A Proposed Framework for Simulation Based Learning of Inheritance

Abdelbaset Abdellatif, Barry McCollum

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)
266 Downloads (Pure)

Abstract

Different types of serious games have been used in elucidating computer science areas such as computer games, mobile games, Lego-based games, virtual worlds and webbased games. Different evaluation techniques have been conducted like questionnaires, interviews, discussions and tests. Simulation have been widely used in computer science as a motivational and interactive learning tool. This paper aims to evaluate the possibility of successful implementation of simulation in computer programming modules. A framework is proposed to measure the impact of serious games on enhancing students understanding of key computer science concepts. Experiments will be held on the EEECS of Queen’s University Belfast students to test the framework and attain results.
Original languageEnglish
Title of host publication2016 UKSim-AMSS 18th International Conference on Computer Modelling and Simulation (UKSim)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
ISBN (Electronic)978-1-5090-0888-9
ISBN (Print)978-1-5090-0889-6
DOIs
Publication statusPublished - 26 Dec 2016
EventUKSim-AMSS 18th International Conference on Modelling & Simulation - Cambridge University , Cambridge, United Kingdom
Duration: 06 Apr 201608 Apr 2016
Conference number: 18
http://uksim2016.info/

Conference

ConferenceUKSim-AMSS 18th International Conference on Modelling & Simulation
CountryUnited Kingdom
CityCambridge
Period06/04/201608/04/2016
Internet address

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Keywords

  • Simulation
  • e-learning
  • Computer science
  • Serious games
  • Robocode

Cite this

Abdellatif, A., & McCollum, B. (2016). A Proposed Framework for Simulation Based Learning of Inheritance. In 2016 UKSim-AMSS 18th International Conference on Computer Modelling and Simulation (UKSim) Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/UKSim.2016.26