ERIKA E. SMITH AND RICHARD HAYMAN

10. DECIsIoN MAKING AND PRoBlEMs of
EVIDENCE foR EMERGING
EDUCATIoNAl TECHNoloGIEs

To support what is commonly referred to as twenty-first century learning, those in
decision-making roles are often urged to quickly adopt and integrate the newest
educational technologies and abandon older processes—or risk becoming obsolete.
This impetus to quickly adapt can be witnessed in the discourse surrounding the
impact of technologies in today’s educational landscapes. The past decade has been
witness to considerable discussion regarding the purpose and value of educational
technologies, especially regarding the potential of e-learning to “transform”
learning in the twenty-first century. Those in favour of these innovations, such as
Garrison and Anderson (2003), believe that “E-learning will inevitably transform
all forms of education and learning in the twenty-first century… E-learning cannot
be ignored by those who are seriously committed to enhancing teaching and
learning” (p. 2). As such, many technology advocates see the choice as no longer
concerning if technologies should be used, but rather what and how technologies
will be implemented in the learning environment. As some argue, “Universities no
longer have a choice about whether to implement e-learning: they must in order
to remain competitive in the market place … E-learning is now at the heart of a
university’s core business of learning and teaching” (Kregor, Breslin, & fountain,
2012, p. 1382).
Related to this discussion of educational transformation via technologies around
the turn of the twenty-first century, various depictions of the Net generation or
Millennials as “digital natives” (Prensky, 2001a, 2001b; Tapscott, 1998, 2008)
emerged. Digital natives are purported to: (a) be native speakers of the language
of technology; (b) learn differently from preceding generations of students; and (c)
demand a new way of teaching and learning involving technology (Thomas, 2011,
p. 4). Digital native proponents have been criticized for presenting a problematic
utopian vision of technology that is tied to an exoticized picture of liberated young
people (Buckingham, 2011), with critics arguing that such popular claims regarding
the Net generation as digital natives are largely unsupported by substantive research
evidence. Such critics contend that, rather than being theoretically or empirically
informed, such kinds of discourse about educational and technological transformation
and, relatedly, the debates regarding the needs of digital native students, equate
to a form of “moral panic” that restricts critical and rational consideration
P. Newton & D. Burgess (Eds.), The Best Available Evidence, 147–166.
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E. E. SMITH & R. HAYMAN

(Bennett, Maton, & Kervin, 2008; Smith, 2012, 2013). Indeed, similar tropes
defining a crisis in education, as we will see in the following paragraphs, can be
witnessed in the paradigms informing debates on evidence-based education as well
(Pirrie, 2001). As a result, there is a need to revisit and perhaps redevelop approaches
that enable research-informed decision making regarding emerging technologies in
our educational settings.
With the ever-expanding range of emerging educational technologies that could
be introduced to learning environments, making evidence-informed decisions about
whether and how to effectively use e-learning tools for pedagogical purposes is a
critical yet challenging task. How can educators, learners, and administrators make
informed decisions about the use of particular emerging technologies to achieve
desired pedagogical transformation when, due to their relative newness, there is
often a perceived lack of available and “up-to-the-minute” research on the latest
technological trends that may impede evidence-based educational practice? This is a
key problem of evidence for technology use in higher education.
This chapter discusses several exigent problems of evidence for decision making
regarding emerging technologies, particularly for higher education, beginning with
a brief overview of evidence-based practice (EBP) and twenty-first century learning.
We reflect upon strategies that educational practitioners may employ when facing
a perceived lack of up-to-date evidence to support their decision-making processes.
By discussing strategies for identifying affordances and employing environmental
scanning, we describe approaches for mitigating potential research gaps when
considering use of emerging technologies within academic learning contexts.
EMERGING EDUCATIONAL TECHNOLOGIES
IN THE TWENTY-fIRST CENTURY

Notions of teaching and learning in the twenty-first century involve many diverging
views on and visions of the future of education. However, within this range of
views, a key recurring theme is the need to integrate technology and education
effectively and beneficially in the new century (Brown, 2006; Brown & Adler, 2008;
Garrison & Anderson, 2003). Illustrative of such discussions, Wan and Gut (2008)
asserted the following:
In many ways, new media and information are already changing the way that
we learn and teach in the new century. The field of education is faced with the
challenge of redefining teaching and learning to adapt to a rapidly changing
world and what it means to be a teacher and a student. (p. 175)
In this environment, technology proponents assert that such tools change learning
and should be woven into an interactive and responsive learning space, such that
the virtual classroom is just as important as the physical one. Together, these inform
an institutional context where constant connectedness has become so commonplace
that it is often seen as being inseparable from the twenty-first century learning
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environment itself (although here we prefer the term connectedness, for alternative
discussions of connectivism, see Siemens, 2005). Today, educators and learners
experience education not just through the face-to-face classroom, but also via
hardware and networking infrastructures, learning management systems, social
media, mobile devices, and Internet ubiquity.
Emerging Technologies
Coupled with this focus on transforming learning via an information revolution
happening in the twenty-first century, a core conundrum of the term emerging
technologies is that it is often misunderstood and remains ill-defined despite its
frequent use. Broadly, emerging educational technologies can perhaps be understood
as “tools, concepts, innovations, and advancements utilized in diverse educational
settings…evolving organisms that experience hype cycles…not yet fully understood,
and not yet fully researched” (Veletsianos, 2010, pp. 3–4). Even though they are still
in a developmental stage of design and production, emerging technologies are often
seen as inherently strategic, in that they are tied to aspirations, investment, planning,
and thinking about the future (Einsiedel, 2009).
With this future-looking lens, and reflecting views similar to the e-learning
thinkers already mentioned, emerging technologies experts typically focus on tools
that will be “revolutionary” or that alter traditional relationships and cause social
disruption. for example, technologies that will have broad impacts on day-to-day
life, just as historically the automobile, and more recently the Internet and World
Wide Web, dramatically reshaped the known world (Einsiedel, 2009, pp. 3–4). Given
this future-looking and aspirational focus of those concerned with emergence, a key
challenge surrounding research and policies for such technologies in education,
then, is contextualizing and applying relevant knowledge that can be used today and
in the future, and which will not become quickly out-dated.
Convergence
Amidst all of these discussions of technological emergence, to make sense of the
problems facing those in decision-making roles today, there is great potential in
the notion of the converging technologies as understanding the evolving qualities,
integrations, and merger of such tools. According to McLuhan (2002), changes in
pattern or interaction are of utmost importance: “the ‘message’ of any medium or
technology is the change of scale or pace or pattern that it introduces into human
affairs” (p. 8). The idea of emerging technologies as related to convergence
underscores the fact that many technologies we use have evolved and been
synergized in a unifying way (Kaldis, 2010), building upon and integrating the
qualities of previous technologies. from another standpoint, media convergence
may be understood as “the flow of content across multiple media platforms, the
cooperation of multiple media companies, and the migratory behaviour of media
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audiences” (Jenkins, 2006, p. 2). As such, these technological or media patterns and
scale changes can be seen as the message.
An example of the convergence of emerging technologies is Google Apps
(increasingly used in educational settings), which now combines the traditionally
separate features of email with amalgamated features of calendars, documents, and
talk (voice over IP and chat), and further enhanced by online storage and cloud
software (e.g., for document creation and sharing), to name a few. Another example
can be seen in social microblogs such as Twitter, which has combined previously
discrete forms of short message service (SMS), really simple syndication (RSS)
feeds, direct messages (DM), and weblogs (or blogs), all within a micro 140 character
setup. finally, convergence may be seen in the increasing prominence of a platform
across other technologies; for instance, the increasingly common option to use one’s
facebook, Google+, or Twitter account to login and connect to other third-party
social networking applications, such as Pinterest or Academia.edu. This synergy,
unification, or merging of technologies can be a critical point of consideration when
searching for evidence, particularly for those who use technology in their educational
practice, and one to which we will return in our case study.
Emerging web technologies are increasingly used in academic learning
environments, and include a host of social media tools, such as blogs, wikis,
instant messengers (IM), social bookmarks, podcasts, and vodcasts (Saeed, Yun, &
Sinnappan, 2009). Willcockson and Phelps (2010) provided a useful overview
of emerging technologies, in which they list many social media and web-based
technologies, but also include serious games and virtual worlds. Recent editions of
the New Media Consortium’s annual Horizon Report (Johnson et al., 2013; Johnson,
Adams Becker, Estrada, & freeman, 2014, 2015) have outlined key emerging
technologies that they assert will impact higher education in the next five years,
including ubiquitous social media, massively open online courses (MOOCs), tablet
computing, games and gamification, learning analytics, 3D printing, makerspaces,
and wearable technology. In addition to these sources, and within higher education
specifically, information on trending emerging technologies is easily discoverable
via the ECAR Study of Undergraduate Students and Information Technology (see
EDUCAUSE reports, e.g., Dahlstrom, Walker, & Dziuban, 2013; Dahlstrom &
Bichsel, 2014), not to mention various conferences, journals, magazines, and blogs
all interested in detailing new developments in educational technologies. Notably
for higher education, current discussion about transformation and disruption has
centred to a large extent on MOOCs, a topic with widespread media coverage that is
debated as either a revolutionary game-changer (Leckart, 2012) or as an over-hyped
and problematic venture (Schuman, 2013).
EVIDENCE-BASED PRACTICE IN EDUCATION

As the diversity of chapters included in this publication illustrates, ways of using
the best available evidence in education are much discussed, and there are many
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perspectives on the process and constitution of evidence-based practice (EBP)
and decision making for educational contexts. We can see that relating research
evidence and practice is, unsurprisingly, an important focus for many professional
areas. Evidence-based practice has fully emerged in disciplines such as education,
health care (as illustrated by journals such as Evidence-Based Medicine), and
library and information sciences (for further discussion of evidence-based decision
making in professional library contexts, see Hayman & Smith, 2015). These fields
have influenced one another in their definitions of evidence-based practice, and so
while EBP is intended to have specific disciplinary and professional application,
EBP should be understood broadly as an overwhelmingly interdisciplinary and
interprofessional concept. furthermore, the overlap between evidence and practice
within these disciplines reflects the relationship between research and education
as concomitant endeavours involving the discovery and application of new forms
of knowledge for societal and individual betterment. Clearly, this relationship
is especially relevant to universities whose mandates reflect research-teaching
relationships through educational programs at the undergraduate and graduate level,
and who are increasingly involved in lifelong learning and continuous professional
development programs.
Within discussions of evidence-based education, proponents argue for
transformation through increased incorporation of evidence in education to better
inform policy and practice. for instance, Slavin (2002) saw great promise in an
EBP “scientific revolution” that will change education with a “focus on rigorous
experiments evaluating replicable programs and practices” (p. 15). Similarly,
Davies (1999) argued for an increase in evidence-based approaches that involve
utilizing and establishing high-quality research (systematic reviews and metaanalyses, often relying on scientific means and criteria), to inform a set of principles
and practices that enhance and support professional judgment in the field. Davies
(1999) explicitly noted crossover between these characteristics of evidence-based
education and those in evidence-based healthcare, and likewise Slavin (2002) drew
direct connection to medical interventions and experiments. Such approaches to
evidence-based education have been taken up with goal of improving policy and
practice; for example, through initiatives such as the Best Evidence Encyclopedia
(http://www.bestevidence.org/) created by the Johns Hopkins University Center for
Data-Driven Reform in Education.
Several criticisms have been levelled against such approaches to EBP in education,
including the strong relationship to scientific and quantitative strategies at the
exclusion of other approaches. for example, in response to arguments from thinkers
like Slavin (2002) who advocate for a prescriptive or replicable “what works”
approach to education, Olson (2004) proposed that we must examine critically the
underpinning “beliefs, goals, and intentions of those supposedly affected by the
treatments” (p. 24) offered. Other critics, such as Pirrie (2001), point out that these
arguments reflect a form of “moral panic” that precipitates an inflated “crisis of
legitimation” (p. 124) underscoring the rationale for transformation, a stance similar
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to that presented by Bennett, Maton, and Kervin (2008) in response to problems of
evidence within the digital native debate. What these critics present is a concern
about the limited range of methodologies and toolkits (i.e., those solely reflecting
scientific or instrumental paradigms) accepted as a part of evidence-based education.
Such points underscore the need for critical acknowledgement that research and
education should not and cannot take a context-free, one-size-fits-all-approach.
It is our view that, by being reflexive about these issues, educators conducting
research-informed EBP can intentionally take into account a wider range of paradigms,
methodologies, and strategies in ways that avoid unnecessary prescription. One way
that we may do so is by leveraging emerging frameworks that articulate relational
aspects of practice. Such flexible frameworks, as we outline in more detail below,
can also include approaches to environmental scanning and identifying aims and
affordances that may widen the available sources of useful evidence. In recognizing
both the benefits and limitations of an evidence-based approach, we can balance
the value of evidence-informed decision making with the need for contextualized
practice.
PROBLEMS Of EVIDENCE fOR EMERGING
TECHNOLOGIES IN EDUCATION

