AI-Based Learning Content Generation and Learning Pathway Augmentation to Increase Learners Engagement
Year: 2025
Type: article
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.
Author: Mr. Arun Pratap Singh
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: diamond
OpenAlex ID: W4408622166