Enhancing Students’ Learning Outcomes of a STEAM Permutations Course Through a Game Based Visual Programming Environment with Qualifying Rank Strategy

Yu Che Huang, Yueh Ming Huang, Andreja Istenic Starcic

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

Abstract

The main purpose of this research is to develop a visual programming game with a Qualifying Rank strategy (QRVPG), allowing learners to use this system to conduct a STEAM-oriented mathematics course, the content of which is permutation. In the QRVPG system, learners can perform learning tasks with lower cognitive levels in their personal game copies to understand and construct knowledge, as the level of the game role increases, levels with higher cognitive levels will also appear. Then, learners are necessary to analyze and apply the knowledge they learned to complete more difficult learning tasks. In addition, learners can compete in the QRVPG system. This research hopes to introduce the qualifying rank strategy to allow learners with similar abilities to compete with each other, through this way, enhance learners’ learning motivation and engagement. In general, this research hopes to improve learners’ core competence in all aspects of STEAM through the cooperation of game formation and the gradual development of cognitive level.

Original languageEnglish
Title of host publicationInnovative Technologies and Learning - Third International Conference, ICITL 2020, Proceedings
EditorsTien-Chi Huang, Ting-Ting Wu, João Barroso, Frode Eika Sandnes, Paulo Martins, Yueh-Min Huang
PublisherSpringer Science and Business Media Deutschland GmbH
Pages93-99
Number of pages7
ISBN (Print)9783030638849
DOIs
Publication statusPublished - 2020
Event3rd International Conference on Innovative Technologies and Learning, ICITL 2020 - Porto, Portugal
Duration: 2020 Nov 232020 Nov 26

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12555 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd International Conference on Innovative Technologies and Learning, ICITL 2020
CountryPortugal
CityPorto
Period20-11-2320-11-26

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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