Prodotti della ricerca

 

Articoli su rivista

  1. Barbieri B., Sulis I., Porcu M. & Toland M.D. (2019). Italian Teachers’ Well-Being Within the High School Context: Evidence From a Large Scale Survey. Frontiers in Psychology. (ISSN: 1664-1078). doi: 10.3389/fpsyg.2019.01926.
  2. Sulis I., Giambona F., & Porcu M. (2019). Adjusted indicators of quality and equity for monitoring the education systems over time. Insights on EU15 countries from PISA survey. Socio-Economic Planning Sciences. doi: 10.1016/j.seps.2019.05.005.
  3. Sulis I., Porcu M., & Capursi V. (2018) On the use of student evaluation of teaching. A longitudinal analysis combining measurement issues and implications of the exercise.  Social Indicators Research. doi: 10.1007/s11205-018-1946-8.
  4. Barbieri, B., Farnese, M. L., Sulis, I., Dal Corso, L., & De Carlo, A. (2018) One Perception, two perspectives: measuring psychological contract dimensionality through the psychological contract content questionnaire. Testing, Psychometrics, Methodology in Applied Psychology. 25 (1), 21-47. (ISSN: 1972-6325). doi: 10.4473/TPM25.1.2.
  5. Sulis I. & Porcu M. (2017). Handling Missing Data in Item Response Theory. Assessing the Accuracy of a Multiple Imputation Procedure Based on Latent Class Analysis. Journal of Classification. 34 (2), 327–359. (ISSN: 0176-4268). doi:10.1007/s00357-017-9220-3.
  6. Toland, M. D., Sulis, I., Giambona, F., Porcu, M., & Campbell, J. M. (2017). Introduction to bifactor polytomous item response theory analysis. Journal of School Psychology. 60, 41-63. (ISSN: 0022-4405). doi:10.1016/j.jsp.2016.11.001.
  7. La Rocca M., Parrella L., Primerano I., Sulis I. & Vitale M.P. (2017). An integrated strategy for the analysis of student evaluation of teaching: from descriptive measures to explanatory models. Quality & Quantity. 51 (2), 675-691. (ISSN: 0033-5177). doi: 10.1007/s11135-016-0432-0.
  8. Giambona F., Porcu M. & Sulis I. (2017). Students mobility: assessing the determinants of attractiveness across competing territorial areas. Social Indicators Research. 133(3), 1105–1132 (ISSN: 0303-8300). doi: 10.1007/s11205-016-1407-1.
  9. Giambona, F., Pitzalis, M., Porcu, M., & Sulis, I. (2016). Measuring Digital Teaching Innovation Using Item Response Theory Models. Italian Journal of Sociology of Education, 8 (2), 68-109. (ISSN 2035-4983). doi: 10.14658/pupj-ijse-2016-2-5.
  10. Sulis & Toland M. D. (2017). Introduction to Multilevel Item Response Theory Analysis: Descriptive and Explanatory Models. The Journal of Early Adolescence. 37 (1), 85-128. (ISSN: 0272-4316). doi: 10.1177/0272431616642328.
  11. Sulis & Porcu M (2015). Assessing Divergences in Mathematics and Reading Achievement in Italian Primary Schools: A proposal of adjusted indicators of school effectiveness. Social Indicators Research, 122 (2), p. 607-635 (ISSN: 0303-8300). doi: 10.1007/s11205-014-0701-z.
  12. Giambona F., Porcu M. & Sulis (2014). Does Education affect individual well-being? Some Italian Empirical evidences.  Open Journal of Statistics, 4 (5), p. 319-329 (ISSN: 2161-718X). doi: 10.4236/ojs.2014.45032.
  13. Sulis & Capursi V. (2013). Building up adjusted indicators of students’ evaluation of university courses using generalized item response models. Journal of Applied Statistics, 40 (1), p. 88-102. (ISSN 0266-4763). doi: 10.1080/02664763.2012.734796.
  14. Sulis & Porcu M. (2012). Comparing degree programs from students’ assessments: A LCRA-based adjusted composite indicator. Statistical Methods & Applications, 21, p. 193-209, (ISSN: 1618-2510). doi: 10.1007/s10260-011-0185-9.
  15. Sulis I. & Tedesco N. (2009). Measures of Quality of Life among University Students. STATISTICA APPLICATA – Italian Journal of Applied Statistics, 21 (3,4), p. 245-264 (ISSN: 1125-1964).

