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Assessment of learning in higher education is a critical concern to policymakers, educators, parents, and students. And, doing so appropriately is likelyto require including constructed response tests in the assessment system. Weexamined whether scoring costs and other concerns with using open-end measureson a large scale (e.g., turnaround time and inter-reader consistency) could beaddressed by machine grading the answers. Analyses with 1359 students from 14colleges found that two human readers agreed highly with each other in thescores they assigned to the answers to three types of open-ended questions.These reader assigned scores also agreed highly with those assigned by acomputer. The correlations of the machine-assigned scores with SAT scores,college grades, and other measures were comparable to the correlations of thesevariables with the hand-assigned scores. Machine scoring did not widendifferences in mean scores between racial/ethnic or gender groups. Our findingsdemonstrated that machine scoring can facilitate the use of open-endedquestions in large-scale testing programs by providing a fast, accurate, andeconomical way to grade responses.

Characteristics of hand and machine-assigned scores to college students' answers to open-ended tasks