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Geisler, Cheryl – Written Communication, 2018
Coding, the analytic task of assigning codes to nonnumeric data, is foundational to writing research. A rich discussion of methodological pluralism has established the foundational importance of systematicity in the task of coding, but less attention has been paid to the equally important commitment to language complexity. Addressing the interplay…
Descriptors: Coding, Writing Research, Spreadsheets, Computer Software
O'Toole, J. M.; King, R. A. R. – Language Testing, 2011
The "cloze" test is one possible investigative instrument for predicting text comprehensibility. Conceptual coding of student replacement of deleted words has been considered to be more valid than exact coding, partly because conceptual coding seemed fairer to poorer readers. This paper reports a quantitative study of 447 Australian…
Descriptors: Cloze Procedure, Test Results, Language Tests, Reading Comprehension
Cawthon, Stephanie – American Annals of the Deaf, 2011
Linguistic complexity of test items is one test format element that has been studied in the context of struggling readers and their participation in paper-and-pencil tests. The present article presents findings from an exploratory study on the potential relationship between linguistic complexity and test performance for deaf readers. A total of 64…
Descriptors: Language Styles, Test Content, Syntax, Linguistics
Content Characteristics of GRE Analytical Reasoning Items. GRE Board Professional Report No. 84-14P.
Chalifour, Clark; Powers, Donald E. – 1988
In actual test development practice, the number of test items that must be developed and pretested is typically greater, and sometimes much greater, than the number eventually judged suitable for use in operational test forms. This has proven to be especially true for analytical reasoning items, which currently form the bulk of the analytical…
Descriptors: Coding, Difficulty Level, Higher Education, Test Construction

Johnson, G. J. – Psychological Review, 1991
An associative model of serial learning is described based on the assumption that the effective stimulus for a serial-list item is generated by adaptation-level coding of the item's ordinal position. How the model can generate predictions of aspects of serial-learning data is illustrated. (SLD)
Descriptors: Association (Psychology), Associative Learning, Coding, Difficulty Level