@article{SerthStaubitzvanEltenetal.2022,
  author    = {Serth, Sebastian and Staubitz, Thomas and van Elten, Martin and Meinel, Christoph},
  title     = {Measuring the effects of course modularizations in online courses for life-long learners},
  series = {Frontiers in Education},
  volume    = {7},
  journal   = {Frontiers in Education},
  editor    = {Gamage, Dilrukshi},
  publisher = {Frontiers},
  address   = {Lausanne, Schweiz},
  issn      = {2504-284X},
  doi       = {10.3389/feduc.2022.1008545},
  pages     = {15},
  year      = {2022},
  abstract  = {Many participants in Massive Open Online Courses are full-time employees seeking greater flexibility in their time commitment and the available learning paths. We recently addressed these requirements by splitting up our 6-week courses into three 2-week modules followed by a separate exam. Modularizing courses offers many advantages: Shorter modules are more sustainable and can be combined, reused, and incorporated into learning paths more easily. Time flexibility for learners is also improved as exams can now be offered multiple times per year, while the learning content is available independently. In this article, we answer the question of which impact this modularization has on key learning metrics, such as course completion rates, learning success, and no-show rates. Furthermore, we investigate the influence of longer breaks between modules on these metrics. According to our analysis, course modules facilitate more selective learning behaviors that encourage learners to focus on topics they are the most interested in. At the same time, participation in overarching exams across all modules seems to be less appealing compared to an integrated exam of a 6-week course. While breaks between the modules increase the distinctive appearance of individual modules, a break before the final exam further reduces initial interest in the exams. We further reveal that participation in self-paced courses as a preparation for the final exam is unlikely to attract new learners to the course offerings, even though learners' performance is comparable to instructor-paced courses. The results of our long-term study on course modularization provide a solid foundation for future research and enable educators to make informed decisions about the design of their courses.},
  language  = {en}
}
@article{SteinbeckMeinel2023,
  author    = {Steinbeck, Hendrik and Meinel, Christoph},
  title     = {What makes an educational video?},
  series = {EMOOCs 2023 : Post-Covid Prospects for Massive Open Online Courses - Boost or Backlash?},
  journal   = {EMOOCs 2023 : Post-Covid Prospects for Massive Open Online Courses - Boost or Backlash?},
  editor    = {Meinel, Christoph and Schweiger, Stefanie and Staubitz, Thomas and Conrad, Robert and Alario Hoyos, Carlos and Ebner, Martin and Sancassani, Susanna and Żur, Agnieszka and Friedl, Christian and Halawa, Sherif and Gamage, Dilrukshi and Scott, Jeffrey and Kristine Jonson Carlon, May and Deville, Yves and Gaebel, Michael and Delgado Kloos, Carlos and von Schmieden, Karen},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  doi       = {10.25932/publishup-62208},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-622086},
  pages     = {47 -- 58},
  year      = {2023},
  abstract  = {In an effort to describe and produce different formats for video instruction, the research community in technology-enhanced learning, and MOOC scholars in particular, have focused on the general style of video production: whether it is a digitally scripted "talk-and-chalk" or a "talking head" version of a learning unit. Since these production styles include various sub-elements, this paper deconstructs the inherited elements of video production in the context of educational live-streams. Using over 700 videos - both from synchronous and asynchronous modalities of large video-based platforms (YouTube and Twitch), 92 features were found in eight categories of video production. These include commonly analyzed features such as the use of green screen and a visible instructor, but also less studied features such as social media connections and changing camera perspective depending on the topic being covered. Overall, the research results enable an analysis of common video production styles and a toolbox for categorizing new formats - independent of their final (a)synchronous use in MOOCs. Keywords: video production, MOOC video styles, live-streaming.},
  language  = {en}
}
@article{ThomasStaubitzMeinel2023,
  author    = {Thomas, Max and Staubitz, Thomas and Meinel, Christoph},
  title     = {Preparing MOOChub metadata for the future of online learning},
  series = {EMOOCs 2023 : Post-Covid Prospects for Massive Open Online Courses - Boost or Backlash?},
  journal   = {EMOOCs 2023 : Post-Covid Prospects for Massive Open Online Courses - Boost or Backlash?},
  editor    = {Meinel, Christoph and Schweiger, Stefanie and Staubitz, Thomas and Conrad, Robert and Alario Hoyos, Carlos and Ebner, Martin and Sancassani, Susanna and Żur, Agnieszka and Friedl, Christian and Halawa, Sherif and Gamage, Dilrukshi and Scott, Jeffrey and Kristine Jonson Carlon, May and Deville, Yves and Gaebel, Michael and Delgado Kloos, Carlos and von Schmieden, Karen},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  doi       = {10.25932/publishup-62483},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-624830},
  pages     = {329 -- 338},
  year      = {2023},
  abstract  = {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 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.},
  language  = {en}
}