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Can Media Richness and Interaction Act as Stimulants to Medical Professionals' Learning Persistence in MOOCs via Fostering Learning Engagement?
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Yung-Ming Cheng – Interactive Technology and Smart Education, 2024
Purpose: The purpose of this study is to propose a research model based on the stimulus-organism-response (S-O-R) model to examine whether media richness (MR), human-system interaction (HSI) and human-human interaction (HHI) as technological feature antecedents to medical professionals' learning engagement (LE) can affect their learning…
Descriptors: MOOCs, Academic Persistence, Medical Education, Learner Engagement
What Makes Learners Enhance Learning Outcomes in MOOCs? Exploring the Roles of Gamification and Personalization
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Yung-Ming Cheng – Interactive Technology and Smart Education, 2024
Purpose: The purpose of this study is to propose a research model based on the stimulus-organism-response (S-O-R) model to explore whether gamification and personalization as environmental stimuli to learners' learning engagement (LE) can affect their learning persistence (LP) in massive open online courses (MOOCs) and, in turn, their learning…
Descriptors: MOOCs, Gamification, Learner Engagement, Academic Persistence
Research on Personalized Recommendation of MOOC Resources Based on Ontology
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Li, Yuanmin; Chen, Dexin; Zhan, Zehui – Interactive Technology and Smart Education, 2022
Purpose: The purpose of this study is to analyze from multiple perspectives, so as to form an effective massive open online course (MOOC) personalized recommendation method to help learners efficiently obtain MOOC resources. Design/methodology/approach: This study introduced ontology construction technology and a new semantic association algorithm…
Descriptors: MOOCs, Individualized Instruction, Models, Student Characteristics
An Explainable Attention-Based Bidirectional GRU Model for Pedagogical Classification of MOOCs
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Sebbaq, Hanane; El Faddouli, Nour-eddine – Interactive Technology and Smart Education, 2022
Purpose: The purpose of this study is, First, to leverage the limitation of annotated data and to identify the cognitive level of learning objectives efficiently, this study adopts transfer learning by using word2vec and a bidirectional gated recurrent units (GRU) that can fully take into account the context and improves the classification of the…
Descriptors: MOOCs, Classification, Electronic Learning, Educational Objectives
An Evaluation Model Based on Procedural Behaviors for Predicting MOOC Learning Performance: Students' Online Learning Behavior Analytics and Algorithms Construction
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Tong, Yao; Zhan, Zehui – Interactive Technology and Smart Education, 2023
Purpose: The purpose of this study is to set up an evaluation model to predict massive open online courses (MOOC) learning performance by analyzing MOOC learners' online learning behaviors, and comparing three algorithms -- multiple linear regression (MLR), multilayer perceptron (MLP) and classification and regression tree (CART).…
Descriptors: MOOCs, Online Courses, Learning Analytics, Prediction
Decoding and Designing Massive Open Online Courses (MOOCs)
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Shrivastava, Archana; Shrivastava, Ashish – Interactive Technology and Smart Education, 2023
Purpose: This study aims to investigate the attributes of the online programme that are considered and compute their relative importance in the purchase decision. This study aims to identify the most lucrative bundling of these attributes and their levels that can be used by online education companies to craft their product design strategy to…
Descriptors: MOOCs, Distance Education, Program Design, Advertising