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Incorporating a training construct i...

Harris, Matthew E.

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Incorporating a training construct into the Unified Theory of Technology Acceptance and Use of Technology.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Incorporating a training construct into the Unified Theory of Technology Acceptance and Use of Technology./
作者:	Harris, Matthew E.
面頁冊數:	176 p.
附註:	Source: Dissertation Abstracts International, Volume: 77-10(E), Section: A.
Contained By:	Dissertation Abstracts International77-10A(E).
標題:	Instructional design. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10108410
ISBN:	9781339717739

Incorporating a training construct into the Unified Theory of Technology Acceptance and Use of Technology.
Harris, Matthew E.

Incorporating a training construct into the Unified Theory of Technology Acceptance and Use of Technology. - 176 p.

Source: Dissertation Abstracts International, Volume: 77-10(E), Section: A.

Thesis (Ph.D.)--Utah State University, 2016.

The purpose of this study was to identify and examine existing technology acceptance constructs as they relate to end-user participation in training programs. By analyzing technology acceptance constructs and their fit with existing training paradigms, it was expected that there would be a significant increase in use behavior as defined in the Unified Theory of Technology Acceptance and Use (UTAUT) model. An extended model that describes the links between the training paradigms and existing technology acceptance constructs as found in the UTAUT was then introduced and tested to see if the model could be improved by adding a training reactions construct.

ISBN: 9781339717739Subjects--Topical Terms:

3172279
Instructional design.

Incorporating a training construct into the Unified Theory of Technology Acceptance and Use of Technology.
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245 1 0 $a Incorporating a training construct into the Unified Theory of Technology Acceptance and Use of Technology.
300 $a 176 p.
500 $a Source: Dissertation Abstracts International, Volume: 77-10(E), Section: A.
500 $a Adviser: Robert J. Mills.
502 $a Thesis (Ph.D.)--Utah State University, 2016.
520 $a The purpose of this study was to identify and examine existing technology acceptance constructs as they relate to end-user participation in training programs. By analyzing technology acceptance constructs and their fit with existing training paradigms, it was expected that there would be a significant increase in use behavior as defined in the Unified Theory of Technology Acceptance and Use (UTAUT) model. An extended model that describes the links between the training paradigms and existing technology acceptance constructs as found in the UTAUT was then introduced and tested to see if the model could be improved by adding a training reactions construct.
520 $a Online pre and post training surveys were received from 111 students who participated in face-to-face training on structured query language (SQL) during spring 2014 and 2015 semesters. Survey questions were created from previously validated technology acceptance and training studies. From these responses, the basic structure of the original UTAUT model was partially confirmed.
520 $a The first conclusion drawn from this study was that training reactions (TR) significantly impact behavioral intention to use (BIU) information technology and was positively correlated, suggesting when TR increased, BIU also increased. The second conclusion drawn from this study was that the relationship between TR and BIU information technology was not fully mediated by facilitating conditions (FC), but was partially mediated by it. The third conclusion drawn from this study was that from the original UTAUT model, only performance expectancy (PE) was found to be a significant predictor of BIU information technology. Effort expectancy (EE), social influences (SI), and facilitating conditions (FC) were not found to be significant. Also, neither gender nor computer experience moderated any of the independent variables from the original UTAUT model. The fourth conclusion drawn from this study was neither gender, nor computer experience (Exp) moderated TR in predicting BIU.
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