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A biclustering approach to university performances: an Italian case study
Applications · Submitted 24 Apr 2014
abstract compiled · 2026-09-23 · no language-model review
The authors' main claim Thus, we suggest that caution should be used in interpreting standard university rankings as they generally do not account for the complex structure of the data.
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The abstract, sentence by sentence
University evaluation is a topic of increasing concern in Italy as well as in other countries. In empirical analysis, university activities and performances are generally measured by means of indicator variables, summarizing the available information under different perspectives. In this paper, we argue that the evaluation process is a complex issue that can not be addressed by a simple descriptive approach and thus association between indicators and similarities among the observed universities should be accounted for. Particularly, we examine faculty-level data collected from different sources, covering 55 Italian Economics faculties in the academic year 2009/2010. Making use of a clustering framework, we introduce a biclustering model that accounts for both homogeneity/heterogeneity among faculties and correlations between indicators. Our results show that there are two substantial different performances between universities which can be strictly related to the nature of the institutions, namely the Private and Public profiles . Each of the two groups has its own peculiar features and its own group-specific list of priorities, strengths and weaknesses. Thus, we suggest that caution should be used in interpreting standard university rankings as they generally do not account for the complex structure of the data.
background contribution method result interpretation main claim
| # | sentence | role | the authors' own work | states the main conclusion | strength |
|---|---|---|---|---|---|
| s0 | University evaluation is a topic of increasing concern in Italy as well as in other countries. | background 1.00 | 0.04 | 0.01 | asserted 1.00 |
| s1 | In empirical analysis, university activities and performances are generally measured by means of indicator variables, summarizing the available information under different perspectives. | background 1.00 | 0.06 | 0.01 | asserted 1.00 |
| s2 | In this paper, we argue that the evaluation process is a complex issue that can not be addressed by a simple descriptive approach and thus association between indicators and similarities among the observed universities should be accounted for. | gap 0.64 | 0.15 | 0.07 | asserted 0.99 |
| s3 | Particularly, we examine faculty-level data collected from different sources, covering 55 Italian Economics faculties in the academic year 2009/2010. | method 0.88 | 0.85 | 0.02 | asserted 0.95 |
| s4 | Making use of a clustering framework, we introduce a biclustering model that accounts for both homogeneity/heterogeneity among faculties and correlations between indicators. | method 0.85 | 0.94 | 0.06 | asserted 0.99 |
| s5 | Our results show that there are two substantial different performances between universities which can be strictly related to the nature of the institutions, namely the Private and Public profiles . | result 0.99 | 0.95 | 0.72 | asserted 1.00 |
| s6 | Each of the two groups has its own peculiar features and its own group-specific list of priorities, strengths and weaknesses. | interpretation 0.54 | 0.82 | 0.11 | asserted 1.00 |
| s7 | Thus, we suggest that caution should be used in interpreting standard university rankings as they generally do not account for the complex structure of the data. | interpretation 0.99 | 0.22 | 0.62 | hedged possibility 0.92 |
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The paper
Original abstract
University evaluation is a topic of increasing concern in Italy as well as in other countries. In empirical analysis, university activities and performances are generally measured by means of indicator variables, summarizing the available information under different perspectives. In this paper, we argue that the evaluation process is a complex issue that can not be addressed by a simple descriptive approach and thus association between indicators and similarities among the observed universities should be accounted for. Particularly, we examine faculty-level data collected from different sources, covering 55 Italian Economics faculties in the academic year 2009/2010. Making use of a clustering framework, we introduce a biclustering model that accounts for both homogeneity/heterogeneity among faculties and correlations between indicators. Our results show that there are two substantial different performances between universities which can be strictly related to the nature of the institutions, namely the Private and Public profiles . Each of the two groups has its own peculiar features and its own group-specific list of priorities, strengths and weaknesses. Thus, we suggest that caution should be used in interpreting standard university rankings as they generally do not account for the complex structure of the data.
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