Mentors as Female Role Models in STEM Disciplines and Their Benefits

Sulema Torres-Ramos, Nicte Selene Fajardo-Robledo, Lourdes Adriana Pérez-Carrillo, Claudia Castillo-Cruz, Patricia del R. Retamoza-Vega, Verónica M. Rodríguez-Betancourtt and Cristina Neri-Cortés
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Sulema Torres-Ramos: University Center of Exact Sciences and Engineering (CUCEI), University of Guadalajara (UdG), Guadalajara 44100, Jalisco, Mexico
Nicte Selene Fajardo-Robledo: University Center of Exact Sciences and Engineering (CUCEI), University of Guadalajara (UdG), Guadalajara 44100, Jalisco, Mexico
Lourdes Adriana Pérez-Carrillo: University Center of Exact Sciences and Engineering (CUCEI), University of Guadalajara (UdG), Guadalajara 44100, Jalisco, Mexico
Claudia Castillo-Cruz: University Center of Exact Sciences and Engineering (CUCEI), University of Guadalajara (UdG), Guadalajara 44100, Jalisco, Mexico
Patricia del R. Retamoza-Vega: University Center of Exact Sciences and Engineering (CUCEI), University of Guadalajara (UdG), Guadalajara 44100, Jalisco, Mexico
Verónica M. Rodríguez-Betancourtt: University Center of Exact Sciences and Engineering (CUCEI), University of Guadalajara (UdG), Guadalajara 44100, Jalisco, Mexico
Cristina Neri-Cortés: University Center of Exact Sciences and Engineering (CUCEI), University of Guadalajara (UdG), Guadalajara 44100, Jalisco, Mexico

Sustainability, 2021, vol. 13, issue 23, 1-19

Abstract: Several studies have addressed the benefits of mentoring from the mentor’s perspective, especially those related to soft skills. However, to the best of our knowledge, there are no studies that either relate the mentoring in STEM areas with female role models or that analyze them from a data-mining perspective. In this work, a questionnaire was elaborated to address the mentor’s benefits related to soft skills and technical knowledge; afterward, a data-mining methodology was used to analyze the mentor’s perceptions related to female role models and STEM reinforcement. In addition, sentiment analysis was performed in order to determine the emotional polarity in the text used by the mentors to describe their mentoring experience. The results show that soft and technical skills are acquired by the mentors, and participating in mentoring programs allows them to perceive themselves as female role models. Additionally, by using decision trees, it was possible to determine the mentors’ characteristics that perceive a STEM reinforcement or that produce attraction. In addition, the results show that the general perception of the mentors’ experience was positive. Finally, the use of machine learning techniques, specifically data mining and sentiment analysis, allowed us to both confirm the results obtained in a qualitative way and to obtain new interesting results.

Keywords: mentoring; STEM; higher education; female role model; gender gap; equity; data mining (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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