Continue to use Quality Model (CTU-QM) for e-learning Systems based on User Perspective - Abdulhakim Elmoawe Dhow Dreheeb
Recently e-learning systems have emerged as the new paradigm of modern education in the world. The use of e-learning systems has grown rapidly, however its success remains uncertain. From 2005 to 2010, the average dropout rate of e-learners was reported as 40% and the tendency for students to discontinue to use due to low quality of e-learning systems without warning is the most critical issue. The lack of system quality during users’ initial experience has affected the usage of e-learning systems. System quality has a strong relation to the success of e-learning. If the system quality does not meet the users’ expectation, it will discourage users to continue to use e-learning and sustain the usage. Therefore, the main objective of this research is to identity attributes that affect the e-learning usage from the user perspective and develop the Continue to Use Quality Model (CTU-QM). The CTU-QM is derived from the Delone and McLean Model and Expectation-Confirmation Model. The main quality attributes and sub-attributes in the odel were selected based on the Attributes Comparison Matrix Analysis. The relationship between the attributes, sub-attributes and components in the model were evaluated through quantitative evaluation.A total of 408 completed questionnaires were collected and analysed. The questionnaires were distributed to several Malaysian universities in the Kelang Valley. The survey results show that learnability and attractiveness are the sub-attributes to usability (R²=51%); maturity, fault tolerance and consistency are the sub-attributes to reliability (R²=38%); and time behaviour and resource utilization are sub-attributes to efficiency (R²=61%). In comparison, CTU-QM has higher exploratory power (R²=57%) than other existing models that measure system quality to satisfaction and higher exploratory power (R²=55.3%) than other existing models that measure satisfaction to continue to use. This is due to the quality attributes and sub-attributes that have been used in the model. It is hoped that the findings can assist the e-learning developers to develop better systems that meet users’ needs and thus sustain their e-learning usage.