2026 ASEE Annual Conference & Exposition

Sustaining effective mentoring and knowledge transfer in computer science research labs is challenging when students cycle through every three to six semesters, creating recurring gaps in expertise and project continuity. This paper presents the Bee Learning Mentoring Model, a framework for structured mentoring in CS research labs inspired by the social learning mechanisms of honeybees (Apis mellifera). The model was developed and refined over eight years within the Beemon project at Appalachian State University (App State), where undergraduate and graduate students collaboratively design, build, and maintain a remote beehive monitoring system encompassing hardware assembly, software development, networking, and data analysis. Drawing on parallels between honeybee colony organization and educational mentoring theory, the model is organized around four principles: (1) Guided Participation, (2) Peer Learning through Demonstration, (3) Adaptive Role Transitions, and (4) Distributed Knowledge Networks. We derived these principles through longitudinal reflective practice, informed by both honeybee behavioral research and socio-cultural learning theory. Over the eight-year span of the project, 44 students (68% undergraduate, 32% graduate) have participated, with 100% degree completion. Students co-authored 18 peer-reviewed papers and delivered 29 conference presentations with their mentors. Approximately 57% entered the workforce and 43% pursued or are pursuing graduate studies. Unlike conventional mentoring frameworks, this model explicitly addresses knowledge continuity across student generations by embedding adaptive role transitions and distributed knowledge networks as structural features. The paper contributes a biologically grounded, empirically refined mentoring framework with implications for CS education, interdisciplinary research teams, and labs facing similar challenges of student turnover.