analysis of mobile learning as an innovation in higher education –

46
Analysis Of Mobile Learning as an Innovation in Higher Education – A Comparative Study Of Three Countries Shuang Hao, Mengyao Cui, Vanessa P. Dennen, Yalin Turel, Li Mei 1 Featured Research Presentation at AECT 2014 – Jacksonville, FL

Upload: vanessa-dennen

Post on 01-Jul-2015

148 views

Category:

Education


5 download

DESCRIPTION

AECT 2014 Featured Research Session by Shuang Hao, Mengyao Cui, Vanessa P. Dennen, Yalin Turel, and Li Mei

TRANSCRIPT

Page 1: Analysis Of Mobile Learning as an Innovation in Higher Education –

Analysis Of Mobile Learning as an Innovation in Higher Education – A Comparative Study Of Three Countries

Shuang Hao, Mengyao Cui, Vanessa P. Dennen, Yalin Turel, Li Mei �

1 �Featured Research Presentation at AECT 2014 – Jacksonville, FL

Page 2: Analysis Of Mobile Learning as an Innovation in Higher Education –

Overview 2 �

¨  Background Introduction ¨  Research Question ¨  Research Method and Participants ¨  Data Analysis ¨  Results Description ¨  Result Summary and Discussion ¨  Q&A

Page 3: Analysis Of Mobile Learning as an Innovation in Higher Education –

Background Introduction 3 �

¨  Higher education institutions have taken initiatives to experiment on mobile learning, yet at the same time, studies on systematic analysis of mobile learning integration are scarce (Wu et al., 2012).

¨  The prevalence of mobile device ownership among students does not guarantee either use in an educational context or related learning outcomes (Valk, Rashid & Elder, 2010).

¨  Mobile learning is still at its infancy (Martin, Diaz, Sancristobal, Gil, Castro, & Peire, 2011).

Page 4: Analysis Of Mobile Learning as an Innovation in Higher Education –

Mobile Learning as an Innovation 4 �

¨  Five factors that influence adoption of an innovation (Rogers, 2003): ¤  Relative advantage ¤ Compatibility ¤ Complexity ¤  Trialability ¤ Observability

Page 5: Analysis Of Mobile Learning as an Innovation in Higher Education –

Research Question 5 �

¨  What is the current diffusion status of mobile learning in higher education?

Page 6: Analysis Of Mobile Learning as an Innovation in Higher Education –

Research Method and Participants 6 �

¨  A questionnaire was distributed to the students at nine public universities.

¨  Data were collected through 2012-2013.

Country # Participants # Universities

China 272 1

Turkey 300 7

United States 138 1

Page 7: Analysis Of Mobile Learning as an Innovation in Higher Education –

Data Analysis 7 �

¨  Measures of frequency were computed using data sets from each of the three countries.

¨  ANOVA and Tukey’s Studentized Range (HSD) test for post hoc analysis were conducted to compare the commonalities and differences within and across the three countries.

Page 8: Analysis Of Mobile Learning as an Innovation in Higher Education –

Results and Discussion 8 �

Relative Advantage

Compatibility

Complexity Trailability

Observability

Page 9: Analysis Of Mobile Learning as an Innovation in Higher Education –

Relative Advantage – Survey Items 9 �

¨  Survey Items ¤  I prefer collaborating with classmates via mobile device

over meeting face-to-face. ¤  I prefer using my mobile device over using a computer lab

when on campus.

Page 10: Analysis Of Mobile Learning as an Innovation in Higher Education –

Relative Advantage – Results 10 �

¨  General Result Description ¤ Mobile collaboration was accepted as an alternative means

of communication over face-to-face meetings for the American and Chinese groups.

¤  There was not a significant preference among any group when mobile was compared with computer-based learning.

Page 11: Analysis Of Mobile Learning as an Innovation in Higher Education –

Relative Advantage – Frequency Histogram 11 �

1: Not true at all 2 3 4 5: Very true

China 15.85 21.13 31.70 16.60 14.72

US 17.39 22.46 29.71 18.12 12.32

Turkey 42.62 21.14 19.13 10.74 6.38

0.00

5.00

10.00

15.00

20.00

25.00

30.00

35.00

40.00

45.00

Perc

enta

ge

I prefer collaborating with classmates via mobile device over meeting face-to-face.

