| Summary: | Pedagogical agent is a software agent that provides guidance, feedback, or intervention to learners in digital environments. It has the potential to address issues in computer-based learning, particularly online learning, which often neglects affective aspects, such as the emotions of its users. Most systematic literature reviews (SLR) on pedagogical agent have focused on their visual design, types of feedback, and other empirical elements. However, what underlies these agents’ ability to provide interventions personalized to learner’s emotions has not been examined. So, this SLR explores how pedagogical agent has addressed learner’s emotional needs. The study’s research questions include: 1) To what extent does research exist on models, frameworks, or architectures for pedagogical agent, especially those related to emotions? 2) How are pedagogical agent represented, what types of interventions do they use, and how do they affect learner’s emotions? 3) What kinds of inputs are used to activate the pedagogical agent’s functions? This SLR applied the Kitchenham method to select reference sources from 2013 to 2023 and was indexed by Scopus in the Q1 to Q4 range. Our review revealed the absence of a specific model for mapping out interventions tailored to the learner’s emotional needs. Most existing pedagogical agent provide learning interventions that are less adaptive and personalized based on the learner’s emotional state and are applied to asynchronous learning systems such as e-learning. There are still very few pedagogical agents that use real-time input technology by utilizing artificial intelligence to recognize learner’s emotion to trigger an adaptive and personalized intervention.
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