@article{10.11648/j.ajeit.20261002.11,
  author = {Adesegun Nurudeen Osijirin and Khama Valentine Arinze and Umakalu Chioma Precious and Stella Ogechukwu Okpe and Nsangaette Asuquo Udo and Irene Chinyere Ezugwu and George Joseph Etim and Oka Obasi},
  title = {From Awareness to Academic Use: Generative Artificial Intelligence Awareness as a Predictor of Utilisation for Learning Among Allied Health Undergraduates},
  journal = {American Journal of Education and Information Technology},
  volume = {10},
  number = {2},
  pages = {48-59},
  doi = {10.11648/j.ajeit.20261002.11},
  url = {https://doi.org/10.11648/j.ajeit.20261002.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajeit.20261002.11},
  abstract = {Background: Generative artificial intelligence (GenAI) has moved quickly from novelty to an everyday learning resource in higher education. Yet frequent exposure does not necessarily mean that students understand how to use these systems critically, safely, and academically. This distinction is especially consequential in health-related education, where inaccurate outputs, privacy breaches, and uncritical reliance can shape learning habits with implications beyond the classroom. Purpose: This study examined GenAI awareness and learning-oriented utilisation among undergraduates in a specialised allied health sciences university in Nigeria and tested whether awareness statistically predicts academic use. Sample: The sample comprised 220 consenting first-year undergraduates drawn from 14 academic programmes. Design and method: An analytical cross-sectional survey was conducted from 6 to 10 September 2026. A study-specific questionnaire measured GenAI awareness with 10 items and utilisation for learning with 12 items, both on four-point scales. Internal consistency was high for awareness (Cronbach’s α = .86) and utilisation (α = .95). Descriptive statistics, Pearson correlation, and simple linear regression were used, with HC3 robust standard errors and Spearman correlation as robustness checks. Results: GenAI exposure was widespread: 96.8% had heard of GenAI and 94.5% reported prior use. ChatGPT was the most frequently used tool (60.0%). Mean awareness was 3.48 (SD = .45), while mean utilisation was 3.44 (SD = .52). Awareness was moderately associated with utilisation (r = .427, 95% CI [.313, .530], p Conclusions: Awareness matters for academic GenAI use, but it is not sufficient. Students were more aware of GenAI capabilities than of privacy, bias, and academic-integrity risks, revealing a descriptive capability-criticality gap. Allied health institutions should therefore move beyond tool exposure towards structured AI literacy that combines practical use with verification, ethical judgement, confidentiality, and discipline-specific reasoning.},
 year = {2026}
}

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TY  - JOUR
T1  - From Awareness to Academic Use: Generative Artificial Intelligence Awareness as a Predictor of Utilisation for Learning Among Allied Health Undergraduates
AU  - Adesegun Nurudeen Osijirin
AU  - Khama Valentine Arinze
AU  - Umakalu Chioma Precious
AU  - Stella Ogechukwu Okpe
AU  - Nsangaette Asuquo Udo
AU  - Irene Chinyere Ezugwu
AU  - George Joseph Etim
AU  - Oka Obasi
Y1  - 2026/10/23
PY  - 2026
N1  - https://doi.org/10.11648/j.ajeit.20261002.11
DO  - 10.11648/j.ajeit.20261002.11
T2  - American Journal of Education and Information Technology
JF  - American Journal of Education and Information Technology
JO  - American Journal of Education and Information Technology
SP  - 48
EP  - 59
PB  - Science Publishing Group
SN  - 2994-712X
UR  - https://doi.org/10.11648/j.ajeit.20261002.11
AB  - Background: Generative artificial intelligence (GenAI) has moved quickly from novelty to an everyday learning resource in higher education. Yet frequent exposure does not necessarily mean that students understand how to use these systems critically, safely, and academically. This distinction is especially consequential in health-related education, where inaccurate outputs, privacy breaches, and uncritical reliance can shape learning habits with implications beyond the classroom. Purpose: This study examined GenAI awareness and learning-oriented utilisation among undergraduates in a specialised allied health sciences university in Nigeria and tested whether awareness statistically predicts academic use. Sample: The sample comprised 220 consenting first-year undergraduates drawn from 14 academic programmes. Design and method: An analytical cross-sectional survey was conducted from 6 to 10 September 2026. A study-specific questionnaire measured GenAI awareness with 10 items and utilisation for learning with 12 items, both on four-point scales. Internal consistency was high for awareness (Cronbach’s α = .86) and utilisation (α = .95). Descriptive statistics, Pearson correlation, and simple linear regression were used, with HC3 robust standard errors and Spearman correlation as robustness checks. Results: GenAI exposure was widespread: 96.8% had heard of GenAI and 94.5% reported prior use. ChatGPT was the most frequently used tool (60.0%). Mean awareness was 3.48 (SD = .45), while mean utilisation was 3.44 (SD = .52). Awareness was moderately associated with utilisation (r = .427, 95% CI [.313, .530], p Conclusions: Awareness matters for academic GenAI use, but it is not sufficient. Students were more aware of GenAI capabilities than of privacy, bias, and academic-integrity risks, revealing a descriptive capability-criticality gap. Allied health institutions should therefore move beyond tool exposure towards structured AI literacy that combines practical use with verification, ethical judgement, confidentiality, and discipline-specific reasoning.
VL  - 10
IS  - 2
ER  - 

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