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Pezzulo, Giovanni; Cartoni, Emilio; Rigoli, Francesco; io-Lopez, Léo; Friston, Karl – Learning & Memory, 2016
Balancing habitual and deliberate forms of choice entails a comparison of their respective merits--the former being faster but inflexible, and the latter slower but more versatile. Here, we show that arbitration between these two forms of control can be derived from first principles within an Active Inference scheme. We illustrate our arguments…
Descriptors: Interference (Learning), Epistemology, Physiology, Neurology
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Chow, Alan F.; Van Haneghan, James P. – Educational Studies in Mathematics, 2016
This study reports the results of a study examining how easily students are able to transfer frequency solutions to conditional probability problems to novel situations. University students studied either a problem solved using the traditional Bayes formula format or using a natural frequency (tree diagram) format. In addition, the example problem…
Descriptors: Probability, College Students, Mathematical Formulas, Bayesian Statistics
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Sabitha, A. Sai; Mehrotra, Deepti; Bansal, Abhay; Sharma, B. K. – Education and Information Technologies, 2016
Open educational resources (OER) are digitised material freely available to the students and self learners. Many institutions had initiated in incorporating these OERs in their higher educational system, to improve the quality of teaching and learning. These resources promote individualised study, collaborative learning. If they are coupled with…
Descriptors: Integrated Learning Systems, Cooperative Learning, Metadata, Bayesian Statistics
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Landy, David; Silbert, Noah; Goldin, Aleah – Cognitive Science, 2013
Despite their importance in public discourse, numbers in the range of 1 million to 1 trillion are notoriously difficult to understand. We examine magnitude estimation by adult Americans when placing large numbers on a number line and when qualitatively evaluating descriptions of imaginary geopolitical scenarios. Prior theoretical conceptions…
Descriptors: Numbers, Computation, Adults, Models
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Holden, Mark P.; Newcombe, Nora S.; Shipley, Thomas F. – Cognition, 2013
The ability to remember spatial locations is critical to human functioning, both in an evolutionary and in an everyday sense. Yet spatial memories and judgments often show systematic errors and biases. Bias has been explained by models such as the Category Adjustment model (CAM), in which fine-grained and categorical information about locations…
Descriptors: Memory, Geographic Location, Spatial Ability, Bias
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Blackwell, Matthew; Honaker, James; King, Gary – Sociological Methods & Research, 2017
We extend a unified and easy-to-use approach to measurement error and missing data. In our companion article, Blackwell, Honaker, and King give an intuitive overview of the new technique, along with practical suggestions and empirical applications. Here, we offer more precise technical details, more sophisticated measurement error model…
Descriptors: Error of Measurement, Correlation, Simulation, Bayesian Statistics
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Wu, Charley M.; Meder, Björn; Filimon, Flavia; Nelson, Jonathan D. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2017
While the influence of presentation formats have been widely studied in Bayesian reasoning tasks, we present the first systematic investigation of how presentation formats influence information search decisions. Four experiments were conducted across different probabilistic environments, where subjects (N = 2,858) chose between 2 possible search…
Descriptors: Questioning Techniques, Information Seeking, Search Strategies, Search Engines
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Stamey, James D.; Beavers, Daniel P.; Sherr, Michael E. – Sociological Methods & Research, 2017
Survey data are often subject to various types of errors such as misclassification. In this article, we consider a model where interest is simultaneously in two correlated response variables and one is potentially subject to misclassification. A motivating example of a recent study of the impact of a sexual education course for adolescents is…
Descriptors: Bayesian Statistics, Classification, Models, Correlation
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Marsh, John E.; Hughes, Robert W.; Sörqvist, Patrik; Beaman, C. Philip; Jones, Dylan M. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2015
Two experiments examined the extent to which erroneous recall blocks veridical recall using, as a vehicle for study, the disruptive impact of distractors that are semantically similar to a list of words presented for free recall. Instructing participants to avoid erroneous recall of to-be-ignored spoken distractors attenuated their recall but this…
Descriptors: Foreign Countries, Recall (Psychology), Experiments, Semantics
Lang, Charles William McLeod – ProQuest LLC, 2015
Personalization, the idea that teaching can be tailored to each students' needs, has been a goal for the educational enterprise for at least 2,500 years (Regian, Shute, & Shute, 2013, p.2). Recently personalization has picked up speed with the advent of mobile computing, the Internet and increases in computer processing power. These changes…
Descriptors: Individualized Instruction, Electronic Learning, Mathematics, Bayesian Statistics
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Virtanen, T. E.; Lerkkanen, M.-K.; Poikkeus, A.-M.; Kuorelahti, M. – Scandinavian Journal of Educational Research, 2018
Self-ratings of behavioural engagement, cognitive engagement and school burnout were used in person-centred analyses to identify latent profiles among 2,485 Finnish lower-secondary school students. Three profiles were identified: high-engagement/low-burnout (40.6% of the sample), average-engagement/average-burnout (53.9%), and…
Descriptors: Learner Engagement, Burnout, Academic Achievement, Secondary School Students
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Stewart, G. B.; Mengersen, K.; Meader, N. – Research Synthesis Methods, 2014
Bayesian networks (BNs) are tools for representing expert knowledge or evidence. They are especially useful for synthesising evidence or belief concerning a complex intervention, assessing the sensitivity of outcomes to different situations or contextual frameworks and framing decision problems that involve alternative types of intervention.…
Descriptors: Bayesian Statistics, Networks, Cognitive Mapping, Data Collection
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Wellwood, Alexis; Gagliardi, Annie; Lidz, Jeffrey – Language Learning and Development, 2016
Acquiring the correct meanings of words expressing quantities ("seven, most") and qualities ("red, spotty") present a challenge to learners. Understanding how children succeed at this requires understanding, not only of what kinds of data are available to them, but also the biases and expectations they bring to the learning…
Descriptors: Syntax, Computational Linguistics, Task Analysis, Prediction
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Strietholt, Rolf; Rosén, Monica – Measurement: Interdisciplinary Research and Perspectives, 2016
Since the start of the new millennium, international comparative large-scale studies have become one of the most well-known areas in the field of education. However, the International Association for the Evaluation of Educational Achievement (IEA) has already been conducting international comparative studies for about half a century. The present…
Descriptors: Reading Tests, Comparative Analysis, Comparative Education, Trend Analysis
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Chiu, Chia-Yi; Köhn, Hans-Friedrich; Wu, Huey-Min – International Journal of Testing, 2016
The Reduced Reparameterized Unified Model (Reduced RUM) is a diagnostic classification model for educational assessment that has received considerable attention among psychometricians. However, the computational options for researchers and practitioners who wish to use the Reduced RUM in their work, but do not feel comfortable writing their own…
Descriptors: Educational Diagnosis, Classification, Models, Educational Assessment
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