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Reflections on Teaching Computing

Activity: Talk or presentationInvited talkscience-to-public

Description

Results of my research can be read in my published papers, listed by DBLP or Google scholar. I rather wish to initiate a discussion on teaching computing as to (a) content delivery and (b) content development. Thus my talk will not be exhaustive, but give examples to start a discussion. Several personal experiences over the last year stimulated the choice of this topic: (1) Lack of essential skills and holistic knowledge by some (but not all) computing students, (2) the suggestion of using “work-place observation” as main driver for curriculum development, and (3) the mismatch between aims of the high school curriculum and the high-school teacher education curriculum as to Artificial Intelligence. I will identify potential causes for lack of essential skills by students and contemplate about possible measures in content delivery. As to content development, I do not believe that “work-place observation” should be a main driver. We have to be forward looking since information technology is evolving till students graduate in 3-5+ years and will further evolve during the 35+ years of their future working life. I will look back to the Computer Science curriculum of 1980 at TU/Uni Vienna and argue that its high theory content and its foresight in topics taught trained, from a perspective of almost 30 years later, graduates for a working life. Thus, I am very much convinced that we do the best for our students if we keep or increase theory and fundamentals in our curricula in Computer Science as well as in Business Informatics. Finally, I will argue the case for including a compulsory course on “Introduction to Artificial Intelligence” in teacher education curricula.
Period03 Jun 2019
Event titleAustrian Computer Science Day 2019
Event typeConference
LocationAustriaShow on map

Fields of science

  • 102028 Knowledge engineering
  • 102016 IT security
  • 102027 Web engineering
  • 502050 Business informatics
  • 503008 E-learning
  • 102 Computer Sciences
  • 102030 Semantic technologies
  • 102033 Data mining
  • 102010 Database systems
  • 102035 Data science
  • 102015 Information systems
  • 102025 Distributed systems

JKU Focus areas

  • Digital Transformation