Collaborative Center for Literacy Development

Research Questions for CCLD Research Agenda Priority Topic #3: Student Achievement Data

1.     What student achievement data does Kentucky collect that can help us understand how to teach students to read and write better? What additional achievement data need to be collected?

2.     What populations are not currently represented (or are inadequately represented) in existing data sets (i.e. adult prisoners, home and private schools, English-language learners), and how can data on these populations be effectively collected and used?

3.     What are the patterns of student literacy achievement in Kentucky? For example, what variations exist within geographic regions (e.g., by school, grade level, demographics, etc.)?

4.     Historically, how has Kentucky’s performance on nationally-normed assessments (e.g., NAEP) compared with performance on state-designed testing (e.g., KCCT)?

5.     How does student achievement in Kentucky compare to national trends? For example, how does the achievement of Kentucky African-American children compare to the achievement of African-American children nationally?

6.     How can student achievement data be used to analyze patterns in reading and writing scores in Kentucky, including longitudinally?

7.     Which aspects of literacy are measured at different age levels on current assessments? Which components are not assessed?

8.    How well do literacy achievement results align across multiple assessments?

9.     Which data sets can be analyzed to inform achievement (what has been learned), prediction (likelihood of educational success at the next level), and diagnosis (points for learning intervention)?

10.    What affects the literacy development of an individual from early childhood into adulthood (i.e. change of school, relocation, interrupted schooling, period of low skill development)?

11.    What is the relationship of literacy achievement to achievement in content areas and to post-formal education outcomes?

12.     How can large-scale achievement data be used with classroom-level, formative data to inform teaching and learning based on a complete picture of student literacy?