learners’ final achievement in the IBL condition. Similarly, in the IBLSE category, Bolman et al. (2007) also revealed a positive relationship between learners’ IBLSE and their IBL outcomes. Furthermore, it was noted that when attempting to take measures probing learners’ perceptions of self-efficacy, a significant amount of research (e.g. Chiou & Wan, 2007; Joo, Bong, & Choi, 2000; Thompson, Meriac, & Cope, 2002) has adopted search tasks to predict students’ learning outcomes in the Internet-based setting because search tasks may still be considered as the most commonly implemented IBL activities. Nevertheless, in contrast to Moos and Azevedo’s (2009) findings concerning CSE, no relevant research in this review was found on the relationship between individuals’ perceived self-efficacy in the Internet-based setting and their navigational paths. More research may be needed to investigate on the relationship. Finally, some methodological issues may be worthy of notice. First, it seems that all of the Internet-related research concerning self-efficacy is based on questionnaires or surveys for measuring self-efficacy. Researchers should find other ways of assessing students’ Internet-related self-efficacy, such as interviews or observation. Most of the studies in this review employed a quantitative approach; qualitative or mixed research approaches are recommended for future research. In addition, among the 46 papers reviewed, 35 studies used university students as their samples. In other words, most of the participants invited to take part in the related studies were either undergraduates or graduate students in universities. It may be necessary to encourage learners with various kinds of demographic backgrounds to take part in the relevant research. Meanwhile, among the reviewed papers, 19 studies in America, 22 studies in Asia, and 5 studies in Europe were reported. Relevant research based on European samples is relatively rare. Finally, within all of the reviewed studies, only students’ or employees’ perceptions were probed; it may be interesting to investigate instructors’ perceptions of Internet-related self-efficacy. Future study Because the papers selected for the current review were limited to those included in the SSCI database, other relevant research regarding self-efficacy may still be found to outline a more comprehensive review. Future studies can explore the differences between students’ perceptions about CBL and IBL as well as compare students’ CSE and ISE, simultaneously, in order to further examine the relationship between CSE and ISE. Secondly, researchers can further examine the construct of three categories of self-efficacy in IBL by assessing the significance and power of using ISE, ASE and IBLSE to predict students’ IBL performances or outcomes. This could help researchers and educators realize more about the relationships among the three variables and learning outcomes in IBL environments. Thirdly, future studies can examine the relationship between students’ perceived self-efficacy and their learning behaviors in specific Internet-based learning context such as the online search tasks mentioned above. Finally, more qualitative methods are suggested for future Internet-related self-efficacy assessments. Acknowledgement Funding for this research work is supported by the National Science Council, Taiwan, under grant numbers NSC 99- 2511-S-011-005-MY3 and 100-2631-S-011-001. References (papers with * are those selected for current review) *Artino, A. R. (2008). Motivational beliefs and perceptions of instructional quality: Predicting satisfaction with online training. Journal of Computer Assisted Learning, 24, 260-270. Abdous, M., & Yoshimura, M. (2010). Learner outcomes and satisfaction: A comparison of live video-streamed instruction, satellite broadcast instruction, and face-to-face instruction. Computers & Education, 55, 733-741. Bandura, A. (1982). Self-efficacy mechanism in human agency. American Psychologist, 37, 122–<strong>14</strong>7. Bandura, A. (1986). Social foundations of thought and action. Englewood Cliffs, NJ. Prentice Hall. Bandura, A. (1994). Self-efficacy. In V. S. Ramachaudran (Ed.), Encyclopedia of human behavior (Vol. 4, pp. 71–81). New York: Academic Press. 237
Bandura, A. (1997). Self-efficacy: The exercise of control. New York: W.H. Freeman and Company. *Bates, R., & Khasawneh, S. (2007). Self-efficacy and college students’ perceptions and use of online learning systems. Computers in Human Behavior, 23, 175-191. Bernard, R. M., Abrami, P. C., Lou, Y., Borokhovski, E., Wade, A., Wozney, L., Wallet, P.A., Fiset, M., & Huang, B. (2004). How does distance education compare with classroom instruction? A meta-analysis of the empirical literature. Review of <strong>Educational</strong> Research, 74, 379–439. *Bolman, C., Tattersall, W., Waterink, J., Janssen, B., van der Berg, R., van Es, R., & Koper, R. (2007). Learners' evaluation of a navigation support tool in distance education. Journal of Computer Assisted Learning, 23, 