Educational achievement can be considered a multifaceted issue, which takes into account many domains of learning at different levels of the educational path. In Italy, during the secondary school years, such achievements are measured through the administration of the INVALSI tests, which are standardized tests on a national scale that students carry out at different stages of their career, to identify their level of competence in subjects like literacy, numeracy, and English reading and listening proficiencies. They are applied each year to trace a history of students' skills and knowledge, but also to assess the correspondence between skills and competences acquired with respect to ministerial educational programs. Moreover, the high school final mark may be considered an overall result of performance at the end of secondary school, a sort of synthesis of several achievements and marks in different subjects. The aim of the present work is to discover if and how the INVALSI scores and the high school final marks are related. More specifically, we intend to verify how the INVALSI scores are associated with students’ high school final mark, taking into account students’ characteristics as well as school observed (mainly, type of high school) and unobservable characteristics. The present contribution represents a preparatory work to analyse the predictive capability of INVALSI scores and/or high school final marks on university students’ careers. For this reason, the analysis is carried on the INVALSI dataset related with students enrolled in an Italian university. In the next section, we describe data and statistical methods used in the study. Then, we illustrate the main results. A preliminary discussion of results and some final remarks about future research conclude the work.

Assessing the predictive capability of Invalsi tests on high school final mark / Bacci, Silvia; Bertaccini, Bruno; Petrucci, Alessandra; Tocchioni, Valentina. - ELETTRONICO. - 134:(2023), pp. 11-16. (Intervento presentato al convegno ASA 2022 Data-Driven Decision Making tenutosi a Genova nel 12-14 settembre 2022) [10.36253/979-12-215-0106-3.03].

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

Bacci, Silvia;Bertaccini, Bruno;Petrucci, Alessandra;Tocchioni, Valentina
2023

Abstract

Educational achievement can be considered a multifaceted issue, which takes into account many domains of learning at different levels of the educational path. In Italy, during the secondary school years, such achievements are measured through the administration of the INVALSI tests, which are standardized tests on a national scale that students carry out at different stages of their career, to identify their level of competence in subjects like literacy, numeracy, and English reading and listening proficiencies. They are applied each year to trace a history of students' skills and knowledge, but also to assess the correspondence between skills and competences acquired with respect to ministerial educational programs. Moreover, the high school final mark may be considered an overall result of performance at the end of secondary school, a sort of synthesis of several achievements and marks in different subjects. The aim of the present work is to discover if and how the INVALSI scores and the high school final marks are related. More specifically, we intend to verify how the INVALSI scores are associated with students’ high school final mark, taking into account students’ characteristics as well as school observed (mainly, type of high school) and unobservable characteristics. The present contribution represents a preparatory work to analyse the predictive capability of INVALSI scores and/or high school final marks on university students’ careers. For this reason, the analysis is carried on the INVALSI dataset related with students enrolled in an Italian university. In the next section, we describe data and statistical methods used in the study. Then, we illustrate the main results. A preliminary discussion of results and some final remarks about future research conclude the work.
2023
ASA 2022 Data-Driven Decision Making
ASA 2022 Data-Driven Decision Making
Genova
12-14 settembre 2022
Goal 4: Quality education
Bacci, Silvia; Bertaccini, Bruno; Petrucci, Alessandra; Tocchioni, Valentina
File in questo prodotto:
File Dimensione Formato  
37722.pdf

accesso aperto

Descrizione: paperASA2022
Tipologia: Pdf editoriale (Version of record)
Licenza: Open Access
Dimensione 463.86 kB
Formato Adobe PDF
463.86 kB Adobe PDF

I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1318852
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact