2018 Linking Study: Predicting Performance on the NSCAS Summative ELA and Mathematics Assessments based on MAP Growth Scores

Transcription

1 2018 Linking Study: Predicting Performance on the NSCAS Summative ELA and Mathematics Assessments based on MAP Growth Scores November 2018 Revised December 19, 2018 NWEA Psychometric Solutions

2 2018 NWEA. MAP Growth is a registered trademark of NWEA. This report is the product of research conducted by NWEA under contract to the Nebraska Department of Education.

3 Table of Contents Executive Summary Introduction Purpose of the Study Assessment Overview NSCAS Summative Assessments MAP Growth Methods Data Collection Linking Methods MAP Growth Scores MAP Growth Fall and Winter Scores Classification Accuracy Summary Statistics Proficiency Projection Results Study Sample Descriptive Statistics Corresponding MAP Growth and NSCAS Scores Classification Accuracy Summary Statistics Proficiency Projection References...19 Appendix A: Students with High MAP Growth Scores but Low NSCAS Scores...20 Appendix B: MAP Growth Scores that Predict Low, Moderate, and High Probabilities of NSCAS Proficiency...21 List of Tables Table 2.1. Descriptions of Classification Accuracy Summary Statistics...4 Table NSCAS Student Demographics...5 Table 3.2. Linking Study Sample Demographics...6 Table 3.3. Descriptive Statistics of NSCAS and MAP Growth Scores from the Study Sample...6 Table 3.4. Corresponding MAP Growth and NSCAS Scores ELA/Reading...7 Table 3.5. Corresponding MAP Growth and NSCAS Scores Mathematics...8 Table 3.6. Classification Accuracy for Proficiency...9 Table 3.7. Probability of Reaching Proficiency on NSCAS when MAP Growth is taken in...10 Table 3.8. Probability of Reaching Proficiency on NSCAS when MAP Growth is taken in the Fall or Winter ELA/Reading...13 Table 3.9. Probability of Reaching Proficiency on NSCAS when MAP Growth is taken in the Fall or Winter Mathematics Linking Study: Predicting Performance on NSCAS from MAP Growth Page i

4 Executive Summary This linking study, conducted in November 2018 using 2018 data, produced a set of MAP Growth Reading and Mathematics Rasch Unit () cut scores that correspond to the Nebraska Student-Centered Assessment System (NSCAS) Summative English Language Arts (ELA) and Mathematics scale scores associated with the Developing,, and College and Career Readiness (CCR) Benchmark achievement levels. The cut score demarks the minimum level of performance considered to be proficient for accountability purposes. These MAP Growth cut scores help determine whether students are on track to reach proficiency (i.e., the achievement level) on the NSCAS test in the spring based on students MAP Growth scores from the fall, winter, and spring administrations. For example, a Grade 3 student who obtained a MAP Growth Reading score of 200 in the fall is likely to receive proficiency on the NSCAS spring test. The degree to which MAP Growth tests can accurately predict student proficiency status on the NSCAS tests was determined by classification accuracy statistics based on spring test results. The classification accuracy rate is 0.84 for ELA/Reading for all grades and ranges from 0.86 to 0.87 for Mathematics, suggesting that the MAP Growth cut scores for each content area and grade are good predictors of whether a student will reach proficiency on the NSCAS Summative assessment. The results of this study can help educators predict student performance on the NSCAS Summative tests as early as possible and identify students at risk of failing to meet the required performance standards so they can receive the necessary resources and assistance to meet their goals. However, some caution should be taken when using this information: The tables provide information about scores on different tests that measure slightly different constructs. Therefore, the scores cannot be assumed to be interchangeable. ly students who took both the NSCAS and MAP Growth assessments in 2018 were included in the study sample. Since not all students took MAP Growth, the study sample did not include all NSCAS students. Therefore, caution should be exercised when generalizing the results to students who differ significantly in characteristics from this sample Linking Study: Predicting Performance on NSCAS from MAP Growth Page 1

