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Discussion and conclusions In this study, we investigate students' perceptions in choosing the most-beneficial educational systems from the perspective of learning styles. The participants were asked to select one of two versions of an educational game developed based on the sequential/global dimension of the learning style proposed by Felder and Silverman. For the first and the second research questions, the experimental results of 288 students showed that the students were unable to choose educational computer games that fit them best from the learning style perspective; moreover, there was no difference between male and female students in choosing the games. In terms of the third research question, it was found that the choices they made were not related to their cognitive process or learning styles; instead, most students chose the e-learning systems based on intuition or preference, such as "interesting," "relaxing," "easy to use" and "conforming to previous experiences." Furthermore, the pre-test and post-test results showed that the learning achievements of the style-matching group outperformed those of the non-matching group. Therefore, it is concluded that students preferring one game over another does not necessarily mean that they will learn better with what they choose, revealing the importance and necessity of developing learning systems that are able to provide individual students with personalized learning content to best benefit them. That is, this study provides evidence for supporting the development of adaptive learning systems, in particular, for those studies that employ learning styles as a factor for adapting learning content, presentation styles and learning paths for individual students. To sum up, this study contributes several interesting findings to the community of technology-enhanced learning: (a) Students learn better with the version which has been designed for their learning style. This demonstrates the importance of adaptive learning systems which are based on learning styles. (b) Students do not necessarily choose the version which has been designed for their learning style. This is very important, because most adaptive systems create an initial user model based on individual students' answers to a questionnaire or choices of a set of parameters which are always assumed to be "reasonable." The results of the experiment demonstrate that this might be unsafe since users' choices are likely to be irrelevant to their learning performance. This can have a significant impact to the design of adaptable and adaptive learning systems. On the other hand, although this study provides some significant experimental results, the use of the computer educational games in this study might not be able to represent the common features of most learning systems; moreover, the implications of this study are limited owing to the investigation being conducted on only one dimension of a learning style. Some researchers have attempted to investigate the issues concerning game-based learning from different aspects in different application contexts, such as user participation (Hoffman & Nadelson, 2010), learning interactivity and challenges (Susaeta et al., 2010), learning attention (Russell & Newton, 2008), collaborative learning (Huang, Yeh, Li, & Chang, 2010; Paraskeva, Mysirlaki, & Papagianni, 2010), gender differences (Kinzie & Joseph, 2008) and the teachers' considerations (Kebritchi, 2010). In the future, it would be worth conducting further studies to investigate those relevant issues by taking different learning dimensions into account. Acknowledgements This study is supported in part by the National Science Council of the Republic of China under contract numbers NSC 99-2511-S-011-011-MY3 and NSC 100-2631-S-011-003. References Bolliger, D. U., & Supanakorn, S. (2011). Learning styles and student perceptions of the use of interactive online tutorials. British Journal of Educational Technology, 42(3), 470-481. Brusilovsky, P. (1996). Methods and techniques of adaptive hypermedia. User Modeling and User-Adapted Interaction, 6(2-3), 87-129. Brusilovsky, P. (2001). Adaptive hypermedia. User Modeling and User Adapted Interaction, 11, 87-110. 195
Burguillo, J. C. (2010). Using game theory and Competition-based Learning to stimulate student motivation and performance. Computers & Education, 55(2), 566-575. Cagiltay, N. E. (2007). Teaching software engineering by means of computer-game development: Challenges and opportunities. British Journal of Educational Technology, 38(3), 405-415. Chen, C. M. (2008). Intelligent web-based learning system with personalized learning path guidance. Computers & Education, 51(2), 787-814. Chen, C. M., Liu, C. Y., & Chang, M. H. (2006). Personalized curriculum sequencing utilizing modified item response theory for web-based instruction. Expert Systems with Applications, 30(2), 378-396. Dickey, M. D. (2011). Murder on Grimm Isle: The impact of game narrative design in an educational game-based learning environment. British Journal of Educational Technology, 42(3), 456-469. Ebner, M., & Holzinger, A. (2007). Successful implementation of user-centered game based learning in higher education: An example from civil engineering. Computers & Education, 49(3), 873-890. Felder, R. M., & Silverman, L. K.