Learning Applications based on Semantic Web Technologies
Abstract: The interplay between learning and technology is a growing field that is often referred to as Technology Enhanced Learning (TEL). Within this context, learning applications are software components that are useful for learning purposes, such as textbook replacements, information gathering tools, communication and collaboration tools, knowledge modeling tools, rich lab environments that allows experiments etc. When developing learning applications, the choice of technology depends on many factors. For instance, who and how many the intended end-users are, if there are requirements to support in-application collaboration, platform restrictions, the expertise of the developers, requirements to inter-operate with other systems or applications etc.This thesis provides guidance on a how to develop learning applications based on Semantic Web technology. The focus on Semantic Web technology is due to its basic design that allows expression of knowledge at the web scale. It also allows keeping track of who said what, providing subjective expressions in parallel with more authoritative knowledge sources. The intended readers of this thesis include practitioners such as software architects and developers as well as researchers in TEL and other related fields.The empirical part of the this thesis is the experience from the design and development of two learning applications and two supporting frameworks. The first learning application is the web application Confolio/EntryScape which allows users to collect files and online material into personal and shared portfolios. The second learning application is the desktop application Conzilla, which provides a way to create and navigate a landscape of interconnected concepts. Based upon the experience of design and development as well as on more theoretical considerations outlined in this thesis, three major obstacles have been identified:The first obstacle is: lack of non-expert and user friendly solutions for presenting and editing Semantic Web data that is not hard-coded to use a specific vocabulary. The thesis presents five categories of tools that support editing and presentation of RDF. The thesis also discusses a concrete software solution together with a list of the most important features that have crystallized during six major iterations of development.The second obstacle is: lack of solutions that can handle both private and collaborative management of resources together with related Semantic Web data. The thesis presents five requirements for a reusable read/write RDF framework and a concrete software solution that fulfills these requirements. A list of features that have appeared during four major iterations of development is also presented.The third obstacle is: lack of recommendations for how to build learning applications based on Semantic Web technology. The thesis presents seven recommendations in terms of architectures, technologies, frameworks, and type of application to focus on.In addition, as part of the preparatory work to overcome the three obstacles, the thesis also presents a categorization of applications and a derivation of the relations between standards, technologies and application types.
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