Reasoning about Communicating Agents in the Semantic Web

Baldoni, Matteo; Baroglio, Cristina; Giordano, Laura; Martelli, Alberto; Patti, Viviana

doi:10.1007/978-3-540-24572-8_6

Cited by 4 publications

(4 citation statements)

References 27 publications

(21 reference statements)

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“…The use of logics for validating courseware has been investigated by the ALICE project at the University of Torino [9]. The project looks at a range of course construction activities including course verification [36] and construction [9].…”

Section: Related Workmentioning

confidence: 99%

Constraint-Based Validation of Adaptive e-Learning Courseware

Melia

Pahl

2009

IEEE Trans. Learning Technol.

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Personalized e-learning allows the course creator to create courseware that dynamically adapts to the needs of individual learners or learner groupings. This dynamic nature of adaptive courseware makes it difficult to evaluate what the delivery time courseware will be for the learner. The course creator may attempt to validate adaptive courseware through dummy runs, but cannot eliminate the risk of pedagogical problems due to adaptive courseware's inherent variability. Courseware validation checks whether adaptive courseware conforms to a set of pedagogical and nonpedagogical requirements. The validation of adaptive courseware limits the risk of pedagogical problems at delivery time. In this paper, we present our approach to adaptive courseware validation using the Courseware Authoring Validation Information Architecture (CAVIAr). We outline how CAVIAr captures adaptive courseware authoring concerns and validates courseware using a constraint-based approach. We also describe how CAVIAr can be integrated with the state of the art in adaptive e-learning and evaluate our validation approach.

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Section: Related Workmentioning

confidence: 99%

Constraint-Based Validation of Adaptive e-Learning Courseware

Melia

Pahl

2009

IEEE Trans. Learning Technol.

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“…Significant research in curriculum modelling has been carried out over the years in the area of Intelligent Tutoring Systems (Baldoni et al , 2002; Karagiannidis et al , 2001; Murray, 1998; Stern and Park Woolff, 1998; Xu et al , 2005). While this work has a formal basis which meets the generic educational modelling requirements described above, approaches to curriculum modelling in the ITS worlds have tended to involve the modelling of conceptual domain knowledge (what is related to what in the domain) and the modelling of knowledge pre‐requisites (what must be learned before what) so that automatic planning processes can perform curriculum sequencing.…”

Section: Requirements For a Route Modelling Languagementioning

confidence: 99%

Modelling routes towards learning goals

Tattersall

Janssen²,

Berg³

et al. 2006

Campus-Wide Information Systems

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The traditional notion of the curriculum as a fixed list of topics to be studied sequentially is undergoing change informed by constructivist theories. However, abandoning the notion of the curriculum as a study plan raises the need to help learners in understanding both where they stand with respect to their desired competences and how these competences can be attained. This article presents a formal model for the description of routes to learning goals, designed to underpin guidance support systems for learners. The article compares the model to other work in the area, illustrates its application with a number of case studies and concludes with a discussion of the broader e-learning infrastructure required in implementing the approach.

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“…As a main difference, it is fully set inside the logic programming paradigm by defining programs by sets of Hornlike rules and giving a SLD-style proof procedure. DyLOG has been used for implementing a virtual tutor [14], that helps students to build personalized study curricula, while in [10,9,11] the capability of reasoning about interaction protocols, supported by the language, has been exploited for customizing web service selection and composition w.r.t. to the user's constraints, based on a semantic description of the services.…”

Section: Executable Agent Specification Languagesmentioning

confidence: 99%

“…In particular, the use of a language that explicitly represents and uses the agent internal state is useful for proving to which extent certain properties depend on the agent mental state or on the semantics of the speech acts. For instance, in [16,10,9,11] the hypothetical reasoning about the effects of conversations on the agent mental state is used to find conversation plans which are proved to respect the implemented protocols, achieving at the same time some desired goal.…”

Section: Reasoning About Interactionmentioning

confidence: 99%