AI-Based Learning Content Generation and Learning Pathway Augmentation to Increase Learners Engagement

This project investigates AI-driven methods for creating learning material and enriching learning paths to increase learner participation in online learning environments. Conventional MOOCs are hindered by high dropout rates and low participation, mainly because of static, non-interactive content. To overcome this, the project suggests incorporating narrative structures into learning paths, dynamically interweaving them with AI-created content referred to as “narrative fragments”. These pieces comprise “summaries” and “reflection quizzes” that help learners and evaluate their comprehension. The method utilizes Natural Language Processing (N1LP) and Natural Language Generation (NLG) methods in the form of GPT-2 to create content using different learning materials. This process is subject-agnostic, making it possible to be versatile across learning topics, thereby boosting engagement and the efficiency of learning. The system has been rated with automatic metrics and human raters, with promising outcomes in both content quality and potential for learner interaction.

Authors

Publication Details

Journal
International Journal for Research in Applied Science and Engineering Technology
Published
2025-03-19
DOI
https://doi.org/10.22214/ijraset.2025.67456
Primary Topic
Educational Technology and Assessment
Type
article
Field-Weighted Citation Impact
0.00
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article

AI-Based Learning Content Generation and Learning Pathway Augmentation to Increase Learners Engagement

Man Singh
International Journal for Research in Applied Science and Engineering Technology
Educational Technology and Assessment
article

AI-Based Learning Content Generation and Learning Pathway Augmentation to Increase Learners Engagement

Man Singh
article en

Abstract

This project investigates AI-driven methods for creating learning material and enriching learning paths to increase learner participation in online learning environments. Conventional MOOCs are hindered by high dropout rates and low participation, mainly because of static, non-interactive content. To overcome this, the project suggests incorporating narrative structures into learning paths, dynamically interweaving them with AI-created content referred to as “narrative fragments”. These pieces comprise “summaries” and “reflection quizzes” that help learners and evaluate their comprehension. The method utilizes Natural Language Processing (N1LP) and Natural Language Generation (NLG) methods in the form of GPT-2 to create content using different learning materials. This process is subject-agnostic, making it possible to be versatile across learning topics, thereby boosting engagement and the efficiency of learning. The system has been rated with automatic metrics and human raters, with promising outcomes in both content quality and potential for learner interaction.

International Journal for Research in Applied Science and Engineering TechnologyVol. 13(3)
Openalex Percentile: Top 94%
Educational Technology and Assessment
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AI-Based Learning Content Generation and Learning Pathway Augmentation to Increase Learners Engagement — Man Singh · International Journal for Research in Applied Science and Engineering Technology (2025) | TGRS Research Map | TGRS