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Dissertation Defense Conference Call. Mark Moran Doctoral Candidate. Dissertation Title. College Student’s Acceptance of Tablet Personal Computerss a Modification of the Unified Theory of Acceptance and Use of Technology Model . Agenda.

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Dissertation defense conference call

Dissertation Defense Conference Call

Mark Moran

Doctoral Candidate


Dissertation title
Dissertation Title

College Student’s Acceptance

of

Tablet Personal Computerss

a Modification of the

Unified Theory of Acceptance

and Use of Technology Model


Agenda
Agenda

  • Why the Unified Theory of Acceptance and Use of Technology (UTAUT) Model.

  • The Survey Tool.

  • Hypotheses.

    • Changes

  • Data Sample

  • PLS Model

  • Discussion & Conclusions


Sample

263 valid responses were captured in the survey database.

Basic statistics for the data is summarized below for the significant groups.

Class Status:

127 freshman, 66 sophomore, 49 juniors, 16 seniors

First Computer Use:

96 in elementary, 97 in middle school, 37 in high school, 33 in college.

Sample



Significant data findings
Significant Data Findings

  • There were statistically significant difference found in two population groups.

  • The participants who classified themselves as freshman had significant difference with the other classifications.

  • There were also significant differences based on first computer use among participants.


T test p value results for grade declaration

Comparison Groups T-stat p-value

---------------------------------------------------------------

Freshman vs. sophomore 1.67 0.04

Freshman vs. junior 1.45 0.07

Freshman vs. senior 1.59 0.06

T-test & p-value resultsfor grade declaration


T test p value results for first computer use declaration

Comparison Groups T-stat p-value

---------------------------------------------------------------

Elementary vs. college 1.79 0.05

Middle School vs. high school 1.47 0.07

Middle School vs. college 1.84 0.04

T-test & p-value resultsfor first computer use declaration


Agenda1
Agenda

  • Why the Unified Theory of Acceptance and Use of Technology (UTAUT) Model.

  • The Survey Tool.

  • Hypotheses.

    • Changes

  • Data Sample

  • PLS Model

  • Discussion & Conclusions


Pls graph of dissertation model
PLS-Graph of Dissertation Model

  • The next three slides show the PLS-Graph analysis of all the participants.

    • Just the declared freshman participants.

    • Just the junior & senior participants.



Explanation
Explanation

  • The numbers in the middle of the arrows represent the contribution of each independent construct to the dependent constructs.

  • The number below the dependent constructs is the percent of variation of that construct explained by the model.




Pls findings
PLS Findings

Behavioral Use

Model Intent Behavior Total

_______________________________________

All 55% 11% 66%

Freshman 63% 22% 85%

Upper Class 49% 7% 56%


Agenda2
Agenda

  • Why the Unified Theory of Acceptance and Use of Technology (UTAUT) Model.

  • The Survey Tool.

  • Hypotheses.

  • Data Sample

  • PLS Model

  • Discussion & Conclusions


Discussion
Discussion

  • The dissertation model supports five of the six hypotheses as discussed in the slides to follow.

  • This whole process has been extremely rewarding as it opened a new world of behavioral research for this researcher.

  • Although this is a very narrow topic the area has many problems to analyze.


  • This experience has opened the area of web based survey that will be highly valuable for future research.

  • The statistically analysis and PLS-Graph knowledge gained will benefit both the student and his research in the future.

  • The process has changed the way the research thinks about addressing a problem.

  • The learning experience is about the journey not the destination.


University students in this environment accept the tablet pc
University students, in this environment, accept the tablet PC.

  • All participant groups have positive behavioral intent and use behavior and most construct have a positive contribution to the dependent variables.

    Group Behavioral Intent Use behavior

    -----------------------------------------------------------

    All 55% 11%

    Freshman 63% 22%

    Upper Class 49% 7%


The Unified Theory of Acceptance and Use of Technology (UTAUT) does predict the successful acceptance of the Tablet PC.

  • All constructs used in UTAUT have a positive correlation to behavioral intent.

  • Anxiety (- 7%) is not part of UTAUT it was added to this study to support investigative vigor with attitude toward using technology (47%) and self efficacy (12%).


The constructs of the utaut will demonstrate an effect on user acceptance of the tablet pc
The constructs of the UTAUT will demonstrate an effect on user acceptance of the Tablet PC.

  • Supported by the same data as the previous alternative hypothesis.


Computer self efficacy does have an impact students acceptance of the tablet pc
Computer self efficacy does have an impact students acceptance of the Tablet PC.

  • The dissertation model re-introduced this construct and found that in the research environment this variable does impact acceptance.

    Group Self Efficacy Contribution

    -----------------------------------------------------------

    All 12%

    Freshman 10%

    Upper Class minus 2%



Anxiety about computer use does have an impact on student s acceptance of the tablet pc
Anxiety about computer use does have an impact on student’s acceptance of the Tablet PC.

  • The negative contribution of anxiety indicate that there is not a contribution to the dependent construct behavioral intent.

  • Contribution is -7% for the whole population and -12% for both the freshman and upper class groups.


Students use of the tablet pc does impact student s acceptance of the device
Students’ use of the Tablet PC does impact student’s acceptance of the device.

  • Initially I thought that the positive outcome of the dissertation model indicated support for this statement, but after learning more about the PLS-Graph tool I learned that you could reverse the arrow of effect and when I did that for use behavior I found that it did not have a positive contribution to behavioral intent.


The influence of use behavior
The influence of use behavior acceptance of the device.

  • Reversal of the link between the two dependent constructs indicated in the dissertation model that use does not contribute to behavioral intent.

  • The freshman and upper classmen model does indicate a contribution at 7 & 16 percent respectively.

    • This phenomena should be further studied.


Future research
Future Research acceptance of the device.

  • The research for this dissertation has opened my perceptions of all the possible applications of adoption research.

  • There are many opportunities to pursue this type of behavioral research and grant opportunities should be available.

    • Initially I will be collaborating with Dr. Hawkes on the K12 project in South Dakota and publishing the dissertation results with Dr. El-Gayar at the DSI meeting in San Antonio this fall.


  • With the time now, and knowledge, now available to me I will be pursuing grant opportunities and plan to be active in publishing the findings of my research in the next three years.

  • The K12 study with have two data samples, one before the pilot study begins and a follow-up survey after one year of use in the K12 pilot of thirty schools. Approximately 250 teachers will be involved and we hope for more than 50% participation in the survey.


Concluding remarks
Concluding remarks be pursuing grant opportunities and plan to be active in publishing the findings of my research in the next three years.

  • During the dissertation process I have learned much more than I thought I might.

  • Technology acceptance is fundamentally about about two features of technology; ease of use and usefulness. Initially they seem the same but they are not!


  • Ease of use is an interface issue and can be changed pretty easily.

  • Usefulness is based on company requirements and is very hard to change once a project gets to the users.

  • The perception of these characteristics can make or break a project.

  • Measurement of these before project implementation can alert the organization to possible problems that can be averted.


Usefulness

Ease of Use


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