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Direct linkMatthieu Cisel – Canadian Journal of Education, 2024
Over the last decade, teachers in France have been increasingly pressured to use digital learning environments, and to shift from grade-based to skill-based assessment. Educational dashboards, which measure student input electronically, could foster such a transition by providing insights into learners' performances. However, such dashboards could…
Descriptors: Foreign Countries, Computer Assisted Testing, Summative Evaluation, Elementary School Students
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
Download full textLevin, 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
Van Norman, Ethan R.; Ysseldyke, James E. – School Psychology Review, 2020
Within multitiered systems of support, assessment practices that limit the amount of time students miss instruction should be prioritized. At the same time, decisions about student response to intervention need to be based upon technically adequate data. We evaluated the impact of data collection frequency and trend estimation method on the…
Descriptors: Data Collection, Adaptive Testing, Computer Assisted Testing, Computation
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
Nelson, Peter M.; Van Norman, Ethan R.; Klingbeil, Dave A.; Parker, David C. – Psychology in the Schools, 2017
Although extensive research exists on the use of curriculum-based measures for progress monitoring, little is known about using computer adaptive tests (CATs) for progress-monitoring purposes. The purpose of this study was to evaluate the impact of the frequency of data collection on individual and group growth estimates using a CAT. Data were…
Descriptors: Progress Monitoring, Computer Assisted Testing, Data Collection, Scheduling
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
Lawrence, K. S. – National Center on Schoolwide Inclusive School Reform: The SWIFT Center, 2016
This brief describes how to use a free online behavior screener to identify student support needs in middle and high schools. Inclusive Behavior Instruction utilizes data to identify appropriate social-emotional supports for all students. The Lane et al. (2016) study demonstrated system-wide use of a free online behavior screener at the middle and…
Descriptors: Screening Tests, Student Behavior, Behavior Problems, Middle School Students
Scheu, Ian Edward; Lawrence, Thomas – Journal of Educational Computing Research, 2013
This article details the construction of a computer program to test cognitive processing differences in adolescents engaged in a standard presentation of tests versus a fantasy-based game presentation. The article will discuss the challenges of creating a replication of traditional psychological tests into a new medium which holds comparable…
Descriptors: Psychological Testing, Computer Assisted Testing, Games, Adolescents
Hu, Xiangen, Ed.; Barnes, Tiffany, Ed.; Hershkovitz, Arnon, Ed.; Paquette, Luc, Ed. – International Educational Data Mining Society, 2017
The 10th International Conference on Educational Data Mining (EDM 2017) is held under the auspices of the International Educational Data Mining Society at the Optics Velley Kingdom Plaza Hotel, Wuhan, Hubei Province, in China. This years conference features two invited talks by: Dr. Jie Tang, Associate Professor with the Department of Computer…
Descriptors: Data Analysis, Data Collection, Graphs, Data Use
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
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
