Extending Technology Acceptance Model to higher-education students’ use of digital academic reading tools on computers

Abstract Digital academic reading tools on computers bring multiple benefits to higher-education students. Through structural equation modeling methods, this study contributes the following findings: (1) Perceived ease of use, perceived usefulness, and lecturers’ positive responses significantly predict students’ attitudes toward digital computers; (2) lectures’ responses, expectations achievement are predictors usefulness these tools; (3) intentions use (4) experience predicts negative (5) for collaborative learning self-efficacy using tools. Findings in may contribute understanding external factors influencing acceptance with a substantial explanatory power proposed model (R 2 = 64.70–84.20%), which benefit researchers, instructors, students, technology designers.