AI Supported Educational systems have made great strides in recent years both as research tools and teaching applications. Most of the AIED research and development to this point have been in well-defined domains such as Physics, Mathematics, or Chemistry. Such domains are characterized by a well-accepted theory or model that makes it possible unambiguously to classify problems as correct or incorrect.
Not all domains of teaching and inquiry are well-defined, indeed most are not. Domains such as law, argumentation, history, art, medicine, and design are ill-defined. Often even well-defined domains are increasingly ill-defined at the edges where new knowledge is being discovered. Ill-defined domains lack well-defined models and formal theories that can be operationalized, typically problems do not have clear and unambiguous solutions. For those reasons ill-defined domains present a number of unique challenges for researchers in Artificial Intelligence in Education.
These challenges must be faced if the AIED community is ever to branch out from the traditional domains into newer arenas. Over the past few years a number of researchers have begun work in ill-defined domains such as law, medicine, professional ethics and design. This workshop presents a chance to share what has been learned in these pioneering efforts, and may help to further define this unique community of interests.
|9.00 - 9.05||Welcome & Introduction|
|9.05 - 9.55|
Full Paper Session 1
Collin Lynch, Kevin Ashley, Niels Pinkwart
and Vincent Aleven (University of Pittsburgh,
Clausthal University of Technology and
Carnegie Mellon University):
Argument diagramming as
focusing device: does it scaffold reading?
Katerina Avramides and Rose Luckin
(University of Sussex and University of London):
Towards the Design of A Representational Tool
To Scaffold Students: Epistemic Understanding of
Psychology in Higher Education
|9.55 - 10.15||General Discussion|
|10.15 - 10.30||
Impulse Statements for Short Papers
Ig Bittencourt, Evandro Costa, Baldoino Fonseca, Guilherme Maia and Ivo Calado (Federal University of Alagoas and Federal University of Campina Grande):
Themis, a Legal Agent-based ITS
Vu Minh Chieu, Vanda Luengo, Lucile Vadcard and Dima Mufti-Alchawafa (University of
Michigan and Laboratoire CLIPS):
A Framework for Building Intelligent Learning Environments
in Ill-defined Domains
Amanda Nicholas and Brent Martin (University of Canterbury):
Resolving Ambiguity in German Adjectives
|10.30 - 11.15||Poster Session (with coffee)|
|11.15 - 12.05||
Full Paper Session 2
Geneviève Gauthier, Susanne P. Lajoie and Solange Richard (McGill University):
Mapping and Validating Case Specific Cognitive Models
Matthew W. Easterday, Vincent Aleven and Richard Scheines (Carnegie Mellon University):
The logic of Babel: Causal
reasoning from conflicting sources
|12.05 - 12.30||General Discussion|
CALL FOR PAPERS
Potential paper topics include but are not limited to:
Model Development: Production of formal or informal models of ill-defined domains or subsets of such domains.
- Teaching Strategies: Development of teaching strategies for such domains, for example, Socratic, problem-based, task-based, or exploratory strategies.
Search and Inference Strategies: Identification of exploration and inference strategies for ill-defined domains such as heuristic searches and case-based comparisons.
Assessment: Development of Student and Tutor assessment strategies for ill-defined domains. These may include, for example, studies of related-problem transfer and qualitative assessments.
Feedback: Identification of feedback and guidance strategies for ill-defined domains. These may include, for example, Socratic (question-based) methods or related-problem transfer.
Exploratory Systems: Development of intelligent tutoring systems for open-ended domains. These may include, for example, user-driven exploration models and constructivist approaches.
Collaboration: The use of peer-collaboration within ill-defined domains, e.g., to ameliorate modeling issues.
Representation: Free form text is often the most appropriate representation for problems and answers in ill-defined domains; AIED in this area needs tools and techniques for accommodating text.
The topics can be approached from different perspectives: theoretical, systems engineering, application oriented, case study, system evaluation, etc.
- Vincent Aleven, Carnegie Mellon University, USA
- Jerry Andriessen, University of Utrecht, The Netherlands
- Kevin Ashley, University of Pittsburgh, USA
- Paul Brna, University of Glasgow, UK
- Jill Burstein, Educational Testing Service, USA
- Rebecca Crowley, University of Pittsburgh, USA
- Andreas Harrer, University of Duisburg-Essen, Germany
- H. Chad Lane, Institute For Creative Technologies, USC
- Susanne Lajoie, McGill University, Canada
- Collin Lynch, University of Pittsburgh, USA
- Liz Masterman, Oxford University, UK
- Bruce McLaren, German Research Center for Artificial Intelligence, Germany
- Antoinette Muntjewerff, University of Amsterdam, The Netherlands
- Katsumi Nitta, Tokyo Institute of Technology, Japan
- Niels Pinkwart, Clausthal University of Technology, Germany
- Beverly Woolf, University of Massachusetts, USA (to be confirmed)
This workshop will be held
in conjunction with the 13th International Conference on Artificial Intelligence in Education in Los Angeles, CA. We invite submissions of both research papers (up to 10 pages long) and demonstrations (up to 4 pages, describing an application or other work to be demonstrated live at the workshop). Work at all stages of development and covering a wide range of perspectives (e.g. theoretical, systems engineering, application oriented, case study, system evaluation) is invited.
Paper submissions should be made to Vincent Aleven <firstname.lastname@example.org>
and Jo Bodnar <email@example.com>
- 5/1 - Submission deadline
- 5/4 - Papers assigned to reviewers
- 5/25 - Reviews are due
- 6/1 - Reviews back to authors
- 6/15 - Camera ready
Paper submissions should be in the IOS Press format used for the main conference:
- Word template: here.
- Latex power users see: here.