Evaluating Individual Contributions in Teams for Project-Based Learning in Data Science

In this Innovative-Practice Full Paper, we present the design and implementation of a novel strategy for the assessment of the individual contributions of students working in teams for an interdisciplinary project-based learning (PBL) course. Team-based and project-based learning have been the cornerstones of experiential learning in recent years. In such courses, the assessment of students is often performed solely at a team level, resulting in student discontent, concerns about fairness, and social loafing. The application of a single method for evaluating individual contributions has its shortcomings, prompting us to incorporate a combination of evidence-based approaches. Thus, to mitigate these problems, we developed an assessment strategy that involves three components - self and peer evaluation (SPA), instructor's evaluation of individual contribution, and class participation. Anonymized SPA was carried out at three different checkpoints over the semester for both formative and summative assessment. The individual contribution of the students is also evaluated by the instructor and/or other mentors based on their interactions with all the students in the team over the entire semester. Class participation is another component of individual contribution incorporated in our scheme, where instructors evaluate the participation of individual students in classroom activities, presentations, and meetings. We collected feedback about the perception of students towards our assessment policies for individual contribution. We observed overall satisfaction and positive attitudes toward our scheme. We noted positive student perceptions of fairness in grading through our scheme and reduced chances of social loafing. Further, in the feedback, the students noted the effectiveness of using SPA as an evaluation tool, the usefulness of instructor's evaluation, and the role of class participation in creating a more engaging classroom and a more enriching experience. We also emphasize the need to set clear expectations for students with regard to the grading policies early in the semester. Finally, we discuss our experiences in implementing our design and recommendations for incorporating our grading scheme in team-based PBL courses.

Authors

Institutions

Publication Details

Published
2024-10-13
DOI
https://doi.org/10.1109/fie61694.2024.10893455
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Evaluating Individual Contributions in Teams for Project-Based Learning in Data Science

Genevera I. Allen, Arko Barman, Chen Su
Big Data and Business Intelligence
article

Evaluating Individual Contributions in Teams for Project-Based Learning in Data Science

Genevera I. Allen, Arko Barman, Chen Su
article en

Abstract

In this Innovative-Practice Full Paper, we present the design and implementation of a novel strategy for the assessment of the individual contributions of students working in teams for an interdisciplinary project-based learning (PBL) course. Team-based and project-based learning have been the cornerstones of experiential learning in recent years. In such courses, the assessment of students is often performed solely at a team level, resulting in student discontent, concerns about fairness, and social loafing. The application of a single method for evaluating individual contributions has its shortcomings, prompting us to incorporate a combination of evidence-based approaches. Thus, to mitigate these problems, we developed an assessment strategy that involves three components - self and peer evaluation (SPA), instructor's evaluation of individual contribution, and class participation. Anonymized SPA was carried out at three different checkpoints over the semester for both formative and summative assessment. The individual contribution of the students is also evaluated by the instructor and/or other mentors based on their interactions with all the students in the team over the entire semester. Class participation is another component of individual contribution incorporated in our scheme, where instructors evaluate the participation of individual students in classroom activities, presentations, and meetings. We collected feedback about the perception of students towards our assessment policies for individual contribution. We observed overall satisfaction and positive attitudes toward our scheme. We noted positive student perceptions of fairness in grading through our scheme and reduced chances of social loafing. Further, in the feedback, the students noted the effectiveness of using SPA as an evaluation tool, the usefulness of instructor's evaluation, and the role of class participation in creating a more engaging classroom and a more enriching experience. We also emphasize the need to set clear expectations for students with regard to the grading policies early in the semester. Finally, we discuss our experiences in implementing our design and recommendations for incorporating our grading scheme in team-based PBL courses.

Rice University (US), Columbia University (US), The University of Texas at Austin (US)
National Science Foundation
Openalex Percentile: Top 56%
Big Data and Business Intelligence
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.