網際網路創造一個突破時間藩籬與空間距離的彈性學習環境，然而線上學習使得學習者容易感到孤獨與疏離，這些負面的經驗可以藉由提高學習者的社會臨場感感知而降低，社會臨場感也被視為是促進社會互動與學習互動的必要因素。隨著學習科技的發展，學習者可以和其他參與者進行非同步與同步溝通，當電腦設備能夠充分傳遞社會線索，學習者就有可能感受到如同傳統教室一樣的社會情境與學習氣氛。由於每位學習者對於社會臨場感的感知不全然相同，為了有效促進網路教室裡的互動，本研究試圖從社會認知理論觀點建構一個社會臨場感量測模式，並且探討社會臨場感與其他構念之間的關係。
本研究發展了一份具有信效度的問卷用以量測所提出來的變數，受測對象為具有實際線上學習經驗的學習者，總共從三所學校收集了535份有效樣本，結構方程模式被用以進行後續的統計分析與假說檢定。結果顯示十一個一階構念可以形成使用者介面、中介溝通、社會臨場感、互動績效以及學習績效等五個二階構念。使用者介面與中介溝通是影響社會臨場感的重要構念，此外，使用者介面對與中介溝通也有正向影響，同時，本研究證實社會臨場感的確能夠有效提升互動績效，而互動績效對於學習績效也有顯著的影響力。最後，本研究分別針對理論與實務意涵進行深入討論，以期對於未來學術研究與教學應用具有實質貢獻。

Internet enables construction of flexible online learning environments without time and distance barriers. However, learners typically experience isolation and alienation in online learning environments. These negative experiences can be reduced by enhancing perceived social presence of learners. With the development of learning technologies, learners can communicate asynchronously and synchronously with other participants. If social cues could be delivered adequately in online classrooms, it may become a real possibility for learners to experience the benefits that are typically only available in the social environment of a traditional classroom. However, the perceived social presence among learners is not the same for everyone. In order to better facilitate the social presence in an online classroom, this study attempted to build a model for measuring social presence and its relationships with other factors in online learning based on the social cognitive theory.
An instrument with sufficient reliability and validity was developed to measure these factors. A formal study was carried out with a paper-based questionnaire for those learners who had previous learning experiences in online learning. A total of 535 valid samples were collected and analyzed from three schools in Taiwan. The method of structural equation modeling was applied to examine the proposed model and test the hypotheses. The results of measurement model testing show that five second-order constructs, user interface, mediated communication, social presence, interaction performance, and learning performance, can be synthesized from eleven first-order constructs. The results of structural model testing show that user interface and mediated communication have significant influences on social presence. User interface also has positive impact on mediated communication. Moreover, this study provided evidence that social presence has significant effects on interaction performance, and then interaction performance has significant effects on learning performance. Finally, the implications of research findings were discussed for further research directions and practical applications.

論文提要 ii
謝誌 iii
摘要 iv
Abstract v
Contents vii
List of Figures ix
List of Tables x
Chapter 1 Introduction 1
1.1 Research Background and Motivations 1
1.2 Research Objectives and Questions 4
1.3 Overview of this Study 5
Chapter 2 Theoretical Background 7
2.1 Social Cognitive Theory 7
2.2 Social Presence 10
2.3 Online Learning Environments 12
2.4 Learner Interaction 15
Chapter 3 Research Methods 19
3.1 Research Framework and Construct Definitions 19
3.2 Research Hypotheses 26
3.3 Participants 30
3.4 Data Analysis Methods 30
3.5 Instrument 31
Chapter 4 Results 42
4.1 Sample Profile 42
4.2 Measurement Model 44
4.3 Structural Model Analysis 62
Chapter 5 Discussion 67
5.1 Implications for Academic Research 67
5.2 Implications for Instructional Practices 69
Chapter 6 Conclusion 75
6.1 Findings 75
6.2 Contributions 77
6.3 Limitations 78
6.4 Future Research 79
References 81
Appendix I: Questionnaire of English Version 92
Appendix II: Questionnaire of Chinese Version 97

Arbaugh, J. B. (2000). Virtual classroom characteristics and student satisfaction with internet-based MBA courses. Journal of Management Education, 24(1), 32-54.
Arbaugh, J. B., & Benbunan-Fich, R. (2007). The importance of participant interaction in online environments. Decision Support Systems, 43(3), 853-865.
Bandura, A. (1965). Influence of model’ s reinforcement contingencies on the acquisition of imitative responses. Journal oi Personality and Social Psychology, 1(6), 589-595.
Bandura, A. (1977). Social learning theory. New York: General Learning Press.
Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, N. J.: Prentice Hall.
Beaudoin, M. F. (2002). Learning or lurking? Tracking the “invisible” online student. The Internet and Higher Education, 5(2), 147-155.
Beldarrain, Y. (2006). Distance education trends: Integrating new technologies to foster student interaction and collaboration. Distance Education, 27(2), 139-154.
Biocca, F., Harms, C., & Burgoon, J. K. (2003). Toward a more robust theory and measure of social presence: Review and suggested criteria. Presence: Teleoperators & Virtual Environments, 12(5), 456-480.
Bolliger, D. U., & Martindale, T. (2004). Key factors for determining student satisfaction in online courses. International Journal on E-Learning, 3(1), 61-67.
Brandon, D. P., & Hollingshead, A. B. (1999). Collaborative learning and computer-supported groups. Communication Education, 48(2), 109-126.
Brewer, K. R., & Wann, D. L. (1998). Observational learning effectiveness as a function of model characteristics: investigating the importance of social power. Social Behavior and Personality, 26(1), 1-10.
Burgoon, J. K., Buller, D. B., Hale, J. L., & deTurck, M. A. (1984). Relational messages associated with nonverbal behaviors. Human Communication Research, 10(3), 351-378.
Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56(2), 81-105.
Chang, H. H., & Wang, I. C. (2008). An investigation of user communication behavior in computer mediated environments. Computers in Human Behavior, 24(5), 2336-2356.
Chen, G., & Chiu, M. M. (2008). Online discussion processes: Effects of earlier messages' evaluations, knowledge content, social cues and personal information on later messages. Computers & Education, 50(3), 678-692.
Chen, N. S., Ko, H. C., & Lin, T. (2005). A model for synchronous learning using the Internet. Innovations in Education and Teaching International, 42(2), 181-194.
Chen, N. S., Wei, C. W., Kinshuk, & Chen, Y. R. (2008). Classroom climate and learning effectiveness in holistic blended learning environments. International Journal on Digital Learning Technology, 1(1), 72-94.
Chen, Y. J. (2001). Transactional distance in World Wide Web learning environments. Innovations in Education and Training International, 38(4), 327-338.
Cho, Y. S., & Proctor, R. W. (2001). Effect of an initiating action on the up-right/down-left advantage for vertically arrayed stimuli and horizontally arrayed responses. Journal of Experimental Psychology: Human Perception and Performance, 27(2), 472-484.
Churchill, G. A. (1979). A paradigm for developing better measures of marketing constructs. Journal of Marketing Research, 16(1), 64-73.
Costa, P. T., & McCrae, R. R. (1992). Revised NEO Personality Inventory (NEO-PI-R) and NEO Five-Factor Inventory (NEO-FFI) manual. Odessa, FL: Psychological Assessment Resources.
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297-334.
Daft, R. L., & Lengel, R. H. (1984). Information richness: A new approach to managerial behavior and organizational design. In L. L. Cummings & B. M. Staw (Eds.), Research in organizational behavior (Vol. 6, pp. 191-233). Homewood, IL: JAI Press.
Daft, R. L., & Lengel, R. H. (1986). ORGANIZATIONAL INFORMATION REQUIREMENTS, MEDIA RICHNESS AND STRUCTURAL DESIGN. Management Science, 32(5), 554-571.
Dennis, A. R., Fuller, R. M., & Valacich, J. S. (2008). Media, tasks, and communication processes: A theory of media synchronicity. Mis Quarterly, 32(3), 575-600.
