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CARE 2016 - The Seventh International Workshop on Collaborative Agents Research & Development

CARE for Digital Education

In conjunction with the 15th International Autonomous Agents and Multi-Agent Systems (AAMAS 2016). 
GENERAL CHAIRS

 

  • Dr. Fernando Koch ^, Samsung Research Institute, Brazil

  • Dr. Christian Guttmann, UNSW, Australia & IVBAR, Sweden & Karolinska Institute, Sweden 

  • Dr. Tiago Primo, Samsung Research Institute, Brazil

  • Dr. Andrew Koster, Samsung Research Institute, Brazil

STEERING COMMITTEE
 

  • Prof. Raimundo Barreto, Federal University of Amazon, Brazil

  • Prof. Rosa Maria Vicari, Federal University of Rio Grande do Sul, Brazil

  • Prof. Takao Terano, Tokyo Institute of Technology, Japan

  • Dr. Yeunbae Kim, Korea University, South Korea

PROGRAMME

 

Monday May 9th, 2016

AAMAS 2016 – Grand Copthorne Waterfront Hotel, Singapore

 

Special Track along with Workshop on Coordination, Organisations, Institutions and Norms in Agent Systems (COIN) &

Workshop on Engineering Multi-Agent Systems (EMAS)

 

OPENING

16.00 - 16.15 Opening & Presentation 

“Practical results from Samsung Digital Education Research Platform”

by Dr Andrew Koster, Research Scientist, Samsung Research Institute 

 

PAPERS

16.15 – 16.40 Mhd Irvan and Takao Terano. Multi-Agent Simulation for Group Recommendation in E-Learning Environments

16.40 – 17.05 Johan Baldeon, Maite Lopez-Sanchez, Inma Rodríguez and Anna Puig. Gamification in Teaching Multi-Agent Systems

17.05 – 17.30 Yuki Katsura, Kei Nishina, Shogo Okada and Katsumi Nitta. Argumentation Support Tool with Advisory Function

 

Koch, F.L., Primo, T.T., Guttmann, C. (2017), Advances in Social Computing and Digital Education. Communications in Computer and Information Systems, Vol 677, Pub Springer. 169 pp. ISBN 978-3-319-52038-4 .

WORKSHOP SUMMARY

 

"CARE for Digital Education” aims to discuss computational models, social computing, and intelligence applied to Digital Education. We are motivated by a recent OECD Report (OECD, 2015), which points out that despite many years of effort in bringing computing technology to learning practices, there is no appreciable improvement in student achievement. How can Computation Intelligence and Agent-based technology help with that?

 

We aim to bring together experiences around the utilisation of innovative models of ICT in education, particularly in the fields of: content provisioning and intelligent repositories of learning objects; content composition and recommendation systems for composing personalised and adaptive digital content; content delivery and intelligences for content adaptation, personalised tutoring, and reaction to student behaviour; new forms of automatic assessment, and models to understand the impact of social behaviour, and; learning analytics, models to analyse and understand student behaviour, models to predict student behaviour, and so on.

 

The CARE workshop series intends to address a gap in Multi-Agent Systems and AI landscape around practical application of the technology to analyse and address social issues in daily life problems, such as education, health, safety, mobility, and social connectedness. These solutions exploit the combination of social applications, ambient intelligence, social networks, and collective thinking to promote the participation of users, social connectedness, and social intelligence.

 

We expect contributions from members in the industry and applied research in academia. The contributions shall apply AI and agent technology, including distributed AI, situatedness, local interaction, user profiling, social simulation, and others.

RESEARCH QUESTIONS

 

CARE is aimed at the academic and industrial research community that uses and extends AI and multi-agent systems. This edition's topics of interest include, with no limitation:

  • How to apply agents for the next generation Digital Education scenarios? Examples include Personalised Tutoring Systems, Recommendation Systems, Ambient Intelligence, Regulation of Social Behaviour, Collaborative Tasks. How to build a model of the features of individuals and groups in Digital Education environments?

  • How to construct agent-based models to advance the elements of the Digital Education environment, namely Adaptive Content, Tutoring Systems, Intelligent Composition Systems, Learning Analytics, and others?

  • How to build a model of Adaptive Learning and Adjustable Content reactive to Social Behaviour?

  • How to construct agent-based models of social behaviour, aiming to understand, model, and influence complex behaviour, group behaviour, and the impact of micro-macro actions upon the system?

  • How can we make Participatory Education where team members follow agreed procedures (Incentives? Or more fundamental, by designing a new market?)

  • How to build an effective monitoring-recognition-intervention framework in Digital Education?

  • How can we support/guide collaborative teams. How can we offer flexibility in how teams execute plans? How can we make team members follow agreed procedures? Incentives? Or more fundamental, by designing a new market?

  • How to enable an effective communication infrastructure for collaborative education (possibly including both humans and agents)?

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