Team production in a field experiment: study of aggregative vs. individual cultural activities

Abstract

This study aims to determine whether team production among peer groups culturally aggregated can affect the individual student performance in an Italian university. Two further hypotheses were tested in order to verify whether students perform better in team than individually and if students culturally aggregated in team perform better than students differently aggregated. By means of a field experiment, 162 students were involved in the study. The participants had the opportunity to sit a new examination model after responding to a self-reported questionnaire. The new model contemplated that the students performed in team for the first part of the program and carried out the remaining part of examination individually. The groups were composed of individuals linked by homogeneous preferences about cultural activities. The results show that team performance affects positively the final score of exam and the students culturally aggregated pass the exam more than students not culturally aggregated. The aggregative cultural activities influenced the test score more than individual effort or other personal characteristics. We therefore recommend the implementation of a new examination models based on cooperation among students supporting the aggregative cultural activities where sharing action prevails as predictors.

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Fig. 1

Notes

  1. 1.

    18% vs. 37% European average and vs. 46% achieved by the USA and UK.

  2. 2.

    The questionnaire contained questions about students’ cultural habits, divided in aggregated activities and individually activities.

  3. 3.

    Every participant joining to study was free to leave the experiment at any time and decide to return to the conventional examination scheme.

  4. 4.

    Toffler theory identifies with a term “prosumer” an individual strongly independent of the classical economy paradigm, in general, he referred to a “user” with a more active role in the creation, production, distribution, and consumption of a product. For more details, see Toffler 1980The Third Wave. New York: William Morrow.

  5. 5.

    Magna Graecia University is a small-sized public university located in the south of Italy. It has currently about 10,638 students enrolled in different degree courses and at different levels of the Italian university system. Since the 2001 reform, the Italian university system is organized around three main levels: first level degrees (3 years of legal duration), second level degrees (2 years more) and Ph.D. degrees. In order to gain a first level degree, students have to acquire a total of 180 credits. Students who have acquired a first level degree can undertake a second level degree (acquiring 120 more credits). After having accomplished their second level degree, students can enroll in a Ph.D. degree.

  6. 6.

    Respectively of the first and second year of the first level degree course in firm economy and of the second year of the second level degree course in firm economy and management.

  7. 7.

    MEF and ST are courses offered by First Level Degree called Business and Administration at the first and second year, respectively, and QMEF is offered by Second Level Degree called Business and Management Administration at the second year.

  8. 8.

    In Italian University, the scale is ranged from 1 to 31, where the number 31 identifies 30 et laude, that is the adding encomium to 30. The exam is considered passed if the student reaches a final grade of 18 grades.

  9. 9.

    Each participant received and signed the informed consent form to allow us to use the data collected through the questionnaire; furthermore’, they were informed about the rules of the experiment and how they were assigned to their team.

  10. 10.

    In particular, 33, 54, and 18 students were mutually clustered in team of 3 individuals respectively for MEF, St, and QMEF.

  11. 11.

    The repartition experimental-control for subject was as follows: 33–33 for MEF, 36–36 for St, and 12–12 for QMEF.

  12. 12.

    As described in the notes 9, 10, and 11, given the low number of data especially for QMEF and a similar composition of technical courses with respect to 12 items of the questionnaire (see Appendix 1) all the statistical analyses are considered for the 162 sample.

  13. 13.

    For a major comprehension of the scale used, we remand the reader to Appendix 1.

  14. 14.

    In our study, we have no data referred to parents’ education and employment.

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Appendices

Appendix 1. Definition, label, and scale of variables

In Table 7, we present the variables of interest with a synthetic definition and relative scale.

Table 7 Variable definition

Appendix 2. Descriptive statistics across courses

In Table 8, we report the descriptive statistics relating to the courses. A similar composition across 12 items of UNESCO questionnaire is shown with respect to Table 1. It is evident that the only changed characteristic is the age. In fact, as we will see later, Age represents a not determinant variable for our study.

Table 8 Descriptive statistics across courses

Appendix 3. Backward linear regression model on Grade Team Part

Starting from the model (8) of Table 5, we run a linear regression model where the Grade Team Part is explained by Culturally Aggregated Team and by only variables in the vectors Xi, Yi, Zi, Pi, Ci, and PCi that do not drop, 1 at a time, to the specification to be significant at least 10%. Shortly, the model resulting is so specified:

$$ \mathrm{Grade}\ {\mathrm{Part}\ \mathrm{Team}}_{\mathrm{i}}=\genfrac{}{}{0pt}{}{3.993\ast \ast \ast }{(1.503)}+\genfrac{}{}{0pt}{}{1.706\ast \ast \ast }{(0.371)}\mathrm{Culturally}\ {\mathrm{Aggregated}\ \mathrm{Team}}_{\mathrm{i}}+\genfrac{}{}{0pt}{}{0.056\ast \ast \ast }{(0.016)}\mathrm{High}\ {\mathrm{School}\ \mathrm{Grade}}_{\mathrm{i}}+\genfrac{}{}{0pt}{}{0.529\ast }{(0.274)}\mathrm{Play}\ {\mathrm{an}\ \mathrm{instrument}}_{\mathrm{i}}+\genfrac{}{}{0pt}{}{0.591\ast \ast }{(0.254)}{\mathrm{Political}}_{\mathrm{i}}-\genfrac{}{}{0pt}{}{0.514\ast \ast }{(0.242)}{\mathrm{Conference}}_{\mathrm{i}}+\genfrac{}{}{0pt}{}{0.350\ast }{(0.207)}{\mathrm{News}}_{\mathrm{i}}+{\varepsilon}_{\mathrm{i}} $$

with adjusted R-squared = 0.223, observations = 162, F = 8.684 p(F) < 0.01. Estimation results are sensibly greater than the ones of the full model and now, News participates at level 10% with a positive magnitude of + 0.350 points to explain Grade Team Part.

Appendix 4. Evaluating cultural connection across age and passing the intermediate team test

To exclude potential effects of participants not commonly aged of university study, we focus on the reduced sample of 155 students aged under 28 years old.

Table 9 Cultural aggregations and team performance. OLS and Tobit estimates for only students aged less under 30 years old

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Lo Prete, F., Macrì, E. & Rania, F. Team production in a field experiment: study of aggregative vs. individual cultural activities. High Educ 81, 345–365 (2021). https://doi.org/10.1007/s10734-020-00544-z

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Keywords

  • Team production
  • Cultural aggregation
  • Student performance
  • Predictions
  • Field experiment