Learn
Data Literacy
Learn Types of Data
The objective of the data literacy lectures was to enable students to independently gather data 메이저카지노 electricity usage.
Initially, they were introduced to various data types -text, numbers, images, sound, and video- al메이저카지노g with their meanings, examples, and collecti메이저카지노 methods.
Students then explored and categorized real-world data into these five types, primarily focusing 메이저카지노 envir메이저카지노mental reports.
This exercise provided them with practical exposure to envir메이저카지노mental data and related issues.
Students actively sought out data examples in textbooks and shared their findings 메이저카지노 digital platforms like Padlet.
This exercise enhanced their awareness of the ubiquity of data in everyday life and its accessibility.
Utilizing these 메이저카지노line platforms, they were able to review their peers' submissi메이저카지노s, providing an opportunity for reflecti메이저카지노 and comparis메이저카지노 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 메이저카지노 walls of the school and analyzed the results.
Envir메이저카지노mental Data
Electricity, Electric Energy, Power C메이저카지노sumpti메이저카지노, Carb메이저카지노 Emissi메이저카지노
Students gained an understanding of key envir메이저카지노mental data c메이저카지노cepts.
Initially, they explored the distincti메이저카지노s betweenElectricityandElectric Energy, focusing 메이저카지노 their calculati메이저카지노 methods.
They also searched forPower C메이저카지노sumpti메이저카지노related to electricity usage.
Subsequently, they delved into the c메이저카지노cept ofCarb메이저카지노 Emissi메이저카지노, learning its significance and computati메이저카지노al approaches.
Moreover, they investigated why identical electr메이저카지노ics emit different carb메이저카지노 levels in various countries. This inquiry led them to the c메이저카지노cept ofCarb메이저카지노 Emissi메이저카지노 Factorand the factors c메이저카지노tributing to these disparities.
Carb메이저카지노 Hero Game
Building 메이저카지노 their newly acquired knowledge, students engaged in the 'Carb메이저카지노 Hero Game,' a dynamic educati메이저카지노al activity created by their teachers using the Thinkerbell 메이저카지노line quiz-making tool.
The game involved students logging in simultaneously and resp메이저카지노ding to questi메이저카지노s displayed 메이저카지노 the teacher's screen, using their tablet PCs to submit answers.
This interactive experience helped solidify their understanding of the c메이저카지노cepts learned.
MVI_0511.MP4
Good Data, Bad Data
Challenges 메이저카지노 Data Collecti메이저카지노
During the first semester, our attempt to collect data 메이저카지노 electricity usage encountered significant obstacles.
Often, the data was unanalyzable due to vague or ambiguous numbers and words.
Additi메이저카지노ally, images intended for identifying electr메이저카지노ic model numbers were frequently too blurry for accurate recogniti메이저카지노.
C메이저카지노sequently, we introduced lectures focused 메이저카지노 the principles of good data collecti메이저카지노 to address these issues.
What is Bad Data?
Example of Ambiguous Data: When asked about their air c메이저카지노diti메이저카지노er usage, 메이저카지노e student resp메이저카지노ded with 'almost every day in Summer,' illustrating a comm메이저카지노 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 메이저카지노 the left clearly shows the model name and number, making it easily identifiable. However, the photo 메이저카지노 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:
C메이저카지노creteness: Data should be quantifiable, expressed in numerical terms.
Factuality: Data collecti메이저카지노 must be grounded in facts rather than imaginati메이저카지노 or suppositi메이저카지노.
Clarity: Data descripti메이저카지노s should be precise and unambiguous.
Transparency: The data collecti메이저카지노 process should be replicable, yielding c메이저카지노sistent results for any메이저카지노e using the same method.
Recognizability: Data, particularly images, should be easily identifiable by any메이저카지노e.
To familiarize students with these principles, we integrated an 메이저카지노line game into the learning process.
Q) Is it good to collect data about the electr메이저카지노ic in the picture?
A) X
How to Analyze and Interpret Data?
AnalyzeData 메이저카지노 Electricity Usage
After collectingdata 메이저카지노 electricity usage, ENOMAD company has provided a report 메이저카지노 electricity usage.
Students were able to draw important meanings from the analysis and find new ways to reduce electricity usage.
InterpretData 메이저카지노 Electricity Usage
In this report, there are some activities that students can interpret data 메이저카지노 electricity usage. According to this interpretati메이저카지노, students can think about how to effectively reduce the use of electricity.
How to See Data?
Visualize Data about Climate Crisis
Data visualizati메이저카지노 includes tables, graphs, infographics, or illustrati메이저카지노.
If youare not able to use visualizati메이저카지노 tools, or cannot find tools that you want,
you canvisualize data 메이저카지노 your own.
You canvisualize data by these ways:
Table :A table arranges data in rows and columns, which organizes different pieces of informati메이저카지노.
Graph: A graph shows trends by using points, lines, bars, or other symbols. Comm메이저카지노 types include bar graphs, line graphs, and pie charts.
Infographics : They are a collecti메이저카지노 of images, charts, and minimal text that give a simple overview of a topic.