STEM for All (2017-2018)


Female and minority students continue be under-represented in science, technology, engineering and math (STEM) majors. Even among those who enter college intending to major in STEM, there is a relatively high attrition rate after taking introductory STEM courses.

The way in which introductory STEM courses are taught has been identified as one contributing factor to the low retention rates of female and minority students. In particular, many students view these courses as being alienating, competitive, weed-out classes with no personal connections. Despite this finding, introductory STEM courses continue to be taught mainly through lectures, which tend to prevent personal connections in the classroom.

At the same time, a student’s self-efficacy, or the feeling that one can succeed in a task or major, is found to play an important role in the retention of under-represented groups. Preliminary findings suggest that the use of active-learning techniques in the classroom can foster students’ self-efficacy.

Project Description

This Bass Connections project examines the role of active learning in improving retention rates of women and minorities in STEM majors. Building on research by previous versions of this team, the 2017-2018 team will focus on active-learning techniques that are centered around the individual student, as opposed to group/peer methods, and will consider more fully the roles of race and ethnicity in the retention rates of undergraduate STEM majors.

This work will involve summarizing the relevant literature and peer-teaching one another in a specific topic, and further developing a theory regarding how active learning impacts self-efficacy. Current theories do not provide an adequate gender-based or race/ethnicity-based theory of how teaching styles affect self-efficacy. Experiments will focus on one active-learning method, the use of clickers (classroom response systems). These experiments will simulate classroom situations, having brief STEM topics taught in lecture form for control groups and then taught using clickers for the treatment groups. Groups will also be stratified by gender. If the participant pool is large enough, the team will also stratify by race/ethnicity.

Clicker usage is associated with peer/group experiences, as the entire class sees the anonymous answers of the group at large. Other active-learning methods that are not group-based may affect students’ self-efficacy. These methods could include diary and journal writing (not to be read by classmates) or individually constructed projects that will not be viewed by classmates.

The 2017-2018 project team will expand on the previous research by considering individual-centered active-learning methods to determine if there are different effects relative to group-based methods, and by further developing theories regarding how race and ethnicity relate to active learning and self-efficacy. Overall, the continued goals of the project are to determine best practices for introductory STEM courses to increase retention of women and minorities through increasing the self-efficacy of these historically marginalized groups in STEM.

Anticipated Outcomes

Article to submit to a peer-reviewed journal


Summer 2017 – Summer 2018

Team meetings in Fall 2017 will take place on Thursday afternoons.

  • Summer 2017: New students familiarize themselves with the background on the topic and write summaries; returning students review materials and present an overview to new students
  • Fall 2017: Students participate in workshops to learn about additional active-learning techniques and write summaries of each technique, along with their ideas on how each technique may affect self-efficacy; analyze any remaining data from 2016-2017 project, focusing on the effects of clicker usage on self-efficacy by gender; determine which technique(s) to experiment with during the next phase; submit IRB protocol; plan and prepare all materials for experiments; start recruiting participants; participate in workshops to learn more about critical race theory; develop theories in more detail regarding impacts of race and ethnicity in relation to active learning and self-efficacy
  • Spring 2018: Incorporate analysis of race and ethnicity into materials to be used for experiments; conduct experiments; code, enter, clean up all data; analyze current data; compare current experiments with ones from 2016-2017; write draft of research paper to submit to peer-reviewed journal; finalize paper and submit to journal

See earlier related team, STEM for All (2016-2017).

Faculty/Staff Team Members

Mine Cetinkaya-Rundel, Trinity - Statistical Science*
Genna Miller, Trinity - Economics*

Graduate Team Members

Aarthi Sridhar, Pratt - Civil and Environmental Engineering

Undergraduate Team Members

Brigid Burroughs, Psychology (AB)
Young Hoo (Andy) Cho, Statistical Science (BS)
Jesse Ling, Computer Science (AB)

* denotes team leader