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Yangyang Luo; Xibin Han; Chaoyang Zhang – Asia Pacific Education Review, 2024
Learning outcomes can be predicted with machine learning algorithms that assess students' online behavior data. However, there have been few generalized predictive models for a large number of blended courses in different disciplines and in different cohorts. In this study, we examined learning outcomes in terms of learning data in all of the…
Descriptors: Prediction, Learning Management Systems, Blended Learning, Classification
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Mohd Fazil; Angelica Rísquez; Claire Halpin – Journal of Learning Analytics, 2024
Technology-enhanced learning supported by virtual learning environments (VLEs) facilitates tutors and students. VLE platforms contain a wealth of information that can be used to mine insight regarding students' learning behaviour and relationships between behaviour and academic performance, as well as to model data-driven decision-making. This…
Descriptors: Learning Analytics, Learning Management Systems, Learning Processes, Decision Making
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Logan Sizemore; Brian Hutchinson; Emily Borda – Chemistry Education Research and Practice, 2024
Education researchers are deeply interested in understanding the way students organize their knowledge. Card sort tasks, which require students to group concepts, are one mechanism to infer a student's organizational strategy. However, the limited resolution of card sort tasks means they necessarily miss some of the nuance in a student's strategy.…
Descriptors: Artificial Intelligence, Chemistry, Cognitive Ability, Abstract Reasoning
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O. S. Adewale; O. C. Agbonifo; E. O. Ibam; A. I. Makinde; O. K. Boyinbode; B. A. Ojokoh; O. Olabode; M. S. Omirin; S. O. Olatunji – Interactive Learning Environments, 2024
With the advent of technological advancement in learning, such as context-awareness, ubiquity and personalisation, various innovations in teaching and learning have led to improved learning. This research paper aims to develop a system that supports personalised learning through adaptive content, adaptive learning path and context awareness to…
Descriptors: Cognitive Style, Individualized Instruction, Learning Processes, Preferences
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Thomas, Sujith; Srinivasan, Narayanan – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2023
In classification learning of artificial stimuli, participants learn the perfectly diagnostic dimension better than the partially diagnostic dimensions. Also, there is a strong preference for a unidimensional categorization based on the perfectly diagnostic dimension. In a different experimental procedure, called array-based classification task,…
Descriptors: Classification, Bayesian Statistics, Observational Learning, Preferences
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Dehua Zha; Dianzhi Liu – SAGE Open, 2023
This study investigated successful EFL (English as a Foreign Language) students' learning strategies in Chinese universities and explored the classification system of English learning strategies, to guide EFL students how to learn English. A total of 24 successful English majors and non-English majors in Chinese universities were interviewed about…
Descriptors: Foreign Countries, College Students, Second Language Learning, English (Second Language)
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Daniel Fitousi – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2023
For nearly half a century now, Garner interference has been serving as the gold standard measure of dimensional interaction and selective attention. But the mechanisms that generate Garner interference are still not well understood. The current study proposes a novel theory that ascribes the interference (and dimensional interaction in general) to…
Descriptors: Interference (Learning), Attention, Cognitive Processes, Experimental Psychology
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Isaac Wiafe; Akon Obu Ekpezu; Gifty Oforiwaa Gyamera; Fiifi Baffoe Payin Winful; Elikem Doe Atsakpo; Charles Nutropkor; Stephen Gulliver – Education and Information Technologies, 2025
The COVID-19 pandemic has propelled the use of technology in education through platforms such as YouTube and immersive technologies (e.g., virtual reality (VR) and augmented reality (AR)). Despite their potential to improve equity, access, engagement, and cognitive achievement, studies comparing their impacts on learning outcomes are scarce. This…
Descriptors: Educational Technology, Technology Uses in Education, Computer Simulation, Simulated Environment
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Trechsel, Lilian Julia; Diebold, Clara Léonie; Zimmermann, Anne Barbara; Fischer, Manuel – International Journal of Sustainability in Higher Education, 2023
Purpose: This study aims to explore how the boundary between science and society can be addressed to support the transformation of higher education towards sustainable development (HESD) in the sense of the whole institution approach. It analyses students' learning experiences in self-led sustainability projects conducted outside formal curricula…
Descriptors: Science and Society, Transformative Learning, Trust (Psychology), Learning Experience
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Koyuncu, Ilhan; Kilic, Abdullah Faruk; Orhan Goksun, Derya – Turkish Online Journal of Distance Education, 2022
During emergency remote teaching (ERT) process, factors affecting the achievement of students have changed. The purposes of this study are to determine the variables that affect the classification of students according to their course achievements in ERT during the pandemic process and to examine the classification performance of machine learning…
Descriptors: Classification, Distance Education, Academic Achievement, Electronic Learning
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Zhao, Qun; Wang, Jin-Long; Pao, Tsang-Long; Wang, Li-Yu – Journal of Educational Technology Systems, 2020
This study uses the log data from Moodle learning management system for predicting student learning performance in the first third of a semester. Since the quality of the data has great influence on the accuracy of machine learning, five major data transmission methods are used to enhance data quality of log file in the data preprocessing stage.…
Descriptors: Classification, Learning, Accuracy, Prediction
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George, David N.; Oltean, Bianca P. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2020
Learning to categorize perceptually similar stimuli can result in people becoming more sensitive to differences along perceptual dimensions that are relevant to category membership and/or less sensitive to equivalent differences along irrelevant perceptual dimensions. These effects of acquired distinctiveness and acquired equivalence may be caused…
Descriptors: Foreign Countries, College Students, Associative Learning, Learning Processes
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Chelsea Chandler; Rohit Raju; Jason G. Reitman; William R. Penuel; Monica Ko; Jeffrey B. Bush; Quentin Biddy; Sidney K. D’Mello – International Educational Data Mining Society, 2025
We investigated methods to enhance the generalizability of large language models (LLMs) designed to classify dimensions of collaborative discourse during small group work. Our research utilized five diverse datasets that spanned various grade levels, demographic groups, collaboration settings, and curriculum units. We explored different model…
Descriptors: Artificial Intelligence, Models, Natural Language Processing, Discourse Analysis
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Wonkyung Choi; Jun Jo; Geraldine Torrisi-Steele – International Journal of Adult Education and Technology, 2024
Despite best efforts, the student experience remains poorly understood. One under-explored approach to understanding the student experience is the use of big data analytics. The reported study is a work in progress aimed at exploring the value of big data methods for understanding the student experience. A big data analysis of an open dataset of…
Descriptors: College Students, Data Analysis, Data Collection, Learning Analytics
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Balti, Rihab; Hedhili, Aroua; Chaari, Wided Lejouad; Abed, Mourad – Education and Information Technologies, 2023
Since the COVID pandemic, universities propose online education to ensure learning continuity. However, the insufficient preparation led to a major drop in the learner's performance and his/her dissatisfaction with the learning experience. This may be due to several reasons, including the insensitivity of the virtual learning environment to the…
Descriptors: Cognitive Style, Pandemics, COVID-19, Distance Education
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