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

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