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# 数学代写|数学建模代写Mathematical Modeling代考|TMA4195 Data and Analysis

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## 数学代写|数学建模代写Mathematical Modeling代考|Data and Analysis

Data for the research presented here were collected in the first author’s grade $8(n=28)$ class while students worked on the aforementioned task. Although it is not possible to know if the grade 8’s had seen similar tasks in their previous years, this was one of the first of such tasks this group had been given in their grade 8 school year.

Students were randomly assigned to groups of 2-4 and worked on the task during a 75 min class. There were no instructions provided other than what can be seen in Fig. 9. While the students worked the teacher (first author) circulated naturally through the room and engaged in conversations with the students – sometimes prompted by her and sometimes prompted by the students.

These conversations were audio recorded and transcribed. At the same time photographs of student work were taken and students’ finished work was collected. These, coupled with field notes summarizing the interactions as well as observed student activity, allowed us to build cases for each group of students. Each of these cases is a narrative of their modelling experience punctuated by significant moments of activity and emotive expression. These cases constitute the data.

Given that natural and unscripted nature of the teacher’s movement through the room, not all of the cases are equally well documented. Regardless, each of these cases were analyzed separately through the lenses of modelling and flow. More specifically, the cases were analyzed using Borromeo Ferri’s (2006) modelling cycle as well as through Liljedahl’s (2018) modified theory of flow. The results of these disparate analyses were then combined and compared on an event by event basis to see if there were relationships between student engagement and various aspects of their modelling activities intersected.

In what follows we present one of the more complete and comprehensive of the aforementioned cases – the case of Amy and Angela. This is followed by the modelling cycle analysis, the flow analysis, and finally the joint modelling-flow analysis.

## 数学代写|数学建模代写Mathematical Modeling代考|Results and Discussion

Amy and Angela reacted to the modelling task by first asking questions about the parking lot. Amy believed that one of the key factors of the parking lot is the dimensions of a vehicle, and suggested to go outside to the staff parking lot to take some measurements.
Amy: How big is a car [talks to herself]? Can I go outside for a second [asks teacher]?

When she came back, Amy discussed these measurements with Angela, and suggested that they should increase these measurements to accommodate for large vehicles.
Amy: The car I measured was 2.5 metres by 1.5 metres, but it was a slightly smaller car so probably make it a bit bigger? ‘Cause there are bigger cars in the parking lot?
Angela: Like a Chevy.
Amy: What’s that?
Angela: It’s a truck.
After this conversation, Amy and Angela decided to put the parking lot on hold and investigated the possible locations and orientation of some of the building structures on the grid. First, they re-read the instructions provided, and paid attention to the areas on the grid which they were allowed to put buildings and the actual length each square represents. They divided 12.5 (distance between the border and all buildings) by 10 (each square represents $10 \mathrm{~m}$ ) and got “one and one-fourth”, and outlined a rectangle one and a quarter squares inside the border of the grid to represent the space they could put the buildings (see Fig. 10 for details).
Angela: So, all fields, courts, buildings, and parking lots must be no closer than 12.5 metres to any of the property lines. So one and one-fourth.

## 数学代写|数学建模代写Mathematical Modeling代考|Results and Discussion

Amy 和 Angela 对建模任务的反应是首先询问有关停车场的问题。艾米认为停车场的一个关键因素是车辆的尺寸，建议到外面的员工停车场测量一下。

) 得到“一又四分之一”，并在网格的边界内勾勒出一个四分之一的长方形，代表他们可以放置建筑物的空间（详见图 10）。

## MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。