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Machine Learning Unplugged - Development and Evaluation of a Workshop About Machine Learning

  • Elisaweta OssovskiEmail author
  • Michael Brinkmeier
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11913)

Abstract

Machine learning, being an important part of artificial intelligence, is increasingly discussed and rated in the media without explaining its functionality. This can lead to misconceptions of its real impact and range of application, a problem especially concerning young people. This contribution focuses on the theory-driven development and practical experience with an unplugged workshop concept, which is about a simple technique of machine learning, as a basis for possible teaching units for high school students. For this purpose, the focus of the workshop is an action-oriented method to simulate the classification of screws with two different lengths. Workshop participants can reconstruct linear classification by moving a classifier represented by a wooden strip according to defined rules after each insertion of training data on a pinboard. The aim is to examine whether and how the topic can be made understandable at school. Pre- and posttests are used to evaluate the impact of the workshop on the participants’ image of artificial intelligence and machine learning. The results of this research suggest that it is possible to reduce simple methods of machine learning for teaching this topic at school. Moreover, it seems that even a 90-min workshop can change the participants’ conceptions of machine learning and artificial intelligence to a more realistic appreciation of their impact.

Keywords

Machine learning Linear classification Unplugged K-12 education 

References

  1. 1.
    CS Unplugged - Computer Science without a computer. https://classic.csunplugged.org/. Accessed 19 Aug 2019
  2. 2.
    Bortz, J., Schuster, C.: Statistik für Human- und Sozialwissenschaftler [Statistics for human and social scientists], vol. 7. Springer, Heidelberg (2010).  https://doi.org/10.1007/978-3-642-12770-0CrossRefGoogle Scholar
  3. 3.
    Döring, N., Bortz, J.: Forschungsmethoden und Evaluation in den Sozial- und Humanwissenschaften [Research methods and evaluation in the social sciences and humanities], vol. 5. Springer, Heidelberg (2016).  https://doi.org/10.1007/978-3-642-41089-5CrossRefGoogle Scholar
  4. 4.
    Ertel, W.: Introduction to Artificial Intelligence. Springer, London (2011).  https://doi.org/10.1007/978-0-85729-299-5CrossRefGoogle Scholar
  5. 5.
    Gudjons, H.: Handlungsorientiert lehren und lernen: Schüleraktivierung Selbsttätigkeit Projektarbeit [Action-oriented teaching and learning: student activation - self-activity - project work], vol. 8. Klinkhardt Bad Heilbrunn (2014)Google Scholar
  6. 6.
    Hefendehl-Hebeker, L., Schwank, I.: Arithmetik: Leitidee Zahl [Arithmetic: central idea number]. In: Bruder, R., Hefendehl-Hebeker, L., Schmidt-Thieme, B., Weigand, H.-G. (eds.) Handbuch der Mathematikdidaktik [Guide of mathematical didactics], pp. 77–115. Springer, Heidelberg (2015).  https://doi.org/10.1007/978-3-642-35119-8_4. Chap. 4CrossRefGoogle Scholar
  7. 7.
    Lindner, A., Seegerer, S.: AI Unplugged - Wir ziehen künstlicher Intelligenz den Stecker [AI Unplugged - we pull the plug on artificial intelligence]. https://ddi.cs.fau.de/schule/ai-unplugged/. Accessed 07 May 2019
  8. 8.
    Meyer, H.: Unterrichtsmethoden II: Praxisband [Teaching methods II: practical book], 14 edn. Cornelsen Scriptor Berlin (2011)Google Scholar
  9. 9.
    Ministerium für Schule und Weiterbildung des Landes Nordrhein-Westfalen: Kernlehrplan für die Sekundarstufe II Gymnasium/Gesamtschule in Nordrhein-Westfalen Informatik [Curriculum for secondary level II high school/comprehensive school in north rhine-westfalia computer science]. https://www.schulentwicklung.nrw.de/lehrplaene/upload/klp_SII/if/KLP_GOSt_Informatik.pdf (2014). Accessed 07 May 2019
  10. 10.
    Niedersächsisches Kultusministerium: Kerncurriculum für die Schulformen des Sekundarbereichs I Schuljahrgänge 5–10 [Curriculum for school types in lower secondary education years 5–10]. http://db2.nibis.de/1db/cuvo/datei/kc_informatik_sek_i.pdf (2014). Accessed 07 May 2019
  11. 11.
    Niedersächsisches Kultusministerium: Kerncurriculum für das Gymnasium - gymnasiale Oberstufe, die Gesamtschule -gymnasiale Oberstufe, das Kolleg Informatik [Curriculum for high school - upper school, comprehensive school - upper school, college in computer science]. http://www.db2.nibis.de/1db/cuvo/datei/inf_go_kc_druck_2017.pdf (2017). Accessed 27 Aug 2019
  12. 12.
    Rodriguez, B., Rader, C., Camp, T.: Using student performance to assess CS unplugged activities in a classroom environment. In: Proceedings of the 2016 ACM Conference on Innovation and Technology in Computer Science Education, ITiCSE 2016, pp. 95–100. ACM, New York (2016).  https://doi.org/10.1145/2899415.2899465
  13. 13.
    Staatsinstitut für Schulqualität und Bildungsforschung München: Jahrgangsstufen-Lehrplan 11/12 Informatik [Computer science curriculum for years 11/12]. http://www.isb-gym8-lehrplan.de/contentserv/3.1.neu/g8.de/index.php?StoryID=26193 (2004). Accessed 07 May 2019
  14. 14.
    Staatsinstitut für Schulqualität und Bildungsforschung München: Der Lehrplan für das Gymnasium in Bayern im überblick [The curriculum for the high school in bavaria at a glance]. https://www.isb.bayern.de/download/1555/broschuere-der-lehrplan-im-ueberblick.pdf (2010). Accessed 07 May 2019
  15. 15.
    Thies, R., Vahrenhold, J.: On plugging “Unplugged” into CS classes. In: Proceeding of the 44th ACM Technical Symposium on Computer Science Education, SIGCSE 2013, pp. 365–370. ACM, New York (2013).  https://doi.org/10.1145/2445196.2445303

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Universität OsnabrückOsnabrückGermany

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