1. An Interpretation of the 2013 EDUCAUSE Student Use of Technology Study Andrew C. Lawlor, PhD Faculty of the Future Conference Bucks County Community College May 30, 2014

2. Let’s use the technology!  Respond to the poll – test of Poll Anywhere

3. Today’s outcomes  Understand ECAR/EDUCAUSE study purpose and design  Identify results of study  Consider the impact on teaching and learning

4. Purpose  Profile of undergraduates’ ownership and use  What undergraduates say  Students’ perceptions  Trends of student behaviors, attitudes, and perceptions  Benchmark  Longitudinal technology trends  Actionable recommendations on meeting preferences and expectations

5. Scope

6. Methodology  Local Approval/IRB/Sampling Plan  Link sent to students via email  Data collected in March 2013  Incentives?  Any institution – free

7. Analysis  Representative sample – matched profile  1% margin of error – whole population  Findings statistically significant (.001 level)  Conducted four focus groups – public MA institution

8. Summary of Participants and Response Rate

9. Own a Tablet or iPad – US Results  Of those surveyed, how many students own or plan to purchase a tablet or iPad? A.14% B.29% C.43% D.56%

10. Overview of US Results

11. Technology Value &Use

12. Learning Environments

13. Mobile Device Ownership and Use

14. Smartphone Use  Of students responding, how many use their smartphone for a combination of academic and other uses? A.16% B.21% C.54% D.61%

15. Connectivity & Engagement

16. How Bucks Compares

17. Technology Value & Use Bucks – 73.3% & AA – 75.1% Bucks – 73.3% & AA – 75.7% Bucks – 55.5% & AA – 58.7% Bucks – 66.1% & AA – 68.5% Bucks – 69.3% & AA – 67.9% Bucks – 61.6% & AA – 59.9% Bucks – 45.1% & AA – 40.5% Bucks – 20.6% & AA – 30.2% Bucks – 45.8% & AA – 50.8% Bucks – 25.9% & AA – 22.2% Bucks – 28.2% & AA – 26.9% Bucks – 67.9% & AA – 57.9%

18. Learning Environments Bucks – 56.3% & AA – 56.2% Bucks – 1.3% & AA – 1.0% Don’t know what a MOOC is: Bucks – 72.3% & AA – 73.9% Bucks – 32.9% & AA – 34.9% Bucks – 58.1% & AA – 52.5%

19. Instructors effectively using technology  Of those surveyed, how many students feel that most of their instructors effectively use technology?

20. Mobile Device Ownership and Use Bucks – 82.8% & AA – 84.3% Bucks – 80.2% & AA – 73.5% Bucks – 57.8% & AA – 55% Bucks – 32.3% & AA – 32.8% Bucks – 22.1% & AA – 17.6% Bucks – 67.9% & AA – 61.6% Bucks – 4.1% & AA – 3.1% Yes! Same!! Bucks – 23.3% & AA – 21.7% Bucks – 6.5% & AA – 9% Bucks – 18% & AA – 17.4% Bucks – 13.3% & AA – 20.6%

21. Connectivity & Engagement Bucks – 63.7% & AA – 62.1% Bucks – 65% & AA – 61% Bucks – 51.3% & AA – 46.3% Bucks – 60% & AA – 61.3% Bucks – 9.9% & AA – 11.4% Bucks – 86.5% & AA – 82.9% Bucks – 20.5% & AA – 21.5% Bucks – 74.5% & AA – 70.8%

22. What does the literature say?

23. Thompson, S. (2012).  Student use of library computers: Are desktop computers still relevant in today's libraries? Information Technology & Libraries, 31(4), 20-33.  CSU-San Marcos study of computer use in the library; 2009 & 2010  Largely a commuter campus  Students prefer desktop computers in library, even those with laptops  Convenience and close proximity to library services  Was conducted before the iPad/tablet explosion

24. Elder, A. D. (2013).  College students' cell phone use, beliefs, and effects on their learning. College Student Journal, 47(4), 585-592.  Found increased use and acceptance of cell phone use in class  Heavy reliance on college students’ lives  Use of cell phone during a lecture did not negatively affect comprehension, though students predicted poorer scores  No patterns were found among variables of ACT, gender, classification status, ratings of self-reported distraction, ratings of self-reported time using phone

25. Dresselhaus, A. & Shrode, F. (2012).  Mobile technologies & academics: Do students use mobile technologies in their academic lives and are librarians ready to meet this challenge?. Information Technology & Libraries, 31(2), 82-101.  Case study at Utah State University  54% of undergraduates and 50% of graduate students use mobile technology for academic purposes  How often they used library electronic resources - majority a few times each semester  “If library resources were easily accessible on your mobile devices…” – 70% on a smartphone; 47% on an iPad; 46% on an e-book reader; 63% on other devices  Services desired – library catalog, mobile services, articles, reserve study rooms

26. Par, S., Nam, M., & Cha, S. (2012).  University students' behavioral intention to use mobile learning: Evaluating the technology acceptance model. British Journal Of Educational Technology, 43(4), 592-605.  Theoretical framework – Technology Acceptance Model  20 e-learning courses randomly selected; 567 students responded (94.5% return rate)  Of those, 288 used mobile devices; research limited to this sample  Demographic and data gathered based on TAM

27. Technology Acceptance Model (TAM)

28. Results  Model was supported  Explains Behavioral Intention (BI) to use m-learning  Major Relevance (MR) plays a significant role in m-learning Attitude (AT) and Perceived Usefulness (PU)  AT a determinant affecting BI  Korean society encouraged to use IT in every field  Subjective Norm (SN) is directly related to BI  System Accessibility (SA) affected BI; Perceived Effectiveness (PE)

29. Recommendations  Boost AT toward m-learning  Make connection between m-learning and social needs  High quality wireless Internet environment  Provide on-line and off-line support to build up Self Efficacy (SE)

30. TAM  Which recommendation from the TAM study do you feel would have the most impact on adoption of mobile learning?

31. Jelfs, A., & Richardson, J. E. (2013).  The use of digital technologies across the adult life span in distance education. British Journal Of Educational Technology, 44(2), 338-351.  Compared access to digital technologies, attitudes to digital technologies and approaches to studying at UK Open University  Stratified random sample by age – 21 to 100  No evidence of discontinuity of tech use around age of 30  Broadly positive attitudes to tech regardless of age  Older age groups more likely to adopt deep, strategic approach to studying  Modal response for using technology for studying was “1-3 hours” in every age group; younger spent longer for study, however  Limitation – no academic achievement data; all distance ed students

32. Analysis

33. What is different at Bucks?  Tech helps less than expected  Less aware of open educational resources  Value (important for success) for e-books  More familiar with online courses but not as enamored with blended learning  Less laptop adoption, but higher smartphone and desktop  Smartphone use banned or discouraged in class but lower than others, but tablets or laptops encouraged much less  Tech makes students feel connected to faculty slightly higher

34. What is the impact on teaching and learning at Bucks?  Students do not fully recognize connection between their use of technology and their future  Academic outcomes  Future educational plans  Workplace  Might our blended learning courses need to become more dynamic/interactive?  How can we leverage the high smartphone adoption rate?  Keep moving towards more e-books  Keep/encourage interaction using tech – students feel connected

35. Conclusions  Data more valuable than anecdotes  Leverage what information is already available  Participate in the EDUCAUSE/ECAR study (study@educause.edu)  Technology adoption requires sustained, intentional action

36. Contact Info Andrew.Lawlor@bucks.edu Twitter: @andrewclawlor