writings

For this assignment, you will create a multimedia presentation about fast food. To do this, first you will create a research plan that includes an initial research question. Then you will conduct the iterative research process, which may include refining your research question and/or creating secondary questions based on the information you discover. After you have completed your multimedia presentation, you will answer five questions to reflect on the process and describe your experience.

 

Background Information

 

Fast food plays a major role in different aspects of our society. Choose an aspect of fast food in America that interests you to maximize your engagement in the project. Some sample ideas include:

 

 Marketing trends

 

 Role in pop culture

 

 Impact on the economy

 

 Impact on health and well-being

 

 Impact on different groups of people

 

Materials

 

 Computer and internet access

 

 Presentation software

 

 Access to research materials

 

 Note cards

 

Assignment Instructions

 

For this project, you are expected to submit three things:

 

1. A research plan

 

2. Multimedia presentation

 

3. Completed reflection questions

 

Step 1: Prepare for the project.

 

a) Read through the guide before you begin so you know the expectations for this project. b) If there is anything that is not clear to you, be sure to ask your teacher.

 

Step 2: Complete the research plan.

 

a) Fill out the Research Plan section of this document.

 

b) First, write a research question. Make sure that it is open-ended and not narrow or too broad.

 

c) Then, plan your research by completing items 2–4 in the Research Plan section.

 

Step 3: Conduct research.

 

 

 

Student Guide (continued)

 

Copyright © Edgenuity Inc.

 

a) Gather information from sources. Remember to only use relevant, credible, and timely resources. Revisit the lesson if you want a reminder of how to evaluate sources.

 

 Here are some suggestions to help you begin the research process for your multimedia presentation. They include articles and information provided by government agencies, health organizations, and a cable news network. As you search for additional sources, make sure they are credible and unbiased.

 

 https://www.cdc.gov/nchs/products/databriefs/db322.htm

 

 http://www.center4research.org/fast-food-facts-calories-and-fat/

 

 https://fastfoodnutrition.org/

 

 https://www.rwjf.org/en/library/research/2010/11/fast-food-facts.html

 

 https://www.cnn.com/2018/10/03/health/fast-food-consumption-cdc- study/index.html

 

 https://www.acsh.org/news/2018/10/03/1-3-adults-has-fast-food-any-given-day- 13471

 

 https://www.vox.com/the-goods/2019/6/26/18700762/fast-food-america-adam- chandler-drive-thru-dreams

 

b) Use note cards to record information, including details to include on your Works Cited slide.

 

Step 4: Revise your research plan.

 

a) Revisit your research plan.

 

b) Complete item 5 and revise your research question as needed. Add secondary research questions to help complete your research.

 

Step 5: Create a multimedia presentation.

 

a) Create your presentation on the computer using presentation software.

 

b) Create an organized presentation that follows this structure: an introduction that includes the research question, several slides that synthesize and present the findings from your research, a conclusion the summarizes your findings, and a Works Cited slide.

 

c) Make sure you use a proper balance of text and graphics appropriately and effectively.

 

d) Ensure that your presentation is neat, easy to follow, and visually appealing.

 

e) Include media, such as images, video, or audio.

 

Step 6: Complete the reflection questions.

 

a) Once you have completed your multimedia presentation, answer the Reflect questions about your research process. These questions can be found at the end of this document.

 

Step 7: Evaluate your project using this checklist.

 

If you can check each box below, you are ready to submit your project.

 

Did you complete the research plan?

 

Did you revisit the research plan to revise your research question and/or create secondary questions?

 

Does your multimedia presentation include your research question?

 

 

 

Student Guide (continued)

 

Copyright © Edgenuity Inc.

 

Does your presentation include a balance of text and multimedia elements?

 

Does your presentation include a conclusion?

 

Did you include a Works Cited slide?

 

Did you complete the reflection questions?

 

Step 8: Revise and submit your project.

 

a) If you were unable to check off all of the requirements on the checklist, go back and make sure that your project is complete. Save your project before submitting it.

