robin l. donaldson april 29, 2011 dissertation defense florida state university college of...
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Copyright Robin Lee Donaldson. All rights reserved. 1
Student Acceptance of Mobile Learning
Robin L. DonaldsonApril 29, 2011Dissertation Defense
Florida State UniversityCollege of Communication and Information
Copyright Robin Lee Donaldson. All rights reserved. 2
Problem Statement
Study of technology acceptance using IS theories has received extensive attention from research in information systems, library information studies, and from education researchers, however:
Limited research using IS models Mobile learning may have unique characteristic IS models may not fully address mobile learning Impact of mobile devices on higher education and
use for access to library and information resources is unclear
Copyright Robin Lee Donaldson. All rights reserved. 3
Purpose
Use technology acceptance theory as a theoretical framework to examine the determinants associated with community college students’ acceptance and use of mobile learning.
Copyright Robin Lee Donaldson. All rights reserved. 4
Unified Theory of Acceptance and Use of Technology (UTAUT)
Performance Expectancy▪ “the degree to which an individual believes that using the
system will help him or her to attain gains in job performance”
Effort Expectancy▪ “the degree of ease associated with the use of the system”
Social Influence▪ “the degree to which an individual perceives that
important others believe he or she should use the new system”
Facilitating Conditions▪ “the degree to which an individual believes that an
organizational and technical infrastructure exists to support use of the system”
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Additional Constructs
Self-management of learning is “the extent to which an individual feels he or she is self-disciplined and can engage in autonomous learning”
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Additional Construct cont.
Perceived playfulness -a state of mind that includes three dimensions: the extent to which the individual: perceives that his or her attention is
focused, curious during and finds the interaction intrinsically
enjoyable or interesting.
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Additional Construct cont.
Voluntariness of Use “the degree to which use of the
innovation is perceived as being voluntary, or of free will”
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Research Design
Mixed Method Procedure
Archival survey analysis Interviews
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Survey Instrument
Archival survey data UTAUT -Venkatesh, Morris, Davis, and Davis
(2003) Wang, Wu, and Wang (2008)
Demographic and opinion-related questions gender/age access to a home computer Internet experience; frequency of use of mobile devices; types of information, and library and learning
resources currently used and interested in accessing
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Scales
Likert scales (1–7) Anchors
1Strongly agree2Agree3Moderately agree4Slightly agree5Neutral6Disagree7Strongly disagree
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Survey Population & Participants
Community College in North Florida Convenience Sample Students enrolled in credit courses
330 participants Average Age: 27 Gender: Females: 61.8% Males: 38.2%
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Sample Size Needed
a-priori power analysis No. of participants required to detect
a medium effect size (d = .50) with power = .80 for a two-tailed independent samples t-test at a = .05. Suggested that 128 needed to achieve a
power of .80 given these parameters Statistical software G*Power 3.0.8
Copyright Robin Lee Donaldson. All rights reserved. 13
Research Question 1
Is there a statistically significant difference between males and females on the behavioral intention to use mobile learning?
H0: There will be no statistically significant difference between the males and females on the behavioral intention to use mobile learning.
Analysis: independent samples t-test
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Findings Gender and Behavioral Intention
t (289) = -2.03, p < .05
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Research Question 2
Are there statistically significant relationships among the participants’ age, behavioral intention to use mobile learning and the actual use of mobile learning?
H0: There will not be a statistically significant relationship between the participants’ age and their behavioral intention to use mobile learning.