 

 

Capitoli di libri (editori internazionali)

  1. Sulis I., Giambona F., Tedesco N. (2015). Using Discrete-Time Multistate Models to Analyze Students’ University Pathways. In Morlini I., Minerva T., Vichi M. (Eds.), Advances in Statistical Models for Data Analysis, p. 259-268. Springer International Publishing, Switzerland. ISSN: 1431-8814. ISBN 978-3-319-17376-4.
  2. 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. Statistical Models for Data Analysis, p. 279-288. In: Ingrassia S., Giudici P., Rocci R., Vichi M., BERLIN HEIDELBERG: Springer-Verlag . ISBN 978-3-319-00031-2.
  3. Sulis I (2013). A Further Proposal to Perform Multiple Imputation on a Bunch of Polytomous Items Based on Latent Class Analysis. Statistical Models for Data Analysis. In: Ingrassia S., Giudici P., Rocci R., Vichi M., BERLIN HEIDELBERG: Springer-Verlag, p. 361-370. ISBN 978-3-319-00031-2
  4. Sulis I, Tedesco N, Zavarrone E (2011). Scalare la reputazione degli Atenei nella percezione dello studente attraverso la Mokken Scale Analysis. In: CIVARDI M.. Modelli e metodi per valutare la reputazione di strutture formative, vol. 15, p. 135-154, PADOVA:CLEUP, ISBN: 978-88-6129-899-6
  5. Sulis I., Porcu M. (2011). Assessing the Quality of the Management of Degree Programs by Latent Class Analysis. In: ATTANASIO M., CAPURSI E.. Statistical Methods for the Evaluation of University Systems, Contributions to Statistics. p. 161-172, BERLIN HEIDELBERG: Springer-Verlag. ISBN: 978-3-7908-2375-2, doi: 10.1007/978-3-7908-2375-2_11
  6. Sulis I., Porcu M., Tedesco N. (2011). Evaluating lecturer’s capability over time. Some evidence from surveys on university course quality. In: INGRASSIA S., ROCCI R., VICHI M.. New Perspectives in Statistical Modeling and Data Analysis, BERLIN HEIDELBERG: Springer-Verlag . ISBN: 978-3-642-11362-8
  7. Sulis I., Porcu M., Pitzalis M. (2011). Scaling the latent variable cultural capital via Item Response models and Latent Class Analysis. In: FICHET, B., PICCOLO, D., VERDE, R., VICHI, M.. Classification and Multivariate Analysis for Complex Data Structures. p. 269-277, BERLIN HEIDELBERG: Springer-Verlag, ISBN: 978-3-642-13311-4
  8. Sulis I., Porcu M. (2010). A multiple imputation approach in a survey on university teaching evaluation. In: F. PALUMBO, C. N. LAURO, M. J. GREENACRE. Data Analysis and Classification Studies in Classification, Data Analysis and Knowledge Organization. p. 473-482-482, BERLIN HEIDELBERG: Springer-Verlag, ISBN: 978-3-642-03738-2

 Capitoli di libri (editori nazionali)

