Beliefs and needs of academic teachers: a latent class analysis

Silvia Bacci (), Bruno Bertaccini and Alessandra Petrucci
Additional contact information
Silvia Bacci: Florence Center for Data Science, Università degli Studi di Firenze
Bruno Bertaccini: Florence Center for Data Science, Università degli Studi di Firenze
Alessandra Petrucci: Florence Center for Data Science, Università degli Studi di Firenze

Statistical Methods & Applications, 2020, vol. 29, issue 3, No 8, 597-617

Abstract: 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.

Keywords: Graded response model; Higher education; Item response theory; Latent class analysis; Multidimensionality (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10260-019-00495-5 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:stmapp:v:29:y:2020:i:3:d:10.1007_s10260-019-00495-5

Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10260/PS2

DOI: 10.1007/s10260-019-00495-5

Access Statistics for this article

Statistical Methods & Applications is currently edited by Tommaso Proietti

More articles in Statistical Methods & Applications from Springer, Società Italiana di Statistica
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().