April 2012 Volume 15 Number 2 - Educational Technology & Society

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Gardner-Medwin, A. R., & Gahan, M. (2003). Formative and summative confidence-based assessment. Paper presented at the 7th International Computer-Aided Assessment Conference, Loughborough, UK. Gershon, R. C., & Bergstrom, B. (1995, April). Does cheating on CAT pay: NOT! Paper presented at the the annual meeting of the American Educational Research Association, San Francisco, CA. Harvey, R. J., & Hammer, A. L. (1999). Item response theory. The Counseling Psychologist, 27(3), 353–384. Harvil, L. M., & Davis III, G. (1997). Medical students' reasons for changing answers on multiple-choice tests. Academic Medicine, 72(10), S97–S99. Heidenberg, A. J., & Layne, B. H. (2000). Answer changing: A conditional argument. College Student Journal, 34(3), 440–450. Hockemeyer, C. (2002). A comparison of non-deterministic procedures for the adaptive assessment of knowledge. Psychologische Beiträge, 44(4), 495–503. Lunz, M. E., Bergstrom, B. A., & Wright, B. D. (1992). The effect of review on student ability and test efficiency for computerized adaptive tests. Applied Psychological Measurement, 16(1), 33-40. McMorris, R. F., & Weideman, A. H. (1986). Answer changing after instruction on answer changing. Measurement and Evaluation in Counseling and Development, 19(2), 93–101. Mills, C. N., & Stocking, M. L. (1995). Practical issues in large-scale high-stakes computerized adaptive testing. Princeton, NJ: Educational Testing Service. Papanastasiou, E. C. (2002, April). A ‘rearrangement procedure’ for scoring adaptive tests with review options. Paper presented at the the National Council of Measurement in Education, New Orleans, LA. Papanastasiou, E. C. (2005). Item review and the rearrangement procedure: Its process and its results. Educational Research and Evaluation, 11(4), 303–321. Papanastasiou, E. C., & Reckase, M. D. (2007). A "rearrangement procedure" for scoring adaptive tests with review options. International Journal of Testing, 7(4), 387–407. Parshall, C. G., Spary, J. A., Kalhn, J. C., & Davey, T. (2002). Practical considerations in computer based testing. New York: Springer-Verlag. Rulison, K., & Loken, E. (2009). I've fallen and I can't get up: can high-ability students recover from early mistakes in CAT? Applied Psychological Measurement, 33(2), 83. Shatz, M. A., & Best, J. B. (1987). Students' reasons for changing answers on objective tests. Teaching of Psychology, 14(4), 241–242. Stocking, M. L. (1997). Revising item responses in computerized adaptive tests: A comparison of three models. Applied Psychological Measurement, 21(2), 129-142. Stone, G. E., & Lunz, M. E. (1994). The effect of review on the psychometric characteristics of computerized adaptive tests. Applied Measurement in Education, 7(3), 211–222. Vicino, F. L., & Moreno, K. E. (1997). Human factors in the CAT system: A pilot study. In W. A. Sands, B. K. Waters & J. R. McBride (Eds.), Computerized adaptive testing: From inquiry to operation (pp. 157–160). Washington, DC: APA. Vispoel, W. P. (1998). Reviewing and changing answers on computer-adaptive and self-adaptive vocabulary tests. Journal of Educational Measurement, 35(4), 328–345. Vispoel, W. P., Hendrickson, A. B., & Bleiler, T. (2000). Limiting answer review and change on computerized adaptive vocabulary tests: Psychometric and attitudinal results. Journal of Educational Measurement, 37(1), 21–38. Vispoel, W. P., Rocklin, T. R., Wang, T., & Bleiler, T. (1999). Can examinees use a review option to obtain positively biased ability estimates on a computerized adaptive test? Journal of Educational Measurement, 36(2), 141–157. Waddell, D. L., & Blankenship, J. C. (1994). Answer changing: A meta-analysis of the prevalence and patterns. Journal of Continuing Education in Nursing, 25(4), 155–158. Wise, S. L. (1996, April). A critical analysis of the arguments for and against item review in computerized adaptive testing. Paper presented at the the annual meeting of the National Conference on Measurement in Education, New York, NY. Wise, S. L., & Kingsbury, G. G. (2000). Practical issues in developing and maintaining a computerized adaptive testing program. Psicologica, 21(1–2), 135–155. Yen, Y. C., Ho, R. G., Chen, L. J., Chou, K. Y., & Chen, Y. L. (2010). Development and evaluation of a confidence-weighting computerized adaptive testing. Educational Technology & Society, 13(3), 163–176. 243
