Abstract
In the last few years, academic guidance services of the Italian universities have been increasingly involved in planning and organising training courses for academic teachers to improve the quality of teaching. In such a context, it is important to collect information on the teachers’ opinions about their belief on traditional and innovative approaches to teaching and learning evaluation as well as on their need of support to take effective teaching practices. In this contribution we aim at studying the structure of academic teachers’ population of an Italian university in order to detect groups of teachers that are homogenous in terms of beliefs and needs. As beliefs and needs may be conceptualised in terms of an unobservable (or latent) variable composed of multiple traits related with different aspects of beliefs and needs (e.g., passion for teaching, beliefs about teaching methods, ...), the proposed analysis is based on a multidimensional Latent Class Item Response Theory model. This type of model allows us to classify teachers in latent classes with respect to their beliefs and needs in the academic didactic activities. Moreover, it also allows us to identify specific aspects of teaching with respect to which academic teachers tend to disagree/agree, and to relate beliefs and needs of teachers with their individual characteristics. The study involves a sample of academic teachers coming from the University of Florence (IT) that took part in a survey based on a new questionnaire composed of Likert-type items concerning beliefs and needs on several aspects of teaching.
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Notes
For further details on this project see http://paduaresearch.cab.unipd.it/7397/.
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Acknowledgements
The authors are grateful to the University of Florence and to the local referent of the PRODID project, Prof. Giovanna Del Gobbo, for making the data available. The authors also acknowledge the financial support provided by the “Dipartimenti Eccellenti 2018-2022” ministerial funds.
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Bacci, S., Bertaccini, B. & Petrucci, A. Beliefs and needs of academic teachers: a latent class analysis. Stat Methods Appl 29, 597–617 (2020). https://doi.org/10.1007/s10260-019-00495-5
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DOI: https://doi.org/10.1007/s10260-019-00495-5