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  • 标题:Exploring Students’ Intentions towards Game-Based Learning in Statistics
  • 本地全文:下载
  • 作者:Nur Izzah Binti Jamil ; Alia Nadira Rosle ; Farrah Nadia Baharuddin
  • 期刊名称:International Journal of Academic Research in Business and Social Sciences
  • 电子版ISSN:2222-6990
  • 出版年度:2019
  • 卷号:9
  • 期号:13
  • 页码:389-399
  • DOI:10.6007/IJARBSS/v9-i13/6866
  • 语种:English
  • 出版社:Human Resource Management Academic Research Society
  • 摘要:Game based learning has been used as a learning tool for centuries. This study proposes a development of game-based learning in Statistics subject. The game is a 2D prototype and the game is tested and adjusted to be more effective learning tool for learning. Statistics subject has been used for this study, known as a dreaded subject that causes many negative perceptions as students tend to think that learning Statistics is difficult. Premised on this concern, educators should create potential teaching and learning tool as a vector to challenges the perceived difficulty of learning statistics as well engage the learners and help educators access the learning. The aims of this study are to explore students’ gain of using this teaching and learning tool in Statistics for classroom session and identify the factors affect their intention to use it. A total of 195 students were involved in this study using direct questionnaire and statistically observation through pre and post-test on their statistics test. It is reported that the tests of normality on the distribution for the pre marks with (KS=0.153, SW=0.960, p-value=0.00<0.05) and post marks with (KS=0.122, SW=0.969, p-value=0.00<0.005) both were significantly not normal. Thus, Wilcoxon signed ranks test shows that there is a difference in pre and post score test. This preliminary study shows that there is an improvement in score after students used this teaching and learning tool. Multiple linear regression analysis show that students’ intentions to use is significantly influenced by perceived usefulness (t=2.781, p-value=0.000), perceived ease to use (t=5.949, p-value=0.000) and attitude towards innovation (t=8.545, p-value=0.000). In terms of importance, predictor attitude towards innovation made the largest contribution to the model (Standardized coefficient=0.457).
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