5 1. Introduction 1.1. Purpose of the Study NWEA is committed to providing partners with useful tools to help make inferences about student learning from the MAP Growth test scores. An important use of MAP Growth results is to predict a student s performance on the state summative assessment at different times throughout the year. This allows educators and parents to determine if a student is on track in their learning to meet state standards by the end of the year or, given a student s learning profile, is on track to obtain rigorous, realistic growth in their content knowledge and skills. This document presents results from a linking study conducted by NWEA in November 2018 to statistically connect the scales of the Nebraska Student-Centered Assessment System (NSCAS) Summative English Language Arts (ELA) and Mathematics Grades 3 8 assessments with those of the MAP Growth Reading and Mathematics assessments taken during the 2018 term. The purpose of this study is to determine the MAP Growth scores that predict whether students are on track to reach proficiency on the NSCAS Summative ELA and Mathematics assessments. Specifically, this study produced the following outcomes: MAP Growth Reading and Mathematics Rasch Unit () cut scores that correspond to the cut scores on the NSCAS Summative ELA and Mathematics tests using the equipercentile linking procedure for MAP Growth spring results and the 2015 norms for MAP Growth fall and winter results. Classification accuracy summary statistics based on estimated MAP Growth cut scores to determine the degree to which MAP Growth tests accurately predict student proficiency status on the NSCAS tests. The probability of meeting or exceeding grade-level proficiency on the NSCAS spring assessment based on the observed MAP Growth scores taken during the fall and winter using the 2015 norms (Thum & Houser, 2015) Assessment Overview NSCAS Summative Assessments The NSCAS Summative ELA and Mathematics assessments are administered once a year in the spring in Grades 3 8. The NSCAS Summative Science assessment is also administered in the spring in Grades 5 and 8. The assessments include multiple-choice and technologyenhanced items and provide total scores comparable across grades, subscores, growth across administrations, and achievement levels. The Science assessments are administered as fixedform assessments, whereas ELA and Mathematics are administered online adaptively beginning in 2018, with paper-pencil versions available as an accommodation. ELA and Mathematics have two cut scores in each grade that distinguish between the following achievement levels. The cut score (i.e., the score that distinguishes between Developing and performance) demarks the minimum level of performance considered to be proficient for accountability purposes. Developing College and Career Readiness (CCR) Benchmark 2018 Linking Study: Predicting Performance on NSCAS from MAP Growth Page 2

6 MAP Growth MAP Growth Reading and Mathematics are computer adaptive interim assessments aligned to the Nebraska College and Career Ready Standards. The MAP Growth Reading assessments are comparable to the academic content standards in ELA. MAP Growth scores are reported on a vertical scale with a range of in Rasch Unit (). Each content area has its own scale. To aid interpretation of MAP Growth scores, NWEA periodically conducts norming studies of student and school performance on MAP Growth. The most recent MAP Growth norming study by Thum & Hauser (2015) employed multi-level growth models on nearly 500,000 longitudinal test scores from over 100,000 students that were weighted to create large, nationally representative norms. 2. Methods 2.1. Data Collection The linking study is based on data from the 2018 NSCAS ELA and Mathematics and MAP Growth Reading and Mathematics assessments. ly students who took both the NSCAS and MAP Growth assessments in 2018 were included in the study sample. Each of these student s NSCAS record was matched to their MAP Growth score by using the student s first and last names, date of birth, student ID, and other available identifying information. After merging MAP Growth and NSCAS data, the following exclusion rules were applied to remove any invalid students: If a student did not complete the test (i.e., the student did not respond to all 48) If a student does not have either a scale score or achievement level If a student has an invalid test code 2.2. Linking Methods The equipercentile procedure (e.g., Kolen & Brennan, 2004) was used to link the NSCAS scores and the MAP Growth spring scores, and the 2015 MAP Growth norms (Thum & Hauser, 2015) were used to link the NSCAS scores and the MAP Growth fall and winter scores. The MAP Growth spring cut scores could be calculated using the equipercentile linking method because that data is directly connected to the NSCAS spring data used in the study MAP Growth Scores The equipercentile linking procedure matches scores on the two scales that have the same percentile rank (i.e., the proportion of tests at or below each score). Consider the linked scores between two tests. Let x represent a score on Test X (e.g., NSCAS). Its equipercentile equivalent score on Test Y (e.g., MAP Growth), e y (x), can be obtained through a cumulativedistribution-based linking function defined in Equation 1: e y (x) = G 1 [P(x)] (1) where e y (x) is the equipercentile equivalent of score x on NSCAS on the scale of MAP Growth, P(x) is the percentile rank of a given score on Test X, and G 1 is the inverse of the percentile rank function for Test Y that indicates the score on Test Y corresponding to a given percentile. Polynomial loglinear pre-smoothing was applied to reduce irregularities of the score distributions and equipercentile linking curve Linking Study: Predicting Performance on NSCAS from MAP Growth Page 3

