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ISEM 3120 Seminar in ISEM 2014-2015 Semester
Chuk Cheuk Ka Lau Ming Sze Ng Ka Fan Tsoi Chak Fei Wan Chun Kit Wong Tsun Lam
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Content Introduction Research Method Findings Conclusion
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1. Introduction 1.1 Background 1.2 Definitions & Concept 1.3 Objective 1.4 Rationale
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1.1 Background Research case:
Explaining and predicting users’ continuance intention toward e-learning: An extension of the expectation–confirmation model
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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,
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1.2 Definitions & Concepts
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
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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.
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1.3 Objective
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1.4 Rationale
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1.4 Rationale Problems 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
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2. Research Model 2.1 Model 2.2 Questionnaire 2.3 Sampling Techniques & Statistical Method
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2.1 Model Research model and hypotheses based on
Expectation–confirmation model (ECM) Technology acceptance model (TAM) Theory of planned behavior Flow theory
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2.1 Model
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2.1 Model Expectation–confirmation model (ECM)
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2.1 Model Technology acceptance model (TAM) Two particular belief
Perceived usefulness perceived ease of use
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2.1 Model Theory of planned behavior
Based on theory of reasoned action(TRA) Behavioral attitude and subjective norm affect behavioral intention and actual behavior
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2.1 Model Flow theory Three constructs Perceived Enjoyment
Perceived Control Concentration Perceived control is similar to the perceived behavioral control in TPB
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2.2. Questionnaire 1. Construct in research model
Seven-point Likert scale 2. Demographic questions about participants
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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)
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2.2. Questionnaire
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2.2. Questionnaire Factor to test corresponding model
Expectation-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
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2.2. Questionnaire Pilot Test Sample Plan and Data Collection
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2.3 Sampling Techniques & Statistical Methods
Research Methodology Questionnaire development Pilot Test Sample Plan & Data Collection
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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
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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
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2.3 Sampling Techniques & Statistical Methods
PILOT TEST Non-Probability Convenience Sampling Select haphazardly Cases are easier to obtain
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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
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3. Findings Used two-step procedure suggested by Anderson and Gering(1998) Examine the measurement model Examine the structural model
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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
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3. Findings
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3. Findings
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3. Findings
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3. Findings Examine 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
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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
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4. Conclusion 4.1 Limitations 4.2 Further Research
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4.1 Limitations 1. Short-term study of users’ behavior
Cannot show how the users and the relationships among variables change over time 2. Independent and dependent variables from the same respondents Concerns about common method bias 3. Gender distribution was not symmetric Gender difference leads to difference in results findings
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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
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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
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Q & A
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