Does one size fit all? Assessing teamwork in econometrics

Abstract Econometrics has become increasingly important in Economics and Business degrees, since it appears to be narrowly related to several main skills and competencies as information management, creativity, problem‐solving or decision‐making. Furthermore, the development of information technologies, including econometric software, makes it possible to learn Econometrics by doing Econometrics. In this context, teamwork can play an important role in the teaching–learning process by allowing students to collaborate in the development of an econometric model, becoming familiar with econometric software and acquiring a wide variety of teamwork skills as demanded by employers. Moreover, from the teachers' perspective, teamwork represents a good opportunity to reexamine some methodological aspects and suggests new challenges in the monitoring and assessment of teamwork. In this paper we summarise our experiences in the monitoring and assessment of econometrics teamwork, providing some suggesting empirical findings. We present an assessment proposal based on both objective teaching criteria and teammates’ gradings and we use empirical evidence to answer some relevant questions related to the consistency of information provided by students, the existence of significant biases and group effects, and the impact of teamwork on academic results. Context and implications Rationale for this study : To gain a better understanding of teamwork assessment involving students and teachers. To provide empirical evidence about the impact of collaborative work and the potential of students' self‐ and peer‐assessment. Why the new findings matter : The findings confirm the consistency of students when evaluating teamwork, also detecting a negative impact of intragroup heterogeneity on the teamwork outcome. Some significant biases are detected when comparing students' self‐assessment with corresponding peer and teacher assessments. Teamwork efforts have a positive impact on academic results. Implications for policy makers and practitioners : Universities should be encouraging students' participation in the assessment process, especially when dealing with collaborative experiences. Those involved in the teaching–learning process should make use of the available empirical information to better understand the impact of teamwork on academic results and students' motivation. Further research and more institutional support are advisable in this field.

Authors

Institutions

Publication Details

Journal
Review of Education
Published
2025-03-06
DOI
https://doi.org/10.1002/rev3.70053
Primary Topic
Team Dynamics and Performance
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Does one size fit all? Assessing teamwork in econometrics

Rigoberto Pérez‐Suárez, Ana Jesús López Menéndez
Review of Education
Team Dynamics and Performance
article

Does one size fit all? Assessing teamwork in econometrics

Rigoberto Pérez‐Suárez, Ana Jesús López Menéndez
article en

Abstract

Abstract Econometrics has become increasingly important in Economics and Business degrees, since it appears to be narrowly related to several main skills and competencies as information management, creativity, problem‐solving or decision‐making. Furthermore, the development of information technologies, including econometric software, makes it possible to learn Econometrics by doing Econometrics. In this context, teamwork can play an important role in the teaching–learning process by allowing students to collaborate in the development of an econometric model, becoming familiar with econometric software and acquiring a wide variety of teamwork skills as demanded by employers. Moreover, from the teachers' perspective, teamwork represents a good opportunity to reexamine some methodological aspects and suggests new challenges in the monitoring and assessment of teamwork. In this paper we summarise our experiences in the monitoring and assessment of econometrics teamwork, providing some suggesting empirical findings. We present an assessment proposal based on both objective teaching criteria and teammates’ gradings and we use empirical evidence to answer some relevant questions related to the consistency of information provided by students, the existence of significant biases and group effects, and the impact of teamwork on academic results. Context and implications Rationale for this study : To gain a better understanding of teamwork assessment involving students and teachers. To provide empirical evidence about the impact of collaborative work and the potential of students' self‐ and peer‐assessment. Why the new findings matter : The findings confirm the consistency of students when evaluating teamwork, also detecting a negative impact of intragroup heterogeneity on the teamwork outcome. Some significant biases are detected when comparing students' self‐assessment with corresponding peer and teacher assessments. Teamwork efforts have a positive impact on academic results. Implications for policy makers and practitioners : Universities should be encouraging students' participation in the assessment process, especially when dealing with collaborative experiences. Those involved in the teaching–learning process should make use of the available empirical information to better understand the impact of teamwork on academic results and students' motivation. Further research and more institutional support are advisable in this field.

Review of EducationVol. 13(1)
Universidad de Oviedo (ES)
Openalex Percentile: Top 95%
Team Dynamics and Performance
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.