Analysis of System Quality Features In Workplace E-Learning Platforms That Affect Performance Expectancy And Effort Expectancy

Abstract

Caldera, Dilum Analysis of System quality features in workplace E-learning platforms that af-fect performance expectancy and effort expectancy Jyväskylä: University of Jyväskylä, 2024, 58 pp. Information Systems, Master’s Thesis Supervisor: Riekkinen, Janne This study investigates the critical features of workplace e-learning systems that affect user satisfaction and the intention to use these systems continuously, particularly within the context of Sri Lankan organizations. The study adapted the Unified Theory of Acceptance and Use of Technol-ogy (UTAUT) and the DeLone and McLean Information Systems Success Model (ISSM) to propose the theoretical framework and identified and evaluated 7 system features of e-learning systems, namely, learning content quality, content design quality, interactivity, user interface design, functionality and system response. These factors were tested to discover whether they had a relationship with performance expectancy and effort expectancy. A quantitative methodology was conducted, involving data collection from 123 working professionals across various industries in Sri Lanka. The findings reveal that while-learning content quality have a significant impact on performance expectancy, personalization significantly enhance both performance expectancy and effort expectancy, and the user interface design significantly impacts effort expectancy. Results also suggested that features such as interactivity and system response can have a negative impact on performance expectancy and effort expectancy. Performance expectancy was found to have a significant impact on intention to use the e-learning system. These results present valuable insights for e-learning system developers, user interface designers, instructional designers, HR managers and organizational decision makers to consider the quality features when designing and developing e-learning systems so as to increase user satisfaction and system adoption.

Keywords: E-learning Systems, User Adoption, User Acceptance, Quality Features, UTAUT, ISMM