Bibliographic Details
| Title: |
Pre-service teachers as readers: moving beyond reading frequency as a marker of engagement. |
| Authors: |
Cremin, Teresa1 (AUTHOR) teresa.cremin@open.ac.uk, Mukherjee, Sarah Jane1 (AUTHOR) sarahjane.mukherjee@open.ac.uk, Bearne, Eve2 (AUTHOR) eve.bearne@btinternet.com, Therova, Dana3 (AUTHOR) dt942@bath.ac.uk |
| Source: |
Australian Journal of Language & Literacy. Dec2025, Vol. 48 Issue 3, p229-247. 19p. |
| Subject Terms: |
*Engaged reading, *Reading, *Student teachers, *Role models, *Qualitative research, *Literacy |
| Abstract: |
In the light of an international decline in children and young people choosing to read, it is important that pre-service teachers are supported to become reading role models who can authentically share their passion and pleasure in reading. Yet studies indicate pre-service teachers are neither keen or confident readers, and if they read infrequently, they are deemed by researchers to be unenthusiastic and disengaged. In this study of pre-service teachers from three English universities, the data revealed that contrary to some commentators' views, those who read infrequently were positively disposed towards reading, they saw themselves as readers and enjoyed reading. By employing three different analytical approaches: quantitative survey data, corpus linguistics methods to open-up survey responses, and 'reading life-story' vignettes, a more nuanced understanding of these readers who rarely read but still value the activity, was developed. Barriers encountered by the pre-service teachers are examined, and potential ways forward offered, including eschewing over-reliance on reading frequency as the dominant method to discern pre-service teachers' attitudes to and pleasure in reading. [ABSTRACT FROM AUTHOR] |
|
Copyright of Australian Journal of Language & Literacy is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Database: |
Education Research Complete |