American Sign Language (ASL) is 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 creating a language-learning environment to improve the methods and processes used to assess ASL performance. The environment will be designed to reflect pedagogically- and technologicallyadvanced innovations that together improve instructional quality. Parallel to the creation of the system, we are developing Curriculum Based Measurements (CBM) to establish flexible, fast, valid, and reliable techniques for measuring student progress and promoting early detection of learning difficulties. CBM will be integrated into the four-tier software environment to establish (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 individual performance, and (d) an administration component to manage and coordinate performance- and evaluation-data. In this paper, we outline the development and significance of the environment and identify our initial research exploring the optimal framerate and video size for use in performance capture and evaluation.