As the preceding discussion suggests, discovering information on the features
of new technologies themselves is relatively easy given the variety of sources
describing and forecasting technology trends. However, when little is known about
these technologies in practice, such as how tools in production interface with
existing technological infrastructures, policies, and processes, there still exists
a significant challenge: how do we make informed decisions regarding if, where,
and when new technologies should be incorporated into our teaching and learning
environments? This is the crux of the evidence problem at hand: when it comes to
any given emerging technology, where there is a perceived lack of substantive up-todate research regarding its educational use, value, and impact on pedagogy, how can
we address potential barriers and support evidence-based decision-making models?
Wicked Problems
facing the challenges outlined above, decision makers may see the development
of theoretical and empirical evidence that informs use of emerging technologies in
practice as unavailable, or perhaps as too slow or unrealistic, given the ever-changing
and evolving nature of such innovations. As the nature of these issues are seen to be
complex and constantly changing, it can be helpful to understand decision making
and planning related to emerging educational technologies as an unstructured or
wicked problem.
Particularly relevant to planning and policy development, wicked problems were
first defined by Rittel and Webber (1973) as those societal issues that differ from
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problems of math and science precisely because they do not have clear true-false
answers. In other words, finding “one-best answer” is impossible with wicked
problems, as they do not have a definitive formulation or solution. As a result, rather
than searching for value-free or “true” answers, with wicked problems the (social)
context must inform meaningful and iterative judgment of information to resolve,
rather than solve, the items at hand (Rittel & Webber, 1973). furthermore, there is no
opportunity for trial-and-error testing of the proposed solutions to wicked problems,
for all implementations and decisions (or, attempted reversal of decisions) will
have real-world impacts and consequences that cannot be undone. As Rittel and
Webber argued with an example from education, the “effects of an experimental
curriculum will follow the pupils into their adult lives” (p. 163). Along these same
lines, unstructured decisions are seen as those “decision processes that have not been
encountered in quite the same form and for which no predetermined and explicit
set of ordered responses exists in the organization” (Mintzberg, Raisinghani, &
Théorêt, 1976, p. 246). As we have seen, the characteristics of wicked problems and
unstructured decisions can be witnessed in discussions regarding the conundrum of
emerging technologies and their educational impact.
It is useful to understand the issues surrounding decision-making for emerging
educational technologies through the lenses of unstructured or wicked problems and
EBP in education, since there is often an articulated concern about quickly adapting
to technological innovations that have not been encountered in the same form and for
which there is no pre-set response. Rather than searching for the “one-best answer”
or looking for “the best evidence” or even “best” solutions or practices to follow
as we encounter wicked technological and educational problems, it is instead more
useful to consider approaches to the meaningful and iterative judgment of highquality information within our social and educational contexts.
Identifying Problems of Evidence
While several problems of evidence exist regarding emerging educational
technologies, in this chapter we focus on what we have come to understand as a
perceived lack of new “up-to-the-minute” research on evolving technological
innovations. Through our own professional practice working in technology-enhanced
education settings, this is a concern we face regularly in our own educational
roles, and one that we regularly see in our consultations with other academics and
educators. In seeking to effectively adopt emerging technologies, this perceived
lack of evidence leads to a potentially dichotomous position. Must we: (a) quickly
adopt emerging technologies without applying the evidence, therefore falling short
of a true research-informed decision-making process, or else (b) delay the adoption
cycle until evidence exists, in the form of educational research, but risk missing
opportunities for innovation and being seen as out-dated due to the delay in timeto-adoption? If the problem is presented to us in this manner, as is so frequently the
case, then there is no ready solution and no clear answer.
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However, we argue that several approaches can be used to identify and mitigate
such problems of evidence, approaches that do not limit us to these dichotomous
options. Even though new and emerging technologies can (and do) shape practice, a
lack of formal research around a particular new technology does not mean there is no
useful evidence base of information to be found. The following discussion outlines
the complementary approaches of identifying aims and affordances, along with
environmental scanning, and we argue that these methods can be used to recognize
and address the perceived lack of traditional evidence available for effectively
incorporating new technologies into practice.
APPROACHES TO INfORMED DECISION MAKING
REGARDING EMERGING TECHNOLOGIES

