relationship between the dependent variable, curiosity, and the independent variables, gender, race, prior knowledge, and prior visitation. No significant differences were found. Dependent T-tests indicated no significant difference between pretest and posttest cognitive scores. The field trip to the zoo did not cause an increase in participants' knowledge. However, participants did learn on the trip. After the field trip, participants identified more animals displayed by the zoo than they did before. Also, more animals were identified by species and genus names after the trip than before. These differences were significant (alpha = .05). Multiple regression analysis was used to determine the relationship between the dependent variable, posttest cognitive performance, and the independent variables, curiosity, gender, race, prior knowledge, and prior visitation. A significant difference was found for prior knowledge (alpha = .05). No significant differences were found for the other independent variables. Chi-square tests of significance indicated significant differences (alpha = .05) in preferences for types of animals and preference for animals by gender. Significant differences (alpha = .05) were also found between the reasons why animals were preferred. Differences occurred between animals that were liked and disliked, between genders, and between the pretest and the posttest.

An investigation of multitasking information behavior and the influence of working memory and flow

NASA Astrophysics Data System (ADS)

Alexopoulou, Peggy; Hepworth, Mark; Morris, Anne

2015-02-01

This study explored the multitasking information behaviour of Web users and how this is influenced by working memory, flow and Personal, Artefact and Task characteristics, as described in the PAT model. The research was exploratory using a pragmatic, mixed method approach. Thirty University students participated; 10 psychologists, 10 accountants and 10 mechanical engineers. The data collection tools used were: pre and post questionnaires, a working memory test, a flow state scale test, audio-visual data, web search logs, think aloud data, observation, and the critical decision method. All participants searched information on the Web for four topics: two for which they had prior knowledge and two more without prior knowledge. Perception of task complexity was found to be related to working memory. People with low working memory reported a significant increase in task complexity after they had completed information searching tasks for which they had no prior knowledge, this was not the case for tasks with prior knowledge. Regarding flow and task complexity, the results confirmed the suggestion of the PAT model (Finneran and Zhang, 2003), which proposed that a complex task can lead to anxiety and low flow levels as well as to perceived challenge and high flow levels. However, the results did not confirm the suggestion of the PAT model regarding the characteristics of web search systems and especially perceived vividness. All participants experienced high vividness. According to the PAT model, however, only people with high flow should experience high levels of vividness. Flow affected the degree of change of knowledge of the participants. People with high flow gained more knowledge for tasks without prior knowledge rather than people with low flow. Furthermore, accountants felt that tasks without prior knowledge were less complex at the end of the web seeking procedure than psychologists and mechanical engineers. Finally, the three disciplines appeared to differ regarding the multitasking information behaviour characteristics such as queries, web search sessions and opened tabs/windows.

Investigating the Effectiveness of an Inquiry-Based Intervention on Human Reproduction in Relation to Students' Gender, Prior Knowledge and Motivation for Learning in Biology

ERIC Educational Resources Information Center

Hadjichambis, Andreas Ch.; Georgiou, Yiannis; Paraskeva-Hadjichambi, Demetra; Kyza, Eleni A.; Mappouras, Demetrios

2016-01-01

Despite the importance of understanding how the human reproductive system works, adolescents worldwide exhibit weak conceptual understanding, which leads to serious risks, such as unwanted pregnancies and sexually transmitted diseases. Studies focusing on the development and evaluation of inquiry-based learning interventions, promoting the…

Powerful Learning Tools for ELLs: Using Native Language, Familiar Examples, and Concept Mapping to Teach English Language Learners

ERIC Educational Resources Information Center

Dong, Yu Ren

2013-01-01

This article highlights how English language learners' (ELLs) prior knowledge can be used to help learn science vocabulary. The article explains that the concept of prior knowledge needs to encompass the ELL student's native language, previous science learning, native literacy skills, and native cultural knowledge and life experiences.…

Teachers' Beliefs about the Role of Prior Language Knowledge in Learning and How These Influence Teaching Practices

ERIC Educational Resources Information Center

De Angelis, Gessica

2011-01-01

The present study was developed to assess teachers' beliefs on (1) the role of prior language knowledge in language learning; (2) the perceived usefulness of language knowledge in modern society; and (3) the teaching practices to be used with multilingual students. Subjects were 176 secondary schoolteachers working in Italy (N = 103), Austria (N =…

An image based vibration sensor for soft tissue modal analysis in a Digital Image Elasto Tomography (DIET) system.

PubMed

Feng, Sheng; Lotz, Thomas; Chase, J Geoffrey; Hann, Christopher E

2010-01-01

Digital Image Elasto Tomography (DIET) is a non-invasive elastographic breast cancer screening technology, based on image-based measurement of surface vibrations induced on a breast by mechanical actuation. Knowledge of frequency response characteristics of a breast prior to imaging is critical to maximize the imaging signal and diagnostic capability of the system. A feasibility analysis for a non-invasive image based modal analysis system is presented that is able to robustly and rapidly identify resonant frequencies in soft tissue. Three images per oscillation cycle are enough to capture the behavior at a given frequency. Thus, a sweep over critical frequency ranges can be performed prior to imaging to determine critical imaging settings of the DIET system to optimize its tumor detection performance.

What do we need to know prior to thinking about incorporating an epigenetic evaluation into safety assessments

EPA Science Inventory

The Ineternation Life Sciences Institute, Health and Environmental Sciences Institute sponsored a workgroup entitled "state of the science: evaluating epigenetic changes" hosted by NIEHS. The goal was to evaluate and enhance the scientific knowledge base regarding epigenetics an...

Modifying Cookbook Labs.

ERIC Educational Resources Information Center

Clark, Robert, L.; Clough, Michael P.; Berg, Craig A.

2000-01-01

Modifies an extended lab activity from a cookbook approach for determining the percent mass of water in copper sulfate pentahydrate crystals to one which incorporates students' prior knowledge, engenders active mental struggling with prior knowledge and new experiences, and encourages metacognition. (Contains 12 references.) (ASK)

Hybrid forecasting of chaotic processes: Using machine learning in conjunction with a knowledge-based model

NASA Astrophysics Data System (ADS)

Pathak, Jaideep; Wikner, Alexander; Fussell, Rebeckah; Chandra, Sarthak; Hunt, Brian R.; Girvan, Michelle; Ott, Edward

2018-04-01

A model-based approach to forecasting chaotic dynamical systems utilizes knowledge of the mechanistic processes governing the dynamics to build an approximate mathematical model of the system. In contrast, machine learning techniques have demonstrated promising results for forecasting chaotic systems purely from past time series measurements of system state variables (training data), without prior knowledge of the system dynamics. The motivation for this paper is the potential of machine learning for filling in the gaps in our underlying mechanistic knowledge that cause widely-used knowledge-based models to be inaccurate. Thus, we here propose a general method that leverages the advantages of these two approaches by combining a knowledge-based model and a machine learning technique to build a hybrid forecasting scheme. Potential applications for such an approach are numerous (e.g., improving weather forecasting). We demonstrate and test the utility of this approach using a particular illustrative version of a machine learning known as reservoir computing, and we apply the resulting hybrid forecaster to a low-dimensional chaotic system, as well as to a high-dimensional spatiotemporal chaotic system. These tests yield extremely promising results in that our hybrid technique is able to accurately predict for a much longer period of time than either its machine-learning component or its model-based component alone.

Exploiting Genome Structure in Association Analysis

PubMed Central

Kim, Seyoung

2014-01-01

Abstract A genome-wide association study involves examining a large number of single-nucleotide polymorphisms (SNPs) to identify SNPs that are significantly associated with the given phenotype, while trying to reduce the false positive rate. Although haplotype-based association methods have been proposed to accommodate correlation information across nearby SNPs that are in linkage disequilibrium, none of these methods directly incorporated the structural information such as recombination events along chromosome. In this paper, we propose a new approach called stochastic block lasso for association mapping that exploits prior knowledge on linkage disequilibrium structure in the genome such as recombination rates and distances between adjacent SNPs in order to increase the power of detecting true associations while reducing false positives. Following a typical linear regression framework with the genotypes as inputs and the phenotype as output, our proposed method employs a sparsity-enforcing Laplacian prior for the regression coefficients, augmented by a first-order Markov process along the sequence of SNPs that incorporates the prior information on the linkage disequilibrium structure. The Markov-chain prior models the structural dependencies between a pair of adjacent SNPs, and allows us to look for association SNPs in a coupled manner, combining strength from multiple nearby SNPs. Our results on HapMap-simulated datasets and mouse datasets show that there is a significant advantage in incorporating the prior knowledge on linkage disequilibrium structure for marker identification under whole-genome association. PMID:21548809

Dealing with difficult deformations: construction of a knowledge-based deformation atlas

NASA Astrophysics Data System (ADS)

Thorup, S. S.; Darvann, T. A.; Hermann, N. V.; Larsen, P.; Ólafsdóttir, H.; Paulsen, R. R.; Kane, A. A.; Govier, D.; Lo, L.-J.; Kreiborg, S.; Larsen, R.

2010-03-01

Twenty-three Taiwanese infants with unilateral cleft lip and palate (UCLP) were CT-scanned before lip repair at the age of 3 months, and again after lip repair at the age of 12 months. In order to evaluate the surgical result, detailed point correspondence between pre- and post-surgical images was needed. We have previously demonstrated that non-rigid registration using B-splines is able to provide automated determination of point correspondences in populations of infants without cleft lip. However, this type of registration fails when applied to the task of determining the complex deformation from before to after lip closure in infants with UCLP. The purpose of the present work was to show that use of prior information about typical deformations due to lip closure, through the construction of a knowledge-based atlas of deformations, could overcome the problem. Initially, mean volumes (atlases) for the pre- and post-surgical populations, respectively, were automatically constructed by non-rigid registration. An expert placed corresponding landmarks in the cleft area in the two atlases; this provided prior information used to build a knowledge-based deformation atlas. We model the change from pre- to post-surgery using thin-plate spline warping. The registration results are convincing and represent a first move towards an automatic registration method for dealing with difficult deformations due to this type of surgery.

Uncertainty Quantification Techniques for Population Density Estimates Derived from Sparse Open Source Data

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

Stewart, Robert N; White, Devin A; Urban, Marie L

2013-01-01

The Population Density Tables (PDT) project at the Oak Ridge National Laboratory (www.ornl.gov) is developing population density estimates for specific human activities under normal patterns of life based largely on information available in open source. Currently, activity based density estimates are based on simple summary data statistics such as range and mean. Researchers are interested in improving activity estimation and uncertainty quantification by adopting a Bayesian framework that considers both data and sociocultural knowledge. Under a Bayesian approach knowledge about population density may be encoded through the process of expert elicitation. Due to the scale of the PDT effort whichmore » considers over 250 countries, spans 40 human activity categories, and includes numerous contributors, an elicitation tool is required that can be operationalized within an enterprise data collection and reporting system. Such a method would ideally require that the contributor have minimal statistical knowledge, require minimal input by a statistician or facilitator, consider human difficulties in expressing qualitative knowledge in a quantitative setting, and provide methods by which the contributor can appraise whether their understanding and associated uncertainty was well captured. This paper introduces an algorithm that transforms answers to simple, non-statistical questions into a bivariate Gaussian distribution as the prior for the Beta distribution. Based on geometric properties of the Beta distribution parameter feasibility space and the bivariate Gaussian distribution, an automated method for encoding is developed that responds to these challenging enterprise requirements. Though created within the context of population density, this approach may be applicable to a wide array of problem domains requiring informative priors for the Beta distribution.« less

Dental Faculty Members' Pedagogic Beliefs and Curriculum Aims in Problem-Based Learning: An Exploratory Study.

PubMed

von Bergmann, HsingChi; Walker, Judith; Dalrymple, Kirsten R; Shuler, Charles F

2017-08-01

The aims of this exploratory study were to explore dental faculty members' views and beliefs regarding knowledge, the dental profession, and teaching and learning and to determine how these views related to their problem-based learning (PBL) instructional practices. Prior to a PBL in dental education conference held in 2011, all attendees were invited to complete a survey focused on their pedagogical beliefs and practices in PBL. Out of a possible 55 participants, 28 responded. Additionally, during the conference, a forum was held in which preliminary survey findings were shared and participants contributed to focus group data collection. The forum results served to validate and bring deeper understanding to the survey findings. The conference participants who joined the forum (N=32) likely included some or many of the anonymous respondents to the survey, along with additional participants interested in dental educators' beliefs. The findings of the survey and follow-up forum indicated a disconnect between dental educators' reported views of knowledge and their pedagogical practices in a PBL environment. The results suggested that the degree of participants' tolerance of uncertainty in knowledge and the discrepancy between their epistemological and ontological beliefs about PBL pedagogy influenced their pedagogical choices. These findings support the idea that learner-centered, inquiry-based pedagogical approaches such as PBL may create dissonance between beliefs about knowledge and pedagogical practice that require the building of a shared understanding of and commitment to curricular goals prior to implementation to ensure success. The methods used in this study can be useful tools for faculty development in PBL programs in dental education.

Effects of Prior Economic Education, Native Language, and Gender on Economic Knowledge of First-Year Students in Higher Education. A Comparative Study between Germany and the USA

ERIC Educational Resources Information Center

Brückner, Sebastian; Förster, Manuel; Zlatkin-Troitschanskaia, Olga; Walstad, William B.

2015-01-01

The assessment of university students' economic knowledge has become an increasingly important research area within and across countries. Particularly, the different influences of prior education, native language, and gender as some of the main prerequisites on students' economic knowledge have been highlighted since long. However, the findings…

The iSCREEN Electronic Diabetes Dashboard: A Tool to Improve Knowledge and Implementation of Pediatric Clinical Practice Guidelines.

PubMed

Zahanova, Stacy; Tsouka, Alexandra; Palmert, Mark R; Mahmud, Farid H

2017-12-01

Clinical practice guidelines (CPG) provide evidence-based recommendations for patient care but may not be optimally applied in clinical settings. As a pilot study, we evaluated the impact of a computerized, point-of-care decision support system (CDSS) on guideline knowledge and adherence in our diabetes clinic. iSCREEN, a CDSS, integrated with a province-wide electronic health record, was designed based on the Canadian Diabetes Association 2013 Clinical Practice Guidelines for the Prevention and Management of Diabetes in Canada. Evaluation data were gathered by retrospective chart review and clinician questionnaire prior to and after implementation of iSCREEN. Records of patients with type 1 diabetes, 14 to 18 years of age, were assessed for appropriate screening for complications and comorbidities. To assess guideline adherence, 50 charts were reviewed at 2 time periods (25 before and 25 after launch of iSCREEN). Results revealed improved frequency of appropriate screening for diabetic nephropathy (p=0.03) and retinopathy (p=0.04), accompanied by a decrease in under- and overscreening for these outcomes. To assess guideline knowledge, 58 surveys were collected (31 prior to and 27 after the launch of iSCREEN) from care providers in the field of pediatric diabetes. There was a trend toward improved guideline knowledge in all team members (p=0.06). Implementation of a de novo CDSS was associated with improved rates of appropriate screening for diabetes-related complications. A trend toward improvement in health professionals' knowledge of the guidelines was also observed. Evaluation of this point-of-care computerized decision support tool suggests that it may facilitate diabetes care by optimizing complication screening and CPG knowledge, with the potential for broader implementation. Copyright © 2017 Diabetes Canada. Published by Elsevier Inc. All rights reserved.

The influence of the history of science course on pre-service science teachers' understanding of the nature of science concepts

NASA Astrophysics Data System (ADS)

Akcay, Behiye

The purpose of this study was to investigate the influence of a history of science course on pre-service science teachers' understanding of the nature of science concepts. Subjects in the study were divided in two groups: (1) students who enrolled in only in the history of science course, (2) students who enrolled both the meaning of science and the history of science courses. An interpretative-descriptive approach and constant comparative analysis were used to identify similarities and differences among pre-service teachers' views about nature of scientific knowledge prior to and after the history of science course. The results of this study indicate that explicitly addressing certain aspects of the nature of science is effective in promoting adequate understanding of the nature of science for pre-service science teachers. Moreover, the results indicate that a student's prior experience with the history of science helps to improve their understanding of the history and nature of science. The history of science course helped pre-service teachers to develop the following views which are parallel with these advocated in both the Benchmarks (AAAS, 1993) and the National Science Education Standards (NRC, 1996) concerning the nature of scientific knowledge: (1) Scientific knowledge is empirically based and an ongoing process of experimentation, investigation, and observation. (2) Science is a human endeavor. (3) People from different cultures, races, genders, and nationality contribute to science. (4) Scientific knowledge is not based on myths, personal beliefs, and religious values. (5) Science background and prior knowledge have important roles for scientific investigations. (6) Scientific theories and laws represent different kinds of knowledge. (7) Science is affected by political, social, and cultural values. (8) Creativity and imagination are used during all stages of scientific investigations. (9) Theories change because of new evidence and new views of existing data as well as advances in technology. (10) Theories have significant roles in generating future research questions. (11) Adequate understanding of differences between observations and inferences develop from considering the history of science. (12) There is no single universal step-by-step scientific method. (13) Learning about the nature of scientific knowledge helps students to become scientifically literate.

Leadership for Dummies: A Capstone Project for Leadership Students

ERIC Educational Resources Information Center

Moore, Lori L.; Odom, Summer F.; Wied, Lexi M.

2011-01-01

Capstone courses in leadership provide students opportunities to synthesize prior knowledge about various aspects of leadership. This article describes the "Leadership for Dummies" project, which could be used as a capstone experience for leadership majors. Based on his experiences as a psychological researcher, Gardner (2008) identified five…

Low-Cost Avionics Simulation for Aircrew Training.

ERIC Educational Resources Information Center

Edwards, Bernell J.

This report documents an experiment to determine the training effectiveness of a microcomputer-based avionics system trainer as a cost-effective alternative to training in the actual aircraft. Participants--26 operationally qualified C-141 pilots with no prior knowledge of the Fuel Saving Advisory System (FSAS), a computerized fuel management…

78 FR 9391 - Agency Information Collection Activities; Proposed Collection; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2013-02-08

... extend the existing PRA clearance for the information collection requirements associated with the... burden of the FCLCA and Rule based on its knowledge of, and information from, the eye care industry... party prescriber. No substantive provisions in the Rule have been amended or changed since staff's prior...

Enhancing Students' Communication Skills through Treffinger Teaching Model

ERIC Educational Resources Information Center

Alhaddad, Idrus; Kusumah, Yaya S.; Sabandar, Jozua; Dahlan, Jarnawi A.

2015-01-01

This research aims to investigate, compare, and describe the achievement and enhancement of students' mathematical communication skills (MCS). It based on the prior mathematical knowledge (PMK) category (high, medium and low) by using Treffinger models (TM) and conventional learning (CL). This research is an experimental study with the population…

Interactive and Collaborative Professional Development for In-Service History Teachers

ERIC Educational Resources Information Center

Callahan, Cory; Saye, John; Brush, Thomas

2016-01-01

This article advances a continuing line of inquiry into an innovative teacher-support program intended to help in-service history teachers develop professional teaching knowledge for inquiry-based history instruction. Two prior iterations informed our design and use of professional development materials; they also informed the implementation…

Common Knowledge, Learning, and Citation Practices in University Writing

ERIC Educational Resources Information Center

Shi, Ling

2011-01-01

The present study is based on interviews of students (n = 48) and instructors (n = 27) from various disciplines in a North American research university and explores participants' comments on examples of some students' unacknowledged texts appropriated and drawn from published sources, classroom learning, or unidentified prior reading. Although…

Self-Regulated Strategy Instruction in College Developmental Writing

ERIC Educational Resources Information Center

MacArthur, Charles A.; Philippakos, Zoi A.; Ianetta, Melissa

2015-01-01

The purpose of this study was to evaluate the effects of a curriculum for college developmental writing classes, developed in prior design research and based on self-regulated strategy instruction. Students learned strategies for planning, drafting, and revising compositions with an emphasis on using knowledge of genre organization to guide…

Paternity Testing in a PBL Environment

ERIC Educational Resources Information Center

Casla, Alberto Vicario; Zubiaga, Isabel Smith

2010-01-01

Problem Based Learning (PBL) makes use of real-life scenarios to stimulate students' prior knowledge and to provide a meaningful context that is also related to the student's future professional work. In this article, Paternity testing is presented using a PBL approach that involves a combination of classroom, laboratory, and out-of-class…

Nudging toward Inquiry: Developing Questions and a Sense of Wonder

ERIC Educational Resources Information Center

Fontichiaro, Kristin, Comp.

2010-01-01

Inquiry does not replace information literacy; it encompasses it. It encourages librarians to consider instructional design beyond information search, retrieval, citation, and use. Inquiry-based learning invites school librarians to step into all aspects of instructional planning, from activating prior knowledge straight through to reflection.…

Repeating Input-Based Tasks with Young Beginner Learners

ERIC Educational Resources Information Center

Shintani, Natsuko

2012-01-01

The study reported in this article investigated task-repetition with young Japanese children. Fifteen children with no prior knowledge of English completed a communicative listening task that was designed to introduce new vocabulary. The same task was repeated nine times over five weeks. In line with Allwright's (1984) claim that "interaction…

Conversational Agents Improve Peer Learning through Building on Prior Knowledge

ERIC Educational Resources Information Center

Tegos, Stergios; Demetriadis, Stavros

2017-01-01

Research in computer-supported collaborative learning has indicated that conversational agents can be pedagogically beneficial when used to scaffold students' online discussions. In this study, we investigate the impact of an agile conversational agent that triggers student dialogue by making interventions based on the academically productive talk…

Understanding the Impact of Individual Differences on Learner Performance Using Hypermedia Systems

ERIC Educational Resources Information Center

Alhajri, Rana; Alhunaiyyan, Ahmed A.; AlMousa, Eba'

2017-01-01

In recent studies, there has been focus on understanding learner performance and behaviour using Web-Based Instruction (WBI) systems which accommodate individual differences. Studies have investigated the performance of these differences individually such as gender, cognitive style and prior knowledge. In this article, the authors describe a…

Preservice Science Teachers' Science Teaching Orientations and Beliefs about Science

ERIC Educational Resources Information Center

Kind, Vanessa

2016-01-01

This paper offers clarification of science teacher orientations as a potential component of pedagogical content knowledge. Science teaching orientations and beliefs about science held by 237 preservice science teachers were gathered via content-specific vignettes and questionnaire, respectively, prior to participation in a UK-based teacher…

A Data Base for Curriculum Design in Medical Ethics.

ERIC Educational Resources Information Center

Tiberius, Richard G.; Cleave-Hogg, Doreen

1984-01-01

A study to provide information about medical students' prior knowledge of and attitudes toward medical ethics is reported. A questionnaire was administered to 845 entering medical students at the University of Toronto. The results support the need for a course that requires thinking rather than rote memory. (Author/MLW)

Language knowledge and event knowledge in language use.

PubMed

Willits, Jon A; Amato, Michael S; MacDonald, Maryellen C

2015-05-01

This paper examines how semantic knowledge is used in language comprehension and in making judgments about events in the world. We contrast knowledge gleaned from prior language experience ("language knowledge") and knowledge coming from prior experience with the world ("world knowledge"). In two corpus analyses, we show that previous research linking verb aspect and event representations have confounded language and world knowledge. Then, using carefully chosen stimuli that remove this confound, we performed four experiments that manipulated the degree to which language knowledge or world knowledge should be salient and relevant to performing a task, finding in each case that participants use the type of knowledge most appropriate to the task. These results provide evidence for a highly context-sensitive and interactionist perspective on how semantic knowledge is represented and used during language processing. Copyright © 2015. Published by Elsevier Inc.

Knowledge and practices regarding menstruation among adolescent girls in an urban slum, Bijapur.

PubMed

Udgiri, Rekha; Angadi, M M; Patil, Shailaja; Sorganvi, Vijaya

2010-08-01

Adolescence is a crucial period in woman's life. The adolescent girls of today are the mothers of tomorrow in whose hand lie the future of her family, community and the nation. Because of the scarcity of information regarding the problems of adolescent girls, particularly in urban areas, the present study was undertaken to elicit information about the knowledge and practices regarding menstruation among adolescent girls. With this objective, a community-based cross-sectional study was done in an urban field practice area of BLDEA's Shri BM Patil Medical College, Bijapur. The study subjects included all adolescent girls who had attained menarche. Data was collected by questionnaire method and analysed. Out of 342 adolescent girls 324 (94.74%) were literate. Only 63 (18.42%) had knowledge about menstruation prior to attainment of menarche and this association was found to be statistically significant. The main source of information about menstruation was mother ie, 195 (57.01%). Nearly 81.58% adolescent girls were lacking knowledge about menstruation prior to menarche, this reflects upon the standard of awareness in the society to such important event and it also leads to negative reaction to menarche.

Polyenergetic known-component reconstruction without prior shape models

NASA Astrophysics Data System (ADS)

Zhang, C.; Zbijewski, W.; Zhang, X.; Xu, S.; Stayman, J. W.

2017-03-01

Purpose: Previous work has demonstrated that structural models of surgical tools and implants can be integrated into model-based CT reconstruction to greatly reduce metal artifacts and improve image quality. This work extends a polyenergetic formulation of known-component reconstruction (Poly-KCR) by removing the requirement that a physical model (e.g. CAD drawing) be known a priori, permitting much more widespread application. Methods: We adopt a single-threshold segmentation technique with the help of morphological structuring elements to build a shape model of metal components in a patient scan based on initial filtered-backprojection (FBP) reconstruction. This shape model is used as an input to Poly-KCR, a formulation of known-component reconstruction that does not require a prior knowledge of beam quality or component material composition. An investigation of performance as a function of segmentation thresholds is performed in simulation studies, and qualitative comparisons to Poly-KCR with an a priori shape model are made using physical CBCT data of an implanted cadaver and in patient data from a prototype extremities scanner. Results: We find that model-free Poly-KCR (MF-Poly-KCR) provides much better image quality compared to conventional reconstruction techniques (e.g. FBP). Moreover, the performance closely approximates that of Poly- KCR with an a prior shape model. In simulation studies, we find that imaging performance generally follows segmentation accuracy with slight under- or over-estimation based on the shape of the implant. In both simulation and physical data studies we find that the proposed approach can remove most of the blooming and streak artifacts around the component permitting visualization of the surrounding soft-tissues. Conclusion: This work shows that it is possible to perform known-component reconstruction without prior knowledge of the known component. In conjunction with the Poly-KCR technique that does not require knowledge of beam quality or material composition, very little needs to be known about the metal implant and system beforehand. These generalizations will allow more widespread application of KCR techniques in real patient studies where the information of surgical tools and implants is limited or not available.

Level of Skill Argued Students on Physics Material

NASA Astrophysics Data System (ADS)

Viyanti, V.; Cari, C.; Sunarno, W.; Prasetyo, Z. K.

2017-09-01

This study aims to analyze the prior knowledge of students to map the level of skills to argue floating and sinking material. Prior knowledge is the process of concept formation in cognitive processes spontaneously or based on student experience. The study population is high school students of class XI. The sample selection using cluster random sampling, obtained the number of sampel as many as 50 student. The research used descriptive survey method. The data were obtained through a multiple choice test both grounded and interviewed. The data analyzed refers to: alignment the concept and the activity of developing the skill of the argument. The result obtained by the average level of skill argue in terms of the prior knowladge of on “Level 2”. The data show that students have difficulty expressing simple arguments consisting of only one statement. This indicates a lack of student experience in cultivating argumentative skills in their learning. The skill level mapping argued in this study to be a reference for researchers to provide feedback measures to obtain positive change in cognitive conflict argued.

Knowledge and perception of tuberculosis and the risk to become treatment default among newly diagnosed pulmonary tuberculosis patients treated in primary health care, East Nusa Tenggara: a retrospective study.

PubMed

Putera, Ikhwanuliman; Pakasi, Trevino A; Karyadi, Elvina

2015-06-10

Despite the high efficacy of tuberculosis (TB) drug regiments, one of the barriers in the TB control program is the non-compliance to treatment. Morbidity, mortality, and risk to become resistant to drugs are emerging among defaulters. Thus, the aim of this study is to identify the factors, especially knowledge and perceptions of TB and association with treatment default among patients treated in primary care settings, East Nusa Tenggara. This study was part of a bigger cohort community-based controlled trial study. The subjects were newly diagnosed pulmonary TB patients from four districts in East Nusa Tenggara. Knowledge, perception of TB, and other related factors were assessed prior to the treatment. Patients who interrupted the treatment in two consecutive months were classified as defaulters, as World Health Organization stated. Odds ratio (OR) looking for factors associated with becoming defaulter was analyzed. A total of 300 patients were recruited for this study. At the end of the treatment, 255 patients (85%) completed the treatment without interruption from regular visit. In univariate analysis, none of the socio-demographic factors attributed to treatment default yet lack of knowledge and incorrect perception of TB prior therapy (OR 2.49 1.30-4.79 95% CI, p = 0.006; OR 5.40 2.64-11.04 95% CI, p < 0.001, respectively). In multivariate analysis, only incorrect perception of TB showed significant association with treatment default (OR 4.75 2.30-9.86 95% CI). Assessing the knowledge and perception of TB prior to the treatment in newly pulmonary TB patients is important as both of them were known as risk factor for treatment default. Education and counseling may be required to improve patients' compliance to treatment.

