Assessment-based learning environments (ABLEs) make use of assessment information coming from a variety of sources (e.g., formative and summative assessments) to guide instruction. We have developed English ABLE, an assessment-based learning environment designed to help English language learners (ELLs) learn about English grammar. Key features of English ABLE include item/task reuse (900 enhanced Test of English as a Foreign Language™ [TOEFL®] items were recalibrated based on data from native Spanish speakers who have taken the test) and a Bayesian psychometric student model that makes use of item statistics, adaptive feedback, adaptive sequencing of tasks, pedagogical agents (i.e., Dr. Grammar, Jorge, and Carmen), and an indirectly visible student model. This paper describes main issues regarding the design and implementation of English ABLE including findings from a literature review, results from a preliminary market scan, and initial evaluations by domain experts, and the use of enhanced assessment assets (EAA) technology. It also summarizes the results of an initial evaluation with ELLs carried out in November 2006.