Leppisaari, I., & Lee, O. (2012). Modeling Digital Natives’ International Collaboration: Finnish-Korean Experiences of Environmental Education. Educational Technology & Society, 15 (2), 244–256. Modelling Digital Natives’ International Collaboration: Finnish-Korean Experiences of Environmental Education Irja Leppisaari 1 and Okhwa Lee 2 * 1 AVERKO, Central Ostrobothnia University of Applied Sciences, Talonpojankatu 2, 67100, Kokkola, Finland // 2 Dept. of Computer Education, Chungbuk National University, 410 Sungbong-ro, Heungduk-ku, Cheongju city, Chungbuk, Korea 361-763 // irja.leppisaari@cou.fi // ohlee@cbnu.ac.k *Corresponding author (Submitted October 4, 2010; Revised February 10, 2011; Accepted April 10, 2011) ABSTRACT A new generation of young learners often described as digital native school children are attitudinally and technically equipped to employ social media as a social process in learning. However, few international virtual learning projects have been implemented and researched. This article examines a trial which aimed to combine viable technology with future pedagogic solutions for primary students from Korea and Finland and create an international collaboration model in virtual learning for environmental education. The results show various challenges of the operational model and suggest effective implementation strategies. The challenges were organisational, language, technical and collaboration barriers. The operational model illustrates possibilities of implementing cyber space pedagogy, visualization of knowledge using technology, cyber spaces for collaboration, and the motivational impetus provided by the model. This pilot study demonstrates the need to increase greater interactivity between teachers from the partner countries during the planning phase and provide more authentic interaction for inter-learner dialogue. Keywords International collaboration model, Environmental education, ICT in education, Finland, Korea Introduction As the world becomes more inter-connected and globalized, people are asked to be aware of multi-cultural differences, and global education is particularly needed for 21 st century students (Cisco, 2010). Schools are often asked to provide education for global citizenship (Kaivola & Melén-Paaso, 2007; O’Neill, 2006). Information communication technology enables communities to move beyond geographical boundaries and provides a vehicle for people around the world to interact and learn together seamlessly. Concurrently learners in international collaboration on the web are required to face and overcome numerous barriers, e.g. linguistic, temporal and cultural boundaries (Walker & Creanor, 2011). Direct interaction and communication with students from other cultures can be one of the most effective ways to understand and learn about cultural differences. Global environmental issues can be an appropriate means of introducing global citizenship to students. Social software, like Web 2.0 enables students to collaborate through computer-mediated communication and to form learning communities in which they construct and share knowledge. Learning communities emerge when students share common interests (Jonassen, Howland, Marra & Chrismond, 2008; Hakkarainen, Palonen, Paavola & Lehtinen, 2004). Since ICT is already developed enough to easily provide students with international interaction opportunities in teaching and learning, schools should not hesitate to offer international collaboration using ICT, which seems to be a promising means of achieving this goal (O’Neill, 2006). ICT has permeated daily life extensively, and Finland and Korea are known as highly wired countries. Not only are the societies technically equipped, but schools are also. Although great differences continue to exist in resources between schools, extensive national training and school facilities have ensured adequate proficiency of teachers’ technical skills and ability to employ ICT in education. However, schools still face challenges – the use of technology as a learning tool has not increased (Niemi & Kumpulainen, 2008; Kankaanranta & Puhakka, 2008). Developing school practices to reflect contemporary learning concepts powerfully impacts technologic needs in teaching (Niemi & Kumpulainen, 2008). Infrastructure of ICT in Korean and Finnish schools has been well established but pedagogic implementation of ICT in education has not been adopted well. 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. 244
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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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0.065 0.877 (17.56) 0.938 (22.55) 0
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Hwang, G.J., Hsiao, C.L., & Tseng,
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the diverse needs of modern industr
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Figure 1. The framework of interdis
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Research Design Figure 3. Recommend
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friendly. 8. I feel the layout and
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satisfaction, and system acceptance
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Ozok, A. A., Fan, Q., & Norcio, A.
