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Chunking versus Transitional Probabilities: Differentiating between Theories of Statistical Learning
Emerson, Samantha N.; Conway, Christopher M. – Cognitive Science, 2023
There are two main approaches to how statistical patterns are extracted from sequences: The transitional probability approach proposes that statistical learning occurs through the computation of probabilities between items in a sequence. The chunking approach, including models such as PARSER and TRACX, proposes that units are extracted as chunks.…
Descriptors: Statistics Education, Learning Processes, Learning Theories, Pattern Recognition
Toukiloglou, Pavlos; Xinogalos, Stelios – Journal of Educational Computing Research, 2023
Serious games are a growing field in academic research and they are considered an effective tool for education. Game-based learning invokes motivation and engagement in students resulting in effective instructional outcomes. An essential aspect of a serious game is the method of support for presenting the teaching material and providing feedback.…
Descriptors: Educational Games, Programming, Sequential Learning, Cognitive Processes
María Armario; José María Oliva; Natalia Jiménez-Tenorio – International Journal of Science Education, 2025
The progress achieved in the models used by future Spanish primary school teachers on the phenomenon of tides is analysed after implementing a modelling-based didactic sequence. It was implemented throughout ten sessions in two classes (N = 88). An open-ended questionnaire was used as a data collecting instrument. Based on prior studies and the…
Descriptors: Preservice Teachers, Elementary School Teachers, Foreign Countries, Scientific Concepts
Jinnie Shin; Bowen Wang; Wallace N. Pinto Junior; Mark J. Gierl – Large-scale Assessments in Education, 2024
The benefits of incorporating process information in a large-scale assessment with the complex micro-level evidence from the examinees (i.e., process log data) are well documented in the research across large-scale assessments and learning analytics. This study introduces a deep-learning-based approach to predictive modeling of the examinee's…
Descriptors: Prediction, Models, Problem Solving, Performance
Joaquín Cañero-Arias; Ángel Blanco-López; José María Oliva – International Journal of Science Education, 2024
This research integrates context-based learning and modelling. It presents a teaching-learning sequence (TLS) about the dissolution of gases in liquids using carbonated drinks as the context. The impact of the TLS is analysed in a longitudinal short-term study involving two groups of learners aged 13-14 years old (n=53). The results led us to…
Descriptors: Foreign Countries, Science Instruction, Models, Secondary School Science
Dvir, Michal; Ben-Zvi, Dani – Instructional Science: An International Journal of the Learning Sciences, 2023
Estimating and accounting for statistical uncertainty have become essential in today's information age, and crucial for cultivating a sound decision making citizenry. Engaging with statistical uncertainty early on can support the gradual development of uncertainty-related considerations that are often challenging to foster at any age. Statistical…
Descriptors: Learning Processes, Computation, Numeracy, Attitudes
Dayal, Priya Dharshni; Ali-Chand, Zakia – New Zealand Journal of Educational Studies, 2022
This paper discusses the significance of model-based teaching on the topic of ionic and metallic bonding in Year 12 Chemistry in a New Zealand secondary school. Based on the conceptualization of the sub-macro level understanding of the bonding structure and properties of ionic and metallic compounds, models and drawings were used as an effective…
Descriptors: Science Instruction, Teaching Methods, Chemistry, Models

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