April 2012 Volume 15 Number 2 - Educational Technology & Society

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Liaw, S. S. (2008). Investigating students’ perceived satisfaction, behavioral intention, and effectiveness of e-learning: A case study of the Blackboard system. Computers & Education, 51(2), 864-873. Lim, H., Lee, S. G., & Nam, K. (2007). Validating E-learning factors affecting training effectiveness. International Journal of Information Management, 27(1), 22-35 Loh, B. H. (2007). The Antecedents and Outcomes of E-Learning Effectiveness in the Manufacturing Industry (Unpublished master’s thesis). School of Management, Universiti Sains Malaysia, Penang. Long, L. K., DuBois, C. Z., & Faley, R. H. (2008). Online training: The value of capturing trainee reactions. Journal of Workplace Learning, 20(1), 21-37. Lorenzetti, J. P. (2005). How e-learning is changing higher education: A new look. Distance Education Report, 22, 4–7. Martocchio, J. J., & Dulebohn, J. (1994). Performance feedback effects in training: The role of perceived controllability. Personnel Psychology, 47(2), 357–373. Mathieu, J. E., & Martineau, J. W. (1997). Individual and situational influences on training motivation. In J. K. Ford, S. W. J. Kozlowski, K. Kraiger, E. Salas, & M. Teachout (Eds.), Improving Training Effectiveness in Work Organizations (pp. 193-221). Mahwah, NJ: Lawrence Erlbaum. Mathieu, J. E., Tannenbaum, S. I., & Salas, D. (1992). Influences of individual and situational characteristics on measures of training effectiveness. Academy of Management Journal, 35, 828–847. Md. Hashim Nordin, N. H. (2007). Antecedents and outcomes of Intention to use and user satisfaction in E-Learning (Unpublished master’s thesis). School of Management, Universiti Sains Malaysia, Penang. Negash, S., Ryan, T., & Igbaria, M. (2003). Quality and effectiveness in web-based customer support system. Information and Management, 40, 757-768. Noe, R. A. (1986). Trainees’ attributes and attitudes: Neglected influences on training effectiveness. Academy of Management Review, 11(4), 736–749. Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric Theory. New York: McGraw Hill. Oliver, R. L. (1980). A cognitive model for the antecedents and consequences of satisfaction. Journal of Marketing Research, 17(4), 460-469. Rai, A., Lang, S. S., & Welker, R. B. (2002). Assessing the validity of IS success models: An empirical test and theoretical information analysis. Information Systems Research, 13(1), 50-69. Roca, J. C., & Gagné, M. (2008). Understanding e-learning continuance intention in the workplace: A self-determination theory perspective. Computers in Human Behavior, 24(4), 1585-1604. Rosenberg, M. J. (2001). E-learning: Strategies for delivery knowledge in the digital age. New York: McGraw-Hill. Shee, D. Y., & Wang, Y. S. (2008). Multi-criteria evaluation of the web-based e-learning system: A methodology based on learner satisfaction and its applications, Computers & Education, 50(3), 894-905. Spreng, R. A., MacKenzie, S. B., & Olshavsky, R. W. (1996). A reexamination of the determinants of consumer satisfaction. Journal of Marketing, 60(3), 15-32. Taylor, S., & Todd, P. (1995). Assessing IT usage: The role of prior experience. MIS Quarterly, 19(4), 561-570. Taylor, S. S. (2002). Online: Off course or on track? Community College Week, 14(20), 10-12. Torkzadeh, G., & Doll, W.J. (1999). The development of a tool for measuring the perceived impact of information technology on work. Omega—The International Journal of Management Science, 27( 3), 327-339. Tracey, J. B., Tannenbaum, S. I., & Kavanagh, M. J. (1995). Applying trained skills on the job: The importance of the work environment. Journal of Applied Psychology, 80, 239-252. Tracey, J. B., Hinkin, T. R.,Tannenbaum, S., & Mathieu, J. E. (2001). The influence of individual characteristics and the work environment on varying levels of training outcomes. Human Resources Development Quarterly, 12(1), 5-23. Van Slyke, C., Belanger, F., & Comunale, C. (2004). Factors influencing the adoption of web-based shopping: The impact of trust. Database for Advances in Information Systems, 35(2), 32–46. Wang, Y. S. (2003). Assessment of learner satisfaction with asynchronous electronic learning systems. Information & Management, 41(1), 75-86. 137
Wen, Y., Looi, C.-K., & Chen, W. (2012). Supporting Teachers in Designing CSCL Activities: A Case Study of Principle-based Pedagogical Patterns in Networked Second Language Classrooms. Educational Technology & Society, 15 (2), 138–153. Supporting Teachers in Designing CSCL Activities: A Case Study of Principlebased Pedagogical Patterns in Networked Second Language Classrooms Yun Wen, Chee-Kit Looi and Wenli Chen Learning Sciences Lab, National Institute of Education, Nanyang Technological University 1 Nanyang Walk, Singapore 637616 // yun.wen@nie.edu.sg // cheekit.looi@nie.edu.sg (Submitted May 26, 2010; Revised November 20, 2011; Accepted December 11, 2011) ABSTRACT This paper proposes the identification and use of principle-based pedagogical patterns to help teachers to translate design principles into actionable teaching activities, and to scaffold student learning with sufficient flexibility and creativity. A set of pedagogical patterns for networked Second language (L2) learning, categorized and undergirded by rapid collaborative knowledge improvement (RCKI) principles, has been extracted and articulated in our school-based research. The patterns are distilled from a series of over 60 Chinese language lessons conducted in real classrooms which are co-designed by teachers and researchers over a 3-year period in Singapore schools. Each principle-based pedagogical pattern is presented succinctly in a simple pattern language. Two classroom scenarios