When implementing emerging technologies, there are a variety of possible methods
one can use to address the problem of evidence. In this section we highlight two triedand-tested methods: identifying aims and affordances, and the information seeking
environmental scan. We then use a case study to highlight how these two methods
can be applied in an academic environment for practical results. And while it makes
sense to identify affordances before the conducting the environmental scan, we are
not suggesting that this is a rigid, step-by-step process. Ultimately, we propose that
these are complementary methods that are relational in nature and should be used in
tandem, so that each iteratively informs the other.
Identify Aims and Affordances
When facing a lack of up-to-date evidence on a specific new technology, it is often
helpful for practitioners to (re)focus on the aims and affordances related to the
questions and problems at hand. Willcockson and Phelps (2010) called this focus
“keeping learning central,” and make sound recommendations for examining the
learning theories, learner characteristics, and instructional goals when determining
whether or not to use an emerging technology. This may include determining items of
theoretical or philosophical importance. As Kanuka (2008) aptly demonstrated, we
can best understand technologies in practice by first understanding our philosophies
in practice, to avoid simply following the latest trends by taking time to ask why
what we are doing is important. There is a range of helpful literature and empirical
experiences to draw upon regarding pedagogical strategies and philosophical
underpinnings that can support and align to the educational goals in mind and inform
use of a particular technology.
When implementing emerging technologies for education, Willcockson and
Phelps (2010) recommended finding the connection between the affordances of
the technology being considered for implementation and the learning problem,
objective, or goal it is hoped the technology will address. They defined an affordance
as “the way a technology or software can be used and what it allows the user to do
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or not to do” (para. 9). In other words, an affordance is the characteristic that allows
(or disallows) one to carry out an action within an environment or via an object.
In our physical environment, an example of an affordance is a knob that can be
twisted, or an elevator button that can be pressed. In the virtual world an example
of an affordance is an on-screen button that the user can click or touch when using
a mouse or trackpad or touchscreen, i.e., the button affords clicking. Willcockson
and Phelps provided multiple examples of affordance-learning goal matching, such
as using a wiki to meet the outcome of providing students an online mechanism to
collaborate on content creation, or establishing student blogs to create opportunities
for reflective learning via journaling (para. 10).
The idea of affordances has influenced a number of fields, including industrial
design, human-computer interaction, and instructional design. In designing learning
interactions for the physical or virtual environment, we can leverage the notion
of affordances to make informed choices that can enhance optimal aspects or
reduce sub-optimal ones. for example, certain affordances of educational media or
e-learning technologies may be designed to enable optimal presentation, engagement,
or interaction with material (e.g., via graphics, text, sound, etc.), and when used
according to design principles can aid in comprehension (see, e.g., Clark & Mayer,
2011; Mayer, 2005). By considering affordances or the properties of learning
environments and objects, educators can use instructional design to meet goals, and
to make informed choices about the selection and use educational technologies.
They can intentionally design learning objects that use media features, for instance,
to promote learning, to reduce cognitive load, and ultimately to help learners
achieve the intended learning goals (Rabinowitz & Shaw, 2005, p. 51). Perhaps most
importantly, educators and decision makers can endeavour not to simply forecast
technological trends, but to observe and forecast changes and patterns of interaction
between learners, their environment, and the content.
Speaking generally, to connect pedagogical goals with affordances, we suggest
conducting a literature review or evidence search that seeks other implementations
of comparable pedagogical outcomes achieved with similar technologies (or
similar affordances), to understand the pedagogical and technological impact
in situations akin to the one at hand. During this evidence search the guiding
questions may change, for instance, from “How can I use this emerging technology
in my teaching?” to “How can I design learning, given the affordances available,
to meet this pedagogical goal?” However, it is important to remember that the