Cognitive flexibility and undergraduate physiology students: increasing advanced knowledge acquisition within an ill-structured domain.

PubMed

Rhodes, Ashley E; Rozell, Timothy G

2017-09-01

Cognitive flexibility is defined as the ability to assimilate previously learned information and concepts to generate novel solutions to new problems. This skill is crucial for success within ill-structured domains such as biology, physiology, and medicine, where many concepts are simultaneously required for understanding a complex problem, yet the problem consists of patterns or combinations of concepts that are not consistently used or needed across all examples. To succeed within ill-structured domains, a student must possess a certain level of cognitive flexibility: rigid thought processes and prepackaged informational retrieval schemes relying on rote memorization will not suffice. In this study, we assessed the cognitive flexibility of undergraduate physiology students using a validated instrument entitled Student's Approaches to Learning (SAL). The SAL evaluates how deeply and in what way information is processed, as well as the investment of time and mental energy that a student is willing to expend by measuring constructs such as elaboration and memorization. Our results indicate that students who rely primarily on memorization when learning new information have a smaller knowledge base about physiological concepts, as measured by a prior knowledge assessment and unit exams. However, students who rely primarily on elaboration when learning new information have a more well-developed knowledge base about physiological concepts, which is displayed by higher scores on a prior knowledge assessment and increased performance on unit exams. Thus students with increased elaboration skills possibly possess a higher level of cognitive flexibility and are more likely to succeed within ill-structured domains. Copyright © 2017 the American Physiological Society.

Constructivist learning at the science-policy interface: tsunami science informing disaster policy in West Sumatra

NASA Astrophysics Data System (ADS)

McCaughey, J.; Dewi, P. R.; Natawidjaja, D. H.; Sieh, K. E.

2012-12-01

Science communication often falls short when it is based on the blank-slate assumption that if we can just get the message right, then the information will be received and understood as intended. In contrast, constructivist learning theory and practice suggest that we all actively construct our knowledge from a variety of information sources and through particular, novel associations with our prior knowledge. This constructed knowledge can be quite different from any of its original sources, such as a particular science communication. Successful communication requires carefully examining how people construct their knowledge of the topic of interest. Examples from our outreach work to connect hazard-science research with disaster-risk reduction practice in West Sumatra illustrate the mismatch between expert and stakeholder/public mental models of the characteristics of tsunamigenic earthquakes. There are incorrect conceptions that seawater always withdraws before a tsunami, and that a tsunami can be produced by an earthquake only if the epicenter is located at the ocean trench. These incorrect conceptions arise from generalizations based on recent, local earthquake experiences, as well as from unintended consequences of science outreach, science education, and, in one case, the way that tsunami modelling is graphically presented in scientific journals. We directly address these incorrect conceptions in our discussions with government officials and others; as a result, the local disaster-management agency has changed its policies to reflect an increased understanding of the hazard. This outreach success would not have been possible without eliciting the prior knowledge of our audiences through dialogue.

Web Design Curriculum and Syllabus Based on Web Design Practice and Students' Prior Knowledge

ERIC Educational Resources Information Center

Krunic, Tanja; Ruzic-Dimitrijevic, Ljiljana; Petrovic, Branka; Farkas, Robert

2006-01-01

The Advanced Technical School from Novi Sad set up a completely new study group for web design in 2004. The main goals of the paper are to explain the steps that were taken in starting this group, and to present the educational program based on our own research through the organization of the group and course descriptions. Since there is a…

On-the-spot lung cancer differential diagnosis by label-free, molecular vibrational imaging and knowledge-based classification

NASA Astrophysics Data System (ADS)

Gao, Liang; Li, Fuhai; Thrall, Michael J.; Yang, Yaliang; Xing, Jiong; Hammoudi, Ahmad A.; Zhao, Hong; Massoud, Yehia; Cagle, Philip T.; Fan, Yubo; Wong, Kelvin K.; Wang, Zhiyong; Wong, Stephen T. C.

2011-09-01

We report the development and application of a knowledge-based coherent anti-Stokes Raman scattering (CARS) microscopy system for label-free imaging, pattern recognition, and classification of cells and tissue structures for differentiating lung cancer from non-neoplastic lung tissues and identifying lung cancer subtypes. A total of 1014 CARS images were acquired from 92 fresh frozen lung tissue samples. The established pathological workup and diagnostic cellular were used as prior knowledge for establishment of a knowledge-based CARS system using a machine learning approach. This system functions to separate normal, non-neoplastic, and subtypes of lung cancer tissues based on extracted quantitative features describing fibrils and cell morphology. The knowledge-based CARS system showed the ability to distinguish lung cancer from normal and non-neoplastic lung tissue with 91% sensitivity and 92% specificity. Small cell carcinomas were distinguished from nonsmall cell carcinomas with 100% sensitivity and specificity. As an adjunct to submitting tissue samples to routine pathology, our novel system recognizes the patterns of fibril and cell morphology, enabling medical practitioners to perform differential diagnosis of lung lesions in mere minutes. The demonstration of the strategy is also a necessary step toward in vivo point-of-care diagnosis of precancerous and cancerous lung lesions with a fiber-based CARS microendoscope.

Activating lay health influencers to promote tobacco cessation.

PubMed

Muramoto, Myra L; Hall, John R; Nichter, Mark; Nichter, Mimi; Aickin, Mikel; Connolly, Tim; Matthews, Eva; Campbell, Jean Z; Lando, Harry A

2014-05-01

To evaluate the effect of tobacco cessation brief-intervention (BI) training for lay "health influencers," on knowledge, self-efficacy and the proportion of participants reporting BI delivery post-training. Randomized, community-based study comparing In-person or Web-based training, with mailed materials. In-person and Web-training groups had significant post-training cessation knowledge and self-efficacy gains. All groups increased the proportion of individuals reporting BIs at follow-up, with no significant between-group differences. Irrespective of participants' prior intervention experience, 80%-86% reported BIs within the past 90 days; 71%-79% reported >1 in the past 30. Web and In-person training significantly increase health influencer cessation knowledge and self-efficacy. With minimal prompting and materials, even persons without BI experience can be activated to encourage tobacco cessation.

The SwissLipids knowledgebase for lipid biology

PubMed Central

Liechti, Robin; Hyka-Nouspikel, Nevila; Niknejad, Anne; Gleizes, Anne; Götz, Lou; Kuznetsov, Dmitry; David, Fabrice P.A.; van der Goot, F. Gisou; Riezman, Howard; Bougueleret, Lydie; Xenarios, Ioannis; Bridge, Alan

2015-01-01

Motivation: Lipids are a large and diverse group of biological molecules with roles in membrane formation, energy storage and signaling. Cellular lipidomes may contain tens of thousands of structures, a staggering degree of complexity whose significance is not yet fully understood. High-throughput mass spectrometry-based platforms provide a means to study this complexity, but the interpretation of lipidomic data and its integration with prior knowledge of lipid biology suffers from a lack of appropriate tools to manage the data and extract knowledge from it. Results: To facilitate the description and exploration of lipidomic data and its integration with prior biological knowledge, we have developed a knowledge resource for lipids and their biology—SwissLipids. SwissLipids provides curated knowledge of lipid structures and metabolism which is used to generate an in silico library of feasible lipid structures. These are arranged in a hierarchical classification that links mass spectrometry analytical outputs to all possible lipid structures, metabolic reactions and enzymes. SwissLipids provides a reference namespace for lipidomic data publication, data exploration and hypothesis generation. The current version of SwissLipids includes over 244 000 known and theoretically possible lipid structures, over 800 proteins, and curated links to published knowledge from over 620 peer-reviewed publications. We are continually updating the SwissLipids hierarchy with new lipid categories and new expert curated knowledge. Availability: SwissLipids is freely available at http://www.swisslipids.org/. Contact: alan.bridge@isb-sib.ch Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25943471

Daniel Goodman’s empirical approach to Bayesian statistics

USGS Publications Warehouse

Gerrodette, Tim; Ward, Eric; Taylor, Rebecca L.; Schwarz, Lisa K.; Eguchi, Tomoharu; Wade, Paul; Himes Boor, Gina

2016-01-01

Bayesian statistics, in contrast to classical statistics, uses probability to represent uncertainty about the state of knowledge. Bayesian statistics has often been associated with the idea that knowledge is subjective and that a probability distribution represents a personal degree of belief. Dr. Daniel Goodman considered this viewpoint problematic for issues of public policy. He sought to ground his Bayesian approach in data, and advocated the construction of a prior as an empirical histogram of “similar” cases. In this way, the posterior distribution that results from a Bayesian analysis combined comparable previous data with case-specific current data, using Bayes’ formula. Goodman championed such a data-based approach, but he acknowledged that it was difficult in practice. If based on a true representation of our knowledge and uncertainty, Goodman argued that risk assessment and decision-making could be an exact science, despite the uncertainties. In his view, Bayesian statistics is a critical component of this science because a Bayesian analysis produces the probabilities of future outcomes. Indeed, Goodman maintained that the Bayesian machinery, following the rules of conditional probability, offered the best legitimate inference from available data. We give an example of an informative prior in a recent study of Steller sea lion spatial use patterns in Alaska.

Estimating the effect of lay knowledge and prior contact with pulmonary TB patients, on health-belief model in a high-risk pulmonary TB transmission population.

PubMed

Zein, Rizqy Amelia; Suhariadi, Fendy; Hendriani, Wiwin

2017-01-01

The research aimed to investigate the effect of lay knowledge of pulmonary tuberculosis (TB) and prior contact with pulmonary TB patients on a health-belief model (HBM) as well as to identify the social determinants that affect lay knowledge. Survey research design was conducted, where participants were required to fill in a questionnaire, which measured HBM and lay knowledge of pulmonary TB. Research participants were 500 residents of Semampir, Asemrowo, Bubutan, Pabean Cantian, and Simokerto districts, where the risk of pulmonary TB transmission is higher than other districts in Surabaya. Being a female, older in age, and having prior contact with pulmonary TB patients significantly increase the likelihood of having a higher level of lay knowledge. Lay knowledge is a substantial determinant to estimate belief in the effectiveness of health behavior and personal health threat. Prior contact with pulmonary TB patients is able to explain the belief in the effectiveness of a health behavior, yet fails to estimate participants' belief in the personal health threat. Health authorities should prioritize males and young people as their main target groups in a pulmonary TB awareness campaign. The campaign should be able to reconstruct people's misconception about pulmonary TB, thereby bringing around the health-risk perception so that it is not solely focused on improving lay knowledge.

The positive and negative consequences of multiple-choice testing.

PubMed

Roediger, Henry L; Marsh, Elizabeth J

2005-09-01

Multiple-choice tests are commonly used in educational settings but with unknown effects on students' knowledge. The authors examined the consequences of taking a multiple-choice test on a later general knowledge test in which students were warned not to guess. A large positive testing effect was obtained: Prior testing of facts aided final cued-recall performance. However, prior testing also had negative consequences. Prior reading of a greater number of multiple-choice lures decreased the positive testing effect and increased production of multiple-choice lures as incorrect answers on the final test. Multiple-choice testing may inadvertently lead to the creation of false knowledge.

Problem-based Learning Using the Online Medicare Part D Plan Finder Tool

PubMed Central

Stebbins, Marilyn R.; Lai, Eric; Smith, Amanda R.; Lipton, Helene Levens

2008-01-01

Objectives To implement didactic and problem-based learning curricular innovations aimed at increasing students' knowledge of Medicare Part D, improving their ability to apply the online Medicare Prescription Drug Plan Finder tool to a patient case, and improving their attitudes toward patient advocacy for Medicare beneficiaries. Methods A survey instrument and a case-based online Medicare Prescription Drug Plan Finder tool exercise were administered to a single group (n = 120) of second-year pharmacy graduate students prior to and following completion of a course on health policy. Three domains (knowledge, skill mastery and attitudes) were measured before and after two 90-minute lectures on Medicare Part D. Results The online Medicare Prescription Drug Plan Finder exercise and Medicare Part D didactic lectures had positive effects on students' knowledge of Part D, attitudes toward patient advocacy, and ability to accurately use the Medicare Prescription Drug Plan Finder tool. Conclusions The success of these didactic and problem-based curricular innovations in improving pharmacy students' knowledge, skills, and attitudes regarding Part D warrants further evaluation to determine their portability to clinical settings and other pharmacy schools. PMID:18698399

Processing and memory of information presented in narrative or expository texts.

PubMed

Wolfe, Michael B W; Woodwyk, Joshua M

2010-09-01

Previous research suggests that narrative and expository texts differ in the extent to which they prompt students to integrate to-be-learned content with relevant prior knowledge during comprehension. We expand on previous research by examining on-line processing and representation in memory of to-be-learned content that is embedded in narrative or expository texts. We are particularly interested in how differences in the use of relevant prior knowledge leads to differences in terms of levels of discourse representation (textbase vs. situation model). A total of 61 university undergraduates in Expt 1, and 160 in Expt 2. In Expt 1, subjects thought out loud while comprehending circulatory system content embedded in a narrative or expository text, followed by free recall of text content. In Expt 2, subjects read silently and completed a sentence recognition task to assess memory. In Expt 1, subjects made more associations to prior knowledge while reading the expository text, and recalled more content. Content recall was also correlated with amount of relevant prior knowledge for subjects who read the expository text but not the narrative text. In Expt 2, subjects reading the expository text (compared to the narrative text) had a weaker textbase representation of the to-be-learned content, but a marginally stronger situation model. Results suggest that in terms of to-be-learned content, expository texts trigger students to utilize relevant prior knowledge more than narrative texts.

Structured feedback on students' concept maps: the proverbial path to learning?

PubMed

Joseph, Conran; Conradsson, David; Nilsson Wikmar, Lena; Rowe, Michael

2017-05-25

Good conceptual knowledge is an essential requirement for health professions students, in that they are required to apply concepts learned in the classroom to a variety of different contexts. However, the use of traditional methods of assessment limits the educator's ability to correct students' conceptual knowledge prior to altering the educational context. Concept mapping (CM) is an educational tool for evaluating conceptual knowledge, but little is known about its use in facilitating the development of richer knowledge frameworks. In addition, structured feedback has the potential to develop good conceptual knowledge. The purpose of this study was to use Kinchin's criteria to assess the impact of structured feedback on the graphical complexity of CM's by observing the development of richer knowledge frameworks. Fifty-eight physiotherapy students created CM's targeting the integration of two knowledge domains within a case-based teaching paradigm. Each student received one round of structured feedback that addressed correction, reinforcement, forensic diagnosis, benchmarking, and longitudinal development on their CM's prior to the final submission. The concept maps were categorized according to Kinchin's criteria as either Spoke, Chain or Net representations, and then evaluated against defined traits of meaningful learning. The inter-rater reliability of categorizing CM's was good. Pre-feedback CM's were predominantly Chain structures (57%), with Net structures appearing least often. There was a significant reduction of the basic Spoke- structured CMs (P = 0.002) and a significant increase of Net-structured maps (P < 0.001) at the final evaluation (post-feedback). Changes in structural complexity of CMs appeared to be indicative of broader knowledge frameworks as assessed against the meaningful learning traits. Feedback on CM's seemed to have contributed towards improving conceptual knowledge and correcting naive conceptions of related knowledge. Educators in medical education could therefore consider using CM's to target individual student development.

Language knowledge and event knowledge in language use

PubMed Central

Willits, Jon A.; Amato, Michael S.; MacDonald, Maryellen C.

2018-01-01

This paper examines how semantic knowledge is used in language comprehension and in making judgments about events in the world. We contrast knowledge gleaned from prior language experience (“language knowledge”) and knowledge coming from prior experience with the world (“world knowledge”). In two corpus analyses, we show that previous research linking verb aspect and event representations have confounded language and world knowledge. Then, using carefully chosen stimuli that remove this confound, we performed four experiments that manipulated the degree to which language knowledge or world knowledge should be salient and relevant to performing a task, finding in each case that participants use the type of knowledge most appropriate to the task. These results provide evidence for a highly context-sensitive and interactionist perspective on how semantic knowledge is represented and used during language processing. PMID:25791750

Graph cuts with invariant object-interaction priors: application to intervertebral disc segmentation.

PubMed

Ben Ayed, Ismail; Punithakumar, Kumaradevan; Garvin, Gregory; Romano, Walter; Li, Shuo

2011-01-01

This study investigates novel object-interaction priors for graph cut image segmentation with application to intervertebral disc delineation in magnetic resonance (MR) lumbar spine images. The algorithm optimizes an original cost function which constrains the solution with learned prior knowledge about the geometric interactions between different objects in the image. Based on a global measure of similarity between distributions, the proposed priors are intrinsically invariant with respect to translation and rotation. We further introduce a scale variable from which we derive an original fixed-point equation (FPE), thereby achieving scale-invariance with only few fast computations. The proposed priors relax the need of costly pose estimation (or registration) procedures and large training sets (we used a single subject for training), and can tolerate shape deformations, unlike template-based priors. Our formulation leads to an NP-hard problem which does not afford a form directly amenable to graph cut optimization. We proceeded to a relaxation of the problem via an auxiliary function, thereby obtaining a nearly real-time solution with few graph cuts. Quantitative evaluations over 60 intervertebral discs acquired from 10 subjects demonstrated that the proposed algorithm yields a high correlation with independent manual segmentations by an expert. We further demonstrate experimentally the invariance of the proposed geometric attributes. This supports the fact that a single subject is sufficient for training our algorithm, and confirms the relevance of the proposed priors to disc segmentation.

Learning stoichiometry: A comparison of text and multimedia instructional formats

NASA Astrophysics Data System (ADS)

Evans, Karen L.

Even after multiple instructional opportunities, first year college chemistry students are often unable to apply stoichiometry knowledge in equilibrium and acid-base chemistry problem solving. Cognitive research findings suggest that for learning to be meaningful, learners need to actively construct their own knowledge by integrating new information into, and reorganizing, their prior understandings. Scaffolded inquiry in which facts, procedures, and principles are introduced as needed within the context of authentic problem solving may provide the practice and encoding opportunities necessary for construction of a memorable and usable knowledge base. The dynamic and interactive capabilities of online technology may facilitate stoichiometry instruction that promotes this meaningful learning. Entering college freshmen were randomly assigned to either a technology-rich or text-only set of cognitively informed stoichiometry review materials. Analysis of posttest scores revealed a significant but small difference in the performance of the two treatment groups, with the technology-rich group having the advantage. Both SAT and gender, however, explained more of the variability in the scores. Analysis of the posttest scores from the technology-rich treatment group revealed that the degree of interaction with the Virtual Lab simulation was significantly related to posttest performance and subsumed any effect of prior knowledge as measured by SAT scores. Future users of the online course should be encouraged to engage with the problem-solving opportunities provided by the Virtual Lab simulation through either explicit instruction and/or implementation of some level of program control within the course's navigational features.

Simulation-Based Dysphagia Training: Teaching Interprofessional Clinical Reasoning in a Hospital Environment.

PubMed

Miles, Anna; Friary, Philippa; Jackson, Bianca; Sekula, Julia; Braakhuis, Andrea

2016-06-01

This study evaluated hospital readiness and interprofessional clinical reasoning in speech-language pathology and dietetics students following a simulation-based teaching package. Thirty-one students participated in two half-day simulation workshops. The training included orientation to the hospital setting, part-task skill learning and immersive simulated cases. Students completed workshop evaluation forms. They filled in a 10-question survey regarding confidence, knowledge and preparedness for working in a hospital environment before and immediately after the workshops. Students completed written 15-min clinical vignettes at 1 month prior to training, immediately prior to training and immediately after training. A marking rubric was devised to evaluate the responses to the clinical vignettes within a framework of interprofessional education. The simulation workshops were well received by all students. There was a significant increase in students' self-ratings of confidence, preparedness and knowledge following the study day (p < .001). There was a significant increase in student overall scores in clinical vignettes after training with the greatest increase in clinical reasoning (p < .001). Interprofessional simulation-based training has benefits in developing hospital readiness and clinical reasoning in allied health students.

78 FR 29071 - Assessment of Mediation and Arbitration Procedures

Federal Register 2010, 2011, 2012, 2013, 2014

2013-05-17

... proceeding. Program participants in the new arbitration program will have prior knowledge of the issues to be... final rules, all parties opting into the arbitration program will have full prior knowledge that these... including discovery, the submission of evidence, and the treatment of confidential information, and the...

Teaching Practice: A Perspective on Inter-Text and Prior Knowledge

ERIC Educational Resources Information Center

Costley, Kevin C.; West, Howard G.

2012-01-01

The use of teaching practices that involve intertextual relationship discovery in today's elementary classrooms is increasingly essential to the success of young learners of reading. Teachers must constantly strive to expand their perspective of how to incorporate the dialogue included in prior knowledge assessment. Teachers must also consider how…

Elaborative-Interrogation and Prior-Knowledge Effects on Learning of Facts.

ERIC Educational Resources Information Center

Woloshyn, Vera E.; And Others

1992-01-01

The differences among elaborative-interrogation, reading-to-understand, and no-exposure control conditions with familiar domain material in contrast to unfamiliar domain material were studied for 50 Canadian and 50 west German undergraduates. Results provide evidence of effects of both elaborative interrogation and prior knowledge on learning.…

Effects of Example Variability and Prior Knowledge in How Students Learn to Solve Equations

ERIC Educational Resources Information Center

Guo, Jian-Peng; Yang, Ling-Yan; Ding, Yi

2014-01-01

Researchers have consistently demonstrated that multiple examples are better than one example in facilitating learning because the comparison evoked by multiple examples supports learning and transfer. However, research outcomes are unclear regarding the effects of example variability and prior knowledge on learning from comparing multiple…

Relationship of Students' Prior Knowledge and Order of Questions on Tests to Students' Test Scores.

ERIC Educational Resources Information Center

Papp, Klara K.; And Others

1987-01-01

A study examined whether students beginning a cell biology course with prior knowledge of its three areas (genetics, histology, and biochemistry) would retain that advantage throughout the course and whether achievement was influenced by the order of questions in a test. (MSE)

The Impact of Prior Programming Knowledge on Lecture Attendance and Final Exam

ERIC Educational Resources Information Center

Veerasamy, Ashok Kumar; D'Souza, Daryl; Lindén, Rolf; Laakso, Mikko-Jussi

2018-01-01

In this article, we report the results of the impact of prior programming knowledge (PPK) on lecture attendance (LA) and on subsequent final programming exam performance in a university level introductory programming course. This study used Spearman's rank correlation coefficient, multiple regression, Kruskal-Wallis, and Bonferroni correction…

Composing Knowledge: Writing, Rhetoric, and Reflection in Prior Learning Assessment

ERIC Educational Resources Information Center

Leaker, Cathy; Ostman, Heather

2010-01-01

In this article, we argue that prior learning assessment (PLA) essays manifest a series of issues central to composition research and practice: they foreground the "contact zone" between the unauthorized writer, institutional power, and the articulation of knowledge claims; they reinforce the central role of a multifaceted approach to…

Using Analogies to Facilitate Conceptual Change in Mathematics Learning

ERIC Educational Resources Information Center

Vamvakoussi, Xenia

2017-01-01

The problem of adverse effects of prior knowledge in mathematics learning has been amply documented and theorized by mathematics educators as well as cognitive/developmental psychologists. This problem emerges when students' prior knowledge about a mathematical notion comes in contrast with new information coming from instruction, giving rise to…

Specific Previous Experience Affects Perception of Harmony and Meter

ERIC Educational Resources Information Center

Creel, Sarah C.

2011-01-01

Prior knowledge shapes our experiences, but which prior knowledge shapes which experiences? This question is addressed in the domain of music perception. Three experiments were used to determine whether listeners activate specific musical memories during music listening. Each experiment provided listeners with one of two musical contexts that was…

Pre-Test Assessment

ERIC Educational Resources Information Center

Berry, Thomas

2008-01-01

Pre-tests are a non-graded assessment tool used to determine pre-existing subject knowledge. Typically pre-tests are administered prior to a course to determine knowledge baseline, but here they are used to test students prior to topical material coverage throughout the course. While counterintuitive, the pre-tests cover material the student is…

Translating three states of knowledge--discovery, invention, and innovation

PubMed Central

2010-01-01

Background Knowledge Translation (KT) has historically focused on the proper use of knowledge in healthcare delivery. A knowledge base has been created through empirical research and resides in scholarly literature. Some knowledge is amenable to direct application by stakeholders who are engaged during or after the research process, as shown by the Knowledge to Action (KTA) model. Other knowledge requires multiple transformations before achieving utility for end users. For example, conceptual knowledge generated through science or engineering may become embodied as a technology-based invention through development methods. The invention may then be integrated within an innovative device or service through production methods. To what extent is KT relevant to these transformations? How might the KTA model accommodate these additional development and production activities while preserving the KT concepts? Discussion Stakeholders adopt and use knowledge that has perceived utility, such as a solution to a problem. Achieving a technology-based solution involves three methods that generate knowledge in three states, analogous to the three classic states of matter. Research activity generates discoveries that are intangible and highly malleable like a gas; development activity transforms discoveries into inventions that are moderately tangible yet still malleable like a liquid; and production activity transforms inventions into innovations that are tangible and immutable like a solid. The paper demonstrates how the KTA model can accommodate all three types of activity and address all three states of knowledge. Linking the three activities in one model also illustrates the importance of engaging the relevant stakeholders prior to initiating any knowledge-related activities. Summary Science and engineering focused on technology-based devices or services change the state of knowledge through three successive activities. Achieving knowledge implementation requires methods that accommodate these three activities and knowledge states. Accomplishing beneficial societal impacts from technology-based knowledge involves the successful progression through all three activities, and the effective communication of each successive knowledge state to the relevant stakeholders. The KTA model appears suitable for structuring and linking these processes. PMID:20205873

A trial of a reproductive ethics and law curriculum for obstetrics and gynaecology residents.

PubMed

Arora, Kavita Shah

2014-12-01

Prior ethics educational interventions for residents have shown improvement in confidence and knowledge scores strictly in an internal medical resident population. Baseline knowledge and attitudes regarding reproductive ethics and law of obstetrics and gynaecology (ob/gyn) residents were assessed via a survey. Then, after completion of a 20-h curriculum for the residents, the residents were resurveyed in order to assess impact of the curriculum. An online survey with both multiple-choice and open-ended questions was administered to residents both prior to and after curriculum completion. A total of 39 residents (85% of the total ob/gyn residents) completed the survey. 67% of respondents thought ethics was very important in clinical practice, but only 3% considered themselves very familiar with medical ethics. Respondents were asked five case-based questions to assess baseline knowledge and only 10% answered all questions correctly prior to the curriculum. After the residents completed the curriculum, 31 subjects (79% of the original 39 resident respondents) responded to the same survey. 52% of respondents answered all five questions correctly and 31% considered themselves very familiar with medical ethics. Despite the importance placed on reproductive ethics and law by survey respondents including its impact on their clinical practices, there continues to be a deficiency in formal ethics education in ob/gyn. Our curriculum demonstrated both improvement in confidence as well as knowledge of residents towards issues of reproductive ethics and law. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Faded-example as a Tool to Acquire and Automate Mathematics Knowledge

NASA Astrophysics Data System (ADS)

Retnowati, E.

2017-04-01

Students themselves accomplish Knowledge acquisition and automation. The teacher plays a role as the facilitator by creating mathematics tasks that assist students in building knowledge efficiently and effectively. Cognitive load caused by learning material presented by teachers should be considered as a critical factor. While the intrinsic cognitive load is related to the degree of complexity of the material learning ones can handle, the extraneous cognitive load is directly caused by how the material is presented. Strategies to present a learning material in computational learning domains like mathematics are a namely worked example (fully-guided task) or problem-solving (discovery task with no guidance). According to the empirical evidence, learning based on problem-solving may cause high-extraneous cognitive load for students who have limited prior knowledge, conversely learn based on worked example may cause high-extraneous cognitive load for students who have mastered the knowledge base. An alternative is a faded example consisting of the partly-completed task. Learning from faded-example can facilitate students who already acquire some knowledge about the to-be-learned material but still need more practice to automate the knowledge further. This instructional strategy provides a smooth transition from a fully-guided into an independent problem solver. Designs of faded examples for learning trigonometry are discussed.

