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Di Sun; Gang Cheng; Heng Luo – Interactive Learning Environments, 2024
Recently, researchers have proposed to leverage technology-supported data (log files) to investigate temporal and sequential patterns of interaction behaviors in learning processes. There are two major challenges to be addressed: clarifying the positioning of interaction levels and identifying the evolution of the interaction action patterns in…
Descriptors: Foreign Countries, Undergraduate Students, Computer Science, MOOCs
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Yun-Qi Bai; Ya-Qian Xu; Jian-Jun Xiao – Interactive Learning Environments, 2024
This study takes the value-based adoption model and CIE model of the learning process as the theoretical basis and combines them to explore the influencing factors and mechanisms of learners' online interaction and perceived value. Based on the questionnaire survey data of 81 learners' potential factors and their 45,166 real-time behavior data on…
Descriptors: MOOCs, Interaction, Student Behavior, Learning Processes
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Qi, Dan; Zhang, Mingli; Zhang, Yan – Interactive Learning Environments, 2023
With the ever-increasing adoption of MOOCs, the study of MOOCs learning behavior has been paid more and more attention, both in practice and in academia. This study aims to understand the impact of resource integration (including platform resources, teacher resources, and learner resources) on learners' perception of value co-creation (including…
Descriptors: MOOCs, Student Attitudes, Intention, Academic Persistence
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Xianglin Pan; Bihao Hu; Zihao Zhou; Xiang Feng – Interactive Learning Environments, 2023
Academic emotions of learners are important for academic achievement. For the online learning platform, it is of great value to gain insight into the academic emotion of the course in appropriate time interval from the platform. We crawled a large number of student comment texts from MOOC, and used deep learning algorithms (BERT models) to perform…
Descriptors: Emotional Experience, MOOCs, Student Attitudes, Academic Achievement
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Shuang Li; Xinyi He; Jiaqi Chen – Interactive Learning Environments, 2024
To inform the relationships among interaction patterns, social capital accumulation, and learning benefits, based on 29,056 log data from a cMOOC (Connectivist Massive Open Online Course) in China, this study examined the difference in social capital accumulation and content production among different interaction patterns using cluster analysis,…
Descriptors: Social Capital, Capacity Building, Interpersonal Competence, Foreign Countries
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Olga Agatova; Alexander Popov; Suad Abdalkareem Alwaely – Interactive Learning Environments, 2024
The paper examines the special aspects of using Big Data technology in education. The population was made up of 356 third-year university students. To study Big Data technology, a questionnaire was used where respondents rated: cloud technology; apps; Massive Open Online Courses (MOOCs) and digital learning platforms. The study suggested that the…
Descriptors: Data Use, Learning Processes, Technology Uses in Education, Information Storage