Semantic technologies in learning & teaching
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Semantic technologies appear to hold the promise of significantly enhancing formal and informal learning but issues such as building ontology consensus, the logistics of annotating large volumes of learning content and the underpinning pedagogy have been frequently questioned. However, recent developments in Web 2.0 tools and services for teaching and learning show that these concerns may be successfully addressed and benefit HE/FE, informal learning and exploratory learning. This project sought to identify and quantify these benefits and outline a roadmap for semantic technologies adoption in these contexts.
Executive Summary
A definition of semantic technologies was one of the first challenges that this project (SemTech) had to address, although not in the initial scope of the project. However, it was considered necessary to set clear criteria on which technologies would be regarded as semantic for this report. SemTech makes a distinction between what we call soft and hard semantic technologies and between linked data and 'traditional' metadata using ontologies.
- We define soft semantic technologies as those that let people document certain concepts in formats that are easy to communicate to other people. These concepts can be communicated as part of learning and teaching processes. Examples of soft semantic annotation are folksonomies and topic maps
- We define hard semantic technologies as those that support efficient exchange and processing of semantic data between programs and machines. An example would be linked data constructed from RDF statements
- We distinguish between linked data that express the existence of relationships between resources and 'traditional' metadata that express such relationships using ontologies
The survey performed in SemTech shows that there is extensive use of soft semantic technologies in HE at the moment. Hard semantic technologies like RDF are initially used in some HE/FE repositories for interoperability. The HE/FE community seems to have identified the benefits of wider adoption of semantic technologies and there is relevant ongoing work.
36 semantic tools and services were found to be relevant to education and were surveyed at the moment of writing. Relevance was established on their suitability for teaching and learning activities or by their potential in HE/FE learning and teaching support. The survey was to detail this relevance and establish the value that semantic technologies add to them. The surveyed tools and services either use hard semantic technologies or they use soft semantic technologies but with intent of semantic enrichment. The semantic tools for learning and teaching that we surveyed included:
- Repositories
- Collaborative content creation tools
- Knowledge modelling and annotation tools (e.g. semantic wikis)
- Search tools
- Matching tools (e.g. matching experts to certain keywords)
- Mashups making use of linked data
The way these tools can be employed in an educational context at the moment can be seen to involve teachers, students, administrators and researchers; the lack of tools built or repurposed for learning reflects the lack of specific support for educational uses. However, there is evidence that a number of Web 2.0 tools that support soft semantics are used successfully in HE/FE; this report discusses the unique value that enrichment with hard semantics can introduce to such tools.
We considered the value of semantic technologies to the tools that we surveyed. In eighty-six per cent of cases there was value in using well-formed metadata, in forty-four per cent there as value in easing integration and interoperability costs, and in thirty-three per cent there as a value in improved data analysis and reasoning.
RDF is clearly the prevalent technology for annotation. The use of RDF to link data in ways that do not ecessarily require agreement on ontologies makes exposing relationships among data more efficient; more expressive knowledge modelling can then take place in application-specific contexts, potentially over larger linked data sets where RDF concepts are mapped to context-specific ontologies. Some of the tools that seem to make heavier use of knowledge modelling involve matching of people and resources or providing support for argumentation and critical thinking.
The surveyed tools classified as repositories make use of metadata to enable more advanced searching or to expose their data in interoperable and machine processable ways. Semantic wiki tools enable efficient representation of collaboratively authored content, while semantic searching enables contextualised queries. Intelligent recommendation of relevant content, to assist collaborative authoring and Q&A systems, is enabled for tools that match people and resources. The currently exploited value in terms of support of learning and teaching processes appears to be mainly in linking repositories using RDF and in enabling searches across these repositories.
We conclude that the adoption of semantic technologies on a wider scale will be enabled if a sufficiently large volume of linked data is exposed in machine processable and declarative formats like RDF. There are many examples of RDF repositories linked to each other, like dbpedia.org and freebase.com, and many more. Many of the semantic applications we surveyed access RDF repositories or harvest linked data from existing sources using ad-hoc approaches.
Activities to encourage exposure of data by HE/FE institutions in formats like RDF and the linking of data repositories can pave the way for the development of semantic applications to efficiently support learning and teaching; for example matching University courses to student interests or assisting in curriculum alignment across the HE sector. In addition, they can provide a foundation on which more rigorous knowledge modelling can flourish and support innovative applications such as argumentation tools that require more advanced ontologies and reasoning.
The development of semantic applications for teaching and learning for HE/FE over the next 5 years could be supported in a number of steps:
- Encouraging the exposure of HE/FE repositories, VLEs, databases and existing Web 2.0 lightweight knowledge models in linked data formats. Enabling the development of learning and teaching applications that make use of linked data across HE/FE institutions; there is significant activity on linked open data to be considered
- Enabling the deployment of semantic-based searching and matching services to enhance learning. Such applications could support group formation and learning resource recommendation based on linked data. The development of ontologies to which linked data will be matched is anticipated. The specification of patterns of semantic tools and services using linked data could be fostered
- Collaborative ontology building and reasoning for pedagogical ends will be more valuable if deployed over a large volume of education related linked data where the value of searching and matching is sufficiently demonstrated. Pedagogy-aware applications making use reasoning to establish learning context and to support argumentation and critical thinking over a large linked data field could be encouraged at this stage