A Multimodal Sentiment Analysis Framework for Personalized Mentoring in Learning Management Systems.
Year: 2026
Type: book
Abstract: The proliferation of online learning in today's digital world necessitates advanced techniques for personalized mentoring.Online learning has transformed education, but its success hinges on maintaining learner engagement and motivation.A learner's emotional state plays a crucial role in online learning, influencing motivation, engagement, and comprehension.Unlike traditional classrooms, digital environments often lack real-time emotional cues, making it harder to detect struggles or disengagement.Understanding and responding to a learner's emotions enables personalized interventions to create an effective learning experience that enhances both academic performance and well-being.Learning Management Systems (LMS) must recognize learners' preferences, needs, and learning styles to adapt themselves and provide the necessary recommendations and personalized content.Our objective in this paper is a discussion on personalized mentoring-based learning management systems (LMSs) that will enhance the learning motivation of an e-learner through multimodal sentiment analysis (MSA).The emotional state of a learner is a major contributing factor to his or her learning quality.This research states how emotional states could be identified by MSA techniques from their reactions and feedback on different social media platforms like Facebook, Instagram, and Twitter by applying Natural Language Processing (NLP), Computer Vision (CV), Prompt Engineering using Generative AI, and Agentic AI.....
Institution: JIS University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: gold
OpenAlex ID: W7204190375