7 MAP Growth Fall and Winter Scores MAP Growth conditional growth norms provide students expected score gains across testing seasons (Thum & Hauser, 2015). This information was used to estimate the previous fall and winter terms MAP Growth scores that would meet the spring cut, considering the growth that is expected of the previous term s value. Equation 2 was used to determine the fall or winter MAP Growth score needed to reach the spring cut score, considering the expected growth associated with the previous score: = previous + g (2) where: is the MAP Growth spring cut. previous is the unknown fall or winter score. g is the expected growth from fall or winter to spring corresponding to previous Classification Accuracy Summary Statistics The degree to which MAP Growth tests predict student proficiency status on the NSCAS tests can be described using classification accuracy statistics, which are important indicators for evaluating reliability and validity of classification results. Table 2.1 describes the classification accuracy statistics provided in this report. The results are based on the 2018 MAP Growth and NSCAS data for proficiency (i.e., the cut score between Developing and + CCR Benchmark). Table 2.1. Descriptions of Classification Accuracy Summary Statistics Classification Accuracy Statistic Description* Interpretation Overall Classification Accuracy Rate Sensitivity Specificity False Negative Rate False Positive Rate (TP + TN) / (total sample size) TP / (TP + FN) TN / (TN + FP) FN / (FN + TP) FP / (FP + TN) *TN = true negatives. FP = false positives. FN = false negatives. TP = true positives. The proportion of students in the study sample whose proficiency classification on the state test was correctly predicted by MAP Growth cut scores (Pommerich, Hanson, Harris, & Sconing, 2004). The proportion of proficient students who were correctly identified on the MAP Growth test as such. The proportion of below-proficient students who were correctly identified on the MAP Growth test as such. The proportion of proficient students who were incorrectly predicted by MAP Growth test to be below proficiency. The proportion of below-proficient students who were incorrectly predicted by MAP Growth test to be proficient Proficiency Projection In additional to the fall and winter MAP Growth cut scores, the MAP Growth conditional growth norms data were also used to calculate the probability of reaching proficiency on the NSCAS test based on the student s MAP Growth scores from fall, winter, and spring. Equation 3 was used to calculate the probability of a student achieving proficiency (i.e., the achievement level) on the NSCAS test based on their fall or winter MAP Growth score: 2018 Linking Study: Predicting Performance on NSCAS from MAP Growth Page 4

8 Pr(Achieving in spring starting ) = Φ ( previous + g ) (3) SD where: Φ is a standardized normal cumulative distribution. previous is the student s score in fall or winter. g is the expected growth from fall or winter to spring corresponding to that previous. is the MAP Growth cut score for spring. SD is the conditional standard deviation of growth from fall or winter to spring. Equation 4 was used to estimate the probability of a student achieving proficiency on the NSCAS test based on their spring MAP Growth score: Pr(Achieving in spring spring ) = Φ ( ) (4) SE where is the student s score in spring, and SE is the standard error of measurement for MAP Growth. 3. Results 3.1. Study Sample ly students who took both the NSCAS and MAP Growth assessments in 2018 were included in the study sample. Table 3.1 presents the ethnicity and gender distributions for all students who took the 2018 NSCAS Summative assessment, and Table 3.2 presents the demographics of the student sample used in the linking study. While the n-count differs by about 10,000 students for each grade and content area, the ethnicity and gender distributions are very similar, indicating that the study sample is a good representation of the general NSCAS student population. Table NSCAS Student Demographics Content Area ELA Mathematics Ethnicity* Gender Grade N White Black Hispanic Asian AI/AN NH/PI MR Female Male 3 24, , , , , , , , , , , , *AI/AN = American Indian/Alaska Native. NH/PI = Native Hawaiian or Other Pacific Islander. MR = Other/Multi-Race Linking Study: Predicting Performance on NSCAS from MAP Growth Page 5