Diamantopoulos, A., Siguaw, J. A., & Strasse, B. (2006). Formative versus reflective indicators in organizational measure development: A comparison and empirical illustration. British Journal of Management, 17(4), 263-282.
Dinev, T., & Hart, P. (2004). Internet privacy concerns and their antecedents - measurement validity and a regression model. Behaviour & Information Technology, 23(6), 413-422.
Draffan, E. A., & Rainger, P. (2006). A model for the identification of challenges to blended learning. ALT-J, 14(1), 55-67.
Entwistle, N., & Waterston, S. (1988). Approaches to studying and levels of processing in university students. British Journal of Educational Psychology, 58(3), 258-265.
Ferry, D. L., Kydd, C. T., & Sawyer, J. E. (2001). Measuring facts of media richness. Journal of Computer Information Systems, 41(4), 69-78.
Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18(3), 382-388.
Garramone, G. M., Harris, A. C., & Anderson, R. (1986). Uses of political computer bulletin boards. Journal of Broadcasting & Electronic Media, 30(3), 325-339.
Garrison, D. R., Anderson, T., & Archer, W. (2001). Critical thinking, cognitive presence, and computer conferencing in distance education. American Journal of Distance Education, 15(1), 7-23.
Garrison, D. R., & Kanuka, H. (2004). Blended learning: Uncovering its transformative potential in higher education. The Internet and Higher Education, 7(2), 95-105.
Goffman, E. (1959). The presentation of self in everyday life. Garden City, NY: Anchor.
Graham, C. R. (2004). Blended learning systems: Definition, current trends, and future directions. In C. J. Bonk & C. R. Graham (Eds.), Handbook of Blended Learning: Global Perspectives, Local Designs (pp. 3-12). San Francisco, CA: Pfeiffer Publishing.
Gunawardena, C. N. (1995). Social presence theory and implications for interaction and collaborative learning in computer conferences. International Journal of Educational Telecommunications, 1(2/3), 147-166.
Gunawardena, C. N., & Zittle, F. J. (1997). Social Presence as a Predictor of Satisfaction within a Computer-Mediated Conferencing Environment. American Journal of Distance Education, 11(3), 8-26.
Hair, J. F., Black, W. C., Babin, B., Anderson, R., & Tatham, R. (2006). Multivariate data analysis (6 ed.). Upper Saddle River, NJ: Prentice Hall.
Hample, D., & Dallinger, J. M. (1995). A Lewinian Perspective on Taking Conflict Personally: Revision, Refinement, and Validation of the Instrument. Communication Quarterly, 43(3), 297-319.
Heath, R. L., & Bryant, J. (1992). Human communication theory and research: Concepts, contexts, and challenges. In J. Bryant (Ed.), Communication textbook series: General communication theory and methodology (pp. 1-337). Hillsdale, NJ: Erlbaum.
Hillman, D. C. A., Willis, D. J., & Gunawardena, C. N. (1994). Learner-interface interaction in distance education: An extension of contemporary models and strategies for practitioners. The American Journal of Distance Education, 8(2), 30-42.
Homer, B. D., Plass, J. L., & Blake, L. (2008). The effects of video on cognitive load and social presence in multimedia-learning. Computers in Human Behavior, 24(3), 786-797.
Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1-55.
Hu, R., & Wang, S. (2008). Online learning environments. In L. A. Tomei (Ed.), Encyclopedia of information technology curriculum integration (pp. 678-685). Hershey PA: Information Science Reference.
Johansen, R., Vallee, J., & Spangler, K. (1988). Teleconferencing: Electronic group communication. In R. S. Cathcart & L. A. Samover (Eds.), Small group communication: A reader (5 ed., pp. 140–154). Menlo Park, CA: Institute for the Future.
Johnson, S. D., Aragon, S. R., Shaik, N., & Palma-Rivas, N. (2000). Comparative analysis of learner satisfaction and learning outcomes in online and face-to-face learning environments. Journal of Interactive Learning Research, 11(1), 29-50.
Jung, I., Choi, S., Lim, C., & Leem, J. (2002). Effects of different types of interaction on learning achievement, satisfaction and participation in Web-based instruction. Innovations in Education and Teaching International, 39(2), 153-162.
Kerlinger, F. N., & Lee, H. B. (2000). Foundations of behavioral research (4 ed.). Belmont, CA,: Thomson Learning.
Kline, R. B. (2005). Principles and practice of structural equation modeling (2 ed.). NY: The Guilford Press.
Knoll, A. (2007). Guest editor's introduction: Toward high-definition telepresence. Presence-Teleoperators and Virtual Environments, 16(5), I-III.
Knowles, M. S. (1970). The modern practice of adult education. NY: Association Press.
Kreijns, K., Kirschner, P. A., & Jochems, W. (2003). Identifying the pitfalls for social interaction in computer-supported collaborative learning environments: a review of the research. Computers in Human Behavior, 19(3), 335-353.
Kreijns, K., Kirschner, P. A., Jochems, W., & Van Buuren, H. (2004). Measuring perceived quality of social space in distributed learning groups. Computers in Human Behavior, 20(5), 607-632.
Mendlowicz, M. V., & Stein, M. B. (2000). Quality of life in individuals with anxiety disorders. American Journal of Psychiatry, 157(5), 669-682.
Montanelli, R. G., & Humphreys, L. G. (1976). Latent roots of random data correlation matrices with squared multiple correlations on the diagonal: A Monte Carlo study. Psychometrika, 41(3), 341-348.
Moore, M. G. (1989). Three types of interaction. The American Journal of Distance Education, 3(2), 1-6.
Moore, M. G., & Kearsley, G. (1996). Distance education: A systems view. Belmont, CA: Wadsworth Publishing Company.
Morgan, C. K., & Tam, M. (1999). Unravelling the Complexities of Distance Education Student Attrition. Distance Education, 20(1), 96-108.
Nielsen, J. (1999). Designing web usability: The practice of simplicity. Thousand Oaks, CA: New Riders Publishing.
Nowak, K. L., Watt, J., & Walther, J. B. (2009). Computer mediated teamwork and the efficiency framework: Exploring the influence of synchrony and cues on media satisfaction and outcome success. Computers in Human Behavior, 25(5), 1108-1119.
Offir, B., & Lev, J. (2000). Constructing an aid for evaluating teacher-learner interaction in distance learning. Educational Media International, 37(2), 91-97.
Offir, B., & Lev, Y. (1999). Teacher-learner interaction in the process of operating DL (distance learning) systems. Educational Media International, 36(2), 132-136.
Offir, B., Lev, Y., & Bezalel, R. (2008). Surface and deep learning processes in distance education: Synchronous versus asynchronous systems. Computers & Education, 51(3), 1172-1183.
Oliver, R., & McLoughlin, C. (1996). An investigation of the nature and form of interactions in live interactive television.
Ormrod, J. E. (2007). Human learning (5 ed.). Upper Saddle River, NJ: Prentice Hall.
Otondo, R. F., Van Scotte, J. R., Allen, D. G., & Palvia, P. (2008). The complexity of richness: Media, message, and communication outcomes. Information & Management, 45(1), 21-30.
Paas, F., Vanmerrienboer, J. J. G., & Adam, J. J. (1994). Measurement of cognitive load in instructional-research. Perceptual and Motor Skills, 79(1), 419-430.
Palmer, M. (1995). Interpersonal communication and virtual reality: Mediating interpersonal relationships. In F. Biocca & M. Levy (Eds.), Communication in the age of virtual reality (pp. 277-299). Mahwah, NJ: Lawrence Erlbaum Associates.
Raykov, T. (1997). Estimation of composite reliability for congeneric measures. Applied Psychological Measurement, 21(2), 173-184.
Richardson, J. C., & Swan, K. (2003). Examining social presence in online courses in relation to students’ perceived learning and satisfaction. Journal of Asynchronous Learning Networks, 7(1), 68-88.
Rifkind, L. J. (1992). Immediacy as a predictor of teacher effectiveness in the instructional television classroom. Journal of Interactive Television, 1(1), 31-38.
