Farzana Rahman
Electrical engineering and computer science (EECS) Professor Farzana Rahman received a 2020 Google exploreCSR award to fund the development of an undergraduate student engagement workshop program, Research Exposure in Socially Relevant Computing (RESORC).
The RESORC program will provide research opportunities to undergraduate students from ϲ and nearby institutions targeting populations underrepresented in computing, including Latinx, African American, American Indian or Indigenous and LGBTQIA+ students.
According Rahman, the population of students pursuing computer science and computing degrees is not representative of the diversity of people in the U.S., with women and other groups persistently underrepresented.
Additionally, research has shown that computing research pipeline is not diverse since women and underrepresented students face many barriers like lack of self-confidence, stereotype threat, and lack of women role models. There is also lack of knowledge regarding research opportunities and the potential benefit of research careers.
Many unrepresented students are never exposed to research due to coming from institutions with limited research capabilities. The intersectionality of these students also places more structural barriers for them to explore anything other than a regular degree. RESORC aims to diversify the Ph.D. pipeline through peer-assisted, team-based research exposure that places special emphasis on mentoring women.
The primary objectives of this workshop are to:
The RESORC experience will expose participants to research in socially relevant computing though close mentoring provided by the graduate students of the SU EECS department. These graduate mentors will attend a training session informed by best practices for mentoring underrepresented students by NCWIT.
The workshop will use Social Cognitive Career Theory that will help to influence the career ambitions and choices of participants in computing through guided research exploration. It will also use a Peer-Assisted Team Research (PATR) model that will involve participants in research experiences within teams with a dedicated graduate mentor’s supervision. PATR will improve student’s scientific reasoning abilities, research self-efficacy, and sense of belonging in computing.
“I expect that this experience will enable our Ph.D. student volunteers to be better, more inclusive mentors as they pursue their own careers,” says Rahman.
After an initial proof-of-concept year, Rahman hopes to sustain and expand RESORC to reach more students at ϲ and nearby other institutions in the area.
