Has created adatadashboard foreducationalpurposes.Has knowledgeof basicstatisticalconcepts(mean, median,etc.).Can describe areal-worldexample of data-driven decision-making ineducation.Can explainthe conceptof datavisualization.Has applieddata analyticsin aneducationalresearch paper.Has applieddata analyticsto improveteachingstrategies.Has usedMicrosoftExcel fordataanalysis.Can discussthe role ofpredictivemodeling ineducation.Has an interestin machinelearningapplications ineducation.Candemonstrate abasic datavisualizationusing any tool.Has usedGoogleSheets forcollaborativedata projects.Has aninterest indata ethicsand privacy.Has attendeda dataanalyticsconference orwebinar.Has used datato identifypatterns instudentbehavior.Can explaintheimportance ofdata qualityin analytics.Has knowledgeof differenttypes of data(qualitative,quantitative).Has useddata toevaluatestudentperformance.Has contributedto a researchprojectinvolving dataanalysis.Hascollaborated ona team projectinvolving dataanalysis.Hasparticipated in adata analyticsworkshop ortraining.Can discusschallenges andopportunitiesin educationaldata analytics.Has experiencewitheducationaldatamanagementsystems.Has workedwith datarelated tostudentengagement.Can namethree dataanalyticstools orsoftware.Has created adatadashboard foreducationalpurposes.Has knowledgeof basicstatisticalconcepts(mean, median,etc.).Can describe areal-worldexample of data-driven decision-making ineducation.Can explainthe conceptof datavisualization.Has applieddata analyticsin aneducationalresearch paper.Has applieddata analyticsto improveteachingstrategies.Has usedMicrosoftExcel fordataanalysis.Can discussthe role ofpredictivemodeling ineducation.Has an interestin machinelearningapplications ineducation.Candemonstrate abasic datavisualizationusing any tool.Has usedGoogleSheets forcollaborativedata projects.Has aninterest indata ethicsand privacy.Has attendeda dataanalyticsconference orwebinar.Has used datato identifypatterns instudentbehavior.Can explaintheimportance ofdata qualityin analytics.Has knowledgeof differenttypes of data(qualitative,quantitative).Has useddata toevaluatestudentperformance.Has contributedto a researchprojectinvolving dataanalysis.Hascollaborated ona team projectinvolving dataanalysis.Hasparticipated in adata analyticsworkshop ortraining.Can discusschallenges andopportunitiesin educationaldata analytics.Has experiencewitheducationaldatamanagementsystems.Has workedwith datarelated tostudentengagement.Can namethree dataanalyticstools orsoftware.

Data Explorer BINGO - Call List

(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.


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  1. Has created a data dashboard for educational purposes.
  2. Has knowledge of basic statistical concepts (mean, median, etc.).
  3. Can describe a real-world example of data-driven decision-making in education.
  4. Can explain the concept of data visualization.
  5. Has applied data analytics in an educational research paper.
  6. Has applied data analytics to improve teaching strategies.
  7. Has used Microsoft Excel for data analysis.
  8. Can discuss the role of predictive modeling in education.
  9. Has an interest in machine learning applications in education.
  10. Can demonstrate a basic data visualization using any tool.
  11. Has used Google Sheets for collaborative data projects.
  12. Has an interest in data ethics and privacy.
  13. Has attended a data analytics conference or webinar.
  14. Has used data to identify patterns in student behavior.
  15. Can explain the importance of data quality in analytics.
  16. Has knowledge of different types of data (qualitative, quantitative).
  17. Has used data to evaluate student performance.
  18. Has contributed to a research project involving data analysis.
  19. Has collaborated on a team project involving data analysis.
  20. Has participated in a data analytics workshop or training.
  21. Can discuss challenges and opportunities in educational data analytics.
  22. Has experience with educational data management systems.
  23. Has worked with data related to student engagement.
  24. Can name three data analytics tools or software.