Abstract: A resource allocation can be utilized to control resources to determine trustworthy item scores for a respondent's response to an assessment item. Embodiments may utilize one or more resources to extract the student response to an item, one or more resources to establish an item score for that item based on the extracted response, and one or more resources to evaluate the extracted or score and further utilize such resources until a trustworthy item score is established. Confidence indicators may be used for both digital representations of student responses and the scores derived from such digital representations of student responses.

Abstract: A resource allocation can be utilized to control resources to determine trustworthy item scores for a respondent's response to an assessment item. Embodiments may utilize one or more resources to extract the student response to an item, one or more resources to establish an item score for that item based on the extracted response, and one or more resources to evaluate the extracted or score and further utilize such resources until a trustworthy item score is established. Confidence indicators may be used for both digital representations of student responses and the scores derived from such digital representations of student responses.

Abstract: A method, system, and algorithm detects graphite responses in optical mark recognition documents using inexpensive visible-light scanners. The invention is invariant to the numerous background colors and artwork in typical optical mark recognition documents. A superposition of a graphite response image and a background image is modeled. The background image in turn is modeled as a superposition of screening, artwork, lines, and machine text components. A sequence of image processing operations and a pattern recognition algorithm is used to isolate the graphite response image from a test document by systematically removing the components of the background image. The image processing operations consist of grayscale and color segmentation and the application of the Hough transform. Components that are not removed by image processing operations are identified by calculating their texture features, and removed using a multivariate Gaussian classifier.