Students’ Behavioral Intention towards Adoption of Peer Recommender Systems in Tanzania

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Henrick Mwasita
Joel Mtebe
Mercy Mbise

Abstract

This work investigates factors influencing students’ behavioral intention to use peer recommender systems for collaborative learning in Tanzanian secondary schools. Peer-assisted learning (PAL) is a longstanding educational approach, and recommender systems (RS) offer a technological means to enhance PAL by matching students with suitable peers beyond their immediate classrooms. However, the successful adoption of such systems depends on user acceptance, especially in developing contexts where technological and cultural factors play a significant role. Drawing upon the Unified Theory of Acceptance and Use of Technology (UTAUT), we developed a research model with four core determinants: Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions. These factors were hypothesized to predict students’ intention to adopt a peer recommender system. A survey of 1,029 secondary students from 8 schools in Tanzania was conducted. Results indicate that all four factors significantly affect behavioral intention. Performance expectancy, social influence, and facilitating conditions showed positive effects, while effort expectancy demonstrated a significant negative effect. The UTAUT model explained approximately 74% of the variance in students’ behavioral intention, demonstrating its strong explanatory power in this context. Key recommendations include investing in necessary ICT infrastructure, ensuring the system is easy to use, leveraging social support from teachers and peers, and clearly communicating learning benefits to students. With the proper supportive conditions and user-centric design, peer recommender systems can be a viable tool to foster online peer learning among secondary school students in Tanzania.

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How to Cite
Mwasita, H., Mtebe, J., & Mbise, M. (2025). Students’ Behavioral Intention towards Adoption of Peer Recommender Systems in Tanzania. Journal of ICT Systems, 3(2), 24–43. https://doi.org/10.56279/jicts.v3i2.264
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