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Auflistung nach Autor:in "Yun, Haeseon"

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  • Conference Paper 
    Code of Practice for Sensor-Based Learning
    (DELFI 2019, 2019) Yun, Haeseon; Riazy, Shirin; Fortenbacher, Albrecht; Simbeck, Katharina
    Sensor-based learning refers to utilizing physiological sensor data from learners and information from a learning environment to promote learning. Sensor data enclose learner’s personal information so ethical practice of adopting sensor data in learning analytics needs to be explored thoroughly. In this positional paper, we examine current ethical practices in learning analytics to derive a code of practice for sensor-based learning. Furthermore, we critically validate a wearable sensor device developed as a learning support against the derived code of practice.
  • Conference Paper 
    Sensor Based Adaptive Learning - Lessons Learned
    (DELFI 2019, 2019) Fortenbacher, Albrecht; Ninaus, Manuel; Yun, Haeseon; Helbig, René; Moeller, Korbinian
    Recent advances in sensor technology allow for investigating emotional and cognitive states of learners. However, making use of sensor data is a complex endeavor, even more so when considering physiological data to support learning. In the BMBF-funded project Learning Analytics for sensor-based adaptive learning (LISA), we developed a comprehensive solution for adaptive learning using sensor data for acquiring skin conductance, heart rate, as well as environmental factors (e.g. CO2). In particular, we developed, (i) a sensor wristband acquiring physiological and environmental data, (ii) a tablet application (SmartMonitor) for monitoring and visualizing sensor data, (iii) a learning analytics backend, which processes and stores sensor data obtained from SmartMonitor, and (iv) learning applications utilizing these features. In an ongoing study, we applied our solution to a serious game to adaptively control its difficulty. Post-hoc interviews indicated that learners became aware of the adaptation and rated the adaptive version better and more exciting. Although potentials of utilizing physiological data for learning analytics are very promising, more interdisciplinary research is necessary to exploit these for real-world educational settings.
  • Konferenzbeitrag
    User-Centric Approach to the Design of a Mobile Learning Companion
    (Mensch und Computer 2017 - Workshopband, 2017) Yun, Haeseon; Israel, Johann Habakuk; Fortenbacher, Albrecht; Rott, Helena; Metzler, Delia
    In the LISA project, a mobile device (SmartMonitor) to support learners will be developed. SmartMonitor serves as a learning companion, receiving a learner’s sensor data, connecting to a learning analytics system and interacting with a learner without distracting from learning. This paper is about design considerations and first prototypical work for a SmartMonitor device.