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Published Version (Advanced Access)CC BY-NC-ND V4.0, Open Access
Journal article
Teaching assistants’ experiences navigating first-year statistics
International Journal of Mathematical Education in Science and Technology, Vol.Advanced access
2025
Appears in UniSC Supported Open Access Outputs
Abstract
Teaching assistants (TAs) are often used in higher education to deliver content in large courses, but TAs’ experiences are poorly understood. For some large courses, such as foundation statistics, different universities have different profiles from which to draw the TAs, depending on whether the universities offer graduate programmes aligned with those courses. In this paper, we compare the experiences of TAs who teach foundation statistics at two universities; some TAs have a strong discipline-specific and online-teaching background, while other have less background in content and online teaching but a strong teaching background. The TAs' experiences are compared for teaching specific topics, and for face-to-face and online teaching. While we found different experiences and challenges for the different TAs, TAs at both universities reported online teaching as more challenging and less effective than face-to-face teaching. Training or mentoring TAs is suggested, but in different areas for the different TAs (though all would benefit from assistance with online teaching). The TAs state that mentoring from experienced TAs is effective for navigating the teaching of first-year statistics. However, challenges with training and mentoring TAs are identified.
Details
- Title
- Teaching assistants’ experiences navigating first-year statistics
- Authors
- Peter K Dunn (Corresponding Author) - University of the Sunshine Coast, Queensland, School of Science, Technology and EngineeringTaryn Axelsen - University of Southern Queensland
- Publication details
- International Journal of Mathematical Education in Science and Technology, Vol.Advanced access
- Publisher
- Taylor & Francis
- DOI
- 10.1080/0020739X.2025.2563125
- ISSN
- 1464-5211; 0020-739X
- Copyright note
- © 2025 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.
- Data Availability
- Data are not available due to ethics requirements.
- Organisation Unit
- School of Science, Technology and Engineering
- Language
- English
- Record Identifier
- 991183643902621
- Output Type
- Journal article
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