384-392. *Brown, S. W., Boyer, M. A., Mayall, H. J., Johnson, P. R., Meng, L., Butler, M. J., Weir, K., Florea, N., Hernandez, M. & Reis, S. (2003). The GlobalEd project: gender differences in a problem-based learning environment of international negotiations. Instructional Science, 34, 255–276. Caprara, G. V., Fida, R., Vecchione, M., Del Bove, G., Vecchio, G. M., Barbaranelli, C., & Bandura, A. (2008). Longitudinal analysis of the role of perceived efficacy for self-regulated learning in academic continuance and achievement. Journal of <strong>Educational</strong> Psychology, 100, 525-534. *Chang, S.C., & Tung, F. C. (2008). An empirical investigation of students’ behavioural intentions to use the online learning course websites. British Journal of <strong>Educational</strong> <strong>Technology</strong>, 39, 71-83. *Chiou, W.-B. & Wan, C.-S. (2007). The dynamic change of self-efficacy in information searching on the Internet: Influence of valence of experience and prior self-efficacy. The Journal of Psychology, <strong>14</strong>1, 589–603. *Choi, D. H., Kim, J., & Kim, S. H. (2006). ERP training with a web-based electronic learning system: The flow theory perspective. International Journal of Human-Computer Studies, 65, 223-243. *Chu, R. J.-C., & Tsai, C.-C. (2009). Self-directed learning readiness, Internet self-efficacy and preferences towards constructivist Internet-based learning environments among higher-aged adults. Journal of Computer Assisted Learning, 25, 489–501. Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: development of a measure and initial test. MIS Quarterly, 19, 189–211. *Crippen K. J. & Earl, B. L., (2007). The impact of Web-based worked examples and self-explanation on performance, problem solving, and self-efficacy. Computers & Education, 49, 809-821. Delialioglu, O., & Yildirim, Z. (2008). Design and development of a technology enhanced hybrid instruction based on MOLTA model: its effectiveness in comparison to traditional instruction. Computers & Education, 51, 474–483. Eastin, M. A., & LaRose, R. L. (2000). Internet self-efficacy and the psychology of the digital divide. Journal of Computer Mediated Communication, 6. Available at: http://jcmc.indiana.edu/vol6/issue1/eastin.html (<strong>October</strong> 23, 2010) *Farel, A,, Umble, K., & Polhamus, B. (2001). Impact of an online analytic skills course. Evaluation & the Health Professions, 24, 446–459. *Francescato, D., Mebane, M.E., Porcelli, R., Attanasio C., & Pulino M. (2007). Developing professional skills and social capital through computer supported collaborative learning in university contexts. International Journal of Human-Computer Studies, 65, <strong>14</strong>0-152. *Francescato, D., Porcelli, R., Mebane, M., Cudetta, M., Klobas, J., & Renzi, P. (2006). Evaluation of the efficacy of collaborative learning in face to face and computer supported university contexts. Computers in Human Behavior, 22, 163-176. Girasoli, A. J., & Hannafin, R. D. (2008). Using asynchronous AV communication tools to increase academic self-efficacy. Computers & Education, 51, 1676-1682. Guan, Y.-H., Tsai, C.-C., & Hwang, F.-K. (2006). Content analysis of online discussion on a senior-high-school discussion forum of a virtual physics laboratory. Instructional Science, 34, 279-311. Hoffman, B., & Spatariu, A. (2008). The influence of self-efficacy and metacognitive prompting on math problem-solving efficiency. Contemporary <strong>Educational</strong> Psychology, 33, 875-893. *Hong, T. (2006). The Internet and tobacco cessation: The roles of Internet self-efficacy and search task on the informationseeking process. Journal of Computer-Mediated Communication, 11, 536–556. *Johnson, R. D., Hornik, S. & Salas, E. (2008). An empirical examination of factors contributing to the creation of successful elearning environments. International Journal of Human-Computer Studies, 66, 356–369. *Joo, Y., Bong, M., & Choi, H.-J. (2000). Self-efficacy for self-regulated learning, academic self-efficacy, and Internet selfefficacy in Web-based instruction. <strong>Educational</strong> <strong>Technology</strong> Research and Development, 48, 5–17. Katz, J. E., & Aspeden, P. (1996, <strong>October</strong>). Motivations for and barriers to Internet usage: Results of a national public opinion survey. Paper presented at the 24 th Annual Telecommunications Policy Research Conference, Solomons , MD . 238
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October 2011 Volume 14 Number 4
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Supporting Organizations Centre for
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Time-Quality Tradeoff of Waiting St
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Ibáñez, M. B., García, J. J., Ga
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Situated learning. It states that k
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executed in the client, the server
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The participants were twelve non-na
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Huang, H. M., Rauch, U., & Liaw, S.
