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English, Lyn D. – ZDM: Mathematics Education, 2023
This article proposes an interconnected framework, "Ways of thinking in STEM-based Problem Solving," which addresses cognitive processes that facilitate learning, problem solving, and interdisciplinary concept development. The framework comprises critical thinking, incorporating critical mathematical modelling and philosophical inquiry,…
Descriptors: STEM Education, Problem Solving, Cognitive Processes, Learning
Thiessen, Erik D.; Pavlik, Philip I., Jr. – Cognitive Science, 2013
Statistical learning refers to the ability to identify structure in the input based on its statistical properties. For many linguistic structures, the relevant statistical features are distributional: They are related to the frequency and variability of exemplars in the input. These distributional regularities have been suggested to play a role in…
Descriptors: Mathematical Models, Memory, Language Acquisition, Learning
Griffiths, Thomas L.; Lewandowsky, Stephan; Kalish, Michael L. – Cognitive Science, 2013
Information changes as it is passed from person to person, with this process of cultural transmission allowing the minds of individuals to shape the information that they transmit. We present mathematical models of cultural transmission which predict that the amount of information passed from person to person should affect the rate at which that…
Descriptors: Culture, Information Dissemination, Mathematical Models, Prediction
Vogt, Paul – Cognitive Science, 2012
Cross-situational learning has recently gained attention as a plausible candidate for the mechanism that underlies the learning of word-meaning mappings. In a recent study, Blythe and colleagues have studied how many trials are theoretically required to learn a human-sized lexicon using cross-situational learning. They show that the level of…
Descriptors: Vocabulary Development, Learning, Mathematical Models, Robustness (Statistics)
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
Wiedmann, Michael; Leach, Ryan C.; Rummel, Nikol; Wiley, Jennifer – Instructional Science: An International Journal of the Learning Sciences, 2012
Schwartz and Martin ("Cogn Instr" 22:129-184, 2004) as well as Kapur ("Instr Sci", this issue, 2012) have found that students can be better prepared to learn about mathematical formulas when they try to invent them in small groups before receiving the canonical formula from a lesson. The purpose of the present research was to investigate how the…
Descriptors: Mathematical Formulas, Intellectual Property, Learning, Multivariate Analysis
Mischo, Christoph; Maaß, Katja – Journal of Education and Training Studies, 2013
This paper presents an intervention study whose aim was to promote teacher beliefs about mathematics and learning mathematics and student competences in mathematical modeling. In the intervention, teachers received written curriculum materials about mathematical modeling. The concept underlying the materials was based on constructivist ideas and…
Descriptors: Mathematical Models, Teacher Attitudes, Beliefs, Intervention
Peer reviewedGentner, Dedre; Markman, Arthur B. – American Psychologist, 1997
It is suggested that both similarity and analogy involve a process of structural alignment and mapping. The structure mapping process is described as it has been worked out for analogy, and this view is then extended to similarity and used to generate new predictions. (SLD)
Descriptors: Analogy, Learning, Mathematical Models, Prediction
Peer reviewedWolter, David G.; Earl, Robert W. – Psychometrika, 1972
Descriptors: Bayesian Statistics, Learning, Mathematical Models, Probability
Peer reviewedOwston, Ronald D. – Psychometrika, 1979
The method of scoring is used to obtain maximum likelihood estimates of the parameters in White and Clark's (EJ 075 122) learning hierarchy validation model. From the proportion of the population possessing only the superordinate skill in a pair of hierarchical skills, and its variance, the hypothesis of inclusion is tested. (Author/CTM)
Descriptors: Learning, Mathematical Models, Organization, Scoring
Snelsire, Robert W. – 1969
The problem of designing computer programs that will approach human capabilities in pattern recognition is discussed. Human beings are much better at recognizing patterns that are highly structured than at recognizing patterns that are not. In contrast, a computer system's performance in pattern recognition is almost independent of the amount of…
Descriptors: Classification, Game Theory, Learning, Mathematical Models
Brieske, Gerald F. – 1969
The study is concerned with the problem of determining stimulus discrimination thresholds in non-human vertebrates. In constrast to conventional methods of teaching differentiation of various stimuli by fixed reinforcement schedules, stimulus discrimination threshold determination is related to a teaching system that adjusts to continuously…
Descriptors: Behavior, Environment, Interaction, Learning
Peer reviewedWittmann, E. – International Journal of Mathematical Education in Science and Technology, 1975
In this paper the mathematical structures of Bourbaki, the Piagetian developmental structures, and Polya's heuristic structures are compared. (SD)
Descriptors: Comparative Analysis, Learning, Mathematical Models, Mathematics
Paulson, James A. – 1973
Three different strategies of choosing items for presentation in a simple list learning situation are compared. The instructional task was to teach the correct response to a number of stimulus items, using a paired-associate teaching procedure. Only one item could be presented on a given trial and the total number of trials was limited. The…
Descriptors: Educational Psychology, Instruction, Learning, Learning Theories
Peer reviewedKingma, Johannes; Van Den Bos, Kees P. – Educational and Psychological Measurement, 1987
A FORTRAN 77 program is described that computes both the different response success-error patterns and their summary statistics for learning and forgetting in fixed trial experiments using a two-stage Markov model. (Author/GDC)
Descriptors: Computer Software, Educational Experiments, Hypothesis Testing, Learning

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