Document Type thesis Author Name Whorton, Skyler URN etd-041913-095912 Title Can a computer adaptive assessment system determine, better than traditional methods, whether students know mathematics skills? Degree MS Department Computer Science Advisors Neil T. Heffernan, Advisor Joseph Beck, Reader Keywords intelligent tutoring system computer adaptive test item response theory assessment education Date of Presentation/Defense 2013-04-19 Availability unrestricted
Schools use commercial systems specifically for mathematics benchmarking and longitudinal assessment. However these systems are expensive and their results often fail to indicate a clear path for teachers to differentiate instruction based on studentsí individual strengths and weaknesses in specific skills. ASSISTments is a web-based Intelligent Tutoring System used by educators to drive real-time, formative assessment in their classrooms. The software is used primarily by mathematics teachers to deliver homework, classwork and exams to their students. We have developed a computer adaptive test called PLACEments as an extension of ASSISTments to allow teachers to perform individual student assessment and by extension school-wide benchmarking. PLACEments uses a form of graph-based knowledge representation by which the exam results identify the specific mathematics skills that each student lacks. The system additionally provides differentiated practice determined by the studentsí performance on the adaptive test. In this project, we describe the design and implementation of PLACEments as a skill assessment method and evaluate it in comparison with a fixed-item benchmark.
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