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Chelsea M. Parlett-Pelleriti; Elizabeth Stevens; Dennis Dixon; Erik J. Linstead – Review Journal of Autism and Developmental Disorders, 2023
Large amounts of autism spectrum disorder (ASD) data is created through hospitals, therapy centers, and mobile applications; however, much of this rich data does not have pre-existing classes or labels. Large amounts of data--both genetic and behavioral--that are collected as part of scientific studies or a part of treatment can provide a deeper,…
Descriptors: Artificial Intelligence, Autism Spectrum Disorders, Classification, Supervision
Aydogdu, Seyhmus – Turkish Online Journal of Distance Education, 2020
The purpose of this research is a comprehensive review of studies towards educational data mining (EDM) in Turkey. For the purpose of this study, graduate theses and articles conducted in Turkey were examined in detail. As a result of the literature review, 48 studies were analyzed in the context of the data mining purpose, the technique used in…
Descriptors: Foreign Countries, Information Retrieval, Data Analysis, Academic Achievement
Cascallar, Eduardo; Musso, Mariel; Kyndt, Eva; Dochy, Filip – Frontline Learning Research, 2014
Two articles, Edelsbrunner and, Schneider (2013), and Nokelainen and Silander (2014) comment on Musso, Kyndt, Cascallar, and Dochy (2013). Several relevant issues are raised and some important clarifications are made in response to both commentaries. Predictive systems based on artificial neural networks continue to be the focus of current…
Descriptors: Artificial Intelligence, Research Methodology, Prediction, Classification
Nokelainen, Petri; Silander, Tomi – Frontline Learning Research, 2014
This commentary to the recent article by Musso et al. (2013) discusses issues related to model fitting, comparison of classification accuracy of generative and discriminative models, and two (or more) cultures of data modeling. We start by questioning the extremely high classification accuracy with an empirical data from a complex domain. There is…
Descriptors: Models, Classification, Accuracy, Regression (Statistics)
Strobl, Carolin; Malley, James; Tutz, Gerhard – Psychological Methods, 2009
Recursive partitioning methods have become popular and widely used tools for nonparametric regression and classification in many scientific fields. Especially random forests, which can deal with large numbers of predictor variables even in the presence of complex interactions, have been applied successfully in genetics, clinical medicine, and…
Descriptors: Artificial Intelligence, Decision Making, Psychological Studies, Research Methodology

Clancey, William J. – 1986
This paper reviews the research leading from the GUIDON rule-based tutoring system, including the reconfiguration of MYCIN into NEOMYCIN and NEOMYCIN's generalization into the heuristic classification shell, HERACLES. The presentation is organized chronologically around pictures and dialogues that represent turning points and crystallize the basic…
Descriptors: Artificial Intelligence, Classification, Computer System Design, Expert Systems
Baker, Eva; And Others – 1990
This sourcebook is intended to provide researchers and users of natural language computer systems with a classification scheme to describe language-related problems associated with such systems. Methods from the disciplines of artificial intelligence (AI), education, linguistics, psychology, anthropology, and psychometrics were applied in an…
Descriptors: Artificial Intelligence, Classification, Cognitive Psychology, Computer Oriented Programs
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers