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Ellen M. Kok; Diederick C. Niehorster; Anouk van der Gijp; Dirk R. Rutgers; William F. Auffermann; Marieke van der Schaaf; Liesbeth Kester; Tamara van Gog – Advances in Health Sciences Education, 2024
Self-monitoring is essential for effectively regulating learning, but difficult in visual diagnostic tasks such as radiograph interpretation. Eye-tracking technology can visualize viewing behavior in gaze displays, thereby providing information about visual search and decision-making. We hypothesized that individually adaptive gaze-display…
Descriptors: Foreign Countries, Medical Students, Eye Movements, Pretests Posttests
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Kyosuke Takami; Brendan Flanagan; Yiling Dai; Hiroaki Ogata – International Journal of Distance Education Technologies, 2024
Explainable recommendation, which provides an explanation about why a quiz is recommended, helps to improve transparency, persuasiveness, and trustworthiness. However, little research examined the effectiveness of the explainable recommender, especially on academic performance. To survey its effectiveness, the authors evaluate the math academic…
Descriptors: Bayesian Statistics, Epistemology, Mathematics Achievement, Artificial Intelligence
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Kok, Ellen; Hormann, Olle; Rou, Jeroen; Saase, Evi; der Schaaf, Marieke; Kester, Liesbeth; Gog, Tamara – Journal of Computer Assisted Learning, 2022
Background: Performance monitoring plays a key role in self-regulated learning, but is difficult, especially for complex visual tasks such as navigational map reading. Gaze displays (i.e. visualizations of participants' eye movements during a task) might serve as feedback to improve students' performance monitoring. Objectives: We hypothesized…
Descriptors: Metacognition, Eye Movements, Task Analysis, Visualization
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How, Meng-Leong; Hung, Wei Loong David – Education Sciences, 2019
Artificial intelligence-enabled adaptive learning systems (AI-ALS) are increasingly being deployed in education to enhance the learning needs of students. However, educational stakeholders are required by policy-makers to conduct an independent evaluation of the AI-ALS using a small sample size in a pilot study, before that AI-ALS can be approved…
Descriptors: Stakeholders, Artificial Intelligence, Bayesian Statistics, Probability
Suh, Youngsuk; Cho, Sun-Joo; Bottge, Brian A. – Grantee Submission, 2018
This article presents a multilevel longitudinal nested logit model for analyzing correct response and error types in multilevel longitudinal intervention data collected under a pretest-posttest, cluster randomized trial design. The use of the model is illustrated with a real data analysis, including a model comparison study regarding model…
Descriptors: Hierarchical Linear Modeling, Longitudinal Studies, Error Patterns, Change
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Warren, Aaron R. – Physical Review Physics Education Research, 2020
The evaluation of hypotheses, and the ability to learn from critical reflection on experimental and theoretical tests of those hypotheses, is central to an authentic practice of physics. A large part of physics education therefore seeks to help students understand the significance of this kind of reflective practice and to develop the strategies…
Descriptors: Epistemology, Bayesian Statistics, Physics, Science Instruction
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Foster, Colin – Educational Studies in Mathematics, 2018
Achieving fluency in important mathematical procedures is fundamental to students' mathematical development. The usual way to develop procedural fluency is to practise repetitive exercises, but is this the only effective way? This paper reports three quasi-experimental studies carried out in a total of 11 secondary schools involving altogether 528…
Descriptors: Mathematics Achievement, Mathematics Instruction, Comparative Analysis, Quasiexperimental Design
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Han, Hyemin; Park, Joonsuk; Thoma, Stephen J. – Journal of Moral Education, 2018
In this article, we discuss the benefits of Bayesian statistics and how to utilize them in studies of moral education. To demonstrate concrete examples of the applications of Bayesian statistics to studies of moral education, we reanalyzed two data sets previously collected: one small data set collected from a moral educational intervention…
Descriptors: Moral Development, Bayesian Statistics, Computer Software, Intervention
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Mao, Ye; Lin, Chen; Chi, Min – Journal of Educational Data Mining, 2018
Bayesian Knowledge Tracing (BKT) is a commonly used approach for student modeling, and Long Short Term Memory (LSTM) is a versatile model that can be applied to a wide range of tasks, such as language translation. In this work, we directly compared three models: BKT, its variant Intervention-BKT (IBKT), and LSTM, on two types of student modeling…
Descriptors: Prediction, Pretests Posttests, Bayesian Statistics, Short Term Memory
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DiCerbo, Kristen E.; Xu, Yuning; Levy, Roy; Lai, Emily; Holland, Laura – Educational Assessment, 2017
Inferences about student knowledge, skills, and attributes based on digital activity still largely come from whether students ultimately get a correct result or not. However, the ability to collect activity stream data as individuals interact with digital environments provides information about students' processes as they progress through learning…
Descriptors: Models, Cognitive Processes, Elementary School Students, Grade 3
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Hooshyar, Danial; Ahmad, Rodina Binti; Yousefi, Moslem; Fathi, Moein; Horng, Shi-Jinn; Lim, Heuiseok – Innovations in Education and Teaching International, 2018
In learning systems and environment research, intelligent tutoring and personalisation are considered the two most important factors. An Intelligent Tutoring System can serve as an effective tool to improve problem-solving skills by simulating a human tutor's actions in implementing one-to-one adaptive and personalised teaching. Thus, in this…
Descriptors: Intelligent Tutoring Systems, Problem Solving, Skill Development, Programming
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Andrade, Alejandro; Danish, Joshua A.; Maltese, Adam V. – Journal of Learning Analytics, 2017
Interactive learning environments with body-centric technologies lie at the intersection of the design of embodied learning activities and multimodal learning analytics. Sensing technologies can generate large amounts of fine-grained data automatically captured from student movements. Researchers can use these fine-grained data to create a…
Descriptors: Measurement, Interaction, Models, Educational Environment
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van Viersen, Sietske; de Bree, Elise H.; Kalee, Lilian; Kroesbergen, Evelyn H.; de Jong, Peter F. – Reading and Writing: An Interdisciplinary Journal, 2017
A few studies suggest that gifted children with dyslexia have better literacy skills than averagely intelligent children with dyslexia. This finding aligns with the hypothesis that giftedness-related factors provide compensation for poor reading. The present study investigated whether, as in the native language (NL), the level of foreign language…
Descriptors: Foreign Countries, Second Language Learning, Reading Instruction, Spelling Instruction
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Liu, Ran; Koedinger, Kenneth R. K – International Educational Data Mining Society, 2017
Research in Educational Data Mining could benefit from greater efforts to ensure that models yield reliable, valid, and interpretable parameter estimates. These efforts have especially been lacking for individualized student-parameter models. We collected two datasets from a sizable student population with excellent "depth" -- that is,…
Descriptors: Data Analysis, Intelligent Tutoring Systems, Bayesian Statistics, Pretests Posttests