(Print) Use this randomly generated list as your call list when playing the game. There is no need to say the BINGO column name. Place some kind of mark (like an X, a checkmark, a dot, tally mark, etc) on each cell as you announce it, to keep track. You can also cut out each item, place them in a bag and pull words from the bag.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
Can explain the concept of data visualization.
Has created a data dashboard for educational purposes.
Has participated in a data analytics workshop or training.
Has applied data analytics in an educational research paper.
Has used Microsoft Excel for data analysis.
Can discuss the role of predictive modeling in education.
Has used Google Sheets for collaborative data projects.
Has collaborated on a team project involving data analysis.
Has attended a data analytics conference or webinar.
Has an interest in machine learning applications in education.
Has contributed to a research project involving data analysis.
Can explain the importance of data quality in analytics.
Has used data to evaluate student performance.
Can discuss challenges and opportunities in educational data analytics.
Can describe a real-world example of data-driven decision-making in education.
Has knowledge of different types of data (qualitative, quantitative).
Has experience with educational data management systems.
Can demonstrate a basic data visualization using any tool.
Has knowledge of basic statistical concepts (mean, median, etc.).
Can name three data analytics tools or software.
Has an interest in data ethics and privacy.
Has applied data analytics to improve teaching strategies.
Has used data to identify patterns in student behavior.
Has worked with data related to student engagement.
