Performance Evaluation and Improvement Decision-Making Rules for E-Learning System  
Author Yen-Po Chen

 
Co-Author(s) Yu-Ling Chen;  Chun-Hung Yu; Chun-Min Yu

 
Abstract With the maturity of the Internet of Things (IoT), and especially after the COVID-19 pandemic, online courses at all levels of education have become mainstream, often replacing in-person instruction. Improving the operational performance of e-learning systems can enhance learner satisfaction, attract more geographically dispersed learners, create more business and increase economic activity. Additionally, since learners can study from home, this reduces traffic impact and lowers carbon emissions, thereby alleviating environmental pollution. A solid evaluation and improvement decision model for e-learning systems helps system administrators understand user satisfaction across various service components. Therefore, this paper designed a questionnaire to investigate user satisfaction. A performance evaluation matrix was constructed using the satisfaction index of each service item as the horizontal axis and the influence index of the correlation between each service item and overall satisfaction as the vertical axis. Using statistical testing principles, we also propose an improvement decision model to identify critical-to-quality (CTQ) items. Under limited resources, this model can assist administrators in prioritizing which service items to improve to enhance overall learner satisfaction.

 
Keywords E-learning system, IoT, Satisfaction index, Influence index, Performance evaluation matrix
   
    Article #:  RQD2025-77
 

Proceedings of 30th ISSAT International Conference on Reliability & Quality in Design
August 6-8, 2025