Feasibility and usability of MentorPal, a framework for rapid development of virtual mentors (bibtex)
by Nye, Benjamin D., Davis, Dan M., Rizvi, Sanad Z., Carr, Kayla, Swartout, William, Thacker, Raj and Shaw, Kenneth
Abstract:
One-on-one mentoring is an effective method to help 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 attempt to provide the best answers. MentorPal has developed strategies for the rapid development of new virtual mentors, where training data will be sparse. In a usability study, 31 high school students self-reported a) increased career knowledge and confidence, b) positive ease-of-use, and that c) mentors were helpful (87%) but often did not cover their preferred career (29%). Results demonstrate the feasibility of scalable virtual mentoring, but efficacy studies are needed to evaluate the impact of virtual mentors, particularly for groups with limited STEM opportunities.
Reference:
Feasibility and usability of MentorPal, a framework for rapid development of virtual mentors (Nye, Benjamin D., Davis, Dan M., Rizvi, Sanad Z., Carr, Kayla, Swartout, William, Thacker, Raj and Shaw, Kenneth), In Journal of Research on Technology in Education, 2020.
Bibtex Entry:
@article{nye_feasibility_2020,
	title = {Feasibility and usability of {MentorPal}, a framework for rapid development of virtual mentors},
	issn = {1539-1523, 1945-0818},
	url = {https://www.tandfonline.com/doi/full/10.1080/15391523.2020.1771640},
	doi = {10.1080/15391523.2020.1771640},
	abstract = {One-on-one mentoring is an effective method to help 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 attempt to provide the best answers. MentorPal has developed strategies for the rapid development of new virtual mentors, where training data will be sparse. In a usability study, 31 high school students self-reported a) increased career knowledge and confidence, b) positive ease-of-use, and that c) mentors were helpful (87\%) but often did not cover their preferred career (29\%). Results demonstrate the feasibility of scalable virtual mentoring, but efficacy studies are needed to evaluate the impact of virtual mentors, particularly for groups with limited STEM opportunities.},
	journal = {Journal of Research on Technology in Education},
	author = {Nye, Benjamin D. and Davis, Dan M. and Rizvi, Sanad Z. and Carr, Kayla and Swartout, William and Thacker, Raj and Shaw, Kenneth},
	month = jul,
	year = {2020},
	keywords = {Learning Sciences, Virtual Humans},
	pages = {1--23}
}
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