Supervised Classification of Board Games for Active Learning to Enhance Business Knowledge and Skills
| Autor: | Kris Sincharoenkul, Nattapong Tongtep, Lerluck Boonlamp |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Knowledge management
020205 medical informatics Computer science business.industry Process (engineering) Business knowledge Knowledge engineering ComputingMilieux_PERSONALCOMPUTING Decision tree 02 engineering and technology Stratified sampling Game type 03 medical and health sciences 0302 clinical medicine Active learning 0202 electrical engineering electronic engineering information engineering 030212 general & internal medicine business |
| Zdroj: | 2020 17th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON). |
| DOI: | 10.1109/ecti-con49241.2020.9158301 |
| Popis: | Active learning is recognized as one of the innovative and successful education types. Also, game-based learning has been used as an active learning tool in the past decades. Recently, Board games have been recognized and used as a supporting tool in the learning process at various educational levels. So, the purpose of this paper is to develop the learning in business knowledge and skills by gathering, analyzing, and categorizing board games which to be used for each business knowledge and skill learning. In this research, a preliminary experiment is investigated by acquiring 100 games from related economic categories with four different complexity levels. Board game characteristics are extracted as features and five-fold crossvalidation with a stratified sampling technique is applied. The result shows the characteristic of board games categorized into five main business learning fields based on several criteria such as game type, complexity, playing time, and the number of players. Furthermore, the properties of board games can be used to support business knowledge and skills with 49% accuracy using the decision tree classification model. |
| Databáze: | OpenAIRE |
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