Predictive Model for Factors Influencing Students’ Continuance Usage Intention on a Gamified Formative Assessment Application - Roslan, Rosfuzah; Mohd Ayub, Ahmad Fauzi; Ghazali, Norliza; Zulkifli, Nurul Nadwa; Md Latip, Siti Noor Haslina; Abu Hanifah, Siti Syuhada (Journal of Technical Education and Training, 2023)
Formative assessments help students identify their strengths and weaknesses as well as the target areas that need work. Meanwhile, the success of gamification implementation in mobile learning (m-learning) applications has been proven by many research associated with technology acceptance. However, studies on the technology post-acceptance phase are scarce. Deploying gamification concepts in competency-based education and assessment method, aim to diversify the game dynamics usage in new and practical areas such as technical and vocational education. Therefore, this study focused on the development of a predictive model for a gamified m-learning application that extends the Expectation Confirmation Model (ECM) with perceived enjoyment. This study applied a correlational research design on the students of Technical and Vocational Education and Training (TVET) based diploma programmes in one of Malaysian public university. An online survey was conducted, and garnered 269 responses, which were used in the final analysis based on the Partial Least Square-Structural Equation Modelling (PLS-SEM). The findings showed that all the factors in the model, which are the confirmation of expectation, satisfaction, perceived usefulness and perceived enjoyment, appeared to be significantly influencing the students’ continuance usage intention towards the gamified m-learning application as well as jointly explained 64.6% (R2) of the changes. The addition of variable perceived enjoyment provided an increment of 2.7% compared to the R2 value of the original ECM model. Most importantly, the proposed extended ECM proved to be a reliable prediction model when the Q2 values for continuance use intention and perceived usefulness displayed strong predictive accuracy, having 0.368 (Q2) for both variables, while satisfaction showed moderate strength with the value of 0.305 (Q2). Therefore, the predictive model is reliable to be used to investigate future usage and effective designs of gamified m-learning products among the technical and vocational education students in other Higher Education Institution (HEI).