Artificial intelligence awareness perception acceptance and utilization as predictors of academic publishing competence among academics in Nigerian universities

Bibliographic Data

ID24021575
AuthorsUsani Joseph Ofem (0000-0001-8906-7954, Funai Electric (Japan), corresponding author), Ntabiosi C N Igu (Funai Electric (Japan)), Patricia Olom (University of Calabar), Catherine Nkiruka Elechi, Emeka Nwinyinya (Funai Electric (Japan)), Asenath Ebaye (University of Cross River State), Veronica Ngozi Odenigbo (Enugu State University of Science and Technology), Getrude Nkechi Okenwa (Enugu State University of Science and Technology), Thelca Amogechukwu Eze (Enugu State University of Science and Technology), James Omaji Ukatu (Funai Electric (Japan)), James Ukatu
Year2026
Volume4
Issue1
Publication date2026-08-04
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueDiscover Global Society (JOURNAL)
Journal identifiersISSN: 2731-9687 • E-ISSN: 2731-9687
PublisherSpringer Science+Business Media (PUBLISHER • DE)
DOI10.1007/s44282-026-00474-8
OpenAlexW7172389945
LanguageEN
References cited76

The adoption of Artificial Intelligence (AI) in higher education has significantly reshaped research and academic publishing by providing tools that facilitate literature review, data analysis, manuscript preparation, and plagiarism detection. Despite increasing attention on AI in academia, the impact of academic staff’s awareness, perception, acceptance, and utilization of AI on research publishing competence remains insufficiently investigated, especially in Sub-Saharan universities. This study explored these relationships among 1,420 academic staff from five public universities using a predictive correlational research design. Data were gathered through five validated instruments with strong psychometric properties and analyzed via descriptive statistics, one-sample t-tests, and multiple linear regression. The results indicated that staff demonstrated moderately positive awareness and perception of AI, while acceptance and utilization levels were high, reflecting increasing adoption in research activities. Regression analysis identified AI utilization as the most significant predictor of research publishing competence, followed by acceptance and awareness, whereas perception showed a minimal negative effect. These findings imply that while knowledge and positive attitudes toward AI are relevant, active engagement with AI tools is the key determinant of publishing competence. The study underscores the importance of structured training, institutional support, and policy initiatives to promote effective AI integration, enhancing research productivity, publication quality, and academic competitiveness globally.

Competence (human resources) · Descriptive statistics · Higher education · Perception · Publishing · Self-efficacy · Artificial Intelligence in Healthcare and Education · Ethics and Social Impacts of AI · scientometrics and bibliometrics research

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Open DOIOpen Access