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Sami Baral; Eamon Worden; Wen-Chiang Lim; Zhuang Luo; Christopher Santorelli; Ashish Gurung; Neil Heffernan – Grantee Submission, 2024
The effectiveness of feedback in enhancing learning outcomes is well documented within Educational Data Mining (EDM). Various prior research have explored methodologies to enhance the effectiveness of feedback to students in various ways. Recent developments in Large Language Models (LLMs) have extended their utility in enhancing automated…
Descriptors: Automation, Scoring, Computer Assisted Testing, Natural Language Processing
Botarleanu, Robert-Mihai; Dascalu, Mihai; Allen, Laura K.; Crossley, Scott Andrew; McNamara, Danielle S. – Grantee Submission, 2021
Text summarization is an effective reading comprehension strategy. However, summary evaluation is complex and must account for various factors including the summary and the reference text. This study examines a corpus of approximately 3,000 summaries based on 87 reference texts, with each summary being manually scored on a 4-point Likert scale.…
Descriptors: Computer Assisted Testing, Scoring, Natural Language Processing, Computer Software
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Jamshidian, Mortaza; Bentler, Peter M. – Journal of Educational and Behavioral Statistics, 1999
Describes the maximum likelihood (ML) estimation of mean and covariance structure models when data are missing. Describes expectation maximization (EM), generalized expectation maximization, Fletcher-Powell, and Fisher-scoring algorithms for parameter estimation and shows how software can be used to implement each algorithm. (Author/SLD)
Descriptors: Algorithms, Estimation (Mathematics), Maximum Likelihood Statistics, Scoring
Kurz, Terri Barber – 1999
Multiple-choice tests are generally scored using a conventional number right scoring method. While this method is easy to use, it has several weaknesses. These weaknesses include decreased validity due to guessing and failure to credit partial knowledge. In an attempt to address these weaknesses, psychometricians have developed various scoring…
Descriptors: Algorithms, Guessing (Tests), Item Response Theory, Multiple Choice Tests
Chevalier, Shirley A. – 1998
In conventional practice, most educators and educational researchers score cognitive tests using a dichotomous right-wrong scoring system. Although simple and straightforward, this method does not take into consideration other factors, such as partial knowledge or guessing tendencies and abilities. This paper discusses alternative scoring models:…
Descriptors: Ability, Algorithms, Aptitude Tests, Cognitive Tests
Schnipke, Deborah L.; Reese, Lynda M. – 1997
Two-stage and multistage test designs provide a way of roughly adapting item difficulty to test-taker ability. All test takers take a parallel stage-one test, and, based on their scores, they are routed to tests of different difficulty levels in subsequent stages. These designs provide some of the benefits of standard computerized adaptive testing…
Descriptors: Ability, Adaptive Testing, Algorithms, Comparative Analysis
Baker, Sheldon R.; And Others – 1995
A paradigm for the recalibration of teacher-made assessment that assesses and evaluates in one operation is formulated. The effort to make the classroom the primary source of educational research activity is contingent on redefining educational research as empirical and not experimental. This emphasizes that the empirical analysis of instructional…
Descriptors: Algorithms, Educational Assessment, Educational Research, Elementary Secondary Education
Raymond, Mark R.; Houston, Walter M. – 1990
Performance rating systems frequently use multiple raters in order to improve the reliability of ratings. However, unless all candidates are rated by the same raters, some candidates will be at an unfair advantage or disadvantage solely because they were rated by more stringent or lenient raters. To obtain fair and accurate evaluations of…
Descriptors: Algorithms, Computer Simulation, Educational Assessment, Evaluation Methods