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Assessing the predictive capability of Invalsi tests on high school final mark

  • Silvia Bacci
  • Bruno Bertaccini
  • Alessandra Petrucci
  • Valentina Tocchioni

Educational achievement can be considered a multifaceted issue, which comprises different domains of learning. In Italy, on one hand the INVALSI tests administered to students through the schooling years aim to measure the ability of students in numeracy, literacy and English reading and listening competencies, separately. On the other hand, the high school final mark may be considered an overall performance outcome, formed by the combination of several marks in different subjects. Finally, at university academic achievement may be represented by the number of credits earned during the first year of enrolment, usually considered a good predictor of successful academic performances. The aim of the present work is to understand if the INVALSI scores, the high school final mark and the number of credits earned in the first academic year are associated. More specifically, our objective is twofold: first, we intend to verify if and how the INVALSI scores are associated with students’ high school final mark; second, we aim to check if the INVALSI scores and / or the high school final mark are predictive of students’ career in terms of credits earned in the first year. We will interpret our results concentrating our attention on eventual differences depending on type of school, university, field of study, student’s geographical area of residence. We use the MOBYSU.it database, selecting nearly 200.000 students who obtained their high school diploma in Italy in 2019 and enrolled in an Italian university in academic year 2019/2020. For the first objective, we estimate a multilevel ordered logit models, with students nested within high schools; as for the second objective, we estimate a cross-classified multilevel models, with students nested within high schools and athenaeums. We interpret our results in the light of assessing eventual divergences in students’ performances during the transition from high school to university.

  • Keywords:
  • University students,
  • academic performance,
  • educational achievement,
  • multilevel models,
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Silvia Bacci

University of Florence, Italy - ORCID: 0000-0001-8097-3870

Bruno Bertaccini

University of Florence, Italy - ORCID: 0000-0002-5816-2964

Alessandra Petrucci

University of Florence, Italy - ORCID: 0000-0001-9952-0396

Valentina Tocchioni

University of Florence, Italy - ORCID: 0000-0002-0793-6122

  1. Goldstein, H. (2010). Multilevel Statistical Models. 4th Edition, John Wiley & Sons, Ltd
  2. Liu, I., Agresti, A. (2005). The analysis of ordered categorical data: An overview and a survey of recent developments. Test, 14(1), pp. 1-73.
  3. Snijders, T. A.B., Bosker, R. J. (2012). Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling. London, Sage Publishers.
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  • Publication Year: 2023
  • Pages: 11-16
  • Content License: CC BY 4.0
  • © 2023 Author(s)

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  • Publication Year: 2023
  • Content License: CC BY 4.0
  • © 2023 Author(s)

Chapter Information

Chapter Title

Assessing the predictive capability of Invalsi tests on high school final mark

Authors

Silvia Bacci, Bruno Bertaccini, Alessandra Petrucci, Valentina Tocchioni

Language

English

DOI

10.36253/979-12-215-0106-3.03

Peer Reviewed

Publication Year

2023

Copyright Information

© 2023 Author(s)

Content License

CC BY 4.0

Metadata License

CC0 1.0

Bibliographic Information

Book Title

ASA 2022 Data-Driven Decision Making

Book Subtitle

Book of short papers

Editors

Enrico di Bella, Luigi Fabbris, Corrado Lagazio

Peer Reviewed

Publication Year

2023

Copyright Information

© 2023 Author(s)

Content License

CC BY 4.0

Metadata License

CC0 1.0

Publisher Name

Firenze University Press, Genova University Press

DOI

10.36253/979-12-215-0106-3

eISBN (pdf)

979-12-215-0106-3

eISBN (xml)

979-12-215-0107-0

Series Title

Proceedings e report

Series ISSN

2704-601X

Series E-ISSN

2704-5846

73

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