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than students in a conventional cla
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shown in Figure 2 to include the st
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(1996) Pleasure-Arousal-Dominance (
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Based on this connection, we consid
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Final dominance measurements were p
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student mood and thereby allow comp
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Sessink, O., Beeftink, H., Tramper,
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The rationale behind the video form
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usefulness of the movies and their
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case of the first two questions and
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this paper in order to evaluate the
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The survey questions Appendix A In
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E-training in organizations E-train
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efficacy regarding online training,
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Method Sample and procedure Figure
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0.874 which exceeded the recommende
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Even though the result does not con
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Brown, M., & Cudeck, R. (1993). Alt
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Wen, Y., Looi, C.-K., & Chen, W. (2
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when they are designing and impleme
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paper focuses on the first three st
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their self-esteem to be partners in
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Democratizing knowledge and symmetr
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1) Reading the article: At the star
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Effects of RCKI principle-based ped
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References Alexander, C. (1979). Th
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Valsamidis, S., Kontogiannis, S., K
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The Analog system (Yan et al., 1996
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First, the number of the sessions a
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BioLayout uses a modified version o
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As shown in figure 3, all metrics c
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Figure 7. The detailed results for
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Enright, A. J., van Dongen, S., Ouz
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Chu, S. K. W., Kwan, A. C. M., & Wa
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teachers, as well as collaboration
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from the students’ ratings appear
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Table 5 summarizes the students’
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eading blogs (i.e., reminders, easy
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Luehmann, A. L. (2008). Using blogg
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Uzunboylu et al. (2009) examined th
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System implementation Overview of M
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Methods Before the experiment, a mo
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too simple, incomplete, or they eve
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Comparisons of UMLS Questionnaire i
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already described may play an impor
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Page 201 and 202: Literature review The related varia
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Page 205 and 206: Self-efficacy 92 5 21 13.37 3.726 W
Page 207 and 208: In this problem, intention was take
Page 209 and 210: References Ajjan, H., & Hartshorne,
Page 211 and 212: Tan, T.-H., Lin, M.-S., Chu, Y.-L.,
Page 213 and 214: Students perused the course materia
Page 215 and 216: problem. All articles were then sen
Page 217 and 218: tests, electronic tests are more li
Page 219 and 220: Students 10 and 11: My classmate Ed
Page 221 and 222: collection was also approved by all
Page 223 and 224: Ubiquitous Revision Seamless Collab
Page 225 and 226: Tai, Y. (2012). Contextualizing a M
Page 227 and 228: tasks were developed from task type
Page 229 and 230: experiences in this phase. Moreover
Page 231 and 232: test is administered again right af
Page 233 and 234: The collected data were analyzed wi
Page 235 and 236: Gorp, K. V., & Bogaert, N. (2006).
Page 237 and 238: 4PL IRT model According to the numb
Page 239 and 240: examinee’s ability more accuratel
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Page 251 and 252: Selection of the virtual tool The t
Page 253 and 254: Environmental themes emerged strong
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Page 257 and 258: environments where visual technolog
Page 259 and 260: - Logging in to learning environmen
Page 261 and 262: McNaught, C., Lam, P. & Lam, S.L. (
Page 263 and 264: on-site to finally achieve a meanin
Page 265 and 266: Table 1. Digital game designers and
Page 267 and 268: worldviews are socio-cultural-histo
Page 269 and 270: Phase Methods Visitor data collecti
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Page 275 and 276: Islas Sedano, C., Pawlowski, J., Su
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Page 281 and 282: Technology Acceptance. The 10 items
Page 283 and 284: Table 4. Model Fit Indices Model χ
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Page 287 and 288: Discussion Differing from prior stu
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Page 291 and 292: Ge, Z.-G. (2012). Cyber Asynchronou
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Page 295 and 296: Table 3 shows us the following info
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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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