Transient medial prefrontal perturbation reduces false memory formation.

PubMed

Berkers, Ruud M W J; van der Linden, Marieke; de Almeida, Rafael F; Müller, Nils C J; Bovy, Leonore; Dresler, Martin; Morris, Richard G M; Fernández, Guillén

2017-03-01

Knowledge extracted across previous experiences, or schemas, benefit encoding and retention of congruent information. However, they can also reduce specificity and augment memory for semantically related, but false information. A demonstration of the latter is given by the Deese-Roediger-McDermott (DRM) paradigm, where the studying of words that fit a common semantic schema are found to induce false memories for words that are congruent with the given schema, but were not studied. The medial prefrontal cortex (mPFC) has been ascribed the function of leveraging prior knowledge to influence encoding and retrieval, based on imaging and patient studies. Here, we used transcranial magnetic stimulation (TMS) to transiently perturb ongoing mPFC processing immediately before participants performed the DRM-task. We observed the predicted reduction in false recall of critical lures after mPFC perturbation, compared to two control groups, whereas veridical recall and recognition memory performance remained similar across groups. These data provide initial causal evidence for a role of the mPFC in biasing the assimilation of new memories and their consolidation as a function of prior knowledge. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Interpretation of a Knowledge Claim in the Recognition of Prior Learning (RPL) and the Impact of This on RPL Practice

ERIC Educational Resources Information Center

de Graaff, Frederika

2014-01-01

The question addressed in this paper is: what does a knowledge claim consist of in the context of the Recognition of Prior Learning (RPL)? The research comprises a case study of RPL applicants' entry into a postgraduate diploma (a fourth-year programme) in project management. The focus is on the knowledge claims made as part of the RPL application…

Age differences in suggestibility to contradictions of demonstrated knowledge: the influence of prior knowledge.

PubMed

Umanath, Sharda

2016-11-01

People maintain intact general knowledge into very old age and use it to support remembering. Interestingly, when older and younger adults encounter errors that contradict general knowledge, older adults suffer fewer memorial consequences: Older adults use fewer recently-encountered errors as answers for later knowledge questions. Why do older adults show this reduced suggestibility, and what role does their intact knowledge play? In three experiments, I examined suggestibility following exposure to errors in fictional stories that contradict general knowledge. Older adults consistently demonstrated more prior knowledge than younger adults but also gained access to even more across time. Additionally, they did not show a reduction in new learning from the stories, indicating lesser involvement of episodic memory failures. Critically, when knowledge was stably accessible, older adults relied more heavily on that knowledge compared to younger adults, resulting in reduced suggestibility. Implications for the broader role of knowledge in aging are discussed.

Bias-dependent hybrid PKI empirical-neural model of microwave FETs

NASA Astrophysics Data System (ADS)

Marinković, Zlatica; Pronić-Rančić, Olivera; Marković, Vera

2011-10-01

Empirical models of microwave transistors based on an equivalent circuit are valid for only one bias point. Bias-dependent analysis requires repeated extractions of the model parameters for each bias point. In order to make model bias-dependent, a new hybrid empirical-neural model of microwave field-effect transistors is proposed in this article. The model is a combination of an equivalent circuit model including noise developed for one bias point and two prior knowledge input artificial neural networks (PKI ANNs) aimed at introducing bias dependency of scattering (S) and noise parameters, respectively. The prior knowledge of the proposed ANNs involves the values of the S- and noise parameters obtained by the empirical model. The proposed hybrid model is valid in the whole range of bias conditions. Moreover, the proposed model provides better accuracy than the empirical model, which is illustrated by an appropriate modelling example of a pseudomorphic high-electron mobility transistor device.

Supporting Multimedia Learning with Visual Signalling and Animated Pedagogical Agent: Moderating Effects of Prior Knowledge

ERIC Educational Resources Information Center

Johnson, A. M.; Ozogul, G.; Reisslein, M.

2015-01-01

An experiment examined the effects of visual signalling to relevant information in multiple external representations and the visual presence of an animated pedagogical agent (APA). Students learned electric circuit analysis using a computer-based learning environment that included Cartesian graphs, equations and electric circuit diagrams. The…

The Journey from Rhetoric to Reality: Participatory Evaluation in a Development Context

ERIC Educational Resources Information Center

Chouinard, Jill Anne; Cousins, J. Bradley

2015-01-01

In this paper, we focus on participatory evaluation in the context of international development and specifically on the emerging empirical knowledge base. In a prior review and critique of research on participatory evaluation (Cousins and Chouinard 2012), we examined 121 studies, with only 21 (17%) situated in development contexts. However, the…

English Perceptive Teaching of Middle School in China--Based on an Empirical Study

ERIC Educational Resources Information Center

Lifen, He; Junying, Yong

2016-01-01

Perception is the reconstruction and interaction between the new information and prior knowledge in mind or in the process of internalization about the new information. It has three teaching procedures: First, teachers elicit the learners to acquire text meaning. Second, teachers create situation in practical teaching. Third, learners comprehend…

An Experiment in Teaching Invention

ERIC Educational Resources Information Center

Clark, Andre

2009-01-01

Purpose: The purpose of this paper is to demonstrate that invention can be taught to business students who do not have the prior technical knowledge that is assumed to be a requirement for this kind of activity. Design/methodology/approach: This paper contains reflections on the results of introducing a specific course in inventing based on the…

Towards Individualized Online Learning: The Design and Development of an Adaptive Web Based Learning Environment

ERIC Educational Resources Information Center

Inan, Fethi A.; Flores, Raymond; Ari, Fatih; Arslan-Ari, Ismahan

2011-01-01

The purpose of this study was to document the design and development of an adaptive system which individualizes instruction such as content, interfaces, instructional strategies, and resources dependent on two factors, namely student motivation and prior knowledge levels. Combining adaptive hypermedia methods with strategies proposed by…

Explicit Constructivism: A Missing Link in Ineffective Lectures?

ERIC Educational Resources Information Center

Prakash, E. S.

2010-01-01

This study tested the possibility that interactive lectures explicitly based on activating learners' prior knowledge and driven by a series of logical questions might enhance the effectiveness of lectures. A class of 54 students doing the respiratory system course in the second year of the Bachelor of Medicine and Bachelor of Surgery program in my…

Comparing Societies from the 1500s in the Sixth Grade

ERIC Educational Resources Information Center

Matson, Trista; Henning, Mary Beth

2008-01-01

Inquiry is the process by which teachers give students an open-ended question, and then students investigate the evidence and draw conclusions based upon their findings. This method promotes critical thinking, as students cite evidence to support their opinions. Inquiry is most effective when it builds upon students' prior knowledge. To promote…

Explication: Working to Discover and Share New Knowledge from Prior Experience

ERIC Educational Resources Information Center

Franklin, Peter

2007-01-01

Purpose: The purpose of this paper is to develop the sustained argument that explication can contribute to the emergence and development of the philosopher-manager who is appropriately sceptical of generalisations, and confident in their own abilities to develop local, valid and meaningful theories based on their wisdom and personal experience.…

Why Children Are Left Behind and What We Can Do about It.

ERIC Educational Resources Information Center

Reigeluth, Charles M.; Beatty, Brian J.

2003-01-01

Proposes four main reasons that children are left behind in schools: unmet needs, lack of motivation, lack of foundation and prior knowledge, and lack of support for learning. Discusses Maslow's hierarch of needs; partnerships with parents; connecting to student interests; insisting on mastery; curriculum sequencing; brain-based research; and…

A New Self-Assessment Teaching Assistant Survey for Growth and Development

ERIC Educational Resources Information Center

Mewis, Keith; Dee, Jaclyn; Lam, Vivienne; Obradovich, Shannon; Cassidy, Alice

2018-01-01

During their time as Teaching Assistants (TAs), graduate students develop a variety of skills, knowledge, and attitudes (SKAs) based on teaching and related facilitation experiences. As TAs move on to future opportunities, their prior experiences form a foundation upon which additional teaching experience builds. Presently, there are few tools to…

An Analysis of Looking Back Method in Problem-Based Learning: Case Study on Congruence and Similarity in Junior High School

NASA Astrophysics Data System (ADS)

Kosasih, U.; Wahyudin, W.; Prabawanto, S.

2017-09-01

This study aims to understand how learners do look back their idea of problem solving. This research is based on qualitative approach with case study design. Participants in this study were xx students of Junior High School, who were studying the material of congruence and similarity. The supporting instruments in this research are test and interview sheet. The data obtained were analyzed by coding and constant-comparison. The analysis find that there are three ways in which the students review the idea of problem solving, which is 1) carried out by comparing answers to the completion measures exemplified by learning resources; 2) carried out by examining the logical relationship between the solution and the problem; and 3) carried out by means of confirmation to the prior knowledge they have. This happens because most students learn in a mechanistic way. This study concludes that students validate the idea of problem solving obtained, influenced by teacher explanations, learning resources, and prior knowledge. Therefore, teacher explanations and learning resources contribute to the success or failure of students in solving problems.

Network reconstruction based on proteomic data and prior knowledge of protein connectivity using graph theory.

PubMed

Stavrakas, Vassilis; Melas, Ioannis N; Sakellaropoulos, Theodore; Alexopoulos, Leonidas G

2015-01-01

Modeling of signal transduction pathways is instrumental for understanding cells' function. People have been tackling modeling of signaling pathways in order to accurately represent the signaling events inside cells' biochemical microenvironment in a way meaningful for scientists in a biological field. In this article, we propose a method to interrogate such pathways in order to produce cell-specific signaling models. We integrate available prior knowledge of protein connectivity, in a form of a Prior Knowledge Network (PKN) with phosphoproteomic data to construct predictive models of the protein connectivity of the interrogated cell type. Several computational methodologies focusing on pathways' logic modeling using optimization formulations or machine learning algorithms have been published on this front over the past few years. Here, we introduce a light and fast approach that uses a breadth-first traversal of the graph to identify the shortest pathways and score proteins in the PKN, fitting the dependencies extracted from the experimental design. The pathways are then combined through a heuristic formulation to produce a final topology handling inconsistencies between the PKN and the experimental scenarios. Our results show that the algorithm we developed is efficient and accurate for the construction of medium and large scale signaling networks. We demonstrate the applicability of the proposed approach by interrogating a manually curated interaction graph model of EGF/TNFA stimulation against made up experimental data. To avoid the possibility of erroneous predictions, we performed a cross-validation analysis. Finally, we validate that the introduced approach generates predictive topologies, comparable to the ILP formulation. Overall, an efficient approach based on graph theory is presented herein to interrogate protein-protein interaction networks and to provide meaningful biological insights.

Unmanned Carrier-Based Aircraft System: Debate over Systems Role Led to Focus on Aerial Refueling

DTIC Science & Technology

2016-03-24

Unmanned Carrier-Based Aircraft System: Debate over System’s Role Led to Focus on Aerial Refueling Prior to February 2016, the Navy had planned to...award of the air system development contract by about 3 years from 2014 to 2017. In that report, we also found that knowledge the Navy had obtained...strike 1Pub. L. No. 113-66, § 213(d) (2013). 2GAO, Unmanned Carrier-Based Aircraft System: Navy Needs

The impacts of data constraints on the predictive performance of a general process-based crop model (PeakN-crop v1.0)

NASA Astrophysics Data System (ADS)

Caldararu, Silvia; Purves, Drew W.; Smith, Matthew J.

2017-04-01

Improving international food security under a changing climate and increasing human population will be greatly aided by improving our ability to modify, understand and predict crop growth. What we predominantly have at our disposal are either process-based models of crop physiology or statistical analyses of yield datasets, both of which suffer from various sources of error. In this paper, we present a generic process-based crop model (PeakN-crop v1.0) which we parametrise using a Bayesian model-fitting algorithm to three different sources: data-space-based vegetation indices, eddy covariance productivity measurements and regional crop yields. We show that the model parametrised without data, based on prior knowledge of the parameters, can largely capture the observed behaviour but the data-constrained model greatly improves both the model fit and reduces prediction uncertainty. We investigate the extent to which each dataset contributes to the model performance and show that while all data improve on the prior model fit, the satellite-based data and crop yield estimates are particularly important for reducing model error and uncertainty. Despite these improvements, we conclude that there are still significant knowledge gaps, in terms of available data for model parametrisation, but our study can help indicate the necessary data collection to improve our predictions of crop yields and crop responses to environmental changes.

Explaining between-race differences in African-American and European-American women's responses to breast density notification.

PubMed

Manning, Mark; Albrecht, Terrance L; Yilmaz-Saab, Zeynep; Penner, Louis; Norman, Andria; Purrington, Kristen

2017-12-01

Prior research shows between-race differences in women's knowledge and emotions related to having dense breasts, thus suggesting that between-race differences in behavioral decision-making following receipt of breast density (BD) notifications are likely. Guided by the theory of planned behavior, this study examined differences in emotion-related responses (i.e., anxiety, worry, confusion) and behavioral cognition (e.g., intentions, behavioral attitudes) following receipt of BD notifications among African American (AA) and European American (EA) women. This study also examined whether race-related perceptions (i.e., discrimination, group-based medical mistrust), relevant knowledge and socioeconomic status (SES) explained the between race differences. Michigan women (N = 457) who presented for routine screening mammogram and had dense breasts, no prior breast cancer diagnoses, and had screen-negative mammograms were recruited from July, 2015 to March 2016. MANOVA was used to examine between race differences in psychological responses (i.e., emotional responses and behavioral cognition), and a multi-group structural regression model was used to examine whether race-related constructs, knowledge and SES mediated the effect of race on emotional responses and behavioral cognition. Prior awareness of BD was accounted for in all analyses. AA women generally reported more negative psychological responses to receiving BD notifications regardless of prior BD awareness. AA women had more favorable perceptions related to talking to their physicians about the BD notifications. Generally, race-related perceptions, SES, and related knowledge partially accounted for the effect of race on psychological response. Race-related perceptions and SES partially accounted for the differences in behavioral intentions. Between-race differences in emotional responses to BD notifications did not explain differences in women's intentions to discuss BD notifications with their physicians. Future examinations are warranted to examine whether there are between-race differences in actual post-BD notification behaviors and whether similar race-related variables account for differences. Copyright © 2017. Published by Elsevier Ltd.

Effects of an Augmented Reality-Based Educational Game on Students' Learning Achievements and Attitudes in Real-World Observations

ERIC Educational Resources Information Center

Hwang, Gwo-Jen; Wu, Po-Han; Chen, Chi-Chang; Tu, Nien-Ting

2016-01-01

Augmented reality (AR) has been recognized as a potential technology to help students link what they are observing in the real world to their prior knowledge. One of the most challenging issues of AR-based learning is the provision of effective strategy to help students focus on what they need to observe in the field. In this study, a competitive…

Toward a dose reduction strategy using model-based reconstruction with limited-angle tomosynthesis

NASA Astrophysics Data System (ADS)

Haneda, Eri; Tkaczyk, J. E.; Palma, Giovanni; Iordache, Rǎzvan; Zelakiewicz, Scott; Muller, Serge; De Man, Bruno

2014-03-01

Model-based iterative reconstruction (MBIR) is an emerging technique for several imaging modalities and appli- cations including medical CT, security CT, PET, and microscopy. Its success derives from an ability to preserve image resolution and perceived diagnostic quality under impressively reduced signal level. MBIR typically uses a cost optimization framework that models system geometry, photon statistics, and prior knowledge of the recon- structed volume. The challenge of tomosynthetic geometries is that the inverse problem becomes more ill-posed due to the limited angles, meaning the volumetric image solution is not uniquely determined by the incom- pletely sampled projection data. Furthermore, low signal level conditions introduce additional challenges due to noise. A fundamental strength of MBIR for limited-views and limited-angle is that it provides a framework for constraining the solution consistent with prior knowledge of expected image characteristics. In this study, we analyze through simulation the capability of MBIR with respect to prior modeling components for limited-views, limited-angle digital breast tomosynthesis (DBT) under low dose conditions. A comparison to ground truth phantoms shows that MBIR with regularization achieves a higher level of fidelity and lower level of blurring and streaking artifacts compared to other state of the art iterative reconstructions, especially for high contrast objects. The benefit of contrast preservation along with less artifacts may lead to detectability improvement of microcalcification for more accurate cancer diagnosis.

Ambulatory Morning Report: A Case-Based Method of Teaching EBM Through Experiential Learning.

PubMed

Luciano, Gina L; Visintainer, Paul F; Kleppel, Reva; Rothberg, Michael B

2016-02-01

Evidence-based medicine (EBM) skills are important to daily practice, but residents generally feel unskilled incorporating EBM into practice. The Kolb experiential learning theory, as applied to curricular planning, offers a unique methodology to help learners build an EBM skill set based on clinical experiences. We sought to blend the learner-centered, case-based merits of the morning report with an experientially based EBM curriculum. We describe and evaluate a patient-centered ambulatory morning report combining the User's Guides to the Medical Literature approach to EBM and experiential learning theory in the internal medicine department at Baystate Medical Center. The Kolb experiential learning theory postulates that experience transforms knowledge; within that premise we designed a curriculum to build EBM skills incorporating residents' patient encounters. By developing structured clinical questions based on recent clinical problems, residents activate prior knowledge. Residents acquire new knowledge through selection and evaluation of an article that addresses the structured clinical questions. Residents then apply and use new knowledge in future patient encounters. To assess the curriculum, we designed an 18-question EBM test, which addressed applied knowledge and EBM skills based on the User's Guides approach. Of the 66 residents who could participate in the curriculum, 61 (92%) completed the test. There was a modest improvement in EBM knowledge, primarily during the first year of training. Our experiential curriculum teaches EBM skills essential to clinical practice. The curriculum differs from traditional EBM curricula in that ours blends experiential learning with an EBM skill set; learners use new knowledge in real time.

Enrichment assessment of multiple virtual screening strategies for Toll-like receptor 8 agonists based on a maximal unbiased benchmarking data set.

PubMed

Pei, Fen; Jin, Hongwei; Zhou, Xin; Xia, Jie; Sun, Lidan; Liu, Zhenming; Zhang, Liangren

2015-11-01

Toll-like receptor 8 agonists, which activate adaptive immune responses by inducing robust production of T-helper 1-polarizing cytokines, are promising candidates for vaccine adjuvants. As the binding site of toll-like receptor 8 is large and highly flexible, virtual screening by individual method has inevitable limitations; thus, a comprehensive comparison of different methods may provide insights into seeking effective strategy for the discovery of novel toll-like receptor 8 agonists. In this study, the performance of knowledge-based pharmacophore, shape-based 3D screening, and combined strategies was assessed against a maximum unbiased benchmarking data set containing 13 actives and 1302 decoys specialized for toll-like receptor 8 agonists. Prior structure-activity relationship knowledge was involved in knowledge-based pharmacophore generation, and a set of antagonists was innovatively used to verify the selectivity of the selected knowledge-based pharmacophore. The benchmarking data set was generated from our recently developed 'mubd-decoymaker' protocol. The enrichment assessment demonstrated a considerable performance through our selected three-layer virtual screening strategy: knowledge-based pharmacophore (Phar1) screening, shape-based 3D similarity search (Q4_combo), and then a Gold docking screening. This virtual screening strategy could be further employed to perform large-scale database screening and to discover novel toll-like receptor 8 agonists. © 2015 John Wiley & Sons A/S.

MRAC Control with Prior Model Knowledge for Asymmetric Damaged Aircraft

PubMed Central

Zhang, Jing

2015-01-01

This paper develops a novel state-tracking multivariable model reference adaptive control (MRAC) technique utilizing prior knowledge of plant models to recover control performance of an asymmetric structural damaged aircraft. A modification of linear model representation is given. With prior knowledge on structural damage, a polytope linear parameter varying (LPV) model is derived to cover all concerned damage conditions. An MRAC method is developed for the polytope model, of which the stability and asymptotic error convergence are theoretically proved. The proposed technique reduces the number of parameters to be adapted and thus decreases computational cost and requires less input information. The method is validated by simulations on NASA generic transport model (GTM) with damage. PMID:26180839

WE-E-BRE-05: Ensemble of Graphical Models for Predicting Radiation Pneumontis Risk

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

Lee, S; Ybarra, N; Jeyaseelan, K

Purpose: We propose a prior knowledge-based approach to construct an interaction graph of biological and dosimetric radiation pneumontis (RP) covariates for the purpose of developing a RP risk classifier. Methods: We recruited 59 NSCLC patients who received curative radiotherapy with minimum 6 month follow-up. 16 RP events was observed (CTCAE grade ≥2). Blood serum was collected from every patient before (pre-RT) and during RT (mid-RT). From each sample the concentration of the following five candidate biomarkers were taken as covariates: alpha-2-macroglobulin (α2M), angiotensin converting enzyme (ACE), transforming growth factor β (TGF-β), interleukin-6 (IL-6), and osteopontin (OPN). Dose-volumetric parameters were alsomore » included as covariates. The number of biological and dosimetric covariates was reduced by a variable selection scheme implemented by L1-regularized logistic regression (LASSO). Posterior probability distribution of interaction graphs between the selected variables was estimated from the data under the literature-based prior knowledge to weight more heavily the graphs that contain the expected associations. A graph ensemble was formed by averaging the most probable graphs weighted by their posterior, creating a Bayesian Network (BN)-based RP risk classifier. Results: The LASSO selected the following 7 RP covariates: (1) pre-RT concentration level of α2M, (2) α2M level mid- RT/pre-RT, (3) pre-RT IL6 level, (4) IL6 level mid-RT/pre-RT, (5) ACE mid-RT/pre-RT, (6) PTV volume, and (7) mean lung dose (MLD). The ensemble BN model achieved the maximum sensitivity/specificity of 81%/84% and outperformed univariate dosimetric predictors as shown by larger AUC values (0.78∼0.81) compared with MLD (0.61), V20 (0.65) and V30 (0.70). The ensembles obtained by incorporating the prior knowledge improved classification performance for the ensemble size 5∼50. Conclusion: We demonstrated a probabilistic ensemble method to detect robust associations between RP covariates and its potential to improve RP prediction accuracy. Our Bayesian approach to incorporate prior knowledge can enhance efficiency in searching of such associations from data. The authors acknowledge partial support by: 1) CREATE Medical Physics Research Training Network grant of the Natural Sciences and Engineering Research Council (Grant number: 432290) and 2) The Terry Fox Foundation Strategic Training Initiative for Excellence in Radiation Research for the 21st Century (EIRR21)« less

Use of knowledge-sharing web-based portal in gross and microscopic anatomy.

PubMed

Durosaro, Olayemi; Lachman, Nirusha; Pawlina, Wojciech

2008-12-01

Changes in worldwide healthcare delivery require review of current medical school curricula structure to develop learning outcomes that ensures mastery of knowledge and clinical competency. In the last 3 years, Mayo Medical School implemented outcomes-based curriculum to encompass new graduate outcomes. Standard courses were replaced by 6-week clinically-integrated didactic blocks separated by student-self selected academic enrichment activities. Gross and microscopic anatomy was integrated with radiology and genetics respectively. Laboratory components include virtual microscopy and anatomical dissection. Students assigned to teams utilise computer portals to share learning experiences. High-resolution computed tomographic (CT) scans of cadavers prior to dissection were made available for correlative learning between the cadaveric material and radiologic images. Students work in teams on assigned presentations that include histology, cell and molecular biology, genetics and genomic using the Nexus Portal, based on DrupalEd, to share their observations, reflections and dissection findings. New generation of medical students are clearly comfortable utilising web-based programmes that maximise their learning potential of conceptually difficult and labor intensive courses. Team-based learning approach emphasising the use of knowledge-sharing computer portals maximises opportunities for students to master their knowledge and improve cognitive skills to ensure clinical competency.

Potentiation in young infants: The origin of the prior knowledge effect?

PubMed Central

Barr, Rachel; Rovee-Collier, Carolyn; Learmonth, Amy

2011-01-01

In two experiments with 6-month-old infants, we found that prior learning of an operant task (remembered for 2 weeks) mediated new learning of a modeling event (remembered for only 1 day) and increased its recall. Infants first learned to associate lever pressing with moving a toy train housed in a large box. One or 2 weeks later, three target actions were modeled on a hand puppet while the train box (a retrieval cue) was in view. Merely retrieving the train memory strengthened it, and simultaneously pairing its retrieved memory with the modeled actions potentiated their learning and recall. When paired 1 week later, deferred imitation increased from 1 day to 4 weeks; when paired 2 weeks later, it increased from 1 day to 6 weeks. The striking parallels between potentiated learning in infants and the prior knowledge effect in adults suggests that the prior knowledge effect originates in early infancy. PMID:21264602

Explicit Instructions Increase Cognitive Costs of Deception in Predictable Social Context

PubMed Central

Falkiewicz, Marcel; Sarzyńska, Justyna; Babula, Justyna; Szatkowska, Iwona; Grabowska, Anna; Nęcka, Edward

2015-01-01

Convincing participants to deceive remains one of the biggest and most important challenges of laboratory-based deception research. The simplest and most prevalent method involves explicitly instructing participants to lie or tell the truth before presenting each task item. The usual finding of such experiments is increased cognitive load associated with deceptive responses, explained by necessity to inhibit default and automatic honest responses. However, explicit instructions are usually coupled with the absence of social context in the experimental task. Context plays a key role in social cognition by activating prior knowledge, which facilitates behaviors consistent with the latter. We hypothesized that in the presence of social context, both honest and deceptive responses can be produced on the basis of prior knowledge, without reliance on truth and without additional cognitive load during deceptive responses. In order to test the hypothesis, we have developed Speed-Dating Task (SDT), which is based on a real-life social event. In SDT, participants respond both honestly and deceptively to questions in order to appear similar to each of the dates. The dates are predictable and represent well-known categories (i.e., atheist or conservative). In one condition participants rely on explicit instructions preceding each question (external cue). In the second condition no explicit instructions are present, so the participants need to adapt based on prior knowledge about the category the dates belong to (internal cue). With internal cues, reaction times (RTs) are similar for both honest and deceptive responses. However, in the presence of external cues (EC), RTs are longer for deceptive than honest responses, suggesting that deceptive responses are associated with increased cognitive load. Compared to internal cues, deception costs were higher when EC were present. However, the effect was limited to the first part of the experiment, only partially confirming our initial hypothesis. The results suggest that the presence of social context in deception tasks might have a significant influence on cognitive processes associated with deception. PMID:26696929

When Relationships Depicted Diagrammatically Conflict with Prior Knowledge: An Investigation of Students' Interpretations of Evolutionary Trees

ERIC Educational Resources Information Center

Novick, Laura R.; Catley, Kefyn M.

2014-01-01

Science is an important domain for investigating students' responses to information that contradicts their prior knowledge. In previous studies of this topic, this information was communicated verbally. The present research used diagrams, specifically trees (cladograms) depicting evolutionary relationships among taxa. Effects of college…

Building Knowledge through Portfolio Learning in Prior Learning Assessment and Recognition

ERIC Educational Resources Information Center

Conrad, Dianne

2008-01-01

It is important for academic credibility that the process of prior learning assessment and recognition (PLAR) keeps learning and knowledge as its foundational tenets. Doing so ensures PLAR's recognition as a fertile ground for learners' cognitive and personal growth. In many postsecondary venues, PLAR is often misunderstood and confused with…

Temporal Learning in 4 1/2- and 6-Year-Old Children: Role of Instructions and Prior Knowledge.

ERIC Educational Resources Information Center

Droit, Sylvie; And Others

1990-01-01

Examined the role of prior temporal knowledge of 4 1/2- and 6-year-olds through the use of high-rate, interval, and minimal instructions in a fixed-interval training schedule. Determined that the subjects' learning depended on their verbal self-control skills. (BC)

Understanding the Complexities of Prior Knowledge

ERIC Educational Resources Information Center

Soiferman, L. Karen

2014-01-01

The purpose of the study was to gain an understanding of the kinds of prior knowledge students bring with them from high school as it relates to the conventions of writing that they are expected to follow in ARTS 1110 Introduction to University. The research questions were "Can first-year students taking the Arts 1110 Introduction to…

An Effectiveness Index and Profile for Instructional Media.

ERIC Educational Resources Information Center

Bond, Jack H.

A scale was developed for judging the relative value of various media in teaching children. Posttest scores were partitioned into several components: error, prior knowledge, guessing, and gain from the learning exercise. By estimating the amounts of prior knowledge, guessing, and error, and then subtracting these from the total score, an index of…

Making Connections in Math: Activating a Prior Knowledge Analogue Matters for Learning

ERIC Educational Resources Information Center

Sidney, Pooja G.; Alibali, Martha W.