Analysis: Simple linear regression
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Findings - Age and Behavioral Intention
F (1, 266) = 0.03, = 0.01, p > .05, R2 = .00
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Findings and DiscussionAge and Behavioral Intention
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Research Question 3
Are the following independent variables significant predictors of the behavioral intention to use mobile learning:
Analysis: multiple regression
1. performance expectancy
2. effort expectancy3. social influence4. facilitating
conditions
5. perceived playfulness
6. self-management of learning
7. voluntariness of use
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Findings - Independent Variables and Behavioral Intention
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Additional Analysis
Demographic and opinion-related questions
• Personal activities• Frequency of Internet access• Internet experience• Types of information, and library and learning resources currently used and interested in accessing
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Personal Activities
Phon
e
Emai
l
Text
mes
sage
Take
vid
eos
Take
pict
ures
Liste
n to
mus
ic
Sche
dule
app
oint
men
ts
Pay
bills
Play
gam
es
Data
apps
to re
ad/e
dit
None
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
90.0%84.4%
61.1%
78.3%
47.1%
76.8%
54.1%50.6%
26.8%
40.4%
29.9%
8.6%
n=314
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Frequency of Mobile Internet Access
Several times a day 1 – 2 times a day 3 – 5 days a week 1 – 2 days a week 1 – 3 times a month Never0
10
20
30
40
50
60
47.9%
13.9%
8.4%
3.6% 3.9%
22.3%
fHbRDGQM6Zj8rvfiiC6nvl
Copyright Robin Lee Donaldson. All rights reserved. 23
Information Resources Used
Internet
Social networks
Video
eBooks and journals
Library resources
Podcasts
0 10 20 30 40 50 60 70 80 90
81.7%
58.6%
50.7%
19.8%
19.4%
16.5%
Weather
Maps and directions
News
Shopping
Other information apps
0 10 20 30 40 50 60 70 80
71.9%
64.7%
59%
35.6%
33.8%
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Interest in Mobile Library Resources
Text a librarian
eBooks
Catalog databases
Book & movie reserves
Ask-a-librarian
Videos & Audio
Library blog
0 10 20 30 40 50 60 70
65.5%
62.2%
54%
50.4%
47.1%
41%
24.8%
Copyright Robin Lee Donaldson. All rights reserved. 25
Interest in Instructional Resources
Blackboard
eTextbooks
Flash cards
Video
Audio
PPT
URL's
Math videos
Writing/grammar videos
Reading improvement videos
0 10 20 30 40 50 60 70 80 90 100
89.6%
72.7%
61.5%
57.3%
54.5%
53.5%
52.4%
52.1%
41.6%
35.7%
Copyright Robin Lee Donaldson. All rights reserved. 26
Qualitative - Purpose
Gather additional data not revealed in survey
Increase understanding of determinants, barriers, and perceptions on use
Determinates of acceptance expected but not pre-designed in interview
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Qualitative - Research Question
Research Question 4 -
What factors influence community college student’s use of mobile devices for learning?
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Qualitative – Setting & Participants
Research Setting – same Sample Population - same Participants - 20 Convenience sampling Selecting participants
Courses targeted – diverse disciplines, level, and utilize library or online resources
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Qualitative - Data Collection & Analysis
Semi structured Research question guide discussion
Protocol One interviewer Script Face-to-face, online, or phone
Coded using inductive analysis Themes (16) derived from interview data
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Qualitative - Barriers
Ownership, acceptance, device attributes, cost, and mobile access to academic services
Knowledge of Library Resources▪ No knowledge of availability & benefits (35%) ▪ “I don’t really know if I can access all that
information”
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Qualitative Data Analysis 90% felt mobile learning useful for
supporting learning Manage time Productive Organize thoughts & tasks Prepare for class
85% use calendar function 40% - Anywhere/anytime access
(mobility)
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Communication
70% Facebook & 60% texting classmates “…Makes it easier to kind of actually form a
community in a sense. Form a community—and you actually get to know people and study together and things like that.”
Faculty respond “quicker than email..usually within
the hour” Too personal, not professional, keep school
separate, not give faculty personal phone number (30%)
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Social Influence – Faculty
Overall, not perceived as supporting or recommending use in or outside of the classroom▪ “..older instructors aren’t real comfortable accepting
new tecnology…”▪ “…never actually spoke to a professor about it because
normally they just don’t want to see your phone.”▪ Turn off in class/out of hands – no note taking
Instances of support were provided by some May readily accept learning if faculty or their
peers do so and feel it is beneficial
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Playfulness & Exploration
No direct question 35% Identified playfulness
component “…more likely to do it because it
wouldn’t seem much of a chore… “fun”
Lose track of time or explore further
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Research Q1 - Discussion
Suggests no significant difference between males and females and intended use of mobile learning.
