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Liu, Zhi; Ren, Yupei; Kong, Xi; Liu, Sannyuya – Journal of Educational Computing Research, 2022
Wearable devices are an emerging technological tool in the field of learning analytics. With the help of wearable technologies, an increasing number of scholars have a strong interest in studying the associations between student data and learning outcomes in different learning environments. This systematic review examines 120 articles published…
Descriptors: Learning Analytics, Educational Research, Physiology, Measurement Equipment
Wanli Xing; Hanxiang Du – Journal of Educational Computing Research, 2023
Online learning communities are becoming increasingly popular as they are known to support collaborative dialogue and knowledge building. Previous studies have typically focused on small, closed learning communities from an individual, static, and aggregated perspective. This research aims to advance our understanding of open and large online…
Descriptors: MOOCs, Social Networks, Learning Analytics, Online Courses
Wen-shuang Fu; Jia-hua Zhang; Di Zhang; Tian-tian Li; Min Lan; Na-na Liu – Journal of Educational Computing Research, 2025
Cognitive ability is closely associated with the acquisition of programming skills, and enhancing learners' cognitive ability is a crucial factor in improving the efficacy of programming education. Adaptive feedback strategies can provide learners with personalized support based on their learning context, which helps to stimulate their interest…
Descriptors: Feedback (Response), Cognitive Ability, Programming, Computer Science Education
Ben-Yaacov, Anat; Hershkovitz, Arnon – Journal of Educational Computing Research, 2023
Block programming has been suggested as a way of engaging young learners with the foundations of programming and computational thinking in a syntax-free manner. Indeed, syntax errors--which form one of two broad categories of errors in programming, the other one being logic errors--are omitted while block programming. However, this does not mean…
Descriptors: Programming, Computation, Thinking Skills, Error Patterns
Chun Yan Enoch Sit; Siu-Cheung Kong – Journal of Educational Computing Research, 2024
Educational process mining aims (EPM) to help teachers understand the overall learning process of their students. Although deep learning models have shown promising results in many domains, the event log dataset in many online courses may not be large enough for deep learning models to approximate the probability distribution of students' learning…
Descriptors: Learning Processes, Learning Analytics, Algorithms, Guidelines
Joseph, Lumy; Abraham, Sajimon; Mani, Biju P.; N., Rajesh – Journal of Educational Computing Research, 2022
A fixed learning path for all learners is a major drawback of virtual learning systems. An online learning path recommendation system has the advantage of offering flexibility to select appropriate learning content. Learning Analytics Intervention (LAI) provides several educational benefits, particularly for low-performing students. Researchers…
Descriptors: Cognitive Style, Learning Analytics, Educational Benefits, Integrated Learning Systems
Meier, Heidi; Lepp, Marina – Journal of Educational Computing Research, 2023
Especially in large courses, feedback is often given only on the final results; less attention is paid to the programming process. Today, however, some programming environments, e.g., Thonny, log activities during programming and have the functionality of replaying the programming process. This information can be used to provide feedback, and this…
Descriptors: Programming, Introductory Courses, Computer Science Education, Teaching Methods
Hershkovitz, Arnon; Tabach, Michal; Cohen, Anat – Journal of Educational Computing Research, 2022
In a large-scale quantitative study that adopted a learning analytics approach, we searched for associations between students' activity in a game-based online mathematics learning environment and their mathematics achievements on a national standardized test. Students were active in the environment throughout the school year, and particularly…
Descriptors: Electronic Learning, Learning Activities, Mathematics Achievement, Elementary School Students
Pei, Bo; Xing, Wanli – Journal of Educational Computing Research, 2022
This paper introduces a novel approach to identify at-risk students with a focus on output interpretability through analyzing learning activities at a finer granularity on a weekly basis. Specifically, this approach converts the predicted output from the former weeks into meaningful probabilities to infer the predictions in the current week for…
Descriptors: At Risk Students, Learning Analytics, Information Retrieval, Models
Jiangyue Liu; Siran Li; Qianyan Dong – Journal of Educational Computing Research, 2024
The emergence of Generative Artificial Intelligence (GAI) has caused significant disruption to the traditional educational teaching ecosystem. GAI possesses remarkable capabilities in generating human-like text and boasts an extensive knowledge repository, thereby paving the way for potential collaboration with humans. However, current research on…
Descriptors: Artificial Intelligence, Learning Analytics, Computer Uses in Education, Instructional Design
The Effects of Three Instructor Participatory Roles on a Small Group's Collaborative Concept Mapping
Ouyang, Fan; Xu, Weiqi – Journal of Educational Computing Research, 2022
Collaborative concept mapping, as one of the widely used computer-supported collaborative learning (CSCL) modes, has been used to foster students' meaning making, problem solving, and knowledge construction. Previous empirical research has used varied instructional scaffoldings and has reported different effects of those scaffoldings on…
Descriptors: Computer Assisted Instruction, Cooperative Learning, Concept Mapping, Problem Solving
Ouyang, Fan – Journal of Educational Computing Research, 2021
Sharing the same philosophy of "relations matter" with computer-supported collaborative learning (CSCL), social network analysis (SNA) has become a common methodology in the CSCL research. In this research, I use SNA methods from "relational ties," "network modes," and "integrated methods" perspectives to…
Descriptors: Social Networks, Cooperative Learning, Electronic Learning, Online Courses
The Associations between Computational Thinking and Creativity: The Role of Personal Characteristics
Israel-Fishelson, Rotem; Hershkovitz, Arnon; Eguíluz, Andoni; Garaizar, Pablo; Guenaga, Mariluz – Journal of Educational Computing Research, 2021
Computational Thinking (CT) and creativity are considered two vital skills for the 21st century that should be incorporated into future curricula around the world. We studied the relationship between these two constructs while focusing on learners' personal characteristics. Two types of creativity were examined: creative thinking and computational…
Descriptors: Correlation, Thinking Skills, Creative Thinking, Problem Solving
Zhang, Zhaoli; Li, Zhenhua; Liu, Hai; Cao, Taihe; Liu, Sannyuya – Journal of Educational Computing Research, 2020
Online learning engagement detection is a fundamental problem in educational information technology. Efficient detection of students' learning situations can provide information to teachers to help them identify students having trouble in real time. To improve the accuracy of learning engagement detection, we have collected two aspects of…
Descriptors: Learner Engagement, Learning Analytics, Nonverbal Communication, Pattern Recognition
Israel-Fishelson, Rotem; Hershkovitz, Arnon; Eguíluz, Andoni; Garaizar, Pablo; Guenaga, Mariluz – Journal of Educational Computing Research, 2021
Creativity and Computational Thinking (CT) have been both extensively researched in recent years. However, the associations between them are still not fully understood despite their recognition as essential competencies for the digital age. This study looks to bridge this gap by examining the association between CT and two types of creativity,…
Descriptors: Learning Analytics, Correlation, Creativity, Creative Thinking
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