Designing Learning Technology Collaboratively: Analysis of a Chatbot Co-Design

Autor/inn/en	Durall Gazulla, Eva; Martins, Ludmila; Fernández-Ferrer, Maite
Titel	Designing Learning Technology Collaboratively: Analysis of a Chatbot Co-Design
Quelle	In: Education and Information Technologies, 28 (2023) 1, S.109-134 (26 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Durall Gazulla, Eva)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1360-2357
DOI	10.1007/s10639-022-11162-w
Schlagwörter	Instructional Design; Cooperation; Educational Technology; Artificial Intelligence; Computer Interfaces; Decision Making; Best Practices; Electronic Learning + Suchen Sie Ihr Suchwort? Lesson concept; Lessonplan; Unterrichtsentwurf; Co-operation; Kooperation; Unterrichtsmedien; Künstliche Intelligenz; Decision-making; Entscheidungsfindung
Abstract	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. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01