পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| Opportunity-to-Learn Index× | Educational Hierarchical Linear Modeling× | |
|---|---|---|
| ক্ষেত্র | Education | Education |
| পরিবার≠ | Process / pipeline | Regression model |
| উদ্ভবের বছর≠ | 1995 | 2002 |
| প্রবর্তক≠ | Carroll (concept); Husén/IEA (measurement); McDonnell; Schmidt (TIMSS) | Stephen Raudenbush & Anthony Bryk |
| ধরন≠ | Quantitative index of students' exposure to instructional content and resources | Multilevel regression for hierarchically nested educational data |
| মৌলিক উৎস≠ | McDonnell, L. M. (1995). Opportunity to learn as a research concept and a policy instrument. Educational Evaluation and Policy Analysis, 17(3), 305–322. DOI ↗ | Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical Linear Models: Applications and Data Analysis Methods (2nd ed.). Sage. ISBN: 9780761919049 |
| অপর নাম | OTL Index, Content Coverage Index, Curriculum Exposure Measure, Opportunity-to-Learn Measurement | Multilevel Models in Education, Students-in-Schools HLM, School Effects Multilevel Model, Random-Effects Models for Educational Data |
| সম্পর্কিত | 4 | 4 |
| সারসংক্ষেপ≠ | An opportunity-to-learn (OTL) index quantifies how much exposure students have had to the content and instructional resources they need to succeed on an assessment. Rooted in Carroll's model of school learning and developed through the IEA international studies, OTL measurement asks whether students were actually taught the material before being tested on it. Constructed from teacher reports, curriculum analysis, or instructional logs, OTL indices are used both as a fairness criterion for interpreting test scores and as a policy instrument for monitoring equitable access to the intended curriculum. | Educational hierarchical linear modeling (HLM) is a multilevel regression framework for data in which students are nested within classrooms and classrooms within schools. Formalized for education by Raudenbush and Bryk, it lets the intercept and slopes of a student-level regression vary across schools, simultaneously estimating student-level relationships, school-level relationships, and the cross-level interactions between them — while producing correct standard errors that single-level regression on clustered data cannot. |
| ScholarGateডেটাসেট ↗ |
|
|