Page 12: Analysis Of Mobile Learning as an Innovation in Higher Education –

Relative Advantage – Frequency Histogram 12 �

1: Not true at all 2 3 4 5: Very true

China 14.76 25.46 26.57 19.19 14.02

US 24.64 26.81 20.29 13.77 14.49

Turkey 19.46 22.48 21.14 19.46 17.45

0

5

10

15

20

25

30

Perc

enta

ge

I prefer using my mobile device over using a computer lab when on campus.

Page 13: Analysis Of Mobile Learning as an Innovation in Higher Education –

Relative Advantage – Results 13 �

¨  Cross-Country Differences ¤  In students’ preference of using mobile learning over face-

to-face learning, Turkish participants had a mean significantly lower than the American and Chinese participants.

¤ When mobile learning was compared with computer labs, no significant difference was found across the three countries.

Page 14: Analysis Of Mobile Learning as an Innovation in Higher Education –

Survey Items    P-value of overall F test

Mean Difference: US - China  

Mean Difference: US - Turkey  

Mean Difference:

China - Turkey  1. I prefer collaborating with classmates via mobile device over meeting face-to-face.   <.0001 -0.0770   0.6839*   0.7609*  

2. I prefer using my mobile device over using a computer lab when on campus.   0.1842 -0.2558   -0.2629   -0.0070  

Relative Advantage – ANOVA Outputs 14 �

Page 15: Analysis Of Mobile Learning as an Innovation in Higher Education –

Compatibility – Survey Items 15 �

¨  Survey Items 1.  If affordable, I want my mobile device to be the model with

the latest functions, services, and/or applications. 2.  I would like to try out new or beta versions of mobile

applications. 3.  I want to be among the first people to try out new mobile

functions, services and/or applications. 4.  I think using mobile learning can increase the effectiveness of

my academic performance. 5.  I think using mobile learning can assist my studying. 6.  I think using mobile learning can enhance my performance in

my courses.

Page 16: Analysis Of Mobile Learning as an Innovation in Higher Education –

Compatibility - Results 16 �

¨  General Result Description ¤  Students constantly update their mobile learning functions,

services, and/or applications, and enjoys trying out new learning possibilities with their mobile devices.

¤  Students perceived mobile learning as a support aid for their studies and can enhance their course performance.

Page 17: Analysis Of Mobile Learning as an Innovation in Higher Education –

Compatibility - Frequency Histogram 17 �

1: Not true at all 2 3 4 5: Very true

China 8.16 8.87 19.86 15.6 47.52

US 2.9 4.35 16.67 40.58 35.51

Turkey 7 16.33 30.33 36 10.33

0

5

10

15

20

25

30

35

40

45

50

Perc

enta

ge

If affordable, I want my mobile device to be the model with the latest functions, services, and /or applications.

Page 18: Analysis Of Mobile Learning as an Innovation in Higher Education –

Compatibility - Frequency Histogram 18 �

1: Not true at all 2 3 4 5: Very true

China 7.09 12.41 28.01 20.92 31.56

US 5.07 23.19 32.61 31.16 7.97

Turkey 4.68 7.36 13.38 47.49 27.09

0

5

10

15

20

25

30

35

40

45

50

Perc

enta

ge

I would like to try out new or beta versions of mobile applications.

Page 19: Analysis Of Mobile Learning as an Innovation in Higher Education –

Compatibility - Frequency Histogram 19 �

1: Not true at all 2 3 4 5: Very true

China 4.61 8.16 35.82 30.5 20.92

US 0 12.32 23.94 52.17 11.59

Turkey 2.33 2 15.33 53.33 27

0

10

20

30

40

50

60

Perc

enta

ge

I think using mobile learning can assist my studying.

Page 20: Analysis Of Mobile Learning as an Innovation in Higher Education –

Compatibility - Frequency Histogram 20 �

1: Not true at all 2 3 4 5: Very true

China 5.32 13.48 38.3 24.11 18.79

US 0.72 10.14 36.96 39.86 12.32

Turkey 1.33 4.67 8.33 51.67 34

0

10

20

30

40

50

60

Perc

enta

ge

I think using mobile learning can enhance my performance in my courses.

Page 21: Analysis Of Mobile Learning as an Innovation in Higher Education –

Compatibility - Results 21 �

¨  Cross-Country Differences ¤  Turkish participants were significantly more likely to

download new applications and try out new functions and services.

¤  Turkish participants perceived mobile learning significantly more useful in assisting learning, enhancing performance and promoting working efficiency than the other two groups of participants.

