A Framework for Detecting Factors Influencing Students’ Academic Performance: A Longitudinal Analysis
| Autor: | Angela Maria D'Uggento, Rosa Ceglie, Francesco Domenico D'Ovidio, Ernesto Toma |
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| Rok vydání: | 2020 |
| Předmět: |
Decision support system
Actuarial science Academic year Sociology and Political Science Performance management Higher education business.industry Corporate governance media_common.quotation_subject 05 social sciences General Social Sciences 050109 social psychology Logistic regression Arts and Humanities (miscellaneous) 0502 economics and business Business intelligence Developmental and Educational Psychology 0501 psychology and cognitive sciences Quality (business) 050207 economics business Psychology media_common |
| Zdroj: | Social Indicators Research. 156:389-407 |
| ISSN: | 1573-0921 0303-8300 |
| DOI: | 10.1007/s11205-020-02334-7 |
| Popis: | Following the introduction of performance management in Italian universities, Business intelligence has become a strategical means to use administrative data in support of governance and decision-making processes. The aim of this paper is to show the important role played by a decision support system inside an organization by evaluating the outcomes of the fair tuition fee policy of the University of Bari, in favour of low-income students, stated as a priority in its mission. A longitudinal analysis is carried out on the cohort of first-year students enrolled in the academic year 2015–2016, searching for a predictive model of their performance given some explicative variables. The usefulness of adopting a periodic monitoring system, investigating data by means of suitable statistical techniques (logistic regression, survival analysis, Cox regression model), allows to early detect those factors to be modified in order to achieve optimal results with respect to student expectations and quality of higher education. |
| Databáze: | OpenAIRE |
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