SATISFACTION WITH AI FOR REPORT GENERATION AMONG UNDERGRADUATE STUDENTS AT KASETSART UNIVERSITY

Abstract

The aims of this research were (1) to assess the level of satisfaction among undergraduate students at Kasetsart University, (2) to compare the satisfaction across different demographic factors, (3) to compare the satisfaction based on the frequency of AI utilization, (4) to compare the satisfaction based on the duration of AI utilization, (5) to investigate the association between AI-assisted tools and the satisfaction, and (6) to study the association between the interface and the satisfaction. Data from 305 students (semester 2/2024) were collected via questionnaire and analyzed using frequency, percentage, mean, standard deviation, t-test, ANOVA, Scheffé, Chi-square, and Cramér's V (α = .05). Overall, the findings indicate that the level of satisfaction was high (Mean = 3.98, S.D. = .55). In addition, the results indicated that mean scores were relatively high across almost all areas, including usability (Mean = 4.19, S.D. = .59), efficiency (Mean = 4.14, S.D. = .62), functionality (Mean = 4.07, S.D. = .64), portability (Mean = 3.98, S.D. = .66), maintainability (Mean = 3.85, S.D. = .70), and reliability (Mean = 3.57, S.D. = .81). The hypothesis testing showed that variations in faculty and the frequency of AI usage resulted in significant differences in the satisfaction. Nonetheless, no notable differences in satisfaction were found concerning sex, academic year, and the length of AI use. Moreover, AI-assisted tools exhibited a weak positive association with the satisfaction level (Cramér’s V = .182). Lastly, the interface had a weak positive association with the satisfaction level (Cramér’s V = .113).