AffectLearn

Track 18. Affective Computing in Learning (AffectLearn@ICALT2017)

Track Program Chairs

 

Scope

Affective computing research has recently experienced the adoption of its own technological advancements by an increasing number of domains (e-commerce, news reading, web 2.0 services, and human-computer interfaces). The capability of affect-aware applications and, especially, games delivering enhanced user immersion and engagement defines the driving force behind this adoption. Inevitably, such environments are unique elicitors of emotion and the study of user experience in those environments is of paramount importance for the understanding of game play internal mechanics. In this framework, games are increasingly used in learning, both in formal education and in teaching social and/or vocational skills, putting into action higher-level psychological concepts, such as attention, engagement and flow, and introducing modern reward systems to make game play more appealing.

Capturing, analyzing and synthesizing player experience in both traditional screen-based games, and augmented- and mixed-reality platforms has been a challenging area within the crossroads of cognitive science, psychology, artificial intelligence and human-computer interaction. Additional gameplay input modalities, such as gestures and movement (e.g. with Nintendo Wii, Microsoft Kinect, or smartphones), image, and speech, enhance the importance of the study and the complexity of player experience. Sophisticated techniques from artificial and computational intelligence can be used to recognize the affective state of player/learner, based on multiple modalities of player-game interaction, and to model emotion in non-playing characters. Multiple modalities of input can also provide a novel means for game platforms to measure player satisfaction and engagement when playing, without necessarily having to resort to post-experience and off-line questionnaires. For instance, players immersed by gameplay will rarely gaze away from the screen, while disappointed or indifferent players will typically show very little response or emotion. Adaptation game techniques can also be used to maximise player experience, thereby, closing the affective game loop: e.g. change the game soundtrack to a vivid or dimmer tune to match the player’s powerful stance or prospect of defeat. In addition to this, procedural content generation techniques may be employed, based on the level of user engagement and interest, to dynamically produce new, adaptable and personalised content (e.g. a new level in a physics skills game, which poses enough challenge to players, without disappointing them or a set of advanced questions or tasks for players that appear to be bored).

Track Topics

  • Natural interaction in learning games
    • controlling games with hand and body gestures, body stance, facial expressions, gaze, speech, and physiology
    • mapping non-verbal cues to affect, emotion, and player satisfaction
  • Emotion in learning experience
    • affective player/learner modelling
    • artificial and computational intelligence for modelling player/learner experience
    • adapting to player/learner affect and experience
    • adaptive learning and player experience
  • affect-driven procedural learning content generation
    • Emotion modelling in non-player characters
  • Higher-level concepts
    • learner engagement, attention and satisfaction
    • maximising user engagement and flow
    • social context awareness and adaptation
  • Games for learning
    • Emotion and affect in user studies and user-centred evaluation
    • Designing for special needs
    • Reward systems and transfer in games
    • User modelling (vocational vs. children games, formal education vs. social skills, etc.)

Track Program Committee

Elisabeth André, University of Augsburg, Germany

Ruth Aylett, Heriot-Watt University, United Kingdom

Nadia Bianchi-Berthouze, University College London, United Kingdom

Ginevra Castellano, Uppsala University, Sweden

Sara de Freitas, Serious Games Institute, UK

Hatice Gunes, Imperial College, United Kingdom

Dirk Heylen, University of Twente, The Netherlands

Katherine Isbister, New York University, USA

Stefanos Kollias, Lincoln University, UK

Nicole Lazzaro, XEODesign, USA

Fotis Liarokapis, Coventry University, UK

Maurizio Mancini, University of Genova, Italy

Catherine Pelachaud, CNRS/TELECOM ParisTech, France

Bjoern Schuller, Technische Universitaet Muenchen, Germany

Gualtiero Volpe, University of Genova, Italy


Important Dates about ICALT 2017 can be found here.

The ICALT 2017 Author Guidelines can be found here.

The ICALT 2017 CfP can be found here.