The aim of this paper is to present a new proposal for the classification of Academic institutions in terms of quality of teaching. Our methodological proposal borrows concepts from operational risk, such as scorecard...The aim of this paper is to present a new proposal for the classification of Academic institutions in terms of quality of teaching. Our methodological proposal borrows concepts from operational risk, such as scorecard models, employed to assess University performances, on the basis of both the perceived and the actual quality. We propose to summarize opinion data using new non parametric indexes able to exploit efficiently the ordinal nature of the analysed variables and to integrate different sources of data. In particular we show how web survey methods can improve the quality and robustness of collected data, especially when integrated with students career data. Empirical evidence is given on the basis of real data from the University of Pavia.展开更多
This contribution deals with a generative approach for the analysis of textual data. Instead of creating heuristic rules forthe representation of documents and word counts, we employ a distribution able to model words...This contribution deals with a generative approach for the analysis of textual data. Instead of creating heuristic rules forthe representation of documents and word counts, we employ a distribution able to model words along texts considering different topics. In this regard, following Minka proposal (2003), we implement a Dirichlet Compound Multinomial (DCM) distribution, then we propose an extension called sbDCM that takes explicitly into account the different latent topics that compound the document. We follow two alternative approaches: on one hand the topics can be unknown, thus to be estimated on the basis of the data, on the other hand topics are determined in advance on the basis of a predefined ontological schema. The two possible approaches are assessed on the basis of real data.展开更多
文摘The aim of this paper is to present a new proposal for the classification of Academic institutions in terms of quality of teaching. Our methodological proposal borrows concepts from operational risk, such as scorecard models, employed to assess University performances, on the basis of both the perceived and the actual quality. We propose to summarize opinion data using new non parametric indexes able to exploit efficiently the ordinal nature of the analysed variables and to integrate different sources of data. In particular we show how web survey methods can improve the quality and robustness of collected data, especially when integrated with students career data. Empirical evidence is given on the basis of real data from the University of Pavia.
文摘This contribution deals with a generative approach for the analysis of textual data. Instead of creating heuristic rules forthe representation of documents and word counts, we employ a distribution able to model words along texts considering different topics. In this regard, following Minka proposal (2003), we implement a Dirichlet Compound Multinomial (DCM) distribution, then we propose an extension called sbDCM that takes explicitly into account the different latent topics that compound the document. We follow two alternative approaches: on one hand the topics can be unknown, thus to be estimated on the basis of the data, on the other hand topics are determined in advance on the basis of a predefined ontological schema. The two possible approaches are assessed on the basis of real data.
