Designing learning technology collaboratively: Analysis of a chatbot co-design

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.

Analysing Conversation Pathways with a Chatbot Tutor to Enhance Self-Regulation in Higher Education

“…The EDUguia chatbot was designed following a collaborative design methodology [10] through carrying out co-design workshops with higher education students and teachers. During these workshops, a clear requirement from the students was that the tool was to be totally anonymous, that is, that it should not require identifiers to log in and that the information it collected should not allow users to be identified.…”

“…A complex task can be defined as one that involves the activation of knowledge, the management of different types of disciplinary content, and the execution of different competencies [9]. Considering that chatbots are still an emerging technology in educational contexts [10], particularly ones aimed at enhancing the self-regulation learning skills, the work reported in this paper intends to contribute to the understanding of students' interactions with chatbots during their learning process.…”

Investigating the Support Provided by Chatbots to Educational Institutions and Their Students: A Systematic Literature Review

“…Yildiz Durak [57] observed that students' perceived course satisfaction is connected with the satisfaction of using the ECA and that the satisfaction of using the ECA is connected with students' engagement in the course. Additionally, the results in the study of Durall Gazulla et al [58] showed that when the students are included in the development process, they feel the need to express their opinion in order to modify the educational matter and adapt it to their needs. Moreover, Belda-Medina and Calvo-Ferrer [52] observed that students were concerned about the privacy of their data.…”

Artificial Intelligence in Education: Literature Review on The Role of Conversational Agents in Improving Learning Experience

“…The term "artificial intelligence" (AI) refers to the capacity of a computer or non-human machine to do activities that would typically require the intellect of a human being (Durall et al, 2023). These activities include learning, problem-solving, decision-making, and many more.…”

“…The capacity of AI to customize a student's educational experience is one of the most significant benefits that it brings to the field of education. Students now have access to educational resources in record time and with greater efficiency than ever before because of advancements in artificial intelligence (AI) technology such as natural language processing, deep learning, and machine learning (Durall Gazulla et al, 2023). Students are able to study at their own pace and in the manner that best suits them because of AI's ability to generate personalized learning paths and deliver customized feedback.…”