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Charles Hulme; Joshua McGrane; Mihaela Duta; Gillian West; Denise Cripps; Abhishek Dasgupta; Sarah Hearne; Rachel Gardner; Margaret Snowling – Language, Speech, and Hearing Services in Schools, 2024
Purpose: Oral language skills provide a critical foundation for formal education and especially for the development of children's literacy (reading and spelling) skills. It is therefore important for teachers to be able to assess children's language skills, especially if they are concerned about their learning. We report the development and…
Descriptors: Automation, Language Tests, Standardized Tests, Test Construction
Chen, Dandan; Hebert, Michael; Wilson, Joshua – American Educational Research Journal, 2022
We used multivariate generalizability theory to examine the reliability of hand-scoring and automated essay scoring (AES) and to identify how these scoring methods could be used in conjunction to optimize writing assessment. Students (n = 113) included subsamples of struggling writers and non-struggling writers in Grades 3-5 drawn from a larger…
Descriptors: Reliability, Scoring, Essays, Automation
Roberts , Amy M.; LoCasale-Crouch, Jennifer; Hamre, Bridget K.; Buckrop, Jordan M. – Online Learning, 2017
Although scalable programs, such as online courses, have the potential to reach broad audiences, they may pose challenges to evaluating learners' knowledge and skills. Automated scoring offers a possible solution. In the current paper, we describe the process of creating and testing an automated means of scoring a validated measure of teachers'…
Descriptors: Video Technology, Scoring, Automation, Computer Assisted Testing
Nese, Joseph F. T.; Kahn, Josh; Kamata, Akihito – Grantee Submission, 2017
Despite prevalent use and practical application, the current and standard assessment of oral reading fluency (ORF) presents considerable limitations which reduces its validity in estimating growth and monitoring student progress, including: (a) high cost of implementation; (b) tenuous passage equivalence; and (c) bias, large standard error, and…
Descriptors: Automation, Speech, Recognition (Psychology), Scores
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