Designing an AI Career Mentor for Early Career Researchers
DOI:
https://doi.org/10.23726/cij.2024.1576Keywords:
Generative artificial intelligence, Career Development, Early career researcher, MentorshipAbstract
This study describes the design and evaluation of a Generative Artificial Intelligence (GenAI) digital mentor tailored for Early Career Researchers (ECRs). Despite the proven benefits of mentorships for ECRs, access to effective mentorship remains limited due to constraints on experienced researchers’ time and their varying mentorship skills. Drawing on Career Construction Theory, research career mentorship, and Design Science methodology, this article documents the creation of a digital mentor and evaluates its assessment accuracy and guidance specificity in responding to career-related queries. The findings indicate that the digital mentor was fast, provided actionable career progression mentoring comments, and made explicit references to the mentee’s experience, skills, and university’s strategy. However, its skills assessment had weak similarity when compared to the mentee’s self-assessment, a peer assessment, and a research leader’s assessment of the mentee’s skills. Nonetheless, ECRs can consider using a digital mentor to obtain fast contextualised comments on developing their career within their university.
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