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Analyzing learner profiles in a microlearning app for training language learning peer feedback skills

Peer feedback can be described as the act of one learner evaluating the performance of another learner. It has been shown to impact student learning and achievement in language learning contexts positively. It is a skill that can be trained, and there have been calls for research on peer feedback tr...

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Autores principales: Gorham, Tom, Majumdar, Rwitajit, Ogata, Hiroaki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9986660/
http://dx.doi.org/10.1007/s40692-023-00264-0
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author Gorham, Tom
Majumdar, Rwitajit
Ogata, Hiroaki
author_facet Gorham, Tom
Majumdar, Rwitajit
Ogata, Hiroaki
author_sort Gorham, Tom
collection PubMed
description Peer feedback can be described as the act of one learner evaluating the performance of another learner. It has been shown to impact student learning and achievement in language learning contexts positively. It is a skill that can be trained, and there have been calls for research on peer feedback training. Mobile microlearning is a type of technology-enhanced learning which is notable for its short duration and flexibility in the time and place of learning. This study aims to evaluate how an asynchronous microlearning app might improve students’ skills for providing peer feedback on spoken content in the context of English as a foreign language (EFL) education. This study used convenience sampling and a quasi-experimental single-group pre-/post- research design. Japanese university students (n = 87) in an EFL course used the Pebasco asynchronous microlearning app to practice peer feedback skills. The students’ app usage data were used to identify five behavioral profiles. The pattern of profile migration over the course of using Pebasco indicates that many participants improved or maintained desirable patterns of behavior and outcomes, suggesting a positive impact on the quality of peer feedback skills and second-language (L2) skills, as well as the ability to detect L2 errors. The findings also suggest improvements that can be made in future design iterations. This research is novel because of a current lack of research on the use of no-code technology to develop educational apps, particularly in the context of microlearning for improving peer feedback skills in EFL.
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spelling pubmed-99866602023-03-06 Analyzing learner profiles in a microlearning app for training language learning peer feedback skills Gorham, Tom Majumdar, Rwitajit Ogata, Hiroaki J. Comput. Educ. Article Peer feedback can be described as the act of one learner evaluating the performance of another learner. It has been shown to impact student learning and achievement in language learning contexts positively. It is a skill that can be trained, and there have been calls for research on peer feedback training. Mobile microlearning is a type of technology-enhanced learning which is notable for its short duration and flexibility in the time and place of learning. This study aims to evaluate how an asynchronous microlearning app might improve students’ skills for providing peer feedback on spoken content in the context of English as a foreign language (EFL) education. This study used convenience sampling and a quasi-experimental single-group pre-/post- research design. Japanese university students (n = 87) in an EFL course used the Pebasco asynchronous microlearning app to practice peer feedback skills. The students’ app usage data were used to identify five behavioral profiles. The pattern of profile migration over the course of using Pebasco indicates that many participants improved or maintained desirable patterns of behavior and outcomes, suggesting a positive impact on the quality of peer feedback skills and second-language (L2) skills, as well as the ability to detect L2 errors. The findings also suggest improvements that can be made in future design iterations. This research is novel because of a current lack of research on the use of no-code technology to develop educational apps, particularly in the context of microlearning for improving peer feedback skills in EFL. Springer Berlin Heidelberg 2023-03-06 /pmc/articles/PMC9986660/ http://dx.doi.org/10.1007/s40692-023-00264-0 Text en © Beijing Normal University 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Gorham, Tom
Majumdar, Rwitajit
Ogata, Hiroaki
Analyzing learner profiles in a microlearning app for training language learning peer feedback skills
title Analyzing learner profiles in a microlearning app for training language learning peer feedback skills
title_full Analyzing learner profiles in a microlearning app for training language learning peer feedback skills
title_fullStr Analyzing learner profiles in a microlearning app for training language learning peer feedback skills
title_full_unstemmed Analyzing learner profiles in a microlearning app for training language learning peer feedback skills
title_short Analyzing learner profiles in a microlearning app for training language learning peer feedback skills
title_sort analyzing learner profiles in a microlearning app for training language learning peer feedback skills
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9986660/
http://dx.doi.org/10.1007/s40692-023-00264-0
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