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Empirical testing of a human perform...

Kang, In Gu.

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Empirical testing of a human performance model: Understanding success in federal agencies using second-order structural equation modeling.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Empirical testing of a human performance model: Understanding success in federal agencies using second-order structural equation modeling./
Author:	Kang, In Gu.
Description:	149 p.
Notes:	Source: Dissertation Abstracts International, Volume: 76-11(E), Section: A.
Contained By:	Dissertation Abstracts International76-11A(E).
Subject:	Educational technology. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3715873
ISBN:	9781321941920

Empirical testing of a human performance model: Understanding success in federal agencies using second-order structural equation modeling.
Kang, In Gu.

Empirical testing of a human performance model: Understanding success in federal agencies using second-order structural equation modeling. - 149 p.

Source: Dissertation Abstracts International, Volume: 76-11(E), Section: A.

Thesis (Ph.D.)--Indiana University, 2015.

Even though various models have been developed in the field of human performance technology (HPT), little research has been done to empirically test these models of human performance (HP) with large amounts of data. This insufficient evidence on whether or not HP models work in practice discourages HPT professionals and workers from applying HP models into their own contexts. This study aims to examine structural relationships among performance support systems (PSS), human behaviors (HB), and performance (PER) in order to test the proposed performance model. Using national government-wide representative data from the 2012 Federal Employee Viewpoint Survey (FEVS, N=687,687, 82 federal agencies), this study has the opportunity to empirically test a comprehensive performance model (Bichelmeyer & Horvitz, 2006) using structural equation modeling (SEM).

ISBN: 9781321941920Subjects--Topical Terms:

517670
Educational technology.

Empirical testing of a human performance model: Understanding success in federal agencies using second-order structural equation modeling.
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100 1 $a Kang, In Gu. $3 3189016
245 1 0 $a Empirical testing of a human performance model: Understanding success in federal agencies using second-order structural equation modeling.
300 $a 149 p.
500 $a Source: Dissertation Abstracts International, Volume: 76-11(E), Section: A.
500 $a Adviser: Barbara A. Bichelmeyer.
502 $a Thesis (Ph.D.)--Indiana University, 2015.
520 $a Even though various models have been developed in the field of human performance technology (HPT), little research has been done to empirically test these models of human performance (HP) with large amounts of data. This insufficient evidence on whether or not HP models work in practice discourages HPT professionals and workers from applying HP models into their own contexts. This study aims to examine structural relationships among performance support systems (PSS), human behaviors (HB), and performance (PER) in order to test the proposed performance model. Using national government-wide representative data from the 2012 Federal Employee Viewpoint Survey (FEVS, N=687,687, 82 federal agencies), this study has the opportunity to empirically test a comprehensive performance model (Bichelmeyer & Horvitz, 2006) using structural equation modeling (SEM).
520 $a In measurement model I, a 1st order confirmatory factor analysis (CFA), all model fit indices were found to be adequate (chi2(93) = 90800.207; CFI = .949; TLI = .926; RMSEA = .038; SRMR = .030). All factor loadings of the observed variables were significant (p < .001), indicating that all first-order factors were well measured by the indicators. In measurement model II, a 2nd order CFA, all model fit indices were also found to be in adequate range (chi2(111) = 120515.246; CFI = .933; TLI = .918; RMSEA = .040; SRMR = .036). All factor loadings of the first-order factors used to measure the second-order factors were statistically significant (p < .001), indicating that all the second-order factors were well measured by the first-order factors. In structural model, a 2nd order SEM, all model fit indices demonstrated the proposed model is entirely adequate (chi2(111) = 120515.381; CFI = .933; TLI = .918; RMSEA = .040; SRMR = .036). In terms of structural relationships, results supported the hypothesized direct associations among PSS, HB, and PER. Four steps outlined by Baron and Kenny (1986) and Judd and Kenny (1981) were taken for mediation analysis. In addition, bootstrapping (1,000) with confidence intervals was used for a robust examination of the mediating effect of HB. The results indicated that HB partially mediated the relationship between PSS and PER (gamma11* beta21 = .35, p < .001, 95% CI [0.34 to 0.37]).
520 $a Finally, implications are discussed based on the results and findings of this study. At the first-order factor level, various sets of practices for Human Performance Technology (HPT), Human Resource Management (HRM), and Human Resource Development (HRD) are presented.
590 $a School code: 0093.
650 4 $a Educational technology. $3 517670
650 4 $a Occupational psychology. $3 2122852
650 4 $a Organization theory. $3 2122787
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710 2 $a Indiana University. $b School of Education. $3 1020202
773 0 $t Dissertation Abstracts International $g 76-11A(E).
790 $a 0093
791 $a Ph.D.
792 $a 2015
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3715873