Learn
Data Literacy
Learn Types of Data
The objective of the data literacy lectures was to enable students to independently gather data on electricity usage.
Initially, they were introduced to various data types - text, numbers, images, sound, and video - along with their meanings, examples, and collection methods.
Students then explored and categorized real-world data into these five types, primarily focusing on environmental reports.
This exercise provided them with practical exposure to environmental data and related issues.
Students actively sought out data examples in textbooks and shared their findings on digital platforms like Padlet.
This exercise enhanced their awareness of the ubiquity of data in everyday life and its accessibility.
Utilizing these online platforms, they were able to review their peers' submissions, providing an opportunity for reflection and comparison of their own results.
Examples of Image Data
Examples of Text Data
Examples of Numeric Data
Also, some students made simple suveys by themselves about the topics that they want to ask to other students.
They displayed the QR codes of surveys on walls of the school and analyzed the results.
Environmental Data
Electricity, Electric Energy, Power Consumption, Carbon Emission
Students gained an understanding of key environmental data concepts.
Initially, they explored the distinctions between Electricity and Electric Energy, focusing on their calculation methods.
They also searched for Power Consumption related to electricity usage.
Subsequently, they delved into the concept of Carbon Emission, learning its significance and computational approaches.
Moreover, they investigated why identical electronics emit different carbon levels in various countries. This inquiry led them to the concept of Carbon Emission Factor and the factors contributing to these disparities.
Carbon Hero Game
Building on their newly acquired knowledge, students engaged in the 'Carbon Hero Game,' a dynamic educational activity created by their teachers using the Thinkerbell online quiz-making tool.
The game involved students logging in simultaneously and responding to questions displayed on the teacher's screen, using their tablet PCs to submit answers.
This interactive experience helped solidify their understanding of the concepts learned.
MVI_0511.MP4
Good Data, Bad Data
Challenges on Data Collection
During the first semester, our attempt to collect data on electricity usage encountered significant obstacles.
Often, the data was unanalyzable due to vague or ambiguous numbers and words.
Additionally, images intended for identifying electronic model numbers were frequently too blurry for accurate recognition.
Consequently, we introduced lectures focused on the principles of good data collection to address these issues.
What is Bad Data?
Example of Ambiguous Data: When asked about their air conditioner usage, one student responded with 'almost every day in Summer,' illustrating a common issue. Several students struggled to quantify usage in precise terms, such as the exact number of hours and dates.
Example of Image-Related Issues: The photos, taken by different students, both depict air purifiers. The photo on the left clearly shows the model name and number, making it easily identifiable. However, the photo on the right was less clear, requiring manual effort to determine the model name.
What is Good Data?
We established the following criteria for good data quality:
Concreteness: Data should be quantifiable, expressed in numerical terms.
Factuality: Data collection must be grounded in facts rather than imagination or supposition.
Clarity: Data descriptions should be precise and unambiguous.
Transparency: The data collection process should be replicable, yielding consistent results for anyone using the same method.
Recognizability: Data, particularly images, should be easily identifiable by anyone.
To familiarize students with these principles, we integrated an online game into the learning process.
Q) Is it good to collect data about the electronic in the picture?
A) X
How to Analyze and Interpret Data?
Analyze Data on Electricity Usage
After collecting data on electricity usage, ENOMAD company has provided a report on electricity usage.
Students were able to draw important meanings from the analysis and find new ways to reduce electricity usage.
Interpret Data on Electricity Usage
In this report, there are some activities that students can interpret data on electricity usage. According to this interpretation, students can think about how to effectively reduce the use of electricity.
How to See Data?
Visualize Data about Climate Crisis
Data visualization includes tables, graphs, infographics, or illustration.
If you are not able to use visualization tools, or cannot find tools that you want,
you can visualize data on your own.
You can visualize data by these ways:
Table : A table arranges data in rows and columns, which organizes different pieces of information.
Graph : A graph shows trends by using points, lines, bars, or other symbols. Common types include bar graphs, line graphs, and pie charts.
Infographics : They are a collection of images, charts, and minimal text that give a simple overview of a topic.