Assessing American Sign Language performance: Developing an environment for capturing, evaluating, and monitoring student progress

American Sign Language (ASL) has become the third most widely used language in America preceded only by English and Spanish; however, the methods used to assess ASL performance are problematic, resulting in a system that is administratively complex and fails to support student learning. We are presently creating a languagelearning environment that will fundamentally improve the methods and processes used to assess ASL performance. The environment will be a cost-effective application of pedagogicallyand technologically-advanced innovations that together improve instructional quality. Parallel to the creation of the system, we are developing Curriculum Based Measures (CBM) to establish a flexible, fast, valid, and reliable technique for measuring student progress and promoting early detection of learning difficulties. The CBM will be integrated into the four-tier software environment that establishes (a) a platform for students to capture, submit, and archive ASL performances, (b) a setting for instructors to evaluate and report student performance, (c) a portfolio where students can monitor performance, and (d) an administration component to manage and coordinate performanceand evaluation-data. In this paper, we outline the existing development and significance of the environment and identify our initial research exploring the optimal frame rate and video size for use in performance capture and evaluation.