of collaborative activities are elucidated, embodying some of the patterns to provide a more grounded feel of how they are enacted in practice. RCKI principle-based pedagogical patterns inform the design of collaborative language learning activities in networked classrooms. Preliminary findings reveal that principle-based pedagogical patterns provide teachers a workable way to design RCKI activities and enable teachers to adopt, internalize and adapt them in classroom use. Keywords Principle-based pedagogical patterns, RCKI, L2 learning, Computer-supported Collaborative Learning (CSCL) Introduction Spurred by rapid developments in information and communication technologies (ICT), diverse tools are now being used in a rich variety of ways to support teaching and learning. Goodyear (2005) uses the term networked learning broadly to include e-learning, web-based learning, online learning, and computer-supported learning. He emphasizes that “networked learning is not necessarily distance learning. It may well involve some face-to-face (FTF) interactions, whether or not these are supported by the use of ICT. The important element is connectedness” (2005, p. 83). In authentic classroom settings, teachers can harness such connectivity to increase opportunities for social interaction, as well as provide resources to support learning. The more dynamic and complex networked learning environment requires taking advantages of new opportunities and working with emergent rather than fixed goals (Sawyer, 2004). Teachers face numerous problems in orchestrating networked classrooms, especially when dealing with complex pedagogies such as collaborative learning (Dimitriadis, 2010). Scripts are a popular means of guiding the design of computer-supported collaborative learning (CSCL) activities and supporting teachers in classroom orchestration by structuring the flow of the collaborative activity (Dillenbourg & Hong, 2008; Dillenbourg & Jermann, 2010). Dimitriadis (2010) attributes pedagogical patterns as a kind of mediating artifacts in a CSCL environment. Pedagogical patterns that are developed from analyzing expert knowledge of the practices of teaching and learning (Pedagogical Pattern Project, n.d.) can provide a more concrete and understandable form of knowledge for teachers instead. They can serve as a powerful way for sharing good practices (Dimitriadis, Goodyear & Retalis, 2009; Fincher, 1999). A growing number of studies have pointed out the potential of the pedagogical pattern approach for teacher professional development (DeBarger, et al, 2010; Law, Laurillard, & Lee, 2011; Prieto, Villagrá-Sobrino, & Dimitriadis, 2011). However, pedagogical patterns that captured good practices in traditional teaching processes cannot be applied directly to CSCL activities in networked classrooms. Traditional pedagogical patterns have fixed goals and comparatively fixed routines. CSCL demands and enables shift the focus of education from learning as knowledge acquisition to learning as building shared meaning, enculturation into social practices and participation in valued activities situated within a community of practice (Roschelle et al., 2011). In such CSCL environments, teachers work with more emergent goal structures and opportunism in knowledge work (Zhang & Scardamalia, 2007). But, ISSN 1436-4522 (online) and 1176-3647 (print). © International Forum of Educational Technology & Society (IFETS). The authors and the forum jointly retain the copyright of the articles. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear the full citation on the first page. Copyrights for components of this work owned by others than IFETS must be honoured. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from the editors at kinshuk@ieee.org. 138
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April 2012 Volume 15 Number 2
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Supporting Organizations Centre for
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Contextualizing a MALL: Practice De
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Kop, R. (2012). The Unexpected Conn
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Human mediation and information flo
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elevant information based on some k
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of learners. A search facilitated t
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information as human mediation mean
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Blau, I., & Barak, A. (2012). How D
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examined whether the readiness to p
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Table 5 presents the ANOVA for the
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However, in discussing a non-sensit
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deviations showed smaller variance,
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actual participation discussing sen
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Mesch, G., & Elgali, Z. (2009). Soc
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Although prior research on overall
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with a score of 39 and below as “
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Table 2 demonstrates mean scores an
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Discussion Although the recent Inte
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Furthermore, the most preferred pla
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MEB. (2009). Internete erisim proje
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Learning Management Systems (LMS) b
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practice and repetition with feedba
