The ability to predict student performance in a course or program creates opportunities to
improve educational outcomes. With effective performance prediction approaches …

Retaining students in science, technology, engineering, and math (STEM) fields is critical as
demand for STEM graduates increases. Whereas many approaches to improve persistence …

O objetivo da presente revisão da literatura é apresentar um perfil das pesquisas sobre
evasão e persistência em cursos de graduação das áreas de Ciências e Matemática …

This study uses social network analysis and the classroom observation protocol for
undergraduate STEM (COPUS) to characterize six research-based introductory physics …

Physics education research is replete with observations and proposed explanations for
gender disparities in physics. In this work, we operationalize a definition for equity as …

Physics outreach programs provide a critical context for informal experiences that promote
the transition from new student to contributing physicist. Prior studies have suggested a …

Engaging in interactions with peers is important for student learning. Many studies have
quantified patterns of student interactions in in-person physics courses using social network …

Abstract Social Network Analysis (SNA) is becoming a popular theoretical and
methodological approximation for educational researchers. SNA enables a deep exploration …

We compute nodal centrality measures on the collaboration networks of students enrolled in
three upper-division physics courses, usually taken sequentially, at the Colorado School of …

Productive learning processes and good learning outcomes can be attained by applying the
basic elements of active learning. The basic elements include fostering discussions and …