Designing an AI mentor for early career researchers

This study describes the design and evaluation of a Generative AI career mentor tailored for Early Career Researchers (ECRs). Despite the proven benefits of mentorships, ECR’s access to mentors remains limited due to time and skill constraints faced by experienced researchers. Drawing on Career Construction Theory and research career mentorship, this research uses Design Science methodology to create and evaluate Generative AI mentor chatbot. To evaluate the design, the AI mentor’s assessment and guidance (i.e. the AI outputs) are compared and critiqued against the researcher’s self assessment, a colleague’s assessment, and a supervisor’s assessment. This study contributes to the career construction literature by exploring how GenAI can adapt career guidance to individual circumstances, thus enhancing the applicability of Career Construction Theory in a digital age. Additionally it advances the ECR mentorship literature by introducing accessible mentoring solution that addresses the limitations of traditional mentorship models.

keywords: generative ai; research mentor; career development; early career researchers

• year: July 2024 – ongoing