Final Report Summary - ISASLC (Intelligent Support for Authoring Semantic Learning Content)
Many types of adaptive learning environments (ALE) rely on sophisticated metadata models that help describe the parameters of learning objects (LO) presented by these environments. These parameters vary from merely descriptive terms facilitating cataloguing and discoverability of LO in content collections, to pedagogical properties of LO and semantic relations between them, which are used by adaptation components of the environment and define the logic of its adaptive intervention. This is why content and knowledge creation for ALE is a very complex procedure that requires considerable time investment and is especially demanding from the point of participating authors’ expertise. It is also characterised by some other factors (see fig.1). This problem has long hindered the dissemination and adoption of adaptive and intelligent technologies in e-Learning.
The ultimate goal of the ISASLC project is to advance the state of the art in the field of authoring technologies for different types of ALE, and especially, 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: the goal is to improve the current practice of authoring interactive exercises in ActiveMath through usage of collaborative authoring support and partial generation of solution graphs and metadata.
• Collaborative authoring support: τhe goal is to widely implement the effective authoring patterns developed on the Social Web and to find the benefits and limitation of collaborative authoring technology for semantic learning content creation.
• Metadata authoring support: the goal is develop a technology that will make authoring semantics for learning content available for a broader category of users;
• Gap detection: the goal is to develop a technology for effective detection of knowledge gaps in learning content;
• Open-corpus content discovery: the goal is to develop a technology for harvesting learning content from online sources and its provision with appropriate metadata.
The ultimate goal of the ISASLC project is to advance the state of the art in the field of authoring technologies for different types of ALE, and especially, 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: the goal is to improve the current practice of authoring interactive exercises in ActiveMath through usage of collaborative authoring support and partial generation of solution graphs and metadata.
• Collaborative authoring support: τhe goal is to widely implement the effective authoring patterns developed on the Social Web and to find the benefits and limitation of collaborative authoring technology for semantic learning content creation.
• Metadata authoring support: the goal is develop a technology that will make authoring semantics for learning content available for a broader category of users;
• Gap detection: the goal is to develop a technology for effective detection of knowledge gaps in learning content;
• Open-corpus content discovery: the goal is to develop a technology for harvesting learning content from online sources and its provision with appropriate metadata.
