Part 1: Comparing Reading Assessments Matrix

Using the topic Resources and your own research, complete the “Comparing Reading Assessments Matrix.”

Part 2: The Importance of Assessments

In 250-500 words, reflect on the following.

• Consider your own professional practice and describe how you assess and support reading within your content area, including discussion of reading assessments, if you use them.
• Based upon what you learned from your research, explain which of the assessments from the matrix would be most beneficial and useful to you as a teacher and explain why. Include discussion about how you would ensure you were properly trained to use the tool, when you would use the tool, and how you would collect, organize, and use the assessment data.
• Explain why it is important for all teachers, regardless of content area, to be aware of reading assessments they can use with their students. Provide real-world examples to support your ideas.

Part 3: Interpreting Assessment Data Results

Review the topic Resources. Using the “Dyslexia Evaluation Report For English-Speaking Students (Non-ELLS)” analyze the reading assessment data presented in the document.

In 500-750 words, discuss the following:

• Summarize overall student progress.
• Interpret the data to determine whether Daisy is responding adequately to Tier 2 instruction. Discuss data that could potentially indicate signs of dyslexia.
• Explain why the support team members disagree about what tier of instruction would best meet Daisy’s needs and justify your answer.
• Describe the tier of instruction you would recommend for Daisy: Tier 1 instruction only, another round of Tier 2 instruction, or intensive Tier 3 instruction. Explain your answer.
• Identify and explain the specific data points that were analyzed and summarize your findings.
• Discuss how you will use this data to plan whole group instruction.
• Explain specific interventions you will employ to assist students who are struggling with dyslexia or reading difficulties.

 This assignment has 3 parts.  In the first paragraph, you will clearly explain what the Lewis dot structure and the Bohr model have in common.  Provide, at least two examples to support your explanation.  The second paragraph should contain an explanation of how Lewis and Bohr are different.  Again, provide at least two examples to support your explanation. In addition, describe what the Bohr model and the Lewis dot structure of sodium would look like.  Again, give me a detailed explanation of the appearance of each of the models for sodium, do NOT simply give me a picture!!!! 

food technology of cookies doughFormat and other important information for your paper 1. Double spaced, 12-point font (Times New Roman, Arial, margins not less than 1 inch). 2. Cover page contains name, course name and number and the date. 3. Use AMA referencing style. 4. Page numbers must be placed in the lower right hand corner. 5. Minimum page limit is 3 pages including references. Only include pertinent information and not a lot of fluff. 6. Your information should be presented in a clear manner that flows from one paragraph to another. 7. For an A paper you MUST have Three (3) resources in your references acquired through the library website. You may also use the textbook and class lectures as references. 8. References and in text citations not in AMA format, 5 point deduction each, for a total of 10 points. 9.-Three references not available through the library website – 10 point deduction 10. No more than two (2) quotes can be used in your paper. If you go over that  number of quotes, you will be counted off five (5) points per quote

Purpose:  

This project will expose you to inference using Bayesian networks. Bayesian networks capture causal relationships and are widely used in fault diagnosis across a wide variety of applications. A Bayesian network can be represented by a directed graph which will model causal relationships between variables. A useful tool to represent and traverse a graph is NetworkX (NetworkX — NetworkX documentation) which contains a comprehensive library of graph types and graph algorithms written in Python. The application that we will be targeting is Car fault diagnosis which was introduced in class. The fundamental issue in such diagnosis applications is to discover the causes or underlying reasons for the fault to occur and to rank these reasons in terms of their importance.

In this application we will be exploring the reasons behind: a) the car not starting and the probability that this event takes place; and b) under what conditions the car battery becomes flat and the likelihood of this occurring.

Project Requirements:

R1 

Use Networkx in Google Colab and represent the network as shown below:

Attach probability tables to each node as specified in the Project 3 discussion document. Visualize the network using Networkx and show the nodes and edges. You do not have to show the probability tables you created but this of course will be embedded in your code. The coloring used in the figure above does not need to be reproduced. Instead, use a neutral color of blue to shade the nodes. Make sure that your edges show directionality.

R2

Compute the probability P (-cs, +ab, +fb)

R3

Compute the probability P (-cs, +ab)

R4

Compute the probability P(-cs, +fb)

R5

For the battery going flat, which of the factors is more important, battery dead or not charging?

Note: 

1. Use the starter code provided for this project. This is essential as many of you will not be familiar with NetworkX.
2. I strongly recommend that you read the Project 3 Discussion Document as it covers not just the probability table creation but also what formulae needs to be used to compute the answers to requirements R2 to R5.