(1988). Learning styles and teaching styles in engineering education. Engineering Education, 78(7), 674-681. Filippidis, S. K., & Tsoukalas, L. A. (2009). On the use of adaptive instructional images based on the sequential-global dimension of the Felder-Silverman learning style theory. Interactive Learning Environments,17(2), 135-150. Graf , S., Liu, T. C., & Kinshuk (2010). Analysis of learners’ navigational behaviour and their learning styles in an online course. Journal of Computer Assisted Learning, 26(2), 116-131. Harris, K., & Reid, D. (2005). The influence of virtual reality play on children's motivation. Canadian Journal of Occupational Therapy, 72(1), 21-30. Hauptman, H., & Cohen, A. (2011). The synergetic effect of learning styles on the interaction between virtual environments and the enhancement of spatial thinking. Computers & Education, 57(3), 2106-2117. Hoffman, B., & Nadelson, L. (2010). Motivational engagement and video gaming: A mixed methods study. Education Technology Research and Development, 58, 245-270. Huang, C. C., Yeh, T. K., Li, T. Y., & Chang, C. Y. (2010). The idea storming cube: Evaluating the effects of using game and computer agent to support divergent thinking. Educational Technology & Society, 13(4), 180-191. Huang, S. L., & Yang C. W. (2009). Designing a semantic bliki system to support different types of knowledge and adaptive learning. Computers & Education, 53(3), 701-712. Hwang, G. J., Sung, H. Y., Hung, C. M., Huang, I., & Tsai, C.-C. (2012). Development of a personalized educational computer game based on students’ learning styles. Educational Technology Research & Development,60(4), 623-638. doi: 10.1007/s11423- 012-9241-x Hwang, G. J., Sung, H. Y., Hung, C. M., Yang, L. H., & Huang, I. (2012). A knowledge engineering approach to developing educational computer games for improving students' differentiating knowledge. British Journal of Educational Technology,44(2), 183-196. doi:10.1111/j.1467-8535.2012.01285.x Hwang, G. J., & Wu, P. H. (2012). Advancements and trends in digital game-based learning research: a review of publications in selected journals from 2001 to 2010. British Journal of Educational Technology, 43(l), E6-E10. Hwang, G. J., Wu, P. H., & Chen, C. C. (2012). An online game approach for improving students' learning performance in webbased problem-solving activities. Computers & Education, 59(4), 1246-1256. doi: 10.1016/j.compedu.2012.05.009 Inal, Y., & Cagiltay, K. (2007). Flow experiences of children in an interactive social game environment. British Journal of Educational Technology, 38(3), 455-464. Karampiperis, P., & Sampson, D. (2005). Adaptive learning resources sequencing in educational hypermedia systems. Educational Technology & Society, 8(4), 128-147. Kebritchi, M. (2010). Factors affecting teachers’ adoption of educational computer games: A case study. British Journal of Educational Technology, 41(2), 256-270. Keefe, J. W. (1979). Learning style: An overview. In National association of secondary school principals (Ed.), Student learning styles: Diagnosing and prescribing programs (pp. 1-17). Reston, Virginia: National Association of Secondary School Principals. Keefe, J. W. (1987). Learning styles: Theory and practice. Reston, VA: National Association of Secondary School Principals. Keefe, J. W. (1991). Learning style: Cognitive and thinking skills. Reston, VA: National Association of Secondary School Principals. Kinshuk, Liu, T. C., & Graf, S. (2009). Coping with mismatched courses: Students' behaviour and performance in courses mismatched to their learning styles. Educational Technology Research and Development, 57(6), 739-752. 196
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http://www.ifets.info ISSN: 1436-45
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Supporting Organizations Centre for
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Timely Diagnostic Feedback for Data
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Lim et al. addressed two gaps, a us
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The new found benefits of technolog
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analysis of all articles submitted
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Since some articles could not meet
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Table 2. Distribution of research t
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Research method Table 8 shows diffe
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authors concluded that mixed-method
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trends. Library and Information Sci
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Taylor, E. W. (2001). Adult Educati
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Zealand 10 paper 15 19 Using mutual
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impact on a variety of sectors arou
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Grand challenges These grand challe
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eport for details of competencies c
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learning repositories to use in con
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Acknowledgements This paper is base
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eliminating duplicates, a total of
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Findings of this review In the foll
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Table 2. Summary of empirical resea
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students’ conception of learning
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their creative capacity in designin
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which make it impossible to see how
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The content knowledge Table 3 depic
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The first revision we have made to
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Angeli, C., & Valanides, N. (2005).
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Lee, H., & Hollebrands, K. (2008).
