Publication Date
In 2025 | 0 |
Since 2024 | 1 |
Since 2021 (last 5 years) | 2 |
Since 2016 (last 10 years) | 5 |
Since 2006 (last 20 years) | 6 |
Descriptor
Computer Assisted Testing | 6 |
Data Collection | 6 |
Grade 8 | 5 |
Computation | 3 |
Accuracy | 2 |
Classification | 2 |
Data Analysis | 2 |
Engineering | 2 |
Feedback (Response) | 2 |
Foreign Countries | 2 |
Grade 4 | 2 |
More ▼ |
Source
International Association for… | 1 |
International Working Group… | 1 |
Journal of Education for… | 1 |
Journal of Educational Data… | 1 |
National Assessment of… | 1 |
Technology, Knowledge and… | 1 |
Author
Publication Type
Reports - Research | 4 |
Journal Articles | 3 |
Collected Works - Proceedings | 1 |
Numerical/Quantitative Data | 1 |
Reports - Descriptive | 1 |
Education Level
Elementary Education | 6 |
Grade 8 | 6 |
Junior High Schools | 6 |
Middle Schools | 6 |
Secondary Education | 6 |
Grade 4 | 3 |
Intermediate Grades | 2 |
Adult Education | 1 |
Elementary Secondary Education | 1 |
Grade 10 | 1 |
Grade 12 | 1 |
More ▼ |
Audience
Researchers | 1 |
Teachers | 1 |
Location
Australia | 1 |
Chile | 1 |
Czech Republic | 1 |
Denmark | 1 |
Finland | 1 |
France | 1 |
Germany | 1 |
Israel | 1 |
Italy | 1 |
Kazakhstan | 1 |
Luxembourg | 1 |
More ▼ |
Laws, Policies, & Programs
Assessments and Surveys
National Assessment of… | 2 |
Massachusetts Comprehensive… | 1 |
What Works Clearinghouse Rating
Ethan R. Van Norman; Emily R. Forcht – Journal of Education for Students Placed at Risk, 2024
This study evaluated the forecasting accuracy of trend estimation methods applied to time-series data from computer adaptive tests (CATs). Data were collected roughly once a month over the course of a school year. We evaluated the forecasting accuracy of two regression-based growth estimation methods (ordinary least squares and Theil-Sen). The…
Descriptors: Data Collection, Predictive Measurement, Predictive Validity, Predictor Variables
Levin, Nathan A. – Journal of Educational Data Mining, 2021
The Big Data for Education Spoke of the NSF Northeast Big Data Innovation Hub and ETS co-sponsored an educational data mining competition in which contestants were asked to predict efficient time use on the NAEP 8th grade mathematics computer-based assessment, based on the log file of a student's actions on a prior portion of the assessment. In…
Descriptors: Learning Analytics, Data Collection, Competition, Prediction
Tate, Tamara P.; Warschauer, Mark – Technology, Knowledge and Learning, 2019
The quality of students' writing skills continues to concern educators. Because writing is essential to success in both college and career, poor writing can have lifelong consequences. Writing is now primarily done digitally, but students receive limited explicit instruction in digital writing. This lack of instruction means that students fail to…
Descriptors: Writing Tests, Computer Assisted Testing, Writing Skills, Writing Processes
Fraillon, Julian, Ed.; Ainley, John, Ed.; Schulz, Wolfram, Ed.; Friedman, Tim, Ed.; Duckworth, Daniel, Ed. – International Association for the Evaluation of Educational Achievement, 2020
IEA's International Computer and Information Literacy Study (ICILS) 2018 investigated how well students are prepared for study, work, and life in a digital world. ICILS 2018 measured international differences in students' computer and information literacy (CIL): their ability to use computers to investigate, create, participate, and communicate at…
Descriptors: International Assessment, Computer Literacy, Information Literacy, Computer Assisted Testing
National Assessment of Educational Progress (NAEP), 2017
The National Assessment of Education Progress (NAEP) is the largest continuing and nationally representative assessment of what the nation's students know and can do in subjects such as civics, geography, mathematics, reading, U.S. history, and writing. The results of NAEP are released as The Nation's Report Card. NAEP is a congressionally…
Descriptors: National Competency Tests, Computer Assisted Testing, Grade 4, Grade 8
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