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Alejandro Ramírez-Contreras; Leopoldo Zúñiga-Silva; Ezequiel Ojeda-Gómez – International Electronic Journal of Mathematics Education, 2023
This paper reports on an exploratory study about probabilistic intuition in learning mathematics for decision-making. The analysis was carried out on a group of high school students in relation to their probabilistic intuition in problem-solving, after performing playful learning activities on a simulation platform specifically designed for this…
Descriptors: High School Students, Mathematics Instruction, Intuition, Probability
María del Mar López-Martín; María Burgos Navarro; Verónica Albanese – Statistics Education Research Journal, 2025
To ensure the learning of mathematics, teachers must be able to analyse their students' mathematical practices when solving tasks, interpret the difficulties that students encounter, and decide how to manage students' difficulties. This competence in didactic analysis and intervention allows teachers to adapt their teaching to meet individual…
Descriptors: Statistics Education, Mathematics Instruction, Student Needs, Preservice Teachers
Li, Xiao; Xu, Hanchen; Zhang, Jinming; Chang, Hua-hua – Journal of Educational and Behavioral Statistics, 2023
The adaptive learning problem concerns how to create an individualized learning plan (also referred to as a learning policy) that chooses the most appropriate learning materials based on a learner's latent traits. In this article, we study an important yet less-addressed adaptive learning problem--one that assumes continuous latent traits.…
Descriptors: Learning Processes, Models, Algorithms, Individualized Instruction
Essien, Anthony A. – ZDM: Mathematics Education, 2021
The teaching of mathematics is mostly done with tasks that learners and teachers do or solve, in and outside of class. These tasks, which are used to illustrate concepts in mathematics, are referred to in this paper as examples in mathematics. Examples that teachers choose and use are fundamental to what mathematics is taught and learned, and what…
Descriptors: Multilingualism, Probability, Mathematics Instruction, Teaching Methods
Batista, Rita; Borba, Rute; Henriques, Ana – Statistics Education Research Journal, 2022
This study aims to analyse the reasoning that children and adults with the same school level use to assess and justify the fairness of games, considering aspects of probability such as randomness, sample space, and comparison of probabilities. Data collection included a Piagetian clinical interview based on games of chance. The results showed that…
Descriptors: Probability, Statistics Education, Intervention, Thinking Skills
Huijser, Stefan; Taatgen, Niels A.; van Vugt, Marieke K. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2021
Preparing for the future during ongoing activities is an essential skill. Yet it is currently unclear to what extent we can prepare for the future in parallel with another task. In two experiments, we investigated how characteristics of a present task influenced whether and when participants prepared for the future, as well as its usefulness. We…
Descriptors: Futures (of Society), Cognitive Processes, Planning, Short Term Memory
Letkowski, Jerzy – Journal of Instructional Pedagogies, 2018
Single-period inventory models with uncertain demand are very well known in the business analytics community. Typically, such models are rule-based functions, or sets of functions, of one decision variable (order quantity) and one random variable (demand). In academics, the models are taught selectively and usually not completely. Students are…
Descriptors: Models, Data Analysis, Decision Making, Teaching Methods
Bramley, Neil R.; Lagnado, David A.; Speekenbrink, Maarten – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2015
Interacting with a system is key to uncovering its causal structure. A computational framework for interventional causal learning has been developed over the last decade, but how real causal learners might achieve or approximate the computations entailed by this framework is still poorly understood. Here we describe an interactive computer task in…
Descriptors: Intervention, Memory, Cognitive Processes, Models
Klein, Joseph – Journal of Education and Training Studies, 2014
Recent neurophysiological advances may support the advisability of delaying decisions when possible and practical. An empirical study, based on an educational dilemma, compared the outcome of postponing an educational decision overnight or for a longer period. 340 teachers read a report on an educational dilemma and gave an immediate opinion.…
Descriptors: Interdisciplinary Approach, Research Utilization, Educational Research, Educational Improvement
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
Thomas, Rick P.; Dougherty, Michael R.; Sprenger, Amber M.; Harbison, J. Isaiah – Psychological Review, 2008
Diagnostic hypothesis-generation processes are ubiquitous in human reasoning. For example, clinicians generate disease hypotheses to explain symptoms and help guide treatment, auditors generate hypotheses for identifying sources of accounting errors, and laypeople generate hypotheses to explain patterns of information (i.e., data) in the…
Descriptors: Hypothesis Testing, Learning Processes, Probability, Thinking Skills

Sampson, Jeffrey R.; Chen, I-Ngo – Psychological Reports, 1971
Descriptors: Decision Making, Learning Processes, Learning Theories, Males
Christ, Richard E. – J Gen Psychol, 1969
Descriptors: Cognitive Processes, Decision Making, Learning Processes, Memory
Frank, Michael J.; Claus, Eric D. – Psychological Review, 2006
The authors explore the division of labor between the basal ganglia-dopamine (BG-DA) system and the orbitofrontal cortex (OFC) in decision making. They show that a primitive neural network model of the BG-DA system slowly learns to make decisions on the basis of the relative probability of rewards but is not as sensitive to (a) recency or (b) the…
Descriptors: Brain, Decision Making, Probability, Reinforcement
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers