1. Assessing learners’ knowledge construction model in an e-learning environment 指導教授 : 陳 明 溥 研 究 生 : 許 良 村 Huang, H.M., & Liaw, S.S.(2004). Assessing learners ’ knowledge construction model in an e-learning environment. November 30- December, 3, ICCE2004, Melbourne, Australia. (NSC92-2520-S- 025-001).

2. Introduction  The current study develops and examines a conceptual model of learners’ perceptions toward online learning as a tool for knowledge construction.  The model explores learners’ knowledge construction toward a E-learning environment that integrated individual experience, teacher factor, multimedia factor, and courseware tools to develop a new aspect of individual attitudes toward problem- solving abilities and knowledge construction.  This study will help us gain an understanding on how learners’experience and perceptions affect the construction of individual knowledge.  Moreover, this study will also provide stronger predictive arguments regarding the observed relationships.

3. Introduction  The model explores learners’ knowledge construction toward a E-learning environment that integrated individual experience, teacher factor, multimedia factor, and courseware tools to develop a new aspect of individual attitudes toward problem-solving abilities and knowledge construction.  This study will help us gain an understanding on how learners’experience and perceptions affect the construction of individual knowledge.  Moreover, this study will also provide stronger predictive arguments regarding the observed relationships.

4. Theoretical model (Variables)  hours spending weekly  computer skills in web browser  computer skills in web design  courseware tools  multimedia factor  teacher factor  problem solving abilities  knowledge construction

5. Research hypotheses  H1-1. The more individual experience in computing a learner has, the more a learner will like the online course represented via teacher video  H1-2. The more individual experience in computing a learner has, the more a learner will like the online course represented via multimedia input  H1-3. The more individual experience in computing a learner has, the more a learner will like the course materials management via courseware tools.  H2-1. The more computer skills a learner has, the more a learner will like the online course represented via teacher input  H2-2. The more computer skills a learner has, the more a learner will like the online course represented via multimedia input.

6. Research hypotheses  H2-3. The more computer skills a learner has, the more a learner will like the online course manage- ment via courseware tools.  H3. The more course materials represented via teacher video input, the more problem-solving abilities of the learners will have.  H4. The more course materials represented via multimedia input, the more problem-solving abilities of the learners will have.  H5. The more course materials represented via courseware tools, the more problem-solving abilities of the learners will have.  H6. The more problem-solving abilities of a learner have, the more abilities of the learner ’ knowledge construction will have.

7. Hours spending weekly Computer skills in Web browser Computer skills in Web design Courseware Tools Hours spending weekly Teacher video input Multimedia input Hours spending weekly Learner ’ s variables Course represent Learner ’ s abilities H1 Hypotheses 1 Hypotheses 1

8. Hours spending weekly Computer skills in Web browser Computer skills in Web design Courseware Tools Hours spending weekly Teacher video input Multimedia input Hours spending weekly Learner ’ s variables Course represent Learner ’ s abilities H2 Hypotheses 2 Hypotheses 2

9. Hours spending weekly Computer skills in Web browser Computer skills in Web design Courseware Tools Hours spending weekly Teacher video input Multimedia input Hours spending weekly Learner ’ s variables Course represent Learner ’ s abilities H5 H4 H3 Hypotheses 3,4,5

10. Hours spending weekly Computer skills in Web browser Computer skills in Web design Courseware Tools Hours spending weekly Teacher video input Multimedia input Hours spending weekly Learner ’ s variables Course represent Learner ’ s abilities H6 Hypotheses 6 Hypotheses 6

11. Experimental methodology  main purposes : - relationships between learners ’ variables and course representations with and learning from the hypermedia Web-based learning environment - relationships between learners ’ variables and course representations with and learning from the hypermedia Web-based learning environment - relationships between course representations and the learners ’ abilities on problem solving and knowledge construction - relationships between course representations and the learners ’ abilities on problem solving and knowledge construction  the subject : - a total of 200 medical students in central Taiwan took part in this study. - a total of 200 medical students in central Taiwan took part in this study. - the sample comprises of 80 males and 91 female students who responded to the questionnaire. - the sample comprises of 80 males and 91 female students who responded to the questionnaire.

12. The Means and standard deviations of students’ perceptions toward knowledge construction

14. Correlation analysis

15. Result and discsusion  1st regression analysis (courseware tools) : - independent variables (computer skills in Web browser, e-mail access, word processing, and computer skills in Web design; individual experience in computer use, taken Web-based courses, hours spent weekly) - independent variables (computer skills in Web browser, e-mail access, word processing, and computer skills in Web design; individual experience in computer use, taken Web-based courses, hours spent weekly) - The results that presented computer skills in Web design, Web browser and hours spent on the system weekly were three predictors of courseware tools - The results that presented computer skills in Web design, Web browser and hours spent on the system weekly were three predictors of courseware tools

16. Hours spending weekly Computer skills in Web browser Computer skills in Web design Courseware Tools Hours spending weekly Teacher video input Multimedia input Hours spending weekly Learner ’ s variables Course represent.22**.19*.31* Learner ’ s abilities

17.  2nd regression analysis (teacher video input): - independent variables (computer skills and individual experience) - independent variables (computer skills and individual experience) -The result that presented only “ours spent weekly” was a predictor of teacher input -The result that presented only “ours spent weekly” was a predictor of teacher input Result and discussion

18. Hours spending weekly Computer skills in Web browser Computer skills in Web design Courseware Tools Hours spending weekly Teacher video input Multimedia input Hours spending weekly Learner ’ s variables Course represent.18* Learner ’ s abilities

19. Result and discussion 3rd regression analysis (multimedia input): - independent variables (computer skills and individual experience) - independent variables (computer skills and individual experience) -The result that web browser skill is the only predictor of multimedia input -The result that web browser skill is the only predictor of multimedia input

20. Hours spending weekly Computer skills in Web browser Computer skills in Web design Courseware Tools Hours spending weekly Teacher video input Multimedia input Hours spending weekly Learner ’ s variables Course represent.19* Learner ’ s abilities

21. Result and discussion 4th regression analysis (problem-solving abilities): - independent variables (courseware tools, multimedia input, teacher video input and knowledge construction ) - independent variables (courseware tools, multimedia input, teacher video input and knowledge construction ) - The result that presented effects of courseware tools, multimedia input, teacher video input and knowledge construction were all predictors of problem-solving abilities. - The result that presented effects of courseware tools, multimedia input, teacher video input and knowledge construction were all predictors of problem-solving abilities.

22. Hours spending weekly Computer skills in Web browser Computer skills in Web design Courseware Tools Hours spending weekly Teacher video input Multimedia input Hours spending weekly Learner ’ s variables Course represent.15**.33**.29** Learner ’ s abilities

23. Result and discussion 5th regression analysis (knowledge construction): - independent variables (problem-solving abilities) - independent variables (problem-solving abilities) - The result indicates that problem-solving abilities can predict of knowledge construction. - The result indicates that problem-solving abilities can predict of knowledge construction.

24. Hours spending weekly Computer skills in Web browser Computer skills in Web design Courseware Tools Hours spending weekly Teacher video input Multimedia input Hours spending weekly Learner ’ s variables Course represent.67** Learner ’ s abilities

25. The results of regression analyses. (*p<.05; **p<.01)

26. Conclusion  in this study and yielded four factors - courseware tools, multimedia factor, teacher factor and problem solving abilities.  computer skills in Web browser and Web design are the key predictors  teacher video input, multimedia input and courseware tools can predict learners ’ abilities on problem solving.  learners will have more abilities on problem solving; then, they can construct more knowledge by themselves in the Web-based learning environment.