Digital Device and Mathematics: Multilevel vs Machine Learning Models for Value-added Ranking in Italy

Donatella Papa

2022

Abstract

With the COVID-19 pandemic and the development of distance education programs, digital learning is popular and strategic in many learning fields. The deployment of Information and Communications Technology and its impact on both national and international learning programs are becoming increasingly significant. This study seeks to explore in the Italian context both the effectiveness of digital learning in Mathematics Education and which features and how affect value-added at the classroom level. To explore Information and Communications Technology contribution and value-added scoring, the study takes into consideration the analytical power of classical multilevel models concerning the predictive power of different types of machine learning models. The study aims to investigate how Information and Communications Technology, and related concepts, impact the Weighted Likelihood Estimates in Mathematics for students in the lower secondary school, using data from the INVALSI of the school year 2017/2018. The main finding is that Personal Computer ownership at home plays an important role in mathematical learning. Finally, a machine learning model incorporated in the educational domain can be an interesting starting point for developing class-predictive policies.

Paper Citation

in Harvard Style

Papa D. (2022). Digital Device and Mathematics: Multilevel vs Machine Learning Models for Value-added Ranking in Italy. In Proceedings of the 14th International Conference on Computer Supported Education - Volume 2: CSEDU, ISBN 978-989-758-562-3, pages 171-178. DOI: 10.5220/0011042700003182

in Bibtex Style

@conference{csedu22,
author={Donatella Papa},
title={Digital Device and Mathematics: Multilevel vs Machine Learning Models for Value-added Ranking in Italy},
booktitle={Proceedings of the 14th International Conference on Computer Supported Education - Volume 2: CSEDU,},
year={2022},
pages={171-178},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011042700003182},
isbn={978-989-758-562-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Conference on Computer Supported Education - Volume 2: CSEDU,
TI - Digital Device and Mathematics: Multilevel vs Machine Learning Models for Value-added Ranking in Italy
SN - 978-989-758-562-3
AU - Papa D.
PY - 2022
SP - 171
EP - 178
DO - 10.5220/0011042700003182