Computer-based classification of preservice physics teachers’ written reflections
- Reflecting in written form on one's teaching enactments has been considered a facilitator for teachers' professional growth in university-based preservice teacher education. Writing a structured reflection can be facilitated through external feedback. However, researchers noted that feedback in preservice teacher education often relies on holistic, rather than more content-based, analytic feedback because educators oftentimes lack resources (e.g., time) to provide more analytic feedback. To overcome this impediment to feedback for written reflection, advances in computer technology can be of use. Hence, this study sought to utilize techniques of natural language processing and machine learning to train a computer-based classifier that classifies preservice physics teachers' written reflections on their teaching enactments in a German university teacher education program. To do so, a reflection model was adapted to physics education. It was then tested to what extent the computer-based classifier could accurately classify the elementsReflecting in written form on one's teaching enactments has been considered a facilitator for teachers' professional growth in university-based preservice teacher education. Writing a structured reflection can be facilitated through external feedback. However, researchers noted that feedback in preservice teacher education often relies on holistic, rather than more content-based, analytic feedback because educators oftentimes lack resources (e.g., time) to provide more analytic feedback. To overcome this impediment to feedback for written reflection, advances in computer technology can be of use. Hence, this study sought to utilize techniques of natural language processing and machine learning to train a computer-based classifier that classifies preservice physics teachers' written reflections on their teaching enactments in a German university teacher education program. To do so, a reflection model was adapted to physics education. It was then tested to what extent the computer-based classifier could accurately classify the elements of the reflection model in segments of preservice physics teachers' written reflections. Multinomial logistic regression using word count as a predictor was found to yield acceptable average human-computer agreement (F1-score on held-out test dataset of 0.56) so that it might fuel further development towards an automated feedback tool that supplements existing holistic feedback for written reflections with data-based, analytic feedback.…
Author details: | Peter WulffORCiD, David BuschhüterORCiDGND, Andrea WestphalORCiDGND, Anna NowakORCiDGND, Lisa Becker, Hugo Robalino, Manfred StedeORCiDGND, Andreas BorowskiORCiDGND |
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DOI: | https://doi.org/10.1007/s10956-020-09865-1 |
ISSN: | 1059-0145 |
ISSN: | 1573-1839 |
Title of parent work (English): | Journal of science education and technology |
Publisher: | Springer |
Place of publishing: | Dordrecht |
Publication type: | Article |
Language: | English |
Date of first publication: | 2020/10/08 |
Publication year: | 2020 |
Release date: | 2022/11/30 |
Tag: | hatural language; machine learning; processing; reflection; teacher professional development |
Volume: | 30 |
Issue: | 1 |
Number of pages: | 15 |
First page: | 1 |
Last Page: | 15 |
Funding institution: | transnational E-RARE grant `CCMCURE (DFG)European Commission [SFB958]; E-RARE [ERL 138397]; Canadian; Institutes for Health ResearchCanadian Institutes of Health Research; (CIHR) [PJT 153000]; the E-RARE grant `CCMCURE |
Organizational units: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Physik und Astronomie |
Humanwissenschaftliche Fakultät / Strukturbereich Kognitionswissenschaften / Department Linguistik | |
Humanwissenschaftliche Fakultät / Strukturbereich Bildungswissenschaften / Department Erziehungswissenschaft | |
DDC classification: | 3 Sozialwissenschaften / 37 Bildung und Erziehung / 370 Bildung und Erziehung |
5 Naturwissenschaften und Mathematik / 50 Naturwissenschaften / 500 Naturwissenschaften und Mathematik | |
Peer review: | Referiert |
Publishing method: | Open Access / Hybrid Open-Access |
License (German): | CC-BY - Namensnennung 4.0 International |