2015-01-01

This study investigated analogical transfer of conceptual structure from a prior-knowledge domain to support learning in a new domain of mathematics: division by fractions. Before a procedural lesson on division by fractions, fifth and sixth graders practiced with a surface analogue (other operations on fractions) or a structural analogue (whole…

An Investigation of the Relationships between Prior Knowledge and Vocabulary Development with Culturally Diverse Students.

ERIC Educational Resources Information Center

Karbon, Jacqueline C.

Using a semantic mapping technique for vocabulary instruction, a study explored how children of diverse groups bring different cultural backgrounds and prior knowledge to tasks involved in learning new words. The study was conducted in three sixth-grade classrooms--one containing rural Native American (especially Menominee) children, another…

The Influence of Prior Knowledge on Perception and Action: Relationships to Autistic Traits

ERIC Educational Resources Information Center

Buckingham, Gavin; Michelakakis, Elizabeth Evgenia; Rajendran, Gnanathusharan

2016-01-01

Autism is characterised by a range of perceptual and sensorimotor deficits, which might be related to abnormalities in how autistic individuals use prior knowledge. We investigated this proposition in a large non-clinical population in the context of the size-weight illusion, where individual's expectations about object weight influence their…

Interplay of Prior Knowledge, Self-Regulation and Motivation in Complex Multimedia Learning Environments

ERIC Educational Resources Information Center

Song, H. S.; Kalet, A. L.; Plass, J. L.

2016-01-01

This study examined the direct and indirect effects of medical clerkship students' prior knowledge, self-regulation and motivation on learning performance in complex multimedia learning environments. The data from 386 medical clerkship students from six medical schools were analysed using structural equation modeling. The structural model revealed…

Effects of Students' Prior Knowledge on Scientific Reasoning in Density.

ERIC Educational Resources Information Center

Yang, Il-Ho; Kwon, Yong-Ju; Kim, Young-Shin; Jang, Myoung-Duk; Jeong, Jin-Woo; Park, Kuk-Tae

2002-01-01

Investigates the effects of students' prior knowledge on the scientific reasoning processes of performing the task of controlling variables with computer simulation and identifies a number of problems that students encounter in scientific discovery. Involves (n=27) 5th grade students and (n=33) 7th grade students. Indicates that students' prior…

Relationship of Prior Knowledge and Working Engineers' Learning Preferences: Implications for Designing Effective Instruction

ERIC Educational Resources Information Center

Baukal, Charles E.; Ausburn, Lynna J.

2017-01-01

Continuing engineering education (CEE) is important to ensure engineers maintain proficiency over the life of their careers. However, relatively few studies have examined designing effective training for working engineers. Research has indicated that both learner instructional preferences and prior knowledge can impact the learning process, but it…

The Influence of Prior Knowledge and Viewing Repertoire on Learning from Video

ERIC Educational Resources Information Center

de Boer, Jelle; Kommers, Piet A. M.; de Brock, Bert; Tolboom, Jos

2016-01-01

Video is increasingly used as an instructional tool. It is therefore becoming more important to improve learning of students from video. We investigated whether student learning effects are influenced through an instruction about other viewing behaviours, and whether these learning effects depend on their prior knowledge. In a controlled…

Students' Achievement in Relation to Reasoning Ability, Prior Knowledge and Gender

ERIC Educational Resources Information Center

Yenilmez, Ayse; Sungur, Semra; Tekkaya, Ceren

2006-01-01

This study investigated students' achievement regarding photosynthesis and respiration in plants in relation to reasoning ability, prior knowledge and gender. A total of 117 eighth-grade students participated in the study. Test of logical thinking and the two-tier multiple choice tests were administered to determine students' reasoning ability and…

The Effectiveness of Using Incorrect Examples to Support Learning about Decimal Magnitude

ERIC Educational Resources Information Center

Durkin, Kelley; Rittle-Johnson, Bethany

2012-01-01

Comparing common mathematical errors to correct examples may facilitate learning, even for students with limited prior domain knowledge. We examined whether studying incorrect and correct examples was more effective than studying two correct examples across prior knowledge levels. Fourth- and fifth-grade students (N = 74) learned about decimal…

Finding gene regulatory network candidates using the gene expression knowledge base.

PubMed

Venkatesan, Aravind; Tripathi, Sushil; Sanz de Galdeano, Alejandro; Blondé, Ward; Lægreid, Astrid; Mironov, Vladimir; Kuiper, Martin

2014-12-10

Network-based approaches for the analysis of large-scale genomics data have become well established. Biological networks provide a knowledge scaffold against which the patterns and dynamics of 'omics' data can be interpreted. The background information required for the construction of such networks is often dispersed across a multitude of knowledge bases in a variety of formats. The seamless integration of this information is one of the main challenges in bioinformatics. The Semantic Web offers powerful technologies for the assembly of integrated knowledge bases that are computationally comprehensible, thereby providing a potentially powerful resource for constructing biological networks and network-based analysis. We have developed the Gene eXpression Knowledge Base (GeXKB), a semantic web technology based resource that contains integrated knowledge about gene expression regulation. To affirm the utility of GeXKB we demonstrate how this resource can be exploited for the identification of candidate regulatory network proteins. We present four use cases that were designed from a biological perspective in order to find candidate members relevant for the gastrin hormone signaling network model. We show how a combination of specific query definitions and additional selection criteria derived from gene expression data and prior knowledge concerning candidate proteins can be used to retrieve a set of proteins that constitute valid candidates for regulatory network extensions. Semantic web technologies provide the means for processing and integrating various heterogeneous information sources. The GeXKB offers biologists such an integrated knowledge resource, allowing them to address complex biological questions pertaining to gene expression. This work illustrates how GeXKB can be used in combination with gene expression results and literature information to identify new potential candidates that may be considered for extending a gene regulatory network.

The Best of Both Worlds

PubMed Central

Ter Wal, Anne L.J.; Alexy, Oliver; Block, Jörn; Sandner, Philipp G.

2016-01-01

Open networks give actors non-redundant information that is diverse, while closed networks offer redundant information that is easier to interpret. Integrating arguments about network structure and the similarity of actors’ knowledge, we propose two types of network configurations that combine diversity and ease of interpretation. Closed-diverse networks offer diversity in actors’ knowledge domains and shared third-party ties to help in interpreting that knowledge. In open-specialized networks, structural holes offer diversity, while shared interpretive schema and overlap between received information and actors’ prior knowledge help in interpreting new information without the help of third parties. In contrast, actors in open-diverse networks suffer from information overload due to the lack of shared schema or overlapping prior knowledge for the interpretation of diverse information, and actors in closed-specialized networks suffer from overembeddedness because they cannot access diverse information. Using CrunchBase data on early-stage venture capital investments in the U.S. information technology sector, we test the effect of investors’ social capital on the success of their portfolio ventures. We find that ventures have the highest chances of success if their syndicating investors have either open-specialized or closed-diverse networks. These effects are manifested beyond the direct effects of ventures’ or investors’ quality and are robust to controlling for the possibility that certain investors could have chosen more promising ventures at the time of first funding. PMID:27499546

Activating Lay Health Influencers to Promote Tobacco Cessation

PubMed Central

Muramoto, Myra L.; Hall, John R.; Nichter, Mark; Nichter, Mimi; Aickin, Mikel; Connolly, Tim; Matthews, Eva; Campbell, Jean Z.; Lando, Harry A.

2014-01-01

Objective Evaluate the effect of tobacco cessation brief-intervention (BI) training for lay “health influencers,” on knowledge, self-efficacy and the proportion of participants reporting BI delivery post-training. Methods Randomized, community-based study comparing In-person or Web-based training, with mailed materials. Results In-person and Web-training groups had significant post-training cessation knowledge and self-efficacy gains. All groups increased the proportion of individuals reporting BIs at follow-up, with no significant between-group differences. Irrespective of participants’ prior intervention experience, 80–86% reported BIs within the past 90 days; 71–79% reported ≥1 in the past 30. Conclusions Web and In-person training significantly increase health influencer cessation knowledge and self-efficacy. With minimal prompting and materials, even persons without BI experience can be activated to encourage tobacco cessation. PMID:24636035

A Prior for Neural Networks utilizing Enclosing Spheres for Normalization

NASA Astrophysics Data System (ADS)

v. Toussaint, U.; Gori, S.; Dose, V.

2004-11-01

Neural Networks are famous for their advantageous flexibility for problems when there is insufficient knowledge to set up a proper model. On the other hand this flexibility can cause over-fitting and can hamper the generalization properties of neural networks. Many approaches to regularize NN have been suggested but most of them based on ad-hoc arguments. Employing the principle of transformation invariance we derive a general prior in accordance with the Bayesian probability theory for a class of feedforward networks. Optimal networks are determined by Bayesian model comparison verifying the applicability of this approach.

Stroke risk perception among participants of a stroke awareness campaign

PubMed Central

Kraywinkel, Klaus; Heidrich, Jan; Heuschmann, Peter U; Wagner, Markus; Berger, Klaus

2007-01-01

Background Subjective risk factor perception is an important component of the motivation to change unhealthy life styles. While prior studies assessed cardiovascular risk factor knowledge, little is known about determinants of the individual perception of stroke risk. Methods Survey by mailed questionnaire among 1483 participants of a prior public stroke campaign in Germany. Participants had been informed about their individual stroke risk based on the Framingham stroke risk score. Stroke risk factor knowledge, perception of lifetime stroke risk and risk factor status were included in the questionnaire, and the determinants of good risk factor knowledge and high stroke risk perception were identified using logistic regression models. Results Overall stroke risk factor knowledge was good with 67–96% of the participants recognizing established risk factors. The two exceptions were diabetes (recognized by 49%) and myocardial infarction (57%). Knowledge of a specific factor was superior among those affected by it. 13% of all participants considered themselves of having a high stroke risk, 55% indicated a moderate risk. All major risk factors contributed significantly to the perception of being at high stroke risk, but the effects of age, sex and education were non-significant. Poor self-rated health was additionally associated with high individual stroke risk perception. Conclusion Stroke risk factor knowledge was high in this study. The self perception of an increased stroke risk was associated with established risk factors as well as low perception of general health. PMID:17371603

The knowledge model of MedFrame/CADIAG-IV.

PubMed

Sageder, B; Boegl, K; Adlassnig, K P; Kolousek, G; Trummer, B

1997-01-01

The medical consultation system MedFrame/CADIAG-IV is a successor of the prior CADIAG projects. It is the result of a complete redesign to account for today's demands on state-of-the-art software. Its knowledge representation and inference process are based on fuzzy set theory and fuzzy logic. Fuzzy sets are used for conversions from measured numeric values and observational data into symbolic ones. Medical relationships between findings, diseases, and therapies, the rules, are represented by fuzzy relations, that express positive or negative associations. Findings, diseases, and therapies are organised in hierarchies.

Fundamentals of microfluidics for high school students with no prior knowledge of fluid mechanics.

PubMed

Tandon, Vishal; Peck, Walter

2013-01-01

Three microfluidics-based laboratory exercises were developed and implemented in a high school science classroom setting. The first exercise demonstrated ways in which flows are characterized, including viscosity, turbulence, shear stress, reversibility, compressibility, and hydrodynamic resistance. Students characterized flows in poly(dimethylsiloxane) microfluidic devices in the other two exercises, where they observed the mixing characteristics of laminar flows, and conservation of volumetric flow rate for incompressible flows. In surveys, the students self-reported increased knowledge of microfluidics, and an improved attitude toward science and nanotechnology.

Accessing and integrating data and knowledge for biomedical research.

PubMed

Burgun, A; Bodenreider, O

2008-01-01

To review the issues that have arisen with the advent of translational research in terms of integration of data and knowledge, and survey current efforts to address these issues. Using examples form the biomedical literature, we identified new trends in biomedical research and their impact on bioinformatics. We analyzed the requirements for effective knowledge repositories and studied issues in the integration of biomedical knowledge. New diagnostic and therapeutic approaches based on gene expression patterns have brought about new issues in the statistical analysis of data, and new workflows are needed are needed to support translational research. Interoperable data repositories based on standard annotations, infrastructures and services are needed to support the pooling and meta-analysis of data, as well as their comparison to earlier experiments. High-quality, integrated ontologies and knowledge bases serve as a source of prior knowledge used in combination with traditional data mining techniques and contribute to the development of more effective data analysis strategies. As biomedical research evolves from traditional clinical and biological investigations towards omics sciences and translational research, specific needs have emerged, including integrating data collected in research studies with patient clinical data, linking omics knowledge with medical knowledge, modeling the molecular basis of diseases, and developing tools that support in-depth analysis of research data. As such, translational research illustrates the need to bridge the gap between bioinformatics and medical informatics, and opens new avenues for biomedical informatics research.

Relationship of resident characteristics, attitudes, prior training and clinical knowledge to communication skills performance.

PubMed

Laidlaw, Toni Suzuki; Kaufman, David M; MacLeod, Heather; van Zanten, Sander; Simpson, David; Wrixon, William

2006-01-01

A substantial body of literature demonstrates that communication skills in medicine can be taught and retained through teaching and practice. Considerable evidence also reveals that characteristics such as gender, age, language and attitudes affect communication skills performance. Our study examined the characteristics, attitudes and prior communication skills training of residents to determine the relationship of each to patient-doctor communication. The relationship between communication skills proficiency and clinical knowledge application (biomedical and ethical) was also examined through the use of doctor-developed clinical content checklists, as very little research has been conducted in this area. A total of 78 first- and second-year residents across all departments at Dalhousie Medical School participated in a videotaped 4-station objective structured clinical examination presenting a range of communication and clinical knowledge challenges. A variety of instruments were used to gather information and assess performance. Two expert raters evaluated the videotapes. Significant relationships were observed between resident characteristics, prior communication skills training, clinical knowledge and communication skills performance. Females, younger residents and residents with English as first language scored significantly higher, as did residents with prior communication skills training. A significant positive relationship was found between the clinical content checklist and communication performance. Gender was the only characteristic related significantly to attitudes. Gender, age, language and prior communication skills training are related to communication skills performance and have implications for resident education. The positive relationship between communication skills proficiency and clinical knowledge application is important and should be explored further.

Profiles of inconsistent knowledge in children's pathways of conceptual change.

PubMed

Schneider, Michael; Hardy, Ilonca

2013-09-01

Conceptual change requires learners to restructure parts of their conceptual knowledge base. Prior research has identified the fragmentation and the integration of knowledge as 2 important component processes of knowledge restructuring but remains unclear as to their relative importance and the time of their occurrence during development. Previous studies mostly were based on the categorization of answers in interview studies and led to mixed empirical results, suggesting that methodological improvements might be helpful. We assessed 161 third-graders' knowledge about floating and sinking of objects in liquids at 3 measurement points by means of multiple-choice tests. The tests assessed how strongly the children agreed with commonly found but mutually incompatible statements about floating and sinking. A latent profile transition analysis of the test scores revealed 5 profiles, some of which indicated the coexistence of inconsistent pieces of knowledge in learners. The majority of students (63%) were on 1 of 7 developmental pathways between these profiles. Thus, a child's knowledge profile at a point in time can be used to predict further development. The degree of knowledge integration decreased on some individual developmental paths, increased on others, and remained stable on still others. The study demonstrates the usefulness of explicit quantitative models of conceptual change. The results support a constructivist perspective on conceptual development, in which developmental changes of a learner's knowledge base result from idiosyncratic, yet systematic knowledge-construction processes. PsycINFO Database Record (c) 2013 APA, all rights reserved.

The cure: design and evaluation of a crowdsourcing game for gene selection for breast cancer survival prediction.

PubMed

Good, Benjamin M; Loguercio, Salvatore; Griffith, Obi L; Nanis, Max; Wu, Chunlei; Su, Andrew I

2014-07-29

Molecular signatures for predicting breast cancer prognosis could greatly improve care through personalization of treatment. Computational analyses of genome-wide expression datasets have identified such signatures, but these signatures leave much to be desired in terms of accuracy, reproducibility, and biological interpretability. Methods that take advantage of structured prior knowledge (eg, protein interaction networks) show promise in helping to define better signatures, but most knowledge remains unstructured. Crowdsourcing via scientific discovery games is an emerging methodology that has the potential to tap into human intelligence at scales and in modes unheard of before. The main objective of this study was to test the hypothesis that knowledge linking expression patterns of specific genes to breast cancer outcomes could be captured from players of an open, Web-based game. We envisioned capturing knowledge both from the player's prior experience and from their ability to interpret text related to candidate genes presented to them in the context of the game. We developed and evaluated an online game called The Cure that captured information from players regarding genes for use as predictors of breast cancer survival. Information gathered from game play was aggregated using a voting approach, and used to create rankings of genes. The top genes from these rankings were evaluated using annotation enrichment analysis, comparison to prior predictor gene sets, and by using them to train and test machine learning systems for predicting 10 year survival. Between its launch in September 2012 and September 2013, The Cure attracted more than 1000 registered players, who collectively played nearly 10,000 games. Gene sets assembled through aggregation of the collected data showed significant enrichment for genes known to be related to key concepts such as cancer, disease progression, and recurrence. In terms of the predictive accuracy of models trained using this information, these gene sets provided comparable performance to gene sets generated using other methods, including those used in commercial tests. The Cure is available on the Internet. The principal contribution of this work is to show that crowdsourcing games can be developed as a means to address problems involving domain knowledge. While most prior work on scientific discovery games and crowdsourcing in general takes as a premise that contributors have little or no expertise, here we demonstrated a crowdsourcing system that succeeded in capturing expert knowledge.

Shared knowledge or shared affordances? Insights from an ecological dynamics approach to team coordination in sports.

PubMed

Silva, Pedro; Garganta, Júlio; Araújo, Duarte; Davids, Keith; Aguiar, Paulo

2013-09-01

Previous research has proposed that team coordination is based on shared knowledge of the performance context, responsible for linking teammates' mental representations for collective, internalized action solutions. However, this representational approach raises many questions including: how do individual schemata of team members become reformulated together? How much time does it take for this collective cognitive process to occur? How do different cues perceived by different individuals sustain a general shared mental representation? This representational approach is challenged by an ecological dynamics perspective of shared knowledge in team coordination. We argue that the traditional shared knowledge assumption is predicated on 'knowledge about' the environment, which can be used to share knowledge and influence intentions of others prior to competition. Rather, during competitive performance, the control of action by perceiving surrounding informational constraints is expressed in 'knowledge of' the environment. This crucial distinction emphasizes perception of shared affordances (for others and of others) as the main communication channel between team members during team coordination tasks. From this perspective, the emergence of coordinated behaviours in sports teams is based on the formation of interpersonal synergies between players resulting from collective actions predicated on shared affordances.

Refusal bias in HIV prevalence estimates from nationally representative seroprevalence surveys.

PubMed

Reniers, Georges; Eaton, Jeffrey

2009-03-13

To assess the relationship between prior knowledge of one's HIV status and the likelihood to refuse HIV testing in populations-based surveys and explore its potential for producing bias in HIV prevalence estimates. Using longitudinal survey data from Malawi, we estimate the relationship between prior knowledge of HIV-positive status and subsequent refusal of an HIV test. We use that parameter to develop a heuristic model of refusal bias that is applied to six Demographic and Health Surveys, in which refusal by HIV status is not observed. The model only adjusts for refusal bias conditional on a completed interview. Ecologically, HIV prevalence, prior testing rates and refusal for HIV testing are highly correlated. Malawian data further suggest that amongst individuals who know their status, HIV-positive individuals are 4.62 (95% confidence interval, 2.60-8.21) times more likely to refuse testing than HIV-negative ones. On the basis of that parameter and other inputs from the Demographic and Health Surveys, our model predicts downward bias in national HIV prevalence estimates ranging from 1.5% (95% confidence interval, 0.7-2.9) for Senegal to 13.3% (95% confidence interval, 7.2-19.6) for Malawi. In absolute terms, bias in HIV prevalence estimates is negligible for Senegal but 1.6 (95% confidence interval, 0.8-2.3) percentage points for Malawi. Downward bias is more severe in urban populations. Because refusal rates are higher in men, seroprevalence surveys also tend to overestimate the female-to-male ratio of infections. Prior knowledge of HIV status informs decisions to participate in seroprevalence surveys. Informed refusals may produce bias in estimates of HIV prevalence and the sex ratio of infections.

Stepwise group sparse regression (SGSR): gene-set-based pharmacogenomic predictive models with stepwise selection of functional priors.

PubMed

Jang, In Sock; Dienstmann, Rodrigo; Margolin, Adam A; Guinney, Justin

2015-01-01

Complex mechanisms involving genomic aberrations in numerous proteins and pathways are believed to be a key cause of many diseases such as cancer. With recent advances in genomics, elucidating the molecular basis of cancer at a patient level is now feasible, and has led to personalized treatment strategies whereby a patient is treated according to his or her genomic profile. However, there is growing recognition that existing treatment modalities are overly simplistic, and do not fully account for the deep genomic complexity associated with sensitivity or resistance to cancer therapies. To overcome these limitations, large-scale pharmacogenomic screens of cancer cell lines--in conjunction with modern statistical learning approaches--have been used to explore the genetic underpinnings of drug response. While these analyses have demonstrated the ability to infer genetic predictors of compound sensitivity, to date most modeling approaches have been data-driven, i.e. they do not explicitly incorporate domain-specific knowledge (priors) in the process of learning a model. While a purely data-driven approach offers an unbiased perspective of the data--and may yield unexpected or novel insights--this strategy introduces challenges for both model interpretability and accuracy. In this study, we propose a novel prior-incorporated sparse regression model in which the choice of informative predictor sets is carried out by knowledge-driven priors (gene sets) in a stepwise fashion. Under regularization in a linear regression model, our algorithm is able to incorporate prior biological knowledge across the predictive variables thereby improving the interpretability of the final model with no loss--and often an improvement--in predictive performance. We evaluate the performance of our algorithm compared to well-known regularization methods such as LASSO, Ridge and Elastic net regression in the Cancer Cell Line Encyclopedia (CCLE) and Genomics of Drug Sensitivity in Cancer (Sanger) pharmacogenomics datasets, demonstrating that incorporation of the biological priors selected by our model confers improved predictability and interpretability, despite much fewer predictors, over existing state-of-the-art methods.

A shape prior-based MRF model for 3D masseter muscle segmentation

NASA Astrophysics Data System (ADS)

Majeed, Tahir; Fundana, Ketut; Lüthi, Marcel; Beinemann, Jörg; Cattin, Philippe

2012-02-01

Medical image segmentation is generally an ill-posed problem that can only be solved by incorporating prior knowledge. The ambiguities arise due to the presence of noise, weak edges, imaging artifacts, inhomogeneous interior and adjacent anatomical structures having similar intensity profile as the target structure. In this paper we propose a novel approach to segment the masseter muscle using the graph-cut incorporating additional 3D shape priors in CT datasets, which is robust to noise; artifacts; and shape deformations. The main contribution of this paper is in translating the 3D shape knowledge into both unary and pairwise potentials of the Markov Random Field (MRF). The segmentation task is casted as a Maximum-A-Posteriori (MAP) estimation of the MRF. Graph-cut is then used to obtain the global minimum which results in the segmentation of the masseter muscle. The method is tested on 21 CT datasets of the masseter muscle, which are noisy with almost all possessing mild to severe imaging artifacts such as high-density artifacts caused by e.g. the very common dental fillings and dental implants. We show that the proposed technique produces clinically acceptable results to the challenging problem of muscle segmentation, and further provide a quantitative and qualitative comparison with other methods. We statistically show that adding additional shape prior into both unary and pairwise potentials can increase the robustness of the proposed method in noisy datasets.

Framing of scientific knowledge as a new category of health care research.

PubMed

Salvador-Carulla, Luis; Fernandez, Ana; Madden, Rosamond; Lukersmith, Sue; Colagiuri, Ruth; Torkfar, Ghazal; Sturmberg, Joachim

2014-12-01

The new area of health system research requires a revision of the taxonomy of scientific knowledge that may facilitate a better understanding and representation of complex health phenomena in research discovery, corroboration and implementation. A position paper by an expert group following and iterative approach. 'Scientific evidence' should be differentiated from 'elicited knowledge' of experts and users, and this latter typology should be described beyond the traditional qualitative framework. Within this context 'framing of scientific knowledge' (FSK) is defined as a group of studies of prior expert knowledge specifically aimed at generating formal scientific frames. To be distinguished from other unstructured frames, FSK must be explicit, standardized, based on the available evidence, agreed by a group of experts and subdued to the principles of commensurability, transparency for corroboration and transferability that characterize scientific research. A preliminary typology of scientific framing studies is presented. This typology includes, among others, health declarations, position papers, expert-based clinical guides, conceptual maps, classifications, expert-driven health atlases and expert-driven studies of costs and burden of illness. This grouping of expert-based studies constitutes a different kind of scientific knowledge and should be clearly differentiated from 'evidence' gathered from experimental and observational studies in health system research. © 2014 John Wiley & Sons, Ltd.

Prior Knowledge Activation: How Different Concept Mapping Tasks Lead to Substantial Differences in Cognitive Processes, Learning Outcomes, and Perceived Self-Efficacy

ERIC Educational Resources Information Center

Gurlitt, Johannes; Renkl, Alexander

2010-01-01

Two experiments investigated the effects of characteristic features of concept mapping used for prior knowledge activation. Characteristic demands of concept mapping include connecting lines representing the relationships between concepts and labeling these lines, specifying the type of the semantic relationships. In the first experiment,…

Formative Assessment Pre-Test to Identify College Students' Prior Knowledge, Misconceptions and Learning Difficulties in Biology

ERIC Educational Resources Information Center

Lazarowitz, Reuven; Lieb, Carl

2006-01-01

A formative assessment pretest was administered to undergraduate students at the beginning of a science course in order to find out their prior knowledge, misconceptions and learning difficulties on the topic of the human respiratory system and energy issues. Those findings could provide their instructors with the valuable information required in…

The Influence of Prior Knowledge, Peer Review, Age, and Gender in Online Philosophy Discussions

ERIC Educational Resources Information Center

Cuddy, Lucas Stebbins

2016-01-01

Using a primarily experimental design, this study investigated whether discussion boards in online community college philosophy classes can be designed in the Blackboard course management system to lead to higher order thinking. Discussions were designed using one of two teaching techniques: the activation of prior knowledge or the use of peer…

Thai University Students' Prior Knowledge about P-Waves Generated during Particle Motion

ERIC Educational Resources Information Center

Rakkapao, Suttida; Arayathanikul, Kwan; Pananont, Passakorn

2009-01-01

The goal of this study is to identify Thai students' prior knowledge about particle motion when P-waves arrive. This existing idea significantly influences what and how students learn in the classroom. The data were collected via conceptual open-ended questions designed by the researchers and through explanatory follow-up interviews. Participants…

The Interpretation of Cellular Transport Graphics by Students with Low and High Prior Knowledge

ERIC Educational Resources Information Center

Cook, Michelle; Carter, Glenda; Wiebe, Eric N.

2008-01-01

The purpose of this study was to examine how prior knowledge of cellular transport influenced how high school students in the USA viewed and interpreted graphic representations of this topic. The participants were Advanced Placement Biology students (n = 65); each participant had previously taken a biology course in high school. After assessing…

The Effects of Prior-Knowledge and Online Learning Approaches on Students' Inquiry and Argumentation Abilities

ERIC Educational Resources Information Center

Yang, Wen-Tsung; Lin, Yu-Ren; She, Hsiao-Ching; Huang, Kai-Yi

2015-01-01

This study investigated the effects of students' prior science knowledge and online learning approaches (social and individual) on their learning with regard to three topics: science concepts, inquiry, and argumentation. Two science teachers and 118 students from 4 eighth-grade science classes were invited to participate in this research. Students…

Python Environment for Bayesian Learning: Inferring the Structure of Bayesian Networks from Knowledge and Data

PubMed Central

Shah, Abhik; Woolf, Peter

2009-01-01

Summary In this paper, we introduce pebl, a Python library and application for learning Bayesian network structure from data and prior knowledge that provides features unmatched by alternative software packages: the ability to use interventional data, flexible specification of structural priors, modeling with hidden variables and exploitation of parallel processing. PMID:20161541

The Instructional Effectiveness of Animated Signaling among Learners with High and Low Prior Knowledge

ERIC Educational Resources Information Center

Li, Shanshan

2012-01-01

The purpose of this study was to investigate the instructional effectiveness of animated signals among learners with high and low prior knowledge. Each of the two treatments was presented with animated instruction either with signals or without signals on the content of how an airplane achieves lift. Subjects were eighty-seven undergraduate…

A Fair and Balanced Look at the News: What Affects Memory for Controversial Arguments?

