TY - GEN
T1 - Enhancing Students’ Learning Outcomes of a STEAM Permutations Course Through a Game Based Visual Programming Environment with Qualifying Rank Strategy
AU - Huang, Yu Che
AU - Huang, Yueh Ming
AU - Starcic, Andreja Istenic
N1 - Funding Information:
Acknowledgements. This research is partially supported by the Ministry of Science and Technology, Taiwan, R.O.C. under Grant no. MOST 109-2511-H-006-011-MY3 and MOST 106-2511-S-006-001-MY3.
Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
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U2 - 10.1007/978-3-030-63885-6_11
DO - 10.1007/978-3-030-63885-6_11
M3 - Conference contribution
AN - SCOPUS:85097565133
SN - 9783030638849
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 93
EP - 99
BT - Innovative Technologies and Learning - Third International Conference, ICITL 2020, Proceedings
A2 - Huang, Tien-Chi
A2 - Wu, Ting-Ting
A2 - Barroso, João
A2 - Sandnes, Frode Eika
A2 - Martins, Paulo
A2 - Huang, Yueh-Min
PB - Springer Science and Business Media Deutschland GmbH
T2 - 3rd International Conference on Innovative Technologies and Learning, ICITL 2020
Y2 - 23 November 2020 through 26 November 2020
ER -