Search Results: (1-5 of 5 records)
Pub Number | Title | Date |
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NCES 2023015 | Middle Grades Longitudinal Study of 2017–18 (MGLS:2017) Assessment Item Level File (ILF), Read Me
This ReadMe provides guidance and documentation for users of the Middle Grades Longitudinal Study of 2017-18 (MGLS:2017) Assessment Item Level File (ILF)(NCES 2023-014) made available to researchers under a restricted use only license. Other supporting documentation includes MGLS_Math_and_Reading_Items_User_Guide.xlsx, MGLS_MS1_Math_Item_Images.pdf, MGLS_MS2_Math_Item_Images.pdf, MGLS_MS1_MS2_Reading_Sample_Item_Type_Images.pdf, MGLS_MS1_MS2_EF_HeartsFlowers_Instructions.pptx, and MGLS_MS2_EF_Spatial_2-back_Instructions.pptx |
8/16/2023 |
NCES 2023013 | User’s Manual for the MGLS:2017 Data File, Restricted-Use Version
This manual provides guidance and documentation for users of the Middle Grades Longitudinal Study of 2017–18 (MGLS:2017) restricted-use school and student data files (NCES 2023-131). An overview of MGLS:2017 is followed by chapters on the study data collection instruments and methods; direct and indirect student assessment data; sample design and weights; response rates; data preparation; data file content, including the composite variables; and the structure of the data file. Appendices include a psychometric report, a guide to scales, field test reports, and school and student file variable listings. |
8/16/2023 |
REL 2016169 | A guide to developing and evaluating a college readiness screener
This guide describes core ideas for colleges to consider when developing a screening tool for estimating college readiness. A key focal point within the guide is a discussion of ways to improve how well a screening tool can identify individuals needing remedial or developmental education along with key considerations that a user or developer of such a tool must address. Specifically, the following steps are discussed: 1.Creating an operational definition of success and college readiness 2.Selecting potential predictors of college readiness 3.Prioritizing types of classification error 4.Collecting and organizing the necessary data 5.Developing predictive models 6.Evaluating the screening results and selecting the final model |
9/7/2016 |
REL 2014042 | The College Readiness Data Catalog Tool: User Guide
The College Readiness Data Catalog Tool and User Guide enable states, districts and other educational entities to assess the presence of college readiness indicators in extant data sets and identify gaps that may present challenges in developing future indicator systems. The College Readiness Data Catalog tool is a flexible Excel workbook that provides a shell for organizing and tracking student data relevant for measuring college readiness. The user guide also includes a sample data catalog summary report and a template for a data catalog summary report. Created by REL Northeast and Islands for the US Virgin Islands College and Career Readiness Research Alliance, the tool may be used by any educational organization to determine whether it has sufficient data to study college readiness indicators. |
9/24/2014 |
REL 2010085 | Processes and Challenges in Identifying Learning Disabilities Among English Language Learner Students in three New York State Districts
To help districts accurately identify students who are English language learners and also have learning disabilities, this study examines practices and challenges in the processes applied in three New York State districts in identifying learning disabilities among students who are English language learners. Using interviews with district and school personnel and documents from state and district web sites, the study finds both similarities and differences in practices, with more differences in the prereferral process than in the referral process. It identifies eight challenges to the identification of learning disabilities in English language learner students: difficulties with policy guidelines; different stakeholder views about timing for referral of English language learner students; insufficient knowledge among personnel involved in identification; difficulties providing consistent, adequate services to English language learner students; lack of collaborative structures in prereferral; lack of access to assessments that differentiate between second language development and learning disabilities; lack of consistent monitoring of struggling students who are English language learners; and difficulty obtaining students' previous school records. Further analysis suggests five interrelated elements that appear to be important for avoiding misidentification of learning disabilities among students who are English language learners: adequate professional knowledge, effective instructional practices, effective and valid assessment and interventions, interdepartmental collaborative structures, and clear policy guidelines. |
2/16/2010 |
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