Artificial Intelligence in Educational Technology: Transforming Learning Culture in the Digital Age

Abstract

Artificial intelligence (AI) is becoming a big part of educational technology, impacting various facets of student access to information, academic work, and digital learning. This study examined AI-related performance expectations, perceived challenges, attitudes, perceptions, and motivation among higher education students and identified the factors predicting motivation and intention to use AI for learning. A quantitative cross-sectional design was applied to secondary survey data from 535 higher education students in Indonesia. Five constructs were measured using 39 four-point Likert-scale items. Descriptive statistics, Cronbach's alpha, Pearson correlation, and multiple linear regression with HC3 robust standard errors were employed for analysis. Performance Expectations recorded the highest mean score (M = 3.055, SD = 0.576), whereas Challenges of AI Use had the lowest (M = 2.459, SD = 0.661). All constructs were positively correlated. Motivation and Intention showed the strongest associations with Attitudes Toward AI (r = 0.663) and AI Use Perceptions (r = 0.619). The regression model explained 55.3% of the variance in motivation and intention. Attitudes Toward AI (β = 0.370), AI Use Perceptions (β = 0.304), and Performance Expectations (β = 0.211) significantly predicted motivation, whereas AI Use Challenges did not. The results emphasize the need for a positive attitude, positive perception, and perceived educational benefits as factors in creating an AI learning culture.