Pedagogical Infrastructures of MOOC Design for Employees Training in Leading Organizations

Farshideh Fathi Hafshejani, Martin Ebner

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

As the most promising form of education, Massive Open Online Courses (MOOCs) have recently received lots of attention, especially in the leading organizations, requiring closer attention to be paid to the MOOCs' implementation platforms before their execution. This qualitative study aims to analyze the pedagogical infrastructures in MOOCs designed for employee training in leading organizations. The research population includes documents retrieved by searching authentic Persian and Latin databases. Out of 142 studies (2013--2023), 73 were selected using a criterion sampling method. Data were gathered using the library research method and then analyzed via thematic analysis. The model validation process was presented using expert judgment. The researcher-made questionnaire for content validation of the conceptual model was then sent to the experts and the final model was approved after the modifications were made. Finally, eight sub-categories (i.e., application of learning paradigms and theories, motivational strategies in the educational environment, application of evaluation module strategies and criteria, provision of an interactive platform, infrastructure for developing the content of the course selection, setting the educational and learning goals, determining the learners' activity in learning, application of the learners engagement types) were obtained.
Original languageEnglish
Title of host publicationLearning and Analytics in Intelligent Systems
EditorsMichael E. Auer, Dominik May
Place of PublicationCham
PublisherSpringer Nature Switzerland AG
Pages227-246
Number of pages20
ISBN (Print)978-3-031-80388-8
DOIs
Publication statusPublished - 20 May 2025

Publication series

NameLearning and Analytics in Intelligent Systems
Volume44
ISSN (Print)2662-3447
ISSN (Electronic)2662-3455

Keywords

  • Educational environment
  • Employee training
  • Leading organizations
  • MOOC
  • Pedagogical infrastructures

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Control and Systems Engineering

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