The Impact of Generative AI on Research Attitudes and Motivation Among Graduate Teacher Education Students in a Philippine State University

Abstract

This research examined the perspectives of graduate teacher education (GTE) students on Generative Artificial Intelligence (GenAI), their motivation to use GenAI, and their research attitudes. The immediate integration of GenAI tools in higher education has transformed academic practices, yet its impact on research attitudes remains underexplored. Generative Artificial Intelligence is known for enhancing efficiency and supporting research tasks but concerns trust and academic integrity persist. In the current study, 307 GTE students enrolled at Cebu Technological University Main campus in Cebu City, Philippines for the school year 2025–2026 participated. The respondents were selected using convenience sampling with random selection within a cohort and completed a three-part adopted survey questionnaire. The data gathered were treated using descriptive statistics and Pearson’s r. The results revealed that the majority of the GTE students used GenAI occasionally while they commonly used ChatGPT (86.32%). The GTE students have a positive perception toward GenAI (WM = 36.38, SD = 0.81) and are highly motivated to use it (WM = 3.69, SD = 0.78). In addition, the GTE students have positive attitudes toward research (WM = 3.87, SD = 0.76). Moreover, correlational analysis revealed a strong positive correlation between the perception of GenAI and the motivation for its use (r = 0.726, p < 0.001). However, weaker significant relationships were demonstrated between students’ perception (r = 0.406, p < 0.001) and students’ motivation (r = 0.339, p < 0.001) to use GenAI and their attitudes toward research. These findings suggest that GenAI positively influences the attitudes of GTE students toward research but the cause may vary. Hence, this underscores the need for higher education institutions to facilitate policy development and curriculum design to promote the responsible, ethical, and effective use of artificial intelligence tools in GTE research.

Ähnliche Arbeiten