ERIC Educational Resources Information Center

Wiley, J.

2005-01-01

This research demonstrates how prior knowledge may allow for qualitative differences in representation of texts about controversial issues. People often experience a memory bias in favor of information with which they agree. In several experiments it was found that individuals with high prior knowledge about the topic were better able to recall…

Prior Knowledge Influence on Self-Explanation Effectiveness when Solving Problems: An Exploratory Study in Science Learning

ERIC Educational Resources Information Center

Ionas, Ioan Gelu; Cernusca, Dan; Collier, Harvest L.

2012-01-01

This exploratory study presents the outcomes of using self-explanation to improve learners' performance in solving basic chemistry problems. The results of the randomized experiment show the existence of a moderation effect between prior knowledge and the level of support self-explanation provides to learners, suggestive of a synergistic effect…

The Impact of Learner's Prior Knowledge on Their Use of Chemistry Computer Simulations: A Case Study

ERIC Educational Resources Information Center

Liu, Han-Chin; Andre, Thomas; Greenbowe, Thomas

2008-01-01

It is complicated to design a computer simulation that adapts to students with different characteristics. This study documented cases that show how college students' prior chemistry knowledge level affected their interaction with peers and their approach to solving problems with the use of computer simulations that were designed to learn…

Activating Junior Secondary School Students' Prior Knowledge for the Development of Vocabulary, Concepts and Mathematics through Instructional Strategies

ERIC Educational Resources Information Center

Oyinloye, Olu; Popoola, Abiodun A.

2013-01-01

This paper investigates the activation of students' prior knowledge for the development of vocabulary, concepts and mathematics. It has been observed that many secondary school students are not performing well in the examination conducted by the West African Examinations Council and National Examinations Council of Nigeria. The situation became…

Measuring the Acceptance of Evolutionary Theory in Texas 2-Year Colleges

ERIC Educational Resources Information Center

Brown, Jack; Scott, Joyce A.

2016-01-01

Evolutionary theory is the central unifying theory of the life sciences. However, acceptance and understanding of the theory have been found to be lacking in the general public, high school, and university populations. Prior research has linked low acceptance of the theory to a poor knowledge base in evolution, to the nature of science, and to…

Exploring Teachers' Process of Change in Incorporating Problem Solving into the Mathematics Classroom

ERIC Educational Resources Information Center

Rutherford, Vanessa

2012-01-01

This study explores how a problem-solving based professional learning community (PLC) affects the beliefs, knowledge, and instructional practices of two sixth-grade mathematics teachers. An interview and two observations were conducted prior to beginning the year-long PLC in order to gather information about the participants' beliefs,…

Student Connections with Academic Texts: A Phenomenographic Study of Reading

ERIC Educational Resources Information Center

MacMillan, Margy

2014-01-01

Concerns about the ability of post-secondary students to read scholarly materials are well documented in the literature. A key aspect of reading at the deeper level expected of these students is connecting new information to prior knowledge. This study is based on an activity where students were explicitly required to make such connections as part…

Developing a Philosophy of Supervision: One Step toward Self-Authorship

ERIC Educational Resources Information Center

McNair, Delores E.

2011-01-01

Self-authorship, as described by Baxter Magolda (2008), is about trusting ourselves (our internal voice), rather than relying on external voices to guide our lives. Young professionals attempt to navigate new experiences based on prior knowledge and begin to distinguish what others tell them from what they believe and value on their own. The path…

Development, Dissemination, and Assessment of a Food Safety Systems Management Curriculum for Agribusiness Students in Armenia

ERIC Educational Resources Information Center

Pokharel, Siroj; Marcy, Joseph E.; Neilan, Angela M.; Cutter, Catherine N.

2017-01-01

This study addresses the development, dissemination, and assessment of a Food Safety System Management (FSSM) curriculum offered to college-aged, agribusiness students in Yerevan, Armenia. Prior to beginning the program, demographic data were collected and a paper-based pretest was administered to access the food safety knowledge, behavior, and…

Prior knowledge-based approach for associating contaminants with biological effects: A case study in the St. Croix river basin, MN, WI, USA.

EPA Science Inventory

Evaluating the potential human health and/or ecological risks associated with exposures to complex chemical mixtures in the ambient environment is one of the central challenges of chemical safety assessment and environmental protection. There is a need for approaches that can he...

Literary Translation, Translating Culture: The Case of Shahriyar, the Famous Iranian Azeri Poet

ERIC Educational Resources Information Center

Kianbakht, Saijad

2016-01-01

A literary translation is a device of art used to release the text from its dependence on prior cultural knowledge (Herzfeld, 2003). The present research investigates the use of pragmatic equivalence in two translations of the Azeri Turkish long poem "Haydar Babaye Salam" by "Shahriyar." Based on Koller's theory of equivalence…

The Influence of Activation Level on Belief Bias in Relational Reasoning

ERIC Educational Resources Information Center

Banks, Adrian P.

2013-01-01

A novel explanation of belief bias in relational reasoning is presented based on the role of working memory and retrieval in deductive reasoning, and the influence of prior knowledge on this process. It is proposed that belief bias is caused by the believability of a conclusion in working memory which influences its activation level, determining…

Enhancing Pre-Service Elementary Teachers' Conceptual Understanding of Solution Chemistry with Conceptual Change Text

ERIC Educational Resources Information Center

Calik, Muammer; Ayas, Alipasa; Coll, Richard Kevin

2007-01-01

This paper reports on the use of a constructivist-based pedagogy to enhance understanding of some features of solution chemistry. Pre-service science teacher trainees' prior knowledge about the dissolution of salts and sugar in water were elicited by the use of a simple diagnostic tool. The test revealed widespread alternative conceptions. These…

Differentiating Digital Writing Instruction: The Intersection of Technology, Writing Instruction, and Digital Genre Knowledge

ERIC Educational Resources Information Center

Martin, Nicole M.; Lambert, Claire

2015-01-01

U.S. adolescents' prior technology experiences and exposure to digital genres vary, but they will often write digital texts as they enter college and adulthood. We explored middle school students' digital writing instructional experience in the context of a university-based summer digital writing camp. The sixth- through eighth-grade adolescents…

Unintended Consequences or Testing the Integrity of Teachers and Students.

ERIC Educational Resources Information Center

Kimmel, Ernest W.

Large-scale testing programs are generally based on the assumptions that the test-takers experience standard conditions for taking the test and that everyone will do his or her own work without having prior knowledge of specific questions. These assumptions are not necessarily true. The ways students and educators use to get around standardizing…

Reducing Hispanic Teenage Pregnancy and Family Poverty: A Replication Guide. Final Version.

ERIC Educational Resources Information Center

Perez, Sonia M.; Duany, Luis A.

This guide was designed to help Hispanic American community-based organizations develop and establish a teenage pregnancy prevention or teenage parenting program for Hispanic American adolescents. The guide does not assume prior knowledge of the scope of the teenage pregnancy problem in the United States, but it does underscore the critical role…

Using Adaptive Learning Technologies to Personalize Instruction to Student Interests: The Impact of Relevant Contexts on Performance and Learning Outcomes

ERIC Educational Resources Information Center

Walkington, Candace A.

2013-01-01

Adaptive learning technologies are emerging in educational settings as a means to customize instruction to learners' background, experiences, and prior knowledge. Here, a technology-based personalization intervention within an intelligent tutoring system (ITS) for secondary mathematics was used to adapt instruction to students' personal interests.…

The Problems of Validation in a Competency-Based Preservice Reading Education Program.

ERIC Educational Resources Information Center

Bergquist, Sidney R.

A problem of teacher education is to successfully integrate the knowledge students learn in the college classroom with the practical experiences of student teaching. A principal objective of an ideal teacher training situation would be to establish a vertical integration of the various types of exposure to reading both prior to and during contact…

What Are Confidence Judgments Made of? Students' Explanations for Their Confidence Ratings and What that Means for Calibration

ERIC Educational Resources Information Center

Dinsmore, Daniel L.; Parkinson, Meghan M.

2013-01-01

Although calibration has been widely studied, questions remain about how best to capture confidence ratings, how to calculate continuous variable calibration indices, and on what exactly students base their reported confidence ratings. Undergraduates in a research methods class completed a prior knowledge assessment, two sets of readings and…

Mechanisms underlying comprehension of health information in adulthood: the roles of prior knowledge and working memory capacity.

PubMed

Soederberg Miller, Lisa M; Gibson, Tanja N; Applegate, Elizabeth A; de Dios, Jeannette

2011-07-01

Prior knowledge, working memory capacity (WMC), and conceptual integration (attention allocated to integrating concepts in text) are critical within many contexts; however, their impact on the acquisition of health information (i.e. learning) is relatively unexplored.We examined how these factors impact learning about nutrition within a cross-sectional study of adults ages 18 to 81. Results showed that conceptual integration mediated the effects of knowledge and WMC on learning, confirming that attention to concepts while reading is important for learning about health. We also found that when knowledge was controlled, age declines in learning increased, suggesting that knowledge mitigates the effects of age on learning about nutrition.

Simulation-Based Cryosurgery Training: Variable Insertion-Depth Planning in Prostate Cryosurgery

PubMed Central

Sehrawat, Anjali; Keelan, Robert; Shimada, Kenji; Wilfong, Dona M.; McCormick, James T.; Rabin, Yoed

2015-01-01

A proof-of-concept for an advanced-level computerized training tool for cryosurgery is demonstrated, based on three-dimensional cryosurgery simulations and a variable insertion-depth strategy for cryoprobes. The objective for system development is twofold: to identify a cryoprobe layout in order to best-match a planning isotherm with the target region shape, and to verify that cryoprobe placement does not violate accepted geometric constraints. System validation has been performed by collecting training data from 17 surgical residents, having no prior experience or advanced knowledge of cryosurgery. This advanced-level study includes an improved training-session design, in order to enhance knowledge dissemination and elevate participant motivation to excel. In terms of match between a planning isotherm and the target region shape, results of this demonstrate trainee performance improvement from 4.4% in a pretest to 44.4% in a posttest over a course of 50 minutes of training. In terms of combined performance, including the above geometrical match and constraints on cryoprobe placement, this study demonstrates trainee performance improvement from 2.2% in the pretest to 31.1% in the posttest. Given the relatively short training session and the lack of prior knowledge, these improvements are significant and encouraging. These results are of particular significance, as they have been obtained from a surgical resident population, which are exposed to the typical stress and constraints in advanced surgical education. PMID:26546576

Putting Priors in Mixture Density Mercer Kernels

NASA Technical Reports Server (NTRS)

Srivastava, Ashok N.; Schumann, Johann; Fischer, Bernd

2004-01-01

This paper presents a new methodology for automatic knowledge driven data mining based on the theory of Mercer Kernels, which are highly nonlinear symmetric positive definite mappings from the original image space to a very high, possibly infinite dimensional feature space. We describe a new method called Mixture Density Mercer Kernels to learn kernel function directly from data, rather than using predefined kernels. These data adaptive kernels can en- code prior knowledge in the kernel using a Bayesian formulation, thus allowing for physical information to be encoded in the model. We compare the results with existing algorithms on data from the Sloan Digital Sky Survey (SDSS). The code for these experiments has been generated with the AUTOBAYES tool, which automatically generates efficient and documented C/C++ code from abstract statistical model specifications. The core of the system is a schema library which contains template for learning and knowledge discovery algorithms like different versions of EM, or numeric optimization methods like conjugate gradient methods. The template instantiation is supported by symbolic- algebraic computations, which allows AUTOBAYES to find closed-form solutions and, where possible, to integrate them into the code. The results show that the Mixture Density Mercer-Kernel described here outperforms tree-based classification in distinguishing high-redshift galaxies from low- redshift galaxies by approximately 16% on test data, bagged trees by approximately 7%, and bagged trees built on a much larger sample of data by approximately 2%.

The Effects of Source Credibility in the Presence or Absence of Prior Attitudes: Implications for the Design of Persuasive Communication Campaigns.

PubMed

Kumkale, G Tarcan; Albarracín, Dolores; Seignourel, Paul J

2010-06-01

Most theories of persuasion predict that limited ability and motivation to think about communications should increase the impact of source credibility on persuasion. Furthermore, this effect is assumed to occur, regardless of whether or not the recipients have prior attitudes. In this study, the effects of source credibility, ability, and motivation (knowledge, message repetition, relevance) on persuasion were examined meta-analytically across both attitude formation and change conditions. Findings revealed that the Source Credibility × Ability/Motivation interaction emerged only when participants lacked prior attitudes and were unable to form a new attitude based on the message content. In such settings, the effects of source credibility decayed rapidly. The implications of these findings for applied communication campaigns are discussed.

The Effects of Source Credibility in the Presence or Absence of Prior Attitudes: Implications for the Design of Persuasive Communication Campaigns1

PubMed Central

Kumkale, G. Tarcan; AlbarracÍn, Dolores; Seignourel, Paul J.

2011-01-01

Most theories of persuasion predict that limited ability and motivation to think about communications should increase the impact of source credibility on persuasion. Furthermore, this effect is assumed to occur, regardless of whether or not the recipients have prior attitudes. In this study, the effects of source credibility, ability, and motivation (knowledge, message repetition, relevance) on persuasion were examined meta-analytically across both attitude formation and change conditions. Findings revealed that the Source Credibility × Ability/Motivation interaction emerged only when participants lacked prior attitudes and were unable to form a new attitude based on the message content. In such settings, the effects of source credibility decayed rapidly. The implications of these findings for applied communication campaigns are discussed. PMID:21625405

Experimental evidence on the impact of food advertising on children's knowledge about and preferences for healthful food.

PubMed

Reisch, Lucia A; Gwozdz, Wencke; Barba, Gianvincenzo; De Henauw, Stefaan; Lascorz, Natalia; Pigeot, Iris

2013-01-01

To understand the rising prevalence of childhood obesity in affluent societies, it is necessary to take into account the growing obesity infrastructure, which over past decades has developed into an obesogenic environment. This study examines the effects of one of the constituent factors of consumer societies and a potential contributory factor to childhood obesity: commercial food communication targeted to children. Specifically, it investigates the impact of TV advertising on children's food knowledge and food preferences and correlates these findings with their weight status. Evaluations of traditional information- and education-based interventions suggest that they may not sustainably change food patterns. Based on prior consumer research, we propose five hypotheses, which we then test using a subsample from the IDEFICS study, a large-scale pan-European intervention study on childhood obesity. The results indicate that advertising has divergent effects on children's food knowledge and preferences and that food knowledge is unrelated to food preferences. This finding has important implications for both future research and public policy.

Image segmentation with a novel regularized composite shape prior based on surrogate study

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

Zhao, Tingting, E-mail: tingtingzhao@mednet.ucla.edu; Ruan, Dan, E-mail: druan@mednet.ucla.edu

Purpose: Incorporating training into image segmentation is a good approach to achieve additional robustness. This work aims to develop an effective strategy to utilize shape prior knowledge, so that the segmentation label evolution can be driven toward the desired global optimum. Methods: In the variational image segmentation framework, a regularization for the composite shape prior is designed to incorporate the geometric relevance of individual training data to the target, which is inferred by an image-based surrogate relevance metric. Specifically, this regularization is imposed on the linear weights of composite shapes and serves as a hyperprior. The overall problem is formulatedmore » in a unified optimization setting and a variational block-descent algorithm is derived. Results: The performance of the proposed scheme is assessed in both corpus callosum segmentation from an MR image set and clavicle segmentation based on CT images. The resulted shape composition provides a proper preference for the geometrically relevant training data. A paired Wilcoxon signed rank test demonstrates statistically significant improvement of image segmentation accuracy, when compared to multiatlas label fusion method and three other benchmark active contour schemes. Conclusions: This work has developed a novel composite shape prior regularization, which achieves superior segmentation performance than typical benchmark schemes.« less

Utilizing knowledge from prior plans in the evaluation of quality assurance

NASA Astrophysics Data System (ADS)

Stanhope, Carl; Wu, Q. Jackie; Yuan, Lulin; Liu, Jianfei; Hood, Rodney; Yin, Fang-Fang; Adamson, Justus

2015-06-01

Increased interest regarding sensitivity of pre-treatment intensity modulated radiotherapy and volumetric modulated arc radiotherapy (VMAT) quality assurance (QA) to delivery errors has led to the development of dose-volume histogram (DVH) based analysis. This paradigm shift necessitates a change in the acceptance criteria and action tolerance for QA. Here we present a knowledge based technique to objectively quantify degradations in DVH for prostate radiotherapy. Using machine learning, organ-at-risk (OAR) DVHs from a population of 198 prior patients’ plans were adapted to a test patient’s anatomy to establish patient-specific DVH ranges. This technique was applied to single arc prostate VMAT plans to evaluate various simulated delivery errors: systematic single leaf offsets, systematic leaf bank offsets, random normally distributed leaf fluctuations, systematic lag in gantry angle of the mutli-leaf collimators (MLCs), fluctuations in dose rate, and delivery of each VMAT arc with a constant rather than variable dose rate. Quantitative Analyses of Normal Tissue Effects in the Clinic suggests V75Gy dose limits of 15% for the rectum and 25% for the bladder, however the knowledge based constraints were more stringent: 8.48   ±   2.65% for the rectum and 4.90   ±   1.98% for the bladder. 19   ±   10 mm single leaf and 1.9   ±   0.7 mm single bank offsets resulted in rectum DVHs worse than 97.7% (2σ) of clinically accepted plans. PTV degradations fell outside of the acceptable range for 0.6   ±   0.3 mm leaf offsets, 0.11   ±   0.06 mm bank offsets, 0.6   ±   1.3 mm of random noise, and 1.0   ±   0.7° of gantry-MLC lag. Utilizing a training set comprised of prior treatment plans, machine learning is used to predict a range of achievable DVHs for the test patient’s anatomy. Consequently, degradations leading to statistical outliers may be identified. A knowledge based QA evaluation enables customized QA criteria per treatment site, institution and/or physician and can often be more sensitive to errors than criteria based on organ complication rates.

A Knowledge Translation Programme to Increase the Utilization of Thoracic Spine Mobilization and Manipulation for Patients with Neck Pain.

PubMed

Karas, Steve; Westerheide, Angela; Daniel, Laura

2016-06-01

There is extensive evidence that mobilization and manipulation of the thoracic spine is associated with improved outcomes in patients with neck pain. However, these evidence-based techniques are not always utilized. Successful knowledge translation programmes are needed to move the best available evidence to clinical practice. The purpose of the present research was to evaluate the effects of a structured knowledge translation programme on the frequency of manual therapy techniques performed by physical therapists on patients with neck pain. Prior to our intervention, we assessed physical therapists' use of thoracic spine intervention for the treatment of neck pain and their knowledge of the evidence. We delivered a multimodal knowledge translation programme and then reassessed their use and knowledge of the interventions. The majority of our physical therapists increased the use of thoracic spine techniques for their patients with neck pain. The increase was greater in those who used the techniques infrequently. Overall knowledge of the evidence appeared unchanged. Knowledge translation programmes are essential in ensuring clinical use of evidence-based practice. Our programme results, although on a small scale and not statistically significant, showed a positive trend toward increased thoracic spine manual therapy use for neck pain. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

A population-based tissue probability map-driven level set method for fully automated mammographic density estimations.

PubMed

Kim, Youngwoo; Hong, Byung Woo; Kim, Seung Ja; Kim, Jong Hyo

2014-07-01

A major challenge when distinguishing glandular tissues on mammograms, especially for area-based estimations, lies in determining a boundary on a hazy transition zone from adipose to glandular tissues. This stems from the nature of mammography, which is a projection of superimposed tissues consisting of different structures. In this paper, the authors present a novel segmentation scheme which incorporates the learned prior knowledge of experts into a level set framework for fully automated mammographic density estimations. The authors modeled the learned knowledge as a population-based tissue probability map (PTPM) that was designed to capture the classification of experts' visual systems. The PTPM was constructed using an image database of a selected population consisting of 297 cases. Three mammogram experts extracted regions for dense and fatty tissues on digital mammograms, which was an independent subset used to create a tissue probability map for each ROI based on its local statistics. This tissue class probability was taken as a prior in the Bayesian formulation and was incorporated into a level set framework as an additional term to control the evolution and followed the energy surface designed to reflect experts' knowledge as well as the regional statistics inside and outside of the evolving contour. A subset of 100 digital mammograms, which was not used in constructing the PTPM, was used to validate the performance. The energy was minimized when the initial contour reached the boundary of the dense and fatty tissues, as defined by experts. The correlation coefficient between mammographic density measurements made by experts and measurements by the proposed method was 0.93, while that with the conventional level set was 0.47. The proposed method showed a marked improvement over the conventional level set method in terms of accuracy and reliability. This result suggests that the proposed method successfully incorporated the learned knowledge of the experts' visual systems and has potential to be used as an automated and quantitative tool for estimations of mammographic breast density levels.

Perceptual learning of degraded speech by minimizing prediction error.

PubMed

Sohoglu, Ediz; Davis, Matthew H

2016-03-22

Human perception is shaped by past experience on multiple timescales. Sudden and dramatic changes in perception occur when prior knowledge or expectations match stimulus content. These immediate effects contrast with the longer-term, more gradual improvements that are characteristic of perceptual learning. Despite extensive investigation of these two experience-dependent phenomena, there is considerable debate about whether they result from common or dissociable neural mechanisms. Here we test single- and dual-mechanism accounts of experience-dependent changes in perception using concurrent magnetoencephalographic and EEG recordings of neural responses evoked by degraded speech. When speech clarity was enhanced by prior knowledge obtained from matching text, we observed reduced neural activity in a peri-auditory region of the superior temporal gyrus (STG). Critically, longer-term improvements in the accuracy of speech recognition following perceptual learning resulted in reduced activity in a nearly identical STG region. Moreover, short-term neural changes caused by prior knowledge and longer-term neural changes arising from perceptual learning were correlated across subjects with the magnitude of learning-induced changes in recognition accuracy. These experience-dependent effects on neural processing could be dissociated from the neural effect of hearing physically clearer speech, which similarly enhanced perception but increased rather than decreased STG responses. Hence, the observed neural effects of prior knowledge and perceptual learning cannot be attributed to epiphenomenal changes in listening effort that accompany enhanced perception. Instead, our results support a predictive coding account of speech perception; computational simulations show how a single mechanism, minimization of prediction error, can drive immediate perceptual effects of prior knowledge and longer-term perceptual learning of degraded speech.

Perceptual learning of degraded speech by minimizing prediction error

PubMed Central

Sohoglu, Ediz

2016-01-01

Human perception is shaped by past experience on multiple timescales. Sudden and dramatic changes in perception occur when prior knowledge or expectations match stimulus content. These immediate effects contrast with the longer-term, more gradual improvements that are characteristic of perceptual learning. Despite extensive investigation of these two experience-dependent phenomena, there is considerable debate about whether they result from common or dissociable neural mechanisms. Here we test single- and dual-mechanism accounts of experience-dependent changes in perception using concurrent magnetoencephalographic and EEG recordings of neural responses evoked by degraded speech. When speech clarity was enhanced by prior knowledge obtained from matching text, we observed reduced neural activity in a peri-auditory region of the superior temporal gyrus (STG). Critically, longer-term improvements in the accuracy of speech recognition following perceptual learning resulted in reduced activity in a nearly identical STG region. Moreover, short-term neural changes caused by prior knowledge and longer-term neural changes arising from perceptual learning were correlated across subjects with the magnitude of learning-induced changes in recognition accuracy. These experience-dependent effects on neural processing could be dissociated from the neural effect of hearing physically clearer speech, which similarly enhanced perception but increased rather than decreased STG responses. Hence, the observed neural effects of prior knowledge and perceptual learning cannot be attributed to epiphenomenal changes in listening effort that accompany enhanced perception. Instead, our results support a predictive coding account of speech perception; computational simulations show how a single mechanism, minimization of prediction error, can drive immediate perceptual effects of prior knowledge and longer-term perceptual learning of degraded speech. PMID:26957596

A bayesian translational framework for knowledge propagation, discovery, and integration under specific contexts.

PubMed

Deng, Michelle; Zollanvari, Amin; Alterovitz, Gil

2012-01-01

The immense corpus of biomedical literature existing today poses challenges in information search and integration. Many links between pieces of knowledge occur or are significant only under certain contexts-rather than under the entire corpus. This study proposes using networks of ontology concepts, linked based on their co-occurrences in annotations of abstracts of biomedical literature and descriptions of experiments, to draw conclusions based on context-specific queries and to better integrate existing knowledge. In particular, a Bayesian network framework is constructed to allow for the linking of related terms from two biomedical ontologies under the queried context concept. Edges in such a Bayesian network allow associations between biomedical concepts to be quantified and inference to be made about the existence of some concepts given prior information about others. This approach could potentially be a powerful inferential tool for context-specific queries, applicable to ontologies in other fields as well.

A Bayesian Translational Framework for Knowledge Propagation, Discovery, and Integration Under Specific Contexts

PubMed Central

Deng, Michelle; Zollanvari, Amin; Alterovitz, Gil

2012-01-01

The immense corpus of biomedical literature existing today poses challenges in information search and integration. Many links between pieces of knowledge occur or are significant only under certain contexts—rather than under the entire corpus. This study proposes using networks of ontology concepts, linked based on their co-occurrences in annotations of abstracts of biomedical literature and descriptions of experiments, to draw conclusions based on context-specific queries and to better integrate existing knowledge. In particular, a Bayesian network framework is constructed to allow for the linking of related terms from two biomedical ontologies under the queried context concept. Edges in such a Bayesian network allow associations between biomedical concepts to be quantified and inference to be made about the existence of some concepts given prior information about others. This approach could potentially be a powerful inferential tool for context-specific queries, applicable to ontologies in other fields as well. PMID:22779044

A Robust Wireless Sensor Network Localization Algorithm in Mixed LOS/NLOS Scenario.

PubMed

Li, Bing; Cui, Wei; Wang, Bin

2015-09-16

Localization algorithms based on received signal strength indication (RSSI) are widely used in the field of target localization due to its advantages of convenient application and independent from hardware devices. Unfortunately, the RSSI values are susceptible to fluctuate under the influence of non-line-of-sight (NLOS) in indoor space. Existing algorithms often produce unreliable estimated distances, leading to low accuracy and low effectiveness in indoor target localization. Moreover, these approaches require extra prior knowledge about the propagation model. As such, we focus on the problem of localization in mixed LOS/NLOS scenario and propose a novel localization algorithm: Gaussian mixed model based non-metric Multidimensional (GMDS). In GMDS, the RSSI is estimated using a Gaussian mixed model (GMM). The dissimilarity matrix is built to generate relative coordinates of nodes by a multi-dimensional scaling (MDS) approach. Finally, based on the anchor nodes' actual coordinates and target's relative coordinates, the target's actual coordinates can be computed via coordinate transformation. Our algorithm could perform localization estimation well without being provided with prior knowledge. The experimental verification shows that GMDS effectively reduces NLOS error and is of higher accuracy in indoor mixed LOS/NLOS localization and still remains effective when we extend single NLOS to multiple NLOS.

The Role of Specificity, Targeted Learning Activities, and Prior Knowledge for the Effects of Relevance Instructions

ERIC Educational Resources Information Center

Roelle, Julian; Lehmkuhl, Nina; Beyer, Martin-Uwe; Berthold, Kirsten

2015-01-01

In 2 experiments we examined the role of (a) specificity, (b) the type of targeted learning activities, and (c) learners' prior knowledge for the effects of relevance instructions on learning from instructional explanations. In Experiment 1, we recruited novices regarding the topic of atomic structure (N = 80) and found that "specific"…

Effects of Prior Knowledge of Topics and the Instructional Objectives on Students' Achievement in Literature-in-English

ERIC Educational Resources Information Center

Mbah, Blessing Akaraka

2015-01-01

This study investigated the effects of prior knowledge of topics with their instructional objectives on senior secondary school class two (SS II) students. The study was carried out in Abakaliki Education Zone of Ebonyi State, Nigeria. The design of the study is quasi experimental of pretest-posttest of non-equivalent control group. Two research…

"She Has to Drink Blood of the Snake": Culture and Prior Knowledge in Science|Health Education

ERIC Educational Resources Information Center

Bricker, Leah A.; Reeve, Suzanne; Bell, Philip

2014-01-01

In this analysis, we argue that science education should attend more deeply to youths' cultural resources and practices (e.g. material, social, and intellectual). Inherent in our argument is a call for revisiting conceptions of "prior knowledge" to theorize how people make sense of the complex ecologies of experience, ideas, and cultural…

Effects of Different Types of True-False Questions on Memory Awareness and Long-Term Retention

ERIC Educational Resources Information Center

Schaap, Lydia; Verkoeijen, Peter; Schmidt, Henk

2014-01-01

This study investigated the effects of two different true-false questions on memory awareness and long-term retention of knowledge. Participants took four subsequent knowledge tests on curriculum learning material that they studied at different retention intervals prior to the start of this study (i.e. prior to the first test). At the first and…

Effects of Prior Knowledge and Concept-Map Structure on Disorientation, Cognitive Load, and Learning

ERIC Educational Resources Information Center

Amadieu, Franck; van Gog, Tamara; Paas, Fred; Tricot, Andre; Marine, Claudette

2009-01-01

This study explored the effects of prior knowledge (high vs. low; HPK and LPK) and concept-map structure (hierarchical vs. network; HS and NS) on disorientation, cognitive load, and learning from non-linear documents on "the infection process of a retrograde virus (HIV)". Participants in the study were 24 adults. Overall subjective ratings of…

The Mediation Effect of In-Game Performance between Prior Knowledge and Posttest Score. CRESST Report 819

ERIC Educational Resources Information Center

Kerr, Deirdre; Chung, Gregory K. W. K.