Page 22: Analysis Of Mobile Learning as an Innovation in Higher Education –

Compatibility – ANOVA Outputs 22 �

Survey Items    P-value of overall F test

Mean Difference: US - China  

Mean Difference: US - Turkey  

Mean Difference:

China – Turkey  

1. If affordable, I want my mobile device to be the model with the latest functions, services, and/or applications. <.0001 0.1599 0.7512* 0.5913*

2. I would like to try out new or beta versions of mobile applications. <.0001 -0.4368* -0.7118* -0.2750*

3. I want to be among the first people to try out new mobile functions, services and/or applications. <.0001 0.0046 -0.6726* -0.6772*

4. I think using mobile learning can increase the effectiveness of my academic performance. <.0001 0.1576 -0.6511* -0.8086*

5. I think using mobile learning can assist my studying. <.0001 0.0808 -0.3762* -0.4570*

6. I think using mobile learning can enhance my performance in my courses. <.0001 0.1531 -0.5944* -0.7475*

Page 23: Analysis Of Mobile Learning as an Innovation in Higher Education –

Complexity – Survey Items 23 �

¨  Survey Items 1.  Mobile apps should be easy to navigate when working on learning

tasks. 2.  It should be easy to learn how to use a new mobile learning

application. 3.  It should be easy to be skillful at using a mobile learning application. 4.  I feel prepared to use mobile devices for a class activity under the

guidance of my instructor. 5.  I feel prepared to use a mobile device to collaborate with classmates

on a project. 6.  I feel prepared to use a mobile device to look up learning

information. 7.  I feel prepared to use a mobile device to provide assistance with my

homework or studying.

Page 24: Analysis Of Mobile Learning as an Innovation in Higher Education –

Complexity - Results 24 �

¨  General Result Description ¤  There is a general expectation of and confidence in the

easy-to-use and easy-to-learn natural of mobile learning.

¤  In general, participants from all three countries still have doubts in conducting mobile learning to collaborate with classmates, to look up learning information, and to provide assistance on homework, even under the guidance of the instructor.

Page 25: Analysis Of Mobile Learning as an Innovation in Higher Education –

Complexity – Frequency Histogram 25 �

1: Not true at all 2 3 4 5: Very true

China 4.61 15.25 34.4 24.47 21.28

US 0.72 5.8 23.91 51.45 18.12

Turkey 8.72 14.77 34.23 31.88 10.4

0

10

20

30

40

50

60

Perc

enta

ge

It should be easy to be skillful at using a mobile learning application.

Page 26: Analysis Of Mobile Learning as an Innovation in Higher Education –

Complexity – Frequency Histogram 26 �

1: Not true at all 2 3 4 5: Very true

China 10.29 25.74 47.06 16.91 0

US 3.62 7.25 48.55 40.58 0

Turkey 4.71 14.14 63.64 17.51 0

0

10

20

30

40

50

60

70

Perc

enta

ge

I feel prepared to use a mobile device to provide assistance with my homework or studying.

Page 27: Analysis Of Mobile Learning as an Innovation in Higher Education –

Complexity - Results 27 �

¨  Cross-Country Differences ¤ American participants had a mean significantly higher than

Chinese participants on all the survey items, and significantly higher than Turkish participants on most items related to perceived ease of use and preparation for mobile learning.

Page 28: Analysis Of Mobile Learning as an Innovation in Higher Education –

Complexity – ANOVA Outputs 28 �

 Survey Items   P-value of overall F test

Mean Difference: US - China  

Mean Difference: US - Turkey  

Mean Difference:

China - Turkey  

1. Mobile apps should be easy to navigate when working on learning tasks. 0.0004 0.3138* 0.2296* -0.0842

2. It should be easy to learn how to use a new mobile learning application. <.0001 0.5421* -0.0687 -0.6108*

3. It should be easy to be skillful at using a mobile learning application. <.0001 0.3788* 0.5997* 0.2208*

4. I feel prepared to use mobile devices for a class activity under the guidance of my instructor. <.0001 0.4646* 0.1541 -0.3105* 5. I feel prepared to use a mobile device to collaborate with classmates on a project. <.0001 0.7219* 0.3311* -0.3908*

6. I feel prepared to use a mobile device to look up learning information. <.0001 0.5906* 0.4048* -0.1858*

7. I feel prepared to use a mobile device to provide assistance with my homework or studying. <.0001 0.5550* 0.3215* -0.2335*

Page 29: Analysis Of Mobile Learning as an Innovation in Higher Education –

Trialability – Survey Items 29 �

¨  Survey Items 1.  I would voluntarily engage in mobile learning. 2.  Instructors should not require students to use mobile resources. 3.  Although they might be helpful, mobile learning activities should not be

compulsory. 4.  I expect within-application instructional assistance (e.g., help or tutorials)

to be available to me when I engage in mobile learning. 5.  Guidance should be available to help select mobile learning applications. 6.  I expect to have specialized person(s) to provide assistance if I encounter

learning difficulties in mobile learning. 7.  I expect to have specialized person(s) to provide assistance if I encounter

technical difficulties in mobile learning. 8.  The availability of wifi is critical to my ability to engage in mobile

learning. 9.  Wifi availability is sufficient at my university. 10.  Wifi stability is sufficient at my university. 11.  Wifi speed is sufficient at my university.

