Abstract:

The insight that problem-solving can also be analyzed as a multi agent communication process obtained new meaning for the net-generation. While new modeling languages and standards of meta-level e-didactic standards emerge, the domain- and problem-specific representation of the dynamics of actual communicative problem solving activities still lags far behind both the cognitive needs and the technical possibilities.
The widely used Educational-purpose Modeling Languages (EML) represent didactic meta-models in a descriptive, prescriptive and operational manner as the IMS Learning Design (IMS-LD) standard or the Learning Design Language (LDL) supports the formalization of collaborative learning patterns in various e-learning frameworks. These representations usually describe pre-designed learning scenarios, specify roles, acts and actors, express given relations of learning objects, orchestrate the scenario execution and are normally used to show static relations between Learning Objects. Representation of the methods are to provide means to prescribe the sequencing of the activities and is in most of the cases the learning processes are sequential, even though proposals based on Workflow Management Systems technology promoted parallel, conditional and iterative routing.
Collective problem solving and serious games require that we consider the knowledge of other participants and reason about the possibilities of the problem space in light of information exchange. We need representations of the temporal properties of the information flow, of the development of common knowledge, of the consequences of announcements and other communicative acts for the knowledge states of the problem-solvers.
Recent developments in Dynamic Epistemic Logic provide tools to represent the changing knowledge state of the participants of a communicative situation who obtain factual and shared information and perform various epistemic actions. We are able to trace group knowledge, and simulate various protocols for information exchange and iterated revisions of individual doxastic states in problem specific learning scenarios.
Dynamic Epistemic MOdeling (DEMO) and other Model Checking Sytems (eg. MCK) describe the environment in which the learners or game players act and communicate, rules and protocols and how the epistemic actions affect individual and collective knowledge states. After giving some examples of simple but representative scenarios in DEMO and MCK the advantages of these systems for e-didactics will be spelled out as compared with the capabilities of standard IMS-LD, EML, or LDL. Uses of visualizations will be compared with case based simulations of rule-systems in legal contexts such as the textual method of Neopolitis, utilizing the PROLOG based ALL-EX system.
The paper comes to conclusion that didactic meta-models should be supplemented with representations and simulations of domain level problem-solving scenarios, with the analysis of communication protocols and the changing knowledge states of the actors. The virtual presentation provides access to online sources.
References:
van Benthem, J. 2010, Logical Dynamics of Information and Interaction, Cambridge U. P.
DEMO at http://www.cwi.nl/~jve/demo/
Futó Ivan, Várkonyi József, 1993, Legal Expert Systems as Simulation Tools, Winter Simulation Conference, Los Angeles.
Gammie P. van der Meyden R. 2004, MCK: Model Checking the Logic of Knowledge. Lect. Notes Comp. Sci., v.3114, p.479-483

Keywords:

e-learning, technology-enhanced learning, knowledge representation, knowledge models, dynamic epistemic logic, collective problem solving, serious games.