Share, Rotate, Split: The Effects of Group Work Role Distributions on Student Outcomes

Abstract

Education literature recommends many different strategies for structuring student group work in labs. Many of these strategies, however, have not been sufficiently evaluated for their effects on student outcomes. One prior study suggested that sharing roles, rather than splitting roles, in lab groups can boost students' physics interest and self-efficacy. Here, we expand upon this literature by evaluating the effects of a broader range of role distributions across several student outcomes from a large sample at two different institutions. We developed a survey item to probe the ways students distribute their roles in lab groups. The item asks for the percent of time in lab they spent working together on lab roles (sharing), working alone on roles but rotating each session (rotating), and working alone in the same role throughout the semester (splitting). We employed hierarchical linear modeling to measure the effects of these role distributions on student critical thinking, self-efficacy, perceived agency, belonging, and sense of recognition based on survey items specific to physics lab contexts. We found that role distributions did not differentially impact student critical thinking. We also found that sharing roles tended to have a positive impact on student attitudes; splitting had a negative effect on attitudes; and rotating fell in between. Statistical significance varied across these attitudinal outcomes. Our findings invite further research and controlled studies to better understand the apparent benefits of sharing, rotating, and splitting roles in introductory physics labs.

Figures (7)

• Figure 1: Factor loadings from confirmatory factor analysis of outcome constructs. "SE" is self-efficacy, "PA" is perceived agency, "BEL" is belonging, and "REC" is recognition. Anchor items for each factor are denoted with a dashed line. Line thickness and shade denote factor loading magnitude. Table \ref{['tab:attitudes']} gives the full text for each survey item.
• Figure 2: Predictor matrix for multiple imputation. "Semester & Course" was used as a cluster variable for all variables. We passively imputed data for "Split" (not shown here).
• Figure 3: Density plots of the reported percent of lab time students spent sharing, rotating, or splitting roles. Data presented are using listwise deletion.
• Figure 4: Bar graphs of the distribution of student scores on the PLIC and attitude constructs. The colored region represents the inter-quartile range and the horizontal line represents the median score. Whiskers indicate the values at $1.5$ times the interquartile range above the third quartile and below the first quartile. Dots indicate outliers defined as scores beyond the range of the whiskers (data presented is using listwise deletion).
• Figure 5: Results of hierarchical linear modeling of change in PLIC and attitude scores controlling for semester and course using data after multiple imputation. A value greater than zero indicates a positive effect on score, whereas a value less than zero indicates a negative effect on score. The horizontal dashed line indicates no observable effect on score. The error bars represent the standard error of the effect size. The asterisks denote statistical significance where $*$ indicates $p < 0.05$, and $**$ indicates $p < 0.01$.