• search hit 3 of 644
Back to Result List

Preparing MOOChub metadata for the future of online learning

  • With the growing number of online learning resources, it becomes increasingly difficult and overwhelming to keep track of the latest developments and to find orientation in the plethora of offers. AI-driven services to recommend standalone learning resources or even complete learning paths are discussed as a possible solution for this challenge. To function properly, such services require a well-defined set of metadata provided by the learning resource. During the last few years, the so-called MOOChub metadata format has been established as a de-facto standard by a group of MOOC providers in German-speaking countries. This format, which is based on schema.org, already delivers a quite comprehensive set of metadata. So far, this set has been sufficient to list, display, sort, filter, and search for courses on several MOOC and open educational resources (OER) aggregators. AI recommendation services and further automated integration, beyond a plain listing, have special requirements, however. To optimize the format for proper support ofWith the growing number of online learning resources, it becomes increasingly difficult and overwhelming to keep track of the latest developments and to find orientation in the plethora of offers. AI-driven services to recommend standalone learning resources or even complete learning paths are discussed as a possible solution for this challenge. To function properly, such services require a well-defined set of metadata provided by the learning resource. During the last few years, the so-called MOOChub metadata format has been established as a de-facto standard by a group of MOOC providers in German-speaking countries. This format, which is based on schema.org, already delivers a quite comprehensive set of metadata. So far, this set has been sufficient to list, display, sort, filter, and search for courses on several MOOC and open educational resources (OER) aggregators. AI recommendation services and further automated integration, beyond a plain listing, have special requirements, however. To optimize the format for proper support of such systems, several extensions and modifications have to be applied. We herein report on a set of suggested changes to prepare the format for this task.show moreshow less

Download full text files

  • SHA-512:64099492228a05ee91723a933585d704545e72d5017090e564ace5ae7a45cc1b2bcd115db8756f9269ad8669120fcc1d1622ca6cc0a35d3420b1b103c70443d4

Export metadata

Additional Services

Search Google Scholar Statistics
Metadaten
Author details:Max Thomas, Thomas StaubitzORCiDGND, Christoph MeinelORCiDGND
URN:urn:nbn:de:kobv:517-opus4-624830
DOI:https://doi.org/10.25932/publishup-62483
Title of parent work (English):EMOOCs 2023 : Post-Covid Prospects for Massive Open Online Courses - Boost or Backlash?
Subtitle (English):optimizing for AI recommendation services
Publisher:Universitätsverlag Potsdam
Place of publishing:Potsdam
Editor(s):Christoph Meinel, Stefanie Schweiger, Thomas Staubitz, Robert Conrad, Carlos Alario Hoyos, Martin Ebner, Susanna Sancassani, Agnieszka Żur, Christian Friedl, Sherif Halawa, Dilrukshi Gamage, Jeffrey Scott, May Kristine Jonson Carlon, Yves Deville, Michael Gaebel, Carlos Delgado Kloos, Karen von Schmieden
Publication type:Article
Language:English
Date of first publication:2023/11/14
Publication year:2023
Publishing institution:Universität Potsdam
Publishing institution:Universitätsverlag Potsdam
Release date:2024/02/02
Tag:Digitale Bildung; Kursdesign; MOOC; Micro Degree; Online-Lehre; Onlinekurs; Onlinekurs-Produktion
digital education; e-learning; micro degree; micro-credential; online course creation; online course design; online teaching
Number of pages:10
First page:329
Last Page:338
RVK - Regensburg classification:ST 670
Organizational units:Digital Engineering Fakultät / Hasso-Plattner-Institut für Digital Engineering GmbH
DDC classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 000 Informatik, Informationswissenschaft, allgemeine Werke
Peer review:Referiert
Publishing method:Universitätsverlag Potsdam
Open Access / Gold Open-Access
Collection(s):Universität Potsdam / Sammelwerke (nicht fortlaufend) / EMOOCs 2023 / Beiträge
License (German):License LogoCC-BY - Namensnennung 4.0 International
Accept ✔
This website uses technically necessary session cookies. By continuing to use the website, you agree to this. You can find our privacy policy here.