以實驗策略增進學生對資訊科學概念瞭解之研究─子計畫III：以實驗策略增進學生對演算法與資料結構重要概念的瞭解(III)
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Date
2005-10-17
Authors
吳正己
Wu, Cheng-Chih
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Abstract
本計畫的主要目的是規劃使用輔助學習工具之實驗活動，以幫助高中學生學習「演算法及資料結構」的重要觀念。所運用的輔助學習工具包括自行設計的視覺化模擬軟體及可程式化控制的實體機器人。第一年的重點是需求分析與模擬軟體工具的發展，計完成了 SimSort（排序演算法）及 SimDS（陣列及二元樹結構）二個模擬軟體。第二年的重點是模擬軟體實驗活動的設計及使用評估。第三年則是進一步設計使用機器人（LEGO MindStorms）的實驗活動，並評估其使用之效益。研究結果發現，模擬軟體及機器人均有助於相關概念之學習，然而學生的學習興趣仍有待進一步提升。此外，實驗活動學習單的設計，有效的提供了學生實驗進行的指引。而隨著學習輔助工具而來的額外學習負擔及工具本身設計的問題在實驗規劃時均應納入考量。
The purposes of this project were to design laboratory-based learning materials for high school students learning algorithms and data structures concepts and to exam effectiveness of such approach. In the first year, we developed two simulation software, namely SimSort and SimDS. SimSort helps students understand the concept of algorithms through sorting array data. While SimDS experiences students with data structures concepts by comparing searching/inserting data in array and tree structures. The 2nd year we developed three SimSort-based and six SimDS-based lab activities and evaluate their effectiveness by conducting experiment in two high schools. In the final (3rd) year, we developed lab activities which using LEGO MindStorms to help students learn algorithm design concepts. A teaching experiment was also conducted in a local high school. The evaluation results showed that both the simulation software and MindStorms helped students learning the concepts. However, students did not show much interest in using the simulation software and doing the lab activities. We also found that the worksheets designed for lab activities were effective scaffolds in supporting students’learning. Finally, problems accompanied with the use of learning tools, such as additional learning contents and system instability, need to be concerned in designing lab activities.
The purposes of this project were to design laboratory-based learning materials for high school students learning algorithms and data structures concepts and to exam effectiveness of such approach. In the first year, we developed two simulation software, namely SimSort and SimDS. SimSort helps students understand the concept of algorithms through sorting array data. While SimDS experiences students with data structures concepts by comparing searching/inserting data in array and tree structures. The 2nd year we developed three SimSort-based and six SimDS-based lab activities and evaluate their effectiveness by conducting experiment in two high schools. In the final (3rd) year, we developed lab activities which using LEGO MindStorms to help students learn algorithm design concepts. A teaching experiment was also conducted in a local high school. The evaluation results showed that both the simulation software and MindStorms helped students learning the concepts. However, students did not show much interest in using the simulation software and doing the lab activities. We also found that the worksheets designed for lab activities were effective scaffolds in supporting students’learning. Finally, problems accompanied with the use of learning tools, such as additional learning contents and system instability, need to be concerned in designing lab activities.