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Combining Abstract Tasks and Haptic Material to Foster Computational Thinking in Computer Science Students

Published: 19 June 2023 Publication History

Abstract

Students of Computer Science often struggle with the abstract nature of the content of their studies, especially in the student entry phase. This is partly due to the fact that on the one hand, many first year students possess only moderate abstract thinking skills, while on the other hand, Computer Science lecturers often take the existence of abstract thinking skills for granted, as they themselves are well versed in this area.
To bridge this gap and foster the students’ abstract thinking skills, we employ haptic material to make abstract tasks and the corresponding solution processes more tangible. This supports the development of abstract thinking skills, and at the same time helps to actively engage students in our classes on software development.
In this paper we describe our experiences with active classroom learning units based on haptic materials, as part of our inverted classroom teaching.

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ECSEE '23: Proceedings of the 5th European Conference on Software Engineering Education
June 2023
264 pages
ISBN:9781450399562
DOI:10.1145/3593663
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 June 2023

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Author Tags

  1. CS education
  2. computational thinking
  3. haptic learning material
  4. programming education
  5. student entry phase

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  • Stiftung Innovation in der Hochschullehre

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ECSEE 2023

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Overall Acceptance Rate 11 of 16 submissions, 69%

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