2012-01-01

Though video games are commonly considered to hold great potential as learning environments, their effectiveness as a teaching tool has yet to be determined. One reason for this is that researchers often run into the problem of multicollinearity between prior knowledge, in-game performance, and posttest scores, thereby making the determination of…

Developmental Change in the Influence of Domain-General Abilities and Domain-Specific Knowledge on Mathematics Achievement: An Eight-Year Longitudinal Study

ERIC Educational Resources Information Center

Geary, David C.; Nicholas, Alan; Li, Yaoran; Sun, Jianguo

2017-01-01

The contributions of domain-general abilities and domain-specific knowledge to subsequent mathematics achievement were longitudinally assessed (n = 167) through 8th grade. First grade intelligence and working memory and prior grade reading achievement indexed domain-general effects, and domain-specific effects were indexed by prior grade…

Why is a Pomegranate an Apple? The Role of Shape, Taxonomic Relatedness, and Prior Lexical Knowledge in Children's Overextensions of "Apple" and "Dog."

ERIC Educational Resources Information Center

Gelman, Susan A.; Croft, William; Fu, Panfang; Clausner, Timothy; Gottfried, Gail

1998-01-01

Examined how object shape, taxonomic relatedness, and prior lexical knowledge influenced children's overextensions (e.g., referring to pomegranates as apples). Researchers presented items that disentangled the three factors and used a novel comprehension task where children could indicate negative exemplars. Error patterns differed by task and by…

Mixture class recovery in GMM under varying degrees of class separation: frequentist versus Bayesian estimation.

PubMed

Depaoli, Sarah

2013-06-01

Growth mixture modeling (GMM) represents a technique that is designed to capture change over time for unobserved subgroups (or latent classes) that exhibit qualitatively different patterns of growth. The aim of the current article was to explore the impact of latent class separation (i.e., how similar growth trajectories are across latent classes) on GMM performance. Several estimation conditions were compared: maximum likelihood via the expectation maximization (EM) algorithm and the Bayesian framework implementing diffuse priors, "accurate" informative priors, weakly informative priors, data-driven informative priors, priors reflecting partial-knowledge of parameters, and "inaccurate" (but informative) priors. The main goal was to provide insight about the optimal estimation condition under different degrees of latent class separation for GMM. Results indicated that optimal parameter recovery was obtained though the Bayesian approach using "accurate" informative priors, and partial-knowledge priors showed promise for the recovery of the growth trajectory parameters. Maximum likelihood and the remaining Bayesian estimation conditions yielded poor parameter recovery for the latent class proportions and the growth trajectories. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

The effect of directive tutor guidance on students' conceptual understanding of statistics in problem-based learning.

PubMed

Budé, Luc; van de Wiel, Margaretha W J; Imbos, Tjaart; Berger, Martijn P F

2011-06-01

Education is aimed at students reaching conceptual understanding of the subject matter, because this leads to better performance and application of knowledge. Conceptual understanding depends on coherent and error-free knowledge structures. The construction of such knowledge structures can only be accomplished through active learning and when new knowledge can be integrated into prior knowledge. The intervention in this study was directed at both the activation of students as well as the integration of knowledge. Undergraduate university students from an introductory statistics course, in an authentic problem-based learning (PBL) environment, were randomly assigned to conditions and measurement time points. In the PBL tutorial meetings, half of the tutors guided the discussions of the students in a traditional way. The other half guided the discussions more actively by asking directive and activating questions. To gauge conceptual understanding, the students answered open-ended questions asking them to explain and relate important statistical concepts. Results of the quantitative analysis show that providing directive tutor guidance improved understanding. Qualitative data of students' misconceptions seem to support this finding. Long-term retention of the subject matter seemed to be inadequate. ©2010 The British Psychological Society.

Automatic Depth Extraction from 2D Images Using a Cluster-Based Learning Framework.

PubMed

Herrera, Jose L; Del-Blanco, Carlos R; Garcia, Narciso

2018-07-01

There has been a significant increase in the availability of 3D players and displays in the last years. Nonetheless, the amount of 3D content has not experimented an increment of such magnitude. To alleviate this problem, many algorithms for converting images and videos from 2D to 3D have been proposed. Here, we present an automatic learning-based 2D-3D image conversion approach, based on the key hypothesis that color images with similar structure likely present a similar depth structure. The presented algorithm estimates the depth of a color query image using the prior knowledge provided by a repository of color + depth images. The algorithm clusters this database attending to their structural similarity, and then creates a representative of each color-depth image cluster that will be used as prior depth map. The selection of the appropriate prior depth map corresponding to one given color query image is accomplished by comparing the structural similarity in the color domain between the query image and the database. The comparison is based on a K-Nearest Neighbor framework that uses a learning procedure to build an adaptive combination of image feature descriptors. The best correspondences determine the cluster, and in turn the associated prior depth map. Finally, this prior estimation is enhanced through a segmentation-guided filtering that obtains the final depth map estimation. This approach has been tested using two publicly available databases, and compared with several state-of-the-art algorithms in order to prove its efficiency.

PRIOR-WK&E: Social Software for Policy Making in the Knowledge Society

NASA Astrophysics Data System (ADS)

Turón, Alberto; Aguarón, Juan; Escobar, María Teresa; Gallardo, Carolina; Moreno-Jiménez, José María; Salazar, José Luis

This paper presents a social software application denominated as PRIOR-WK&E. It has been developed by the Zaragoza Multicriteria Decision Making Group (GDMZ) with the aim of responding to the challenges of policy making in the Knowledge Society. Three specific modules have been added to PRIOR, the collaborative tool used by the research group (GDMZ) for considering the multicriteria selection of a discrete set of alternatives. The first module (W), that deals with multiactor decision making through the Web, and the second (K), that concerns the extraction and diffusion of knowledge related to the scientific resolution of the problem, were explained in [1]. The new application strengthens securitization and includes a third module (E) that evaluates the effectiveness of public administrations policy making.

Towards building a disease-phenotype knowledge base: extracting disease-manifestation relationship from literature

PubMed Central

Xu, Rong; Li, Li; Wang, QuanQiu

2013-01-01

Motivation: Systems approaches to studying phenotypic relationships among diseases are emerging as an active area of research for both novel disease gene discovery and drug repurposing. Currently, systematic study of disease phenotypic relationships on a phenome-wide scale is limited because large-scale machine-understandable disease–phenotype relationship knowledge bases are often unavailable. Here, we present an automatic approach to extract disease–manifestation (D-M) pairs (one specific type of disease–phenotype relationship) from the wide body of published biomedical literature. Data and Methods: Our method leverages external knowledge and limits the amount of human effort required. For the text corpus, we used 119 085 682 MEDLINE sentences (21 354 075 citations). First, we used D-M pairs from existing biomedical ontologies as prior knowledge to automatically discover D-M–specific syntactic patterns. We then extracted additional pairs from MEDLINE using the learned patterns. Finally, we analysed correlations between disease manifestations and disease-associated genes and drugs to demonstrate the potential of this newly created knowledge base in disease gene discovery and drug repurposing. Results: In total, we extracted 121 359 unique D-M pairs with a high precision of 0.924. Among the extracted pairs, 120 419 (99.2%) have not been captured in existing structured knowledge sources. We have shown that disease manifestations correlate positively with both disease-associated genes and drug treatments. Conclusions: The main contribution of our study is the creation of a large-scale and accurate D-M phenotype relationship knowledge base. This unique knowledge base, when combined with existing phenotypic, genetic and proteomic datasets, can have profound implications in our deeper understanding of disease etiology and in rapid drug repurposing. Availability: http://nlp.case.edu/public/data/DMPatternUMLS/ Contact: rxx@case.edu PMID:23828786

Knowledge does not protect against illusory truth.

PubMed

Fazio, Lisa K; Brashier, Nadia M; Payne, B Keith; Marsh, Elizabeth J

2015-10-01

In daily life, we frequently encounter false claims in the form of consumer advertisements, political propaganda, and rumors. Repetition may be one way that insidious misconceptions, such as the belief that vitamin C prevents the common cold, enter our knowledge base. Research on the illusory truth effect demonstrates that repeated statements are easier to process, and subsequently perceived to be more truthful, than new statements. The prevailing assumption in the literature has been that knowledge constrains this effect (i.e., repeating the statement "The Atlantic Ocean is the largest ocean on Earth" will not make you believe it). We tested this assumption using both normed estimates of knowledge and individuals' demonstrated knowledge on a postexperimental knowledge check (Experiment 1). Contrary to prior suppositions, illusory truth effects occurred even when participants knew better. Multinomial modeling demonstrated that participants sometimes rely on fluency even if knowledge is also available to them (Experiment 2). Thus, participants demonstrated knowledge neglect, or the failure to rely on stored knowledge, in the face of fluent processing experiences. (c) 2015 APA, all rights reserved).

Prospective regularization design in prior-image-based reconstruction

NASA Astrophysics Data System (ADS)

Dang, Hao; Siewerdsen, Jeffrey H.; Webster Stayman, J.

2015-12-01

Prior-image-based reconstruction (PIBR) methods leveraging patient-specific anatomical information from previous imaging studies and/or sequences have demonstrated dramatic improvements in dose utilization and image quality for low-fidelity data. However, a proper balance of information from the prior images and information from the measurements is required (e.g. through careful tuning of regularization parameters). Inappropriate selection of reconstruction parameters can lead to detrimental effects including false structures and failure to improve image quality. Traditional methods based on heuristics are subject to error and sub-optimal solutions, while exhaustive searches require a large number of computationally intensive image reconstructions. In this work, we propose a novel method that prospectively estimates the optimal amount of prior image information for accurate admission of specific anatomical changes in PIBR without performing full image reconstructions. This method leverages an analytical approximation to the implicitly defined PIBR estimator, and introduces a predictive performance metric leveraging this analytical form and knowledge of a particular presumed anatomical change whose accurate reconstruction is sought. Additionally, since model-based PIBR approaches tend to be space-variant, a spatially varying prior image strength map is proposed to optimally admit changes everywhere in the image (eliminating the need to know change locations a priori). Studies were conducted in both an ellipse phantom and a realistic thorax phantom emulating a lung nodule surveillance scenario. The proposed method demonstrated accurate estimation of the optimal prior image strength while achieving a substantial computational speedup (about a factor of 20) compared to traditional exhaustive search. Moreover, the use of the proposed prior strength map in PIBR demonstrated accurate reconstruction of anatomical changes without foreknowledge of change locations in phantoms where the optimal parameters vary spatially by an order of magnitude or more. In a series of studies designed to explore potential unknowns associated with accurate PIBR, optimal prior image strength was found to vary with attenuation differences associated with anatomical change but exhibited only small variations as a function of the shape and size of the change. The results suggest that, given a target change attenuation, prospective patient-, change-, and data-specific customization of the prior image strength can be performed to ensure reliable reconstruction of specific anatomical changes.

Accessing and Integrating Data and Knowledge for Biomedical Research

PubMed Central

Burgun, A.; Bodenreider, O.

2008-01-01

Summary Objectives To review the issues that have arisen with the advent of translational research in terms of integration of data and knowledge, and survey current efforts to address these issues. Methods Using examples form the biomedical literature, we identified new trends in biomedical research and their impact on bioinformatics. We analyzed the requirements for effective knowledge repositories and studied issues in the integration of biomedical knowledge. Results New diagnostic and therapeutic approaches based on gene expression patterns have brought about new issues in the statistical analysis of data, and new workflows are needed are needed to support translational research. Interoperable data repositories based on standard annotations, infrastructures and services are needed to support the pooling and meta-analysis of data, as well as their comparison to earlier experiments. High-quality, integrated ontologies and knowledge bases serve as a source of prior knowledge used in combination with traditional data mining techniques and contribute to the development of more effective data analysis strategies. Conclusion As biomedical research evolves from traditional clinical and biological investigations towards omics sciences and translational research, specific needs have emerged, including integrating data collected in research studies with patient clinical data, linking omics knowledge with medical knowledge, modeling the molecular basis of diseases, and developing tools that support in-depth analysis of research data. As such, translational research illustrates the need to bridge the gap between bioinformatics and medical informatics, and opens new avenues for biomedical informatics research. PMID:18660883

The Best of Both Worlds: The Benefits of Open-specialized and Closed-diverse Syndication Networks for New Ventures' Success.

PubMed

Ter Wal, Anne L J; Alexy, Oliver; Block, Jörn; Sandner, Philipp G

2016-09-01

Open networks give actors non-redundant information that is diverse, while closed networks offer redundant information that is easier to interpret. Integrating arguments about network structure and the similarity of actors' knowledge, we propose two types of network configurations that combine diversity and ease of interpretation. Closed-diverse networks offer diversity in actors' knowledge domains and shared third-party ties to help in interpreting that knowledge. In open-specialized networks, structural holes offer diversity, while shared interpretive schema and overlap between received information and actors' prior knowledge help in interpreting new information without the help of third parties. In contrast, actors in open-diverse networks suffer from information overload due to the lack of shared schema or overlapping prior knowledge for the interpretation of diverse information, and actors in closed-specialized networks suffer from overembeddedness because they cannot access diverse information. Using CrunchBase data on early-stage venture capital investments in the U.S. information technology sector, we test the effect of investors' social capital on the success of their portfolio ventures. We find that ventures have the highest chances of success if their syndicating investors have either open-specialized or closed-diverse networks. These effects are manifested beyond the direct effects of ventures' or investors' quality and are robust to controlling for the possibility that certain investors could have chosen more promising ventures at the time of first funding.

Breastfeeding knowledge, attitudes, prior exposure, and intent among undergraduate students.

PubMed

Kavanagh, Katherine F; Lou, Zixin; Nicklas, Jennifer C; Habibi, Mona F; Murphy, Lee T

2012-11-01

Understanding breastfeeding knowledge, attitudes, and exposures among nonpregnant youth who are likely to be future parents may provide significant pathways to successfully increasing breastfeeding as the normal, accepted way of feeding infants. However, based on a recent review of the literature, only 3 studies have assessed these factors in nonpregnant, young adults in the United States in the past 10 years. The objective of this study was to gather more recent data regarding breastfeeding knowledge, attitudes, and prior exposure among undergraduate university students. This was a cross-sectional survey, conducted in November 2010. A convenience sample, consisting of undergraduates in attendance in 2 sections of an introductory nutrition class at a large research university, was used for this project (N = 248). Breastfeeding knowledge was relatively good. However, overall breastfeeding attitudes were more neutral, which appeared to be explained by the belief that breastfeeding is painful, restrictive, and inconvenient, both in general and specifically for the working mother. Though support for breastfeeding in public was low, men were significantly less likely than women to believe it to be embarrassing or unacceptable. In addition, breastfeeding attitudes were more positive among older students and those who were breastfed as infants. Those who were breastfed as infants were also significantly more likely to intend to breastfeed future children. Though this sample indicates good breastfeeding knowledge, attitudes were more neutral, and support for breastfeeding in public appears low. This finding is contradictory and warrants further exploration.

Continuity and change: the interpretation of illness in an Anishinaabe (Ojibway) community.

PubMed

Garro, L C

1990-12-01

Rich descriptions of Anishinaabe medical knowledge and the cultural meanings associated with illness are available in the anthropological literature, especially in the writings of A.I. Hallowell. Most of this work is based on fieldwork carried out prior to 1940 and was often motivated by a desire to reconstruct the pre-contact situation. Since that time, there have been numerous changes affecting health status and health care. This paper examines lay medical knowledge in a contemporary Canadian Anishinaabeg community, with particular attention to change and continuity in the way people explain and respond to the occurrence of illness.

Developing Year 2 Students' Theory of Biology with Concepts of the Gene and DNA

ERIC Educational Resources Information Center

Venville, Grady; Donovan, Jenny

2007-01-01

This paper presents a case study of a teaching intervention designed to enrich Year 2 students' theory of biology through the introduction of causal mechanisms of inheritance such as the gene and DNA. The researchers worked collaboratively with the classroom teacher to design the intervention based on the students' prior knowledge of living things…

Surface shape analysis of rough lumber for wane detection

Treesearch

Sang-Mook Lee; A. Lynn Abbott; Daniel L. Schmoldt

2003-01-01

The initial breakdown of hardwood logs into lumber produces boards with rough surfaces. These boards contain wane (missing wood that emanates from the log exterior, often containing residual bark) that is removed by edge and trim cuts prior to sale. Because hardwood lumber value is determined based on board size and quality, knowledge of wane position and defects is...

The Effects of Repetition and L1 Lexicalization on Incidental Vocabulary Acquisition by Iranian EFL Learners

ERIC Educational Resources Information Center

Heidari-Shahreza, Mohammad Ali; Tavakoli, Mansoor

2016-01-01

Based on a prior study by Chen and Truscott, the present study investigated the possible effects of repetition (repeated exposure) and L1 lexicalization on the incidental acquisition and retention of 10 English target words by 90 Persian-speaking EFL learners at an Iranian university. Seven aspects of vocabulary knowledge were measured, including…

Prior Knowledge of Potential School-Based Violence: Information Students Learn May Prevent a Targeted Attack

ERIC Educational Resources Information Center

Pollack, William S.; Modzeleski, William; Rooney, Georgeann

2008-01-01

In the wake of several high-profile shootings at schools in the United States, most notably the shootings that occurred at Columbine High School on April 20, 1999, the United States Secret Service (Secret Service) and the United States Department of Education (ED) embarked on a collaborative endeavor to study incidents of planned (or…

How to Achieve Synergy between Medical Education and Cognitive Neuroscience? An Exercise on Prior Knowledge in Understanding

ERIC Educational Resources Information Center

Ruiter, Dirk J.; van Kesteren, Marlieke T. R.; Fernandez, Guillen

2012-01-01

A major challenge in contemporary research is how to connect medical education and cognitive neuroscience and achieve synergy between these domains. Based on this starting point we discuss how this may result in a common language about learning, more educationally focused scientific inquiry, and multidisciplinary research projects. As the topic of…

Toward End-to-End Face Recognition Through Alignment Learning

NASA Astrophysics Data System (ADS)

Zhong, Yuanyi; Chen, Jiansheng; Huang, Bo

2017-08-01

Plenty of effective methods have been proposed for face recognition during the past decade. Although these methods differ essentially in many aspects, a common practice of them is to specifically align the facial area based on the prior knowledge of human face structure before feature extraction. In most systems, the face alignment module is implemented independently. This has actually caused difficulties in the designing and training of end-to-end face recognition models. In this paper we study the possibility of alignment learning in end-to-end face recognition, in which neither prior knowledge on facial landmarks nor artificially defined geometric transformations are required. Specifically, spatial transformer layers are inserted in front of the feature extraction layers in a Convolutional Neural Network (CNN) for face recognition. Only human identity clues are used for driving the neural network to automatically learn the most suitable geometric transformation and the most appropriate facial area for the recognition task. To ensure reproducibility, our model is trained purely on the publicly available CASIA-WebFace dataset, and is tested on the Labeled Face in the Wild (LFW) dataset. We have achieved a verification accuracy of 99.08\\% which is comparable to state-of-the-art single model based methods.

Calibration of Magnetometers with GNSS Receivers and Magnetometer-Aided GNSS Ambiguity Fixing

PubMed Central

Henkel, Patrick

2017-01-01

Magnetometers provide compass information, and are widely used for navigation, orientation and alignment of objects. As magnetometers are affected by sensor biases and eventually by systematic distortions of the Earth magnetic field, a calibration is needed. In this paper, a method for calibration of magnetometers with three Global Navigation Satellite System (GNSS) receivers is presented. We perform a least-squares estimation of the magnetic flux and sensor biases using GNSS-based attitude information. The attitude is obtained from the relative positions between the GNSS receivers in the North-East-Down coordinate frame and prior knowledge of these relative positions in the platform’s coordinate frame. The relative positions and integer ambiguities of the periodic carrier phase measurements are determined with an integer least-squares estimation using an integer decorrelation and sequential tree search. Prior knowledge on the relative positions is used to increase the success rate of ambiguity fixing. We have validated the proposed method with low-cost magnetometers and GNSS receivers on a vehicle in a test drive. The calibration enabled a consistent heading determination with an accuracy of five degrees. This precise magnetometer-based attitude information allows an instantaneous GNSS integer ambiguity fixing. PMID:28594369

Calibration of Magnetometers with GNSS Receivers and Magnetometer-Aided GNSS Ambiguity Fixing.

PubMed

Henkel, Patrick

2017-06-08

Magnetometers provide compass information, and are widely used for navigation, orientation and alignment of objects. As magnetometers are affected by sensor biases and eventually by systematic distortions of the Earth magnetic field, a calibration is needed. In this paper, a method for calibration of magnetometers with three Global Navigation Satellite System (GNSS) receivers is presented. We perform a least-squares estimation of the magnetic flux and sensor biases using GNSS-based attitude information. The attitude is obtained from the relative positions between the GNSS receivers in the North-East-Down coordinate frame and prior knowledge of these relative positions in the platform's coordinate frame. The relative positions and integer ambiguities of the periodic carrier phase measurements are determined with an integer least-squares estimation using an integer decorrelation and sequential tree search. Prior knowledge on the relative positions is used to increase the success rate of ambiguity fixing. We have validated the proposed method with low-cost magnetometers and GNSS receivers on a vehicle in a test drive. The calibration enabled a consistent heading determination with an accuracy of five degrees. This precise magnetometer-based attitude information allows an instantaneous GNSS integer ambiguity fixing.

Requirements analysis, domain knowledge, and design

NASA Technical Reports Server (NTRS)

Potts, Colin

1988-01-01

Two improvements to current requirements analysis practices are suggested: domain modeling, and the systematic application of analysis heuristics. Domain modeling is the representation of relevant application knowledge prior to requirements specification. Artificial intelligence techniques may eventually be applicable for domain modeling. In the short term, however, restricted domain modeling techniques, such as that in JSD, will still be of practical benefit. Analysis heuristics are standard patterns of reasoning about the requirements. They usually generate questions of clarification or issues relating to completeness. Analysis heuristics can be represented and therefore systematically applied in an issue-based framework. This is illustrated by an issue-based analysis of JSD's domain modeling and functional specification heuristics. They are discussed in the context of the preliminary design of simple embedded systems.

Dutch home-based pre-reading intervention with children at familial risk of dyslexia.

PubMed

van Otterloo, Sandra G; van der Leij, Aryan

2009-12-01

Children (5 and 6 years old, n = 30) at familial risk of dyslexia received a home-based intervention that focused on phoneme awareness and letter knowledge in the year prior to formal reading instruction. The children were compared to a no-training at-risk control group (n = 27), which was selected a year earlier. After training, we found a small effect on a composite score of phoneme awareness (d = 0.29) and a large effect on receptive letter knowledge (d = 0.88). In first grade, however, this did not result in beneficial effects for the experimental group in word reading and spelling. Results are compared to three former intervention studies in The Netherlands and comparable studies from Denmark and Australia.

University Students' Knowledge Structures and Informal Reasoning on the Use of Genetically Modified Foods: Multidimensional Analyses

NASA Astrophysics Data System (ADS)

Wu, Ying-Tien

2013-10-01

This study aims to provide insights into the role of learners' knowledge structures about a socio-scientific issue (SSI) in their informal reasoning on the issue. A total of 42 non-science major university students' knowledge structures and informal reasoning were assessed with multidimensional analyses. With both qualitative and quantitative analyses, this study revealed that those students with more extended and better-organized knowledge structures, as well as those who more frequently used higher-order information processing modes, were more oriented towards achieving a higher-level informal reasoning quality. The regression analyses further showed that the "richness" of the students' knowledge structures explained 25 % of the variation in their rebuttal construction, an important indicator of reasoning quality, indicating the significance of the role of students' sophisticated knowledge structure in SSI reasoning. Besides, this study also provides some initial evidence for the significant role of the "core" concept within one's knowledge structure in one's SSI reasoning. The findings in this study suggest that, in SSI-based instruction, science instructors should try to identify students' core concepts within their prior knowledge regarding the SSI, and then they should try to guide students to construct and structure relevant concepts or ideas regarding the SSI based on their core concepts. Thus, students could obtain extended and well-organized knowledge structures, which would then help them achieve better learning transfer in dealing with SSIs.

Superposing pure quantum states with partial prior information

NASA Astrophysics Data System (ADS)

Dogra, Shruti; Thomas, George; Ghosh, Sibasish; Suter, Dieter

2018-05-01

The principle of superposition is an intriguing feature of quantum mechanics, which is regularly exploited in many different circumstances. A recent work [M. Oszmaniec et al., Phys. Rev. Lett. 116, 110403 (2016), 10.1103/PhysRevLett.116.110403] shows that the fundamentals of quantum mechanics restrict the process of superimposing two unknown pure states, even though it is possible to superimpose two quantum states with partial prior knowledge. The prior knowledge imposes geometrical constraints on the choice of input states. We discuss an experimentally feasible protocol to superimpose multiple pure states of a d -dimensional quantum system and carry out an explicit experimental realization for two single-qubit pure states with partial prior information on a two-qubit NMR quantum information processor.

The Impacts of Virtual Manipulatives and Prior Knowledge on Geometry Learning Performance in Junior High School

ERIC Educational Resources Information Center

Lee, Chun-Yi; Chen, Ming-Jang

2014-01-01

Previous studies on the effects of virtual and physical manipulatives have failed to consider the impact of prior knowledge on the efficacy of manipulatives. This study focuses on the learning of plane geometry in junior high schools, including the sum of interior angles in polygons, the sum of exterior angles in polygons, and the properties of…

How Word Decoding, Vocabulary and Prior Topic Knowledge Predict Reading Comprehension. A Study of Language-Minority Students in Norwegian Fifth Grade Classrooms

ERIC Educational Resources Information Center

Rydland, Veslemoy; Aukrust, Vibeke Grover; Fulland, Helene

2012-01-01

This study examined the contribution of word decoding, first-language (L1) and second-language (L2) vocabulary and prior topic knowledge to L2 reading comprehension. For measuring reading comprehension we employed two different reading tasks: Woodcock Passage Comprehension and a researcher-developed content-area reading assignment (the Global…

Effects of Reading Ability, Prior Knowledge, Topic Interest, and Locus of Control on At-Risk College Students' Use of Graphic Organizers and Summarizing.

ERIC Educational Resources Information Center

Balajthy, Ernest; Weisberg, Renee

A study investigated the influence of key factors (general comprehension ability, prior knowledge of passage topic, interest in passage topic, and locus of control) on training at-risk college students in the use of graphic organizers as a cognitive learning strategy. Subjects, 60 college freshmen required to take a developmental reading/study…

Prior-knowledge-based feedforward network simulation of true boiling point curve of crude oil.

PubMed

Chen, C W; Chen, D Z

2001-11-01

Theoretical results and practical experience indicate that feedforward networks can approximate a wide class of functional relationships very well. This property is exploited in modeling chemical processes. Given finite and noisy training data, it is important to encode the prior knowledge in neural networks to improve the fit precision and the prediction ability of the model. In this paper, as to the three-layer feedforward networks and the monotonic constraint, the unconstrained method, Joerding's penalty function method, the interpolation method, and the constrained optimization method are analyzed first. Then two novel methods, the exponential weight method and the adaptive method, are proposed. These methods are applied in simulating the true boiling point curve of a crude oil with the condition of increasing monotonicity. The simulation experimental results show that the network models trained by the novel methods are good at approximating the actual process. Finally, all these methods are discussed and compared with each other.

