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Toth, E. (2009). "Virtual Inquiry" in the science classroom: What is the role of technological pedagogial content knowledge? International Journal of Information & Communication Technology Education, 5(4), 78-87. doi:10.4018/jicte.2009041008 Valtonen, T., Kukkonen, J., Wulff, A. (2006). High school teachers' course designs and their professional knowledge of online teaching. Informatics in Education, 5(2), 301-316. Wilson, E., & Wright, V. (2010). Images over time: The intersection of social studies through technology, content, and pedagogy. Contemporary Issues in Technology and Teacher Education (CITE Journal), 10(2), 220-233. Wu, W.-H., Chen, W.-F., Wang, T.-L., Su, C.-H. (2008). Developing and evaluating a game-based software engineering educational system. International Journal of Engineering Education, 24(4), 681-688. 51
Rushby, N. (2013). The Future of Learning Technology: Some Tentative Predictions. Educational Technology & Society, 16 (2), 52–58. The Future of Learning Technology: Some Tentative Predictions Nick Rushby Editor, British Journal of Educational Technology, UK // nick.rushby@dsl.pipex.com ABSTRACT This paper is a snapshot of an evolving vision of what the future may hold for learning technology. It offers three personal visions of the future and raises many questions that need to be explored if learning technology is to realise its full potential. Keywords Future trends, History, Innovation, Technology life cycle, Visions Introduction Some twenty one years ago I quoted an old Chinese proverb that “Prophesy is dangerous—especially when it concerns the future” and noted that it was “not so very long ago that those who claimed to be able to see into the future were given a show trial and then burned at the stake” (Rushby, 1990). These days it is only the expert’s reputation that is burned. I am even more hesitant to make prophesies when I read Philip Tetlock’s award winning research on expert political judgement (Tetlock, 2005) which concluded that the “experts” were only slightly better than straight chance in their predictions about the future. For those of you who do not know this work, Tetlock asked 284 experts to make 28,000 predictions. The experts were drawn from many different fields. They ranged from university professors to journalists and had widely different beliefs from Marxists to free-marketeers. The predictions were followed up over a twenty year period and were—on average—dismally inaccurate. Interestingly, the most inaccurate were those experts who were certain in their predictions: those who spoke in terms of probabilities did rather better. The lesson we should take from this, is that the rest of this paper and the companion papers from other editors, should be treated with great caution. You may do better by rolling dice! I should also add that the thoughts which are set out in this paper are a work in process. I set out to write what, in an abbreviated form, is the first part of the paper. In conversations with myself and with colleagues, I began to realise that the traditional vision (now Vision 1) was flawed. As you read on, I hope you will understand why. First however, let me deal with the question of why a journal such as the British Journal of Educational Technology (BJET) needs to be interested in what the future may hold for learning technology. It is more than idle curiosity! Journals have a complex relationship with the future: They are trying to predict the future so that, from the papers that are submitted for publication, they can select those that are likely to be of interest to readers in the future, and conversely, by their choice of papers they shape what people read and thus influence the future direction of research in their field. The past forty years It happens that 2011 marks my 40 th Anniversary in the learning technology business. My postgraduate research in 1971 was on the use of artificial intelligence techniques in computer assisted instruction. Contrary to current popular belief, the use of computers for learning was already well established and we had no doubt that CAI was going to revolutionise education and training. Over the following years, artificial intelligence grew and diminished in importance. It continues to support some learning systems, but the promise of intelligent tutoring systems has never quite been realised on any significant scale. 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. 52
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http://www.ifets.info ISSN: 1436-45
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Supporting Organizations Centre for
Page 5 and 6: Timely Diagnostic Feedback for Data
Page 7 and 8: Lim et al. addressed two gaps, a us
Page 9 and 10: The new found benefits of technolog
Page 11 and 12: analysis of all articles submitted
Page 13 and 14: Since some articles could not meet
Page 15 and 16: Table 2. Distribution of research t
Page 17 and 18: Research method Table 8 shows diffe
Page 19 and 20: authors concluded that mixed-method
Page 21 and 22: trends. Library and Information Sci
Page 23 and 24: Taylor, E. W. (2001). Adult Educati
Page 25 and 26: Zealand 10 paper 15 19 Using mutual
Page 27 and 28: impact on a variety of sectors arou
Page 29 and 30: Grand challenges These grand challe
Page 31 and 32: eport for details of competencies c
Page 33 and 34: learning repositories to use in con
Page 35 and 36: Acknowledgements This paper is base
Page 37 and 38: eliminating duplicates, a total of
Page 39 and 40: Findings of this review In the foll
Page 41 and 42: Table 2. Summary of empirical resea
Page 43 and 44: students’ conception of learning
Page 45 and 46: their creative capacity in designin
Page 47 and 48: which make it impossible to see how
Page 49 and 50: The content knowledge Table 3 depic
Page 51 and 52: The first revision we have made to
Page 53 and 54: Angeli, C., & Valanides, N. (2005).