affordances discovered within technologies, whether emergent or long-standing,
do not necessarily inherently lead or connect to learning outcomes. As Day and
Lloyd (2007) argued, it is important to recognize that affordances should be
understood as “products of a whole learning context, of which online [and other]
technologies are an integral part, rather than being inherent properties of the
technologies in isolation from the context in which they are used” (p. 20). When
we recommend identifying affordances to inform decision making when facing a
problem of evidence, it is this more broad perspective we envision, a perspective
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that accounts for one’s proposed learning outcomes, learning environment, and
learner characteristics.
The importance of discussing affordances with regard to decision making for
emerging educational technologies here comes back to our earlier point that an
evidence base must be contextualized to the learning goals and outcomes intended.
After identifying learning goals and affordances within our educational setting,
objects, and materials, we can then create an evidence base by searching for and
utilizing existing research literature and empirical observations on similar goals and
affordances. Thus, rather than simply focusing on a current technological trend or on a
newly launched innovation in isolation, there can be a focus on learning from research
on, and experiences with, pedagogical goals and affordances that have existed and
perhaps evolved or converged over time. When we critically examine whether these
characteristics or features can enhance or subvert our intended educational purpose,
we can make informed decisions about how best to work within the constraints of
our circumstances to achieve the desired educational results. If we adhere to the
argument that there exists no one-size-fits-all approach to making evidence-based
decisions that will work for every circumstance, then looking at goals and aligning
the intended outcomes with appropriate affordances becomes a powerful way to find
and refine useful information from similar areas that will hold relevance.
Although emerging technologies are often perceived to be so revolutionary and
new that no formal research around their use exists, it is important to emphasize that
often these technologies build upon and incorporate lessons learned and information
from publications and empirical observation of established features, functionalities,
and affordances. There is a well-established body of literature on educational
strategies, instructional design, and e-learning that can be leveraged when one has
identifiable pedagogical outcomes and affordances in mind, regardless of whether a
particular trend or theme is at play. Thus, we recommend that practitioners seeking
an evidence base should look for recent implementation of similar affordances or
features that may have converged across similar, related technologies, rather than
focus on the one specific technology under consideration. for example, someone
who is considering whether to implement Google Talk for synchronous chat- and
text-based communication in a distance education setting may consult existing
research on chat and talk tools within learning management systems, or within older
or established technologies like Skype and MSN Messenger. Consulting existing
research on converging technologies with similar characteristics that reflect the
particular learning goals to be met through implementation is one recommended
method for addressing the problem of evidence.
Environmental Scanning
When faced with an important decision around adoption of a new technology,
particularly in situations where technology integration is deemed to be required, but
where formal, specific evidence is perceived to be lacking, the use of environmental
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scanning is a tried and tested method of information gathering. Many postsecondary institutions and other organizations do this as part of a strategic and often
future-looking planning process (Gibbs, 1996; Grummon, 2012). In many respects,
the aforementioned ECAR Study and the Horizon Report both use environmental
scanning as the foundation for their reporting.
Environmental scanning takes many forms depending on the discipline or focus
of the scan, and there are various definitions and types depending on the need and
anticipated outcome. from an information-gathering standpoint, the activity of
scanning the environment can perhaps best be understood as the “acquisition and use
of information about events, trends, and relationships in an organization’s external
environment, the knowledge of which would assist management in planning the
organization’s future course of action” (Choo, 2001, para. 1). further to this definition,
Chrusciel (2011) defined an environmental scan as a crucial part of the strategic
planning process for organizations, particularly for identifying quality of service,
