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Austin Wyman; Zhiyong Zhang – Grantee Submission, 2025
Automated detection of facial emotions has been an interesting topic for multiple decades in social and behavioral research but is only possible very recently. In this tutorial, we review three popular artificial intelligence based emotion detection programs that are accessible to R programmers: Google Cloud Vision, Amazon Rekognition, and…
Descriptors: Artificial Intelligence, Algorithms, Computer Software, Identification
Mathilde Léon; Shoba S. Meera; Anne-Caroline Fiévet; Alejandrina Cristia – Research Ethics, 2024
The last decade has seen a rise in big data approaches, including in the humanities, whereby large quantities of data are collected and analysed. In this paper, we discuss long-form audio recordings that result from individuals wearing a recording device for many hours. Linguists, psychologists and anthropologists can use them, for example, to…
Descriptors: Foreign Countries, Developing Nations, Data Collection, Audio Equipment
Swist, Teresa; Humphry, Justine; Gulson, Kalervo N. – Learning, Media and Technology, 2023
There is a broad impetus across policy and institutional domains to expand public engagement and involvement with emerging technology research and innovation. Yet innovative theory, methods, and practices to critically explore algorithmic system controversies and democratic possibilities are still in nascent form. In this paper, we bring together…
Descriptors: Algorithms, Data Analysis, Democracy, Design
Chenguang Pan; Zhou Zhang – International Educational Data Mining Society, 2024
There is less attention on examining algorithmic fairness in secondary education dropout predictions. Also, the inclusion of protected attributes in machine learning models remains a subject of debate. This study delves into the use of machine learning models for predicting high school dropouts, focusing on the role of protected attributes like…
Descriptors: High School Students, Dropouts, Dropout Characteristics, Artificial Intelligence
Peer reviewedMurtagh, F. – Information Processing and Management, 1984
Using examples of data from the areas of information retrieval and of multivariate data analysis, six hierarchic clustering algorithms (single link, median, centroid, group average, complete link, Wards's) are examined and evaluated by using three proposed coefficients of hierarchic structure. Nine references are cited. (EJS)
Descriptors: Algorithms, Cluster Analysis, Cluster Grouping, Data Analysis
Misanchuk, Earl R. – Journal of Instructional Development, 1985
This personal reaction to Cummings'"Comparison of Three Algorithms for Analyzing Questionnaire-Type Needs Assessment Data to Establish Need Priorities" specifically questions Cummings' use of the Mean Difference Analysis for comparison with Weighted Needs Index, and his focus on characteristics of the statistic that are of secondary…
Descriptors: Algorithms, Communication (Thought Transfer), Comparative Analysis, Data Analysis
Mandeville, Garrett K. – 1988
This paper describes and evaluates a computerized system, MATCH, which is being used in South Carolina to match or link student records from year to year. The functioning of MATCH and its specific features are described, and its use in matching student test scores is detailed. The problem of mismatched records and the use of visual editing to…
Descriptors: Algorithms, Computer Oriented Programs, Computer Software, Data Analysis
Cummings, Oliver W. – Journal of Instructional Development, 1985
This study of training needs utilized a questionnaire to assess participant's opinions of knowledge level that should exist and knowledge level that does exist in 25 content areas and analyzed the resultant data using three different approaches: mean difference analysis, multicomponent data analysis, and weighted need index. (MBR)
Descriptors: Algorithms, Attitude Measures, Comparative Analysis, Data Analysis
Muraki, Eiji – 1984
This study examines the application of the marginal maximum likelihood (MML) EM algorithm to the parameter estimation problem of the three-parameter normal ogive and logistic polychotomous item response models. A three-parameter normal ogive model, the Graded Response model, has been developed on the basis of Samejima's two-parameter graded…
Descriptors: Algorithms, Data Analysis, Estimation (Mathematics), Goodness of Fit

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