Findings were unexpected Prior research - moderating effect of
gender on predictor variables This research – examined differences
between males and females on BI Need additional research
Copyright Robin Lee Donaldson. All rights reserved. 36
Research Q2 - Discussion
Suggests age does not have a relationship with intention to use mobile learning
Findings were unexpected Prior - Wang, Wu, Wang (2008) research - moderating effect of gender on
predictor variables. Computer literature suggest a there is an age relationship This research – examined differences between males and females on BI
May be due to the age range of the participants 27.13 years average Nine out of ten 18-29 year old more likely to use mobile data
applications 65% access the Internet from their cell phones (Smith, 2010)
Need additional research
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Omnibus model accounts for 75 % percent of the variance in BI to use • UTAUT study (70%) • Wang et al., (2008) (58%)
Regression coefficients for all respondents*p < 0.05 **p < 0.01
Research Q3 - Discussion
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Implications
Clear interest in mobile access to learning and library information content
Experience with browsing/searching on mobile devices higher levels of BI to use, perceived ease of use, and
perceived usefulness of mobile learning (Akour, 2009)
Potential to reduce digital divide (Hahn,2008)
Increased usage for personal purposes may lead to increased demand for mobile academic purposes
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Librarians
Students are interested in mobile access to library resources and services
Point toward the need to familiarize students with: benefits of mobile access to library
resources mobile library resources available completing various learning tasks, recommendations for applications
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Administrators
Point toward the need to:
provide support for mobile access to services
assist students in gaining necessary skills and knowledge to successfully use mobile learning
promote the performance benefits of usage
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Educators
Point toward the need to familiarize students with: ways to support both classroom and
remote learning available instructional mobile resources performance benefits and ‘playfulness’
aspect and providing content and information
on resources formatted for mobile devices
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Research Limitations
Convenience sample
Cross sectional
Single community college -not generalizabile
Statistical significance within the design does not imply cause-and-effect relationships
Predictors identified may not be found to be predictors in other mobile learning research. Those that were not found to be predictors may be found to be predictors in other mobile learning research
Copyright Robin Lee Donaldson. All rights reserved. 43
Future Research
Examine self-management alone to understand its importance as a predictor in mobile learning.
Examine the significance of the predictors for educators.
Examine effort expectancy using individuals with varying levels of experience with mobile devices and a wider age range of users.
Similar research on mobility as a significant predictor for access to digital resources and support from academic libraries
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Questions?
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Image Attribution
Schaefer, Andreas (2008). iX-ray. Retrieved from: http://flickrcc.bluemountains.net
Also available in multiple sizes at Flickr Website: http://www.flickr.com/photos/36266791@N00/2986303105
Some rights reserved. This image is licensed with a Creative Commons Attribution, Non-Commercial, Share Alike license. http://creativecommons.org/licenses/by-nc-sa/2.0/deed.en
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Null Hypotheses
H1. Performance expectancy will not have a positive effect on behavioral intention to use mobile learning.
H2. Effort expectancy will not have a positive effect on behavioral intention to use mobile learning.
H3. Social influence will not have a positive effect on behavioral intention to use mobile learning.
H4. Self-management of learning will not have a positive effect on behavioral intention to use mobile learning.
H5. Perceived playfulness will not have a positive effect on behavioral intention to use mobile learning.
H6. Voluntariness of use will not have a positive effect on behavioral intention to use mobile learning.
H7. Behavioral intention will not have a positive influence on mobile learning intention to use .
H8. Facilitating conditions will not have a positive influence on mobile learning intention to use.