AN EVALUATION OF THE INFORMATION QUALITY OF THE KU GENAI PLATFORM AMONG UNDERGRADUATE STUDENTS AT KASETSART UNIVERSITY

Abstract

This study aimed to: (1) examine the level of information quality evaluation of the KU GenAI platform among undergraduate students at Kasetsart University; (2) compare evaluations across personal factors; (3) investigate the association between instructors’ support for AI use and information quality evaluation; (4) examine the relationship between instructional materials for AI use and evaluation levels; and (5) explore the association between prompt engineering knowledge and information quality evaluation. The sample consisted of 530 undergraduate students enrolled in the second semester of the 2025 academic year. Data were collected using a questionnaire. Statistical analyses included frequency, percentage, mean, standard deviation, t-test, One-Way ANOVA with Bonferroni post hoc comparison, Chi-square, Cramér’s V, and Pearson correlation, with a significance level of .05. The results showed that the overall level of information quality evaluation of the KU GenAI platform was high (Mean = 4.14, S.D. = .54). All dimensions were rated at a high level, including answer presentation (Mean = 4.21, S.D. = .53), alignment with user needs (Mean = 4.17, S.D. = .57), and information credibility (Mean = 4.04, S.D. = .61). Hypothesis testing showed that students’ evaluations of information quality differed significantly by sex, faculty, and AI usage experience. Instructors’ support and instructional materials for AI use had weak positive associations with evaluation levels (Cramér’s V = .13). Knowledge of prompt engineering showed a small positive correlation with information quality evaluation (r = .284).

Keywords: Information Quality, Generative Artificial Intelligence in Higher Education, User Evaluation, AI-Supported Instruction, Prompt Engineering Knowledge