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Anne-Mai Meesak; Dmitri Rozgonjuk; Tiia Õun; Eve Kikas – Education 3-13, 2024
Children's development during early childhood affects their well-being and educational success, but there are few reliable assessment instruments available. The aim of the study was to develop, pilot and validate an e-assessment instrument for assessing five-year-old children's development in cognitive processes, learning, language and…
Descriptors: Test Validity, Computer Assisted Testing, Measures (Individuals), Child Development
Kim, Jin-Young – Educational Technology & Society, 2015
This study explores and describes different viewpoints on Computer Based Assessment (CBA) by using Q methodology to identify perspectives of students and instructors and classify these into perceptional typologies. Thirty undergraduate students taking CBA courses and fifteen instructors adopting CBA into their curriculum at a university in Korea,…
Descriptors: Computer Assisted Testing, Classification, Q Methodology, Undergraduate Students
Deane, Paul – ETS Research Report Series, 2014
This paper explores automated methods for measuring features of student writing and determining their relationship to writing quality and other features of literacy, such as reading rest scores. In particular, it uses the "e-rater"™ automatic essay scoring system to measure "product" features (measurable traits of the final…
Descriptors: Writing Processes, Writing Evaluation, Student Evaluation, Writing Skills
Arce-Ferrer, Alvaro J.; Guzman, Elvira Martinez – Educational and Psychological Measurement, 2009
This study investigates the effect of mode of administration of the Raven Standard Progressive Matrices test on distribution, accuracy, and meaning of raw scores. A random sample of high school students take counterbalanced paper-and-pencil and computer-based administrations of the test and answer a questionnaire surveying preferences for…
Descriptors: Factor Analysis, Raw Scores, Statistical Analysis, Computer Assisted Testing
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