Page 55: Lee, H., & Hollebrands, K. (2008).
Page 59 and 60: The top ten in the 2011 survey were
Page 61 and 62: My first vision of the future is on
Page 63 and 64: References Dienstag, J. (2006). Pes
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Page 71 and 72: espect, the literature about school
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Page 75 and 76: Disruptive technology When mainfram
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Page 79 and 80: mockups, and then embedded in compu
Page 81 and 82: the global marketplace. Students in
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Page 87 and 88: education reform. In the following
Page 89 and 90: error elimination and/or refutation
Page 91 and 92: In essence, as depicted in figure 1
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Page 95 and 96: Simon, H. (1996). The Sciences of t
Page 97 and 98: 2010). Similar patterns can be obse
Page 99 and 100: To complement the literature search
Page 101 and 102: Figure 1. Domains of sustainable e-
Page 103 and 104: Discussion and conclusions This sco
Page 105 and 106: 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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5. “Then move on to Loop 2.” Ea
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fact that the students could not ge
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conceptualization, and testing in n
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Soloway, E., Norris, C., Blumenfeld
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all image search queries result in
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instance, not knowing how to naviga
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displays in real time. The authors
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Significance was not found for main
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manifestation of visual literacy; a
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Mayer, R. E. (2001). Multimedia lea
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McMillen (1996) considered virtual
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Learning of area concepts in elemen
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shrink. changed. Hints and Show but
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Based on teacher observations and c
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Appendix 1. Sample items of BACT *I
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Wong, L.-H., Hsu, C.-K., Sun, J., &
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Johnson and Johnson (1994) identifi
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Design of game-based learning activ
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Findings The students exhibited hig
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We take two instances of character
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In designing Chinese-PP, we instead
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Boticki, I., Looi, C.-K., & Wong, L
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Hwang, G.-J., Sung, H.-Y., Hung, C.
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2000). For example, Filippidis and
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amount of information about the lea
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The factors that affected the stude
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Burguillo, J. C. (2010). Using game
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Wong, L.-H. (2013). Analysis of Stu
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Recognizing both the importance and
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Student responses were coded based
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English with the translations of th
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With her mother’s support, Jane w
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LGC that could occur in any physica
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The significance of the reported st
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Chen, Y.-L., Pan, P.-R., Sung, Y.-T
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them develop new concepts to facili
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Figure 1. Visualization of how mino
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experimental group all the other le
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Procedures All subjects in both gro
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misconceptions corrected by a learn
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exploration environment constructed
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Küçüközer, H., & Kocakülah, S.
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Lin, J.-W., Lai, Y.-C., & Chuang, Y
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The related works Feedback should b
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E 2 1 R 23 N E 5 R 15 E 1 R 13 E 3
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Once the frequent itemsets have bee
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The first phase generates a diagnos
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To assure pretest validity and reli
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Questionnaire and interviews To und
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Maughan, S., Peet, D., & Willmott,
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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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