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Affect is at the core of learning experiences, and is described as a mood, feeling, or emotion. Represented by cognitive structures in the mind, affect transmits information about the world we experience, compelling us to act and make decisions. Studies find that a learner’s inability (or ability) to regulate the affect they experience (e.g., confusion or frustration) greatly impacts their ability to engage in learning with emerging technologies (e.g., intelligent tutoring systems, game-based learning environments, MOOCs, virtual reality). Yet only a handful of papers over the last few years have focused on the role of affect across learning analytics and educational data mining communities.

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In the "Situating Affect in Learning Analytics: Addressing Educational Challenges" workshop, which is part of the LAK 2023 conference, we will bring together leading interdisciplinary research groups from the fields of affective sciences and affective computing, multimodal learning analytics, neuroscience, data science, education, learning sciences, psychology, and cognitive science to discuss current challenges and new directions to unlock the full potential of leveraging links between affect and learning analytics to augment education for diverse learners.