National and local initiatives focused on the transformation of STEM teaching in higher education have multiplied over the last decade. These initiatives often focus on measuring change in instructional practices, but it is difficult to monitor such change without a national picture of STEM educational practices, especially as characterized by common observational instruments. We characterized a snapshot of this landscape by conducting the first large scale observation-based study. We found that lecturing was prominent throughout the undergraduate STEM curriculum, even in classrooms with infrastructure designed to support active learning, indicating that further work is required to reform STEM education. Additionally, we established that STEM faculty’s instructional practices can vary substantially within a course, invalidating the commonly-used teaching evaluations based on a one-time observation.

Educational development traditionally has been a practice-based field. We propose that asa profession weadopt the methods of thescholarship of teaching and learning (SoTL), so often shared with our clients, in order to look through a scholarly lens at theoutcomes ofourownpractice. Using SoTL approaches in our work would deepen the research literature in ourfield and improve theeffectiveness ofdecisions we makeaboutwhere to spend limited time and resources. In this chapter, weexplore what it might mean for individual developers, andfor ourp~ofessiollal community, toapply SoTL methods toourpractice.. E ducational development (ED) is a profession dedicated to helping colleges and universities function effectively as teaching and learning communities. This field includes all the areas for which we often name it: faculty development; TA development; instructional, academic, and organizational 93

Decline in student motivation is a concern for STEM education, especially for underrepresented groups in the sciences. Using the Science Motivation Questionnaire II, 41 foundational STEM courses were surveyed at the beginning and end of each semester in an academic year at a small primarily undergraduate university. Significant pre-to post-semester declines were observed in each of five measured motivational factors (Intrinsic motivation, Career motivation, Self determination, Self-efficacy, and Grade motivation), with effect sizes ranging from 0.21 to 0.41. However, in the second semester pre-survey, four motivational factors rebounded, including three returning to initial levels, suggesting that the observed motivational decline is not long-lasting. Analysis suggests that declines are not related to survey fatigue or student demographics, but rather to grades and, in the case of one motivational factor, to academic field. These findings suggest that a refocus on grading practices across STEM fields may influence student motivation and persistence in STEM. ARTICLE HISTORY Literature reviewIn 2012, the U. S. President's Council of Advisors on Science and Technology set a goal of increasing the number of science, technology, engineering, and mathematics (STEM) bachelor's degrees by one million across a 10-year period (PCAST, 2012). The Council acknowledged that this goal is ambitious, but it could be met through a relatively modest improvement in the less than 40% persistence rate of students entering college as STEM majors. As STEM motivation is a critical contributor to student persistence (Simon, Aulls, Dedic, Hubbard, & Hall, 2015), a better understanding of student motivation broadly across STEM disciplines and how it changes in introductory courses, where attrition is high (Daempfle, 2003), is essential to improving the number of students graduating with STEM degrees.

Assessing the work of teaching and learning centers is crucial to maintain the support of our institutions; however, collecting and interpreting the right data can be a challenge. This chapter explores practical strategies for integrating assessment into daily work flow in order to generate information that accurately measures our impact, helps others understand and value our work, and enables us to improve what we do, without creating a major “add‐on” task. We discuss ways to measure, track, and report work, and share means to use data for both summative and formative purposes that we hope will make the work of faculty developers easier, better, and appreciated.

Educational development traditionally has been a practice-based field. We propose that asa profession weadopt the methods of thescholarship of teaching and learning (SoTL), so often shared with our clients, in order to look through a scholarly lens at theoutcomes ofourownpractice. Using SoTL approaches in our work would deepen the research literature in ourfield and improve theeffectiveness ofdecisions we makeaboutwhere to spend limited time and resources. In this chapter, weexplore what it might mean for individual developers, andfor ourp~ofessiollal community, toapply SoTL methods toourpractice.