Chapter 1 INTRODUCTION 1.1 Background of the Study It has been said that modeling the learner is the central aspect of intelligent tutoring systems. This realization spurred the development of student modeling systems or systems that diagnose student errors. These systems proved to be effective in areas like mathematics (subtraction, highschool algebra, differentiation) and computer programming (Pascal, Lisp,C++). The essential elements in constructing a student model are the background knowledge
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logical structure 物理结构 phyical structure 线性结构 linear structure 非线性结构 nonlinear structure 基本数据类型 atomic data type 固定聚合数据类型 fixed-aggregate data type 可变聚合数据类型 variable-aggregate data type 线性表 linear list 栈 stack 队列 queue 串 string 数组 array 树 tree 图 grabh 查找，线索 searching 更新 updating 排序（分类) sorting 插入 insertion 删除 deletion 前趋 predecessor 后继 successor 直接前趋 immediate predecessor 直接后继 immediate successor 双端列表 deque(double-ended queue) 循环队列 cirular queue 指针 pointer 先进先出表（队列） first-in
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and anything that has been sent. This will also allow the coordination of meetings, appointments, contacts and all public folders to share access. If one or more domain exist, as in a merger, you can combine the multiple domains into a hierarchical tree structure. If one company is using its own dedicated DNS server this is the best possible solution. We also need all of the afore mentioned information so we can set up a DNS forwarding solution. This will help to improve the efficiency of name resolutions
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Questions for the Merck Case Create a decision tree for Merck. The 2 leftmost branches would identify the alternatives related to licensing Davarink (specifically license versus not to license). Next, if Merck decides to pursue license, they go into phase I which results in a success, or failure. Phase I success is followed by phase II where Merck has the opportunity to develop the drug to treat depression alone, weight loss alone, or both, or contemplate phase II failure. Finally phase
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MIDTERM: CS 6375 INSTRUCTOR: VIBHAV GOGATE October, 23 2013 The exam is closed book. You are allowed a one-page cheat sheet. Answer the questions in the spaces provided on the question sheets. If you run out of room for an answer, use an additional sheet (available from the instructor) and staple it to your exam. • NAME • UTD-ID if known • SECTION 1: • SECTION 2: • SECTION 3: • SECTION 4: • SECTION 5: • Out of 90: 1 CS 6375 FALL 2013 Midterm, Page 2 of 13 October
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Section 9.1 Exercise 2 The graph is not a tree, because there more than one paths from one vertex to another. Exercise 3 The graph is not a tree, because not all of the vertices of the graph are connected. Thus, there is no an existing unique path between some vertices. Exercise 9 The height of the tree in the Exercise 8 is 4 Exercise 10 [pic] The height of this tree is 5 Exercise 12 An example of the hierarchical relationship is a family tree: [pic] Section 9.2 Exercise 5 Siblings
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It was a warm, cloudy, winter day in Gordon, Wisconsin. The trees were leafless and brown, with the exception of the pine trees which had all their green needles still hanging on to the tree. Julianne, Anja and their dog Flynn were going out to their fort by the river that flowed behind their house. Julianne Huesby was a thirteen-year-old girl. She was tall, slim and blond. She also had a kind personality and was not quick to anger. Anja Huesby, Julianne’s sister, was also tall and blond.
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Dr. Phillip S. Rokicki Precision Tree and the Prescott Furniture Company Instructions: From time to time your professor makes available extra credit opportunities that allow you to add to your total point values for this class. This is such an opportunity. Using Palisades Precision Tree software create a tree that graphically shows the various options open to customers of the Prescott Furniture Company. You must import your Precision Tree into a Word document that contains the NSU/SBE
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Decision Trees Using TreePlan 16 16.1 TREEPLAN OVERVIEW TreePlan is a decision tree add-in for Microsoft Excel 97–2007 for Windows and Macintosh. TreePlan helps you build a decision tree diagram in an Excel worksheet using dialog boxes. Decision trees are useful for analyzing sequential decision problems under uncertainty. Your decision tree model may include various controllable alternatives (e.g., whether to introduce a new product, whether to bid on a new project) and uncontrollable uncertainties
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Let’s suppose the prediction for the sales demand that Ann Queen derived from other comparable events is accurate. It is relatively easy to figure out the possible DVDs that can be sold with expected probability if we draw a decision tree. From the above tree graph, we can tell that the total possibility to sell 4000 DVDs in Saturday and Sunday is 25%. If Ann Queen’s expectation about the possibility of DVD sold is accurate and nothing new information will be available after Friday’s and Saturday’s
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