9 Table 3.2. Linking Study Sample Demographics Content Area ELA Mathematics Ethnicity* Gender Grade N White Black Hispanic Asian AI/AN NH/PI MR Female Male 3 15, , , , , , , , , , , , *AI/AN = American Indian/Alaska Native. NH/PI = Native Hawaiian or Other Pacific Islander. MR = Other/Multi-Race Descriptive Statistics Table 3.3 provides descriptive statistics of the NSCAS and MAP Growth scores for 2018, including the correlation coefficient (r) between the two scales. As shown in the table, the correlation coefficients between MAP Growth and NSCAS scores range from 0.81 to 0.83 for ELA/Reading and 0.85 to 0.87 for Mathematics. In general, these correlations can be considered criterion-related validity evidence between MAP Growth and NSCAS assessments by content area. These results indicate that the relationship between MAP Growth and NSCAS test scores is strong. Table 3.3. Descriptive Statistics of NSCAS and MAP Growth Scores from the Study Sample Content Area Grade N r ELA Mathematics NSCAS* MAP Growth* Mean SD Min. Max. Mean SD Min. Max. 3 15, , , , , , , , , , , , *SD = standard deviation. Min. = minimum. Max. = maximum Linking Study: Predicting Performance on NSCAS from MAP Growth Page 6

10 3.3. Corresponding MAP Growth and NSCAS Scores Table 3.4 and Table 3.5 present the NSCAS scale scores for each achievement level and the corresponding MAP Growth cut scores and percentile ranges by content area and grade. These tables can be used to predict a student s likely achievement level on the NSCAS test when MAP Growth is taken in the spring, fall, or winter. For example, a Grade 6 student who obtained a MAP Growth Reading score of 222 in the spring is likely to reach proficiency on the NSCAS test. A Grade 3 student who obtained a MAP Growth Reading score of 200 in the fall is also likely to reach proficiency on the NSCAS spring test. Table 3.4. Corresponding MAP Growth and NSCAS Scores ELA/Reading NSCAS ELA Grade Developing * CCR Benchmark MAP Growth Reading () Developing CCR Benchmark Grade Percentile * Percentile Percentile Grade MAP Growth Reading (Winter) Developing CCR Benchmark Percentile * Percentile Percentile Grade MAP Growth Reading (Fall) Developing CCR Benchmark Percentile * Percentile Percentile *Bolded numbers indicate the cut scores considered to be at least proficient for accountability purposes Linking Study: Predicting Performance on NSCAS from MAP Growth Page 7

11 Table 3.5. Corresponding MAP Growth and NSCAS Scores Mathematics NSCAS Mathematics Grade Developing * CCR Benchmark MAP Growth Mathematics () Developing CCR Benchmark Grade Percentile * Percentile Percentile MAP Growth Mathematics (Winter) Developing CCR Benchmark Grade Percentile * Percentile Percentile MAP Growth Mathematics (Fall) Developing CCR Benchmark Grade Percentile * Percentile Percentile *Bolded numbers indicate the cut scores considered to be at least proficient for accountability purposes Linking Study: Predicting Performance on NSCAS from MAP Growth Page 8

12 3.4. Classification Accuracy Summary Statistics Table 3.6 presents the overall classification accuracy rate, sensitivity, specificity, false positive rate, and false negative rate. These results indicate how well MAP Growth spring scores predict proficiency on the NSCAS tests, providing insight into the predictive validity of MAP Growth tests. The overall classification accuracy rate is 0.84 for ELA/Reading for all grades and ranges from 0.86 to 0.87 for Mathematics. These values suggest that the MAP Growth cut scores for each content area and grade are good predictors of whether a student will reach proficiency on the NSCAS Summative assessment. Table 3.6. Classification Accuracy for Proficiency Grade ELA/Reading N Score Rate* MAP Growth NSCAS Class. Accuracy* FP FN Sensitivity Specificity 3 15, , , , , , Mathematics 3 15, , , , , , *Class. Accuracy = overall classification accuracy rate. FP = false positives. FN = false negatives Proficiency Projection Table 3.7, Table 3.8, and Table 3.9 present the estimated probability of meeting the achievement level on the spring NSCAS test based on students observed MAP Growth score when MAP Growth is taken in the spring, fall, or winter, respectively. For example, a Grade 3 student who obtained a MAP Growth Mathematics score of 199 in the fall has an 83% chance of reaching proficiency or higher on the NSCAS spring test Linking Study: Predicting Performance on NSCAS from MAP Growth Page 9

