Development of AI Adaptive, and Recommendation Course on LMS for Optimization of Digital Learning Services

The Use of Adaptive Feedback using Artificial Intelligence (AI) in a Learning Management System (LMS) is an innovative way to provide automatically tailored feedback to users based on their behavior and performance. This important research process also considers feedback from AI tailored to each user's individual needs and level of understanding. Research methodology conducted by making prototype LMS platform model based on AI through creating personalization or learning style for each user, developing a feedback system for users, analyzing needs and designing user learning patterns, integration of learning resources, and data analysis and decision-making, also creating learning routes and monitoring user progress. Research process was designed by AI algorithms to systematically collect and analyse based on data, including course types, student performance, engagement metrics, and interaction patterns, teachers and score of assessment specific to the open and distance education context. The AI-driven adaptive feedback system provides real-time, personalized feedback, emphasizing strengths, pinpointing areas for leaning. Seamlessly integrated into the LMS, the user-friendly interface features a visual analytics dashboard, benchmarking capabilities, Research conclusion has represented a significant AI to elevate reflective feedback on course recommendation and materials personally of students before, ultimately enhancing the quality of education services.

Authors

Publication Details

Journal
Nanotechnology Perceptions
Published
2024-11-04
DOI
https://doi.org/10.62441/nano-ntp.vi.3008
Citations
1
Primary Topic
Technology and Data Analysis
Type
article
Field-Weighted Citation Impact
0.78
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article

Development of AI Adaptive, and Recommendation Course on LMS for Optimization of Digital Learning Services

Muhammad Ashar, Deni Darmawan, Ikhsan Ikhsan
1 citations
Nanotechnology Perceptions
Technology and Data Analysis
0.78
article

Development of AI Adaptive, and Recommendation Course on LMS for Optimization of Digital Learning Services

Muhammad Ashar, Deni Darmawan, Ikhsan Ikhsan
article en
1 citations

Abstract

The Use of Adaptive Feedback using Artificial Intelligence (AI) in a Learning Management System (LMS) is an innovative way to provide automatically tailored feedback to users based on their behavior and performance. This important research process also considers feedback from AI tailored to each user's individual needs and level of understanding. Research methodology conducted by making prototype LMS platform model based on AI through creating personalization or learning style for each user, developing a feedback system for users, analyzing needs and designing user learning patterns, integration of learning resources, and data analysis and decision-making, also creating learning routes and monitoring user progress. Research process was designed by AI algorithms to systematically collect and analyse based on data, including course types, student performance, engagement metrics, and interaction patterns, teachers and score of assessment specific to the open and distance education context. The AI-driven adaptive feedback system provides real-time, personalized feedback, emphasizing strengths, pinpointing areas for leaning. Seamlessly integrated into the LMS, the user-friendly interface features a visual analytics dashboard, benchmarking capabilities, Research conclusion has represented a significant AI to elevate reflective feedback on course recommendation and materials personally of students before, ultimately enhancing the quality of education services.

Nanotechnology Perceptions
Openalex Percentile: Top 19%
Technology and Data Analysis
0.78
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Development of AI Adaptive, and Recommendation Course on LMS for Optimization of Digital Learning Services — Muhammad Ashar, Deni Darmawan, et al. · Nanotechnology Perceptions (2024) | TGRS Research Map | TGRS