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Optimizing the design, pedagogical decision-making and development of MOOCs through the use of Ai-Based tools

  • This work explores the use of different generative AI tools in the design of MOOC courses. Authors in this experience employed a variety of AI-based tools, including natural language processing tools (e.g. Chat-GPT), and multimedia content authoring tools (e.g. DALLE-2, Midjourney, Tome.ai) to assist in the course design process. The aim was to address the unique challenges of MOOC course design, which includes to create engaging and effective content, to design interactive learning activities, and to assess student learning outcomes. The authors identified positive results with the incorporation of AI-based tools, which significantly improved the quality and effectiveness of MOOC course design. The tools proved particularly effective in analyzing and categorizing course content, identifying key learning objectives, and designing interactive learning activities that engaged students and facilitated learning. Moreover, the use of AI-based tools, streamlined the course design process, significantly reducing the time required to designThis work explores the use of different generative AI tools in the design of MOOC courses. Authors in this experience employed a variety of AI-based tools, including natural language processing tools (e.g. Chat-GPT), and multimedia content authoring tools (e.g. DALLE-2, Midjourney, Tome.ai) to assist in the course design process. The aim was to address the unique challenges of MOOC course design, which includes to create engaging and effective content, to design interactive learning activities, and to assess student learning outcomes. The authors identified positive results with the incorporation of AI-based tools, which significantly improved the quality and effectiveness of MOOC course design. The tools proved particularly effective in analyzing and categorizing course content, identifying key learning objectives, and designing interactive learning activities that engaged students and facilitated learning. Moreover, the use of AI-based tools, streamlined the course design process, significantly reducing the time required to design and prepare the courses. In conclusion, the integration of generative AI tools into the MOOC course design process holds great potential for improving the quality and efficiency of these courses. Researchers and course designers should consider the advantages of incorporating generative AI tools into their design process to enhance their course offerings and facilitate student learning outcomes while also reducing the time and effort required for course development.zeige mehrzeige weniger

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Verfasserangaben:Miguel Morales-ChanORCiD, Héctor R. Amado-SalvatierraORCiD, Rocael Hernández-Rizzardini
URN:urn:nbn:de:kobv:517-opus4-623870
DOI:https://doi.org/10.25932/publishup-62387
Titel des übergeordneten Werks (Englisch):EMOOCs 2023 : Post-Covid Prospects for Massive Open Online Courses - Boost or Backlash?
Verlag:Universitätsverlag Potsdam
Verlagsort:Potsdam
Herausgeber*in(nen):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
Publikationstyp:Wissenschaftlicher Artikel
Sprache:Englisch
Datum der Erstveröffentlichung:14.11.2023
Erscheinungsjahr:2023
Veröffentlichende Institution:Universität Potsdam
Veröffentlichende Institution:Universitätsverlag Potsdam
Datum der Freischaltung:31.01.2024
Freies Schlagwort / 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
Seitenanzahl:9
Erste Seite:95
Letzte Seite:103
RVK - Regensburger Verbundklassifikation:ST 670
Organisationseinheiten:Digital Engineering Fakultät / Hasso-Plattner-Institut für Digital Engineering GmbH
DDC-Klassifikation:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 000 Informatik, Informationswissenschaft, allgemeine Werke
Peer Review:Referiert
Publikationsweg:Universitätsverlag Potsdam
Open Access / Gold Open-Access
Sammlung(en):Universität Potsdam / Sammelwerke (nicht fortlaufend) / EMOOCs 2023 / Beiträge
Lizenz (Deutsch):License LogoCC-BY - Namensnennung 4.0 International
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