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Multimodal Learning Analytics of Collaborative Patterns during Pair Programming in Higher Education
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Xu, Weiqi; Wu, Yajuan; Ouyang, Fan – International Journal of Educational Technology in Higher Education, 2023
Pair programming (PP), as a mode of collaborative problem solving (CPS) in computer programming education, asks two students work in a pair to co-construct knowledge and solve problems. Considering the complex multimodality of pair programming caused by students' discourses, behaviors, and socio-emotions, it is of critical importance to examine…
Descriptors: Cooperative Learning, Problem Solving, Computer Science Education, Programming
Unraveling Temporally Entangled Multimodal Interactions: Investigating Verbal and Nonverbal Contributions to Collaborative Construction of Embodied Math Knowledge
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Hanall Sung; Mitchell J. Nathan – International Journal of Educational Technology in Higher Education, 2025
In various technology-enhanced learning (TEL) environments, knowledge co-creation progresses through multimodal interactions that integrate verbal and nonverbal modalities, such as speech and gestures. This study investigated two distinct analytical approaches for analyzing multimodal interactions--triangulating and interleaving--by applying them…
Descriptors: Technology Uses in Education, Epistemology, Research and Development, Nonverbal Learning
An Integrated Approach for Knowledge Extraction and Analysis in Collaborative Knowledge Construction
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Zhang, Ning; Ouyang, Fan – International Journal of Educational Technology in Higher Education, 2023
Collaborative knowledge construction (CKC) involved students' sharing of information, improvement of ideas, and construction of collective knowledge. In this process, knowledge extraction and analysis can provide valuable insights into students' knowledge capacities, depths, and levels in order to improve the CKC quality. However, existing studies…
Descriptors: Cooperative Learning, Computer Assisted Instruction, Concept Mapping, Learning Activities
Promoting Knowledge Elaboration, Socially Shared Regulation, and Group Performance in Collaborative Learning: An Automated Assessment and Feedback Approach Based on Knowledge Graphs
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Zheng, Lanqin; Long, Miaolang; Chen, Bodong; Fan, Yunchao – International Journal of Educational Technology in Higher Education, 2023
Online collaborative learning is implemented extensively in higher education. Nevertheless, it remains challenging to help learners achieve high-level group performance, knowledge elaboration, and socially shared regulation in online collaborative learning. To cope with these challenges, this study proposes and evaluates a novel automated…
Descriptors: Learning Analytics, Computer Assisted Testing, Cooperative Learning, Graphs
Using Learning Analytics to Explore Peer Learning Patterns in Asynchronous Gamified Environments
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Jewoong Moon; Laura McNeill; Christopher Thomas Edmonds; Seyyed Kazem Banihashem; Omid Noroozi – International Journal of Educational Technology in Higher Education, 2024
This study explored the dynamics of students' knowledge co-construction in an asynchronous gamified environment in higher education, focusing on peer discussions in college business courses. Utilizing epistemic network analysis, sequence pattern mining, and automated coding, we analyzed the interactions of 1,319 business students. Our findings…
Descriptors: Learning Analytics, Cooperative Learning, Asynchronous Communication, Gamification
Integration of Artificial Intelligence Performance Prediction and Learning Analytics to Improve Student Learning in Online Engineering Course
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Ouyang, Fan; Wu, Mian; Zheng, Luyi; Zhang, Liyin; Jiao, Pengcheng – International Journal of Educational Technology in Higher Education, 2023
As a cutting-edge field of artificial intelligence in education (AIEd) that depends on advanced computing technologies, AI performance prediction model is widely used to identify at-risk students that tend to fail, establish student-centered learning pathways, and optimize instructional design and development. A majority of the existing AI…
Descriptors: Technology Integration, Artificial Intelligence, Performance, Prediction