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McConnell-Nzunga, J.; Naylor, P. J.; Macdonald, H.; Rhodes, R. E.; Hofer, S. M.; McKay, H. – Measurement in Physical Education and Exercise Science, 2018
Body mass index is a common proxy for proportion of body fat. However, body mass index may not classify youth similarly across ages and ethnicities. We used sex- and ethnic-specific receiver operating characteristic curves to determine how obesity classifications compared between body mass index and dual energy x-ray absorptiometry-based body fat…
Descriptors: Classification, Obesity, Ethnicity, Body Composition
Ballance, Oliver James – Computer Assisted Language Learning, 2017
One of the most promising avenues of research in computer-assisted language learning is the potential for language learners to make use of language corpora. However, using a corpus requires use of a corpus tool as an interface, typically a concordancer. How such a tool can be made most accessible to learners is an important issue. Specifically,…
Descriptors: Teaching Methods, Indexes, Multivariate Analysis, Classification
Fried, J.B.; And Others – 1968
The objectives of this research were to investigage (1) the feasibility of an index simulator, and (2) the use of a sequential analysis model for the automatic classification of documents. Index simulation was studied in general for various types of indexes, and in depth for the simulation of an inverted coordinate index to a document collection…
Descriptors: Automation, Classification, Computer Programs, Computers
Wolfe, Edward W.; Myford, Carol M.; Engelhard, George, Jr.; Manalo, Jonathan R. – College Board, 2007
In this study, we investigated a variety of Reader effects that may influence the validity of ratings assigned to AP® English Literature and Composition essays. Specifically, we investigated whether Readers exhibit changes in their levels of severity and accuracy, and their use of individual scale categories over time. We refer to changes in these…
Descriptors: Advanced Placement Programs, Essays, English Literature, Writing (Composition)
United Nations Educational, Scientific, and Cultural Organization, Paris (France). Div. of Statistics on Education. – 1976
An international numerical coding structure is presented for classification of data on education according to level category, educational field, and program type. Explanation of the overall system and a guide for its use is followed by a listing of levels, fields, and programs of education in coded order. The various educational program…
Descriptors: Classification, Codification, Comparative Analysis, Data