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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
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
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
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
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
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

Bennett, Randy Elliot; Steffen, Manfred; Singley, Mark Kevin; Morley, Mary; Jacquemin, Daniel – Journal of Educational Measurement, 1997
Scoring accuracy and item functioning were studied for an open-ended response type test in which correct answers can take many different surface forms. Results with 1,864 graduate school applicants showed automated scoring to approximate the accuracy of multiple-choice scoring. Items functioned similarly to other item types being considered. (SLD)
Descriptors: Adaptive Testing, Automation, College Applicants, Computer Assisted Testing
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
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
Helfer, Doris Small – Searcher, 1998
Argues that librarians should actively accept their responsibility to ensure and provide useful content to the general Internet public. Discusses change brought on by electric commerce and the need for librarians to fill traditional roles, as well as new roles in providing and encouraging Web usage by the public. (AEF)
Descriptors: Graduate Students, Graduate Study, Information Retrieval, Information Services

Deshpande, Pradeep B. – Chemical Engineering Education, 1988
Describes an engineering course for graduate study in process control. Lists four major topics: interaction analysis, multiloop controller design, decoupling, and multivariable control strategies. Suggests a course outline and gives information about each topic. (MVL)
Descriptors: Automation, College Science, Course Content, Course Descriptions

Alnaes, T. – Education for Information, 1988
Describes library and information science education in Norway with emphasis on a postgraduate program in information science and data processing, and a research and development group integrated into that program. The discussion covers the importance of data processing training in preparing students for information handling in libraries and other…
Descriptors: Curriculum Design, Data Processing, Developed Nations, Distance Education

Sharp, Robert L.; And Others – Analytical Chemistry, 1988
Discusses the use of robotics in the analytical chemistry laboratory. Suggests using a modular setup to best use robots and laboratory space. Proposes a sample preparation system which can perform aliquot measurement, dilution, mixing, separation, and sample transfer. Recognizes attributes and shortcomings. (ML)
Descriptors: Automation, Biochemistry, Chemistry, College Science
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
Attali, Yigal; Burstein, Jill – ETS Research Report Series, 2005
The e-rater® system has been used by ETS for automated essay scoring since 1999. This paper describes a new version of e-rater (v.2.0) that differs from the previous one (v.1.3) with regard to the feature set and model building approach. The paper describes the new version, compares the new and previous versions in terms of performance, and…
Descriptors: Essay Tests, Automation, Scoring, Comparative Analysis