Advertisement

Five Inspiring Course (Re-)Designs

Examples of Innovations in Teaching and Learning BISE
  • Stefan StreckerEmail author
  • Ulrike Baumöl
  • Dimitris Karagiannis
  • Agnes Koschmider
  • Monique Snoeck
  • Rüdiger Zarnekow
Discussion
  • 24 Downloads

Introduction

The innovation of teaching and, correspondingly, learning in higher education has been producing numerous examples of inspiring and stimulating course designs and redesigns only too rarely reported. Tying in with Strecker et al. (2018), the present compilation adds five examples of innovative course (re-)designs, each including a reflection on student and instructor appraisal (“lessons learned”). Intended as a contribution to sharing teaching experiences much like flying pilots practice knowledge sharing, and to inspire further reflection on teaching and learning in higher education, the contributions in this compilation discuss course (re-)designs from introductory courses to more advanced courses in five different institutional settings.

Ulrike Baumöl discusses the challenges of redesigning an existing course and places the challenges she faces as a course instructor in the wider context of societal change. Among others, mixing media including videos produced by the...

References

  1. Bork D, Fill HG, Karagiannis D, Miron ET, Tantouris N (2015) Walch M (2015) Conceptual modelling for smart cities: a teaching case. Interact Des Archit 27:10–28Google Scholar
  2. Bork D, Buchmann R, Hawryszkiewycz I, Karagiannis D, Tantouris N, Walch M (2016) Using conceptual modeling to support innovation challenges in smart cities. In: 14th IEEE international conference on smart city, Sydney, pp 1317–1324Google Scholar
  3. Bork D, Buchmann RA, Karagiannis D, Moonkun L, Miron ET (2019) An open platform for modeling method conceptualization: The OMiLAB digital ecosystem. Commun Assoc Inf Syst (under review)Google Scholar
  4. Buchmann RA, Ghiran AM (2017) Engineering the cooking recipe modelling method: a teaching experience report. In: Proceedings of PrOse 2017, CEUR-WS 1999(5). ftp://SunSITE.Informatik.RWTH-Aachen.DE/pub/publications/CEUR-WS/Vol-1999.zip. Accessed 23 Jan 2019
  5. Crook C, Schofield L (2017) The video lecture. Internet High Educ 34:56–64CrossRefGoogle Scholar
  6. Dieterle S, Koschmider A, Reichenberger T, Schoder D (2018) Crowde: Individuelles Lernen durch individualisierte Klausuren. In: Krömker D, Schroeder U (Eds.) DeLFI 2018 - Die 16. E-Learning Fachtagung Informatik, Goethe-Universität Frankfurt am Main, 10.-13. September 2018. Lecture notes in informatics, vol 248, pp 287–288Google Scholar
  7. Erenli K (2016) Generation I(mmersion) – how to meet learner expectations of tomorrow. Int J Adv Corp Learn 9(1):19–25CrossRefGoogle Scholar
  8. Guo PJ, Kim J, Rubin R (2014) How video production affects student engagement: an empirical study of MOOC videos. In: 1st ACM conference on learning @ Scale, Atlanta, pp 41–50Google Scholar
  9. Guthrie CH (2014) Who are we teaching? The learning expectations of “digital tribes” in the classroom. Int J e-Educ e-Bus e-Manag e-Learn 4(2):146–150Google Scholar
  10. Hattie J, Timperley H (2007) The power of feedback. Rev Educ Res 77(1):81–112CrossRefGoogle Scholar
  11. Jung R, Lehrer C (2017) Guidelines for education in business and information systems engineering at tertiary institutions. Bus Inf Syst Eng 59(3):189–203CrossRefGoogle Scholar
  12. Karagiannis D (2016) Conceptual modelling methods: the AMME agile engineering approach. In: International conference on informatics in economy, LNBIP 273, Springer, pp 3–19Google Scholar
  13. Karagiannis D, Buchmann RA, Burzynski P, Reimer U, Walch M (2016a) Fundamental conceptual modeling languages in OMiLAB. In: Domain-specific conceptual modeling. Springer, Cham pp 3–30Google Scholar
  14. Karagiannis D, Mayr HC, Mylopoulos J (2016b) Domain-specific conceptual modeling. Springer, New YorkCrossRefGoogle Scholar
  15. Karagiannis D, Burzynski P, Miron ET (2017) The IMKER case study. http://vienna.omilab.org/repo/files/Bee-Up/The_IMKER_Case_Study.pdf. Accessed 2 July 2018
  16. Koschmider A, Buschfeld D (2016) Shifting the process of exam preparation towards active learning: a crowdsourcing based approach. In: Informatik 2016. Lecture Notes in Informatics, vol 259Google Scholar
