Publication Date
| In 2025 | 0 |
| Since 2024 | 0 |
| Since 2021 (last 5 years) | 0 |
| Since 2016 (last 10 years) | 0 |
| Since 2006 (last 20 years) | 2 |
Descriptor
| Educational Research | 2 |
| Incentives | 2 |
| Research Methodology | 2 |
| Standards | 2 |
| Academic Achievement | 1 |
| Academic Persistence | 1 |
| Affective Behavior | 1 |
| Algebra | 1 |
| Alignment (Education) | 1 |
| Asynchronous Communication | 1 |
| Behavior | 1 |
| More ▼ | |
Author
Publication Type
| Collected Works - Proceedings | 1 |
| Reports - Research | 1 |
Education Level
| Elementary Education | 2 |
| Secondary Education | 2 |
| Elementary Secondary Education | 1 |
| Grade 6 | 1 |
| Higher Education | 1 |
| Intermediate Grades | 1 |
| Junior High Schools | 1 |
| Middle Schools | 1 |
| Postsecondary Education | 1 |
Audience
Laws, Policies, & Programs
Assessments and Surveys
| Program for International… | 1 |
What Works Clearinghouse Rating
Download full textRoschelle, Jeremy; Feng, Mingyu; Gallagher, H. Alix; Murphy, Robert; Harris, Christopher; Kamdar, Danae; Trinidad, Gucci – Grantee Submission, 2014
Recruitment is a key challenge for researchers conducting any large school-based study. Control is needed not only over the condition participants receive, but also over how the intervention is implemented, and may include restrictions in other areas of school and classroom functioning. We report here on our experiences in recruiting participants…
Descriptors: Research Methodology, Control Groups, Experimental Groups, Educational Research
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection