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Theoretical background Feedback, is
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There are already a number of tools
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output used were blogs, written by
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Question Table 2: Perceived Relevan
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Black, P., & Wiliam, D. (2009). Dev
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detection, and analysis of affectiv
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experience is a suitable method of
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Collins, 1998). The appraisal theor
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encompasses the finer shades of an
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and can also track faces with glass
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Acknowledgements This research was
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Merill, D. C., Reiser, B. J., Traft
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to the above-discussed issues of th
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The annotation part of the SDM onto
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that enables the office users to ac
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Figure 4. Semantic document browser
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to the group’s shared semantic do
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participants performed less mouse c
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Bastili, V.R., Gianluigi, C., & Rom
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esource contribution, enabling conv
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Semantic Search In contrast to the
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Participation: P i i i NiVadd Vde
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and comment on each page as well. T
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Table 1. Questionnaire results (N=2
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propose for him, as well as calenda
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Discussion and Conclusion Collabora
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Sampson, D. G., & Zervas, P. (2011)
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Obtaining: the first step of the li
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process (Palmer & Richardson, 2004)
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and ratings (the use of star rating
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(K1) is the number of non-reusable
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Case 3: The process of reusing a se
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Washizaki, H., Yamamoto, Y. & Fukaz
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to examine determinants for pre-ser
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Overview of the model The first res
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significance of relationships. All
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Discussion This study represents a
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Davis, F., Bagozzi, R., & Warshaw,
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Ko, C.-C., Chiang, C.-H., Lin, Y.-L
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Interestingly, the Universal Design
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Figure 1. Framework of the TriAcces
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Experiment This experiment aimed to
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Table 2. Descriptive statistics for
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Foulds, R., & Camacho, C. (2003). T
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answer. However, students can choos
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Hartley & Collins-Brown, 1999; Morl
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Subjects Figure 4. Partial misconce
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correct for a four-option MC item i
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from −3 to 3 for any four-option
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Kansup, W. (1973). A comparison of
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The theory of mental models explain
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computer-mediated counter-arguments
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Learning in this study refers to, w
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the experiment process was anonymou
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supported. However, significant dif
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Cannon-Bowers, J. A., Salas, E., &
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Lee, Y.-H., Hsieh, Y.-C., & Hsu, C.
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Many researchers have conducted emp
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Trialability Some studies have empi
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Results Instrument validation Two c
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In this study, Amos 6.0 was employe
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Our results strongly supported the
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Fornell, C., & Larcker, D. F. (1981
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Kimmerle, J., Moskaliuk, J., & Cres
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What becomes clear from this short
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Figure 1. Distribution of informati
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Results In order to test the hypoth
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esults of the present study with th
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Kolbitsch, J., & Maurer, H. (2006).
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A conceptual framework of this stud
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eveal positive effects on students
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learning resources; and able to acc
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Discussion This study suggests that
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146). Also, role of constructivist
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eform strategy, namely, the MOE-Int
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McNaughton, S. (2002). Meeting of m
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Wu, T.-T., Sung, T.-W., Huang, Y.-M
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Ubiquitous English-Reading Learning
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include the number of times and ran
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initial value for the predetermined
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The following Eq. (18) expresses th
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Limitations This experiment adopted
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Table 3 shows the analysis of the p
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enhance learning outcomes, it impor
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Ogata, H., & Yano, Y. (2004a). Cont
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Communication seems to be more effe
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the audience only listened, one whe
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- Page 259 and 260: Figure 1. The UE Faculty Web Portal
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