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    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/26132

    Title: 以貝氏網路為基礎之微積分適性診斷測驗暨學習系統研發(2/3)
    Authors: 劉湘川
    Contributors: 資訊學院;生物與醫學資訊學系
    Date: 2011
    Issue Date: 2013-07-18 15:33:24 (UTC+8)
    Abstract: 微積分既然是大學工程教育中最重要的基礎科目,也是科學相關領域的學生都必須修這個基礎數學課程,更是踏入高等科學發展的必經歷程。然而現階段微積分課程的教學與評量,大都僅及於紙筆測驗的方式,若以電腦化施測大部分測驗系統還是侷限於選擇題。本計劃所開發「以貝氏網路為基礎之微積分適性診斷測驗暨學習系統」有別於一般將紙筆測驗電腦化,僅提供分數的回饋,本研究所建置之系統透過知識結構選題與貝氏網路的推論,可以適性且精細的找出學生學習的盲點,藉此「因才施測」而後「因才施教」。本系統中也會建置微積分建構反應題型,此題型最大的特色是學生可透過電腦所提供之工具,直接於電腦上操作解題,如此一來,除了像傳統的紙筆測驗可提供學生的答題反應之外,系統亦可記錄學生解題時所使用的工具、解題的歷程與解題的時間,可依據這些資料(答題反應、工具、歷程、算式、與時間)分析出學生的錯誤概念,推論學生能力與錯誤概念。並以實驗設計驗證學生使用本研究建置之「以貝氏網路為基礎之微積分適性診斷測驗暨學習系統」之成效。

    Calculus is one of the most important courses in university mathematics education. Specially for students in scientific area, in order to prepare for future advanced course one need to lay a good foundation of mathematics skills. However in most Calculus curriculums’for teaching and assessment, frequently allow only paperandpencil examinations. Even thought a few examinations are computerized but still limited in the format of choice test. In stead of most “Computer NonAdaptive Testing” only providing the score but back coupling, this program is constructing a “Bayesian Network Calculus Computerized Adaptive Diagnostic Test” and “Learning System”. This system bases on the structure of competence indicators of selected mathematics topics and Bayesian network's deduction. It is adaptive and can discover the learning scotoma of student. We will also establish the Calculus construction response topics system. The significance of the system is to provide a tool where students may precede the problem solving on the computer system directly. Therefore, besides the data provided as traditional written examination, the system may also record how the students use the tools in system when solving problem. In other words, the information of answer response, tool, course, mathematical formula and time of student problem solving can be recorded to analyze student's erroneous picture. These will deduce the student ability and misconception. Finally, we will precede an experience test in class to verify the affectedness of the instruction.
    Appears in Collections:[生物資訊與醫學工程學系 ] 科技部研究計畫

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