THE USE OF GENERATIVE ARTIFICIAL INTELLIGENCE IN HIGHER EDUCATION: UNIVERSITY SOCIAL RESPONSIBILITY AND STAKEHOLDERS’ PERCEPTIONS
DOI:
https://doi.org/10.17770/etr2024vol2.8015Keywords:
generative artificial intelligence; higher education, information technologies; technological integration in academia; university social responsibilityAbstract
This pilot study assesses the reliability and validity of measurement tools and instrumentation to ensure accurate measurement of the variables and defines possible problems of the follow-up larger-scale research. The study’s overall goal is to measure stakeholders' perspectives on the use of generative artificial intelligence (AI) in higher education and its implications for university social responsibility (USR) with the purpose of better understanding how AI technologies are deployed in academic institutions. The primary aim of this pilot study is to evaluate the effectiveness of the designed questionnaire by calculating Cronbach's alpha coefficient of the measurement scales. A questionnaire of 20 items was disseminated to the relevant stakeholders, including students, and academic and administrative staff, with the total number of received valid responses being 101. Cronbach's alpha was used as a measure of internal consistency to test the reliability of the measurement scale that consists of two groups of items: Scale B) perceptions of AI use in higher education of all the relevant stakeholders; Scale C) AI integration into higher education and its implications for USR. Key findings and implications from the study results include good or acceptable internal consistency > 0.7 among the majority of the items in the questionnaire. Specific recommendations for improving some of the items were suggested based on the findings. Modifying language, rephrasing questions, or deleting items that lead to reduced internal consistency are examples of these. The pilot study provides useful insights on the viability of employing the questionnaire in a larger-scale study, and considerations for time and resource allocation to ensure practicality in the subsequent study.
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