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Showing 1 to 15 of 16 results Save | Export
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Fitzgerald, Colleen E. – Perspectives of the ASHA Special Interest Groups, 2020
Purpose: A variety of pediatric clinical populations have difficulty with the correct use of pronouns. The available clinical literature labels these errors in inconsistent terms leading to great variation in how treatment objectives are worded. The purpose of this tutorial is to encourage a shift in pronoun assessment and treatment planning…
Descriptors: Classification, Form Classes (Languages), Error Patterns, Error Correction
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Gerbing, David W. – Journal of Statistics and Data Science Education, 2021
R and Python are commonly used software languages for data analytics. Using these languages as the course software for the introductory course gives students practical skills for applying statistical concepts to data analysis. However, the reliance upon the command line is perceived by the typical nontechnical introductory student as sufficiently…
Descriptors: Statistics Education, Teaching Methods, Introductory Courses, Programming Languages
Cai, Zhiqiang; Siebert-Evenstone, Amanda; Eagan, Brendan; Shaffer, David Williamson; Hu, Xiangen; Graesser, Arthur C. – Grantee Submission, 2019
Coding is a process of assigning meaning to a given piece of evidence. Evidence may be found in a variety of data types, including documents, research interviews, posts from social media, conversations from learning platforms, or any source of data that may provide insights for the questions under qualitative study. In this study, we focus on text…
Descriptors: Semantics, Computational Linguistics, Evidence, Coding
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Strickland, S.; Rand, B. – PRIMUS, 2016
This paper describes a framework for identifying, classifying, and coding student proofs, modified from existing proof-grading rubrics. The framework includes 20 common errors, as well as categories for interpreting the severity of the error. The coding scheme is intended for use in a classroom context, for providing effective student feedback. In…
Descriptors: Guidelines, Undergraduate Students, Classification, Mathematics Instruction
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Pelánek, Radek; Rihák, Ji?rí – International Educational Data Mining Society, 2016
In online educational systems we can easily collect and analyze extensive data about student learning. Current practice, however, focuses only on some aspects of these data, particularly on correctness of students answers. When a student answers incorrectly, the submitted wrong answer can give us valuable information. We provide an overview of…
Descriptors: Foreign Countries, Online Systems, Geography, Anatomy
Gropper, George L. – Educational Technology, 2015
Instructional design can be more effective if it is as fixedly dedicated to the accommodation of individual differences as it currently is to the accommodation of subject matters. That is the hypothesis. A menu of accommodation options is provided that is applicable at each of three stages of instructional development or administration: before,…
Descriptors: Instructional Design, Individual Differences, Student Needs, Remedial Instruction
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Schwarzmueller, April – Teaching of Psychology, 2011
This article details a multi-modal active learning experience to help students understand elements of social categorization. Each student in a group dynamics course observed two groups in conflict and identified examples of in-group bias, double-standard thinking, out-group homogeneity bias, law of small numbers, group attribution error, ultimate…
Descriptors: Childhood Attitudes, Active Learning, Group Dynamics, Classification
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Soto, Fabian A.; Wasserman, Edward A. – Psychological Review, 2010
A wealth of empirical evidence has now accumulated concerning animals' categorizing photographs of real-world objects. Although these complex stimuli have the advantage of fostering rapid category learning, they are difficult to manipulate experimentally and to represent in formal models of behavior. We present a solution to the representation…
Descriptors: Animals, Classification, Photography, Visual Stimuli
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Priem, Jason – Journal of Educational Computing Research, 2010
The study of student error, important across many fields of educational research, has begun to attract interest in the field of e-learning, particularly in relation to usability. However, it remains unclear when errors should be avoided (as usability failures) or embraced (as learning opportunities). Many domains have benefited from taxonomies of…
Descriptors: Electronic Learning, Educational Research, Distance Education, Classification
Daniel, Larry G.; Onwuegbuzie, Anthony J. – 2000
This paper proposes a new typology for understanding common research errors that expands on the four types of error commonly discussed in the research literature. Examples are presented to illustrate Type I and Type II errors, errors related to the interpretation of statistically significant and nonsignificant results respectively, with attention…
Descriptors: Classification, Error Patterns, Research Methodology, Research Problems
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Kohli, Rajeev; Jedidi, Kamel – Psychometrika, 2005
The authors introduce subset conjunction as a classification rule by which an acceptable alternative must satisfy some minimum number of criteria. The rule subsumes conjunctive and disjunctive decision strategies as special cases. Subset conjunction can be represented in a binary-response model, for example, in a logistic regression, using only…
Descriptors: Psychometrics, Probability, Models, Classification
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Livingston, Kenneth R.; Andrews, Janet K. – Developmental Science, 2005
After learning to categorize a set of alien-like stimuli in the context of a story, a group of 5-year-old children and adults judged pairs of stimuli from different categories to be less similar than did groups not learning the category distinction. In a same-different task, the learning group made more errors on pairs of non-identical stimuli…
Descriptors: Stimuli, Young Children, Adults, Concept Formation
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Lott, David – ELT Journal, 1983
Areas of contradiction and controversy over error analysis are discussed, and an interference error analysis project is described, giving a detailed definition of interference error. Several practical approaches to teaching out interference errors are outlined. (MSE)
Descriptors: Classification, English (Second Language), Error Analysis (Language), Error Patterns
Selden, Annie; Selden, John – Online Submission, 2003
In this paper we describe a number of types of errors and underlying misconceptions that arise in mathematical reasoning. Other types of mathematical reasoning errors, not associated with specific misconceptions, are also discussed. We hope the characterization and cataloging of common reasoning errors will be useful in studying the teaching of…
Descriptors: Educational Strategies, Research Methodology, Misconceptions, Error Patterns
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Shriberg, Lawrence D.; Lewis, Barbara A.; Tomblin, J. Bruce; McSweeny, Jane L.; Karlsson, Heather B.; Scheer, Alison R. – Journal of Speech, Language, and Hearing Research, 2005
Converging evidence supports the hypothesis that the most common subtype of childhood speech sound disorder (SSD) of currently unknown origin is genetically transmitted. We report the first findings toward a set of diagnostic markers to differentiate this proposed etiological subtype (provisionally termed "speech delay-genetic") from other…
Descriptors: Delayed Speech, Speech Language Pathology, Diagnostic Tests, Language Impairments
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