robin l. donaldson april 29, 2011 dissertation defense florida state university college of...

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


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


Purpose

Use technology acceptance theory as a theoretical framework to examine the determinants associated with community college students’ acceptance and use of mobile learning.


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”


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”


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.


Additional Construct cont.

Voluntariness of Use “the degree to which use of the

innovation is perceived as being voluntary, or of free will”


Research Design

Mixed Method Procedure

Archival survey analysis Interviews


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


Scales

Likert scales (1–7) Anchors

1Strongly agree2Agree3Moderately agree4Slightly agree5Neutral6Disagree7Strongly disagree


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%


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


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


Findings Gender and Behavioral Intention

t (289) = -2.03, p < .05


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


Findings - Age and Behavioral Intention

F (1, 266) = 0.03, = 0.01, p > .05, R2 = .00


Findings and DiscussionAge and Behavioral Intention


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


Findings - Independent Variables and Behavioral Intention


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


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


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


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%


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%


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%


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


Qualitative - Research Question

Research Question 4 -

What factors influence community college student’s use of mobile devices for learning?


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


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


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”


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)


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%)


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


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


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



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


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



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


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


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


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


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


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


Questions?


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

http://flickrcc.bluemountains.net/

http://www.flickr.com/photos/36266791@N00/2986303105

http://www.flickr.com/photos/36266791@N00/2986303105

http://creativecommons.org/licenses/by-nc-sa/2.0/deed.en

http://creativecommons.org/licenses/by-nc-sa/2.0/deed.en


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.

robin l. donaldson april 29, 2011 dissertation defense florida state university college of...

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