 

b) Turn in your research plan and reflection questions to your teacher. Be sure that your name is on the document.

 

c) Submit your multimedia presentation through the virtual classroom. d) Congratulations! You have completed your project.

While you certainly can research a particular disease and write about the disease phenotypes and genetic cause, there are many other topics you can chose.

 

Choose something that interests you or something you’ve always wondered about but never had the time to research.

 

Use your imagination when coming up with a topic!

 

Outline:

 

Part I: What was the question you wanted to answer? Why did you choose this topic? (10 points)

 

Part II: How does this topic relate to something you learned in class this semester? (10 points)

 

Part III: Discuss what information and published research you found to better understand your topic and answer your original question. This part will make up the bulk of your essay and should be written in an essay format. Make sure to include references as needed. (120 points)

 

· Introduction.

 

· Body. First Point. Second Point. Third Point.

 

· Conclusion.

 

Part IV: What was the most interesting thing you learned from this exercise? (10 points)

In this project you will explore some techniques in unsupervised learning as well as ensemble methods. It is important to realize that understanding an algorithm or technique requires understanding how it behaves under a variety of circumstances. You will go through the process of choosing and exploring two classification datasets, tuning the algorithms you have learned about, writing a thorough analysis of your findings, and presenting your findings. The most crucial part of this assignment is the analysis and your ability to explain and justify your results.

 

I. Choosing Datasets

 

The first task in this assignment is choosing two interesting classification datasets, these can be binary or multiclass. The features can be of any type, and it is recommended that you choose datasets with diverse feature sets. I don’t care where you get the data from. You can download some, take some from your own research, or make some up on your own. What I do care about is that the datasets must be interesting. They should contain a decent amount of features and a sufficiently large amount of examples. Do not choose an “easy” dataset, however don’t go crazy either trying to find the perfect one. Your two datasets should also differ in some way such that you can compare and contrast your results between the two. You should also be following standard machine learning practice by splitting your dataset into training and testing, and only touching the testing dataset at the very end when you are ready to report results. (Cross validation is highly recommended).

 

II. Coding (10%)

 

After choosing your datasets you will now be tasked with writing code to apply the machine learning algorithms you have learned about. Your code must be written in python, but you may use any libraries that have already implemented the machine learning algorithms (e.g scikit-learn). You are not expected to code the algorithms from scratch, and in fact I would highly discourage it. What you may not do is copy code from the internet. Below are the analyses you are required to run.

 

1) Run K-means and Hierarchical Clustering on your datasets and analyze what you observe.

 

2) Run two dimensionality reduction algorithms (PCA and t-SNE) on your datasets. Observe and analyze the results.

 

3) Re-run the K-means and Hierarchical Clustering on your dimensionality reduced datasets and compare the results to part (1).

 

4) Tune and train two ensemble models (AdaBoost and Random Forests) on both your original and dimensionality reduced datasets. Compare and analyze the results.

 

Your code does not have to be pretty or well written. However, it must be written in python and I must be able to run one script (main.py) that will produce all the results and figures in your report.

 

III. Report (80%)

 

You will then produce a report describing and analyzing your methods and results. Here you will describe the datasets you have chosen and why they are interesting. You will then provide an analysis on how the different machine learning algorithms performed on each dataset. The report must be limited to 10 pages maximum. Plots and figures are highly recommended. It is up to you how you wish to demonstrate your understanding of the machine learning algorithms you have explored, but below I have listed some potential ideas for analysis and items you may wish to include in the report.

 

• A description of your two datasets and why you feel that they are interesting. • Hypotheses on how you believe the learning algorithms will perform on each

 

dataset and why. • How you dealt with different features in your datasets? missing data? different

 

scalings? • Training and testing error rates you obtained for your various learning

 

algorithms (some sort of cross validation is highly recommended) • The effect of hyperparameters on performance • Comparing and contrasting results between datasets • Comparing and contrasting results between learning algorithms • Training and testing error rates as a function of training dataset size • Timing analysis of how long it takes to train/test each algorithm • Conclusions • Ideas for future analyses • What you may have done differently • References

 

You are NOT being graded on how well the algorithms perform on your datasets. What is most important is WHY? You should be explaining and justifying all of your figures and results, and demonstrating that you understand the intricate details of the machine learning process, and the machine leaning algorithms you are using.

