Staying Ahead in the MOOC-Era by Teaching Innovative AI Courses

Patrick Glauner

Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop, PMLR 170:5-9, 2022.

Abstract

As a result of the rapidly advancing digital transformation of teaching, universities have started to face major competition from Massive Open Online Courses (MOOCs). Universities thus have to set themselves apart from MOOCs in order to justify the added value of three to five-year degree programs to prospective students. In this paper, we show how we address this challenge at Deggendorf Institute of Technology in ML and AI. We first share our best practices and present two concrete courses including their unique selling propositions: Computer Vision and Innovation Management for AI. We then demonstrate how these courses contribute to Deggendorf Institute of Technology’s ability to differentiate itself from MOOCs (and other universities).

Cite this Paper

BibTeX


@InProceedings{pmlr-v170-glauner22a,
  title = 	 {Staying Ahead in the MOOC-Era by Teaching Innovative AI Courses},
  author =       {Glauner, Patrick},
  booktitle = 	 {Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop},
  pages = 	 {5--9},
  year = 	 {2022},
  editor = 	 {Kinnaird, Katherine M. and Steinbach, Peter and Guhr, Oliver},
  volume = 	 {170},
  series = 	 {Proceedings of Machine Learning Research},
  month = 	 {08--13 Sep},
  publisher =    {PMLR},
  pdf = 	 {https://proceedings.mlr.press/v170/glauner22a/glauner22a.pdf},
  url = 	 {https://proceedings.mlr.press/v170/glauner22a.html},
  abstract = 	 {As a result of the rapidly advancing digital transformation of teaching, universities have started to face major competition from Massive Open Online Courses (MOOCs). Universities thus have to set themselves apart from MOOCs in order to justify the added value of three to five-year degree programs to prospective students. In this paper, we show how we address this challenge at Deggendorf Institute of Technology in ML and AI. We first share our best practices and present two concrete courses including their unique selling propositions: Computer Vision and Innovation Management for AI. We then demonstrate how these courses contribute to Deggendorf Institute of Technology’s ability to differentiate itself from MOOCs (and other universities).}
}

Endnote

%0 Conference Paper
%T Staying Ahead in the MOOC-Era by Teaching Innovative AI Courses
%A Patrick Glauner
%B Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop
%C Proceedings of Machine Learning Research
%D 2022
%E Katherine M. Kinnaird
%E Peter Steinbach
%E Oliver Guhr	
%F pmlr-v170-glauner22a
%I PMLR
%P 5--9
%U https://proceedings.mlr.press/v170/glauner22a.html
%V 170
%X As a result of the rapidly advancing digital transformation of teaching, universities have started to face major competition from Massive Open Online Courses (MOOCs). Universities thus have to set themselves apart from MOOCs in order to justify the added value of three to five-year degree programs to prospective students. In this paper, we show how we address this challenge at Deggendorf Institute of Technology in ML and AI. We first share our best practices and present two concrete courses including their unique selling propositions: Computer Vision and Innovation Management for AI. We then demonstrate how these courses contribute to Deggendorf Institute of Technology’s ability to differentiate itself from MOOCs (and other universities).

APA


Glauner, P.. (2022). Staying Ahead in the MOOC-Era by Teaching Innovative AI Courses. Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop, in Proceedings of Machine Learning Research 170:5-9 Available from https://proceedings.mlr.press/v170/glauner22a.html.

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