Humboldt-Universität zu Berlin - Mathematisch-Naturwissenschaftliche Fakultät - Institut für Informatik

PhD topic presentation: Hae Seon Yun

“Multimodal Learning Companions”
  • Wann 04.07.2023 ab 13:15 Uhr
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The effects of pedagogical agents have been widely researched in Intelligent Tutoring System to promote learners’ motivation and learning performance. Among various types and roles of pedagogical agents, learning companions emphasize relational interaction with learners by focusing on providing more agency on learners’ competency.

To design learning companions that support learners, learners’ cognitive and emotional states should be understood. However, previous research mainly focused on analyzing learners’ online activities and self-reported data to relate to their learning performance. As emotion plays an important role maintaining a positive learning experience and physiological data such as electrodermal activity (EDA) and facial expression can provide insights into learners’ emotional states, these data should be explored as input sources when designing a learning companion.With respect to interaction between human and learning companions, current studies focus primarily on a screen-based design utilizing visual feedback, yet learning companions can be designed in various forms such as in humanoid and non-humanoid robots to provide different modality of feedback. 

Therefore, by adhering to the logic of design research, the dissertation aims to investigate 1) how physiological and mobile sensor data can be utilized to indicate learning states in the design of multimodal learning companions, 2) how screen based and robotic learning companions can be designed to interact with users and 3) how non-programmers can be supported in designing their own scenario on robotic multimodal learning companions. 

Each research question is answered by describing the background and aims of research projects, theoretical and practical design ideas & considerations, interdisciplinary development and implementation processes, evaluation using mixed methods and interpretations of the findings by reflecting on theoretical grounds.