Creating an integrative research framework that extends a model frequently used in the Information Systems field, the Technology Acceptance Model, together with variables used in the Education field, this empirical study investigates the factors influencing student performance as reflected by their final course grade. The Technology Acceptance Model explains computer acceptance in general terms. The model measures the impact of external variables on internal beliefs, attitudes, and intentions. Perceived Usefulness and Perceived Ease of Use, two main constructs in the model, refer to an individual's perception of how the adoption of a new technology will increase their efficiency, and the individual's perception of how easy the technology will be to use. The lower the perceived effort is, the easier the technology will be to adopt. Thus, Perceived Usefulness, Perceived Ease of Use, Computer Self-Efficacy, and Computer Anxiety were measured to determine their effect on student performance. The proliferation of the personal computer was possible because of the applications written for it. The continuous creation of new applications has created ample ground to test the Technology Acceptance Model to determine how a user will decide to adopt such applications. The recent escalation of delivering online education via the Internet has again sparked a new dimension of information systems. This has given rise to research using the Technology Acceptance Model for applications in the Education field. Today’s modern classroom, whether online or campus-based, uses e-learning tools and Learning Management Systems that capture student cognition and engages them in the learning process via technology, while increasing their need for self-directedness. In view of this, the present study also considers the students’ ability to work independently. The results of the statistical analysis used in this study revealed marked differences in student perceptions of e-learning tools between students who chose to take an online course and students who preferred to take the campus-based section. Additionally, Perceived Usefulness, Perceived Ease of Use, and the students’ ability to work independently were all statistically significant factors in predicting students’ final grades.
Galy, Edith, et al. “The Effect of Using E-Learning Tools in Online and Campus-Based Classrooms on Student Performance.” Journal of Information Technology Education: Research, vol. 10, 2011, pp. 209–30. doi:10.28945/1503.
Journal of Information Technology Education: Research