Global Journal of Human Social Science, G: Linguistics and Education, Volume 25 Issue 3

1 2 3 4 5 6 7 8 9 10 11 12 1. Attitude towards using ChatGPT 2. Behavioral Intention 0,705 3. ChatGPT Resistance 0,197 0,218 4. Ethical Values/Morals/Integrity 0,225 0,364 0,114 5. Perceived Academic Integrity 0,697 0,457 0,074 0,282 6. Perceived Bias/Inaccuracies 0,172 0,144 0,330 0,111 0,091 7. Perceived Credibility 0,716 0,704 0,205 0,207 0,519 0,170 8. Perceived Instructor AI Competency 0,257 0,301 0,108 0,429 0,345 0,175 0,319 9. Perceived Usefulness 0,682 0,735 0,269 0,349 0,425 0,086 0,554 0,267 10. Riligosity 0,306 0,269 0,088 0,270 0,113 0,202 0,224 0,201 0,243 11. Student Digital Literacy 0,498 0,659 0,241 0,555 0,459 0,083 0,427 0,530 0,588 0,224 12. Social Norms 0,327 0,477 0,070 0,571 0,271 0,185 0,306 0,356 0,377 0,284 0,408 b) Assessment of the Structural Model Given the fact that the measurement model has been proven to be correct, it is now possible to move on to the structural model portion of the study. According to Cohen (1992) r-square value .12 or below indicate low, between .13 to .25 values indicate medium, .26 or above and above values are considered high . Table 4 highlights the (R 2 ) for all endogenous variables in the study, highlighting the fact that they exceed 0.26 and above. R Square Cohen (1992) Attitude towards using ChatGPT 0.554 High Behavioral Intention 0.364 High c) Direct Relationships From the results obtained in Table 5, this study explores the factors influencing the adoption and usage of ChatGPT among students in universities. The analysis for Hypothesis 1 (H1), it finds that if students think ChatGPT is useful (beta = 0.270, p-value = 0.000), they will have a more positive attitude towards it. This agrees with other research showing that AI tools can improve learning quality and offer practical benefits in learning environments. For Hypothesis 2 (H2), if students think ChatGPT is trustworthy (beta = 0.255, p-value = 0.000), they will also have a positive attitude. Trust is important for adopting new educational technologies. Hypothesis 3 (H3) is not supported since the P value is higher than 0.05 (p-value = 0.286, beta = 0.052), meaning what peers think doesn’t really affect student attitudes towards ChatGPT. Students care more about their own experiences and preferences than about social influences. This could be because students personal experiences and preferences are more important than what their peers think. Hypothesis 4 (H4) is also not supported (p-value = 0.268, beta = 0.061), showing that knowing how to use digital tools doesn’t make students more likely to like ChatGPT. Familiarity with digital tools doesn't necessarily predict favorable attitudes towards specific technologies. Hypothesis 5 (H5) is supported since the p value is lower than 0.05 (beta = 0.092, p-value = 0.046). Even if students think ChatGPT might have some bias or inaccuracies, they still tend to like it. This indicates that concerns about biases can actually engage students to use ChatGPT. Hypothesis 6 (H6) is supported (beta = -0.098, p-value = 0.014), showing that resistance to new technology makes students less likely to like ChatGPT. This reflects the challenges in technology adoption where resistance can stem from various user concerns. Hypothesis 7 (H7) is not supported because the p value is higher than 0.05 (beta = -0.077, p-value = 0.143), meaning ethical concerns don’t really affect student attitudes towards ChatGPT. Other factors, like how useful or easy ChatGPT is to use, might be more important to students than ethical considerations. Hypothesis 8 (H8) is strongly supported (beta = 0.343, p-value = 0.000), showing that if students think ChatGPT helps with ChatGPT in Moroccan Education Sector: Examining the Attitude of Student Acceptance and Usage Intent Global Journal of Human-Social Science ( G ) XXV Issue III Version I Year 2025 17 © 2025 Global Journals Table 3: Disciminant Validity (Heterotrait-Monotrait Ratios-HTMT) Table 4: Coefficient of Determination