  1.  La Rocca, M., Parrella M.L., Primerano I., Sulis, Vitale M.P. (2016). L’analisi dell’opinione degli studenti sulla didattica universitaria: potenzialità dei modelli IRT e dei modelli multilivello, in Buono. P, Gallo M, Ragozini G., Reverchon E., Rostirolla P., Il sistema universitario campano tra miti e realtà. Aspetti metodologici, analisi e risultati. Milano: Franco Angeli. ISBN 978-88917-4230-8.
  2. Giambona F., Pitzalis M., Porcu M, Sulis (2015). Insegnanti e innovazione. La scuola sarda e la sfida del digitale. In Calidoni P. and Casula C. (Ed), Education 2.0: esperienze, riflessioni, scenari.CUEC.  ISBN 978-88-8467-946-8.
  3. Pitzalis M., Giambona F., De Feo A., Ghiaccio M.F., Porcu M., Sulis (2015). La rivoluzione digitale nella scuola sarda. Caratteristiche strutturali del sistema, culture professionali, organizzative e didattiche di fronte alla sfida dell’innovazione. CUEC. ISBN:978 -88 -8467- 895 -9.
  4. Sulis, Tedesco N., Zavarrone E. (2011). Scalare la reputazione degli Atenei nella percezione dello studente attraverso la Mokken Scale Analysis. In CIVARDI M. (Ed). Modelli e metodi per valutare la reputazione di strutture formative, vol. 15, p. 135-154. PADOVA: CLEUP, ISBN: 978-88-6129-899-6.

