Shima Salehi

Bifocal modeling: mixing real and virtual labs for advanced science learning

In this paper, we describe a set of user studies within the Bifocal Modeling (BM) framework. BM juxtaposes physical and computer models using sensor-based and computer modeling technologies, highlighting the discrepancies between ideal and real systems. When creating bifocal models, students build both a physical model with sensors of a given scientific phenomenon, and a computer model of the same phenomenon, connecting the two in real time with a special hardware interface. In this paper, we describe four formats for using BM in the classroom, as well as its affordances and characteristics.

Enhancing Diversity in Undergraduate Science: Self-Efficacy Drives Performance Gains with Active Learning

An active-learning pedagogy increased all students’ science self-efficacy, but this increase led to improved academic performance only for underrepresented minority students—an improvement that eliminated the performance gap present in the traditional lecture semester.

Exams disadvantage women in introductory biology

The gender gap in STEM fields has prompted a great deal of discussion, but what factors underlie performance deficits remain poorly understood. We show that female students underperformed on exams compared to their male counterparts across ten large introductory biology course sections in fall 2016 (N > 1500 students). Females also reported higher levels of test anxiety and course-relevant science interest. Results from mediation analyses revealed an intriguing pattern: for female students only, and regardless of their academic standing, test anxiety negatively impacted exam performance, while interest in the course-specific science topics increased exam performance. Thus, instructors seeking equitable classrooms can aim to decrease test anxiety and increase student interest in science course content. We provide strategies for mitigating test anxiety and suggestions for alignment of course content with student interest, with the hope of successfully reimagining the STEM pathway as one that is equally accessible to all.

Improving the Replicability of Psychological Science Through Pedagogy

Replications are important to science, but who will do them? One proposal is that students can conduct replications as part of their training. As a proof of concept for this idea, here we report a series of 11 preregistered replications of findings from the 2015 volume of Psychological Science, all conducted as part of a graduate-level course. As was expected given larger, more systematic prior efforts, the replications typically yielded effects that were smaller than the original ones: The modal outcome was partial support for the original claim. This work documents the challenges facing motivated students as they attempt to replicate previously published results on a first attempt. We describe the workflow and pedagogical methods that were used in the class and discuss implications both for the adoption of this pedagogical model and for replication research more broadly.