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This study provides practical suggestions for the features to be prioritized in spending limited resources to create and improve educational technology like Cell Collective. The results suggest a need to prioritize features improving the learning rather than the teaching side to motivate instructors more effectively to adopt and use the technology.

 

Graduate students are more than six times as likely to experience depression compared with the general population. However, few studies have examined how graduate school specifically affects depression. In this qualitative interview study of 50 life sciences PhD students from 28 institutions, we examined how research and teaching affect depression in PhD students and how depression in turn affects students’ experiences teaching and researching. Using inductive coding, we identified factors that either positively or negatively affected student depression. Graduate students more commonly mentioned factors related to research that negatively affected their depression and factors related to teaching that positively affected their depression. We identified four overarching aspects of graduate school that influenced student depression: the amount of structure in teaching and research, positive and negative reinforcement, success and failure, and social support and isolation. Graduate students reported that depression had an exclusively negative effect on their research, primarily hindering their motivation and self-confidence, but that it helped them to be more compassionate teachers. This work pinpoints specific aspects of graduate school that PhD programs can target to improve mental health among life sciences graduate students. 

Past research on group work has primarily focused on promoting change through implementation of interventions designed to increase performance. Recently, however, education researchers have called for more descriptive analyses of group interactions. Through detailed qualitative analysis of recorded discussions, we studied the natural interactions of students during group work in the context of a biology laboratory course. We analyzed multiple interactions of 30 different groups as well as data from each of the 91 individual participants to characterize the ways students engage in discussion and how group dynamics promote or prevent meaningful discussion. Using a set of codes describing 15 unique behaviors, we determined that the most common behavior seen in student dialogue was analyzing data, followed by recalling information and repeating ideas. We also classified students into one of 10 different roles for each discussion, determined by their most common behaviors. We found that, although students cooperated with one another by exchanging information, they less frequently fully collaborated to explain their conclusions through the exchange of reasoning. Within this context, these findings show that students working in groups generally choose specific roles during discussions and focus on data analysis rather than constructing logical reasoning chains to explain their conclusions.