Applying the Technology Acceptance Model (TAM) to Automatic Grading Technology for Large Projects

Christopher Kreider, Georgia Institute of Technology


Autograding technology, a form of Computer Based Assessment (CBA), should allow course enrollments to grow without reducing the number of exercises, however, these gains are not expected to be immune to problems with adoption. This study utilizes the Technology Acceptance Model (TAM) to explore student and staff perceptions of autograding technology. This phenomena in the context of large projects. Our study explores the perceptions of 128 students and course staff in an online master degree program in computer science at a large public university. Our research design was chosen to leverage existing theories while also providing findings that will enable practitioners to apply them to their decision making regarding autograding technology. We find that perceived usefulness was significantly correlated with behavioral intention for both students and staff, leading to our hypotheses being supported and partially supported. Additionally, we find that perceived ease of use is only significantly correlated with student’s intentions, and does not apply to course staff.