FULL-SCALE TRAINING MODEL EDITOR FOR COMPUTER TRAINING COMPLEXES

The article is devoted to questions of synthesis of full-scale - model realizations of data series on the basis of natural data for modeling of controllable and uncontrollable influences at research of operating and projected control systems, and also in training systems of computer training. The possibility of formation of model effects on the basis of joint use of multivariate dynamic databases and natural data simulator is shown. Dynamic databases store information that characterizes the typical representative situations of systems in the form of special functions - generating functions. Multiple variability of dynamic databases is determined by the type of the selected generating function, the methods of obtaining parameters (coefficients) of this function, as well as the selected accuracy of approximation. The situation models recovered by generating functions are used as basic components (trends) in the formation of the resulting full-scale - model implementations and are input into the natural data simulator. The data simulator allows for each variant of initial natural data to form an implementation of the perturbation signal with given statistical properties on a given simulation interval limited by the initial natural implementation. This is achieved with the help of a two-circuit structure, where the first circuit is responsible for evaluation and cor-rection of initial properties of the natural signal, and the second - for iterative correction of deviations of properties of the final implementation from the specified ones. The resulting realizations reflect the properties of their full-scale components, which are difficult to describe by analytical models, and are supplemented by model values, allowing in increments to correct the properties to the specified ones. The given approach allows to form set of variants of course of processes on the basis of one situation with different set degree of uncertainty and conditions of functioning.

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A Systematic Approach to Improving In-House Computer Literacy

Journal of Educational Technology Systems ◽

10.2190/9n9k-4tw8-9tu9-70tc ◽

1992 ◽

Vol 21 (1) ◽

pp. 51-70 ◽

Cited By ~ 2

Author(s):

John S. Craig

Keyword(s):

Computer Literacy ◽

Technical Communication ◽

Systematic Approach ◽

Computer Systems ◽

Computer Training ◽

Training Model ◽

Writing Strategies ◽

Computer User ◽

Technical Writers ◽

Technical Communicators

Computer trainers and technical writers responsible for instructing end users on the proper use of in-house computer systems are challenged with a task that is becoming increasingly complex and vital to an organization's efficiency. Since in-house computer systems are custom-designed for use within organizations, classroom trainers, writers, and other technical communicators must provide comprehensive classroom instruction and documentation for users. This article cites recent research on computer training and writing strategies in the technical communication and instructional technology fields, and how these strategies can be used by technical communicators to instruct users of in-house computer systems. An in-house computer training model is presented to help technical communicators design in-house computer training sessions, improve existing sessions, and create and revise in-house, instructional computer user documentation.

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V1394: Laped® Ureteroscopy Training Model

The Journal of Urology ◽

10.1016/s0022-5347(18)32192-x ◽

2007 ◽

Vol 177 (4S) ◽

pp. 459-459

Author(s):

Hak J. Lee ◽

Corollos S. Abdelshehid ◽

Geoffrey N. Box ◽

Jose B.A. Abraham ◽

Elspeth M. McDougall ◽

...

Keyword(s):

Training Model

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Relation of Statistically Significant, Abnormal, and Typical WAIS-R VIQ-PIQ Discrepancies to Full Scale IQs

European Journal of Psychological Assessment ◽

10.1027//1015-5759.16.2.107 ◽

2000 ◽

Vol 16 (2) ◽

pp. 107-114 ◽

Cited By ~ 3

Author(s):

Louis M. Hsu ◽

Judy Hayman ◽

Judith Koch ◽

Debbie Mandell

Keyword(s):

Graphical Method ◽

The United States ◽

Full Scale ◽

True Score ◽

Absolute Value ◽

Normative Population ◽

The Us ◽

The Mean ◽

And Performance ◽

Quadratic Models

Summary: In the United States' normative population for the WAIS-R, differences (Ds) between persons' verbal and performance IQs (VIQs and PIQs) tend to increase with an increase in full scale IQs (FSIQs). This suggests that norm-referenced interpretations of Ds should take FSIQs into account. Two new graphs are presented to facilitate this type of interpretation. One of these graphs estimates the mean of absolute values of D (called typical D) at each FSIQ level of the US normative population. The other graph estimates the absolute value of D that is exceeded only 5% of the time (called abnormal D) at each FSIQ level of this population. A graph for the identification of conventional “statistically significant Ds” (also called “reliable Ds”) is also presented. A reliable D is defined in the context of classical true score theory as an absolute D that is unlikely (p < .05) to be exceeded by a person whose true VIQ and PIQ are equal. As conventionally defined reliable Ds do not depend on the FSIQ. The graphs of typical and abnormal Ds are based on quadratic models of the relation of sizes of Ds to FSIQs. These models are generalizations of models described in Hsu (1996) . The new graphical method of identifying Abnormal Ds is compared to the conventional Payne-Jones method of identifying these Ds. Implications of the three juxtaposed graphs for the interpretation of VIQ-PIQ differences are discussed.

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A Modification of the Payne-Jones Method of Identifying Abnormal Differences in WISC-R Performance and Verbal IQ's

European Journal of Psychological Assessment ◽

10.1027/1015-5759.12.1.27 ◽

1996 ◽

Vol 12 (1) ◽

pp. 27-32 ◽

Cited By ~ 1

Author(s):

Louis M. Hsu

Keyword(s):

Full Scale ◽

True Score ◽

Verbal Iq ◽

Score Difference ◽

The Difference ◽

And Performance

The difference (D) between a person's Verbal IQ (VIQ) and Performance IQ (PIQ) has for some time been considered clinically meaningful ( Kaufman, 1976 , 1979 ; Matarazzo, 1990 , 1991 ; Matarazzo & Herman, 1985 ; Sattler, 1982 ; Wechsler, 1984 ). Particularly useful is information about the degree to which a difference (D) between scores is “abnormal” (i.e., deviant in a standardization group) as opposed to simply “reliable” (i.e., indicative of a true score difference) ( Mittenberg, Thompson, & Schwartz, 1991 ; Silverstein, 1981 ; Payne & Jones, 1957 ). Payne and Jones (1957) proposed a formula to identify “abnormal” differences, which has been used extensively in the literature, and which has generally yielded good approximations to empirically determined “abnormal” differences ( Silverstein, 1985 ; Matarazzo & Herman, 1985 ). However applications of this formula have not taken into account the dependence (demonstrated by Kaufman, 1976 , 1979 , and Matarazzo & Herman, 1985 ) of Ds on Full Scale IQs (FSIQs). This has led to overestimation of “abnormality” of Ds of high FSIQ children, and underestimation of “abnormality” of Ds of low FSIQ children. This article presents a formula for identification of abnormal WISC-R Ds, which overcomes these problems, by explicitly taking into account the dependence of Ds on FSIQs.

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