Search for: All records

Grade point average in “other” courses (GPAO) is an increasingly common measure used to control for prior academic performance and to predict future academic performance. In previous work, there are two distinct approaches to calculating GPAO, one based on only courses taken concurrently (term GPAO) and one based on all previous courses taken (cumulative GPAO). To our knowledge, no one has studied whether these methods for calculating the GPAO result in equivalent analyses and conclusions. As researchers often use one definition or the other without comment on why that choice was made, if the two calculations of GPAO are different, researchers might be inducing systematic error into their results and publishing potentially inaccurate conclusions. We looked at more than 3,700 courses at a public, research-intensive university over a decade and found limited evidence that the choice of GPAO calculation affects the conclusions. At most, one in seven courses could be affected. Further analysis suggests that there may be situations where one form of GPAO may be preferred over the other when it comes to examining inequity in courses or predicting student grades. However, we did not find sufficient evidence to universally recommend one form of GPAO over the other. 

It is difficult for instructors, and even students themselves, to become aware in real-time of inequitable behaviors occurring on student teams. Here, we explored a potential measure for inequitable teamwork drawing on data from a digital pedagogical tool designed to surface and disrupt such team behaviors. Students in a large, undergraduate business course completed seven surveys about team health (called team checks) at regular intervals throughout the term, providing information about team dynamics, contributions, and processes. The ways in which changes in students’ scores from team check to team check compared to the median changes for their team were used to identify the proportions of teams with outlier student scores. The results show that for every team size and team check item, the proportion of teams with outliers at the end of the term was smaller than at the beginning of the semester, indicating stabilization in how teammates evaluated their team experiences. In all but two cases, outlying students were not disproportionately likely to identify with historically marginalized groups based on gender or race/ethnicity. Thus, we did not broadly identify teamwork inequities in this specific context, but the method provides a basis for future studies about inequitable team behavior. 

Social-psychological interventions have raised the learning and performance of students in rigorous efficacy trials. Yet, after they are distributed “in the wild” for students to self-administer, there has been little research following up on their translational effectiveness. We used cutting-edge educational technology to tailor, scale up, and track a previously-validated Strategic Resource Use intervention among 12,065 college students in 14 STEM and Economics classes. Students who self-administered this “Exam Playbook” benefitted by an average of 2.17 percentage points (i.e., a standardized effect size of 0.18), compared to non-users. This effect size was 1.65 percentage points when controlling for college entrance exam scores and 1.75 [−1.88] for adding [dropping] the Exam Playbook in stratified matching analyses. Average benefits differed in magnitude by the conduciveness of the class climate (including peer norms and incentives), gender, first-generation status, as well as how often and how early they used the intervention. These findings on how, when, and who naturally adopts these resources address a need to improve prediction, translation, and scalability of social-psychological intervention benefits.