Parkway’s Math Common Assessments A brief study of their validity and ability to predict MAP scores
Reliability versus Validity • Reliability measures consistency. • Does a test consistently give us the same result time after time? • Validity measures accuracy. • Does a test measure what it is supposed to be measuring?
Target Practice http://www.socialresearchmethods.net/kb/relandval.php
How do we determine validity? • Validity can be determined by running correlations. • The most common is Pearson’s Product-Moment Correlation Coefficient (r). • In this case, we compare student common assessment scores to MAP test scores.
Pearson’s Coefficient (r) • A value between -1 and 1. • -1 is a perfect negative correlation. • 1 is a perfect positive correlation. • 0 is no correlation. • -0.8 is a strong negative correlation. • 0.8 is a strong positive correlation. Correlations measure the relationship between two variables. They do not measure causation.
Quick way to determine what a specific coefficient means Size of coefficientGeneral Interpretation • .8 to 1.0 Very strong relationship • .6 to .8 Strong relationship • .4 to .6 Moderate relationship • .2 to .4 Weak relationship • 0 to .2 Weak or no relationship Salkind (2005) – cited in report
Correlation Coefficients http://mste.illinois.edu/courses/ci330ms/youtsey/scatterinfo.html
Pearson Coefficients of Correlations (r) forCorresponding 2009 Common Assessments and MAP Math Tests
So what could we do about it? • Perform an item by item validity analysis by calculating correlations between common assessment items and MAP test items . • Obviously, the common assessment items and the MAP items we compared would have to be testing the same concept. • Then delete the poorly correlated items and replace them with new items. • Check how the new items correlate the following year.
Predicting MAP scores using multiple regression • It is very common to use accepted data to offer a prediction of the future. The opportunity of using existing data to predict future outcomes is viewed as model-building. That is to say, existing data are used to build a model of the future, with a predetermined degree of error built into the model. Multiple regression is a common and useful tool for model building. (Thomas W. MacFarland, 1998) http://www.nyx.net/~tmacfarl/STAT_TUT/reg_sion.ssi
Common Assessment Percentages and Corresponding Predicted Achievement LevelOn the MAP Math Test
Or, you can use these equations for individual students. . . 5th Grade: 6th Grade: 7th Grade: 8th Grade: