Technology Acceptance Model of Perplexity AI and Its Impact on Student Academic Achievement: A PLS-SEM Approach - Muhammad Ilham Suherman; Haripuddin; Ninik Rahayu Ashadi; Wirawan Setialaksana; Muhammad Riska (Journal of Education for Creativity and Innovation, 2026)
This study aims to analyze the effect of using Perplexity AI on the academic achievement of students in the Informatics and Computer Education Study Program at Makassar State University using the Technology Acceptance Model (TAM) framework. The background of this study is based on the increasing use of artificial intelligence in higher education, particularly the use of Perplexity AI, which helps students complete academic assignments and search for references. Although it offers convenience, the use of AI also poses challenges related to critical thinking and academic integrity, while research examining its influence on student academic achievement is still limited. This study uses a quantitative approach with an ex-post facto design. The research sample consisted of 249 students from the 2022–2023 cohort, determined using probability sampling techniques. Data were collected through questionnaires and analyzed using Partial Least Square–Structural Equation Modeling (PLS-SEM). The results show that Perceived Ease of Use (PEOU) has a significant effect on Perceived Usefulness (PU) with a value of β=0.800, t=27.297, p<0.001, but no significant effect on Behavioral Intention (BI) with a value of β=0.038, t=0.465, p=0.642. Furthermore, PU significantly affects BI with a value of β=0.685, t=8.724, p<0.001 and Academic Achievement (PA) with a value of β=0.368, t=4.220, p<0.001. BI significantly affects Actual System Usage (ASU) with a value of β=0.758, t=17.614, p<0.001, and ASU significantly affects PA with β=0.489, t=5.847, p<0.001. Therefore, it can be concluded that the use of Perplexity AI has a positive impact on improving student academic achievement through perceived benefits and actual usage intensity.