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Clement, Benjamin; Oudeyer, Pierre-Yves; Lopes, Manuel – International Educational Data Mining Society, 2016
Online planning of good teaching sequences has the potential to provide a truly personalized teaching experience with a huge impact on the motivation and learning of students. In this work we compare two main approaches to achieve such a goal, POMDPs that can find an optimal long-term path, and Multi-armed bandits that optimize policies locally…
Descriptors: Intelligent Tutoring Systems, Markov Processes, Models, Teaching Methods
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Shen, Shitian; Mostafavi, Behrooz; Barnes, Tiffany; Chi, Min – Journal of Educational Data Mining, 2018
An important goal in the design and development of Intelligent Tutoring Systems (ITSs) is to have a system that adaptively reacts to students' behavior in the short term and effectively improves their learning performance in the long term. Inducing effective pedagogical strategies that accomplish this goal is an essential challenge. To address…
Descriptors: Teaching Methods, Markov Processes, Decision Making, Rewards
Budgett, Stephanie; Pfannkuch, Maxine – Teaching and Learning Research Initiative, 2016
This report summarises the research activities and findings from the TLRI-funded project entitled "Visualising Chance: Learning Probability Through Modelling." This exploratory study was a 2-year collaboration among two researchers, two conceptual software developers/interactive graphics experts, three university lecturers/practitioners,…
Descriptors: Statistics, Probability, Mathematical Models, Computer Software
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Zhou, Guojing; Wang, Jianxun; Lynch, Collin F.; Chi, Min – International Educational Data Mining Society, 2017
In this study, we applied decision trees (DT) to extract a compact set of pedagogical decision-making rules from an original "full" set of 3,702 Reinforcement Learning (RL)- induced rules, referred to as the DT-RL rules and Full-RL rules respectively. We then evaluated the effectiveness of the two rule sets against a baseline Random…
Descriptors: Learning Theories, Teaching Methods, Decision Making, Intelligent Tutoring Systems
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Lee, Hee Seung; Betts, Shawn; Anderson, John R. – Cognitive Science, 2016
Learning to solve a class of problems can be characterized as a search through a space of hypotheses about the rules for solving these problems. A series of four experiments studied how different learning conditions affected the search among hypotheses about the solution rule for a simple computational problem. Experiment 1 showed that a problem…
Descriptors: Problem Solving, Hypothesis Testing, Experiments, Cognitive Processes
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Cheteyan, Leslie A.; Hengeveld, Stewart; Jones, Michael A. – College Mathematics Journal, 2011
In this paper, we review the rules and game board for "Chutes and Ladders", define a Markov chain to model the game regardless of the spinner range, and describe how properties of Markov chains are used to determine that an optimal spinner range of 15 minimizes the expected number of turns for a player to complete the game. Because the Markov…
Descriptors: Markov Processes, Mathematics Instruction, Games, Teaching Methods
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Stamper, John; Barnes, Tiffany; Croy, Marvin – International Journal of Artificial Intelligence in Education, 2011
The Hint Factory is an implementation of our novel method to automatically generate hints using past student data for a logic tutor. One disadvantage of the Hint Factory is the time needed to gather enough data on new problems in order to provide hints. In this paper we describe the use of expert sample solutions to "seed" the hint generation…
Descriptors: Cues, Prompting, Learning Strategies, Teaching Methods
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Barnes, Tiffany, Ed.; Chi, Min, Ed.; Feng, Mingyu, Ed. – International Educational Data Mining Society, 2016
The 9th International Conference on Educational Data Mining (EDM 2016) is held under the auspices of the International Educational Data Mining Society at the Sheraton Raleigh Hotel, in downtown Raleigh, North Carolina, in the USA. The conference, held June 29-July 2, 2016, follows the eight previous editions (Madrid 2015, London 2014, Memphis…
Descriptors: Data Analysis, Evidence Based Practice, Inquiry, Science Instruction
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Lynch, Collin F., Ed.; Merceron, Agathe, Ed.; Desmarais, Michel, Ed.; Nkambou, Roger, Ed. – International Educational Data Mining Society, 2019
The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…
Descriptors: Data Collection, Data Analysis, Information Retrieval, Content Analysis
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Stevens, Ron; Johnson, David F.; Soller, Amy – Cell Biology Education, 2005
The IMMEX (Interactive Multi-Media Exercises) Web-based problem set platform enables the online delivery of complex, multimedia simulations, the rapid collection of student performance data, and has already been used in several genetic simulations. The next step is the use of these data to understand and improve student learning in a formative…
Descriptors: Majors (Students), Undergraduate Students, Problem Solving, Genetics