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.

This article analyses a practice of formative peer-assessment based on an experience in university teaching innovation. From a review of the literature on feedback for self-regulation, the traits of formative assessment practices are determined and a task and the assessment criteria are designed in a consistent way with these traits. After the application of the experience, the results are discussed in terms of students’ involvement; activity performance of said experience and of the whole subject; motivation and self-perception of learning and of the competency-based development of the students. The results show positive effects on the involvement, motivation and learning perception but not on performance improvement, suggesting that future research should address the effects of self-regulating feedback on the estimated learning from objective measurements and should expand the studies of the effects of these practices on the immediate and future self-regulating capacity.

Chatbots can have a significant positive impact on learning. There is a growing interest in their application in teaching and learning. The self-regulation of learning is fundamental for the development of lifelong learning skills, and for this reason, education should contribute to its development. In this sense, the potential of chatbot technologies for supporting students to self-regulate their learning activity has already been pointed out. The objective of this work is to explore university students’ interactions with EDUguia chatbot to understand whether there are patterns of use linked to phases of self-regulated learning and academic task completion. This study presents an analysis of conversation pathways with a chatbot tutor to enhance self-regulation skills in higher education. Some relevant findings on the length, duration, and endpoints of the conversations are shared. In addition, patterns in these pathways and users’ interactions with the tool are analysed. Some findings are relevant to the analysis of the link between design and user experience, but they can also be related to implementation decisions. The findings presented could contribute to the work of other educators, designers, and developers interested in developing a tool addressing this goal.

The proliferation of Massive Open Online Courses (MOOCs) in recent years has generated much debate. MOOCs have been presented as technology-based educational practices, but many researchers question if this kind of open courses really respects some of the consolidated principles behind the education offered at universities. In light of this situation, consulting the teachers most closely tied to this type of course can provide an authoritative view of the issue and can allow the most important elements to be highlighted in order to carry out further research. Using a qualitative methodology based on an open questionnaire, this work presents the opinions and perceptions of teachers/lecturers in educational technology regarding these new courses key elements. These key elements are analysed through analysing its controversial definition, their pedagogical advantages and limitations, the functions of a tutor in a MOOC and their assessment (or accreditation). In addition, a comparison is made between the contributions of teachers from a traditional university with a face-to-face model and those from a distance university, which is based entirely on a virtual training offer and which has a greater possibility of coming into direct competition with these Massive Open Online Courses.

This research presents how the adoption of self-regulation strategies using peer feedback and chatbots promotes the transformation of online assessment. The evaluation of the design of a learning activity that integrates a peer feedback intervention to suggest improvements in academic essay writing is described. Based on a design-based research approach, three main phases are established, a first one for the design of the proposal and two consecutive implementations. In the first, a satisfaction questionnaire was distributed to 348 students and the analysis of the responses was used to redesign the proposal. In the second implementation, a questionnaire was used with 24 students and a group interview with the faculty. The results allowed a positive assessment of the relationship between peer feedback and the development of self-regulation and learning to learn competencies. Finally, it is concluded that it is necessary to propose more often strategies of this type that also include the use of AI, thus giving more opportunities to students in the development of their autonomy and a conscious and efficient management of their learning process, so this article also presents a design proposal for a new iteration with AI. Esta investigación presenta cómo a partir de la adopción de estrategias de autorregulación utilizando el feedback entre pares y los chatbots se promueve la transformación de la evaluación en línea. Se describe la evaluación del diseño de una actividad de aprendizaje que integra una intervención de feedback entre pares para sugerir mejoras en la elaboración de ensayos académicos. A partir de un enfoque de investigación basado en el diseño se establecen tres fases principales, una primera de diseño de la propuesta y dos implementaciones consecutivas. En la primera se distribuyó un cuestionario de satisfacción a 348 estudiantes y el análisis de las respuestas se utilizó para el rediseño de la propuesta. En la segunda implementación, se utilizó un cuestionario con 24 estudiantes y una entrevista grupal al profesorado. Los resultados permitieron valorar positivamente la relación entre el feedback por pares, y el desarrollo de las competencias de autorregulación y de aprender a aprender. Finalmente, se concluye que es necesario proponer más a menudo estrategias de este tipo y que incluyan además el uso de la IA, dando así más oportunidades al estudiantado en el desarrollo de su autonomía y una gestión consciente y eficiente de su proceso aprendizaje, por lo que en este artículo se presenta también una propuesta de diseño para una nueva iteración con IA.