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Online peer assessment Peer assessm
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At an international conference on m
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� Ability to produce rich assessm
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Meishar-Tal, H., & Tal-Elhasid, E.
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Tsai, S. C. (2012). Integration of
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order to decrease text complexity a
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matter how the learners’ aptitude
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If compared by programs, WP student
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mean F2F 4.64 4.52 4.35 4.44 *: p
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een analyzed and were compared with
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Chen, G.-D., Lee, J.-H., Wang, C.-Y
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and diverse cognitional and emotion
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Encourage and persuade students wit
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Materials and procedure Each studen
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The lower part of Figure 4 shows st
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Mayer, R. E., Sobko, K., & Mautone,
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that an item is answered correctly
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Table 1. Relative concepts frequenc
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The Account Management Module provi
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Experiment 1 and results Figure 7.
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Utilization of Test Item 36 33 30 2
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Utilization of Test Item 36 33 30 2
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Page 95 and 96: the diverse needs of modern industr
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Page 117 and 118: student mood and thereby allow comp
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Page 121 and 122: The rationale behind the video form
Page 123 and 124: usefulness of the movies and their
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Page 129 and 130: The survey questions Appendix A In
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Page 135 and 136: Method Sample and procedure Figure
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Page 141: Brown, M., & Cudeck, R. (1993). Alt
Page 145 and 146: when they are designing and impleme
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Page 151 and 152: Democratizing knowledge and symmetr
Page 153 and 154: 1) Reading the article: At the star
Page 155 and 156: Effects of RCKI principle-based ped
Page 157 and 158: References Alexander, C. (1979). Th
Page 159 and 160: Valsamidis, S., Kontogiannis, S., K
Page 161 and 162: The Analog system (Yan et al., 1996
Page 163 and 164: First, the number of the sessions a
Page 165 and 166: BioLayout uses a modified version o
Page 167 and 168: As shown in figure 3, all metrics c
Page 169 and 170: Figure 7. The detailed results for
Page 171 and 172: Enright, A. J., van Dongen, S., Ouz
Page 173 and 174: Chu, S. K. W., Kwan, A. C. M., & Wa
Page 175 and 176: teachers, as well as collaboration
Page 177 and 178: from the students’ ratings appear
Page 179 and 180: Table 5 summarizes the students’
Page 181 and 182: eading blogs (i.e., reminders, easy
Page 183 and 184: Luehmann, A. L. (2008). Using blogg
Page 185 and 186: Uzunboylu et al. (2009) examined th
Page 187 and 188: System implementation Overview of M
Page 189 and 190: Methods Before the experiment, a mo
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Comparisons of UMLS Questionnaire i
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already described may play an impor
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Parker, D., Manstead, A. S. R., Str
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Avci, U., & Askar, P. (2012). The C
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Literature review The related varia
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collected through Personal Informat
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Self-efficacy 92 5 21 13.37 3.726 W
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In this problem, intention was take
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References Ajjan, H., & Hartshorne,
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Tan, T.-H., Lin, M.-S., Chu, Y.-L.,
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Students perused the course materia
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problem. All articles were then sen
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tests, electronic tests are more li
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Students 10 and 11: My classmate Ed
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collection was also approved by all
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Ubiquitous Revision Seamless Collab
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Tai, Y. (2012). Contextualizing a M
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tasks were developed from task type
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experiences in this phase. Moreover
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test is administered again right af
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The collected data were analyzed wi
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Gorp, K. V., & Bogaert, N. (2006).
