Presentations: Session G

With the support of an NSF-IUSE award, we designed the year-long faculty development Deep Teaching Residency (DTR) in order to substantially change faculty mindsets and inclusive pedagogy practices. 'Deep Teaching' (Dewsbury, 2019) is an inclusive pedagogical philosophy that seeks to better understand and apply the social context of the education process. This involves faculty engagement in a constant, critical evaluation of how instructor self-awareness, students' personal histories, and broad social structures impact the development of an equitable pedagogy. This project has the potential for large-scale transformation of the ways that faculty view and approach their students and their instructional roles in creating inclusive classrooms.

The Deep Teaching Residency (DTR) engages participants in a 4-day face-to-face summer residency program sandwiched between preparatory readings and reflections (Pre-Work) and a sustained virtual community during the subsequent fall and spring semesters. The immersive summer program includes interactive workshops, beginning with an exploration of self and student in the context of social structures and inequities, and then building pedagogical approaches and networking practices from that foundation. Substantial time is dedicated for participants to develop an individual plan to transform an aspect of their teaching or departmental practices at their home institutions during the subsequent academic year. Feedback from the first two cohorts show that DTR provided a safe and respectful space for participants to engage with topics of anti-racism, identity, and bias and to self-reflect about how to modify their own practices to create more equitable course structures and build supportive relationships with students. Feedback also emphasized the value of having sustained time to think and plan, and to do so through discussions and with the support of a community of colleagues. Formal program evaluation and data analysis are underway and will inform next steps for the DTR program.

The Inclusive and Equitable Teaching (IE-Teaching) Assessment is an initiative designed to promote more inclusive and equitable teaching practices by using data to motivate, inform, and tailor change efforts to the departmental contexts in which they will be implemented (Reinholz & Apkarian, 2018; Ngai et al. 2020). Staff in the Teaching + Learning Lab (TLL) at MIT partnered with three academic departments across disciplines to pilot test the IE-Teaching Assessment, which involved collecting multiple types of data (including surveys administered to students and instructors, qualitative analyses of course syllabi, and a review of departmental policies and practices) and using these data to guide collaborative discussions about teaching practices within the department. Each data source was designed to capture indicators of inclusive and equitable teaching, guided by the equity-focused teaching principles advanced by the University of Michigan Center for Research on Teaching & Learning (2021). After analyzing the data at the department level, we shared the findings with faculty, instructional staff, and other stakeholders to motivate and inform instructors' re-examination of their teaching practices and the departmental structures that influence teaching within the department. The data collection and sharing processes inform our understanding of the structures and cultures within the department that act as supports and barriers to change, while identifying the various levels of adoption of inclusive and equitable teaching among instructors, consistent with the CACAO model of change (Dormant, 2011; Earl et al., 2020). In this presentation, we will highlight (1) how and why we focused on working with academic departments, rather than individual instructors, to promote inclusive teaching; (2) how different sources of data, from multiple stakeholder perspectives, provided nuanced information to guide change efforts; and (3) how we are leveraging these data to support departmental stakeholders in developing their own plans and resources for promoting inclusive and equitable teaching.

We present on progress made in developing a student evaluation of teaching (SET) inventory that reduces implicit bias, is instructor-actionable, and is reliable across student evaluators. Our approach has focused on elevating faculty doing the "invisible work" disproportionately done by minorities and/or women that evidence demonstrates is required for underrepresented student success, but is rarely rewarded by traditional university structures. In particular, SETs focused on the affective-domain have been criticized for being race and gender biased and for failing to measure the underlying construct: teaching effectiveness. For example, although research-validated high-impact teaching practices (HIPs) are more likely to be used in courses with minority and/or women instructors in a variety of fields, this population often scores lower on SETs, which are frequently used in personnel decisions. To construct an SET, we started with the Faculty Inventory of Methods and Practices Associated with Competent Teaching (F-IMPACT), which is a validated instructor self-report of research-based HIPs usage. Language was modified to turn the F-IMPACT into a student observation protocol, where over the course of 15 prompts students identify HIPs used in the course. In contrast to affective-domain SETs, this approach was designed to minimize subjective judgements. Either a student did or did not observe a specific practice. Initial face validity of the SET has been established via student focus groups and clarity surveys (N = 22), and reliability and congruent validity studies are reported from a single institution pilot (N = 512). We also discuss the validity of the underlying F-IMPACT instrument, SET pilot efforts currently underway at several institutions, and efforts made to include faculty concerns and perception of barriers.