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

TL;DR

This paper discusses strategies for universities to differentiate their AI and ML courses from MOOCs by sharing best practices and unique course offerings, enhancing their value proposition in a competitive digital education landscape.

Contribution

It presents specific course examples and best practices that help universities stand out from MOOCs in AI education.

Findings

Courses like Computer Vision and Innovation Management for AI enhance university differentiation.

Best practices improve the perceived value of university AI programs.

Concrete course offerings contribute to competitive advantage.

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).