Self-Monitoring and Knowledge-Building in Learning by Teaching

ERIC Educational Resources Information Center

Roscoe, Rod D.

2014-01-01

Prior research has established that learning by teaching depends upon peer tutors' engagement in knowledge-building, in which tutors integrate their knowledge and generate new knowledge through reasoning. However, many tutors adopt a "knowledge-telling bias" defined by shallow summarizing of source materials and didactic lectures.…

Lending a Helping Hand: Voluntary Engagement in Knowledge Sharing

ERIC Educational Resources Information Center

Mergel, Ines; Lazer, David; Binz-Scharf, Maria Christina

2008-01-01

Knowledge is essential for the functioning of every social system, especially for professionals in knowledge-intensive organisations. Since individuals do not possess all the work-related knowledge that they require, they turn to others in search for that knowledge. While prior research has mainly focused on antecedents and consequences of…

Science Literacy and Prior Knowledge of Astronomy MOOC Students

NASA Astrophysics Data System (ADS)

Impey, Chris David; Buxner, Sanlyn; Wenger, Matthew; Formanek, Martin

2018-01-01

Many of science classes offered on Coursera fall into fall into the category of general education or general interest classes for lifelong learners, including our own, Astronomy: Exploring Time and Space. Very little is known about the backgrounds and prior knowledge of these students. In this talk we present the results of a survey of our Astronomy MOOC students. We also compare these results to our previous work on undergraduate students in introductory astronomy courses. Survey questions examined student demographics and motivations as well as their science and information literacy (including basic science knowledge, interest, attitudes and beliefs, and where they get their information about science). We found that our MOOC students are different than the undergraduate students in more ways than demographics. Many MOOC students demonstrated high levels of science and information literacy. With a more comprehensive understanding of our students’ motivations and prior knowledge about science and how they get their information about science, we will be able to develop more tailored learning experiences for these lifelong learners.

Memory and the Moses illusion: failures to detect contradictions with stored knowledge yield negative memorial consequences.

PubMed

Bottoms, Hayden C; Eslick, Andrea N; Marsh, Elizabeth J

2010-08-01

Although contradictions with stored knowledge are common in daily life, people often fail to notice them. For example, in the Moses illusion, participants fail to notice errors in questions such as "How many animals of each kind did Moses take on the Ark?" despite later showing knowledge that the Biblical reference is to Noah, not Moses. We examined whether error prevalence affected participants' ability to detect distortions in questions, and whether this in turn had memorial consequences. Many of the errors were overlooked, but participants were better able to catch them when they were more common. More generally, the failure to detect errors had negative memorial consequences, increasing the likelihood that the errors were used to answer later general knowledge questions. Methodological implications of this finding are discussed, as it suggests that typical analyses likely underestimate the size of the Moses illusion. Overall, answering distorted questions can yield errors in the knowledge base; most importantly, prior knowledge does not protect against these negative memorial consequences.

Meeting the Discipline-Culture Framework of Physics Knowledge: A Teaching Experience in Italian Secondary School

NASA Astrophysics Data System (ADS)

Levrini, Olivia; Bertozzi, Eugenio; Gagliardi, Marta; Tomasini, Nella Grimellini; Pecori, Barbara; Tasquier, Giulia; Galili, Igal

2014-09-01

The paper deals with physics teaching/learning in high school. An investigation in three upper secondary school classes in Italy explored the reactions of students to a structuring lecture on optics within the discipline-culture (DC) framework that organises physics knowledge around four interrelated fundamental theories of light. The lecture presented optics as an unfolding conceptual discourse of physicists regarding the nature of light. Along with the knowledge constructed in a school course of a scientific lyceum, the students provided epistemological comments, displaying their perception of physics knowledge presented in the classroom. Students' views and knowledge were investigated by questionnaires prior to and after the lecture and in special discussions held in each class. They revealed a variety of attitudes and views which allowed inferences about the potential of the DC framework in an educational context. The findings and interpretation indicate the positive and stimulating impact of the lecture and the way in which DC-based approach to knowledge organization makes physics at school cultural and attractive.

Bayesian analysis of caustic-crossing microlensing events

NASA Astrophysics Data System (ADS)

Cassan, A.; Horne, K.; Kains, N.; Tsapras, Y.; Browne, P.

2010-06-01

Aims: Caustic-crossing binary-lens microlensing events are important anomalous events because they are capable of detecting an extrasolar planet companion orbiting the lens star. Fast and robust modelling methods are thus of prime interest in helping to decide whether a planet is detected by an event. Cassan introduced a new set of parameters to model binary-lens events, which are closely related to properties of the light curve. In this work, we explain how Bayesian priors can be added to this framework, and investigate on interesting options. Methods: We develop a mathematical formulation that allows us to compute analytically the priors on the new parameters, given some previous knowledge about other physical quantities. We explicitly compute the priors for a number of interesting cases, and show how this can be implemented in a fully Bayesian, Markov chain Monte Carlo algorithm. Results: Using Bayesian priors can accelerate microlens fitting codes by reducing the time spent considering physically implausible models, and helps us to discriminate between alternative models based on the physical plausibility of their parameters.

The structural approach to shared knowledge: an application to engineering design teams.

PubMed

Avnet, Mark S; Weigel, Annalisa L

2013-06-01

We propose a methodology for analyzing shared knowledge in engineering design teams. Whereas prior work has focused on shared knowledge in small teams at a specific point in time, the model presented here is both scalable and dynamic. By quantifying team members' common views of design drivers, we build a network of shared mental models to reveal the structure of shared knowledge at a snapshot in time. Based on a structural comparison of networks at different points in time, a metric of change in shared knowledge is computed. Analysis of survey data from 12 conceptual space mission design sessions reveals a correlation between change in shared knowledge and each of several system attributes, including system development time, system mass, and technological maturity. From these results, we conclude that an early period of learning and consensus building could be beneficial to the design of engineered systems. Although we do not examine team performance directly, we demonstrate that shared knowledge is related to the technical design and thus provide a foundation for improving design products by incorporating the knowledge and thoughts of the engineering design team into the process.

The influence of activation level on belief bias in relational reasoning.

PubMed

Banks, Adrian P

2013-04-01

A novel explanation of belief bias in relational reasoning is presented based on the role of working memory and retrieval in deductive reasoning, and the influence of prior knowledge on this process. It is proposed that belief bias is caused by the believability of a conclusion in working memory which influences its activation level, determining its likelihood of retrieval and therefore its effect on the reasoning process. This theory explores two main influences of belief on the activation levels of these conclusions. First, believable conclusions have higher activation levels and so are more likely to be recalled during the evaluation of reasoning problems than unbelievable conclusions, and therefore, they have a greater influence on the reasoning process. Secondly, prior beliefs about the conclusion have a base level of activation and may be retrieved when logically irrelevant, influencing the evaluation of the problem. The theory of activation and memory is derived from the Atomic Components of Thought-Rational (ACT-R) cognitive architecture and so this account is formalized in an ACT-R cognitive model. Two experiments were conducted to test predictions of this model. Experiment 1 tested strength of belief and Experiment 2 tested the impact of a concurrent working memory load. Both of these manipulations increased the main effect of belief overall and in particular raised belief-based responding in indeterminately invalid problems. These effects support the idea that the activation level of conclusions formed during reasoning influences belief bias. This theory adds to current explanations of belief bias by providing a detailed specification of the role of working memory and how it is influenced by prior knowledge. Copyright © 2012 Cognitive Science Society, Inc.

Atypical combinations and scientific impact.

PubMed

Uzzi, Brian; Mukherjee, Satyam; Stringer, Michael; Jones, Ben

2013-10-25

Novelty is an essential feature of creative ideas, yet the building blocks of new ideas are often embodied in existing knowledge. From this perspective, balancing atypical knowledge with conventional knowledge may be critical to the link between innovativeness and impact. Our analysis of 17.9 million papers spanning all scientific fields suggests that science follows a nearly universal pattern: The highest-impact science is primarily grounded in exceptionally conventional combinations of prior work yet simultaneously features an intrusion of unusual combinations. Papers of this type were twice as likely to be highly cited works. Novel combinations of prior work are rare, yet teams are 37.7% more likely than solo authors to insert novel combinations into familiar knowledge domains.

Optimal Multiple Surface Segmentation With Shape and Context Priors

PubMed Central

Bai, Junjie; Garvin, Mona K.; Sonka, Milan; Buatti, John M.; Wu, Xiaodong

2014-01-01

Segmentation of multiple surfaces in medical images is a challenging problem, further complicated by the frequent presence of weak boundary evidence, large object deformations, and mutual influence between adjacent objects. This paper reports a novel approach to multi-object segmentation that incorporates both shape and context prior knowledge in a 3-D graph-theoretic framework to help overcome the stated challenges. We employ an arc-based graph representation to incorporate a wide spectrum of prior information through pair-wise energy terms. In particular, a shape-prior term is used to penalize local shape changes and a context-prior term is used to penalize local surface-distance changes from a model of the expected shape and surface distances, respectively. The globally optimal solution for multiple surfaces is obtained by computing a maximum flow in a low-order polynomial time. The proposed method was validated on intraretinal layer segmentation of optical coherence tomography images and demonstrated statistically significant improvement of segmentation accuracy compared to our earlier graph-search method that was not utilizing shape and context priors. The mean unsigned surface positioning errors obtained by the conventional graph-search approach (6.30 ± 1.58 μm) was improved to 5.14 ± 0.99 μm when employing our new method with shape and context priors. PMID:23193309

The Cure: Design and Evaluation of a Crowdsourcing Game for Gene Selection for Breast Cancer Survival Prediction

PubMed Central

Loguercio, Salvatore; Griffith, Obi L; Nanis, Max; Wu, Chunlei; Su, Andrew I

2014-01-01

Background Molecular signatures for predicting breast cancer prognosis could greatly improve care through personalization of treatment. Computational analyses of genome-wide expression datasets have identified such signatures, but these signatures leave much to be desired in terms of accuracy, reproducibility, and biological interpretability. Methods that take advantage of structured prior knowledge (eg, protein interaction networks) show promise in helping to define better signatures, but most knowledge remains unstructured. Crowdsourcing via scientific discovery games is an emerging methodology that has the potential to tap into human intelligence at scales and in modes unheard of before. Objective The main objective of this study was to test the hypothesis that knowledge linking expression patterns of specific genes to breast cancer outcomes could be captured from players of an open, Web-based game. We envisioned capturing knowledge both from the player’s prior experience and from their ability to interpret text related to candidate genes presented to them in the context of the game. Methods We developed and evaluated an online game called The Cure that captured information from players regarding genes for use as predictors of breast cancer survival. Information gathered from game play was aggregated using a voting approach, and used to create rankings of genes. The top genes from these rankings were evaluated using annotation enrichment analysis, comparison to prior predictor gene sets, and by using them to train and test machine learning systems for predicting 10 year survival. Results Between its launch in September 2012 and September 2013, The Cure attracted more than 1000 registered players, who collectively played nearly 10,000 games. Gene sets assembled through aggregation of the collected data showed significant enrichment for genes known to be related to key concepts such as cancer, disease progression, and recurrence. In terms of the predictive accuracy of models trained using this information, these gene sets provided comparable performance to gene sets generated using other methods, including those used in commercial tests. The Cure is available on the Internet. Conclusions The principal contribution of this work is to show that crowdsourcing games can be developed as a means to address problems involving domain knowledge. While most prior work on scientific discovery games and crowdsourcing in general takes as a premise that contributors have little or no expertise, here we demonstrated a crowdsourcing system that succeeded in capturing expert knowledge. PMID:25654473

Automatized spleen segmentation in non-contrast-enhanced MR volume data using subject-specific shape priors

NASA Astrophysics Data System (ADS)

Gloger, Oliver; Tönnies, Klaus; Bülow, Robin; Völzke, Henry

2017-07-01

To develop the first fully automated 3D spleen segmentation framework derived from T1-weighted magnetic resonance (MR) imaging data and to verify its performance for spleen delineation and volumetry. This approach considers the issue of low contrast between spleen and adjacent tissue in non-contrast-enhanced MR images. Native T1-weighted MR volume data was performed on a 1.5 T MR system in an epidemiological study. We analyzed random subsamples of MR examinations without pathologies to develop and verify the spleen segmentation framework. The framework is modularized to include different kinds of prior knowledge into the segmentation pipeline. Classification by support vector machines differentiates between five different shape types in computed foreground probability maps and recognizes characteristic spleen regions in axial slices of MR volume data. A spleen-shape space generated by training produces subject-specific prior shape knowledge that is then incorporated into a final 3D level set segmentation method. Individually adapted shape-driven forces as well as image-driven forces resulting from refined foreground probability maps steer the level set successfully to the segment the spleen. The framework achieves promising segmentation results with mean Dice coefficients of nearly 0.91 and low volumetric mean errors of 6.3%. The presented spleen segmentation approach can delineate spleen tissue in native MR volume data. Several kinds of prior shape knowledge including subject-specific 3D prior shape knowledge can be used to guide segmentation processes achieving promising results.

JANIS-2: An Improved Version of the NEA Java-based Nuclear Data Information System

NASA Astrophysics Data System (ADS)

Soppera, N.; Henriksson, H.; Nouri, A.; Nagel, P.; Dupont, E.

2005-05-01

JANIS (JAva-based Nuclear Information Software) is a display program designed to facilitate the visualisation and manipulation of nuclear data. Its objective is to allow the user of nuclear data to access numerical and graphical representations without prior knowledge of the storage format. It offers maximum flexibility for the comparison of different nuclear data sets. Features included in the latest release are described such as direct access to centralised databases through JAVA Servlet technology.

JANIS-2: An Improved Version of the NEA Java-based Nuclear Data Information System

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

Soppera, N.; Henriksson, H.; Nagel, P.

2005-05-24

JANIS (JAva-based Nuclear Information Software) is a display program designed to facilitate the visualisation and manipulation of nuclear data. Its objective is to allow the user of nuclear data to access numerical and graphical representations without prior knowledge of the storage format. It offers maximum flexibility for the comparison of different nuclear data sets. Features included in the latest release are described such as direct access to centralised databases through JAVA Servlet technology.

The Role of "Creative Transfer" in Professional Transitions

ERIC Educational Resources Information Center

Triantafyllaki, Angeliki

2016-01-01

This paper discusses the concept of "knowledge transfer" in terms of expansion of prior knowledge, creativity and approaches to generating new knowledge. It explores professional transitions in which knowledge restructuring and identity reformation are pathways into greater work flexibility and adjustment. Two studies, exploring…

Cognitive patterns of neuroanatomy concepts: Knowledge organizations that emerge from problem solving versus information gathering

NASA Astrophysics Data System (ADS)

Weidner, Jeanne Margaret O'malley

2000-10-01

This study was motivated by some of the claims that are found in the literature on Problem-Based Learning (PBL). This instructional technique, which uses case studies as its primary instructional tool, has been advanced as an alternative to traditional instruction in order to foster more meaningful, integrative learning of scientific concepts. Several of the advantages attributed to Problem-Based Learning are that it (1) is generally preferred by students because it appears to foster a more nurturing and enjoyable learning experience, (2) fosters greater retention of knowledge and concepts acquired, and (3) results in increased ability to apply this knowledge toward solving new problems. This study examines the differences that result when students learn neuroanatomy concepts under two instructional contexts: problem solving vs. information gathering. The technological resource provided to students to support learning under each of these contexts was the multimedia program BrainStorm: An Interactive Neuroanatomy Atlas (Coppa & Tancred, 1995). The study explores the influence of context with regard to subjects' performance on objective post-tests, organization of knowledge as measured by Pathfinder Networks, differential use of the multimedia software and discourse differences emerging from the transcripts. The findings support previous research in the literature that problem-solving results in less knowledge acquisition in the short term, greater retention of material over time, and a subjects' preference for the method. However, both the degree of retention and preference were influenced by subjects' prior knowledge of the material in the exercises, as there was a significant difference in performance between the two exercises: for the exercise about which subjects appeared to have greater background information, memory decay was less, and subject attitude toward the problem solving instructional format was more favorable, than for the exercise for which subjects had less prior knowledge. Subjects also used the software differently under each format with regard to modules accessed, time spent in modules, and types of information sought. In addition, analyses of the transcripts showed more numerous occurrences of explanations and summarizations in the problem-solving context, compared to the information gathering context. The attempts to show significant differences between the contexts by means of Pathfinder analyses were less than successful.

An innovative addition to team-based-learning pedagogy to enhance teaching and learning: Students' perceptions of team exams.

PubMed

Khansari, Parto S; Coyne, Leanne

The study investigates students' perceptions of the value of implementing a team exam to enhance learning prior to a summative assessment. Team exams are similar to midterm exams, except that answering questions is a team effort. Data was collected from second year pharmacy students at California Northstate University College of Pharmacy (CNUCOP) through a self-administered online survey. The survey questions included closed-ended questions to evaluate students' perception on preparedness for a summative assessment and to rank advantages and disadvantages of the team exams. Of the 40 students who completed the survey (38% response rate), 100% of participants agreed that having a team exam prior to a major exam made them feel more prepared for a major summative exam. Ninety-seven percent of students believed that the team exam helped them to identify gaps in their knowledge and 85% agreed that taking a team exam reinforced their knowledge by teaching other students. The survey results did not identify any major disadvantages to holding a team exam. Students perceived that taking a team exam prior to a midterm exam is an effective approach to review the course contents and identify areas of improvement. Copyright © 2017. Published by Elsevier Inc.

KnowLife: a versatile approach for constructing a large knowledge graph for biomedical sciences.

PubMed

Ernst, Patrick; Siu, Amy; Weikum, Gerhard

2015-05-14

Biomedical knowledge bases (KB's) have become important assets in life sciences. Prior work on KB construction has three major limitations. First, most biomedical KBs are manually built and curated, and cannot keep up with the rate at which new findings are published. Second, for automatic information extraction (IE), the text genre of choice has been scientific publications, neglecting sources like health portals and online communities. Third, most prior work on IE has focused on the molecular level or chemogenomics only, like protein-protein interactions or gene-drug relationships, or solely address highly specific topics such as drug effects. We address these three limitations by a versatile and scalable approach to automatic KB construction. Using a small number of seed facts for distant supervision of pattern-based extraction, we harvest a huge number of facts in an automated manner without requiring any explicit training. We extend previous techniques for pattern-based IE with confidence statistics, and we combine this recall-oriented stage with logical reasoning for consistency constraint checking to achieve high precision. To our knowledge, this is the first method that uses consistency checking for biomedical relations. Our approach can be easily extended to incorporate additional relations and constraints. We ran extensive experiments not only for scientific publications, but also for encyclopedic health portals and online communities, creating different KB's based on different configurations. We assess the size and quality of each KB, in terms of number of facts and precision. The best configured KB, KnowLife, contains more than 500,000 facts at a precision of 93% for 13 relations covering genes, organs, diseases, symptoms, treatments, as well as environmental and lifestyle risk factors. KnowLife is a large knowledge base for health and life sciences, automatically constructed from different Web sources. As a unique feature, KnowLife is harvested from different text genres such as scientific publications, health portals, and online communities. Thus, it has the potential to serve as one-stop portal for a wide range of relations and use cases. To showcase the breadth and usefulness, we make the KnowLife KB accessible through the health portal (http://knowlife.mpi-inf.mpg.de).

Effects of Process-Oriented and Product-Oriented Worked Examples and Prior Knowledge on Learner Problem Solving and Attitude: A Study in the Domain of Microeconomics

ERIC Educational Resources Information Center

Brooks, Christopher Darren

2009-01-01

The purpose of this study was to investigate the effectiveness of process-oriented and product-oriented worked example strategies and the mediating effect of prior knowledge (high versus low) on problem solving and learner attitude in the domain of microeconomics. In addition, the effect of these variables on learning efficiency as well as the…

Influence of Prior Knowledge and Interest on Fourth- and Fifth-Grade Passage Comprehension on the Qualitative Reading Inventory-4

ERIC Educational Resources Information Center

Clark, Mary Kristen; Kamhi, Alan G.

2014-01-01

Purpose: In 2 experiments, we examined the influence of prior knowledge and interest on 4th- and 5th-grade students' passage comprehension scores on the Qualitative Reading Inventory-4 (QRI-4) and 2 experimenter constructed passages. Method: In Experiment 1, 4th- and 5th-grade students were administered 4 Level 4 passages or 4 Level 5…

Effects of Type of Exploratory Strategy and Prior Knowledge on Middle School Students' Learning of Chemical Formulas from a 3D Role-Playing Game

ERIC Educational Resources Information Center

Chen, Ming-Puu; Wong, Yu-Ting; Wang, Li-Chun

2014-01-01

The purpose of this study was to examine the effects of the type of exploratory strategy and level of prior knowledge on middle school students' performance and motivation in learning chemical formulas via a 3D role-playing game (RPG). Two types of exploratory strategies-RPG exploratory with worked-example and RPG exploratory without…

The nature of undergraduates' conceptual understanding of oxygen transport and utilization in humans: Can cardiopulmonary simulation software enhance learning of propositional knowledge and/or diagnose alternative conceptions in novices and intermediates?

NASA Astrophysics Data System (ADS)

Wissing, Dennis Robert

The purpose of the this research was to explore undergraduates' conceptual development for oxygen transport and utilization, as a component of a cardiopulmonary physiology and advanced respiratory care course in the allied health program. This exploration focused on the student's development of knowledge and the presence of alternative conceptions, prior to, during, and after completing cardiopulmonary physiology and advanced respiratory care courses. Using the simulation program, SimBioSysTM (Samsel, 1994), student-participants completed a series of laboratory exercises focusing on cardiopulmonary disease states. This study examined data gathered from: (1) a novice group receiving the simulation program prior to instruction, (2) a novice group that experienced the simulation program following course completion in cardiopulmonary physiology, and (3) an intermediate group who experienced the simulation program following completion of formal education in Respiratory Care. This research was based on the theory of Human Constructivism as described by Mintzes, Wandersee, and Novak (1997). Data-gathering techniques were based on theories supported by Novak (1984), Wandersee (1997), and Chi (1997). Data were generated by exams, interviews, verbal analysis (Chi, 1997), and concept mapping. Results suggest that simulation may be an effective instructional method for assessing conceptual development and diagnosing alternative conceptions in undergraduates enrolled in a cardiopulmonary science program. Use of simulation in conjunction with clinical interview and concept mapping may assist in verifying gaps in learning and conceptual knowledge. This study found only limited evidence to support the use of computer simulation prior to lecture to augment learning. However, it was demonstrated that students' prelecture experience with the computer simulation helped the instructor assess what the learner knew so he or she could be taught accordingly. In addition, use of computer simulation after formal instruction was shown to be useful in aiding students identified by the instructor as needing remediation.

Comparison of Three Instructional Strategies in Food and Nutrition Education: Developing a Diet Plan for a Diabetic Case

ERIC Educational Resources Information Center

Darabi, Aubteen; Pourafshar, Shirin; Suryavanshi, Rinki; Arrington, Thomas

2016-01-01

This study examines the performance of dietitians-in-training on developing a diet plan for a diabetic patient either independently or after peer discussion. Participants (n = 58) from an undergraduate program in food and nutrition were divided into two groups based on their prior knowledge before being randomly assigned into three conditions: (1)…

Tests of a Prior Marksmanship Knowledge Predictor Test

DTIC Science & Technology

2014-01-01

shooters based on their anticipated performance. Further research and test development is needed to group Soldiers for BRM training according to...Things get more challenging, however, as the size of the instructional group increases for one simple reason: the instructor feedback that helps one ...might stand to benefit from additional instruction on sight alignment. Expanding this example to larger groups such as a platoon or company, one

Faculty Perceptions of the Need to Include Training in Pedagogy in Non-Teaching Degree Programs in Florida

ERIC Educational Resources Information Center

Robinson, Terrell Emon

2012-01-01

Just as PK-12 teachers are taught how to teach, college and university professors should also receive instruction in how to teach. They should acquire pedagogical skills and understand methods for planning and content delivery prior to entering the classroom. The knowledge base of the discipline and a focus on research are emphasized in the…

Feature Selection and Classifier Development for Radio Frequency Device Identification

DTIC Science & Technology

2015-12-01

adds important background knowledge for this research . 41 Four leading RF-based device identification methods have been proposed: Radio...appropriate level of dimensionality. Both qualitative and quantitative DRA dimensionality assessment methods are possible. Prior RF-DNA DRA research , e.g...Employing experimental designs to find optimal algorithm settings has been seen in hyperspectral anomaly detection research , c.f. [513–520], but not

Detection of entanglement with few local measurements

NASA Astrophysics Data System (ADS)

Gühne, O.; Hyllus, P.; Bruß, D.; Ekert, A.; Lewenstein, M.; Macchiavello, C.; Sanpera, A.

2002-12-01

We introduce a general method for the experimental detection of entanglement by performing only few local measurements, assuming some prior knowledge of the density matrix. The idea is based on the minimal decomposition of witness operators into a pseudomixture of local operators. We discuss an experimentally relevant case of two qubits, and show an example how bound entanglement can be detected with few local measurements.

The Extension-Reduction Strategy: Activating Prior Knowledge

ERIC Educational Resources Information Center

Sloyer, Cliff W.

2004-01-01

A mathematical problem is solved using the extension-reduction or build it up-tear it down tactic. This technique is implemented in reviving students' earlier knowledge to enable them to apply this knowledge to solving new problems.

Interplay between Content Knowledge and Scientific Argumentation

ERIC Educational Resources Information Center

Hakyolu, Hanife; Ogan-Bekiroglu, Feral

2016-01-01

This research study aimed to analyze the relationship between content knowledge and argumentation by examining students' prior subject matter knowledge and their production of arguments as well as by comparing students' arguments with their knowledge-in-use during scientific argumentation sessions. A correlational research design was carried out…

Experimental Evidence on the Impact of Food Advertising on Children's Knowledge about and Preferences for Healthful Food

PubMed Central

Reisch, Lucia A.; Gwozdz, Wencke; De Henauw, Stefaan; Lascorz, Natalia; Pigeot, Iris

2013-01-01

To understand the rising prevalence of childhood obesity in affluent societies, it is necessary to take into account the growing obesity infrastructure, which over past decades has developed into an obesogenic environment. This study examines the effects of one of the constituent factors of consumer societies and a potential contributory factor to childhood obesity: commercial food communication targeted to children. Specifically, it investigates the impact of TV advertising on children's food knowledge and food preferences and correlates these findings with their weight status. Evaluations of traditional information- and education-based interventions suggest that they may not sustainably change food patterns. Based on prior consumer research, we propose five hypotheses, which we then test using a subsample from the IDEFICS study, a large-scale pan-European intervention study on childhood obesity. The results indicate that advertising has divergent effects on children's food knowledge and preferences and that food knowledge is unrelated to food preferences. This finding has important implications for both future research and public policy. PMID:23691285

From Data to Knowledge – Promising Analytical Tools and Techniques for Capture and Reuse of Corporate Knowledge and to Aid in the State Evaluation Process

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

Danielson, Gary R.; Augustenborg, Elsa C.; Beck, Andrew E.

2010-10-29

The IAEA is challenged with limited availability of human resources for inspection and data analysis while proliferation threats increase. PNNL has a variety of IT solutions and techniques (at varying levels of maturity and development) that take raw data closer to useful knowledge, thereby assisting with and standardizing the analytical processes. This paper highlights some PNNL tools and techniques which are applicable to the international safeguards community, including: • Intelligent in-situ triage of data prior to reliable transmission to an analysis center resulting in the transmission of smaller and more relevant data sets • Capture of expert knowledge in re-usablemore » search strings tailored to specific mission outcomes • Image based searching fused with text based searching • Use of gaming to discover unexpected proliferation scenarios • Process modeling (e.g. Physical Model) as the basis for an information integration portal, which links to data storage locations along with analyst annotations, categorizations, geographic data, search strings and visualization outputs.« less

From science to action: Principles for undertaking environmental research that enables knowledge exchange and evidence-based decision-making.

