ISEM 3120 Seminar in ISEM 2014-2015 Semester Chuk Cheuk Ka12204560 Lau Ming Sze12202401 Ng Ka Fan12202967 Tsoi Chak Fei14204991 Wan Chun Kit12203033 Wong.

ISEM 3120Seminar in ISEM

2014-2015 Semester

Chuk Cheuk Ka 12204560

Lau Ming Sze 12202401

Ng Ka Fan 12202967

Tsoi Chak Fei 14204991

Wan Chun Kit 12203033

Wong Tsun Lam 12210498

Content

1. Introduction2. Research Method3. Findings 4. Conclusion

1. Introduction

1.1 Background1.2 Definitions & Concept1.3 Objective1.4 Rationale

1.1 BackgroundResearch case:

Explaining and predicting users’ continuance intention toward e-learning: An extension of the expectation–confirmation model

1.1 Background

Lee M.C. (2010), Explaining and predicting users’ continuance intention toward e-learning: An extension of the

expectation-confirmation model, Computers & Education 54, 506-516

1.2 Definitions & Concepts

Definitions

E-learning is the use of electronic media,

educational technology and information

and communication technologies (ICT) in

education.

In this article, author focus on the web-

based e-learning program

1.2 Definitions & Concept

Concept

The intention to continue using e-

Learning system is still very low

Understanding the factors affecting

customers’ intention to continue using

e-learning can:

1. Assist e-learning developers in

designing popular contents

2. Help teachers and vendors design

strategies that are more likely to

increase the use of e-learning.

1.3 Objective

1.4 Rationale

1.4 RationaleProblems of Previous Research

Employs inadequate factors which

affect the intentions

It did not show what attitude beliefs

would affect user’s attitude towards

e-learning

The flow theory can capture the

elements of motivation

Bridge the EXISTING GAP between

acceptance and continuance streams

2.1 Model2.2 Questionnaire2.3 Sampling Techniques & Statistical Method

2. Research Model

2.1 ModelResearch model and hypotheses based on

Expectation–confirmation model (ECM)

Technology acceptance model (TAM)

Theory of planned behavior

Flow theory

2.1 Model

Expectation–confirmation model (ECM)

2.1 Model

2.1 Model

Technology acceptance

model (TAM)

Two particular belief

• Perceived usefulness

• perceived ease of use

2.1 ModelTheory of planned behavior

Based on theory of reasoned action(TRA)Behavioral attitude and subjective norm affect behavioral intention and actual behavior

Flow theory

Three constructs• Perceived

Enjoyment• Perceived Control• Concentration

Perceived control is similar to the perceived behavioral control in TPB

2.1 Model

2.2. Questionnaire

1. Construct in research model

Seven-point Likert scale

2. Demographic questions

about participants

2.2. Questionnaire

Measuring factor

Perceived usefulness and ease of use (Davis

1989)

Subject norm, perceived behavior control and

attitude (Taylor and Todd 1995)

Perceived enjoyment and concentration (Moon

and Kim 2001)

Continuance intention, satisfaction and

confirmation (Bhattachjee 2001)

2.2. Questionnaire

2.2. Questionnaire

Factor to test corresponding modelExpectation-confirmation model (ECM)

Confirmation, Perceived usefulness, Satisfaction and Continuance Intention

The technology acceptance model (TAM)Perceived usefulness, Perceived ease of use, Attitude and Continuance Intention

Theory of planned behavior (TPB)Continuance Intention, Attitude, Subject norm and Perceived behavior control

Flow experience and user acceptance of e-learning (Flow)Perceived enjoyment and Concentration

2.2. Questionnaire Pilot Test Sample Plan and Data Collection

2.3 Sampling Techniques & Statistical Methods

Research Methodology

Questionnaire development

Pilot Test

Sample Plan & Data Collection

2.3 Sampling Techniques & Statistical Methods

Questionnaire Sent to three academic experts on e-

learning for reviews

Pilot Test Conducted 150 convenient

sampling

Sample Plan & Data Collection Took study samples from 12 class

section Distributed 487 surveys to

individuals who at least took one course offered by the e-learning service

ALL ARE NON-PROBABILITY SAMPLING TECHNIQUES

2.3 Sampling Techniques & Statistical Methods

QUESTIONNAIRE & SAMPLE PLAN

Non-probability

Only select a group of people to do

the sample

Do not require generalization

Convenient accessibility

Rating: “ disagree strongly” or

“agree strongly”

Purposive

2.3 Sampling Techniques & Statistical Methods

PILOT TEST

Non-Probability

Convenience Sampling

Select haphazardly

Cases are easier to obtain

2.3 Sampling Techniques & Statistical Methods

PILOT TEST Cronbach’s alpha set: 0.7

SAMPLE PLAN & DATA COLLECTION Student’s t-test: to test differences

between two means when there are only two samples

ANOVA: the analysis of variance when there are more than two groups

Mean Scores: p>0.05

3. Findings

Used two-step procedure suggested by Anderson

and Gering(1998)

1. Examine the measurement model

2. Examine the structural model

3. Findings

Examine the measurement model

Based on the three criteria suggested by

Fornell and Larcker(1981)

1. All indicator factor loadings (k) should be

significant and exceed 0.5.

2. Construct reliabilities should exceed 0.8.

3. Average variance extracted (AVE) by each

construct should exceed the variance

due to measurement error for the

construct

3. Findings

3. Findings

3. Findings

3. FindingsExamine the structural model

The good fit index, comparative fit index,

normed fit index and relative fit index is

greater than 0.9

Indicates a good model fit

Root mean square error of approximation is

0.05

Indicates the model is acceptable

3. Findings

Interpretation

The research model had an R-square of 80% for

continued intention to use e-learning

An R-square of 65% for satisfaction

65% for attitude toward continued intention

The extended ECM model is capable of

explaining a relatively high proportion of

variation of continued intention to use e-

learning

4. Conclusion

4.1 Limitations4.2 Further Research

4.1 Limitations

1. Short-term study of users’ behavior

Cannot show how the users and the

relationships among variables change over

time2. Independent and dependent

variables from the same respondents

Concerns about common method bias3. Gender distribution was not

symmetric

Gender difference leads to difference in

results findings

4.2 Further Research

Wider Range of Research

Only focus on web-based program

Other ways like TV, CD-ROM are also

kinds of e-learning

Can show different relationships

Gender Distribution

Examine the moderating effect of gender

difference

Considering Other External Factors

the technology or user characteristics

constructs

Understanding more about users’ continuance

intention to use

Q & A