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Introduction To The Middle School Data Team. This Demo Uses Fictional Data For Purposes of Example The Ultimate Goal is to Answer Your Questions with Your Data. DataTeamConsulting.Com. Middle School Data Team. Purpose of the Data Team
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Introduction To The Middle School Data Team This Demo Uses Fictional Data For Purposes of Example The Ultimate Goal is to Answer Your Questions with Your Data DataTeamConsulting.Com
Middle School Data Team Purpose of the Data Team The purpose of the Middle School data team is to use quantitative and qualitative data, as much as possible, to improve teaching and learning. • Members of the Data Team • The purpose of this presentation is to invite you to become a member of the data team. To provide a taste of the possibilities, we will present one line of inquiry of interest to the current members. The current members: • Roberto da Costa • Samuel Guthrie • Xi’an Coy Manh • Danielle Moonstar • Sean Parker (consultant) • Rahne Sinclair DataTeamConsulting.Com
How well do 5th grade Math MCAS scores predict 6th grade Math MCAS scores? Scatterplot of 6th grade math scores vs. 5th grade math scores (n = 159). We will use MCAS scale scores. 220 = N.I. 240 = Prof. 260 = Adv. Advanced Proficient Needs Improvement Warning/Failing DataTeamConsulting.Com
What does the scatterplot tell us? Scatterplot of 6th grade math scores vs. 5th grade math scores (n = 159). Initials: F.J. Math MCAS 5th Grade: 222 6th Grade: 228 Initials: L.M. Math MCAS 5th Grade: 280 6th Grade: 274 Initials: J.P. Math MCAS 5th Grade: 244 6th Grade: 224 Initials: R.K. Math MCAS 5th Grade: 246 6th Grade: 268 Initials: L.H. Math MCAS 5th Grade: 238 6th Grade: 248 DataTeamConsulting.Com
Each data point is a small part of a much larger story. Scatterplot of 6th grade math scores vs. 5th grade math scores (n = 159). DataTeamConsulting.Com
We can make predictions based on the (limited) data. Scatterplot of 6th grade math scores vs. 5th grade math scores (n = 159). DataTeamConsulting.Com
The prediction line is “pulled” by every observation. Scatterplot of 6th grade math scores vs. 5th grade math scores (n = 159). DataTeamConsulting.Com
Once we have a prediction line, we can use it to make predictions. Scatterplot of 6th grade math scores vs. 5th grade math scores (n = 159). Example: For students who score 240 on the 5th grade Math MCAS, we predict that they will score 242 on the 6th grade Math MCAS. 242 Of course, some students do much better (or worse) than our prediction. DataTeamConsulting.Com
We can also use the prediction to identify students who break the pattern. Scatterplot of 6th grade math scores vs. 5th grade math scores (n = 159). Example: Some students do much better on the 6th grade Math MCAS than we would predict based on their 5th grade scores. Is there a pattern within the pattern? DataTeamConsulting.Com
Is there a pattern within the pattern? • We have two valuable resources to answer this question. • First and foremost, we have teachers with deep professional knowledge of these students. For example, if given a list of names of students who do better than predicted, teachers may be able to discern commonalities and perhaps causes. • Secondly, we have additional quantitative information that we can bring to bear. For example, first semester grades provide information over and above the previous year’s MCAS score. (Note that numbers alone cannot get at causes unless we have random “treatment” and “control” groups.) For grades, we will use an average of English, social studies, math and science, because we know that all subjects are correlated with all MCAS tests. (We will include more subjects in the average as we get the data.) DataTeamConsulting.Com
Using grades to uncover the pattern within the pattern. Students who earned an A in their first semester at Middle School: RED DataTeamConsulting.Com
Using grades to uncover the pattern within the pattern. Students who earned an A in their first semester at Middle School: RED Students who earned a B in their first semester at Middle School: Blue A DataTeamConsulting.Com
Using grades to uncover the pattern within the pattern. Students who earned a B in their first semester at Middle School: Blue Students who earned a Cin their first semester at Middle School: Green A B DataTeamConsulting.Com
Using grades to uncover the pattern within the pattern. Students who earned a Cin their first semester at Middle School: Green A B C DataTeamConsulting.Com
We can use the prediction lines to make predictions. Predicted 6th grade math scores based on 5th grade math scores and first-semester grades. Example: For students who score 240 on the 5th grade Math MCAS, we predict differently depending on how they perform in the first semester of the 6th grade. A 252 242 B 232 C The previous year’s MCAS score is not destiny. DataTeamConsulting.Com
We can use this information to flag students who may need extra help. Predicted 6th grade math scores based on 5th grade math scores and first-semester grades. Example: Almost all students who earn a C in the first semester of the 6th grade are at risk of scoring less than 240, regardless of how they scored on the 5th grade math MCAS. A B C
Some students break the pattern, and teachers can see who. Predicted 6th grade math scores based on 5th grade math scores and first-semester grades. Example: Some students do much better on the 6th grade Math MCAS than we would predict based on 5th grade scores and first term grades. A B C DataTeamConsulting.Com
We can construct plots for not only Math MCAS but also for ELA MCAS. Predicted 6th grade MCAS scores based on 5th grade scores and first-semester grades. Math ELA DataTeamConsulting.Com
We can also construct plots to predict 7th grade scores. Predicted 7th grade MCAS scores based on 6th grade scores and first-semester grades. Math ELA DataTeamConsulting.Com
We can also construct plots to predict 8th grade scores. Predicted 8th grade MCAS scores based on 7th grade scores and first-semester grades. Math ELA DataTeamConsulting.Com
Future Lines of Inquiry Future lines of inquiry for the data team: • Does the MCAS/grades pattern hold up across the years? (The current patterns are based on one cohort.) • What other factors do we need to consider? E.g., special education status, free lunch eligibility, classroom conduct as assessed by teachers. • Based on professional experience and knowledge, what are the potential causes? How can we dig deeper into the causes using qualitative and quantitative data? Future lines of inquiry for an action team: What policies and interventions do the data suggest? (The data team and the action teams should be separate. The purpose of the data team should be informative.) DataTeamConsulting.Com
Appendix I GPA 4.0 Scale (Continuous) See Appendix II for 3-D Scatterplot RVF Plot: • Assumption Checking • Appears Normal • Independence Is Tricky • Appears Homoskedastic • Appears Linear • No Apparent Outlier Problem • No Stat Sig Interaction DataTeamConsulting.Com
Appendix II DataTeamConsulting.Com