Intelligent tutoring systems, and intelligent learning environments support learning in a variety of domains from basic math and physics to legal argument, and hypothesis generation. These latter domains are ill-defined referring to a broad range of cognitively complex skills and requiring solvers to structure or recharacterize them in order to solve problems or address open questions. Ill-defined domains are very challenging and have been relatively unexplored in the intelligent learning community. They usually require novel learning environments which use nondidactic methods, such as Socratic instruction, peer-supported exploration, simulation and/or exploratory learning methods, or informal learning techniques in collaborative settings
Ill-defined domains such as negotiation, intercultural competence, and argument are increasingly important in educational settings. As a result, interest in ill-defined domains has grown in recent years with many researchers seeking to develop systems that support both structured problem solving and open-ended recharacterization. Ill-defined problems and ill-defined domains however pose a number of challenges. These include:
- Defining viable computational models for open-ended exploration coupled intertwined with appropriate meta-cognitive scaffolding;
- Developing systems that may assess and respond to fully novel solutions relying on unanticipated background knowledge;
- Constraining students to productive behavior in otherwise underspecified domains;
- Effective provision of feedback when the problem-solving model is not definitive and the task at hand is ill-defined;
- Structuring of learning experiences in the absence of a clear problem, strategy, and answer;
- Developing user models that accommodate the uncertainty, dynamicity, and multiple perspectives of ill-defined domains;
- Designing interfaces that can guide learners to productive interactions without artificially constraining their work.
These challenges must be faced in order to develop effective tutoring systems in these attractive, open, and important arenas. A stimulating series of workshops has been held at ITS 2006, AIED 2007, and ITS 2008. Each workshop brought together a range of researchers focusing on domains as diverse as database design and diagnostic imaging. The work they presented ranged from nascent system designs to robust systems with a solid user base. While the domains and problems addressed differed from system to system, many of the techniques were shared allowing for fruitful cross-pollination.
Due to the success of those workshops and the growing interest in extending intelligent tutoring systems and learning environments to address ill-defined domains we feel a workshop at ITS 2010 is warranted. This event will allow researchers from prior workshops to share their lessons learned while allowing new developers to explore the this dynamic area.
We invite work at all stages of development, including particularly innovative approaches in their early phases. Full research papers (up to 8 pages) and demonstrations (up to 4 pages, describing an application or other work to be demonstrated live at the workshop) are welcome for submission.
Paper topics may include but are not limited to:
- Model Development: Production of formal or informal models of ill-defined domains, constraints or characteristics of such domains or important subdomains.
- Teaching Strategies: Development of teaching strategies for ill-defined problems and ill-defined domains, for example, Socratic, peer-guided, or exploratory strategies.
- Metacognition and Skill-Transfer: Identification of essential skills for ill-defined problems and domains and the transfer of skills across domains and problems.
- Assessment: Development of student and tutor assessment strategies for ill-defined domains. These may include, for example, qualitative assessments and peer-review.
- 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, simulations, and constructivist approaches.
- Representation: Free form text is often the most appropriate representation for problems and answers in ill-defined domains; ITSs in these areas need to accommodate and yet guide this free description.
The topics can be approached from different perspectives: theoretical, systems engineering, application oriented, case study, system evaluation, etc.
Papers should be submitted to EasyChair using the LNCS Format specified on the conference website. As stated above papers may be short (4 pages) or long (8 pages). Submit all papers no later than April 15th. Papers will be published via USB along with the conference proceedings.
* Submissions due: April 15th 2010.
* Author Notification: May 10th 2010.
* Camera Ready Copy due: May 25th 2010.
* June 14th-18th ITS2010.
* Collin Lynch University of Pittsburgh, United States.
* Dr. Kevin Ashley University of Pittsburgh, United States.
* Prof Tanja Mitrovic University of Canterbury, New Zealand
* Dr. Vania Dimitrova University of Leeds, United Kingdom.
* Dr. Niels Pinkwart, Clausthal University of Technology, Germany.
* Dr. Vincent Aleven Carnegie Mellon University, United States.
* Vincent Aleven, Carnegie Mellon University, USA.
* Kevin D. Ashley, University of Pittsburgh, USA.
* Vania Dimitrova, University of Leeds UK.
* Declan Dager, Trinity College Dublin, Ireland.
* Paula Durlach, Army Research Institute, USA.
* Matthew Easterday, Carnegie Mellon University USA.
* Nikos Karacapilidis, University of Patras, GR
* Lydia Lau, University of Leeds, UK.
* Collin Lynch, University of Pittsburgh, USA.
* George Magoulas, London Knowledge Lab, UK.
* Moffat Mathews, University of Canterbury, NZ.
* Tanja Mitrovic, University of Canterbury NZ.
* Amy Ogan, Carnegie Mellon University, USA.
* Niels Pinkwart, Clausthal University of Technology, DE.
* Amali Weerasinghe, University of Canterbury, NZ.