Vol. 2 No. 3 (2023): December Special Issue of The QUEST: Journal of Multidisciplinary Research and Development
Articles

Development and Assessment of Learning System with Analytics

  • Ye He,
  • Jet Aquino
Ye He
Chongqing Vocational College of Building Technology
Jet Aquino
Nueva Ecija University of Science and Technology
DOI: https://doi.org/10.60008/thequest.v2i3.97

Published 12/30/2023

Keywords

  • Analytics; Learning Development System; Learning System

How to Cite

He, Y., & Aquino, J. (2023). Development and Assessment of Learning System with Analytics. The QUEST: Journal of Multidisciplinary Research and Development, 2(3). https://doi.org/10.60008/thequest.v2i3.97

Copyright (c) 2023 The QUEST: Journal of Multidisciplinary Research and Development

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Abstract

This study focuses on exploring the feasibility and effectiveness of employing data analysis techniques in the development of learning systems. Through a comprehensive evaluation of existing learning systems, this research identifies their principal advantages and disadvantages. In response to these issues, a novel learning system is proposed, leveraging data analysis to optimize the learning process. Experimental verification demonstrates a significant enhancement in learning effectiveness and learner satisfaction with this innovative system. The research findings provide valuable guidance for the design and application of future learning systems, emphasizing the importance of considering factors such as cost-effectiveness, sustainability, and long-term benefits for successful development and implementation. Results from an acceptability score survey indicate positive ratings from end users for the Learning System with Analytics, covering functionality, performance efficiency, compatibility, usability, reliability, maintainability, and security. Users express satisfaction with the system's performance, reliability, ease of maintenance, and security. The developed system is recognized as functional, reliable, usable, efficient, maintainable, and portable according to user feedback. Additionally, user suggestions are deemed valuable for potential enhancements to the system in the future. Overall, this research contributes insights into the application of data analysis in learning systems, emphasizing user satisfaction and offering practical implications for system development and refinement.

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