2022-12-17, 17:20–17:40 (Europe/Athens), Room 1
The current work is a proposal for Moodle administrators who aim to provide content creators and teachers with capabilities to describe in a semi-automatic way their learning resources with LOM-based metadata and make these metadata available to search service providers so that other stakeholders can easily find and retrieve them. It was composed within ARETE project to support reusability and discov-erability of 3D/AR and other types of educational resources included in the project’s Moodle digital repository.
Aiming on utilising previous work on this domain, the code of two exist-ing plugins was modified and enriched to serve the project’s needs. This paper aims to demonstrate in detail two plugins that will be utilised in ARETE’s Moodle digital repository to support the discoverability of learning resources by creating and exposing their metadata to make them available for harvesting. The content in the ARETE repository is particularly relevant to 3D/AR learning activities created through an XR authoring toolkit. Nevertheless, educational content in other formats continues to be supported by the aforementioned plugins.
The integration of IEEE-LOM and OAI-PMH standards to a Moodle repository seems to be a feasible way to enhance the development of learning content by utilizing relevant already existing resources that can be easily found and retrieved. However, the difficulty of finding service providers that could support the collection of learning resource metadata and be willing to build search engines on top of them suggests the need to consider different approaches.
Eleni Mangina carried out her PhD work at the University of Strathclyde (UK), Department of Electronic and Electrical Engineering, working on Agent-based applications for intelligent data interpretation (1998-2001). The research area focused on software analysis, design and development of multi agent systems, which utilize different Artificial Intelligence (AI) techniques (Knowledge based systems, Artificial Neural Networks, Case Based Reasoning systems and Model based Reasoning systems). Eleni Mangina holds an M.Sc. in Artificial Intelligence from the Department of Artificial Intelligence at University of Edinburgh in the UK and an MSc in Agricultural Science from Agricultural University of Athens in Greece. In 2002 she joined the School of Computer Science, at University College Dublin, Ireland. Dr Eleni Mangina is currently Professor at the School of Computer Science, University College Dublin in Ireland and the Vice Principal (International) for College of Science. Eleni Mangina is guided by her own definition of the art of persistence, that involves both courage and compassion with research integrity and authenticity. Her lab operates at the intersection between applied Artificial Intelligence (VR/AR; Data Analytics; UAVs; Information Systems) and a portfolio development within interdisciplinary applications (i.e. Energy Sector and Educational Systems with XR). She has extensive experience for the last 20 years in National, EU and International funded projects and she is project coordinator of two (2) H2020 projects (ARETE & AHA), one (1) Erasmus+KA2 (FANTASIA) and partner within other H2020 projects (i.e. iSEED) and three (3) Erasmus+ projects (XRforPed, BASE, RoboPisces). She is funded investigator as part of SFI Energy Systems Integration Partnership Programme (ESIPP), NEXSYS and academic supervisor for two (2) SFI Centres for Research Training (CRT) (Machine Learning – ML-Labs; Digitally-Enhanced Reality – D-REAL). She has authored more than 200 peer-reviewed articles in national and international peer reviewed workshops and conferences and international journals, including in IEEE and ACM. Eleni Mangina also contributes as a committee member for reviews to many international conferences and journals. Eleni Mangina also contributes actively to IEEE Standards and is the Executive Editor for the publications of the IEEE Global Initiative on XR Ethics. She is currently the Chair of Athena SWAN Bronze Award application for the School of Computer Science as an advocate of gender equality, diversion and inclusion in ICT.