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Jean-Paul Fox – Journal of Educational and Behavioral Statistics, 2025
Popular item response theory (IRT) models are considered complex, mainly due to the inclusion of a random factor variable (latent variable). The random factor variable represents the incidental parameter problem since the number of parameters increases when including data of new persons. Therefore, IRT models require a specific estimation method…
Descriptors: Sample Size, Item Response Theory, Accuracy, Bayesian Statistics
Kylie L. Anglin – Annenberg Institute for School Reform at Brown University, 2025
Since 2018, institutions of higher education have been aware of the "enrollment cliff" which refers to expected declines in future enrollment. This paper attempts to describe how prepared institutions in Ohio are for this future by looking at trends leading up to the anticipated decline. Using IPEDS data from 2012-2022, we analyze trends…
Descriptors: Validity, Artificial Intelligence, Models, Best Practices
Edgar C. Merkle; Oludare Ariyo; Sonja D. Winter; Mauricio Garnier-Villarreal – Grantee Submission, 2023
We review common situations in Bayesian latent variable models where the prior distribution that a researcher specifies differs from the prior distribution used during estimation. These situations can arise from the positive definite requirement on correlation matrices, from sign indeterminacy of factor loadings, and from order constraints on…
Descriptors: Models, Bayesian Statistics, Correlation, Evaluation Methods
Mark Johnson; Rafiq Saleh – Interactive Learning Environments, 2024
Educational assessment is inherently uncertain, where physiological, psychological and social factors play an important role in establishing judgements which are assumed to be "absolute". AI and other algorithmic approaches to grading of student work strip-out uncertainty, leading to a lack of inspectability in machine judgement and…
Descriptors: Artificial Intelligence, Evaluation Methods, Technology Uses in Education, Man Machine Systems

Koyama, Masafumi; Morita, Kazuhiro; Fuketa, Masao; Aoe, Jun-Ichi – Information Processing & Management, 1998
Presents a faster method for determining hierarchical relationships in information retrieval by using trie structures instead of a linear storage of a concept code. Highlights include case structures, a knowledge representation for natural-language understanding with semantic constraints; a compression algorithm of tries; and evaluation.…
Descriptors: Algorithms, Evaluation Methods, Information Retrieval, Knowledge Representation

Mostafa, J.; Lam, W. – Information Processing & Management, 2000
Presents a multilevel model of the information filtering process that permits document classification. Evaluates a document classification approach based on a supervised learning algorithm, measures the accuracy of the algorithm in a neural network that was trained to classify medical documents on cell biology, and discusses filtering…
Descriptors: Algorithms, Classification, Cytology, Evaluation Methods

Stejic, Zoran; Takama, Yasufumi; Hirota, Kaoru – Information Processing & Management, 2003
Proposes local similarity pattern (LSP) as a new method for computing digital image similarity. Topics include optimizing similarity computation based on genetic algorithm; relevance feedback; and an evaluation of LSP on five databases that showed an increase in retrieval precision over other methods for computing image similarity. (Author/LRW)
Descriptors: Algorithms, Databases, Evaluation Methods, Genetics

Rasmussen, Edie M. – Annual Review of Information Science and Technology (ARIST), 1992
Examines parallel computer architecture and the use of parallel processors for text. Topics discussed include parallel algorithms; performance evaluation; parallel information processing; parallel access methods for text; parallel and distributed information retrieval systems; parallel hardware for text; and network models for information…
Descriptors: Algorithms, Computer Networks, Evaluation Methods, Information Processing

O'Neill, Edward T.; Chan, Lois Mai; Childress, Eric; Dean, Rebecca; El-Hoshy, Lynn M.; Vizine-Goetz, Diane – Library Resources & Technical Services, 2001
Discusses form subdivisions as part of Library of Congress Subject Headings (LCSH) and the MARC format, which did not have a separate subfield code to identify form subdivisions. Describes the development of an algorithm to identify form subdivisions and reports results of an evaluation of the algorithm. (LRW)
Descriptors: Algorithms, Authority Control (Information), Cataloging, Evaluation Methods

Montesi, Danilo; Trombetta, Alberto; Dearnley, Peter A. – Information Processing & Management, 2003
Discusses imprecision in multimedia data on the Web and proposes a formal framework in which to formulate powerful queries and presentations of the answers. Introduces a fuzzy-based algebra which allows user preferences, in the form of weights, to alter query expression, and presents algorithms for the evaluation of similarity-based queries.…
Descriptors: Algebra, Algorithms, Evaluation Methods, Multimedia Materials

Reinke, William A. – Canadian Journal of Program Evaluation/La Revue canadienne d'evaluation de programme, 1999
Presents an algorithm for integrating evaluative concerns of cost effectiveness, equity, quality, and sustainability in program evaluation and offers suggestions for refining the system of measurement and analysis. (SLD)
Descriptors: Algorithms, Cost Effectiveness, Evaluation Methods, Measurement Techniques
Structure and Process in Pupils' Essays: A Graphical Analysis of the Organisation of Extended Prose.

Costa Pereira, D.J.V.; Maskill, R. – British Journal of Educational Psychology, 1983
Suggests a method for analyzing structure and process in prose using algorithms based on graph theory and rules based in syntax. Describes application of the method to essays written by 52 fourteen year old pupils on a newly learned topic in chemistry. (Author/GC)
Descriptors: Algorithms, Behavior, Evaluation Methods, Graphs
Juola, Patrick – 1995
This paper describes an attempt to combine the advantages of both example-based translation and stochastic translation methods in an attempt to develop a method for inferring symbolic transfer functions from a bilingual corpus. By formalizing the translation process and applying standard optimization techniques, a system can be developed that will…
Descriptors: Algorithms, Computational Linguistics, English, Evaluation Methods

Lopez-Pujalte, Cristina; Guerrero Bote, Vicente P.; Moya Anegon, Felix de – Information Processing & Management, 2002
Discussion of information retrieval, query optimization techniques, and relevance feedback focuses on genetic algorithms, which are derived from artificial intelligence techniques. Describes an evaluation of different genetic algorithms using a residual collection method and compares results with the Ide dec-hi method (Salton and Buckley, 1990…
Descriptors: Algorithms, Artificial Intelligence, Comparative Analysis, Evaluation Methods

Walster, Dian – Emergency Librarian, 1997
Discusses search engines and provides methods for determining what resources are searched, the quality of the information, and the algorithms used that will improve the use of search engines on the World Wide Web, online public access catalogs, and electronic encyclopedias. Lists strategies for conducting searches and for learning about the latest…
Descriptors: Algorithms, Encyclopedias, Evaluation Methods, Information Seeking
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