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Designing learning technology collaboratively: Analysis of a chatbot co-design
Collaborative design approaches have been increasingly adopted in the design of learning technologies since they contribute to develop pedagogically inclusive and appropriate learning designs. Despite the positive reception of collaborative design strategies in technology-enhanced learning, little a...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9226288/ https://www.ncbi.nlm.nih.gov/pubmed/35765268 http://dx.doi.org/10.1007/s10639-022-11162-w |
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author | Durall Gazulla, Eva Martins, Ludmila Fernández-Ferrer, Maite |
author_facet | Durall Gazulla, Eva Martins, Ludmila Fernández-Ferrer, Maite |
author_sort | Durall Gazulla, Eva |
collection | PubMed |
description | Collaborative design approaches have been increasingly adopted in the design of learning technologies since they contribute to develop pedagogically inclusive and appropriate learning designs. Despite the positive reception of collaborative design strategies in technology-enhanced learning, little attention has been dedicated to analyzing the challenges faced in design processes using a collaborative approach. In this paper, we disclose the collaborative design of a chatbot for self-regulated learning in higher education using an action research approach. We analyze the design process of EDUguia chatbot, which includes diverse evidence from questionnaires and workshops with students and lecturers, as well as intermediary design objects. Based on the qualitative analysis, we identify several challenges that are transversal to the co-design work, as well as specific to the design phases. We critically reflect on the strategies deployed to overcome these challenges and how they relate to decision-making processes, highlighting the need to make stakeholders’ tacit knowledge explicit, cultivate trust-building and support democratic decision-making in technology design processes. We believe that the recommendations we present in this paper contribute to developing best practices in the collaborative design of chatbots for the self-regulation of learning, as well as learning technology in general. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10639-022-11162-w. |
format | Online Article Text |
id | pubmed-9226288 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-92262882022-06-24 Designing learning technology collaboratively: Analysis of a chatbot co-design Durall Gazulla, Eva Martins, Ludmila Fernández-Ferrer, Maite Educ Inf Technol (Dordr) Article Collaborative design approaches have been increasingly adopted in the design of learning technologies since they contribute to develop pedagogically inclusive and appropriate learning designs. Despite the positive reception of collaborative design strategies in technology-enhanced learning, little attention has been dedicated to analyzing the challenges faced in design processes using a collaborative approach. In this paper, we disclose the collaborative design of a chatbot for self-regulated learning in higher education using an action research approach. We analyze the design process of EDUguia chatbot, which includes diverse evidence from questionnaires and workshops with students and lecturers, as well as intermediary design objects. Based on the qualitative analysis, we identify several challenges that are transversal to the co-design work, as well as specific to the design phases. We critically reflect on the strategies deployed to overcome these challenges and how they relate to decision-making processes, highlighting the need to make stakeholders’ tacit knowledge explicit, cultivate trust-building and support democratic decision-making in technology design processes. We believe that the recommendations we present in this paper contribute to developing best practices in the collaborative design of chatbots for the self-regulation of learning, as well as learning technology in general. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10639-022-11162-w. Springer US 2022-06-24 2023 /pmc/articles/PMC9226288/ /pubmed/35765268 http://dx.doi.org/10.1007/s10639-022-11162-w Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Durall Gazulla, Eva Martins, Ludmila Fernández-Ferrer, Maite Designing learning technology collaboratively: Analysis of a chatbot co-design |
title | Designing learning technology collaboratively: Analysis of a chatbot co-design |
title_full | Designing learning technology collaboratively: Analysis of a chatbot co-design |
title_fullStr | Designing learning technology collaboratively: Analysis of a chatbot co-design |
title_full_unstemmed | Designing learning technology collaboratively: Analysis of a chatbot co-design |
title_short | Designing learning technology collaboratively: Analysis of a chatbot co-design |
title_sort | designing learning technology collaboratively: analysis of a chatbot co-design |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9226288/ https://www.ncbi.nlm.nih.gov/pubmed/35765268 http://dx.doi.org/10.1007/s10639-022-11162-w |
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