Effect of Artificial Intelligence-Supported Problem-Based Learning on Employability Skills and Academic Achievement of Vocational Agricultural Education Students in Nigerian Universities

The integration of artificial intelligence into higher education has created opportunities for innovative instructional approaches that may enhance students' employability skills and academic achievement. This study investigated Artificial Intelligence-Supported Problem-Based Learning (AI-PBL) in relation to the self-reported employability skills and percentage academic achievement of Vocational Agricultural Education students in selected Nigerian universities. A quasi-experimental pretest-posttest nonequivalent control group design was adopted. The study involved 138 students drawn from two federal universities in South East Nigeria using multistage sampling procedures. The experimental group was taught using AI-PBL for six weeks with the support of ChatGPT, Microsoft Copilot, and other approved artificial intelligence resources, while the control group received instruction using the conventional lecture method. Data were collected using the Employability Skills Assessment Scale (ESAS) and the Agricultural Education Achievement Test (AEAT). Raw scores obtained from the AEAT were converted to percentage scores before analysis. The instruments were validated by experts, while reliability coefficients of 0.89 and 0.86 were obtained for the ESAS and AEAT, respectively. The mean and standard deviation were used to answer the research questions, whereas Analysis of Covariance was employed to test the hypotheses at the 0.05 level of significance after confirming that the assumptions underlying ANCOVA were satisfied. The findings revealed that students exposed to AI-PBL obtained significantly higher self-reported employability skills and percentage academic achievement than those taught using the conventional lecture method (p < .001), with large effect sizes observed for both outcomes. No statistically significant gender differences were found among students within the AI-PBL group. The findings suggest that AI-PBL is associated with higher workplace-related competencies and academic learning outcomes among Vocational Agricultural Education students under the conditions of the present study. The study recommends the integration of AI-PBL into university curricula alongside institutional support for the ethical and responsible use of artificial intelligence in teaching and learning.

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Publication Details

Journal
Educational Point
Published
2026-11-05
DOI
https://doi.org/10.71176/edup/19767
Primary Topic
Problem and Project Based Learning
Type
article
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0.00
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article

Effect of Artificial Intelligence-Supported Problem-Based Learning on Employability Skills and Academic Achievement of Vocational Agricultural Education Students in Nigerian Universities

Nwali Evaristus Ogochukwu, Oluchi Kizito Okafor, Chiamaka C. Ojiako, Toochukwu Collins Nwakile
Educational Point
Problem and Project Based Learning
article

Effect of Artificial Intelligence-Supported Problem-Based Learning on Employability Skills and Academic Achievement of Vocational Agricultural Education Students in Nigerian Universities

Nwali Evaristus Ogochukwu, Oluchi Kizito Okafor, Chiamaka C. Ojiako, Toochukwu Collins Nwakile
article en

Abstract

The integration of artificial intelligence into higher education has created opportunities for innovative instructional approaches that may enhance students' employability skills and academic achievement. This study investigated Artificial Intelligence-Supported Problem-Based Learning (AI-PBL) in relation to the self-reported employability skills and percentage academic achievement of Vocational Agricultural Education students in selected Nigerian universities. A quasi-experimental pretest-posttest nonequivalent control group design was adopted. The study involved 138 students drawn from two federal universities in South East Nigeria using multistage sampling procedures. The experimental group was taught using AI-PBL for six weeks with the support of ChatGPT, Microsoft Copilot, and other approved artificial intelligence resources, while the control group received instruction using the conventional lecture method. Data were collected using the Employability Skills Assessment Scale (ESAS) and the Agricultural Education Achievement Test (AEAT). Raw scores obtained from the AEAT were converted to percentage scores before analysis. The instruments were validated by experts, while reliability coefficients of 0.89 and 0.86 were obtained for the ESAS and AEAT, respectively. The mean and standard deviation were used to answer the research questions, whereas Analysis of Covariance was employed to test the hypotheses at the 0.05 level of significance after confirming that the assumptions underlying ANCOVA were satisfied. The findings revealed that students exposed to AI-PBL obtained significantly higher self-reported employability skills and percentage academic achievement than those taught using the conventional lecture method (p < .001), with large effect sizes observed for both outcomes. No statistically significant gender differences were found among students within the AI-PBL group. The findings suggest that AI-PBL is associated with higher workplace-related competencies and academic learning outcomes among Vocational Agricultural Education students under the conditions of the present study. The study recommends the integration of AI-PBL into university curricula alongside institutional support for the ethical and responsible use of artificial intelligence in teaching and learning.

Educational PointVol. 3(2)
University of Nigeria (NG)
Openalex Percentile: Top 9%
Problem and Project Based Learning
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