Call: ANIMATAS Symposium on “Human-Machine Interaction. Perception, Social Learning, Personalised Adaptation in Educational Settings”

Call for Papers

ANIMATAS Symposium on ‘Human-Machine Interaction. Perception, Social Learning, Personalised Adaptation in Educational Settings’
October 12-14, 2021
Virtual event

Symposium Website:

Submission Deadline: 16th of August 2021


As emerging technologies continue to grow in complexity and availability, the question of how to successfully integrate such technologies into our society is attracting growing research interest. Social robots, virtual agents, and (explainable) artificial intelligence models are increasingly being implemented in healthcare systems, in entertainment or retail, or in educational settings as a means to reduce burden on human workers and maximise user experience.

Education is a particularly relevant context for the implementation of advanced robotic, virtual, or AI systems. Teachers around the world suffer from overcrowded classrooms, limited resources, and diverse student needs. These challenges are being especially highlighted in the face of the COVID-19 pandemic. Thus, there is a clear need to develop and implement effective technological solutions into both virtual and physical classroom settings. If successful, such systems could help in reducing teacher burden, providing personalised learning experiences, and minimising costs.

The ANIMATAS project is aimed at understanding human-machine interaction in the context of education. Three broad research areas are targeted: 1) understanding perception of robotic or virtual agents, 2) development of social learning mechanisms, and 3) personalised adaptation of agents to unstructured social interactions.

This three-day virtual symposium aims to bring together researchers and stakeholders of each of these areas to discuss and present relevant outcomes and research findings. Through this symposium, we hope to foster interdisciplinary discussions on topics relevant to embodiment, social learning, and personalisation and adaptation within the context of education.


Participants are invited to submit full papers (12-15 pages) and short papers (6-8 pages) following the Lecture Notes in Computer Science formatting guidelines, on the central topic of perception of robotic and/or virtual agents, development of social learning mechanisms, and personalised adaptation. All manuscripts will be peer-reviewed and accepted submissions will be published as part of our symposium proceedings by Springer. The camera ready versions of the accepted submissions are due after the symposium to allow authors to modify their manuscripts based on comments received during the symposium.

Potential topics for submission include, but are not limited to:

  • Quantitative and/or qualitative research methodology to assess human-machine interaction in educational settings.
  • Theoretical reflections on the conceptualization or operationalization of educational scenarios for human machine interaction.
  • Ethical reflections on settings and methods in/by which to assess human-machine interaction in education.
  • Design and technical implementation of systems and scenarios by which to evaluate human machine interaction (e.g., machine-learning models, semi-autonomousor autonomous robot systems, Wizard of Oz) scenarios.’

Submission Link:


  • August 16, 2021 – Submission Deadline
  • September 16, 2021 – Decision Notification
  • November 1, 2021 – Camera-ready Deadline
  • October 12-14, 2021 – Symposium


  • Brian Scassellati (Yale University, USA)
  • Kerstin Dautenhahn (University of Waterloo, Canada)
  • Tony Belpaeme (Ghent University, Belgium & Plymouth University, England)
  • Jonathan Gratch (USC Institute for Creative Technologies, USA)


  • Rebecca Stower (Jacobs University Bremen, Germany)
  • Sooraj Krishna (Sorbonne Université, France)
  • Natalia Calvo-Barajas (Uppsala University, Sweden)
  • Karen Tatarian (SoftBank Robotics Europe, France)
  • Sahba Zojaji (KTH Royal Institute of Technology, Sweden)
  • Sina Shahmoradi (EPFL, Switzerland)
  • Utku Norman (EPFL, Switzerland)
  • Sebastian Wallkötter (Uppsala University, Sweden)
  • Manuel Bied (Sorbonne Université, France)
  • Ramona Merhej (INESC-ID, Portugal)
  • Tanvi Dinkar (Télécom Paris Institut Polytechnique de Paris, France)
  • Jauwairia Nasir (EPFL, Switzerland)
  • Sera Büyükgöz (SoftBank Robotics Europe, France)
  • Silvia Tulli (INESC-ID, Portugal)
  • Maha Elgarf (KTH Royal Institute of Technology, Sweden)


If you have any comments or questions, please contact the organisers at

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