Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 0 |
| Since 2017 (last 10 years) | 0 |
| Since 2007 (last 20 years) | 3 |
Descriptor
Author
| Algina, James | 1 |
| Cheung, Alan C. K. | 1 |
| Clariana, Roy | 1 |
| Deering, Kathleen N. | 1 |
| Keselman, H. J. | 1 |
| Lix, Lisa M. | 1 |
| Slavin, Robert E. | 1 |
| Wilcox, Rand R. | 1 |
Publication Type
| Journal Articles | 2 |
| Reports - Descriptive | 1 |
| Reports - Evaluative | 1 |
| Reports - Research | 1 |
Education Level
| Elementary Education | 2 |
| Elementary Secondary Education | 1 |
| Grade 6 | 1 |
| Secondary Education | 1 |
Audience
Location
| Pennsylvania | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
| Does not meet standards | 1 |
Direct linkCheung, Alan C. K.; Slavin, Robert E. – Center for Research and Reform in Education, 2011
The use of educational technology in K-12 classrooms has been gaining tremendous momentum across the country since the 1990s. Many school districts have been investing heavily in various types of technology, such as computers, mobile devices, internet access, and interactive whiteboards. Almost all public schools have access to the internet and…
Descriptors: Evidence, Elementary Secondary Education, Mathematics Achievement, Program Effectiveness
Peer reviewedClariana, Roy – Journal of Computers in Mathematics and Science Teaching, 2009
This quasi-experimental investigation considers the second year of implementation of wireless laptops (1:1 ratio) in three 6th grade mathematics classrooms in one school compared to non-laptop classrooms (5:1 ratio) in seven other schools in the district. Comprehensive mathematics software from CompassLearning delivered via the internet was…
Descriptors: State Standards, Mathematics Achievement, Computer Software, Effect Size
A Generally Robust Approach for Testing Hypotheses and Setting Confidence Intervals for Effect Sizes
Keselman, H. J.; Algina, James; Lix, Lisa M.; Wilcox, Rand R.; Deering, Kathleen N. – Psychological Methods, 2008
Standard least squares analysis of variance methods suffer from poor power under arbitrarily small departures from normality and fail to control the probability of a Type I error when standard assumptions are violated. This article describes a framework for robust estimation and testing that uses trimmed means with an approximate degrees of…
Descriptors: Intervals, Testing, Least Squares Statistics, Effect Size
