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Gardner, John; O'Leary, Michael; Yuan, Li – Journal of Computer Assisted Learning, 2021
Artificial Intelligence is at the heart of modern society with computers now capable of making process decisions in many spheres of human activity. In education, there has been intensive growth in systems that make formal and informal learning an anytime, anywhere activity for billions of people through online open educational resources and…
Descriptors: Artificial Intelligence, Educational Assessment, Formative Evaluation, Summative Evaluation
LaFlair, Geoffrey T.; Langenfeld, Thomas; Baig, Basim; Horie, André Kenji; Attali, Yigal; von Davier, Alina A. – Journal of Computer Assisted Learning, 2022
Background: Digital-first assessments leverage the affordances of technology in all elements of the assessment process--from design and development to score reporting and evaluation to create test taker-centric assessments. Objectives: The goal of this paper is to describe the engineering, machine learning, and psychometric processes and…
Descriptors: Computer Assisted Testing, Affordances, Scoring, Engineering

Harper, R. – Journal of Computer Assisted Learning, 2003
Discusses multiple choice questions and presents a statistical approach to post-test correction for guessing that can be used in spreadsheets to automate the correction and generate a grade. Topics include the relationship between the learning objectives and multiple-choice assessments; and guessing correction by negative marking. (LRW)
Descriptors: Behavioral Objectives, Computer Assisted Testing, Grades (Scholastic), Guessing (Tests)