1. The Effect of Student Interactions and Internet Self-Efficacy on Satisfaction in Two Synchronous Interwise Course Sessions Yu-Chun Kuo Yu-Tung Kuo Andrew Walker

2. Purpose An examination of the relationships between predictors (learner-learner interaction, learner-instructor interaction, and Internet self-efficacy) and student satisfaction

3. Literature Review Interaction  Learner-learner interaction  Learner-instructor interaction Internet self-efficacy  the belief in one’s capability to organize and execute courses of Internet actions required to produce given attainments

4. Course Implementation 2 weeks of online sessions & 14 weeks of traditional face-to- face sessions online synchronous sessions: Interwise technology tools Interwise: A Web conferencing tool that provides individuals the opportunities of real-time communications by voice and graphics over the Internet (Academic Technology Center, 2006).

5. Sample Course: Introduction to Transportation Technology, Department of Industrial Technology Education (ITE), National Taiwan Normal University The return rate: 88%.

6. Measurement A questionnaire: four major sections (student basic information, student perceptions of two types of interactions, Internet self- efficacy and student satisfaction) Interaction & satisfaction: A 5–point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree) Internet self-efficacy scale: A 7-point scale that ranged from 1 (very unlikely) to 7 (very likely)

7. Data Collection and Analysis Paper-based and electronic surveys SPSS

8. Descriptive Information Interactions & SatisfactionMeanStd. Deviation α learner-learner interaction (7 items)3.040.74 0.852 learner-instructor interaction (8 items) 3.350.67 0.859 Internet self-efficacy (8 items)4.660.82 0.860 Satisfaction (5 items)3.270.80 0.898

9. Correlation analyses learner- learner learner- instructor Internet self- efficacysatisfaction learner-learner －.462**.160.559** learner-instructor －.523**.747** Internet self-efficacy －.398** satisfaction －

10. Regression analyses Variables BSE BβtpToleranceVIF (Constant) -.220.455 -.483.631 learner-learner.298.104.2762.869.006**.7771.287 learner-instructor.715.133.5985.361.000***.5801.725 Internet self- efficacy.040.098.041.414.681.7181.392

11. Conclusions Learner-learner and learner-instructor interactions are both good predictors of student satisfaction Learner-instructor interaction was found to be the strongest predictor in this study, compared to learner-learner interaction