Page 30: Analysis Of Mobile Learning as an Innovation in Higher Education –

Trialability - Results 30 �

¨  General Result Description ¤ Noncompulsory mobile learning and expected to have

external supports from the learning applications and experts to help with pedagogical or technical difficulties.

¤  The availability of wifi is considered critical among all three groups.

Page 31: Analysis Of Mobile Learning as an Innovation in Higher Education –

Trialability – Frequency Histogram 31 �

1: Not true at all 2 3 4 5: Very true

China 4.61 15.6 30.14 23.05 26.6

US 0.00 13.77 19.57 52.17 14.49

Turkey 24.67 36.33 24 11.67 3.33

0

10

20

30

40

50

60

Perc

enta

ge

I would voluntarily engage in mobile learning.

Page 32: Analysis Of Mobile Learning as an Innovation in Higher Education –

Trialability – Frequency Histogram 32 �

1: Not true at all 2 3 4 5: Very true

China 10.45 10.07 24.63 17.16 37.69

US 10.14 9.42 17.39 18.84 44.2

Turkey 4.71 7.74 13.13 30.98 43.43

0

5

10

15

20

25

30

35

40

45

50

Perc

enta

ge

The availability of wifi is crtical to my ability to engage in mobile learning.

Page 33: Analysis Of Mobile Learning as an Innovation in Higher Education –

Trialability – Frequency Histogram 33 �

1: Not true at all 2 3 4 5: Very true

China 47.21 17.1 18.22 10.04 7.43

US 0 12.32 23.91 31.88 31.88

Turkey 45.79 20.54 18.52 10.77 4.38

0

5

10

15

20

25

30

35

40

45

50

Perc

enta

ge

Wifi availability is sufficient at my university.

Page 34: Analysis Of Mobile Learning as an Innovation in Higher Education –

Trialability - Results 34 �

¨  Cross-Country Comparison ¤  Turkish participants had significantly lower score in their

willingness to try out mobile learning voluntarily than the other two groups of participants.

¤ Chinese participants expect outside facilitations to depend upon significantly more than the American and Turkish participants.

¤  The Chinese and Turkish participants rated significantly lower than American students regarding their wifi environment on campus.

Page 35: Analysis Of Mobile Learning as an Innovation in Higher Education –

Trialability – ANOVA Outputs 35 �

 Survey Items  P-value of overall F

test

Mean Difference: US - China  

Mean Difference: US - Turkey  

Mean Difference:

China - Turkey  

1. I would voluntarily engage in mobile learning. <.0001 0.1597 1.3473* 1.1875* 2. Instructors should not require students to use mobile resources. <.0001 -0.3361* 0.1129 0.4490* 3. Although they might be helpful, mobile learning activities should not be compulsory. <.0001 -0.4795* -0.1293 0.3502* 4. I expect within-application instructional assistance (e.g., help for tutorials) to be available to me when I engage in mobile learning. <.0001 0.0629 0.5357* 0.4727* 5. Guidance should be available to help select mobile learning applications. 0.8695 0.0163 0.0425 0.0262 6. I expect to have specialized person(s) to provide assistance if I encounter learning difficulties in mobile learning. 0.0031 -0.3188* -0.0907 0.2282* 7. I expect to have specialized person(s) to provide assistance if I encounter technical difficulties in mobile learning. <.0001 -0.2351* 0.1249 0.3600*

Page 36: Analysis Of Mobile Learning as an Innovation in Higher Education –

Trialability – ANOVA Outputs Continued 36 �

   P-value of

overall F test

Mean Difference: US - China  

Mean Difference: US - Turkey  

Mean Difference:

China - Turkey  8. The availability of wifi is critical to my ability to engage in mobile learning. 0.001 0.1597 -0.2314 -0.3911* 9. Wifi availability is sufficient at my university. <.0001 1.6995* 1.75926* 0.0598

10. Wifi stability is sufficient at my university. <.0001 1.1603* 1.2947* 0.1344

11. Wifi speed is sufficient at my university. <.0001 1.3290* 1.3999* 0.0709

Page 37: Analysis Of Mobile Learning as an Innovation in Higher Education –

Observability – Survey Items 37 �

¨  Survey Items ¤ What kind of learning tasks do you engage in with your

mobile device? ¤  Please describe any ways in which you currently use mobile

devices to support learning. (open-ended)

Page 38: Analysis Of Mobile Learning as an Innovation in Higher Education –

Observability – Quantitative Results 38 �

¨  General Result Description ¤  The participants have already engaged in various formal

and informal mobile learning activities, from working on projects to simple web inquiries.

