1. Dissertation Defense Conference Call Mark Moran Doctoral Candidate

2. Dissertation Title College Student’s Acceptance of Tablet Personal Computerss a Modification of the Unified Theory of Acceptance and Use of Technology Model

3. Agenda Why the Unified Theory of Acceptance and Use of Technology (UTAUT) Model. The Survey Tool. Hypotheses. Data Sample PLS Model Discussion & Conclusions

4. The Unified Theory of Acceptance and Use of Technology This is a publication distilled from Viswanath Venkatesh’s dissertation from 1998, University of Minnesota. Viswanath studied under Fred Davis, the publisher of the technology acceptance model (TAM) which came from his dissertation. Dr. Davis completed his dissertation in 1986 which was the basis for TAM.

5. Improved prediction UTAUT model was developed to help predict new technology implementation. Empirical validation showed that the new model successfully explained 70% of the variance of user acceptance intent (Venkatesh et al., 2003). Prior to then the models were successful predictors between 17 and 50%.

6. Agenda Why the Unified Theory of Acceptance and Use of Technology (UTAUT) Model. The Survey Tool. Hypotheses. Data Sample PLS Model Discussion & Conclusions

7. The survey tool The survey is a web based tool created in MS FrontPage that was used to gather participant responses based on a seven item likert scale captured in database. The tool can be examined at: www.homepage.dsu.edu/moranm/researc hwww.homepage.dsu.edu/moranm/researc h

8. The participant pool The survey was administered to 361 college students had been using the tablet PC for three months to more than a year. Students were surveyed in their normally schedule classes. –Classes were selected to target students who received their tablet the prior semester.

9. Agenda Why the Unified Theory of Acceptance and Use of Technology (UTAUT) Model. The Survey Tool. Hypotheses. Data Sample PLS Model Dissertation Timeline

10. Null Hypotheses' H01: University students, in the study environment, reject the Tablet PC. H02: The Unified Theory of Acceptance and Use of Technology (UTAUT) does not predict the successful acceptance of the Tablet PC H03: The constructs of the UTAUT will not demonstrate an effect on users acceptance of the tablet PC. H04: Computer self efficacy does not impact students acceptance of the Tablet PC. H05: Anxiety about computer use does not impact students’ acceptance of the Tablet PC H06: Students use pattern of the Tablet PC does not impact their acceptance of the device.

11. Alternate Hypotheses' Ha1: University students, in the study environment, accept the Tablet PC. Ha2: The Unified Theory of Acceptance and Use of Technology (UTAUT) does predict the successful acceptance of the Tablet PC Ha3: The constructs of the UTAUT will demonstrate an effect on user acceptance of the tablet PC. Ha4: Computer self efficacy does have an impact on students acceptance of the Tablet PC. Ha5: Anxiety about computer use does have an impact on students’ acceptance of the Tablet PC. Ha6 Students use of the Tablet PC does not impact student’s acceptance of the device.

12. Agenda Why the Unified Theory of Acceptance and Use of Technology (UTAUT) Model. The Survey Tool. Hypotheses. –Changes Data Sample PLS Model Discussion & Conclusions

13. 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.

14. Graphical Representation

15. Significant Data Findings There were statistically significant difference found in two population groups. The participants who classified themselves as freshman had significant variance with the other classifications. There were significant differences based on first computer use among participants.

16. T-test & p-value results for grade declaration Comparison GroupsT-statp-value --------------------------------------------------------------- Freshman vs. sophomore1.670.04 Freshman vs. junior1.450.07 Freshman vs. senior1.590.06

17. T-test & p-value results for first computer use declaration Comparison GroupsT-statp-value --------------------------------------------------------------- Elementary vs. college1.790.05 Middle School vs. high school1.470.07 Middle School vs. college1.840.04

18. Agenda Why the Unified Theory of Acceptance and Use of Technology (UTAUT) Model. The Survey Tool. Hypotheses. –Changes Data Sample PLS Model Discussion & Conclusions

19. Partial Least Squares is the analytical model most commonly used to analyze data in TAM and UTAUT publications.

20. 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.

21. All participants

22. 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.

23. Freshman only (N = 127)

24. Juniors & Senior Participants

25. PLS Findings BehavioralUse ModelIntentBehavior Total _______________________________________ All 55%11% 66% Freshman 63%22% 85% Upper Class49%7% 56%

26. Agenda Why the Unified Theory of Acceptance and Use of Technology (UTAUT) Model. The Survey Tool. Hypotheses. Data Sample PLS Model Discussion & Conclusions

27. 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.

28. 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.

29. 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. GroupBehavioral IntentUse behavior ----------------------------------------------------------- All55%11% Freshman63%22% Upper Class49% 7%

30. 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%).

31. 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.

32. 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. GroupSelf Efficacy Contribution ----------------------------------------------------------- All12% Freshman10% Upper Classminus 2%

33. The contribution of self efficacy will be studied more in depth in subsequent research with a K12 one-on-one study that will be conducted in South Dakota with 30 pilot schools.

34. 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.

35. 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.

36. The influence of use behavior 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.

37. Concluding remarks 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!

38. 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.

39. These are multistable preceptions users can rarely recognize both but project success requires both so management needs to be aware before it is too late! Usefulness Ease of Use

40. Future Research The research for this dissertation has opened my preceptions 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 colaborating 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.

41. With the time now, and knowledge, not available to me I will be pursuing grant opportunities and plan to be active in publishing the findings of our research in the next few 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.