Conceptual framework of a Learning Experience Platform (LXP) to strengthen AI competence by linking simulation technologies and AI

  • David Weigert ,
  • Fabian Behrendt
  • a,b,c,d  Laboratory of the Science of Risks, IMT Mines-Alès, 30100, Alès, France
Cite as
Weigert D., and Behrendt E. (2022)., Experience Platform (LXP) to strengthen AI competence by linking simulation technologies and AI. Proceedings of the 21st International Conference on Modelling and Applied Simulation MAS 2022). , 024 . DOI: https://doi.org/10.46354/i3m.2022.mas.024

Abstract

Artificial intelligence is considered one of the most important driving forces for future economic development. In order to sustainably increase this potential, this paper describes a conceptual framework for a holistic and spiritual Learning Experience Platform (LXP). The basis is formed by the application areas of production and logistics within Industry 4.0. Through this, all subareas of a modern model factory with fischertechnik components are mapped with simulation, automation and visualisation modules.

References

  1. Alderucci, D., & Ashley, K. (2020). Using AI to Analyze Patent Claim Indefiniteness. IP Theory, 9(1). https://www.repository.law.indiana.edu/ipt/vol9/iss1/2
  2. Artificial intelligence in education: challenges and opportunities for sustainable development - UNESCO Digital Library. (n.d.). Retrieved May 13, 2022, from https://unesdoc.unesco.org/ark:/48223/pf0000366994
  3. Bates, T., Cobo, C., Mariño, O., & Wheeler, S. (2020). Can artificial intelligence transform higher education? In International Journal of Educational Technology in Higher Education (Vol. 17, Issue 1, pp. 1–12). Springer. https://doi.org/10.1186/s41239-020-00218-x
  4. Damioli, G., Van Roy, V., & Vertesy, D. (2021). The impact of artificial intelligence on labor productivity. Eurasian Business Review, 11(1). https://doi.org/10.1007/s40821-020-00172-8
  5. De La Higuera, C. (2019). A preliminary report about Teaching and Learning Artificial Intelligence: Overview of key issues. https://www.k4all.org/wp-content/uploads/2019/11/Teaching_AI-report_09072019.pdf
  6. de Witt, C., & Karolyi, H. (2021). Anforderungen an ein Next Generation LMS zur Unterstützung von Personalisierung aus bildungswissenschaftlicher Perspektive. Eleed, 14(1). http://nbn-resolving.de/urn:nbn:de:0009-5-52841
  7. du Boulay, B. (2019). Escape from the Skinner Box: The case for contemporary intelligent learning environments. British Journal of Educational Technology, 50(6), 2902–2919. https://doi.org/10.1111/bjet.12860
  8. Graetz, G., Michaels, G., Beerli, A., Caselli, F., Falck, O., Garred, J., Manning, A., Nordström Skans, O., Pischke, S., & Schönberg, U. (2017). Georg Graetz and Guy Michaels Robots at work Article (Accepted version) (Refereed) Robots at Work *. Direct.Mit.Edu. https://direct.mit.edu/rest/article-abstract/100/5/753/58489
  9. Hooshyar, D., Kori, K., Pedaste, M., & Bardone, E. (2019). The potential of open learner models to promote active thinking by enhancing self‐regulated learning in online higher education learning environments. British Journal of Educational Technology, 50(5), 2365–2386. https://doi.org/10.1111/bjet.12826
  10. The Path to Becoming a Data-Driven Public Sector | OECD iLibrary. (n.d.). Retrieved May 13, 2022, from https://www.oecd-ilibrary.org/sites/059814a7-en/index.html?itemId=/content/publication/059814a7-en