Thesis: Supporting the discoverability of Open Educational Resources.

My research investigates and proposes strategies to better support educators in discovering OERs. The literature suggests that the effectiveness of existing search systems could be improved by supporting high-level and domain-oriented tasks. Hence a preliminary taxonomy of discovery-related tasks was developed, based on the analysis of the literature, interpreted through Information Foraging Theory. This taxonomy was empirically evaluated with a few experienced educators, to preliminary identify an interesting class of Query By Examples (QBE) expansion by similarity tasks, which avoids the need to decompose natural high-level tasks in a complex sequence of sub-tasks. Following the Design Science Research methodology, three prototypes to support as well as to refine those tasks were iteratively designed, implemented, and evaluated involving an increasing number of educators in usability oriented studies. The resulting high-level and domain-oriented blended search/recommendation strategy, transparently replicates Google searches in specialized networks, and identifies similar resources with a QBE strategy. It makes use of a domain-oriented similarity metric based on shared schema.org/LRMI alignments to educational frameworks, and clusters results in expandable classes of comparable degree of similarity. The summative evaluation shows that educators appreciate this exploratory-oriented strategy because, balancing similarity and diversity, it supports their high-level tasks, such as lesson planning and personalization of education.

Personal info:

I have background experience in R&D sectors in the context of the European Space Agency, European Community and CERN, as well as technology transfer sectors at the International Telecommunication Union. I had the opportunity to work with various interesting technologies: human computer interaction, e-learning, software engineering, artificial intelligence, operating systems design, image processing, parallel architectures, telecommunication, hardware and VLSI design.

I left the corporate rat race a couple of lives ago, to work as a consultant and educator, and in my fourth life I have engaged in this academic research experience.

Keys: linked data, schema.org, collective intelligence, merging search and recommendation systems, foraging theory, evaluation.

Fernandez, M., Tirado, A., Pavon-Perez, A., Duddin, K., Zhang, M., Bakina, K., Bandara, A., Capdevila, R., Lazard, L. and Jurasz, O. (2025) Co-creating an Ontology of Online Gender-Based Harms: An Interdisciplinary Perspective, ISWC 2025 - The 24th International Semantic Web Conference, Nara, Japan

Ghafourian, Y., Hanbury, A. and Knoth, P. (2025) Ranking To Learn: Human Experts, Search Engines, or LLMs for Learning Guidance, TPDL 2025: The 29th International Conference on Theory and Practice of Digital Libraries, Tampere, Finland

Cancellieri, M., El-Ebshihy, A., Fink, T., Fröbe, M., Galuščáková, P., Goeuriot, L., Iommi, D., Keller, J., Knoth, P., Mulhem, P., Piroi, F., Pride, D. and Schaer, P. (2025) Extended Abstract of LongEval at CLEF 2025: Longitudinal Evaluation of IR Systems on Web and Scientific Data, 16th International Conference of the CLEF Association (CLEF 2025), Madrid, Spain

Tsaneva, S., Dessì, D., Osborne, F. and Sabou, M. (2025) Knowledge graph validation by integrating LLMs and human-in-the-loop, Information Processing & Management, 62, Elsevier

Cancellieri, M., Docekal, M., Pride, D., Gruenpeter, M., Douard, D. and Knoth, P. (2025) Interoperable verification and dissemination of software assets in repositories using COAR Notify, The 20th International Conference on Open Repositories, Chicago, Illinois, USA