Student Perceptions of Group Work and Group Formation Strategies

Group work is a common practice in statistics and data science courses. However, students in introductory courses often have a wide range of previous experience with group work. In this study, we examine the perceptions of introductory statistics students around group formation at a medium-sized liberal arts university. Group experiences were implemented in two ways. First, students rotated through assigned group seating throughout the semester to work in new teams on in-class work. Second, students completed two group projects. For the first group project, students were randomly assigned a team, and on the second project, students could choose between picking a team of students or being randomized into a team. Pre- and post-semester surveys were used to gather student perceptions around group work formation and to better understand perceived benefits of each method. Students also completed post-project reflections about their project experiences. Surveys and reflections indicated that students preferred working with others that they knew best, but respondents still identified benefits such as getting to know other classmates when working in randomly assigned teams. Responses also indicated the importance of work ethic (e.g., trusting partners, fair distribution of workload) regarding potential teammates for both randomized and self-selected groups.

Authors

Institutions

Publication Details

Journal
Journal of Statistics and Data Science Education
Published
2025-05-19
DOI
https://doi.org/10.1080/26939169.2025.2507765
Primary Topic
Innovative Teaching and Learning Methods
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Student Perceptions of Group Work and Group Formation Strategies

Nicholas W. Bussberg, Laura Taylor
Journal of Statistics and Data Science Education
Innovative Teaching and Learning Methods
article

Student Perceptions of Group Work and Group Formation Strategies

Nicholas W. Bussberg, Laura Taylor
article en

Abstract

Group work is a common practice in statistics and data science courses. However, students in introductory courses often have a wide range of previous experience with group work. In this study, we examine the perceptions of introductory statistics students around group formation at a medium-sized liberal arts university. Group experiences were implemented in two ways. First, students rotated through assigned group seating throughout the semester to work in new teams on in-class work. Second, students completed two group projects. For the first group project, students were randomly assigned a team, and on the second project, students could choose between picking a team of students or being randomized into a team. Pre- and post-semester surveys were used to gather student perceptions around group work formation and to better understand perceived benefits of each method. Students also completed post-project reflections about their project experiences. Surveys and reflections indicated that students preferred working with others that they knew best, but respondents still identified benefits such as getting to know other classmates when working in randomly assigned teams. Responses also indicated the importance of work ethic (e.g., trusting partners, fair distribution of workload) regarding potential teammates for both randomized and self-selected groups.

Journal of Statistics and Data Science Education
Elon University (US)
Openalex Percentile: Top 89%
Innovative Teaching and Learning Methods
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.