Unit 4 Lesson 7: Online PD Discussion


#1

Use this space to discuss the challenge activity for online pd. If you completed this lesson as part of your PD, be sure to share the following:

  • Any visualizations or other lessons artifacts created by completing your challenge activity
  • The assessment question or extending learning activity that you produced for this lesson.
  • Notes for others who are going to teach this lesson. This should include:
    • Advice for someone who is going to teach this lesson (consider what was challenging about doing the lesson, what you think students will struggle with, etc).
    • What ideas do you have about how to structure and teach this lesson? what modifications do you plan to make to the lesson?
    • What additional resources (if any) might be helpful in teaching this lesson.

#2

As we started to prepare for this lesson, we discussed how to motivate our students to work and to summarize their data using the several tools available to them. Then we will work on the options they have to make their summary easy to understand using charts and graphs. Finally, each student will perform a short presentation and be evaluated by their peers.

Please, find bellow the link to our raw data, the data categorization and a sample chart representing the summary data.

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#3

This lesson involves teaching the students about data collection and representation. The students will become familiar with collecting data based on the survey questions generated (either by teacher or students in groups). Once they collect the data, they will also learn to sort, filter and clean the data. The students will also learn to standardize the text data and create the graphic representation for the data categorized.
The following link shows how this information can be standardized and graphically represented,

The students can be also taught to use different ways to represent data using charts in Excel or Google sheets.
Assessments include student categorization and representation of data.


#4

In this lesson, students begin working with the data that they have been collecting since the first lesson of the unit. They are introduced to the first step in analyzing data: cleaning the data. Students will follow a guide in Code Studio, which demonstrates the common techniques of filtering and sorting data to familiarize themselves with its contents. Then they will correct errors they find in the data by either hand-correcting invalid values or deleting them. Finally they will categorize any free-text columns that were collected to prepare them for analysis. This lesson introduces many new skills with spreadsheets and reveals the sometimes subjective nature of data analysis.

Using the online tools students will work in pairs to clean data so that it is machine readable and capable of being analyzed. One of the most lengthy processes in analysis is cleaning data, and students need to begin to learning how to clean data as soon as possible. Before turning students lose on the programming tool, Show students example of real world datasets and let them identify steps that need to be done to clean the data. THis is the biggest deviation from the lesson plan I would include. Other than that, follow the lesson plan


#5

Here is the link to my cleaned spreadsheet:
https://docs.google.com/a/mymail.lausd.net/spreadsheets/d/1QRbIJYAUO7tXyOjMb-eLatWTXjRFzMo8_uKA9KqxRBQ/edit?usp=sharing

I ended up flitering by followers count and then created a new column which indicated whether the tweet was a retweet or not based on searching for the “RT” at the beginning of the tweet.

Assessment Question
For which of the following scenarios should you delete the data? Select all that apply.
A. Values that are too large or too small to make sense.
B. Values are smaller than most of the others in the data set.
C. Value should have been a number but is text instead
D. Values contain a misspelled word

Advice/Ideas
Cleaning data is often not the most fun but is a necessary evil. In order to spice it up and add some social interactions, I would have students share their cleaned data and have their partner try to guess how it was filtered/modified.


#6

Thanks for sharing. I like the presentation idea.


#7

Here is the link for my a) cleaned data b) and the lesson extension.

Extension and Artifact


#8

I can say that the tweets are not good for sorting :frowning:


#9

Assessment questions:
What are some ways that one could decrease the time required for “cleaning” data?
Is there more than one way to clean data?
If so, are some ways of cleaning data better than other ways? Explain.

Notes & Advice:
Data itself, let alone cleaning data, can be dry and difficult for students to appreciate. Some good examples of the importance and power of data collection and cleaning would be helpful.

Ideas & Mods:
Show students example of real world data sets and let them identify steps that need to be done to clean the data.

Resources:
Perhaps a YouTube video on cleaning small and big data.

Overview:
In this lesson, students begin working with the data that they have been collecting since the first lesson of the unit. They are introduced to the first step in analyzing data: cleaning the data. Students will follow a guide in Code Studio, which demonstrates the common techniques of filtering and sorting data to familiarize themselves with its contents. Then they will correct errors they find in the data by either hand-correcting invalid values or deleting them. Finally they will categorize any free-text columns that were collected to prepare them for analysis. This lesson introduces many new skills with spreadsheets and reveals the sometimes subjective nature of data analysis.

Using the online tools students will work in pairs to clean data so that it is machine readable and capable of being analyzed. One of the most lengthy processes in analysis is cleaning data, and students need to begin to learning how to clean data as soon as possible. Before turning students lose on the programming tool, This is the biggest deviation from the lesson plan I would include. Other than that, follow the lesson plan

–kyle tower & david selby


#10

Extension: Students share their cleaned data sheet digitally with two other students and leave comments regarding data choices in the form of I notice and I wonder. After reviewing feedback, determine if an adjustment needs to be made and either alter your sheet or leave it the same. In any case, write a short reflection regarding your decisions given your feedback. Share this reflection with your teacher.

Teacher- This extension is an activity used to debrief student choices through evaluation and reflection. Use Google docs and Google sheets to create and share products.

This lesson is straightforward. Students will have to make choices regarding their data sheets. These solutions may vary and it is okay. Students may struggle with being able to determine necessary adjustments. However, if they do not identify items, these ideas can be identified during the discussion.


#11

Link to product: https://docs.google.com/spreadsheets/d/1020lxFjJqkou7pDnOIu05JWeT11_VCnNuk6HDbNtG-o/edit?usp=sharing

Extension questions:

  1. What are different ways to categorize the freeform text?
  2. What are pros and cons of the different ways of categorizing the freeform text?
  3. How might the audience or purpose affect how the text is categorized?

Notes:
I’m concerned the idea of going “we’ll need to analyze this - let’s prepare our data!” is a bit abstract and/or dry for my students. It’s definitely crucial. I’m wondering if there’s something I can do to add context, like telling my students “Say you’re writing an article in the student newspaper on what are happy student habits…” or “You’re want to create a product/service to help students be happier…” Perhaps giving my students a goal with the data will help provide context, guidance, and maybe engagement in slogging through the data and making subjective decisions.

Oh, and I think I got lazy with my categorization. I just put “RT” (retweet) as a category. It was also pretty tough to categorize some of them. I’m not sure if it would’ve been “cheating” to just put an “other” category. I just ended up sorta tossing those into a random category. From a data analysis perspective, that’s probably worse huh…


#12

I agree. I suppose they’re good at providing a challenge though.


#13

The Twitter data is already an extension on the original lesson plan for lesson 8. Since the lesson has the class all working on the same set of data they had collected over the previous few weeks and it had specific task. Giving a new data set and having them put it into a useful format.

My artifact took the twitter data and first filtered the language then by followers and re-twets. I was able to sort by time.

The cleaning of data and forming another column to standardized can get tricky and students have to work out beforehand what is acceptable.