Rourke, L., & Anderson, T. (2002). Exploring social communication in asynchronous, text-based computer conferencing. Journal of Interactive Learning Research, 13(3), 259-275.
Rourke, L., Anderson, T., Garrison, D. R., & Archer, W. (1999). Assessing social presence in asynchronous text-based computer conferencing. Journal of Distance Education, 14(2), 50-71.
Rovai, A. P. (2001). Building classroom community at a distance: A case study. Etr&D-Educational Technology Research and Development, 49(4), 33-48.
Rovai, A. P. (2007). Facilitating online discussions effectively. The Internet and Higher Education, 10(1), 77-88.
Rumble, G. (1986). The planning and management of distance education. New York.: St Martins Press.
Short, J., Williams, E., & Christie, B. (1976). The social psychology of telecommunications. London: John Wiley & Sons.
Sternberg, R. J. (1997). Construct validation of a triangular love scale. European Journal of Social Psychology, 27(3), 313-335.
Summers, J. J., Waigandt, A., & Whittaker, T. A. (2005). A comparison of student achievement and satisfaction in an online versus a traditional face-to-face statistics class. Innovative Higher Education, 29(3), 233-250.
Sun, P. C., Tsai, R. J., Finger, G., Chen, Y. Y., & Yeh, D. (2008). What drives a successful e-Learning? An empirical investigation of the critical factors influencing learner satisfaction. Computers & Education, 50(4), 1183-1202.
Taylor, J. C. (1998). Flexible delivery: The globalisation of lifelong learning. Indian Journal of Open Learning, 7(1), 55-65.
Thurlow, C., Lengel, L. B., & Tomic, A. (2004). Computer mediated communication: Social interaction and the Internet. London: Sage.
Tu, C. H. (2000). On-line learning migration: from social learning theory to social presence theory in a CMC environment. Journal of Network and Computer Applications, 23(1), 27-37.
Tu, C. H. (2002a). The measurement of social presence in an online learning environment. International Journal on E-Learning, 1(2), 34-45.
Tu, C. H. (2002b). The relationship between social presence and online privacy. The Internet and Higher Education, 5(4), 293-318.
Tu, C. H., & McIsaac, M. S. (2002). The relationship of social presence and interaction in online classes. The American Journal of Distance Education, 16(3), 131-150.
Tung, F. W., & Deng, Y. S. (2006). Designing social presence in e-learning environments: Testing the effect of interactivity on children. Interactive Learning Environments, 14(3), 251-264.
Van Gog, T., Paas, F., Marcus, N., Ayres, P., & Sweller, J. (2009). The Mirror Neuron System and Observational Learning: Implications for the Effectiveness of Dynamic Visualizations. Educational Psychology Review, 21(1), 21-30.
Vrasidas, C., & McIsaac, M. S. (1999). Factors influencing interaction in an online course. American Journal of Distance Education, 13(3), 22-36.
Wang, Y. S. (2003). Assessment of learner satisfaction with asynchronous electronic learning systems. Information & Management, 41(1), 75-86.
Watkins, D. (1983). Depth of processing and the quality of learning outcomes. Instructional Science, 12(1), 49-58.
West, S. G., Finch, J. F., & Curran, P. J. (1995). Structural equation modeling with nonnormal variables: Problems and remedies. In R. H. Hoyle (Ed.), Structural equation modeling: Concepts, issues, and applications (pp. 56–75). Thousand Oaks, CA: Sage Publications.
Woo, Y., & Reeves, T. C. (2007). Meaningful interaction in web-based learning: A social constructivist interpretation. The Internet and Higher Education, 10(1), 15-25.
Zhang, Q., & Oetzel, J. G. (2006). Constructing and validating a teacher immediacy scale: A Chinese perspective. Communication Education, 55(2), 218-241.
Zhao, S. Y. (2003). Toward a taxonomy of copresence. Presence-Teleoperators and Virtual Environments, 12(5), 445-455.
Zmud, R. W., Lind, M. R., & Young, F. W. (1990). An attribute space for organizational communication channels. Information Systems Research, 1(4), 440-457.