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Esteban Villalobos; Mar Perez-Sanagustin; Roger Azevedo; Cedric Sanza; Julien Broisin – IEEE Transactions on Learning Technologies, 2024
Blended learning (BL) has become increasingly popular in higher education institutions. Despite its popularity and the advances in methodologies for the detection of learning tactics and strategies from trace data, little is known about how they apply to BL settings and, therefore, how students use them to plan, organize, monitor, and regulate…
Descriptors: Metacognition, Learning Strategies, Blended Learning, Instructional Design
Seunghan Lee; Amar Sadanand Shetty; Lora A. Cavuoto – IEEE Transactions on Learning Technologies, 2024
Recent usage of virtual reality (VR) technology in surgical training has emerged because of its cost-effectiveness, time savings, and cognition-based feedback generation. However, the quantitative evaluation of its effectiveness in training is still not thoroughly studied. This article demonstrates the effectiveness of a VR-based surgical training…
Descriptors: Markov Processes, Computer Simulation, Teaching Methods, Surgery
Almorza, D.; Prada, A.; Kandús, M. V.; Salerno, J. C. – Journal of Biological Education, 2023
Graduates in biology or genetics learn Mendel's laws and Hardy-Weinberg equilibrium as students, and they know, use, and sometimes teach these concepts. However, it is unusual to learn about stochastic processes during the graduate studies of these topics, although the applications of Markov chains in the fields of genetics or biology are…
Descriptors: Graduate Students, College Science, Biology, Genetics
Kumar, Amruth N. – International Educational Data Mining Society, 2023
Is there a pattern in how students solve Parsons puzzles? Is there a difference between the puzzle-solving strategies of C++ and Java students? We used Markov transition matrix to answer these questions. We analyzed the solutions of introductory programming students solving Parsons puzzles involving if-else statements and while loops in C++ and…
Descriptors: Markov Processes, Puzzles, Introductory Courses, Computer Science Education
Lokkila, Erno; Christopoulos, Athanasios; Laakso, Mikko-Jussi – Informatics in Education, 2023
Prior programming knowledge of students has a major impact on introductory programming courses. Those with prior experience often seem to breeze through the course. Those without prior experience see others breeze through the course and disengage from the material or drop out. The purpose of this study is to demonstrate that novice student…
Descriptors: Prior Learning, Programming, Computer Science Education, Markov Processes
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
Johnson, Marina E.; Misra, Ram; Berenson, Mark – Decision Sciences Journal of Innovative Education, 2022
In the era of artificial intelligence (AI), big data (BD), and digital transformation (DT), analytics students should gain the ability to solve business problems by integrating various methods. This teaching brief illustrates how two such methods--Bayesian analysis and Markov chains--can be combined to enhance student learning using the Analytics…
Descriptors: Bayesian Statistics, Programming Languages, Artificial Intelligence, Data Analysis
Ross, Matthew M.; Wright, A. Michelle – Journal of Education for Business, 2022
We use Markov chain Monte Carlo (MCMC) analysis to construct a three-question math quiz to assess key skills needed for introductory finance. We begin with data collected from a ten-question criterion-referenced math quiz given to 314 undergraduates on the first day of class. MCMC indicates the top three questions for predicting overall course…
Descriptors: Mathematics Tests, Markov Processes, Monte Carlo Methods, Introductory Courses
Gupta, Anika; Garg, Deepak; Kumar, Parteek – IEEE Transactions on Learning Technologies, 2022
With the onset of online education via technology-enhanced learning platforms, large amount of educational data is being generated in the form of logs, clickstreams, performance, etc. These Virtual Learning Environments provide an opportunity to the researchers for the application of educational data mining and learning analytics, for mining the…
Descriptors: Markov Processes, Online Courses, Learning Management Systems, Learning Analytics
Kazu, Ibrahim Yasar; Kuvvetli, Murat – International Journal of Psychology and Educational Studies, 2023
Correct pronunciation significantly increases the intelligibility of communication. However, it is uncertain whether acquiring the pronunciation of the words enhances word retention capability. Therefore, the major purpose of this research is to evaluate whether vocabulary acquisition with the aid of pronouncing with artificial intelligence leads…
Descriptors: Artificial Intelligence, Teaching Methods, Pronunciation Instruction, High School Students