Intersections: Student Background and Early Literacy Performance
Saved in:
| Title: | Intersections: Student Background and Early Literacy Performance |
|---|---|
| Language: | English |
| Authors: | Mariann Lemke, Dan Murphy, Aaron Soo Ping Chow, Angela Acuña, WestEd |
| Source: | WestEd. 2024. |
| Availability: | WestEd. 730 Harrison Street, San Francisco, CA 94107-1242. Tel: 877-493-7833; Tel: 415-565-3000; Fax: 415-565-3012; Web site: http://www.wested.org |
| Peer Reviewed: | N |
| Page Count: | 8 |
| Publication Date: | 2024 |
| Document Type: | Reports - Descriptive |
| Education Level: | Elementary Education Secondary Education |
| Descriptors: | Elementary School Students, Secondary School Students, Literacy, Screening Tests, Grants, State Aid, Emergent Literacy, Progress Monitoring, Comparative Testing, Reports |
| Geographic Terms: | Massachusetts |
| Abstract: | Beginning with the 2020/21 school year, the Massachusetts Department of Elementary and Secondary Education (DESE) began an ongoing effort to collect and analyze early literacy screening assessment data from schools and districts participating in certain state grants to inform improvement efforts. Outcome data suggest that the current educational system often does not provide adequate support for students from historically marginalized groups, such as those learning English or students with disabilities. Early literacy screening assessments aim to identify students who are not on track to become successful readers and who therefore require additional support. Analysis of the numbers of students identified as significantly below benchmark (using the benchmarks provided within each screening assessment that identify students who need support) shows--as decades of research have shown--that there are differences in student performance that are associated with students' backgrounds. Although prior analysis considers student background characteristics separately, this issue brief examines the multiple overlapping identities that characterize students' backgrounds. To explore how students' intersecting social and economic characteristics relate to risk of reading difficulties, the authors estimated a multilevel statistical model that examines how these characteristics and school-level factors interact with one another and with the outcome of being classified as significantly below bench mark more than once during the school year. Model results show that the likelihood of students being identified as needing additional support increases as their association with groups that have been historically undersupported in the general education system increases, but that these increases vary by student groups and school characteristics. |
| Abstractor: | ERIC |
| Entry Date: | 2025 |
| Accession Number: | ED663858 |
| Database: | ERIC |
| Abstract: | Beginning with the 2020/21 school year, the Massachusetts Department of Elementary and Secondary Education (DESE) began an ongoing effort to collect and analyze early literacy screening assessment data from schools and districts participating in certain state grants to inform improvement efforts. Outcome data suggest that the current educational system often does not provide adequate support for students from historically marginalized groups, such as those learning English or students with disabilities. Early literacy screening assessments aim to identify students who are not on track to become successful readers and who therefore require additional support. Analysis of the numbers of students identified as significantly below benchmark (using the benchmarks provided within each screening assessment that identify students who need support) shows--as decades of research have shown--that there are differences in student performance that are associated with students' backgrounds. Although prior analysis considers student background characteristics separately, this issue brief examines the multiple overlapping identities that characterize students' backgrounds. To explore how students' intersecting social and economic characteristics relate to risk of reading difficulties, the authors estimated a multilevel statistical model that examines how these characteristics and school-level factors interact with one another and with the outcome of being classified as significantly below bench mark more than once during the school year. Model results show that the likelihood of students being identified as needing additional support increases as their association with groups that have been historically undersupported in the general education system increases, but that these increases vary by student groups and school characteristics. |
|---|
