Intelligent Tutors as Intelligent Testers
2013
The great promise of criterion-referenced testing for creating an effective new form of individualized instruction that ensures mastery by all students has not materialized. To a large measure, this may be due to limitations in the technology The advent of intelligent learning environments in which students are actively engaged in the process of problem solving presents an opportunity for revolutionary changes in the way in which students&s; competence can be assessed. Within such environments, students interact with a system that simulates real-world problems. Their mode of reasoning is more generative than evaluative. They plan and carry out strategies for solving problems, rather than working backwards from multiple-choice response alternatives. All aspects of their performance are available for measurement purposes, ranging from records of the problems they have solved to inferences about their actual problem-solving processes (based on their solution methods and their past performance). Some developers of intelligent tutoring systems have been so bold as to describe their assessments of the individual as "student models" (Clancey, 1983), or formal representations of the students&s; declarative and procedural knowledge. These new possibilities for assessment in the course of instruction are being developed by individuals whose primary interest is in learning and instruction, rather than by psychometricians. As in criterion-referenced testing, the goal is the development of effective, individualized instructional systems.