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The Credit Accumulation Process to Assess the Performances of Degree Programs: An Adjusted Indicator Based on the Result of Entrance Tests

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Statistical Models for Data Analysis

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Abstract

In the frame of the performance indicators this paper aims to consider the bias produced by micro-level Potential Confounding Factors—PCF—by comparing the results observed using adjusted and unadjusted measures of outcome. Results at the university entrance tests together with the previous school experiences have been used as proxies of students’ competencies at the beginning of their academic career. The regularity of schooling process has been monitored using as an outcome variable the students’ status (drop out, still enrolled) and the number of credits gathered after one academic year. Adjusted indicators of the regularity of the students’ career are obtained using the results of zero-augmented models to investigate the relationships between the outcome measures and the potential PCF which are not directly associated to the learning process under evaluation.

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Authors and Affiliations

  1. Dip. Scienze Sociali e delle Istituzioni, Università di Cagliari, Cagliari, Italy

    Mariano Porcu & Isabella Sulis

Authors
  1. Mariano Porcu
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  2. Isabella Sulis
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Corresponding author

Correspondence to Mariano Porcu .

Editor information

Editors and Affiliations

  1. Department of Economics, and Management, University of Pavia, Via San Felice 7, Pavia, 27100, Italy

    Paolo Giudici

  2. Department of Economics, and Business, University of Catania, Corso Italia 55, Catania, 95129, Italy

    Salvatore Ingrassia

  3. , Department of Statistics, University of Rome "La Sapienza", Piazzale Aldo Moro 5, Rome, 00185, Italy

    Maurizio Vichi

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Porcu, M., Sulis, I. (2013). The Credit Accumulation Process to Assess the Performances of Degree Programs: An Adjusted Indicator Based on the Result of Entrance Tests. In: Giudici, P., Ingrassia, S., Vichi, M. (eds) Statistical Models for Data Analysis. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00032-9_32

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