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Shahat, Mohamed A.; Boone, William J.; Ambusaidi, Abdullah K.; Al Bahri, Khalsa; Ohle-Peters, Annika – Journal of Baltic Science Education, 2022
A range of pedagogical learning theories has been proposed to guide science teachers' classroom teaching. This study presents the results of the development and use of an 18-item Arabic language rating scale survey to assess Omani teachers' (N = 400) views towards the application of selected pedagogical learning theories of potential use in their…
Descriptors: Science Teachers, Teacher Surveys, Teacher Attitudes, Item Analysis
Martínez-Zarzuelo, Angélica; Roanes-Lozano, Eugenio; Fernández-Díaz, María José – International Journal for Technology in Mathematics Education, 2017
The educational laws establish an organization and a grouping of the contents of the educational system they rule. As far as we know, the set of experts who design it neither follow precise objective criteria nor use computer tools. That is why they are not usually rotund. We consider that defining precise objective criteria is the key to develop…
Descriptors: Network Analysis, Secondary School Students, Mathematics Instruction, Teaching Methods
Cai, Jinfa, Ed. – National Council of Teachers of Mathematics, 2017
This volume, a comprehensive survey and critical analysis of today's issues in mathematics education, distills research to build knowledge and capacity in the field. The compendium is a valuable new resource that provides the most comprehensive evidence about what is known about research in mathematics education. The 38 chapters present five…
Descriptors: Mathematics Education, Educational Research, Educational Trends, Trend Analysis
Stewart, Wayne; Stewart, Sepideh – PRIMUS, 2014
For many scientists, researchers and students Markov chain Monte Carlo (MCMC) simulation is an important and necessary tool to perform Bayesian analyses. The simulation is often presented as a mathematical algorithm and then translated into an appropriate computer program. However, this can result in overlooking the fundamental and deeper…
Descriptors: Markov Processes, Monte Carlo Methods, College Mathematics, Mathematics Instruction
Nakamura, Yasuyuki; Yasutake, Koichi; Yamakawa, Osamu – International Association for Development of the Information Society, 2012
There are some mathematical learning models of collaborative learning, with which we can learn how students obtain knowledge and we expect to design effective education. We put together those models and classify into three categories; model by differential equations, so-called Ising spin and a stochastic process equation. Some of the models do not…
Descriptors: Cooperative Learning, Mathematical Models, Probability, Calculus
Fisher, Anna V.; Matlen, Bryan J.; Godwin, Karrie E. – Cognition, 2011
Prior research suggests that preschoolers can generalize object properties based on category information conveyed by semantically-similar labels. However, previous research did not control for co-occurrence probability of labels in natural speech. The current studies re-assessed children's generalization with semantically-similar labels.…
Descriptors: Semantics, Generalization, Probability, Inferences
Buehner, Marc J.; May, Jon – Journal of Problem Solving, 2009
Contemporary theories of Human Causal Induction assume that causal knowledge is inferred from observable contingencies. While this assumption is well supported by empirical results, it fails to consider an important problem-solving aspect of causal induction in real time: In the absence of well structured learning trials, it is not clear whether…
Descriptors: Attribution Theory, Problem Solving, Logical Thinking, Time
Huh, Namjung; Jo, Suhyun; Kim, Hoseok; Sul, Jung Hoon; Jung, Min Whan – Learning & Memory, 2009
Reinforcement learning theories postulate that actions are chosen to maximize a long-term sum of positive outcomes based on value functions, which are subjective estimates of future rewards. In simple reinforcement learning algorithms, value functions are updated only by trial-and-error, whereas they are updated according to the decision-maker's…
Descriptors: Learning Theories, Animals, Rewards, Probability
Smith, Troy A.; Kimball, Daniel R. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2010
Most modern research on the effects of feedback during learning has assumed that feedback is an error correction mechanism. Recent studies of feedback-timing effects have suggested that feedback might also strengthen initially correct responses. In an experiment involving cued recall of trivia facts, we directly tested several theories of…
Descriptors: Feedback (Response), Error Correction, Probability, Experiments
Temperley, David – Cognitive Science, 2008
This study presents a probabilistic model of melody perception, which infers the key of a melody and also judges the probability of the melody itself. The model uses Bayesian reasoning: For any "surface" pattern and underlying "structure," we can infer the structure maximizing P(structure [vertical bar] surface) based on knowledge of P(surface,…
Descriptors: Expectation, Intervals, Probability, Information Retrieval
Gierl, Mark J.; Cui, Ying – Measurement: Interdisciplinary Research and Perspectives, 2008
One promising application of diagnostic classification models (DCM) is in the area of cognitive diagnostic assessment in education. However, the successful application of DCM in educational testing will likely come with a price--and this price may be in the form of new test development procedures and practices required to yield data that satisfy…
Descriptors: Educational Testing, Classification, Psychometrics, Test Construction

Heritage, Raymond S. – Mathematics in School, 1974
This article is the third in a series on the teaching of sets and some of the reasons for doing so. A discussion is presented of the use of set language in teaching concepts from logic, probability and algebra. (JP)
Descriptors: Algebra, Learning, Learning Theories, Logic
Garling, Tommy; Gamble, Amelie; Juliusson, Asgeir – Journal of Experimental Psychology: Applied, 2007
In 3 experiments, the authors investigated learning of the value of money from product prices in an unfamiliar currency when the prices are proportional to quantity. In support of the second stage of a hypothesized 2-stage process of learning, Experiment 1, in which 32 undergraduates participated, shows that response times for inferences of…
Descriptors: Learning Processes, Inferences, Learning Theories, Reaction Time

Greeno, James G.; And Others – Psychometrika, 1971
Earlier Analyses are shown to involve special cases of the equations developed here; also that a general four-state chain has the same parameter space as an all-or-none model if and only if its representation with an observable absorbing state is lumpable into a Markov chain with three states. (Author/GS)
Descriptors: Learning Theories, Mathematical Models, Probability, Research Methodology

Fischer, Gloria J. – American Journal of Psychology, 1971
Descriptors: Environmental Influences, Hypothesis Testing, Learning Theories, Probability