What is Data and Why Should You Care?
Did I zonk out in class? That is my typical response after a topic like "data" gains steam and becomes the talk-of-the-town. Discussions quickly turn complex.
Those of us who may not have a firm understanding of the basics are left behind wondering, "I need to drink more coffee and sleep less!" We may even tune out discussions because we don’t have a baseline. Or, maybe we feel awkward asking questions.
Everyone assumes the basics are understood. To use a popular data phrase, “the signal is lost in the noise.”
More people are in the same boat than you think. Take data privacy - an important, but complex topic. Before seeing the merits of data privacy and navigating through the nuance, it's important to understand data basics and why it's important.
Let's go back to the data basics...data point one. Here is the signal.
What is data?
3. Where you click on a page
4. Values (test scores, comparison)
5. Demographics (age, ethnicity, income)
6. Answers to questions
7. Media - pictures and video
8. Questions you ask Siri
9. Route used during Waze
10. Movies watched in Netflix
11. Stuff you buy on Amazon
12. Content of a Facebook post
13. Words used in an email
14. Searches you do
15. The temperature of your house
16. Credit card purchases
17. Scientific data
Some of this data is collected explicitly. You may enter your name, age, interests, etc. into an app or site. You may upload a photo or video to Instagram. Data can be also collected through ancillary means such as your browsing history, website clicks, etc. Sometimes we are given a fair, non-cryptic warning. Sometimes, we have no clue that our data is collected or where it’s going.
Why should you care as a consumer and/or human being?
We see that data can be a lot of different stuff. It’s not just numbers. With enough of it, data can be used to make predictions.
A prediction is the likelihood about something in the future. To see into the future with precision is powerful stuff! That's why, in part, data is called the new currency.
Some use the data to sell you stuff (products, ads, etc.) and make money. Some use the data to predict data for the next flu strain. Some want to see if their favorite sports player will do well.
The intention behind collecting data is the elephant in the room. An important detail that I don’t think is underscored enough.
An important point here is that predictions aren't necessarily just numbers. A quick example is, "If you are this height, you will be this weight." Sometimes predictions are classifications and clusters of things. Classifications take your data and classify it (is that email SPAM or not SPAM). Clusters take data and move it into "group" based on similar characteristics (are these dogs or cats in the photos?).
Lastly, predictions can always become better. They learn. As more data is collected, they get better over time. The predictions become more precise. That's why you are encouraged to "feed the beast" (add more data).
Bottom-line: For every piece of data, with enough of it, predictions can be made. This is why so many platforms make it easy and free to add yours and other's data. You may not be paying with dollars, euros, or shekels. Your data is payment enough.
Why should you care as an educator?
Our students’ data and subsequent predictions of learning gives us another tool for the benefits of them, the teacher, class, school, and field as a whole. We can use this data on a daily basis, to determine the effectiveness of technology and programs, and enrich the process in ways that aren’t possible with data’s precision. In moderation, data can be beneficial.
It’s no secret. Teachers and schools have troves of data. The tricky part is the data can identify students. Additionally, students (or their parents/guardians) may not want data released. Nowadays, there are blurred lines and it can be hard to tell who is seeing what data.
Bottom-line for Educators: Don't underestimate the worth of your students' data. It's like the old garage sale saying, "Someone else's trash is another's treasure." What you may not think as important can be gold to someone making predictions. Be careful of who sees what data. Used in moderation, data’s predictive power can be useful for you and your students.