@article{DietzRoth2023,
  author    = {Dietz, Michael and Roth, Dennis},
  title     = {Student-centered re-design of an online course with card sorting},
  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-62484},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-624843},
  pages     = {339 -- 350},
  year      = {2023},
  abstract  = {"How can a course structure be redesigned based on empirical data to enhance the learning effectiveness through a student-centered approach using objective criteria?", was the research question we asked. "Digital Twins for Virtual Commissioning of Production Machines" is a course using several innovative concepts including an in-depth practical part with online experiments, called virtual labs. The teaching-learning concept is continuously evaluated. Card Sorting is a popular method for designing information architectures (IA), "a practice of effectively organizing, structuring, and labeling the content of a website or application into a structuref that enables efficient navigation" [11]. In the presented higher education context, a so-called hybrid card sort was used, in which each participants had to sort 70 cards into seven predefined categories or create new categories themselves. Twelve out of 28 students voluntarily participated in the process and short interviews were conducted after the activity. The analysis of the category mapping creates a quantitative measure of the (dis-)similarity of the keywords in specific categories using hierarchical clustering (HCA). The learning designer could then interpret the results to make decisions about the number, labeling and order of sections in the course.},
  language  = {en}
}