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Featured research:
Can learning analytics increase learners’ experiences, satisfaction, engagement and performance?
An internal project of the DICE Research Group in collaboration with the HELM team aims to identify the role of learning analytics in students’ education.
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HELMOPEN in the era of the semantic web
Exploring the benefits of an interconnected platform through semantic web techniques.
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Completed research
Why decision support systems are important for medical education
The inclusion of digital tools in health education over the last few decades has seen us move quickly into an increasingly digital era. Together, the vast quantity of online interactions between learners and tutors; the description, creation, reuse and sharing of digital educational resources; the interlinkage between them; and the availability of cheap storage technology, has led to an enormous amount of educational data.
Medical education is unique due to the accuracy of information needed, continuous changing competencies required and alternative methods of education used. Nowadays medical education standards help to organise educational data and paradata. Analysis of this data through education data mining techniques is in its infancy, but decision support systems (DSSs) for medical education need further research.
This project addressed the clear need to identify the challenges for DSSs in medical education, describing the future actions we believe are necessary. Read more about the project.
The role of taxonomies in social media and the semantic web for health education: A study of SNOMED CT terms in YouTube health video tags
The aim of this project was to identify the use of standardised medical thesauri (SNOMED CT) in YouTube health video tags. Because these videos play a key role in educating professionals and patients, using a more standardised vocabulary could facilitate better sharing of resources. We wanted to demonstrate an information technology architecture for treating the tags of these videos, investigate the percentage of tags that related to SNOMED CT terms and demonstrate how these resources could be most fully exploited using today’s technology.
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Health information recommended system: enriching YouTube health videos with Medline Plus information by the use of SNOMED CT terms
The quantity of health information available online is enormous, but the validity of large chunks of it is questionable. This project proposed a health information recommender system to connect YouTube videos with trustworthy information from very reliable medical sources, such as Medline Plus. According to each video’s metadata, this system detects the main topic of the video and enriches it with information from very well-known resources. Our results revealed that using SNOMED CT terms to identify relative information was the most appropriate basis for the system.
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