The Task-Technology Fit, Technology Induced Engagement, and Technology Induced Motivation on Higher Education Students Learning Performance during COVID-19

Abstract

Indonesia was one of the countries affected by the COVID-19 pandemic. This condition encourages the implementation of various policies, including online learning for students to prevent the spread of the virus. Unfortunately, students have difficulties with this learning system. Therefore, this research aims to analyze the condition factors that support learning performance for university students in Indonesia, namely Task-Technology Fit (TTF), Technology-Induced Engagement (TIE), and Technology-Induced Motivation (TIM). Demographic factors, such as location and gender, were also considered in the analysis. Learning success is assessed from the student's Grade Point Average (GPA) during one semester of online lectures. Data collection was carried out using an online questionnaire strategy, which succeeded in reaching 40 valid respondents. The fuzzyset Qualitative Comparative Analysis (fsQCA) method was used to analyse the configuration model for student online learning success. This research succeeded in formulating six combinations of factor conditions that were sufficient to achieve online learning success. Successful online learning includes whether it was related to gender or not, as well as the location of the student's home, and a combination of other factors. Three combinations of conditions that must exist in every successful configuration of student online learning in Indonesia are, urban study location, students having a high TIE, and also a high TIM. The results of this study contribute to lecturers and higher education management regarding the conditions that need to be prepared to support the success of students' online learning.