Abstract
Health literacy constitutes an important step towards patient empowerment and the Web is presently the biggest repository of medical information and, thus, the biggest medical resource to be used in the learning process. However, at present, web medical information is mainly accessed through generic search engines that do not take into account the user specific needs and starting knowledge and so they are not able to support learning activities tailored to the specific user requirements. This work presents “ULearn” a meta engine that supports access, understanding and learning on the Web in the medical domain based on specific user requirements and knowledge levels towards what we call “balanced learning”. Balanced learning allows users to perform learning activities based on specific user requirements (understanding, deepening, widening and exploring) towards his/her empowerment. We have designed and developed ULearn to suggest search keywords correlated to the different user requirements and we have carried out some preliminary experiments to evaluate the effectiveness of the provided information.
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Acknowledgements
This work was partially supported by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 754489 and by Science Foundation Ireland grant 13/RC/2094 with a co-fund of the European Regional Development Fund through the Southern & Eastern Regional Operational Programme to Lero - the Irish Software Research Centre (www.lero.ie).
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Alfano, M., Lenzitti, B., Taibi, D., Helfert, M. (2019). ULearn: Personalized Medical Learning on the Web for Patient Empowerment. In: Herzog, M., Kubincová, Z., Han, P., Temperini, M. (eds) Advances in Web-Based Learning – ICWL 2019. ICWL 2019. Lecture Notes in Computer Science(), vol 11841. Springer, Cham. https://doi.org/10.1007/978-3-030-35758-0_20
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