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Visualizing students flows to monitor persistence

  • Founded in 2013, OpenClassrooms is a French online learning company that offers both paid courses and free MOOCs on a wide range of topics, including computer science and education. In 2021, in partnership with the EDA research unit, OpenClassrooms shared a database to solve the problem of how to increase persistence in their paid courses, which consist of a series of MOOCs and human mentoring. Our statistical analysis aims to identify reasons for dropouts that are due to the course design rather than demographic predictors or external factors.We aim to identify at-risk students, i.e. those who are on the verge of dropping out at a specific moment. To achieve this, we use learning analytics to characterize student behavior. We conducted data analysis on a sample of data related to the “Web Designers” and “Instructional Design” courses. By visualizing the student flow and constructing speed and acceleration predictors, we can identify which parts of the course need to be calibrated and when particular attention should be paid to theseFounded in 2013, OpenClassrooms is a French online learning company that offers both paid courses and free MOOCs on a wide range of topics, including computer science and education. In 2021, in partnership with the EDA research unit, OpenClassrooms shared a database to solve the problem of how to increase persistence in their paid courses, which consist of a series of MOOCs and human mentoring. Our statistical analysis aims to identify reasons for dropouts that are due to the course design rather than demographic predictors or external factors.We aim to identify at-risk students, i.e. those who are on the verge of dropping out at a specific moment. To achieve this, we use learning analytics to characterize student behavior. We conducted data analysis on a sample of data related to the “Web Designers” and “Instructional Design” courses. By visualizing the student flow and constructing speed and acceleration predictors, we can identify which parts of the course need to be calibrated and when particular attention should be paid to these at-risk students.zeige mehrzeige weniger

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Metadaten
Verfasserangaben:Mehdi KhaneboubiORCiD
URN:urn:nbn:de:kobv:517-opus4-623906
DOI:https://doi.org/10.25932/publishup-62390
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:11
Erste Seite:121
Letzte Seite:131
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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