Hybrid Human-AI Curriculum Development for Personalised Informal Learning Environments

Open Access
Authors
  • M. Tavakoli
  • A. Faraji
  • M. Molavi
  • S.T. Mol ORCID logo
Publication date 2022
Book title LAK22 conference proceedings
Book subtitle the Twelfth International Conference on Learning Analytics & Knowledge : learning analytics for transition, disruption and social change : March 21-25, 2022, Online, Everywhere
ISBN (electronic)
  • 9781450395731
Event 12th International Conference on Learning Analytics & Knowledge
Pages (from-to) 563-569
Publisher New York, NY: The Association for Computing Machinery
Organisations
  • Faculty of Economics and Business (FEB) - Amsterdam Business School Research Institute (ABS-RI)
  • Faculty of Economics and Business (FEB)
Abstract
Informal learning procedures have been changing extremely fast over the recent decades not only due to the advent of online learning, but also due to changes in what humans need to learn to meet their various life and career goals. Consequently, online, educational platforms are expected to provide personalized, up-to-date curricula to assist learners. Therefore, in this paper, we propose an Artificial Intelligence (AI) and Crowdsourcing based approach to create and update curricula for individual learners. We show the design of this curriculum development system prototype, in which contributors receive AI-based recommendations to be able to define and update high-level learning goals, skills, and learning topics together with associated learning content. This curriculum development system was also integrated into our personalized online learning platform. To evaluate our prototype we compared experts’ opinion with our system’s recommendations, and resulted in 89%, 79%, and 93% F1-scores when recommending skills, learning topics, and educational materials respectively. Also, we interviewed eight senior level experts from educational institutions and career consulting organizations. Interviewees agreed that our curriculum development method has high potential to support authoring activities in dynamic, personalized learning environments.
Document type Conference contribution
Language English
Published at https://doi.org/10.48550/arXiv.2112.12100 https://doi.org/10.1145/3506860.3506917
Downloads
2112.12100 (Accepted author manuscript)
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