Influence of AI-based Chatbots on University Students' Post-class Review, Learning Attitudes and Motivation in Nigeria

The rapid integration of artificial intelligence (AI) technologies into educational environments has significantly transformed students’ learning experiences, particularly in higher education. Among these innovations, AI-based chatbots have emerged as accessible and interactive tools that support academic engagement beyond the classroom. In the Nigerian context, where digital learning adoption is steadily increasing, university students are increasingly utilizing AI chatbots for post-class review, clarification of concepts, and self -directed learning. This study examined the influence of AI -based chatbots on university students’ post -class review practices, learning attitudes, and motivation in North Central Nigeria. A descriptive research design of the surv ey type was adopted for the study. The target population comprised undergraduate students from selected universities within the region. A structured questionnaire was used as the primary instrument for data collection. The data collected were analyzed using descriptive statistics, including mean scores, standard deviation, and frequency distributions. The findings of the study revealed that AI -based chatbots significantly support students’ post-class review by providing immediate feedback, simplifying complex concepts, and enhancing independent learning. The results further indicated a positive relationship between chatbot usage and students’ learning attitudes, as students demonstrated increased interest, engagement, and willingness to explore academic content beyond formal lectures. Additionally, the study found that the use of AI chatbots contributes to improved academic motivation, as students reported greater confidence in their understanding of course materials and a heightened sense of academic autonomy. Based on these findings, the study concludes that AI -based chatbots play a crucial role in enhancing post -class learning experiences, fostering positive learning attitudes, and improving motivation among university students in North Central Nigeria. It is therefore recommended that universities integrate AI -driven learning tools into their instructional support systems, provide digital literacy training for students, and establish guidelines for the effective and ethical use of AI technologies in academic settings. Further research is also suggested to explore long-term impacts and potential challenges associated with AI-assisted learning in Nigerian higher education.

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Publication Details

Journal
Gamification Fatigue and Continuance Intention in Technology‑Enhanced Learning Platforms A Post‑Adoption Extension of TAM
Published
2026-08-24
DOI
https://doi.org/10.66397/260426.20260824
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00
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article

Influence of AI-based Chatbots on University Students' Post-class Review, Learning Attitudes and Motivation in Nigeria

E. O. Tinuoye, K.M. NUHU, C.O. Olumorin, M. A. Abubakar et al.
Gamification Fatigue and Continuance Intention in Technology‑Enhanced Learning Platforms A Post‑Adoption Extension of TAM
AI in Service Interactions
article

Influence of AI-based Chatbots on University Students' Post-class Review, Learning Attitudes and Motivation in Nigeria

E. O. Tinuoye, K.M. NUHU, C.O. Olumorin, M. A. Abubakar, O. Samuel, S. A. Hassan
article en

Abstract

The rapid integration of artificial intelligence (AI) technologies into educational environments has significantly transformed students’ learning experiences, particularly in higher education. Among these innovations, AI-based chatbots have emerged as accessible and interactive tools that support academic engagement beyond the classroom. In the Nigerian context, where digital learning adoption is steadily increasing, university students are increasingly utilizing AI chatbots for post-class review, clarification of concepts, and self -directed learning. This study examined the influence of AI -based chatbots on university students’ post -class review practices, learning attitudes, and motivation in North Central Nigeria. A descriptive research design of the surv ey type was adopted for the study. The target population comprised undergraduate students from selected universities within the region. A structured questionnaire was used as the primary instrument for data collection. The data collected were analyzed using descriptive statistics, including mean scores, standard deviation, and frequency distributions. The findings of the study revealed that AI -based chatbots significantly support students’ post-class review by providing immediate feedback, simplifying complex concepts, and enhancing independent learning. The results further indicated a positive relationship between chatbot usage and students’ learning attitudes, as students demonstrated increased interest, engagement, and willingness to explore academic content beyond formal lectures. Additionally, the study found that the use of AI chatbots contributes to improved academic motivation, as students reported greater confidence in their understanding of course materials and a heightened sense of academic autonomy. Based on these findings, the study concludes that AI -based chatbots play a crucial role in enhancing post -class learning experiences, fostering positive learning attitudes, and improving motivation among university students in North Central Nigeria. It is therefore recommended that universities integrate AI -driven learning tools into their instructional support systems, provide digital literacy training for students, and establish guidelines for the effective and ethical use of AI technologies in academic settings. Further research is also suggested to explore long-term impacts and potential challenges associated with AI-assisted learning in Nigerian higher education.

Gamification Fatigue and Continuance Intention in Technology‑Enhanced Learning Platforms A Post‑Adoption Extension of TAMVol. 1(4)
Quality Education
Openalex Percentile: Top 8%
AI in Service Interactions
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