customer expectations, and anticipating future needs. However it is worth noting
that an environmental scan itself must be more than just an exercise in information
gathering, and that the resources must be assessed for applicability to one’s situation
and context. As Zhang, Majid, and foo (2010) concluded, the environmental scan
requires important information literacy skills that involve the evaluation and use of
the information discovered, and connecting that use to the intended outcomes.
Though discussions of environmental scanning are often framed within a
managerial or organizational planning lens, we believe that an understanding of these
activities should be expanded to include educational practitioners across all levels
of the institution. The ES can be conducted by undertaking information-gathering,
observation, and experimentation with technologies. In this way, environmental
scanning and information gathering activities can help in constructing shared
knowledge-bases via networks, within communities of practice (Wenger, 1998) and
communities of inquiry (Garrison, Anderson, & Archer, 2000, 2010), both inside and
beyond an individual’s own institutional systems.
To put it simply, when it comes to decisions around new technologies, creating an
evidence base may be realized by establishing an empirical foundation using a range
of strategies that incorporate the experiences, observations, and experimentation
done by others. This is not to devalue the literature review process, which is an
essential undertaking, but rather underscores the importance of going beyond the
extant research literature during the information gathering process, especially when
faced with an initial dearth of recorded evidence. As Alderman, Towers, and Bannah
(2012) described in their study on student feedback mechanisms, “although the main
emphasis is on sources demonstrating evidence-based research supported by sound
theoretical underpinnings, other relevant resources such as observational studies,
reports and conference papers are also taken into account” (p. 262) to inform their
research.
When engaging in decision making with respect to putting new or unfamiliar
technologies into practice, we recommend information seeking via Internet
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searching, one of the most common forms of environmental scanning. The ES
may incorporate readily accessible (public) websites and news sources, along with
sometimes hard to discover reports, white papers, and other informally published
resources traditionally classified as grey literature. The kinds of resources discovered
for the ES may depend on the type of technology and pedagogical setting that is
the subject of the scan, and naturally there are limits to this type of scanning. for
instance, Internet scanning success can be hit-or-miss depending on whether one’s
selected search terms match against indexed metadata recognized by the search
engine being used. Moreover, typically this type of scan will not successfully
discover material in the Deep Web, such as material behind a password-protected
portal (e.g., an institution’s employee-only intranet or LMS), potentially missing
key resources that would be helpful for constructing a more fulsome evidence base.
Nevertheless, to address the problem of evidence this type of scanning is still useful.
Increasingly, social media applications and online social networks can further aid
in environmental scanning. for instance, Academia.edu provides not only availability
of some online resources, but also provides connections to a community of researchers
and practitioners with whom one may discuss issues of interest. Tools for community
building, such as online forums and online news sources, may also prove useful for
connecting with a community of academics, practitioners, or other user groups also
in the midst of exploring similar questions and issues. Of course, ethical and privacy
issues may limit the availability or effectiveness of information shared in online
contexts, however it is not within the scope of this chapter to discuss those items in
detail. Ultimately, the scanner must then account for the credibility and utility of these
resources through applying information-literacy skills, and then determine how these
examples can be applied and contextualized within their own scenario.
In regards to both strategies of identifying aims and affordances and conducting
an environmental scan, clearly each approach should inform the other as decision
makers refine their own understandings and make sense of the available evidence
related to pedagogical aims and outcomes, as well as technological features and
affordances. As a wicked problem, the challenge of finding evidence for emerging
educational technologies may be mitigated by refocusing on the purpose and
characteristics of the pedagogical and technological items at hand.
CASE STUDY: IPADS IN AN ACADEMIC LIBRARY

