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Journal article
Collaborative augmentation and simplification of text (CoAST): pedagogical applications of natural language processing in digital learning environments
Learning environments research, Vol.25(2), pp.399-421
07/2022
Appears in Recent Faculty of Education Publications
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Abstract
The digitisation of higher education is raising significant questions about the impact of artificial intelligence and automation on teaching and learning environments, highlighting the need to investigate how teachers and students can work with new educational technologies in complementary ways. This paper reports results from a pilot study of the collaborative augmentation and simplification of text (CoAST) system, which is online software designed to facilitate the engagement of university students with theoretically-sophisticated academic texts. CoAST offers a digital learning interface that uses natural language processing algorithms to identify words that can be difficult to understand for readers at different ability levels. Course lecturers use their pedagogical content knowledge to add brief annotations to identified words. The software was trialed using a quasi-experimental design with (1) 23 undergraduate Education Studies students and (2) 23 digital and technology solutions students. Results suggest that CoAST offers a digital learning environment that can effectively mediate and enhance pedagogical relationships between teachers, students, and complex theoretical texts.
Details
- Title
- Collaborative augmentation and simplification of text (CoAST): pedagogical applications of natural language processing in digital learning environments
- Creators
- Matthew Shardlow - Manchester Metropolitan UniversitySam Sellar - Manchester Metropolitan UniversityDavid Rousell - [RMIT, Melbourne, Australia]
- Publication Details
- Learning environments research, Vol.25(2), pp.399-421
- Publisher
- Springer Nature B.V.
- Number of pages
- 23
- Grant note
- Centre for Excellence in Teaching and Learning at Manchester Metropolitan University
- Identifiers
- 991013054783002368
- Copyright
- © Crown 2021. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
- Academic Unit
- Faculty of Education
- Language
- English
- Resource Type
- Journal article