EDUCATOR PERSPECTIVES ON GENERATIVE AI IN HIGHER EDUCATION: TEACHING PRACTICES AND INSTITUTIONAL READINESS
Abstract
The use of generative AI in higher education is becoming more apparent, but adoption is uneven and shaped by issues of
usefulness, readiness, and responsible use. It is also of significance to comprehend how teachers see these tools in order
to interpret their impact in pedagogy and institutional preparedness. This study examined educator perspectives on
generative AI in higher education, with attention to patterns of use, perceived impact across key academic domains, and
differences between AI users and non-users. A quantitative secondary analysis was conducted using cross-sectional survey
data from 139 university educators. Descriptive statistics were used to summarize respondent characteristics and
perception patterns, while Mann–Whitney U tests and chi-square analyses were applied to examine group differences and
associations. More than half of the respondents reported using AI tools, and overall perceptions were moderately positive.
The strongest agreement was observed for training needs and administrative efficiency. Educators with prior AI use
reported significantly more favorable views regarding teaching processes, administrative tasks, student understanding,
and career-related guidance, while concerns related to training, data use, and student dependency were evident across
groups. Generative AI is therefore viewed primarily as a practical support tool rather than a substitute for educators, and
its effective integration appears to depend on institutional guidance, professional development, and responsible use
frameworks.
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