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Tom Reshef-Israeli; Shulamit Kapon – Online Submission, 2024
As problems become increasingly complex, science educators need to better understand how new knowledge is constructed and applied in heterogeneous team collaborations, and how to teach students to productively engage in these processes. We discuss the emergence of insights in collaborative sensemaking and suggest a model that articulates the…
Descriptors: Comprehension, Constructivism (Learning), Teaching Methods, Learner Engagement
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Mohamed Elgeddawy; Mahmoud Abouraia; Hesham Magd – International Society for Technology, Education, and Science, 2024
The paper investigates the intellectual traditions that underscore the assumptions of academic and carrier advising, toward an understanding of what it means to advise college students and the pedagogical ramifications of this understanding. The discussion articulates the driving forces that stand behind a university model that goes beyond course…
Descriptors: Academic Advising, Career Counseling, Educational Improvement, Faculty Advisers
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Michael Kroth; Davin Carr-Chellman; Donna Daniels; Joshua Kingsley; Carol Rogers-Shaw; Laura B. Holyoke – American Association for Adult and Continuing Education, 2023
The purpose of this article is to share early results from an ongoing literature review intended to (a) explore the intersection of spiritual formation, aging, and lifelong learning, (b) situate this intersection within profound learning theory, and (c) develop a rich understanding and conceptual model which characterizes the qualities and…
Descriptors: Religious Factors, Age, Lifelong Learning, Learning Theories
Reima Al-Jarf – Online Submission, 2024
Multimodal learning refers to teaching strategies that involve multiple sensory systems simultaneously. Teachers can create materials for students with different learning styles (auditory, visual, kinesthetic reading, and writing). Multimodal learning keeps students engaged, encourages them to apply what they learn in real-life situations,…
Descriptors: Grammar, Multimedia Instruction, Problem Solving, Student Projects
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Lee, Morgan P.; Croteau, Ethan; Gurung, Ashish; Botelho, Anthony F.; Heffernan, Neil T. – International Educational Data Mining Society, 2023
The use of Bayesian Knowledge Tracing (BKT) models in predicting student learning and mastery, especially in mathematics, is a well-established and proven approach in learning analytics. In this work, we report on our analysis examining the generalizability of BKT models across academic years attributed to "detector rot." We compare the…
Descriptors: Bayesian Statistics, Models, Generalizability Theory, Longitudinal Studies
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Shu-Jing Wu; Feng-Lan Liu; Yan-Yu Xu; Tin-Chang Chang; Zeng-Han Lee – International Association for Development of the Information Society, 2023
This study aimed to build a model to detect the factors to enhance student engagement and learning development in mobile learning during the COVID-19 Pandemic. Data from a total of 400 junior-high-school students were collected in China in the fall semester of 2020, and a large proportion of students preferred accessing their study with cellphones…
Descriptors: Junior High School Students, Foreign Countries, Learner Engagement, Models
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Amjad Almusaed; Asaad Almssad; Marisol Rico Cortez – International Society for Technology, Education, and Science, 2023
This article overviews a new teaching method from COVID-19. It uses multimedia resources and more traditional classroom activities together. The course focuses on the benefits of using online parts of hybrid learning in addition to in-person instruction. The benefits of such learning include more opportunities for contact with classmates,…
Descriptors: Learner Engagement, Blended Learning, COVID-19, Pandemics
Li, Chenglu; Xing, Wanli; Leite, Walter – Grantee Submission, 2021
To support online learners at a large scale, extensive studies have adopted machine learning (ML) techniques to analyze students' artifacts and predict their learning outcomes automatically. However, limited attention has been paid to the fairness of prediction with ML in educational settings. This study intends to fill the gap by introducing a…
Descriptors: Learning Analytics, Prediction, Models, Electronic Learning
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Chu, Wei; Pavlik, Philip I., Jr. – International Educational Data Mining Society, 2023
In adaptive learning systems, various models are employed to obtain the optimal learning schedule and review for a specific learner. Models of learning are used to estimate the learner's current recall probability by incorporating features or predictors proposed by psychological theory or empirically relevant to learners' performance. Logistic…
Descriptors: Reaction Time, Accuracy, Models, Predictor Variables
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Tran, Tuan M.; Hasegawa, Shinobu – International Association for Development of the Information Society, 2022
A learner model reflects learning patterns and characteristics of a learner. A learner model with learning history and its effectiveness plays a significant role in supporting a learner's understanding of their strengths and weaknesses of their way of learning in order to make proper adjustments for improvement. Nowadays, learners have been…
Descriptors: Markov Processes, Learning Processes, Models, Scores
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Zhang, Jiayi; Andres, Juliana Ma. Alexandra L.; Hutt, Stephen; Baker, Ryan S.; Ocumpaugh, Jaclyn; Mills, Caitlin; Brooks, Jamiella; Sethuraman, Sheela; Young, Tyron – International Educational Data Mining Society, 2022
Self-regulated learning (SRL) is a critical component of mathematics problem solving. Students skilled in SRL are more likely to effectively set goals, search for information, and direct their attention and cognitive process so that they align their efforts with their objectives. An influential framework for SRL, the SMART model, proposes that…
Descriptors: Mathematics Instruction, Teaching Methods, Problem Solving, Metacognition
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Rho, Jihyun; Rau, Martina A.; Van Veen, Barry D. – International Educational Data Mining Society, 2022
Instruction in many STEM domains heavily relies on visual representations, such as graphs, figures, and diagrams. However, students who lack representational competencies do not benefit from these visual representations. Therefore, students must learn not only content knowledge but also representational competencies. Further, as learning…
Descriptors: Learning Processes, Models, Introductory Courses, Engineering Education
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Agnes D. Garciano; Debbie Marie B. Verzosa; Ma. Louise Antonette N. De Las Peñas; Maria Alva Q. Aberin; Juan Carlo F. Mallari; Jumela F. Sarmiento; Mark Anthony C. Tolentino – International Association for Development of the Information Society, 2023
This paper discusses the "Just Keep Solving" apps that are designed based on deliberate practice model for developing mathematical skills. Features of deliberate practice include well-defined goals involving areas of weakness as determined by a knowledgeable other such as a teacher. The integration of game design features provides a…
Descriptors: Students, Student Centered Learning, Play, Electronic Learning
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Zhang, Qiao; Maclellan, Christopher J. – International Educational Data Mining Society, 2021
Knowledge tracing algorithms are embedded in Intelligent Tutoring Systems (ITS) to keep track of students' learning process. While knowledge tracing models have been extensively studied in offline settings, very little work has explored their use in online settings. This is primarily because conducting experiments to evaluate and select knowledge…
Descriptors: Electronic Learning, Mastery Learning, Computer Simulation, Intelligent Tutoring Systems
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Prihar, Ethan; Vanacore, Kirk; Sales, Adam; Heffernan, Neil – International Educational Data Mining Society, 2023
There is a growing need to empirically evaluate the quality of online instructional interventions at scale. In response, some online learning platforms have begun to implement rapid A/B testing of instructional interventions. In these scenarios, students participate in series of randomized experiments that evaluate problem-level interventions in…
Descriptors: Electronic Learning, Intervention, Instructional Effectiveness, Data Collection
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