 

IV. Presentation (10%)

 

Finally you will give a maximum 7 minute presentation of your results (You will be cut off exactly at the 7 minute mark). In this presentation you will describe your datasets, your methods, and any interesting results you found!

 

What to turn in?

 

Below is a list of items you will be required to turn in via canvas. Please make sure all documents are named as described bellow.

 

• report.pdf – Your maximum 10 page report in pdf format. Do not use super tiny or large font. No specific formatting is required but use common sense.

 

• presentation.pptx or presentation.key – Your presentation slides either in a powerpoint or keynote document.

 

• code.zip – A zip file with all of the code you have written. Within the folder there should a file called README.txt that contains instructions on how to run your code, and a python file called main.py that will produce all figures and plots in your report/presentation. I should be able to reproduce your results easily.

 

• data.zip – A zip file that contains the two datasets you have chosen.

 

Grading

 

You are being scored on your analysis more than anything else. Roughly speaking, implementing everything and getting it to run is worth very little for this assignment. Of course though, analysis without proof of working code makes the analysis suspect. The key thing is that your explanations should be

 

both thorough and concise, and your analysis should prove to me you have a deep understanding of the machine learning process and the machine learning algorithms you are using.

In this assignment, you will create a production possibilities schedule and curve to determine what your opportunity costs are and which product is the best for you to produce.

 

Directions:

Gather materials and necessary information.

 

Ask your teacher which word-processing software you will be using.

 

Keep your lesson and assignment open in case you need to review what you have learned.

 

Read and follow each set of instructions carefully.

 

a) Compete the production possibilities schedule and production possibilities curve, starting with the information provided. Be sure to ask your teacher for help if you are not sure how to do this.

 

b) Make sure you complete the questions on each page.

 

Assignment: Determining Production Possibilities

You are getting ready to open The Shoe Hut, but you need to determine whether you have the absolute or comparative advantage in the production of specific items. This will help you determine which product is the best for specialization.

 

Your production possibilities are as follows:

 

· You have the resources to produce up to 15 running shoe inserts.

 

· You have the resources to produce up to 10 hiking boot inserts.

 

· For every 2 hiking boot inserts produced, you give up the production of 3 running shoe inserts.

 

Your production possibilities schedule will help you determine:

 

· your opportunity costs.

 

· your best options for production.

 

Scroll to the next page to complete your production possibilities schedule.

 

1. Using the information that you learned about your ability to produce running shoe inserts and hiking boot inserts, complete your production possibilities schedule. (5 points)

 

Combinations

 

Running shoe inserts

 

Hiking boot inserts

 

A

 

B

 

C

 

D

 

E

 

F

 

1. Use the information from your production possibilities schedule to create your production possibilities curve by filling in the following graph. Use textboxes to insert text, and use lines and circles from the shapes function to illustrate your production possibilities. Be sure to mark points A through F on the graph. (5 points)

 

While you certainly can research a particular disease and write about the disease phenotypes and genetic cause, there are many other topics you can chose.

 

Choose something that interests you or something you’ve always wondered about but never had the time to research.

 

Use your imagination when coming up with a topic!

 

Outline:

 

Part I: What was the question you wanted to answer? Why did you choose this topic? (10 points)

 

Part II: How does this topic relate to something you learned in class this semester? (10 points)

 

Part III: Discuss what information and published research you found to better understand your topic and answer your original question. This part will make up the bulk of your essay and should be written in an essay format. Make sure to include references as needed. (120 points)

 

· Introduction.

 

· Body. First Point. Second Point. Third Point.

 

· Conclusion.

 

Part IV: What was the most interesting thing you learned from this exercise? (10 points)