We introduce a short answer scoring engine made up of an ensemble of deep neural networks and a Latent Semantic Analysis-based model to score short constructed responses for a large suite of questions from a national assessment program. We evaluate the performance of the engine and show that the engine achieves above-human-level performance on a…

Language test developers have a responsibility to ensure that their tests are accessible to test takers of various backgrounds and characteristics and also that they have the opportunity to perform to the best of their ability. This principle is widely recognised by educational and language testing associations in guidelines for the production and…

Research suggests that between 25% to 40% of students experience test anxiety, with students with disabilities and those from culturally and linguistically diverse backgrounds having higher prevalence rates. Since test anxiety impacts student well-being and the validity of the important educational decisions based on testing data, this article…

Comparison of special education teacher (n=18) and computer-scored curriculum-based measurements (CBM) of spelling found that computer scoring accuracy was significantly higher and more stable. Additionally, high correlations were found between the CBM spelling scores and a standardized test of spelling achievement. (DB)

This collection explores the theory and applications of educational testing. It is divided into sections on theory and general principles of educational measurement, administration of tests and scoring, and applications of testing. The following chapters present information on test theory and use: (1) "Current Perspectives and Future…