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Spector, J. M. (2013). Emerging Educational Technologies and Research Directions. Educational Technology & Society, 16 (2), 21–30. Emerging Educational Technologies and Research Directions J. Michael Spector Department of Learning Technologies, University of North Texas, USA // jmspector007@gmail.com Abstract Two recent publications report the emerging technologies that are likely to have a significant impact on learning and instruction: (a) New Media Consortium’s 2011 Horizon Report (Johnson, Smith, Willis, Levine & Haywood, 2011), and (b) A Roadmap for Education Technology funded by the National Science Foundation in the USA (to download the report see http://www.cra.org/ccc/edtech.php). Some of the common technologies mentioned in both reports include personalized learning, mobile technologies, data mining, and learning analytics. This paper analyzes and synthesizes these two reports. Two additional sources are considered in the discussion: (a) the IEEE Technical Committee on Learning Technology’s report on curricula for advanced learning technology, and, (b) the European STELLAR project that is building the foundation for a network of excellence for technology enhanced learning. The analysis focuses on enablers of (e.g., dynamic online formative assessment for complex learning activities) and barriers to (e.g., accessibility and personalizability) to sustained and systemic success in improving learning and instruction with new technologies. In addition, two critical issues cutting across emerging educational technologies are identified and examined as limiting factors – namely, political and policy issues. Promising efforts by several groups (e.g., the National Technology Leadership Coalition, the IEEE Technical Committee on Learning Technology, Networks of Excellence, etc.) will be introduced as alternative ways forward. Implications for research and particular for assessment and evaluation are included in the discussion as means to establish credible criteria for improvement. Keywords Accessibility, Emerging technology, Network of excellence, Online assessment, Personalization Introduction New and more powerful information and communications technologies (ICT) continue to emerge at a rapid pace. Their use in business, government, and the entertainment sectors is widespread and the impact remarkable. E-commerce continues to grow at a rate of about 20% globally and is expected to approach a trillion US dollars in 2013 (JP Morgan, 2008). E-government is now well established at many levels in both developed and developing countries around the globe and particularly critical in times of national and international crisis (United Nations Public Administration Netwrok, 2010). The entertainment industry is perhaps the leader in ICT innovations as demonstrated by the popularity of animated 3D feature-length movies and massively multi-player games on smart phones. Given the growth and impact of ICT in other sectors, it is reasonable to wonder what impact emerging educational technologies will have on learning and instruction and how research might be directed to explore that impact. As it happens, scholars have been exploring the issue of emerging educational technologies and their impact for years. Two recent sources will be discussed in this paper: (a) the New Media Consortium’s (2011) 2011 Horizon Report (Johnson et al, 2011), and (b) Roadmap for Education Technology commission by the National Science Foundation in 2010 (Woolf, 2010). In addition to these two highly regarded sources, two projects that have been exploring emerging educational technologies will also be examined and included in the discussion: (a) the European STELLAR project that is developing a network of excellence for technology enhanced learning (see http://www.stellarnet.eu/), and (b) the IEEE Technical Committee on Learning Technology’s effort to recommend curricula for advanced learning technologies (Hartley, Kinshuk, Koper, Okamoto, & Spector, 2010). The analysis will focus on enablers and barriers for systemic and sustained improvements in making effective use of ICT in learning and instruction. The paper concludes with the role that politics and policy play as enablers of and barriers to technology enhanced learning, along with recommendations for research agendas to promote technology enhanced learning. The 2011 Horizon Report The New Media Consortium, a globally-focused not-for-profit consortium, (see http://www.nmc.org) established the Horizon Project in 2002 to identify and describe emerging technologies that seemed likely to have a significant 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. 21
impact on a variety of sectors around the world. Potential impacts on teaching, learning and creative inquiry have been a focus from the very first Horizon Report. The 2011 Horizon Report (Johnson et al., 2011) includes sections on key trends, critical challenges and technologies to watch. The report identifies six technologies to watch in three time-to-adoption contexts: one year or less, two to three years, and four to five years. In addition to the primary report, there are reports on specific sectors (e.g., K-12) and regions (e.g., Australia). To gain a complete understanding of the report, it is a good idea to look at previous reports and use the new Navigator tool to explore the huge sets of data used to develop the various Horizon Reports; these are available to the general public at no cost on the NMC Website. Key trends The 2011 Horizon Report identified four key trends, all of which also appeared in the 2010 Horizon Report. First, the massive amount of resources and relationship opportunities afforded by the Internet create a continuing need to reexamine the role of an educator with regard to sense-making, coaching, and credentialing. Second, people continue to expect to work, learn and study at their convenience in terms of time and place. Third, work is increasingly collaborative which creates a need to [re-]structure student projects to reflect authentic and realistic contexts likely to be encountered outside study environments. Fourth, technologies are increasingly cloud-based. Taken together, these trends suggest that learning environments should be more collaborative and that they should make use of tools, technologies, processes and resources likely to be encountered in the workplace. While this is not ground-shaking news to educational technologists and researchers, the implications for schools really are ground-shaking in the sense that significant transformations need to occur if schools are to be responsive to such trends. Critical challenges Four critical challenges are also identified in the 2011 Horizon Report (Johnson et al., 2011). First and foremost, digital media literacy is again ranked as the most important challenge. In order to maintain currency with emerging technologies and the trends previously described, being literate in the area of digital media is vital. Digital literacy is a multi-faceted skill that covers the ability to find, use, interpret, modify, and create a variety of digital media. Falling behind in this area contributes to the digital divide, which is widening just when accessibility and resources are expanding. A second significant challenge is in the area of evaluation metrics, which was noted in 2010 as well. The challenge in this area is in part because much of the research being conducted is designed for earlier forms of education resulting in no significant differences being found for new forms of education. Third, economic pressures associated with new media are challenging traditional forms of education to compete in novel ways. In response to the trend for teaching and learning anywhere and anytime, online universities and programs are attracting increasing numbers of students causing traditional universities to compete for students who would have been presumed to prefer traditional universities. Fourth, due to the proliferation of information, resources, tools and devices, it is increasingly difficult for teachers and students to maintain their knowledge and skills. As would be expected, the challenges are closely connected with the trends noted earlier. It is worth noting here that the challenge of developing appropriate evaluation metrics, along with associated assessments, is especially important in the sense that without such metrics, progress in any of the areas mentioned is merely speculative. This issue arises in the NSF Roadmap to be discussed in a subsequent section. Technologies to watch In the near term (one year or less), the report identifies two technologies, consistent with findings in previous years: electronic books and mobile devices. Both of these are well known and have already made their way in educational contexts. Moreover, they are consistent with the trends and challenges presented previously. Electronic books add to the wealth of information and resources available on the Internet, but they may not be accessible to everyone. Mobile devices do allow people to learning almost anywhere at their convenience, but keeping pace with new mobile devices is a challenge and there are places where the devices or the networks to facilitate their use are not accessible or affordable. 22
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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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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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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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