Atti di convegno

  1. Columbu, S., Porcu, M., Primerano, I., Sulis, I., Vitale, M. (2019). Exploring the Italian student mobility flows in higher education. In Statistical Methods for Service Quality Evaluation. Matilde Bini, Pietro Amenta, Antonello D’Ambra, Ida Camminatiello Editors. Book of short papers of IES 2019 Rome, Italy, July 4-5, pag. 46-49, Cuzzolin Editore, Napoli. ISBN: 978-88-86638-65-4.
  2. Columbu, S., Porcu, M., Sulis, I. (2018), `University choice and the attractiveness of the study area. Insights from an analysis based on generalized mixed-effect models.’ In Book of short Papers SIS 2018″. Antonino Abbruzzo, Eugenio Brentari, Marcello Chiodi &Davide Piacentino Publisher: Pearson. Editors (E-book) ISBN-9788891910233.
  3. Sulis I., Giambona F. & Porcu M. (2017). Multivariate mixed models for assessing equity and efficacy in education. An analysis over time using EU15 PISA data. In F. Greselin, F. Mola and Ma. Zenga Editors, CLADAG 2017. Book of Short Papers International Conference of The CLAssification and Data Analysis Group of the Italian Statistical Society, Milano-Bicocca, September 13-15. Universitas Studiorum (E-book).ISBN 978-88-99459-71-0.
  4. Sulis I., Porcu M. (2013) Handling missing data in item response theory. Assessing the accuracy in estimation of two multiple imputation procedures. In V. M. R. Muggeo, V. Capursi, G. Boscaino, and G. Lovison, editors, Proceedings of the 28th International Workshop on Statistical Modelling, vol. 2, Istituto Poligrafico Europeo, Palermo. p. 795-798. ISBN: 978-88-96251-49-2.
  5. Sulis I., Capursi V. (2013) Analyzing SET over time using multilevel multidimensional explanatory Item Response Theory models. In: V. M. R. Muggeo, V. Capursi, G. Boscaino, and G. Lovison, editors, Proceedings of the 28th International Workshop on Statistical Modelling, vol. 2, Istituto Poligrafico Europeo, Palermo. p 789-793. ISBN: 978-88-96251-49-2.
  6. Porcu M, Sulis I. (2013) Detecting differences between primary schools in mathematics and reading achievement by using schools added-value measures of performance. In: T. Minerva, I. Morlini, F. Palumbo, editors, Cladag 2013. Book of Abstract 9th Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society, September 18-20 Modena. p. 389-394. PADOVA: Cleup (ITALY). ISBN:  978-88-67871-17-9
  7. Sulis I., Giambona F., Tedesco N. (2013) Analyzing university students’ careers using Multi-State Models. In: T. Minerva, I. Morlini, F. Palumbo, editors, Cladag 2013. Book of Abstract 9th Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society, September 18-20 Modena. p. 451-453. PADOVA: Cleup (ITALY). ISBN:  978-88-67871-17-9
  8. Porcu M, Sulis I (2012). Comparing degree programs using unadjusted performance indicators. Assessing the bias from the Potential Confounding Factors. In: Società Italiana di Statistica. 46TH SCIENTIFIC MEETING OF THE ITALIAN STATISTICAL SOCIETY. Roma – Sapienza University of Rome, 20-22 giugno 2012, ISBN: 978-88-6129-882-8
  9. Sulis I. (2011). A further proposal to multiple impute missing categorical values using Latent Class Analysis. In: 8th Scientific Meeting of the CLAssification and Data Analysis Group of the Italian Statistical Society. University of Pavia, September 7-9, 2011. Short Papers USB pen, p. 1-4, ISBN: 978-88-906639
  10. Sulis I., Porcu M. (2011). Evaluating the University System Controlling for Potential Confounding Factors. In: 8th Scientific Meeting of the CLAssification and Data Analysis Group of the Italian Statistical Society. University of Pavia, September 7-9, 2011. Short Papers USB pen, p. 1-4, ISBN: 978-88-906639
  11. Porcu M., Sulis I., Tedesco N. (2009), Evaluating lecturer’s capability over time. Some evidence from surveys on university course quality, in Classification and Data Analysis 2009, Book of Short Papers, 7th Meeting of the Classification and Data Analysis Group of the Italian Statistical Society, Catania. 9-11. September 2009. PADOVA: CLEUP (ITALY). ISBN 978-88-6129-406-6
  12. Pitzalis M, Porcu M., Sulis I. (2008). Scaling the Latent Variable Cultural Capital Via Item Response Models and Latent Class Analysis. In: First Joint Meeting of the Société Francophone de Classification and the Classification and Data Analysis Group of the Italian Statistical Society – BOOK OF SHORT PAPERS. SFC – CLADAG 2008. Caserta. 11-13 June 2008. (pp. 393-396). NAPOLI: Edizioni Scientifiche Italiane (ITALY). ISBN/ISSN: 978-88-495-1656-2
  13. Sulis I., Porcu M. (2008). Pointing Out Homogeneous Classes of Students Moving from Assessments of Management of Their Degree Schemes. In: Atti della XLIV Riunione Scientifica. XLIV Riunione Scientifica della Società Italiana di Statistica. Arcavacata di Rende. 25 – 27 giugno 2008. PADOVA: Cleup (ITALY). ISBN/ISSN: 978-88-6129-228-4
  14. Sulis I., Tedesco N. (2008). Quality of Life Among University Students: a Comparison Study Based on Item Response Models. In: Atti della XLIV Riunione Scientifica. XLIV Riunione Scientifica della Società Italiana di Statistica. Arcavacata di Rende. 25-27 giugno 2008. PADOVA: Cleup (ITALY). . ISBN/ISSN: 978-88-6129-228-4
  15. Sulis I., Porcu M. (2007), A multiple imputation approach in a survey on university teaching evaluation, in “Classification and Data Analysis 2007” Meeting of the Classification and Data Analysis Group of the Italian Statistical Society, Macerata 11-12 Settembre 2007, p. 295-298, Macerata, Edizioni Università di Macerata. ISBN: 978-88-6056-020-9
  16. Sulis I. (2007), Measuring students’ assessment on ‘university course quality’ using mixed-effects models, in “Classification and Data Analysis 2007” Meeting of the Classification and Data Analysis Group of the Italian Statistical Society, Macerata 11-12 Settembre 2007, p. 709-712, Macerata, Edizioni Università di Macerata. ISBN: 978-88-6056-020-9
  17. Sulis I., Porcu M. (2007), The evaluation of university teaching. An imputation procedure to recover for missingness, in “Rischio e previsione”, SIS, Atti della riunione intermedia, Venezia 6-8 Giugno 2007, p. 511-512, Padova, CLEUP. ISBN: 978-88-6129-093-8 .

 

Titolo: Multivariate mixed models for assessing equity and efficacy in education. An analysis over time using EU15 PISA data
Autori: 
Data di pubblicazione: 2017
Handle: http://hdl.handle.net/11584/224416
ISBN: 9788899459710
Tipologia:2.1 Contributo in volume (Capitolo o Saggio)

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