Descriptor
Source
Author
| Clancey, William J. | 3 |
| Arsenault, Joseph | 1 |
| Baker, Eva | 1 |
| Bear, George G. | 1 |
| Becker, Lee A. | 1 |
| Cataldo, Donna | 1 |
| Flood, James, Ed. | 1 |
| Gayeski, Diane M. | 1 |
| Glutting, Joseph J. | 1 |
| Goodfriend, Phyllis | 1 |
| Kunen, Seth | 1 |
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Publication Type
Education Level
Audience
| Researchers | 20 |
| Practitioners | 7 |
| Teachers | 1 |
Location
Laws, Policies, & Programs
Assessments and Surveys
| Kaufman Assessment Battery… | 1 |
| Slosson Intelligence Test | 1 |
| Stanford Binet Intelligence… | 1 |
| Wechsler Adult Intelligence… | 1 |
| Wechsler Intelligence Scale… | 1 |
What Works Clearinghouse Rating
IQ Is Irrelevant to the Definition of Learning Disabilities: A Position in Search of Logic and Data.
Peer reviewedLyon, G. Reid – Journal of Learning Disabilities, 1989
This response to a paper by Linda Siegel (EC221505) on the relationship between Intelligence Quotient and learning disabilities addresses the differences between classification and identification, limitations in Siegel's conceptualization of intelligence, and the representation of the language and learning domains subsumed within the learning…
Descriptors: Classification, Educational Diagnosis, Elementary Secondary Education, Handicap Identification
Why We Do Not Need Intelligence Test Scores in the Definition and Analyses of Learning Disabilities.
Peer reviewedSiegel, Linda S. – Journal of Learning Disabilities, 1989
Issues raised in responses to Linda Siegel's paper (EC221505) on the relationship between intelligence test scores and learning disabilities are addressed. Discussed are the nature of intelligence, classification of learning disabilities by discrepancy between intelligence test scores and achievement scores, the existence of learning disabilities,…
Descriptors: Academic Achievement, Classification, Educational Diagnosis, Elementary Secondary Education
Peer reviewedGayeski, Diane M. – Journal of Educational Technology Systems, 1985
Presents a model which integrates design and hardware attributes for both videotape and videodisc technologies and incorporates a wider range of equipment and presentation/testing strategies than taxonomies dealing with hardware only. Model is designed to aid potential designers/users in categorizing and selecting appropriate hardware/software…
Descriptors: Artificial Intelligence, Classification, Instructional Design, Interaction
Peer reviewedSzatmari, Peter – Journal of Autism and Developmental Disorders, 1992
This paper reviews 20 studies that investigated the internal or external validity of various subtypes of autistic spectrum disorders. At least three groups could be distinguished from autism on clinical grounds: an Asperger syndrome subtype, and two atypical subtypes characterized by either low intelligence quotient or high intelligence quotient.…
Descriptors: Classification, Clinical Diagnosis, Handicap Identification, Intelligence Quotient
PDF pending restorationClancey, 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
Peer reviewedRada, Roy – Information Processing and Management, 1987
Reviews aspects of the relationship between machine learning and information retrieval. Highlights include learning programs that extend from knowledge-sparse learning to knowledge-rich learning; the role of the thesaurus; knowledge bases; artificial intelligence; weighting documents; work frequency; and merging classification structures. (78…
Descriptors: Algorithms, Artificial Intelligence, Classification, Documentation
Peer reviewedMinskoff, Esther H.; And Others – Journal of Learning Disabilities, 1989
Learning-disabled adults (N=145) participating in vocational rehabilitation were found to constitute a homogeneous group with severe deficits, exhibiting: low-average general intelligence; lower verbal than performance Intelligence Quotients; attention, reasoning, and auditory memory deficits; academic achievement at the fourth/fifth-grade level;…
Descriptors: Academic Achievement, Adults, Classification, Evaluation
Rumelhart, David E.; Norman, Donald A. – 1983
This paper reviews work on the representation of knowledge from within psychology and artificial intelligence. The work covers the nature of representation, the distinction between the represented world and the representing world, and significant issues concerned with propositional, analogical, and superpositional representations. Specific topics…
Descriptors: Artificial Intelligence, Classification, Generalization, Literature Reviews
Peer reviewedKunen, Seth; And Others – Mental Retardation, 1996
Concurrent validity testing of the Slosson Intelligence Test-Revised with the Stanford-Binet Intelligence Scale (Fourth Edition), involving 191 individuals (ages 5-69 and IQs of 36 to 110), found a high correlation between the two scales. However, the Slosson unsatisfactorily matched the Stanford-Binet's assignment of individuals to IQ categories.…
Descriptors: Adults, Children, Classification, Cognitive Tests
PDF pending restorationThompson, Timothy F.; Clancey, William J. – 1986
This report describes the application of a shell expert system from the medical diagnostic system, Neomycin, to Caster, a diagnostic system for malfunctions in industrial sandcasting. This system was developed to test the hypothesis that starting with a well-developed classification procedure and a relational language for stating the…
Descriptors: Artificial Intelligence, Classification, Clinical Diagnosis, Computer System Design
Becker, Lee A. – Programmed Learning and Educational Technology, 1987
Presents and develops a general model of the nature of a learning system and a classification for learning systems. Highlights include the relationship between artificial intelligence and cognitive psychology; computer-based instructional systems; intelligent instructional systems; and the role of the learner's knowledge base in an intelligent…
Descriptors: Artificial Intelligence, Classification, Cognitive Psychology, Computer Assisted Instruction
Peer reviewedGlutting, Joseph J.; Bear, George G. – Learning Disability Quarterly, 1989
The study evaluated the utility of Kaufman-Assessment Battery for Children (K-ABC) subtests in differentiating learning-disabled children from students with other handicapping conditions, and compared K-ABC subtests with Wechsler Intelligence Scale for Children-Revised subtests. Results showed that subtest scores did not enhance differential…
Descriptors: Classification, Educational Diagnosis, Elementary Education, Evaluation Methods
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
Flood, James, Ed. – 1984
Intended to illuminate current understanding of how the reader's cognition and language and the text's structure affect the processing of prose, this volume contains articles written by educators, linguists, psychologists, and artificial intelligence experts on issues of comprehension research. The first part of the book examines reading…
Descriptors: Artificial Intelligence, Child Language, Classification, Cognitive Processes
Peer reviewedManis, Franklin R.; And Others – Annals of Dyslexia, 1988
Forty normal readers and 50 dyslexic children (age 9-14) were matched on reading level and intelligence quotient and tested. Analysis revealed 3 major subgroups: specific deficit in phonological processing of print (52 percent), deficits in processing both the phonological and orthographic features of printed words (24 percent), and phonological…
Descriptors: Classification, Dyslexia, Handicap Identification, Intelligence Quotient
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