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Rushby, N. (2013). The Future of Le
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The top ten in the 2011 survey were
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My first vision of the future is on
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References Dienstag, J. (2006). Pes
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industries, new laws, and new areas
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or distractive effects of technolog
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This may be further complicated by
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espect, the literature about school
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Tondeur, J., Van Keer, H., van Braa
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Disruptive technology When mainfram
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with the physical environment, such
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mockups, and then embedded in compu
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the global marketplace. Students in
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games, and virtual worlds are domin
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Malone, T. W. & Lepper, M. R. (1987
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education reform. In the following
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error elimination and/or refutation
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In essence, as depicted in figure 1
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of our students, who are the future
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Simon, H. (1996). The Sciences of t
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2010). Similar patterns can be obse
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To complement the literature search
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Figure 1. Domains of sustainable e-
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Discussion and conclusions This sco
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Baty, P. (2010, July 1). Global rep
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Loewenberger, P., & Bull, J. (2003)
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applied query expansion techniques
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di, 1 ≤ i ≤ n , 0 < d i ≤ 1,
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Procedure Figure 2 schematically de
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Phase 3. Wiki-based revision Throug
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Table 4. Comparison of the performa
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materials manually by working alone
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# Question 1 2 3 4 5 Table 7. Users
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Kuo, Y. H., & Huang, Y. M. (2009).
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Nevertheless, one of the major prob
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Rlj indicates the answer of the l t
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Relative weight Very low 5 ww , ∈
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Experiment and evaluation Figure 7.
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and CG (59.06 and 13.52). The resul
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Expert 1 Expert 2 Expert 3 Correctn
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The EFWA algorithm Appendix Defini
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y the fourth student correctly is:
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drA = − + − + − = 2 2 2 ( , M
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students have achieved what they wa
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environments. This gap can be bridg
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can understand, as well as a vehicl
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Page 167 and 168: Mayer, R. E. (2001). Multimedia lea
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Page 177 and 178: Appendix 1. Sample items of BACT *I
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Page 181 and 182: Johnson and Johnson (1994) identifi
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Page 185 and 186: Findings The students exhibited hig
Page 187 and 188: We take two instances of character
Page 189 and 190: In designing Chinese-PP, we instead
Page 191 and 192: Boticki, I., Looi, C.-K., & Wong, L
Page 193 and 194: Hwang, G.-J., Sung, H.-Y., Hung, C.
Page 195 and 196: 2000). For example, Filippidis and
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Page 203 and 204: Wong, L.-H. (2013). Analysis of Stu
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Page 225 and 226: Procedures All subjects in both gro
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Page 235 and 236: The related works Feedback should b
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Page 239 and 240: Once the frequent itemsets have bee
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Page 245 and 246: Questionnaire and interviews To und
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Page 249 and 250: According to Angeli and Valanides (
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description, objectives, and entry
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TCK: For the fourth activity, the g
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A questionnaire focusing on Instruc
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eing aware of the importance of sel
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References Airasian, P. W., & Walsh
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Instructional Technology Instructio
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and He (2006) revealed that technol
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Model and hypothesis development Sa
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Table 1. Student profile Gender: Ma
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H3 Student satisfaction has positiv
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Conclusions Addressing four PRS iss
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Tao, Y.-H., & Yeh, R. C. (2009, Jul
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My overall experience of PRS is abs
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skills can move to the next learnin
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were divided into an experimental g
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illustrates the Monopoly gameplay m
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Comparison of monopoly and instruct
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Guskey, T. R., & Gates, S. L. (1986
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Yang, C.-C., Tseng, S.-S., Liao, A.
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text only because learners are able
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Figure 2. Structure of poetry multi
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time period. Bandwidth is measured
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Participants and experimental proce
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owses multimedia resources. Fewer p
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the other approach. Meanwhile, the
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Wang, Y.-H., Young, S. S.-C., & Jan
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mistakes in front of the teacher an
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Basic English learning materials we
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The instructor also showed positive
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H.L, M = 38.11) which occurred in b
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Discussions Tangible learning compa
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We can conclude from the current st
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Joo, Y. J., Joung, S., & Kim, E. K.
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on 506 students registered for cybe
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and management systems, learning se
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multivariate normal distribution as
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Structural model examination Table
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Direct effect Flow ← Satisfaction
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Second, the results of this study c
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Kim, H. S. (2008). The effects of t
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language accurately, or product-ori
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Thailand 5 Vietnam 25 Total 208 Res
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Procedures of data collection Figur
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discussions. From Brian’s log fil
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universities. There were 259 studen
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and he provided his arguments and r
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Within groups Total Test 4 Between
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Crooks, B. (2003). The combined use
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Appendix A 342
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teenager. Chapter four, “Identity
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