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Hengtao Tang; Yu Bao – Interactive Learning Environments, 2024
Self-regulated learning is a crucial skill that may enable massive numbers of learners to thrive in MOOCs, but MOOC learners differ in their self-regulated learning skills, as low self-regulated learners need support to regulate their learning process in MOOCs. Designing self-regulated learning scaffoldings builds upon an accurate appraisal of…
Descriptors: Self Management, Profiles, MOOCs, Land Grant Universities
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Xiang Feng; Keyi Yuan; Xiu Guan; Longhui Qiu – Interactive Learning Environments, 2024
Datasets are critical for emotion analysis in the machine learning field. This study aims to explore emotion analysis datasets and related benchmarks in online learning, since, currently, there are very few studies that explore the same. We have scientifically labeled the topic and nine-category emotion of 4715 comment texts in online learning…
Descriptors: MOOCs, Psychological Patterns, Artificial Intelligence, Prediction
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Xiao Wen; Hu Juan – Interactive Learning Environments, 2024
To address three issues identified in previous research this study proposes a clustering-based MOOC dropout identification method and an early prediction model based on deep learning. The MOOC learning behavior of self-paced students was analyzed, and two well-known MOOC datasets were used for analysis and validation. The findings are as follows:…
Descriptors: MOOCs, Dropouts, Dropout Characteristics, Dropout Research
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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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Aïcha Bakki; Lahcen Oubahssi; Youness Laghouaouta; Sébastien George – Interactive Learning Environments, 2024
Business Process Model and Notation (BPMN) is a standard formalism for business process modeling that is very popular in professional practices due to its expressiveness, the well-defined meta-model, and its easiness of use by non-technical users. For instance, BPMN2.0 is used for business processes in commercial areas such as banks, shops,…
Descriptors: MOOCs, Learning Management Systems, Business Education, Models
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Lei Xie; Cixiao Wang – Interactive Learning Environments, 2024
Connectionist MOOC (cMOOC) is a type of MOOC, which can provide an online learning space for learners to sustainable connect. This study analyzed the learning behavior and motivation of repeat learners in the cMOOC "Internet + Education: a dialogue between theory and practice" to study the repeat learning needs and characteristics of…
Descriptors: Learning Analytics, Motivation Techniques, MOOCs, Sustainability
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Carina Titus Swai; Qingtang Liu; Linjing Wu – Interactive Learning Environments, 2024
Massive Open Online Courses (MOOCs) are platforms teachers can use to seek guidance on different strategies to update their teaching skills. This study finds the effectiveness of MOOCs in developing professional performance and skills of school teachers. It tries to show the extent to which school teachers can benefit from these courses and how…
Descriptors: MOOCs, Professionalism, Faculty Development, Teaching Methods
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Yalin Li; Min Zhao – Interactive Learning Environments, 2024
Massive Open Online Courses (MOOCs) are the product of "internet + education", offering open educational resources to global students. This study analyzed the factors influencing students' intention to continue using MOOCs based on their satisfaction. To achieve research objectives this study integrates the unified theory of acceptance…
Descriptors: MOOCs, Interpersonal Relationship, Influences, Student Attitudes
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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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Jing Chen; Bei Fang; Hao Zhang; Xia Xue – Interactive Learning Environments, 2024
High dropout rate exists universally in massive open online courses (MOOCs) due to the separation of teachers and learners in space and time. Dropout prediction using the machine learning method is an extremely important prerequisite to identify potential at-risk learners to improve learning. It has attracted much attention and there have emerged…
Descriptors: MOOCs, Potential Dropouts, Prediction, Artificial Intelligence
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Xu Yaqian; Zheng Qinhua – Interactive Learning Environments, 2024
The interactive mechanism between social and concept networks is a key question in connectivist learning, which explains the impact of interaction on cognitive development and knowledge generation. The successful practice of "Internet Change Education: Dialogue between Theory and Practice", the first cMOOC in China, provides data support…
Descriptors: Correlation, Social Networks, Status, MOOCs
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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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Guomin Chen; Pengrun Chen; Ying Wang; Nan Zhu – Interactive Learning Environments, 2024
The paper describes the research of causal relationships between the factors of technological, organizational, environmental, and personal contexts and their influence on the development of learning intentions in potential students. Its purpose was to develop a mechanism for designing a public online educational resource platform based on the…
Descriptors: MOOCs, Electronic Learning, Design, Technology Uses in Education
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Luyu Zhu; Jia Hao; Jianhou Gan – Interactive Learning Environments, 2024
Nowadays, Massive Open Online Courses (MOOC) has been gradually accepted by the public as a new type of education and teaching method. However, due to the lack of timely intervention and guidance from educators, learners' performance is not as effective as it could be. To address this problem, predicting MOOC learners' performance and providing…
Descriptors: MOOCs, Academic Achievement, Prediction, Bayesian Statistics
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Cixiao Wang; Yaqian Xu – Interactive Learning Environments, 2024
Different from the group formation approaches led by teachers, learners' generative learning objectives and the independent choice of collaborative partners are important in the Internet learning environment. This study takes the cMOOC (connectivist massive open online course) 5.0 "Internet + education: dialogue between theory and…
Descriptors: Open Education, Computer Mediated Communication, Cooperative Learning, Social Networks
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