Publication Date
| In 2025 | 0 |
| Since 2024 | 0 |
| Since 2021 (last 5 years) | 0 |
| Since 2016 (last 10 years) | 1 |
| Since 2006 (last 20 years) | 4 |
Descriptor
| Bayesian Statistics | 4 |
| Comparative Analysis | 4 |
| Regression (Statistics) | 4 |
| Achievement Gains | 3 |
| Computation | 3 |
| Correlation | 3 |
| Data Analysis | 3 |
| Prediction | 3 |
| Scores | 3 |
| Accountability | 2 |
| Age Differences | 2 |
| More ▼ | |
Author
| Foorman, Barbara R. | 2 |
| Kershaw, Sarah | 2 |
| Koon, Sharon | 2 |
| Petscher, Yaacov | 2 |
| Allen, Jeff | 1 |
| Barnes, Tiffany, Ed. | 1 |
| Desmarais, Michel, Ed. | 1 |
| Romero, Cristobal, Ed. | 1 |
| Ventura, Sebastian, Ed. | 1 |
Publication Type
| Reports - Research | 2 |
| Collected Works - Proceedings | 1 |
| Journal Articles | 1 |
| Reports - Evaluative | 1 |
Education Level
| Grade 10 | 4 |
| Grade 9 | 4 |
| Secondary Education | 4 |
| Elementary Education | 3 |
| Elementary Secondary Education | 3 |
| Grade 4 | 3 |
| Grade 7 | 3 |
| Grade 8 | 3 |
| Grade 3 | 2 |
| Grade 5 | 2 |
| Grade 6 | 2 |
| More ▼ | |
Audience
Location
| Florida | 2 |
| Australia | 1 |
| Czech Republic | 1 |
| Israel | 1 |
| Massachusetts | 1 |
| Netherlands | 1 |
| North Carolina | 1 |
| Pennsylvania | 1 |
| Slovakia | 1 |
| Spain | 1 |
| Utah | 1 |
| More ▼ | |
Laws, Policies, & Programs
Assessments and Surveys
| Florida Comprehensive… | 2 |
| Dynamic Indicators of Basic… | 1 |
| Massachusetts Comprehensive… | 1 |
| SAT (College Admission Test) | 1 |
| Woodcock Reading Mastery Test | 1 |
What Works Clearinghouse Rating
Peer reviewed
Direct linkAllen, Jeff – Applied Measurement in Education, 2017
Using a sample of schools testing annually in grades 9-11 with a vertically linked series of assessments, a latent growth curve model is used to model test scores with student intercepts and slopes nested within school. Missed assessments can occur because of student mobility, student dropout, absenteeism, and other reasons. Missing data…
Descriptors: Achievement Gains, Academic Achievement, Growth Models, Scores
Download full textPetscher, Yaacov; Kershaw, Sarah; Koon, Sharon; Foorman, Barbara R. – Regional Educational Laboratory Southeast, 2014
Districts and schools use progress monitoring to assess student progress, to identify students who fail to respond to intervention, and to further adapt instruction to student needs. Researchers and practitioners often use progress monitoring data to estimate student achievement growth (slope) and evaluate changes in performance over time for…
Descriptors: Reading Comprehension, Reading Achievement, Elementary School Students, Secondary School Students
Petscher, Yaacov; Kershaw, Sarah; Koon, Sharon; Foorman, Barbara R. – Regional Educational Laboratory Southeast, 2014
Districts and schools use progress monitoring to assess student progress, to identify students who fail to respond to intervention, and to further adapt instruction to student needs. Researchers and practitioners often use progress monitoring data to estimate student achievement growth (slope) and evaluate changes in performance over time for…
Descriptors: Response to Intervention, Achievement Gains, High Stakes Tests, Prediction
Barnes, Tiffany, Ed.; Desmarais, Michel, Ed.; Romero, Cristobal, Ed.; Ventura, Sebastian, Ed. – International Working Group on Educational Data Mining, 2009
The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…
Descriptors: Data Analysis, Educational Research, Conferences (Gatherings), Foreign Countries
