Abstract Thinking of Beginning Electrical Engineering and Computer Science Students

Aharon Gero, Mohammed Ali Hadish, Shahar Kvatinsky

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Abstract thinking is the capability to deal with relevant information for a given phase while temporarily disregarding the irrelevant details for the current step. Abstract thinking is required in a wide variety of disciplines. It is of special importance in engineering, where examining many topics at different detail levels is needed. However, the literature implies that the abstract thinking of beginning students is insufficient. In light of the above, the research aimed to assess the abstract thinking of beginning electrical engineering and computer science students. The study used closed and open-ended instruments, and involved 64 undergraduate students at the Technion – Israel Institute of Technology. According to the findings, the average abstract thinking of the participants is moderate, with no significant difference between the two groups of students.

Original languageEnglish
Title of host publicationTowards a Hybrid, Flexible and Socially Engaged Higher Education - Proceedings of the 26th International Conference on Interactive Collaborative Learning ICL 2023
EditorsM.E. Auer, U.R. Cukierman, Eduardo Vendrell Vidal, Edmundo Tovar Caro
Pages323-328
Number of pages6
DOIs
StatePublished - 2024
Event26th International Conference on Interactive Collaborative Learning, ICL 2023 - Madrid, Spain
Duration: 26 Sep 202329 Sep 2023

Publication series

NameLecture Notes in Networks and Systems
Volume901 LNNS
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389

Conference

Conference26th International Conference on Interactive Collaborative Learning, ICL 2023
Country/TerritorySpain
CityMadrid
Period26/09/2329/09/23

Keywords

  • Abstract Thinking
  • Computer Science Students
  • Electrical Engineering Students

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Signal Processing
  • Computer Networks and Communications

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