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Yang Shi; Robin Schmucker; Keith Tran; John Bacher; Kenneth Koedinger; Thomas Price; Min Chi; Tiffany Barnes – Journal of Educational Data Mining, 2024
Understanding students' learning of knowledge components (KCs) is an important educational data mining task and enables many educational applications. However, in the domain of computing education, where program exercises require students to practice many KCs simultaneously, it is a challenge to attribute their errors to specific KCs and,…
Descriptors: Programming Languages, Undergraduate Students, Learning Processes, Teaching Models
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Xia, Xiaona; Qi, Wanxue – Education and Information Technologies, 2023
Interactive learning is a two-way learning method of learners independently by using computer and network technology. In the interactive relationships, interactive learning plays a role for learners to achieve the learning purpose, interactive learning has become an important effect of online learning, but it also has many problems that need to be…
Descriptors: Foreign Countries, Identification, Interaction, Learning Processes
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Vo, Thi Ngoc Chau; Nguyen, Phung – IEEE Transactions on Learning Technologies, 2021
A course-level early final study status prediction task is to predict as soon as possible the final success of each student after studying a course. It is significant because each successful course accomplishment is required for a degree. Further, early predictions provide enough time to make necessary changes for ultimate success. This article…
Descriptors: Prediction, Academic Achievement, Data Collection, Learning Processes
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Obaid, Teeba; Nesbit, John C.; Mahmoody Ghaidary, Ahmad; Jain, Misha; Hajian, Shiva – Instructional Science: An International Journal of the Learning Sciences, 2023
Understanding scientific phenomena requires learners to construct mental models of causal systems. Simulation-based discovery learning offers learners the opportunity to construct mental models and test them against the behavior of a simulation. The purpose of this study was to investigate sequential patterns of learner actions and utterances…
Descriptors: Inferences, Simulation, Discovery Learning, Science Education
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Oliveira, Wilk; Tenório, Kamilla; Hamari, Juho; Pastushenko, Olena; Isotani, Seiji – Smart Learning Environments, 2021
The flow experience (i.e., challenge-skill balance, action-awareness merging, clear goals, unambiguous feedback, concentration, sense of control, loss of self-consciousness, transformation of time, and "autotelic" experience) is an experience highly related to the learning experience. One of the current challenges is to identify whether…
Descriptors: Prediction, Psychological Patterns, Learning Processes, Student Behavior
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Coulton, Gary F. – Psychology Teaching Review, 2022
There is considerable evidence that 'active learning' strategies are more efficacious than traditional 'passive learning' methods (e.g. lecture). Presented here is a small group active learning project developed for undergraduate social psychology students. The activity involves carrying out and reporting the results of a structured demonstration…
Descriptors: Victims, Undergraduate Students, Social Psychology, Active Learning
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Danielle S. McNamara; Tracy Arner; Elizabeth Reilley; Paul Alvarado; Chani Clark; Thomas Fikes; Annie Hale; Betheny Weigele – Grantee Submission, 2022
Accounting for complex interactions between contextual variables and learners' individual differences in aptitudes and background requires building the means to connect and access learner data at large scales, across time, and in multiple contexts. This paper describes the ASU Learning@Scale (L@S) project to develop a digital learning network…
Descriptors: Electronic Learning, Educational Technology, Networks, Learning Analytics
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Saint, John; Whitelock-Wainwright, Alexander; Gasevic, Dragan; Pardo, Abelardo – IEEE Transactions on Learning Technologies, 2020
The recent focus on learning analytics (LA) to analyze temporal dimensions of learning holds the promise of providing insights into latent constructs, such as learning strategy, self-regulated learning (SRL), and metacognition. These methods seek to provide an enriched view of learner behaviors beyond the scope of commonly used correlational or…
Descriptors: Undergraduate Students, Engineering Education, Learning Analytics, Learning Strategies
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Dina Fitria Murad; Meta Amalya Dewi; Arbaiah Inn; Silvia Ayunda Murad; Noor Udin; Taufik Darwis – Journal of Educators Online, 2025
This study aims to produce a more personalized recommendation system for online learning using multicriteria in collaborative filtering and data from the Binus Online Learning repository as a knowledge base. The study uses forecasting (regression) and consists of three stages: (1) collecting data on the results of the learning process; (2) adding…
Descriptors: Electronic Learning, Data Collection, Context Effect, Learning Processes
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Cenka, Baginda Anggun Nan; Santoso, Harry B.; Junus, Kasiyah – Knowledge Management & E-Learning, 2022
Online learning implementation has been growing year by year across countries, including Indonesia. Many higher education institutions use a Learning Management System (LMS) to facilitate online learning. Unfortunately, many issues arise during online learning implementation, such as a lack of student behaviour monitoring. This study adopts an…
Descriptors: Knowledge Management, Electronic Learning, Integrated Learning Systems, Student Behavior
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McGregor, Debra, Ed.; Anderson, Dayle, Ed. – Contributions from Science Education Research, 2023
This book presents a wide range of international perspectives that explore the different ways the diverse forms of drama supports learning in science. It illustrates how learning science by adopting and adapting theatrical techniques can offer more inclusive ways for students to relate to scientific ideas and concepts. The theatrical processes by…
Descriptors: Science Education, Drama, Theater Arts, Teaching Methods
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Leblay, Joffrey; Rabah, Mourad; Champagnat, Ronan; Nowakowski, Samuel – International Association for Development of the Information Society, 2018
How can we learn to use properly business software, digital environments, games or intelligent tutoring systems (ITS)? Mainly, we assume that the new user will learn by doing. But what about the efficiency of such a method? Our approach proposes an answer by introducing on-line coaching. In learning process, learners may need guidance to help them…
Descriptors: Intelligent Tutoring Systems, Coaching (Performance), Efficiency, Learning Processes
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Ifenthaler, Dirk; Gibson, David; Zheng, Longwei – International Association for Development of the Information Society, 2018
This study is part of a research programme investigating the dynamics and impacts of learning engagement in a challenge-based digital learning environment. Learning engagement is a multidimensional concept which includes an individual's ability to behaviourally, cognitively, emotionally, and motivationally engage in an on-going learning process.…
Descriptors: Learner Engagement, Electronic Learning, Learning Analytics, College Students
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Browne, Tom; Lyle, John – Canadian Journal of Learning and Technology, 2018
This exploratory case study evaluates the implementation and use by student coaches of an innovative coaching profiling system, Touch Screen Technology (TST), to assess coaching behaviours. The study was designed to evaluate the potential of this technologically-enhanced assessment system as a profiling option for gathering, storing, retrieving,…
Descriptors: Case Studies, Athletic Coaches, Innovation, Competence
Barbara Woods McElroy; Bruce H. Lubich – Sage Research Methods Cases, 2017
This case describes the research process followed by two professors who chose to study student outcomes in our online accounting classrooms. Motivated by the discovery of a possible anomaly in classroom outcomes, we decided to look further. We thought the anomaly might be explained by student procrastination. If our perception proved true, the…
Descriptors: College Students, Accounting, Distance Education, Online Courses
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