Fondazione GRINS
Growing Resilient,
Inclusive and Sustainable
Galleria Ugo Bassi 1, 40121, Bologna, IT
C.F/P.IVA 91451720378
Finanziato dal Piano Nazionale di Ripresa e Resilienza (PNRR), Missione 4 (Infrastruttura e ricerca), Componente 2 (Dalla Ricerca all’Impresa), Investimento 1.3 (Partnership Estese), Tematica 9 (Sostenibilità economica e finanziaria di sistemi e territori).
Open Access
GRINS THEMATIC AREAS
RESOURCES
We study the impact of a program designed to enhance data literacy on graduate students’ skills and academic outcomes at a large Italian university. The program (i.e. a minor ) targets students who are expected to have weak quantitative competences and offers 120-hour training focused on improving their ability to interpret and process data, in addition to the regular courses of the master’s program in which students are enrolled (i.e. their major ).
The admission process to the minor is characterized by rationing, resolved by random assignment of available slots to applicants. Exploiting the resulting exogenous variation for identification, we find that the program substantially improves data literacy among participants with low pre-treatment levels of numeracy. Despite the additional effort required by the program, we find no evidence of a slowdown in students’ progress in their major, as they pass at least as many exams as their peers in the control group.
We also find evidence of positive spillovers on the GPA of students with lower initial numeracy. Finally, using follow-up survey data collected approximately two years after, we show that participants with low pre-treatment numeracy are more likely to be in paid employment.
KEYWORDS
AKNOWLEDGEMENTS
In Alphabetic Order: Conceptualization: M.Fort, A. Loviglio; Field work administration and data management: M. Fort., A. Loviglio, S. Tinti; Data analysis: M. Fort, A. Loviglio, S. Tinti; Draft preparation, review and editing: M. Fort, A.Loviglio, S. Tinti; Funding acquisition: M.Fort, A. Loviglio. Funding from MIUR to the Department of Economics (Department of Excellence grant - 2018-2022) for baseline and endline data collection and from European Union - NextGenerationEU, Mission 4, Component 2, in the framework of the GRINS -Growing Resilient, INclusive and Sustainable project (GRINS PE00000018 – CUP J33C22002910001) for follow-up data collection is gratefully acknowledged. We gratefully thank A. Saia who contributed to the design of the ad-hoc survey on data literacy and offered funds to support the data collection. S. Tinti gratefully acknowledges financial support by the EU - NextGenerationEU with funds made available by National Recovery and Resilience Plan (NRRP) Mission 4, Component 1, Investment 4.1 (MD 351/2022) – Public Administration (PhD fellowship 38-412-03-DOT22K2552-43 CUP J33C22001850002). A. Loviglio and M. Fort gratefully acknowledge funding by the European Union - NextGenerationEU, Mission 4, Component 2, in the framework of the GRINS -Growing Resilient, INclusive and Sustainable project (GRINS PE00000018 – CUP J33C22002910001). We are grateful to the board of the LEDA program and to the data warehouse of the University that hosted the minor program for their support. All authors have read and agreed to the published version of the manuscript. We thank participants of the Public Governance Management and Policy PhD Forum and the ESPANET Conference 2024, specifically L. Bonaccini, N. Montanari, G. Pignataro and L. Vergolini for useful comments and remarks on an earlier version of the project. The views and opinions expressed are solely those of the authors and do not necessarily reflect those of the European Union, nor can the European Union be held responsible for them. Similarly, they do not reflect those of the Ministry of Economy and Finance, nor can the Ministry of Economy and Finance be held responsible for them. An earlier version of the manuscript appeared as GRINS DP N. 03/2025 May 2025 with the title “The consequences of promoting data literacy among graduate students”. This version integrates the previous one with additional results on follow-up data.
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