Teaching machine learning to programming novices: An action-oriented didactic concept

Michal Tkáč, Jakub Sieber, Anne Meyer, Lara Kuhlmann, Matthias Brueggenolte, Alexandru Rinciog, Michael Henke, Artur M. Schweidtmann, Qinghe Gao, Maximilian F. Theisen, Radwa El Shawi

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

Abstract

Machine Learning (ML) techniques are encountered nowadays across disciplines, from social sciences, through natural sciences to engineering. However, teaching ML is a daunting task. Aside from the methodological complexity of ML algorithms, both with respect to theory and implementation, the interdisciplinary and empirical nature of the field need to be taken into consideration. This paper introduces the MachineLearnAthon format, an innovative didactic concept designed to be inclusive for students of different disciplines with heterogeneous levels of mathematics, programming, and domain expertise. The format is grounded in a systematic literature review and the didactic principles action orientation, constructivism, and problem orientation. At the heart of the concept lie ML challenges, which make use of industrial data sets to solve real-world problems. Micro-lectures enable students to learn about ML concepts and algorithms, and associated risks. They cover the entire ML pipeline, promoting data literacy and practical skills, from data preparation, through deployment, to evaluation.

Original languageEnglish
Title of host publicationProceedings IDIMT 2024 Changes to ICT, Management, and Business Processes through AI
Subtitle of host publication32nd Interdisciplinary Information Management Talks
EditorsPetr Doucek, Michael Sonntag, Lea Nedomova
Place of PublicationLinz, Austria
PublisherTRAUNER Verlag + Buchservice GmbH
Pages123-131
Number of pages9
ISBN (Electronic)978-3-99151-527-2
DOIs
Publication statusPublished - 2024
Event32nd Interdisciplinary Information Management Talks: Changes to ICT, Management, and Business Processes through AI, IDIMT 2024 - Hradec Kralove, Czech Republic
Duration: 4 Sept 20246 Sept 2024

Publication series

NameSchriftenreihe Informatik
Volume53

Conference

Conference32nd Interdisciplinary Information Management Talks: Changes to ICT, Management, and Business Processes through AI, IDIMT 2024
Country/TerritoryCzech Republic
CityHradec Kralove
Period4/09/246/09/24

Keywords

  • Machine learning
  • education
  • interdisciplinarity
  • didactic concept

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