PubMed

Cvitanovic, C; McDonald, J; Hobday, A J

2016-12-01

Effective conservation requires knowledge exchange among scientists and decision-makers to enable learning and support evidence-based decision-making. Efforts to improve knowledge exchange have been hindered by a paucity of empirically-grounded guidance to help scientists and practitioners design and implement research programs that actively facilitate knowledge exchange. To address this, we evaluated the Ningaloo Research Program (NRP), which was designed to generate new scientific knowledge to support evidence-based decisions about the management of the Ningaloo Marine Park in north-western Australia. Specifically, we evaluated (1) outcomes of the NRP, including the extent to which new knowledge informed management decisions; (2) the barriers that prevented knowledge exchange among scientists and managers; (3) the key requirements for improving knowledge exchange processes in the future; and (4) the core capacities that are required to support knowledge exchange processes. While the NRP generated expansive and multidisciplinary science outputs directly relevant to the management of the Ningaloo Marine Park, decision-makers are largely unaware of this knowledge and little has been integrated into decision-making processes. A range of barriers prevented efficient and effective knowledge exchange among scientists and decision-makers including cultural differences among the groups, institutional barriers within decision-making agencies, scientific outputs that were not translated for decision-makers and poor alignment between research design and actual knowledge needs. We identify a set of principles to be implemented routinely as part of any applied research program, including; (i) stakeholder mapping prior to the commencement of research programs to identify all stakeholders, (ii) research questions to be co-developed with stakeholders, (iii) implementation of participatory research approaches, (iv) use of a knowledge broker, and (v) tailored knowledge management systems. Finally, we articulate the individual, institutional and financial capacities that must be developed to underpin successful knowledge exchange strategies. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

A Comparison of Functional Models for Use in the Function-Failure Design Method

NASA Technical Reports Server (NTRS)

Stock, Michael E.; Stone, Robert B.; Tumer, Irem Y.

2006-01-01

When failure analysis and prevention, guided by historical design knowledge, are coupled with product design at its conception, shorter design cycles are possible. By decreasing the design time of a product in this manner, design costs are reduced and the product will better suit the customer s needs. Prior work indicates that similar failure modes occur with products (or components) with similar functionality. To capitalize on this finding, a knowledge base of historical failure information linked to functionality is assembled for use by designers. One possible use for this knowledge base is within the Elemental Function-Failure Design Method (EFDM). This design methodology and failure analysis tool begins at conceptual design and keeps the designer cognizant of failures that are likely to occur based on the product s functionality. The EFDM offers potential improvement over current failure analysis methods, such as FMEA, FMECA, and Fault Tree Analysis, because it can be implemented hand in hand with other conceptual design steps and carried throughout a product s design cycle. These other failure analysis methods can only truly be effective after a physical design has been completed. The EFDM however is only as good as the knowledge base that it draws from, and therefore it is of utmost importance to develop a knowledge base that will be suitable for use across a wide spectrum of products. One fundamental question that arises in using the EFDM is: At what level of detail should functional descriptions of components be encoded? This paper explores two approaches to populating a knowledge base with actual failure occurrence information from Bell 206 helicopters. Functional models expressed at various levels of detail are investigated to determine the necessary detail for an applicable knowledge base that can be used by designers in both new designs as well as redesigns. High level and more detailed functional descriptions are derived for each failed component based on NTSB accident reports. To best record this data, standardized functional and failure mode vocabularies are used. Two separate function-failure knowledge bases are then created aid compared. Results indicate that encoding failure data using more detailed functional models allows for a more robust knowledge base. Interestingly however, when applying the EFDM, high level descriptions continue to produce useful results when using the knowledge base generated from the detailed functional models.

Biomedical image segmentation using geometric deformable models and metaheuristics.

PubMed

Mesejo, Pablo; Valsecchi, Andrea; Marrakchi-Kacem, Linda; Cagnoni, Stefano; Damas, Sergio

2015-07-01

This paper describes a hybrid level set approach for medical image segmentation. This new geometric deformable model combines region- and edge-based information with the prior shape knowledge introduced using deformable registration. Our proposal consists of two phases: training and test. The former implies the learning of the level set parameters by means of a Genetic Algorithm, while the latter is the proper segmentation, where another metaheuristic, in this case Scatter Search, derives the shape prior. In an experimental comparison, this approach has shown a better performance than a number of state-of-the-art methods when segmenting anatomical structures from different biomedical image modalities. Copyright © 2013 Elsevier Ltd. All rights reserved.

Improving semantic scene understanding using prior information

NASA Astrophysics Data System (ADS)

Laddha, Ankit; Hebert, Martial

2016-05-01

Perception for ground robot mobility requires automatic generation of descriptions of the robot's surroundings from sensor input (cameras, LADARs, etc.). Effective techniques for scene understanding have been developed, but they are generally purely bottom-up in that they rely entirely on classifying features from the input data based on learned models. In fact, perception systems for ground robots have a lot of information at their disposal from knowledge about the domain and the task. For example, a robot in urban environments might have access to approximate maps that can guide the scene interpretation process. In this paper, we explore practical ways to combine such prior information with state of the art scene understanding approaches.

Pilot Study Evaluating a Practice-Based Learning and Improvement Curriculum Focusing on the Development of System-Level Quality Improvement Skills

PubMed Central

Tomolo, Anne M; Lawrence, Renée H; Watts, Brook; Augustine, Sarah; Aron, David C; Singh, Mamta K

2011-01-01

Background We developed a practice-based learning and improvement (PBLI) curriculum to address important gaps in components of content and experiential learning activities through didactics and participation in systems-level quality improvement projects that focus on making changes in health care processes. Methods We evaluated the impact of our curriculum on resident PBLI knowledge, self-efficacy, and application skills. A quasi-experimental design assessed the impact of a curriculum (PBLI quality improvement systems compared with non-PBLI) on internal medicine residents' learning during a 4-week ambulatory block. We measured application skills, self-efficacy, and knowledge by using the Systems Quality Improvement Training and Assessment Tool. Exit evaluations assessed time invested and experiences related to the team projects and suggestions for improving the curriculum. Results The 2 groups showed differences in change scores. Relative to the comparison group, residents in the PBLI curriculum demonstrated a significant increase in the belief about their ability to implement a continuous quality improvement project (P  =  .020), comfort level in developing data collection plans (P  =  .010), and total knowledge scores (P < .001), after adjusting for prior PBLI experience. Participants in the PBLI curriculum also demonstrated significant improvement in providing a more complete aim statement for a proposed project after adjusting for prior PBLI experience (P  =  .001). Exit evaluations were completed by 96% of PBLI curriculum participants who reported high satisfaction with team performance. Conclusion Residents in our curriculum showed gains in areas fundamental for PBLI competency. The observed improvements were related to fundamental quality improvement knowledge, with limited gain in application skills. This suggests that while heading in the right direction, we need to conceptualize and structure PBLI training in a way that integrates it throughout the residency program and fosters the application of this knowledge and these skills. PMID:22379523

Pilot study evaluating a practice-based learning and improvement curriculum focusing on the development of system-level quality improvement skills.

PubMed

Tomolo, Anne M; Lawrence, Renée H; Watts, Brook; Augustine, Sarah; Aron, David C; Singh, Mamta K

2011-03-01

We developed a practice-based learning and improvement (PBLI) curriculum to address important gaps in components of content and experiential learning activities through didactics and participation in systems-level quality improvement projects that focus on making changes in health care processes. We evaluated the impact of our curriculum on resident PBLI knowledge, self-efficacy, and application skills. A quasi-experimental design assessed the impact of a curriculum (PBLI quality improvement systems compared with non-PBLI) on internal medicine residents' learning during a 4-week ambulatory block. We measured application skills, self-efficacy, and knowledge by using the Systems Quality Improvement Training and Assessment Tool. Exit evaluations assessed time invested and experiences related to the team projects and suggestions for improving the curriculum. The 2 groups showed differences in change scores. Relative to the comparison group, residents in the PBLI curriculum demonstrated a significant increase in the belief about their ability to implement a continuous quality improvement project (P  =  .020), comfort level in developing data collection plans (P  =  .010), and total knowledge scores (P < .001), after adjusting for prior PBLI experience. Participants in the PBLI curriculum also demonstrated significant improvement in providing a more complete aim statement for a proposed project after adjusting for prior PBLI experience (P  =  .001). Exit evaluations were completed by 96% of PBLI curriculum participants who reported high satisfaction with team performance. Residents in our curriculum showed gains in areas fundamental for PBLI competency. The observed improvements were related to fundamental quality improvement knowledge, with limited gain in application skills. This suggests that while heading in the right direction, we need to conceptualize and structure PBLI training in a way that integrates it throughout the residency program and fosters the application of this knowledge and these skills.

Evaluation of virtual microscopy in medical histology teaching.

PubMed

Mione, Sylvia; Valcke, Martin; Cornelissen, Maria

2013-01-01

Histology stands as a major discipline in the life science curricula, and the practice of teaching it is based on theoretical didactic strategies along with practical training. Traditionally, students achieve practical competence in this subject by learning optical microscopy. Today, students can use newer information and communication technologies in the study of digital microscopic images. A virtual microscopy program was recently introduced at Ghent University. Since little empirical evidence is available concerning the impact of virtual microscopy (VM) versus optical microscopy (OM) on the acquisition of histology knowledge, this study was set up in the Faculty of Medicine and Health Sciences. A pretest-post test and cross-over design was adopted. In the first phase, the experiment yielded two groups in a total population of 199 students, Group 1 performing the practical sessions with OM versus Group 2 performing the same sessions with VM. In the second phase, the research subjects switched conditions. The prior knowledge level of all research subjects was assessed with a pretest. Knowledge acquisition was measured with a post test after each phase (T1 and T2). Analysis of covariance was carried out to study the differential gain in knowledge at T1 and T2, considering the possible differences in prior knowledge at the start of the study. The results pointed to non-significant differences at T1 and at T2. This supports the assumption that the acquisition of the histology knowledge is independent of the microscopy representation mode (VM versus OM) of the learning material. The conclusion that VM is equivalent to OM offers new directions in view of ongoing innovations in medical education technology. Copyright © 2013 American Association of Anatomists.

Expert videotape analysis and critiquing benefit laparoscopic skills training of urologists.

PubMed

Nakada, Stephen Y; Hedican, Sean P; Bishoff, Jay T; Shichman, Steven J; Wolf, J Stuart

2004-01-01

Teaching laparoscopic skills has become the focus of the latest generation of hands-on laparoscopic courses. Thirty-four practicing urologists, ages 31 to 61 years (mean, 46.6 years) with laparoscopic experience (range, 0 to 200, mean, 27.6 cases), 32 of whom had taken prior American Urological Association (AUA) laparoscopy courses, participated in an AUA-sponsored hands-on laparoscopic skills course over a 2-day period in August 2002 or March 2003. They all took a knowledge assessment examination and performed standardized tasks (rope passing, ring placement, and laparoscopic suturing and knot tying) at the beginning and the end of the course with a videotape analysis and critique. Prior to the repeat-skills assessment, each participant was individually critiqued and instructed based on a videotape review of their initial performance. The urologists also participated in a porcine laboratory and a pelvic trainer session totaling 6 hours between skills assessments. None of the participants had performed significant laparoscopic suturing prior to the course. Using Wilcoxon's signed rank test, the participants improved from a mean of 119.32 seconds to 98.36 seconds with the rope pass (P = 0.0001), and with the ring placement from a mean of 9.70/minute to 12.09/minute (P = 0.0001). All participants had significantly fewer false passes (mean, 9.35 compared with 5.21) during repeat skills assessments (P = 0.0001). Participants improved from 0.54 sutures/minute to 1.22 sutures/ minute following the video critique and practice (P = 0.0001). Degree of laparoscopic experience (number of cases), age of the urologist, and precourse knowledge (examination score) had no significant bearing on results in the initial skills assessment or in the improvement of task time (Spearman correlation coefficients). Urologists with some laparoscopic experience (mean 27.6 cases) can improve laparoscopic skills using mentored videotape analysis and experience gained from a 2-day hands-on course. Prior knowledge, degree of experience, and urologist age had no significant bearing on performance in this setting.

Practically prepared? Pre-intern student views following an education package.

PubMed

McKenzie, Susan; Mellis, Craig

2017-01-01

Graduating medical students enter their internship with varied levels of practical experience in procedural skills. To address this problem, many medical schools have introduced intensive skill training courses immediately prior to graduation. This study examines the impact of a pre-intern (PrInt) education package, consisting of a short intensive course, followed by a one-month clinical attachment. In September 2014, all PrInt students (n = 53) at the Central Clinical School (Sydney, NSW, Australia) attended three days of intensive training. This included a didactic introduction, case-based scenarios, and interactive workshops. This was followed by four weeks of targeted, experiential learning during a clinical attachment (PrInt term). Immediately prior to training and following PrInt, all students were invited to complete a six-domain questionnaire containing 40 subscale closed questions to assess their knowledge, experience, and confidence in key practical skills essential for a successful internship. A total of 41/53 (77%) students completed an identical questionnaire prior to PrInt, and 37/53 (70%) immediately following PrInt. Respondents reported statistically significant increases in their experience, ability, knowledge, and confidence in a number of domains. The key changes were the following: knowledge of pharmacy skills (mean improvement = 26.48, confidence interval 95% [CI 95%] = 17.29-35.66, p ≤ 0.0001) and management of procedural skills (mean = 24.46, CI 95% = 16.58-32.34, p ≤ 0.0001). Despite the positive overall increase in most domains, some subscale results remained low following the educational package; only 44% students had inserted a nasogastric tube; only 44% reported confidence in commencing patients on warfarin; and only 42% in managing a hospital emergency. Surprisingly, there was a slight decline both in confidence in communicating with members of the hospital team (10%) and in awareness of the causes of hypoglycemia (7%). Final year students perceived substantial benefit from an educational package specifically aimed at improving their practical skills immediately prior to internship.

Practically prepared? Pre-intern student views following an education package

PubMed Central

McKenzie, Susan; Mellis, Craig

2017-01-01

Background Graduating medical students enter their internship with varied levels of practical experience in procedural skills. To address this problem, many medical schools have introduced intensive skill training courses immediately prior to graduation. This study examines the impact of a pre-intern (PrInt) education package, consisting of a short intensive course, followed by a one-month clinical attachment. Methods In September 2014, all PrInt students (n = 53) at the Central Clinical School (Sydney, NSW, Australia) attended three days of intensive training. This included a didactic introduction, case-based scenarios, and interactive workshops. This was followed by four weeks of targeted, experiential learning during a clinical attachment (PrInt term). Immediately prior to training and following PrInt, all students were invited to complete a six-domain questionnaire containing 40 subscale closed questions to assess their knowledge, experience, and confidence in key practical skills essential for a successful internship. Results A total of 41/53 (77%) students completed an identical questionnaire prior to PrInt, and 37/53 (70%) immediately following PrInt. Respondents reported statistically significant increases in their experience, ability, knowledge, and confidence in a number of domains. The key changes were the following: knowledge of pharmacy skills (mean improvement = 26.48, confidence interval 95% [CI 95%] = 17.29–35.66, p ≤ 0.0001) and management of procedural skills (mean = 24.46, CI 95% = 16.58–32.34, p ≤ 0.0001). Despite the positive overall increase in most domains, some subscale results remained low following the educational package; only 44% students had inserted a nasogastric tube; only 44% reported confidence in commencing patients on warfarin; and only 42% in managing a hospital emergency. Surprisingly, there was a slight decline both in confidence in communicating with members of the hospital team (10%) and in awareness of the causes of hypoglycemia (7%). Conclusion Final year students perceived substantial benefit from an educational package specifically aimed at improving their practical skills immediately prior to internship. PMID:28184172

49 CFR 240.209 - Procedures for making the determination on knowledge.

Code of Federal Regulations, 2010 CFR

2010-10-01

... knowledge. 240.209 Section 240.209 Transportation Other Regulations Relating to Transportation (Continued... determination on knowledge. (a) Each railroad, prior to initially certifying or recertifying any person as an... with the requirements of § 240.125 of this part, demonstrated sufficient knowledge of the railroad's...

Activation of Background Knowledge for Inference Making: Effects on Reading Comprehension

ERIC Educational Resources Information Center

Elbro, Carsten; Buch-Iversen, Ida

2013-01-01

Failure to "activate" relevant, existing background knowledge may be a cause of poor reading comprehension. This failure may cause particular problems with inferences that depend heavily on prior knowledge. Conversely, teaching how to use background knowledge in the context of gap-filling inferences could improve reading comprehension in…

Agricultural mapping using Support Vector Machine-Based Endmember Extraction (SVM-BEE)

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

Archibald, Richard K; Filippi, Anthony M; Bhaduri, Budhendra L

Extracting endmembers from remotely sensed images of vegetated areas can present difficulties. In this research, we applied a recently developed endmember-extraction algorithm based on Support Vector Machines (SVMs) to the problem of semi-autonomous estimation of vegetation endmembers from a hyperspectral image. This algorithm, referred to as Support Vector Machine-Based Endmember Extraction (SVM-BEE), accurately and rapidly yields a computed representation of hyperspectral data that can accommodate multiple distributions. The number of distributions is identified without prior knowledge, based upon this representation. Prior work established that SVM-BEE is robustly noise-tolerant and can semi-automatically and effectively estimate endmembers; synthetic data and a geologicmore » scene were previously analyzed. Here we compared the efficacies of the SVM-BEE and N-FINDR algorithms in extracting endmembers from a predominantly agricultural scene. SVM-BEE was able to estimate vegetation and other endmembers for all classes in the image, which N-FINDR failed to do. Classifications based on SVM-BEE endmembers were markedly more accurate compared with those based on N-FINDR endmembers.« less

Challenges with Evidence-Based Management of Stable Ischemic Heart Disease.

PubMed

Patel, Amit V; Bangalore, Sripal

2017-02-01

Stable ischemic heart disease (SIHD) is a highly prevalent condition associated with increased costs, morbidity, and mortality. Management goals of SIHD can broadly be thought of in terms of improving prognosis and/or improving symptoms. Treatment options include medical therapy as well as revascularization, either with percutaneous coronary intervention or coronary artery bypass grafting. Herein, we will review the current evidence base for treatment of SIHD as well as its challenges and discuss ongoing studies to help address some of these knowledge gaps. There has been no consistent reduction in death or myocardial infarction (MI) with revascularization vs. medical therapy in patients with SIHD in contemporary trials. Angina and quality of life have been shown to be relieved more rapidly with revascularization vs. optimal medical therapy; however, the durability of these results is uncertain. There have been challenges and limitations in several of the trials addressing the optimal treatment strategy for SIHD due to potential selection bias (due to knowledge of coronary anatomy prior to randomization), patient crossover, and advances in medical therapy and revascularization strategies since trial completion. The challenges inherent to prior trials addressing the optimal management strategy for SIHD have impacted the generalizability of results to real-world cohorts. Until the results of additional ongoing trials are available, the decision for revascularization or medical therapy should be based on patients' symptoms, weighing the risks and benefits of each approach, and patient preference.

Acquired von Willebrand Syndrome Associated to Secondary IgM MGUS Emerging after Autologous Stem Cell Transplantation for AL Amyloidosis

PubMed Central

Qamar, Hina; Lee, Adrienne; Valentine, Karen; Skeith, Leslie; Jimenez-Zepeda, Victor H

2017-01-01

Acquired von Willebrand syndrome (AVWS) is a rare hemorrhagic disorder that occurs in patients with no prior personal or family history of bleeding. Here, we describe a case of AVWS occurring after autologous stem cell transplantation (ASCT). Interestingly, AVWS developed after bortezomib-based induction and conditioning regimens. Recent evidence suggests that the proximity of the bortezomib therapy to the collection of stem cells with consequent depletion of regulatory T cells after the conditioning regimen could explain some of the unusual autoimmune complications reported in patients receiving bortezomib prior to ASCT. In addition, this patient developed a secondary MGUS post-ASCT, which may have also contributed to the AVWS. To the best of our knowledge, this is the first case of post-ASCT AVWS reported. Prospective data is needed to better elucidate the mechanisms by which these unusual complications occur in patients receiving bortezomib prior to ASCT. PMID:28512563

Acquired von Willebrand Syndrome Associated to Secondary IgM MGUS Emerging after Autologous Stem Cell Transplantation for AL Amyloidosis.

PubMed

Qamar, Hina; Lee, Adrienne; Valentine, Karen; Skeith, Leslie; Jimenez-Zepeda, Victor H

2017-01-01

Acquired von Willebrand syndrome (AVWS) is a rare hemorrhagic disorder that occurs in patients with no prior personal or family history of bleeding. Here, we describe a case of AVWS occurring after autologous stem cell transplantation (ASCT). Interestingly, AVWS developed after bortezomib-based induction and conditioning regimens. Recent evidence suggests that the proximity of the bortezomib therapy to the collection of stem cells with consequent depletion of regulatory T cells after the conditioning regimen could explain some of the unusual autoimmune complications reported in patients receiving bortezomib prior to ASCT. In addition, this patient developed a secondary MGUS post-ASCT, which may have also contributed to the AVWS. To the best of our knowledge, this is the first case of post-ASCT AVWS reported. Prospective data is needed to better elucidate the mechanisms by which these unusual complications occur in patients receiving bortezomib prior to ASCT.

Building on prior knowledge without building it in.

PubMed

Hansen, Steven S; Lampinen, Andrew K; Suri, Gaurav; McClelland, James L

2017-01-01

Lake et al. propose that people rely on "start-up software," "causal models," and "intuitive theories" built using compositional representations to learn new tasks more efficiently than some deep neural network models. We highlight the many drawbacks of a commitment to compositional representations and describe our continuing effort to explore how the ability to build on prior knowledge and to learn new tasks efficiently could arise through learning in deep neural networks.

Visual representations in science education: The influence of prior knowledge and cognitive load theory on instructional design principles

NASA Astrophysics Data System (ADS)

Cook, Michelle Patrick

2006-11-01

Visual representations are essential for communicating ideas in the science classroom; however, the design of such representations is not always beneficial for learners. This paper presents instructional design considerations providing empirical evidence and integrating theoretical concepts related to cognitive load. Learners have a limited working memory, and instructional representations should be designed with the goal of reducing unnecessary cognitive load. However, cognitive architecture alone is not the only factor to be considered; individual differences, especially prior knowledge, are critical in determining what impact a visual representation will have on learners' cognitive structures and processes. Prior knowledge can determine the ease with which learners can perceive and interpret visual representations in working memory. Although a long tradition of research has compared experts and novices, more research is necessary to fully explore the expert-novice continuum and maximize the potential of visual representations.

Sleep Spindle Density Predicts the Effect of Prior Knowledge on Memory Consolidation

PubMed Central

Lambon Ralph, Matthew A.; Kempkes, Marleen; Cousins, James N.; Lewis, Penelope A.

2016-01-01

Information that relates to a prior knowledge schema is remembered better and consolidates more rapidly than information that does not. Another factor that influences memory consolidation is sleep and growing evidence suggests that sleep-related processing is important for integration with existing knowledge. Here, we perform an examination of how sleep-related mechanisms interact with schema-dependent memory advantage. Participants first established a schema over 2 weeks. Next, they encoded new facts, which were either related to the schema or completely unrelated. After a 24 h retention interval, including a night of sleep, which we monitored with polysomnography, participants encoded a second set of facts. Finally, memory for all facts was tested in a functional magnetic resonance imaging scanner. Behaviorally, sleep spindle density predicted an increase of the schema benefit to memory across the retention interval. Higher spindle densities were associated with reduced decay of schema-related memories. Functionally, spindle density predicted increased disengagement of the hippocampus across 24 h for schema-related memories only. Together, these results suggest that sleep spindle activity is associated with the effect of prior knowledge on memory consolidation. SIGNIFICANCE STATEMENT Episodic memories are gradually assimilated into long-term memory and this process is strongly influenced by sleep. The consolidation of new information is also influenced by its relationship to existing knowledge structures, or schemas, but the role of sleep in such schema-related consolidation is unknown. We show that sleep spindle density predicts the extent to which schemas influence the consolidation of related facts. This is the first evidence that sleep is associated with the interaction between prior knowledge and long-term memory formation. PMID:27030764

The influence of analogical reasoning instruction on the pedagogical reasoning ability of preservice elementary teachers

NASA Astrophysics Data System (ADS)

James, Mark Charles

Novice teachers with little prior knowledge of science concepts often resort to teaching science as a litany of jargon and definitions. The primary objective of this study was to establish the efficacy of analogy-based pedagogy on influencing the teaching performance of preservice elementary teachers, a group that has been identified for their particular difficulties in teaching science content. While numerous studies have focused on the efficacy of analogy-based instruction on the conceptual knowledge of learners, this was the first study to focus on the influence of analogy-based pedagogy instruction on the teaching performance of novice teachers. The study utilized a treatment/contrast group design where treatment and contrast groups were obtained from intact sections of a university course on methods of teaching science for preservice elementary education students. Preservice teachers in the treatment group were provided instruction in pedagogy that guided them in the generation of analogies to aid in the explanation phase of their learning cycle lessons. The process of generating and evaluating analogies for use in teaching was instrumental in focusing the preservice teachers' lesson planning efforts on critical attributes in target concepts, and away from misplaced concentrations on jargon and definitions. Teaching performance was primarily analyzed using coded indicants of Shulman's (1986) six stages of pedagogical reasoning ability. The primary data source was preservice teachers' work submitted for a major course assignment where the preservice teachers interviewed an elementary school student to gauge prior knowledge of Newtonian force concepts. The culmination of the semester-long assignment was the design of an individualized lesson that was presented by the preservice teachers to individual elementary school students. The results of this study strongly suggest that instruction in methods to include analogy-based pedagogy within a learning cycle lesson format can positively influence the pedagogical reasoning ability of some elementary preservice teachers. The study also provided insights into techniques that can be utilized to introduce analogy-based pedagogy to elementary preservice teachers.

Tuberculosis and HIV at the national level in Kenya: results from the Second Kenya AIDS Indicator Survey.

PubMed

Mbithi, Agneta; Gichangi, Anthony; Kim, Andrea A; Katana, Abraham; Weyenga, Herman; Williamson, John; Robinson, Katherine; Oluoch, Tom; Maina, William K; Kellogg, Timothy A; De Cock, Kevin M

2014-05-01

Co-morbidity with tuberculosis and HIV is a common cause of mortality in sub-Saharan Africa. In the second Kenya AIDS Indicator Survey, we collected data on knowledge and experience of HIV and tuberculosis, as well as on access to and coverage of relevant treatment services and antiretroviral therapy (ART) in Kenya. A national, population-based household survey was conducted from October 2012 to February 2013. Information was collected through household questionnaires, and blood samples were taken for HIV, CD4 cell counts, and HIV viral load testing at a central laboratory. Overall, 13,720 persons aged 15-64 years participated; 96.7% [95% confidence interval (CI): 96.3 to 97.1] had heard of tuberculosis, of whom 2.0% (95% CI: 1.7 to 2.2) reported having prior tuberculosis. Among those with laboratory-confirmed HIV infection, 11.6% (95% CI: 8.9 to 14.3) reported prior tuberculosis. The prevalence of laboratory-confirmed HIV infection in persons reporting prior tuberculosis was 33.2% (95% CI: 26.2 to 40.2) compared to 5.1% (95% CI: 4.5 to 5.8) in persons without prior tuberculosis. Among those in care, coverage of ART for treatment-eligible persons was 100% for those with prior tuberculosis and 88.6% (95% CI: 81.6 to 95.7) for those without. Among all HIV-infected persons, ART coverage among treatment-eligible persons was 86.9% (95% CI: 74.2 to 99.5) for persons with prior tuberculosis and 58.3% (95% CI: 47.6 to 69.0) for those without. Morbidity from tuberculosis and HIV remain major health challenges in Kenya. Tuberculosis is an important entry point for HIV diagnosis and treatment. Lack of knowledge of HIV serostatus is an obstacle to access to HIV services and timely ART for prevention of HIV transmission and HIV-associated disease, including tuberculosis.

House Parties: An Innovative Model for Outreach and Community-Based Health Education.

PubMed

Anderson-Reeves, Timika; Goodman, Jacqueline; Bragg, Brian; Leruth, Chelsey

2017-12-01

Purpose To connect low resource communities to innovative services that address gaps in health access and knowledge. Description We describe the house party model, as a community-based workshop approach to health education developed by the Westside Healthy Start program (WHS) in Chicago, Illinois. Key elements of the WHS house party model include use of community health workers as facilitators, collaboration with participants and community-based organizations, referrals to health care and social services, and engagement strategies such as interactive activities, personal stories, and discussion. Assessment In 2014 and 2015, WHS completed 23 house parties with 271 participants, delivering education on relevant maternal and child health (MCH) topics. Participants demonstrated improvements in knowledge of several health-related areas. About half of participants were able to identify causes or signs of preterm labor prior to the house party, compared to over 80% after. In addition, 94% of participants rated the house party workshops "excellent" or "good". Conclusion House parties are a promising strategy for increasing knowledge about MCH topics and linking hard-to-reach populations to resources in the community.

45 CFR 1616.3 - Qualifications.

Code of Federal Regulations, 2010 CFR

2010-10-01

...) Academic training and performance; (b) The nature and extent of prior legal experience; (c) Knowledge and understanding of the legal problems and needs of the poor; (d) Prior working experience in the client community...