Harvesting Metadata for XR Digital Learning Objects

Author:

Psyrra GeorgiaORCID,Mangina EleniORCID

Abstract

AbstractThe 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 discoverability of 3D/AR and other types of educational resources included in the project’s Moodle digital repository.Aiming on utilizing previous work on this domain, the code of two existing plugins was modified and enriched to serve the project’s needs. This paper aims to demonstrate in detail two plugins that will be utilized 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.

Publisher

Springer Nature Switzerland

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Using xAPIs for Monitoring Behavioral Lessons in Augmented Reality;Perspectives on Learning Analytics for Maximizing Student Outcomes;2023-10-24

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3