Previous research on student processing of empathic chatbot feedback has been limited, often neglecting learning performance and its impact on student’s motivation, self-regulation, and metacognitive reasoning. The objective was to analyze the effectiveness of empathic feedback, cognitive and affective, on these four issues in online learning, specifically, in the practical assignments of the Distributed Systems course. The data originated from the students whose syllabus is related to developing computer competencies after receiving feedback from the human teacher and empathic chatbot (empathic pedagogical conversational agent). The course was Distributed Systems of the Computer Engineering and Telecommunications Technology Degree at Universitat Oberta de Catalunya. Several instruments (e.g., tests, questionnaires, etc.) were used to collect quantitative data on students' learning performance, student processing of feedback, human teacher and empathic chatbot feedback, student perceptions of that feedback, etc. A test was used to collect quantitative data on students’ learning performance in each Practical Assignment phase in the Distributed Systems course. In addition, a questionnaire was used to collect quantitative data on student feedback processing, human teacher and empathic chatbot feedback, and student perceptions of that feedback. The total number of participants is 196.

This work was supported by the Universitat Oberta de Catalunya [Doctoral theses in Education and ICT (e-learning) - 2022/2023]