ERIC Number: EJ1466230
Record Type: Journal
Publication Date: 2025
Pages: 14
Abstractor: As Provided
ISBN: N/A
ISSN: N/A
EISSN: EISSN-1302-6488
Available Date: 0000-00-00
Improving Online Learning Using Deep Learning and Student's Intelligences
Turkish Online Journal of Distance Education, v26 n2 Article 3 p39-52 2025
The emergence of online learning has sparked increased interest in predicting learners' academic performance to enhance teaching effectiveness and personalized learning. In this context, we propose a complex model APPMLT-CBT which aims to predict learners' performance in online learning settings. This systemic model integrates cognitive, social, emotional, contextual, and normative aspects to predict the learners' performance in online learning environment. This model, based on Competency-Based Learning Traces, takes a holistic approach by integrating various data reflecting knowledge acquisition and skills development. By taking into account the exchanges among the learners, as well as the interactions with their teachers and the complexity of their online learning environment, the model aims to provide accurate and informed predictions of academic performance. This study provides a detailed overview of the APPMLT-CBT model, its data collection methodology, and discusses its potential implications for online teaching. Results suggest that the model can serve as a robust framework for improving online teaching and learning while offering a deep understanding of the underlying mechanisms of online learning.
Descriptors: Models, Online Courses, Educational Improvement, Learning Processes, Academic Achievement, Instructional Effectiveness, Individualized Instruction, Competency Based Education, Holistic Approach, Teacher Student Relationship, Peer Relationship, Prediction, Skill Development, Accuracy, Learning Analytics, Algorithms, Artificial Intelligence, Computer Software, Multiple Intelligences, Scores
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Publication Type: Journal Articles; Reports - Descriptive
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A
Author Affiliations: N/A