Feasibility and usability of MentorPal, a framework for rapid development of virtual mentors. Issue 1 (2nd January 2021)

• Record Type: Journal Article
• Authors: Nye, Benjamin D.; Davis, Dan M.; Rizvi, Sanad Z.; Carr, Kayla; Swartout, William; Thacker, Raj; Shaw, Kenneth
• Is Part Of: Journal of research on technology in education. Volume 53:Issue 1(2021)
• Page Start: 21
• Page End: 43
• Publication Date: 2021-01-02
• Subjects: Virtual agents -- mentoring -- natural language processing -- artificial intelligence -- STEM outreach; Computer-assisted instruction -- Periodicals; Educational technology -- Periodicals; Internet in education -- Periodicals; Distance education -- Periodicals; 371.3305
• DOI: 10.1080/15391523.2020.1771640
• Languages: English
• ISSNs: 1539-1523

Abstract

Abstract: One-on-one mentoring is effective for helping novices with career development. However, traditional mentoring scales poorly. To address this problem, MentorPal emulates conversations with a panel of virtual mentors based on recordings of real STEM professionals. Students freely ask questions as they might in a career fair, while machine learning algorithms respond with best-match answers. MentorPal is researching rapid development of new virtual mentors, where training data will be sparse. In a usability study, 31 high school students reported (a) increased career knowledge and confidence, (b) positive ease-of-use, and that (c) mentors were helpful (87%) but seldom covered their preferred career (29%). These results demonstrate feasibility for virtual mentoring, but efficacy studies are needed to evaluate its impact, particularly for groups with limited STEM opportunities.