Multimodal Tutors: Enhancing learning using multimodal data and machine learning.

  • Daniele Di Mitri (Speaker)

    Activity: Talk or presentation typesTalk or presentation (not at a conference)Academic


    Artificial intelligence (AI) systems find today application in a wide range of sectors including manufacturing, retail, automotive and consumer services. In several occasions, intelligent machines have outperformed humans, especially in tasks executed in closed and predictable environments which are simple to model. In contrast, in tasks taking place in open-ended and unpredictable environments, intelligent systems are much more difficult to model. Example of these tasks are human-led processes such as education and learning. The design of intelligent systems that interface with human processes is a frontier for future generation AI. Today with wearable sensors and Internet of Things devices is possible to track multiple modalities including biomechanics movements, physiological information; it is possible to monitor learning context and activity and ultimately generate feedback and support the learning. The Learning Analytics community is using the analysis of social signals to monitor learning activities happening in the physical space that go beyond mouse and keyboard computer interaction data. In this workshop, we will show the progress of the learning analytics research using multimodal interaction methods and AI to develop intelligent tutoring systems that support human learning. We will present some of the use cases which are currently being developed at the Technology Enhanced Learning and Innovation department of the Welten Institute, a research centre for teaching and learning and technology of the Open Universiteit.
    Period24 Nov 2018
    Event titleInformatica StudieDag: Kunstmatige intelligentie en machine learning
    Event typeSeminar
    LocationEindhoven, NetherlandsShow on map
    Degree of RecognitionNational