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  • 學位論文

「空氣與燃燒」單元之線上診斷測驗建製與分析

Developing and Analyzing online diagnostic test for the "Air and Combustion"unit

指導教授 : 劉湘川
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摘要


在知識快速變遷的時代裡,網路結合了教育與科技,拋開時間與空間的限制,讓學生學習更方便、更簡單;數位行動教材、數位學習課程及線上教學網站如雨後春筍般應運而生。 本研究嘗試研發自然與生活科技領域之電腦化建構反應題與診斷模式,依據「空氣與燃燒」單元之子技能以設計適合運用電腦化測驗的試題,結合貝氏網路為基礎的數位教材之教學內容,將資訊融入教學課程內容當中,尤以透過電腦呈現建構適性題庫,這是傳統紙筆測驗所無法表達出來的迷思概念,就可以透過這一連串的設計,教師可以透過這一連串的實驗過程,分析學生的迷思概念以及需要補強的部分,針對缺點進行補強的工作。 配合建立自動化分析模型與建置診斷系統,期盼經由電腦網路紀錄學生的解題歷程,分析學生的迷思概念,減輕教師的閱卷負擔,讓學生能立即且有效地得到回饋,同時教學者也能從中獲得學生的學習成效,在最短的時間掌握學生的迷思概念,以便進行補救教學,讓學生的學習更完善。 研究結果發現: 1. 學生在「空氣與燃燒」單元之電腦化建構反應題與診斷模式測驗時,呈現樣本中具有異於選擇題之迷思概念,顯示此測驗能診斷出學生多元的能力。 2. 此系統判斷迷思概念平均正確率可達99%,顯示本測驗診斷模式成效優異。 由以上結果可知,本研究所建置的電腦化建構反應題與診斷模式開發,可達到因材施教目的,對於學生學習能力可顯著提升教學成效的。 關鍵詞:電腦化建構反應題、子技能、迷思概念。

並列摘要


Rapid changes in the knowledge era, the Internet combined with the education and science and technology, set aside time and space constraints, so that students learn more convenient, easier; Digital Action Jiao Cai, e-learning courses and online teaching sites are springing into being . This study attempts to develop the natural and life science and technology of computerized building response questions and diagnostic model, based on ”air and combustion” unit of the sub-skills to design for the use of computerized test questions, combined with Bayesian network-based digital teaching materials for teaching content, together with information into the teaching curriculum of which, especially through the construction of computer adaptive question bank show, which is expressed in the traditional pencil and paper tests are not misconceptions, we can through this series of design, teachers can, through this series of experiment, analysis of student misconceptions and the need for some reinforcement for the work reinforce shortcomings. With the model and build an automated diagnostic system, looking forward to record the students through a computer network problem solving processes, analysis of student misconceptions, relieve teachers of the scoring burden, so that students can get feedback immediately and effectively, while also teaching those who obtained from the effectiveness of learning, students in the shortest possible time to grasp the concept of myth for remedial instruction for students to learn better. The results showed: 1. Students in the ”air and combustion” unit of computerized diagnostic model constructed response questions and tests, the samples show different from the multiple-choice questions with the misconception, showing that this test can diagnose the capacity of diverse students. 2. This system determine the correct misconceptions the average rate of 99%, showing excellent results in this test diagnostic mode. These results show that, in this study build computerized diagnostic model constructed response questions and the development can be individualized to achieve the purpose for learning ability can significantly enhance teaching effectiveness. Key words: computerized construct reaction problems, child skills, misconceptions.

參考文獻


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被引用紀錄


梁志強(2011)。人工智慧方法於線上診斷測驗之應用~以國小五年級「表面積」為例〔碩士論文,亞洲大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0118-1511201215470386

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