Models of text mining to measure improvements to doctoral courses suggested by “STELLA” phd survey respondents
We present Text Mining models to thematically categorise and measure the suggestions of PhD holders on improving PhD programmes in the STELLA survey (Statistiche in TEma di Laureati e LAvoro). The coded responses questionnaire, designed to evaluate the employment opportunities of students and asses...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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University of Bologna
2014-10-01
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| Series: | Statistica |
| Subjects: | |
| Online Access: | http://rivista-statistica.unibo.it/article/view/4500 |
| _version_ | 1818110794863214592 |
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| author | Pasquale Pavone Maria Francesca Romano |
| author_facet | Pasquale Pavone Maria Francesca Romano |
| author_sort | Pasquale Pavone |
| collection | DOAJ |
| description | We present Text Mining models to thematically categorise and measure the suggestions of PhD holders on improving PhD programmes in the STELLA survey (Statistiche in TEma di Laureati e LAvoro). The coded responses questionnaire, designed to evaluate the employment opportunities of students and assess their learning experience, included open-ended questions on how to improve PhD programmes. The Corpus analysed was taken from the data of Italian PhD holders between 2005 and 2009 in eight universities (Bergamo, Brescia, Milano Statale, Milano Bicocca, Pisa, Scuola Superiore Sant’Anna, Palermo and Pavia). The usual methodological approach to text analysis allowed us to categorize open-ended proposals of PhD courses improvements in 8 Italian Universities. |
| first_indexed | 2024-12-11T02:52:49Z |
| format | Article |
| id | doaj.art-a6d6ef189428458c84ff0f26acd55f1b |
| institution | Directory Open Access Journal |
| issn | 0390-590X 1973-2201 |
| language | English |
| last_indexed | 2024-12-11T02:52:49Z |
| publishDate | 2014-10-01 |
| publisher | University of Bologna |
| record_format | Article |
| series | Statistica |
| spelling | doaj.art-a6d6ef189428458c84ff0f26acd55f1b2022-12-22T01:23:15ZengUniversity of BolognaStatistica0390-590X1973-22012014-10-0173446347510.6092/issn.1973-2201/45004131Models of text mining to measure improvements to doctoral courses suggested by “STELLA” phd survey respondentsPasquale Pavone0Maria Francesca Romano1Scuola Superiore Sant’Anna, PisaScuola Superiore Sant’Anna, PisaWe present Text Mining models to thematically categorise and measure the suggestions of PhD holders on improving PhD programmes in the STELLA survey (Statistiche in TEma di Laureati e LAvoro). The coded responses questionnaire, designed to evaluate the employment opportunities of students and assess their learning experience, included open-ended questions on how to improve PhD programmes. The Corpus analysed was taken from the data of Italian PhD holders between 2005 and 2009 in eight universities (Bergamo, Brescia, Milano Statale, Milano Bicocca, Pisa, Scuola Superiore Sant’Anna, Palermo and Pavia). The usual methodological approach to text analysis allowed us to categorize open-ended proposals of PhD courses improvements in 8 Italian Universities.http://rivista-statistica.unibo.it/article/view/4500textual analysisautomatic classificationmulti-class categorisationTF IDFassessment of the learning experience |
| spellingShingle | Pasquale Pavone Maria Francesca Romano Models of text mining to measure improvements to doctoral courses suggested by “STELLA” phd survey respondents Statistica textual analysis automatic classification multi-class categorisation TF IDF assessment of the learning experience |
| title | Models of text mining to measure improvements to doctoral courses suggested by “STELLA” phd survey respondents |
| title_full | Models of text mining to measure improvements to doctoral courses suggested by “STELLA” phd survey respondents |
| title_fullStr | Models of text mining to measure improvements to doctoral courses suggested by “STELLA” phd survey respondents |
| title_full_unstemmed | Models of text mining to measure improvements to doctoral courses suggested by “STELLA” phd survey respondents |
| title_short | Models of text mining to measure improvements to doctoral courses suggested by “STELLA” phd survey respondents |
| title_sort | models of text mining to measure improvements to doctoral courses suggested by stella phd survey respondents |
| topic | textual analysis automatic classification multi-class categorisation TF IDF assessment of the learning experience |
| url | http://rivista-statistica.unibo.it/article/view/4500 |
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