Irvin Mabokgole
Papers
1
Total Citations
2
H-Index
1
About
Irvin Mabokgole is an emerging scholar in the fields of educational robotics and human-robot interaction, with a particular focus on the sociotechnical barriers that shape learning and career development. His most-cited work, "Bayesian factorial regression of perceived barriers in robotics education: heterogeneous associations by career stage, gender, and training" (2025), employs advanced Bayesian statistical methods to uncover how perceptions of obstacles in robotics education differ significantly across career stages, gender, and training backgrounds. This research provides a nuanced, data-driven framework for understanding why certain groups—such as early-career researchers or women—face distinct challenges in robotics fields, offering actionable insights for educators and policymakers. Though early in his career, Mabokgole’s work has already garnered attention for its methodological rigor and its potential to inform more inclusive robotics curricula. By bridging quantitative modeling with educational equity, he contributes to a growing body of literature that seeks to democratize access to robotics and AI training. His findings are particularly relevant for designing targeted interventions that reduce attrition and support diverse talent in STEM.
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Top Papers
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