Research Question

How well and for whom is active learning working in a revised General Chemistry I lecture?

Rationale

The use of evidence-based teaching pedagogies in STEM classrooms has become more popular at UMD and at many institutions of higher learning due to the conclusive evidence that active learning increases student performance. Increasingly, evidence also seems to suggest that some teaching pedagogies have differential effects on groups of students typically marginalized in STEM, including first-generation college students, women, students of color, and students of lower economic status. It is as yet unclear what factors influence these differential effects, and it is not well understood of these observations are generalizable across identities, STEM disciplines, or educational contexts.

Hypothesis

We hypothesize that active learning implementation will improve students' overall learning gains. Moreover, we presume that there may be differential learning gains for groups of different identities, particularly those underrepresented in STEM.

Approach

To test our hypothesis, we have gathered student performance data from a General Chemistry course before and after the implementation of active learning techniques. Student performance in these courses was measured using some combination of homework scores, attendance, group work, quizzes, mid-term exams, and standardized American Chemical Society (ACS) exams. By analyzing these performance data, we can determine if student performance (and therefore, student learning) was increased due to a more active course format. In addition, we can also identify factors that predict success in these course formats, such as whether or not participation in specific formative assessments like in-class group activities predicts overall success in the course. 

In addition, we can compare the student performance data used to test the first hypothesis to identifying demographic information kept at the Registrar’s Office, including self-identified race and sex, as well as incoming preparation (i.e. high school GPA and/or ACT scores). Indeed, we have already begun assembling these data for the selected General Chemistry courses. With demographic data in hand, we can identify whether or not a student’s identity is predictive of their performance in General Chemistry I and II, controlling for differences in preparation.