13 Table 3.7. Probability of Reaching Proficiency on NSCAS when MAP Growth is taken in Grade 3 4 Start Percentile ELA/Reading Score Mathematics Score No < No < No < No < No < No < No < No < No < No < No < No < No No No No No No No No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes > Yes > Yes > Yes > Yes > Yes > Yes > Yes > Yes > No < No < No < No < No < No < No < No < No < No < No < No < No No No No No No No No Yes Yes Yes Yes Yes Yes Yes Yes Yes > Yes > Yes > Yes > Yes > Yes > Yes > Yes > Yes > Yes > Linking Study: Predicting Performance on NSCAS from MAP Growth Page 10

14 Grade 5 6 Start Percentile ELA/Reading Score Mathematics Score No < No < No < No < No < No < No < No < No < No < No < No < No < No < No No No No No No No No Yes Yes Yes Yes Yes Yes Yes Yes > Yes > Yes > Yes > Yes > Yes > Yes > Yes > Yes > No < No < No < No < No < No < No < No < No < No < No < No < No < No No No No No No No No Yes No Yes Yes Yes Yes Yes > Yes Yes > Yes Yes > Yes > Yes > Yes > Yes > Yes > Yes > Linking Study: Predicting Performance on NSCAS from MAP Growth Page 11

15 Grade 7 8 Start Percentile ELA/Reading Score Mathematics Score No < No < No < No < No < No < No < No < No < No < No < No < No < No < No < No < No No No No No No No Yes Yes Yes Yes Yes Yes Yes > Yes Yes > Yes > Yes > Yes > Yes > Yes > Yes > No < No < No < No < No < No < No < No < No < No < No < No < No < No < No < No < No No < No No No No No No Yes Yes Yes Yes Yes Yes Yes Yes > Yes > Yes > Yes > Yes > Yes > Yes >0.99 *Prob. = Probability of obtaining proficient status on the NSCAS test in the spring Linking Study: Predicting Performance on NSCAS from MAP Growth Page 12

16 Table 3.8. Probability of Reaching Proficiency on NSCAS when MAP Growth is taken in the Fall or Winter ELA/Reading Grade 3 4 Start Percentile Fall ELA/Reading (Fall) Winter ELA/Reading (Winter) No < No < No < No < No No < No No < No No No No No No No No No No No No No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes > Yes > Yes > No < No < No < No < No No < No No No No No No No No No No No No No No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes > Yes > Yes > Linking Study: Predicting Performance on NSCAS from MAP Growth Page 13

17 Grade 5 6 Start Percentile Fall ELA/Reading (Fall) Winter ELA/Reading (Winter) No < No < No < No < No No < No No < No No No No No No No No No No No No No No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes > Yes > Yes > No < No < No < No < No No < No No < No No < No No No No No No No No No No No No No No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes > Yes > Yes > Linking Study: Predicting Performance on NSCAS from MAP Growth Page 14

18 Grade 7 8 Start Percentile Fall ELA/Reading (Fall) Winter ELA/Reading (Winter) No < No < No < No < No < No < No No < No No < No No No No No No No No No No No No No No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes > Yes > No < No < No < No < No No < No No < No No < No No No No No No No No No No No No No No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes >0.99 *Prob. = Probability of obtaining proficient status on the NSCAS test in the spring Linking Study: Predicting Performance on NSCAS from MAP Growth Page 15

19 Table 3.9. Probability of Reaching Proficiency on NSCAS when MAP Growth is taken in the Fall or Winter Mathematics Grade 3 4 Start Percentile Fall Mathematics (Fall) Winter Mathematics (Winter) No < No < No < No < No No < No No < No No No No No No No No No No No No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes > Yes > Yes > No < No < No < No < No No < No No < No No No No No No No No No No No No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes > Yes Yes > Yes > Yes > Linking Study: Predicting Performance on NSCAS from MAP Growth Page 16