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4PL IRT model According to the numb
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examinee’s ability more accuratel
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would be more accurate if items j+1
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C�I or Change I�I) would be 0.2
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improved by rearrangement procedure
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Table 6. Repeated Measures ANOVA of
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Leppisaari, I., & Lee, O. (2012). M
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Selection of the virtual tool The t
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Environmental themes emerged strong
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Visualization of text (visual langu
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environments where visual technolog
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- Logging in to learning environmen
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McNaught, C., Lam, P. & Lam, S.L. (
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on-site to finally achieve a meanin
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Table 1. Digital game designers and
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worldviews are socio-cultural-histo
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Phase Methods Visitor data collecti
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operate the game without the help o
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Visitors (end users) must be heard.
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Islas Sedano, C., Pawlowski, J., Su
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part of something larger than the s
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Previous studies have developed rel
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Technology Acceptance. The 10 items
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Table 4. Model Fit Indices Model χ
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In the final path model of set 1, t
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Discussion Differing from prior stu
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Haythornthwaite, C., Kazmer, M. M.,
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Ge, Z.-G. (2012). Cyber Asynchronou
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college of a university situated in
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Table 3 shows us the following info
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Appendix B shows Class 1’s respon
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increase one’s ability to process
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Appendix A Responses concerning syn
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Shih, S.-C., Kuo, B.-C., & Liu, Y.-
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Adaptive U-learning Math Path Syste
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Figure 4. Online tutorial courses o
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Participants and Experimental Proce
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the influence of Test1 scores, an e
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Hall, T., & Bannon, L. (2006). Desi
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(Hofer & Pintrich, 1997; Liu, Lin &
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� Through online peer assessment,
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elativism.” High Internet self-ef
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Peng, H., Tsai, C.-C., & Wu, Y.-T.
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Since game-based learning has been
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The second reason is about the sust
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Methods Figure 5. Quest NPCs provid
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These differences indicated that pa
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quests further involves students’
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Chang, I.-H. (2012). The Effect of
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(1) Vision, planning and management
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Based on an examination of the lite
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Table 2. Analysis of reliability an
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λ10 - 0.69 0.83 ε5 14.50 * - 0.32
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Bailey, G. D. (1997). What technolo
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Stegall, P. (1998). The principal:
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instruction has studied the student
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espond and the estimation of possib
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Research question For the purpose o
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READI reliability To verify the con
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Physical -1.43333(*) .44699 .029 -2
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The results of this study suggest t
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Hsu, Y.-C., Ho, H. N. J., Tsai, C.-
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domains. Five research questions we
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Research sample groups (4) Faculty
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13. Policies, Social Culture Impact
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Non-Specified Others Engineering &
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(AR = -2.1) (n = 7) 2. Non-specifie
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(n): Total number of articles Resea
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Compared to the publications in 200
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Pedagogical Content Knowledge (TPAC
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