Data Analysis: Naperville School District 203

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Type of Assessment

PARCC (Partnership for Assessment of Readiness for College and Careers) assessment utilizes the performance-based design aimed at assessing students’ knowledge, skills, and their application. DLM (Dynamic Learning Maps) test is also performance-based; however, it includes open-ended and multiple-choice questions.

Purpose and Characteristics of These Assessments. How Credible is This Source of Data?

PARCC assessment is used to assess critical thinking in students and the level of their knowledge in certain basic subjects. The school districts use it to measure the performance of their students against the performance of other students across the state. It allows students and educators to measure progress, identify and address gaps in learning in order to prepare for a college education or career. The test assesses the knowledge and skills of 3-11 grade students in two basic spheres such as English Language Arts and Mathematics. After several states terminated their membership with the PARCC program, the test was readjusted (Adams & Lyons, 2014). The test was designed by several states, approved by the U.S. Department of Education, and received funding for integration into schools’ curricula. This gives the assessment credibility.

As for the DLM, it is designed to measure the compliance of students who have mental disabilities with state academic content standards. It is administered if a student experiences difficulties with taking regular testing. It helps to uncover the reasons why a student has learning issues and which actions are needed to adapt his or her program to build comprehensive knowledge and skills in accordance with the learning standards. The test aligns with Essential Elements (EEs) that represent state standards for student academic abilities. It is administered to students in elementary, middle, and high school. The credibility of the test is ascertained through its alignment with state-created and approved EEs which are based on scientific data (“Dynamic learning maps essential elements for mathematics,” n.d.).

Analysis of Results

According to the results of the PARCC assessment, about 60 percent of the student population meets the educational standards across the grades from 3 to 8. The number of those who met the expectations is relatively stable across all grades and does not change significantly through the years (2015-2017). However, the percentage of children exceeding expectations decreases sharply in grade 4 and then gradually rises in grade 8. Thus, in the third grade, the percentage of students who scored above the standard expectations in 2017 equaled 26%, and in the next grade decreased dramatically to 10%. By the 8th grade, that figure rose to 17% (ISBE, n.d.b).

As for the DLM, it shows the opposite picture. Only 17-40% of students met the EEs in 2017 (ISBE, n.d.a). Most of the students did not meet the learning criteria and demonstrated only the emerging understanding and ability to apply their knowledge and skills in Mathematics. However, the positive trend can be observed, as through grades 3 to 8 the percentage of students who approached the target rose notwithstanding the sharp fall in the 6th grade. Thus, 46% of the 3rd-grade students showed only the emerging level of compliance, while in grade 8, the percentage dropped to 29 (ISBE, n.d.a).

Patterns of Results Related to Student Achievement

The result patterns for both PARCC and DLM demonstrate the growth of academic achievements in students as they progress through learning stages. Both assessments serve to guide educators on how to address the educational gaps and tailor curriculums. Judging by the results, it appears that they manage to fulfill their task. Yet, PARCC shows a slight decrease in the number of students, whose abilities exceeded the average results in the early grades. This might indicate the lack of attention given to such students. However, the percentile difference is rather small and constitutes only 9%, which might not be a reason for concern yet.

Reliability and Validity of the Data

The reliability, as was mentioned earlier, is backed by the state and national level support for the assessments. In addition, it is established through a continuous 3-year-long assessment that demonstrates the repeatability of the results in both PARCC and DLM. Mathematical skills and knowledge were assessed using adequately tailored items developed according to higher-level standards. The main strength of the data was that the test results were not included in the statistics if the sample was comprised of less than 10 participants. Among the weaknesses, one can mention the lack of numerical values to back percentages.

Recommendations

The decrease in the number of bright students provides grounds for the reassessment of strategies to foster their academic achievements and maintain their interest in learning activities. Overall-high percentage of students who do not meet the EEs poses a concern for early-to-middle education. There should be a dramatic change in teaching practices to increase the level of compliance with standards in students with mental disabilities. For a Balanced Assessment System, there is a need for larger samples, a few more years of data, and the data on the number of students constituting one or another score level.

References

Adams, M., & Lyons, J. (2014). PARCC guidebook: Success strategies for teachers. New York, NY: Lumos Learning.

Dynamic learning maps essential elements for mathematics. (n.d.). Web.

Illinois State Board of Education (ISBE). (n.d.a). DLM. Web.

Illinois State Board of Education (ISBE). (n.d.b). PARCC. Web.

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ChalkyPapers. (2022, February 15). Data Analysis: Naperville School District 203. Retrieved from https://chalkypapers.com/data-analysis-naperville-school-district-203/

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ChalkyPapers. (2022, February 15). Data Analysis: Naperville School District 203. https://chalkypapers.com/data-analysis-naperville-school-district-203/

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"Data Analysis: Naperville School District 203." ChalkyPapers, 15 Feb. 2022, chalkypapers.com/data-analysis-naperville-school-district-203/.

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ChalkyPapers. (2022) 'Data Analysis: Naperville School District 203'. 15 February.

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ChalkyPapers. 2022. "Data Analysis: Naperville School District 203." February 15, 2022. https://chalkypapers.com/data-analysis-naperville-school-district-203/.

1. ChalkyPapers. "Data Analysis: Naperville School District 203." February 15, 2022. https://chalkypapers.com/data-analysis-naperville-school-district-203/.


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ChalkyPapers. "Data Analysis: Naperville School District 203." February 15, 2022. https://chalkypapers.com/data-analysis-naperville-school-district-203/.