EXPLORING HOW RELATIONAL MOTIVATIONS OF EXTENSION EDUCATORS INFLUENCE MENTORING RELATIONSHIPS: A CASE STUDY OF BIU LOCAL GOVERNMENT AREA, BORNO STATE
This study investigates how relational motivations such as empathy, mutual respect, and personal fulfilment affect mentoring relationships among Extension educators. Rooted in Relational Mentoring Theory, the research aims to understand the interpersonal dynamics that drive mentoring within Extension systems in Biu Local Government Area (LGA), Borno State, a rural and agriculturally active region of Nigeria. The objectives of the study are to identify the key relational motivations that influence Extension educators’ participation in mentoring; to explore how these motivations affect the quality and dynamics of mentoring relationships; to assess the influence of relationally motivated mentoring on mentee development and professional outcomes; and to examine how demographic, institutional, or experiential factors shape mentoring behaviour. Using a qualitative phenomenological design, the study captures the lived experiences and internal values of educators who have participated in mentoring over the past three years. Purposive sampling will be employed to recruit a diverse group of 10 to 15 Extension educators, selected based on gender, years of service, and organizational affiliation. Data collection will involve semi-structured interviews, guided by questions focused on relational values, mentoring experiences, and perceived outcomes. All interviews will be audio-recorded, transcribed verbatim, and thematically analyzed using SSPS software, following Braun and Clarke’s six-phase framework. The study is expected to provide in-depth insights into the human and relational factors that shape mentoring practices in Extension services. Findings will inform the development of more effective, relationally driven mentoring strategies that promote capacity building, organizational learning, and professional development within rural Extension systems.
Institutions
- New York State Education Department (US)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-10-16
- DOI
- https://doi.org/10.5281/zenodo.17426303
- Primary Topic
- Computability, Logic, AI Algorithms
- Type
- article
- Field-Weighted Citation Impact
- 0.00