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Rupp, André A. – Applied Measurement in Education, 2018
This article discusses critical methodological design decisions for collecting, interpreting, and synthesizing empirical evidence during the design, deployment, and operational quality-control phases for automated scoring systems. The discussion is inspired by work on operational large-scale systems for automated essay scoring but many of the…
Descriptors: Design, Automation, Scoring, Test Scoring Machines
Peer reviewedSchmoker, Mike – Educational Leadership, 2003
Calls for simplicity when presenting data on student achievement. Data should help teachers improve teaching and learning, and focus on specific goals such as determining how many students are succeeding in a subject and, within that subject, what are the areas of strength or weakness. (Contains 22 references.) (WFA)
Descriptors: Academic Achievement, Data Analysis, Data Collection, Data Interpretation
Peer reviewedPopham, W. James – Educational Leadership, 2003
Discusses which kinds of data educators should respect and which they should reject. Asserts that most state accountability tests fail to produce the kinds of data that will improve teaching and learning. Teachers can get the data they need from their own instructionally useful classroom assessments. (WFA)
Descriptors: Academic Achievement, Accountability, Data Analysis, Data Collection
Brinckerhoff, Loring C.; And Others – 1988
The paper focuses on three critical programming issues in providing support services to higher education students with learning disabilities. The first issue concerns the garnering of administrative support for students with learning disabilities. Administrative support cannot be effectively achieved until college administrators determine where…
Descriptors: Accountability, College Administration, College Programs, College Students

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