BASIC KNOWLEDGE AND UNDERSTANDING OF AI AMONG UNDERGRADUATE STUDENTS AT KASETSART UNIVERSITY

Abstract

This study's aims were to: 1) examine the level of basic knowledge and understanding of AI among among undergraduate students at Kasetsart University, 2) compare the basic knowledge and understanding of AI according to demographic factors, and 3) examine the correlation between frequently used media and the level of basic knowledge and understanding of AI. The sample was 305 undergraduate students at Kasetsart University enrolled for the second semester of the 2024 academic year. Questionnaires collected data. The statistical methods utilized included frequency, percentage, mean, standard deviation, t-tests, One-Way ANOVA, Scheffé tests, Chi-square, and Cramér's V, with a significance level of 0.05. The findings indicated that the sample possessed a strong degree of basic knowledge and comprehension of AI (mean = .82, S.D. = .17). When examined by distinct areas, all were identified to be at a high level, comprising Deep Learning (mean = .86, S.D. = .19), fundamental AI knowledge (mean = .81, S.D. = .19), AI usage at Kasetsart University (mean = .81, S.D. = .23), and Machine Learning (mean = .80, S.D. = .21). The hypothesis testing showed that there was no significant difference in the basic knowledge and understanding of AI according to sex, year of study, and faculty. Moreover, frequently used media showed a weak positive correlation with the level of basic knowledge and understanding of AI (Cramér's V = .105).