Artificial Intelligence for Education and Research: Pilot Study on Perception of Academic Staff

Jelena Titko (), Kaspars Steinbergs (), Mourine Achieng () and Kristine Uzule ()
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Jelena Titko: EKA University of Applied Sciences, Str. Pernavas 62, Riga, LV-1009, Latvia
Kaspars Steinbergs: EKA University of Applied Sciences, Str. Pernavas 62, Riga, LV-1009, Latvia
Mourine Achieng: University of South Africa Graduate School of Business Leadership, Cnr Janadel and, Alexandra Ave, Midrand, 1686, South Africa
Kristine Uzule: EKA University of Applied Sciences, Str. Pernavas 62, Riga, LV-1009, Latvia

Virtual Economics, 2023, vol. 6, issue 3, 7-19

Abstract: Artificial Intelligence (AI) tools have been used across various sectors of the global economy. The use of AI has been associated with both benefits and drawbacks, which is why the goal of this research was to identify the attitudes of academic staff of higher education institutions (HEIs) towards using AI for both academic and research purposes. To attain the goal, there was designed a questionnaire, which was distributed to members of academic staff of different biological genders and ages from 10 European countries. Irrespective of biological gender, age, or country, responses were similar. First, academic staff emphasized the importance of having AI-related regulations at HEIs. Second, academic staff were positive about using AI for information searchers and preparation of teaching materials. Third, academic staff were concerned about AI-related plagiarism issues, which is why they were reluctant to approve the AI use for research and thesis writing. Fourth, slightly more than 40% of the respondents indicated the use of AI. This points to the lack of AI skills among academic staff, which was further supported by a set of basic purposes for which AI was claimed to have been used. One implication of this research relates to the organization of the study process. Managers of HEIs should introduce institutionalized training in AI for academic and research purposes for academic staff to promote digital equality. Another implication of the study relates to the areas of AI training for academic staff. It should cover the topics of AI for the design of teaching materials, formative and summative assessment, and plagiarism check.

Keywords: artificial intelligence; research; education; perception; academic staff (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:aid:journl:v:6:y:2023:i:3:p:7-19

DOI: 10.34021/ve.2023.06.03(1)

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