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    題名: 具有產生參考解答功能的高中化學計算問題生成系統
    A generation system for high school chemistry word problems with accompanying solutions
    作者: 張博城
    Zhang, Bo Cheng
    貢獻者: 陳正佳
    Chen, Cheng Chia
    張博城
    Zhang, Bo Cheng
    關鍵詞: 邏輯程式語言
    有效數字計算
    人工四則運算複雜度
    化學單位計算
    Answer set programing
    Django
    Significant figures calculator
    Chemical unit calculator
    Hypergraph
    日期: 2018
    上傳時間: 2018-06-12 17:58:38 (UTC+8)
    摘要: 近年線上教學平台有著很大的發展,不管是國內的均一教學平台,或國外知名的可汗教育平台,都提供各種學科便利學生自主學習。而在高中化學計算的領域中,這些平台上均提供各種教學課程。美中不足的是在線上的練習系統中,往往題目數量少、題目變化少、無詳細解題步驟,這樣將不足以透過題目衡量一個學生在各個主題的學習上有無明顯的進步。
    本論文的目的是改善上述問題。我們設計並實做一系統,只要使用者輸入簡單需求,即可自動產生高中化學問題以及伴隨詳細解答,可方便出題者快速產生各式不同主題的高中化學應用題目。我們的系統提供一個Web前端供使用者輸入所需要生成的題目之資訊。系統由此收齊相關參數之後,接著即可依據參數產生符合題目限制條件的化學問題生成模型。此問題模型為一hypergraph,節點代表已知或未知相關化學量,超連結(hyperedge)則代表數個化學量間的相依關係。有了此一以ASP(Answer Set Programming)表達的問題模型之後,系統即可利用ASP求解器(Solver)進行單一或多個題目生成,後續工作則是驗證每一生成題目之可行性並產生解題步驟,最後經由Django整合呈現於Web上。
    In recent years there has been great progress in the development of online learning. Well-known platforms such as international Khan Academic or local Junyi Academy in Taiwan provide courses in various subjects allowing interested students to study in a very convenient and autonomous way. As expected, courses on common subjects such as high school chemistry are offered with rich content by these platforms. However, there are shortcomings in these courses about the problems they provide for the students to practice or test. In addition to rich content, an ideal course should provide abundant problems of all possible topics, with each given detailed solution, so that students can evaluate their achievement of study by practicing or testing themselves with these problems. Unfortunately, no courses on these platforms meet the above requirements.
    The purpose of this thesis is to improve the above shortcoming by providing a system which can generate automatically word problems on various topics of high school chemistry, together with detailed accompanied solutions. Our system is a web-based application implemented using Django. It provides a front-end enabling the users to enter related information for the word problems they want the system to generate. According to the parameters collected from the front-end, our system will generate a corresponding chemical problem model. The model is a hypergraph with nodes representing known or unknown chemical quantities related to the problem and hyperedges representing relations or dependencies among these quantities. After the model is generated as a logic program of ASP(Answer-set Programming), the system will use an ASP solver to generate one or more candidate problems. Subsequent works are then used to verify the feasibility of each problem and produce a solution for the feasible one. Finally the generated problems as well as solutions are wrapped in the server side and then sent to and presented friendly in the client's browser.
    參考文獻: [1]. David Goldberg & Ronald J. Zanni. (2001). How to Solve Word Problems in Chemistry, Scientific Calculations (1st ed., chap. 1, pp. 9-21). USA, New York: McGraw-Hill Education
    [2]. Michael B. Cutlip & Mordecai Shacham. (1999). Problem Solving in Chemical Engineering with Numerical Methods(1st ed., chap. 2, pp. 41-84). USA, New Jersey: Prentice Hall
    [3]. Giorgio Ausiello & L.Laura. (2017). Directed Hypergraphs: Introduction and fundamental algorithms—a survey. Theoretical Computer Science, 658, 293-306
    [4]. International System of Units. Retrieved May (2017). From https://en.wikipedia.org/ wiki/International_System_of_Units
    [5]. Physical quantities (numerical value with units) in Python API. Retrieved May (2017). From https://bitbucket.org/birkenfeld/ipython-physics
    [6]. Answer Set Programming. Retrieved May (2017). From https://en.wikipedia.org/wiki/ Answer_set_programming
    [7]. Significant figures. Retrieved May (2017). From https://en.wikipedia.org/wiki/ Significant_figures
    [8]. Numpy. Retrieved May (2017). From http://www.numpy.org/
    [9]. Clingo. Retrieved May (2017). From https://potassco.org/
    [10]. Clingo Python API. Retrieved May (2017). From https://potassco.org/clingo/python-api/current/clingo.html
    [11]. Django. Retrieved May (2017). From https://www.djangoproject.com/
    [12]. Rohit Singh , Sumit Gulwani & Sriram Rajamani . (2012). Automatically Generating Algebra Problems. AAAI'12 Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence (pp. 1620-1627). Canada
    [13]. Yi Chung Lin, Chao-Chun Liang, Kuang-Yi Hsu, Chien-Tsung Huang, Shen-Yun Miao, Wei-Yun Ma, …Keh-Yih Su. (2015). Designing a Tag-Based Statistical Math Word Problem Solver with Reasoning and Explanation. The 27th Conference on Computational Linguistics and Speech Processing (ROCLING 2015). Hsinchu
    [14]. Declarative programming. Retrieved May (2017). From https://en.wikipedia.org/ wiki/Declarative_programming
    [15]. Non-monotonic logic. Retrieved May (2017). From https://en.wikipedia.org/wiki/Non-monotonic_logic
    [16]. Imperative programming. Retrieved May (2017). From https://en.wikipedia.org/wiki/ Imperative_programming
    [17]. 化學計量法。Retrieved May (2017). From https://zh.wikipedia.org/zh-tw/化学计量数
    [18]. 依數性。Retrieved May (2017). From https://en.wikipedia.org/wiki/ Colligative_ properties
    [19]. 除法。Retrieved May (2017). From https://zh.wikipedia.org/wiki/除法
    [20]. 長除法過程。Retrieved May (2017). From https://commons.wikimedia.org/w/ index.php? curid=5818667
    [21]. 化學反應列表。Retrieved May (2017). From https://zh.wikipedia.org/wiki/化学反应方程式列表
    [22]. 直式計算。 Retrieved May (2017). From https://zh.wikipedia.org/wiki/进位
    [23]. 李連順(2000)。國中生活科技線上測驗系統發展研究(未出版之碩士論文)。國立高雄師範大學,高雄市。
    [24]. Tappei Yoshida, Takuya Matsuzaki & Satoshi Sato. (2015, May). 大学入試化学の計算問題の自動解答. The 29th Annual Conference of the Japanese Society for Artificial Intelligence. Japan
    [25]. Python decimal Retrieved May (2017). From https://docs.python.org/2/library/ decimal.html
    [26]. V. Lifschitz. (2002). Answer set programming and plan generation. Artificial Intelligence, 138,39–54
    [27]. Python Dictionary. May (2017) https://docs.python.org/3/tutorial/datastructures.html
    描述: 碩士
    國立政治大學
    資訊科學學系
    103753022
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G0103753022
    資料類型: thesis
    顯示於類別:[資訊科學系] 學位論文

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