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Mike Richards; Kevin Waugh; Mark A Slaymaker; Marian Petre; John Woodthorpe; Daniel Gooch – ACM Transactions on Computing Education, 2024
Cheating has been a long-standing issue in university assessments. However, the release of ChatGPT and other free-to-use generative AI tools has provided a new and distinct method for cheating. Students can run many assessment questions through the tool and generate a superficially compelling answer, which may or may not be accurate. We ran a…
Descriptors: Computer Science Education, Artificial Intelligence, Cheating, Student Evaluation
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Ramineni, Chaitanya; Williamson, David – ETS Research Report Series, 2018
Notable mean score differences for the "e-rater"® automated scoring engine and for humans for essays from certain demographic groups were observed for the "GRE"® General Test in use before the major revision of 2012, called rGRE. The use of e-rater as a check-score model with discrepancy thresholds prevented an adverse impact…
Descriptors: Scores, Computer Assisted Testing, Test Scoring Machines, Automation
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Romero, Jaime; Rozano, Mercedes – World Journal on Educational Technology: Current Issues, 2016
The benefits of solving problems have been widely acknowledged by literature. Its implementation in e-learning platforms can make easier its management and the learning process itself. However, its implementation can also become a very time-consuming task, particularly when the number of problems to generate is high. In this tutorial we describe a…
Descriptors: Automation, Integrated Learning Systems, Problem Solving, Technology Uses in Education
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Zhang, Mo – ETS Research Report Series, 2013
Many testing programs use automated scoring to grade essays. One issue in automated essay scoring that has not been examined adequately is population invariance and its causes. The primary purpose of this study was to investigate the impact of sampling in model calibration on population invariance of automated scores. This study analyzed scores…
Descriptors: Automation, Scoring, Essay Tests, Sampling
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Ramineni, Chaitanya; Trapani, Catherine S.; Williamson, David M.; Davey, Tim; Bridgeman, Brent – ETS Research Report Series, 2012
Automated scoring models for the "e-rater"® scoring engine were built and evaluated for the "GRE"® argument and issue-writing tasks. Prompt-specific, generic, and generic with prompt-specific intercept scoring models were built and evaluation statistics such as weighted kappas, Pearson correlations, standardized difference in…
Descriptors: Scoring, Test Scoring Machines, Automation, Models
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Attali, Yigal; Powers, Don; Freedman, Marshall; Harrison, Marissa; Obetz, Susan – ETS Research Report Series, 2008
This report describes the development, administration, and scoring of open-ended variants of GRE® Subject Test items in biology and psychology. These questions were administered in a Web-based experiment to registered examinees of the respective Subject Tests. The questions required a short answer of 1-3 sentences, and responses were automatically…
Descriptors: College Entrance Examinations, Graduate Study, Scoring, Test Construction
Nunes, Miguel Baptista, Ed.; McPherson, Maggie, Ed. – International Association for Development of the Information Society, 2016
These proceedings contain the papers of the International Conference e-Learning 2016, which was organised by the International Association for Development of the Information Society, 1-3 July, 2016. This conference is part of the Multi Conference on Computer Science and Information Systems 2016, 1-4 July. The e-Learning (EL) 2016 conference aims…
Descriptors: Professional Associations, Conferences (Gatherings), Electronic Learning, Computer Science Education
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Sheehan, Kathleen M.; Kostin, Irene; Futagi, Yoko; Hemat, Ramin; Zuckerman, Daniel – ETS Research Report Series, 2006
This paper describes the development, implementation, and evaluation of an automated system for predicting the acceptability status of candidate reading-comprehension stimuli extracted from a database of journal and magazine articles. The system uses a combination of classification and regression techniques to predict the probability that a given…
Descriptors: Automation, Prediction, Reading Comprehension, Classification
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Rudner, Lawrence M.; Garcia, Veronica; Welch, Catherine – Journal of Technology, Learning, and Assessment, 2006
This report provides a two-part evaluation of the IntelliMetric[SM] automated essay scoring system based on its performance scoring essays from the Analytic Writing Assessment of the Graduate Management Admission Test[TM] (GMAT[TM]). The IntelliMetric system performance is first compared to that of individual human raters, a Bayesian system…
Descriptors: Writing Evaluation, Writing Tests, Scoring, Essays
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Asoodeh, Mike; Bonnette, Roy – AACE Journal, 2006
It has become widely accepted that the computer is an indispensable tool in the study of science and technology. Thus, in recent years curricular programs such as Industrial Technology and associated scientific disciplines have been adopting and adapting the computer as a tool in new and innovative ways to support teaching, learning, and research.…
Descriptors: Program Descriptions, Curriculum Development, Graduate Study, Undergraduate Study