Seton Hall University
A Family and Community Variable Prediction Model for NJ ASK Mathematics Sixth and Seventh Grade Assessments Results: The Impact on School Evaluation
Abstract
dc:description.abstract<p>This study examined the predictive accuracy of family and community demographic variables found in the U.S. Census data on the percentage of students at the school level who scored Proficient or above on the NJ ASK 6 and 7 Mathematics section when controlling for teacher mobility and level of teacher education. Analysis included simultaneous multiple linear regression and hierarchical linear regression. This study looked at 100% of the New Jersey school districts with complete sets of 2010 NJ ASK 6 and 7 data and 2010 census data and tested at least 25 students in each grade level. Only schools servicing Grades 6 and 7 students from their hometown were included to maintain clean demographic data. The results of this study revealed that 67% of school level 2010 NJ ASK 6 Math scores could be predicted within 10 points by looking solely at three out-of-school community variables. The results of this study also revealed that 72% of school level 2010 NJ ASK 7 Math scores could be predicted within 10 points by looking solely at three out-of-school community variables. This research study contributes to the limited but growing body of knowledge indicating inadequacy of the use of state standardized assessments as the sole measure of student achievement.</p>
Degree
thesis:*- Name thesis:degree_name
- Executive Ed.D. in Education Leadership Management and Policy
- Level thesis:degree_level
- Dissertation
- Discipline thesis:degree_discipline
- Education Leadership, Management and Policy
- Year dc:date.available
- 2015
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- McCahill, Kevin R.
- Contributors dc:contributor
-
- Anthony Colella, Ph.D
- Christopher Tienken, Ed.D
- Tracey Polizzi, Ph.D
- Amanda Gunning, Ph.D
Subjects
dc:subject × 9Identifiers
dc:identifier.*- Repository record dc:identifier
- https://scholarship.shu.edu/dissertations/2088
- OAI identifier oai:identifier
- oai:scholarship.shu.edu:dissertations-3132