研究生: |
何品萱 He, Pin-Xuan |
---|---|
論文名稱: |
應用擴增實境學習輔助與教學策略對高低先備知識國中生機器人程式設計學習成效及動機之影響 The Effects of AR-based Learning Assistance and Instructional Strategy on Junior High Students’ Learning Performance and Motivation in Robot Programming |
指導教授: |
陳明溥
Chen, Ming-Puu |
學位類別: |
碩士 Master |
系所名稱: |
資訊教育研究所 Graduate Institute of Information and Computer Education |
論文出版年: | 2017 |
畢業學年度: | 105 |
語文別: | 中文 |
論文頁數: | 147 |
中文關鍵詞: | 程式設計 、擴增實境 、教學策略 、機器人教學 、先備知識 |
英文關鍵詞: | programming, AR, instructional strategy, robotic instruction, prior knowledge |
DOI URL: | https://doi.org/10.6345/NTNU202202541 |
論文種類: | 學術論文 |
相關次數: | 點閱:214 下載:16 |
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本研究旨在探討應用不同學習輔助與教學策略對先備知識國中生在機器人程式設計學習成效及動機之影響。本研究使用Mbot機器人及Scratch程式設計軟體進行實驗教學,並以擴增實境技術搭配智慧型眼鏡在實作程式時,同步擴增虛擬提示資訊以輔助學習者的程式撰寫。研究對象為八年級學習者,有效樣本132人,實驗採用因子設計之準實驗研究法,自變項包含學習輔助型態、教學策略與先備知識。學習輔助依型態分為「擴增實境學習單」與「紙本學習單」,教學策略分為「演示範例」及「問題導向」,學習者的先備知識則分為「高先備知識」與「低先備知識」;依變項包含程式設計學習成效與學習動機。
研究結果顯示:就學習成效而言,(1)在知識理解方面,使用擴增實境學習輔助之學習者在知識理解表現上,優於使用紙本學習輔助之學習者、高先備知識學習者的知識理解表現優於低先備知識學習者、演示範例及問題導向教學策略的學習者則無顯著差異;(2)在知識應用方面,使用問題導向策略的學習者在知識應用表現上優於使用演示範例策略的學習者;使用擴增實境學習輔助時,高先備知識學習者的知識應用表現優於低先備知識學習者、高先備知識學習者,使用擴增實境學習輔助其知識應用表現優於使用紙本學習輔助、低先備知識學習者,不論使用擴增實境及紙本學習輔助或演示範例及問題導向策略皆無顯著差異。在學習動機方面,(3)各實驗組學習者對學習活動皆抱持正向的學習動機,而且使用擴增實境學習輔助的學習者有較高的學習動機。
The purpose of this study was to investigate the effects of two types of learning assistance and instructional strategy with different levels of prior knowledge on junior high school students’ learning performance and motivation in robot programming. This study used Mbot and Scratch for teaching robot programming, combining AR technology with Bt-200 smart glasses which provided programming instruction to help the students with program coding. A quasi-experimental design was employed with type of learning assistance, instructional strategy, and prior knowledge as the independent variables. The participants were the eighth graders and the effective sample size was 132. While the learning assistance consisted of the AR-based sheets and the paper sheets, the instructional strategies included the worked examples and the problem-based learning; the prior knowledge involved high and low prior knowledge. The dependent variables were the students’ learning performance and motivation in robot programming.
The results showed that: (a) for knowledge comprehension performance, the AR-based sheets group outperformed the paper sheets group and high prior knowledge group outperformed the low prior knowledge group, whereas there was no significant difference between the instructional strategies of worked examples and the problem-based learning; (b) concerning the knowledge application, the problem-based learning group outperformed the worked examples group; moreover, high prior knowledge group outperformed the low prior knowledge group when using the AR-based learning assistance; furthermore, in the high prior knowledge group, the learners using AR-based learning assistance outperformed the learners using paper learning assistance, whereas there was no significant difference between the learners in the low prior knowledge group when employing different types of learning assistance and or instructional strategy; and (c) with respect to the learning motivation, all participants showed positive motivation toward the employed learning activity, and the AR-based sheets group particularly showed higher level of participation.
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