Community Research and Development Information Service - CORDIS

Periodic Report Summary 1 - ISASLC (Intelligent Support for Authoring Semantic Learning Content)

The ultimate goal of the ISASLC project is to advance the state of the art in the field of authoring technologies for intelligent tutoring systems (ITS). Content and knowledge creation for ITS is a very complex procedure that requires considerable time investment and is especially demanding from the point of participating authors’ expertise. This problem has long hindered the dissemination and adoption of adaptive and intelligent technologies in e-Learning. Its solution has not been possible before. But now, with recent advancements in Artificial Intelligence and Human-Computer Interaction, and corresponding development of new Web technologies we might have just enough tools and resources to take the next step towards solving this problem.

The ISASLC project attempts to take this step by relying on the methods from such fields as Social Computing, Semantic Web, and Data Mining. From the practical perspective, ISASLC seek to widen the population of potential ITS authors by providing aid to inexperienced authors when it comes to error-prone and expertise-demanding authoring tasks, such as new content creation, metadata authoring, interactivity authoring, error detection and quality control.

The R&D activity within ISASLC is divided into five work-packages:

- Interactivity authoring support;
- Collaborative authoring support;
- Metadata authoring support;
- Gap detection;
- Open-corpus content discovery.

In all of the work-packages the project has achieved most of the expected outcomes by designing, implementing and evaluating technologies and tools for supporting semantic content authoring.

The main technical outcome of the project is the new authoring platform developed for the ActiveMath/Math-Bridge intelligent learning environment. This platform has been implemented as a Web-application and allows authors to create individual learning objects and assemble them into courses. Several dedicated tools have been developed to extend this platform with unique functionality. EXAMAT component supports authoring of various interactive exercises. Semantic Gap detection tool provides authors with an option to verify the correctness of metadata they have supplied (or did not) for the newly created learning objects. Exercise difficulty calibration tool allows post-hoc re-annotation of exercise difficulty. The entire authoring platform supports collaborative authoring of learning objects.

As the final results a series of authoring experiments is necessary to evaluate in more details the effectiveness of the developed authoring infrastructure.

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