  17. Koschmider A, Schaarschmidt M (2017) A crowdsourcing-based learning approach to activate active learning. In: DeLFI & Bildungsräume 2017, Lecture Notes in Informatics, vol 273, pp 99–10Google Scholar
  18. Krathwohl DR (2002) A revision of Bloom’s taxonomy: an overview. Theory Pract 41:212–218CrossRefGoogle Scholar
  19. Lehmann K, Söllner M, Leimeister JM (2015) Der Wert von IT-gestütztem Peer Assessment zur Unterstützung des Lernens in einer universitären Massenlehrveranstaltung. https://www.alexandria.unisg.ch/239338/. Accessed 19 Dec 2018
  20. McPherson MS, Bacow LS (2015) Online higher education: beyond the hype cycle. J Econ Perspect 29(4):135–154CrossRefGoogle Scholar
  21. Österle H, Becker J, Frank U, Hess T, Karagiannis D, Krcmar H, Loos P, Mertens P, Oberweis A, Sinz E (2011) Memorandum on design-oriented information systems research. Eur J Inf Syst 20(1):7–10CrossRefGoogle Scholar
  22. Pinzaru F, Vatamanescu E, Mitan A, Vitelar A, Savulescu R, Noaghea C, Balan M (2016) Millennials at work: investigating the specificity of generation Y versus other generations. Manag Dyn Knowl Econ 4(2):173–192Google Scholar
  23. Sandkuhl K, Fill HG, Hoppenbrouwers S, Krogstie J, Leue A, Matthes F, Opdahl A, Schwabe G, Uludag O, Winter R (2016) Enterprise modelling for the masses—from elitist discipline to common practice. In: Proceedings of PoEM 2016, LNBIP 267, Springer, pp 225–240Google Scholar
  24. Sedrakyan G, Snoeck M (2017) Cognitive feedback and behavioral feedforward automation perspectives for modeling and validation in a learning context. In: International conference on model-driven engineering and software development. CCIS, vol 692, Springer, pp 70–92Google Scholar
  25. Sedrakyan G, Snoeck M, Poelmans S (2014) Assessing the effectiveness of feedback enabled simulation in teaching conceptual modeling. Comput Educ 78:367–382CrossRefGoogle Scholar
  26. Sedrakyan G, De Weerdt J, Snoeck M (2016) Process-mining enabled feedback: “tell me what I did wrong” vs. “tell me how to do it right”. Comput Hum Behav 57:352–376CrossRefGoogle Scholar
  27. Sedrakyan G, Poelmans S, Snoeck M (2017) Assessing the influence of feedback-inclusive rapid prototyping on understanding the semantics of parallel UML statecharts by novice modelers. Inf Softw Technol 82:159–172CrossRefGoogle Scholar
  28. Serral Asensio E, Snoeck M (2016) Conceptual framework for feedback automation in SLEs. Smart Educ E-Learn. Springer, Cham, pp 97–107Google Scholar
  29. Serral Asensio E, De Weerdt J, Sedrakyan G, Snoeck M (2016) Automating immediate and personalized feedback taking conceptual modelling education to a next level. In: IEEE 10th international conference on research challenges in information science, Grenoble, p 439Google Scholar
  30. Snoeck M, Haesen R, Buelens H, De Backer M, Monsieur G (2007) Computer aided modelling exercises. Inform Educ 6(1):231–248Google Scholar
  31. Strayer JF (2012) How learning in an inverted classroom influences cooperation, innovation and task orientation. Learn Environ Res 15(2):171–193CrossRefGoogle Scholar
  32. Strecker S, Kundisch D, Lehner F, Leimeister JM, Schubert P (2018) Higher education and the opportunities and challenges of educational technology. Bus Inf Syst Eng 60(2):181–189CrossRefGoogle Scholar
  33. The ADOxx metamodeling platform (2018) https://www.adoxx.org/. Accessed 2 July 2018
  34. The BEE-UP Modeling Tool (2018) http://austria.omilab.org/psm/content/bee-up. Accessed 2 July 2018
  35. The OMiLAB web portal (2018) http://austria.omilab.org/. Accessed 2 July 2018
  36. Van Merriënboer JJ, Kirschner PA (2012) Ten steps to complex learning: a systematic approach to four-component instructional design. Routledge, New YorkCrossRefGoogle Scholar
  37. Walch M (2018) Operating cyber-physical systems with microservices: the s*IoT conceptual modelling approach. In: Accepted for 7th international congress on advanced applied informatics, YonagoGoogle Scholar

Copyright information

© Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature 2019

Authors and Affiliations

  • Stefan Strecker
    • 1
    Email author
  • Ulrike Baumöl
    • 1
  • Dimitris Karagiannis
    • 2
  • Agnes Koschmider
    • 3
  • Monique Snoeck
    • 4
  • Rüdiger Zarnekow
    • 5
  1. 1.University of HagenHagenGermany
  2. 2.University of ViennaViennaAustria
  3. 3.Karlsruhe Institute of TechnologyKarlsruheGermany
  4. 4.KU LeuvenLeuvenBelgium
  5. 5.Technische Universität BerlinBerlinGermany

Personalised recommendations