When looking at student data, this is much harder. Here are two real examples using NWEA MAP data:
Group 1: Current First Grade Students in Math
Fall Score - 171.66 RIT Mean
Winter Score - 181.48 RIT Mean
Mean Growth - 9.78 RIT
68% of Students make their target growth
19% more overall growth than a class of comparative peers in the Fall
Group 2: Current Fourth Grade Students in Math
Fall Score - 205.73 RIT Mean
Winter Score - 210.80 RIT Mean
Mean Growth - 5.07 RIT
50% of Students make their target growth
2% more overall growth than a class of comparative peers in the Fall
From the data, it Group 1's teachers clearly out performed Group 2's teachers. They added more value. If only it were this easy. Lets add one more data point:
Group 1: Current First Grade Students in Math
Spring Score - 181.30 RIT Mean
Fall Score - 171.66 RIT Mean
Winter Score - 181.48 RIT Mean
Mean Growth (Spring to Winter) - 0.18 RIT
Group 2: Fourth Grade Students in Math
Spring Score - 205.50 RIT Mean
Fall Score - 205.73 RIT Mean
Winter Score - 210.80 RIT Mean
Mean Growth (Spring to Winter) - 5.30 RIT
Group 1 did a great job this year with what they had. Their students lost a significant amount over the Summer (over 10 RIT points) and they brought those children back during the first semester. Who do we blame for the loss? The six-year old students? Their parents? Their Kindergarten teacher who got them that high? Lack of year round schools? None of these are realistic options. These teachers and children had significant growth but it was earn back growth.
Group 2 also did a great job. At the surface it seemed simply average, but as we look deeper this group achieved all new growth. They cut into new territory and helped their children learn new things because of the lack of regression for these students.
Growth is vital to our overall achievement but it is more than a pre-post test scenario. It is complex including multiple factors: school, home, teacher, student, parent(s), and society. We need to drive forward and help improve, but when analyzing the data we can't simply set universal bars and say go achieve. It's far more complicated than that and that's ok. Perhaps there is more to growth of a child than simple numbers.
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