20 Grade 5 6 Start Percentile Fall Mathematics (Fall) Winter Mathematics (Winter) No < No < No < No < No < No < No No < No No < No No No No No No No No No No No No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes > Yes Yes > Yes > Yes > No < No < No < No < No No < No No < No No No No No No No No No No Yes No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes > Yes Yes > Yes > Yes > Yes > Yes > Linking Study: Predicting Performance on NSCAS from MAP Growth Page 17

21 Grade 7 8 Start Percentile Fall Mathematics (Fall) Winter Mathematics (Winter) No < No < No < No < No < No < No < No < No No < No No < No No No No No No No No No No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes > Yes > Yes > Yes > Yes > No < No < No < No < No < No < No < No < No No < No No < No No < No No No No No No No No No No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes > Yes Yes > Yes > Yes >0.99 *Prob. = Probability of obtaining proficient status on the NSCAS test in the spring Linking Study: Predicting Performance on NSCAS from MAP Growth Page 18

22 4. References Kolen, M. J., & Brennan, R. L. (2004). Test equating, scaling, and linking. New York: er. Pommerich, M., Hanson, B., Harris, D., & Sconing, J. (2004). Issues in conducting linkage between distinct tests. Applied Psychological Measurement, 28(4), Thum, Y. M., & Hauser, C. H. (2015). NWEA 2015 MAP norms for student and school achievement status and growth. NWEA Research Report. Portland, OR: NWEA Linking Study: Predicting Performance on NSCAS from MAP Growth Page 19

23 Appendix A: Students with High MAP Growth Scores but Low NSCAS Scores Appendix A: Students with High MAP Growth Scores but Low NSCAS Scores Table A.1 presents the number of students who had high MAP Growth scores but low NSCAS scores by demographics (i.e., their MAP Growth score did not accurately predict their performance on the NSCAS Summative test). Out of the 167,749 students included in this linking study sample across both content areas, 222 of them received a lower NSCAS score than predicted by their MAP Growth score (i.e., less than 1% of the study sample). Most of these cases occurred for the NSCAS ELA assessment. It may be the difference in what is measured between the two assessments is contributing to these cases. Teachers of these students may wish to compare the students reading ability and their writing ability in the classroom as a follow-up investigation given that MAP Growth Reading does not measure writing skills whereas NSCAS ELA does. Table A.1. Number of Students with High MAP Growth, Low NSCAS Scores by Demographics Number of Students* Gender ELL Ethnicity Grade Total F M White Black Hispanic Asian AI/AN NH/PI MR IEP FRL Disability ELA Total Mathematics Total *F = female. M = male. ELL = English language learner. 1 = Current ELL. 2 = Former ELL. 3 = Non-ELL. AI/AN = American Indian/Alaska Native. NH/PI = Native Hawaiian or Other Pacific Islander. MR = Multiracial. IEP = Individual Education Plan. FRL = Free and reduced lunch Linking Study: Predicting Performance on NSCAS from MAP Growth Page 20

24 Appendix B: MAP Growth Scores that Predict Low, Moderate, and High Probabilities of NSCAS Proficiency Appendix B: MAP Growth Scores that Predict Low, Moderate, and High Probabilities of NSCAS Proficiency Table B.1 presents the MAP Growth score ranges that predict whether students are on track to reach proficiency (i.e., or CCR Benchmark achievement levels) on the NSCAS Summative ELA and Mathematics Grades 3 8 assessments based on low, moderate, and high probabilities: Low = less than a 50% chance of being or Above Moderate = between 50% and 75% chance of being or Above High = greater than a 75% chance of being or Above For example, if an ELA Grade 3 student received a MAP Growth Reading score of 209 in the spring, they would have greater than a 75% chance of being proficient on the NSCAS assessment. Teachers who are looking for a higher likelihood of or Above would want to use scores in the high probability range. Table B.1. MAP Growth Score Ranges that Predict Low, Moderate, and High Probabilities of NSCAS Proficiency Grade Low Moderate High ELA/Reading Mathematics Linking Study: Predicting Performance on NSCAS from MAP Growth Page 21