Page 39: Analysis Of Mobile Learning as an Innovation in Higher Education –

Observability – Frequency Table 39 �

Learning Task Chinese Students American Students Turkish Students

Communicate with others 75% 95% 92%

Look up information 81% 81% 76%

Share file with others 56% 48% 60%

Read eBook 59% 18% 36%

Take notes in class 26% 20% 44%

Watch videos or lectures 35% 36% 61%

Practice learning skills 37% 28% 36%

Listen to podcasts 24% 14% 36%

Page 40: Analysis Of Mobile Learning as an Innovation in Higher Education –

Observability – Qualitative Results 40 �

¨  Please describe any ways in which you currently use mobile devices to support learning.

Participation Group Merging Themes

Chinese Students (96 valid entries)

•  Just-in-time research & information lookup (82%) •  Language learning (32%) •  Applications without the need of the Internet, e.g.,

calculator, dictionary, mp3(30%)

American Students (137 valid entries)

•  Course-related activates, e.g., Blackboard, email, view course materials (47%)

•  Just-in-time research & information lookup (36%) •  A replacement for computers/laptops (12%)

Turkish Students (256 valid entries)

•  Just-in-time research & information lookup (40%) •  Group work/ collaboration/sharing files (16%) •  Social networking (8%)

Page 41: Analysis Of Mobile Learning as an Innovation in Higher Education –

Result Summary and Discussion 41 �

¨  Mobile learning is at the budding stage in higher educational settings.

¨  We expected mobile learning to be widely and rapidly implemented in all three countries.

¨  A “social push” from the universities may help the diffusion of mobile learning.

Page 42: Analysis Of Mobile Learning as an Innovation in Higher Education –

Result Summary and Discussion 42 �

Diffusion Curve

Innovation Life Cycle Curve

Introduction Growth Maturity Decline ?

Page 43: Analysis Of Mobile Learning as an Innovation in Higher Education –

Result Summary and Discussion 43 �

¨  Suggestions: ¤ Create a safe and supportive learning environment

¤  Take pedagogical aspects of mobile learning into consideration during curriculum integration

Page 44: Analysis Of Mobile Learning as an Innovation in Higher Education –

Result Summary and Discussion 44 �

¨  Flowchart for using M-COPE to determine mobile learning suitability (Dennen & Hao, 2014) ¤ M: Mobile ¤ C: Conditions ¤ O: Outcomes ¤  P: Pedagogy ¤  E: Ethics

Page 45: Analysis Of Mobile Learning as an Innovation in Higher Education –

Thank You! 45 �

¨  Shuang Hao [email protected] ¨  Mengyao Cui [email protected] ¨  Vanessa P. Dennen [email protected] ¨  Yalın Kılıç TÜREL [email protected] ¨  Li Mei [email protected]

Page 46: Analysis Of Mobile Learning as an Innovation in Higher Education –

References 46 �

¨  Dennen, V. P., & Hao, S. (2014). Intentionally mobile pedagogy: the M-COPE framework for mobile learning in higher education. Technology, Pedagogy and Education, 23(3), 397-419.

¨  Martin, S., Diaz, G., Sancristobal, E., Gil, R., Castro, M., & Peire, J. (November 01, 2011). New technology trends in education: Seven years of forecasts and convergence. Computers & Education, 57(3), 1893-1906.

¨  Rogers, E.M. (2003). Diffusion of innovations (5th ed.). New York: Free Press.

¨  Wu, W. H., Jim, W. Y. C., Chen, C. Y., Kao, H. Y., Lin, C. H., & Huang, S. H. (September 01, 2012). Review of trends from mobile learning studies: A meta-analysis. Computers & Education, 59(2), 817-827.

¨  Valk, J. H., Rashid, A. T., & Elder, L. (2010). Using Mobile Phones to Improve Educational Outcomes: An Analysis of Evidence from Asia. International Review of Research in Open & Distance Learning, 11(1).