At this juncture, an example of early adoption of an emerging technology in a
practice-based pedagogical setting is useful. Our case study involves the 2010 launch
of the Apple iPad, which generated immediate educational interest at the time of
release while also maintaining ongoing relevance for today’s educators. It is worth
noting that there are multiple other emerging technology examples we could have
selected to make this case, but at nearly 94% of the market share for tablet products
for education as of late 2013 (AppleInsider, 2013; Cheng, 2013), the dominance of

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iPads in education make it a highly relevant example even today. The case study
is built from one author’s direct experience implementing iPads in an educational
setting shortly after the device appeared on the market, and therefore provides firsthand insights into ES strategies and implementation issues faced with this particular
emerging technology.
Case Study Background
While upon release the iPads received a lot of attention from academic communities,
it should come as no surprise that at that time there was no available academic
research on successful implementation of this specific iPad technology in an
educational setting. The problem of a lack of evidence in this case is a striking
example of how the impetus to quickly adopt a new and emerging technology poses
immediate challenges. With no iPad-specific evidence to consult to assess what
kind of pedagogical impact would emerge when students began taking the devices
into their classrooms, let alone how to address the logistical challenges of ensuring
access, keeping the devices secure, and providing a support mechanism for users,
those seeking to implement iPads in their learning environments required alternative
evidence gathering opportunities.
In 2010, a medium-sized undergraduate university in Alberta, Canada looked
to implement an iPad-lending program through the library. The iPads were made
available to all members of the university community via a sign-out process within
the library, with a focus on availability first and foremost to students. The project
team identified a number of goals for the project, such as meeting the library’s
commitment to introduce new and innovative technologies into the students’
learning experiences, along with a determination to provide users with an option
for mobile computing that went beyond traditional desktop or laptop computers.
The selection of iPads was also influenced by a number of external factors outside
the original scope of the project, including the fact that some faculty members and
instructors were expressing an interest in tablets and ereader technologies, and
that the university bookstore was independently exploring options for etextbooks.
The timely release of the iPad commercially, and its potential for both general and
educational use, presented an excellent opportunity to take this emerging technology
into an academic setting.
Aims and Affordances
The methods discussed above for addressing the lack of evidence were useful in
identifying how best to proceed, first by identifying outcomes and recognizing
affordances, and then via a web-based environmental scan. Regarding affordances,
the project team recognized that some characteristics of iPad technology could be
easily matched to the expressed project outcomes, as illustrated in Table 1.

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Table 1. Connecting affordance to outcome for iPads available via the library
Desired outcome

Technological use or characteristic

Provide mobile computing options for
users to incorporate into their learning

Tablet computer with wireless Internet
connection; mobility provides anytime,
anywhere access

Improve access to ebooks and electronic
scholarly resources and articles

Can be used as an ebook and PDf reader
through web browser or downloadable
applications

Make available to as many users
as possible

Can be easily erased and restored through
centralized account management, does not
need to be attached to a single user

for instance, one driving factor of the project was the desire to improve access
to the ebook and electronic article content available to users via the library’s online
resource collection. Since an iPad can be used as an ereader via the built-in web
browser, via its ability to open common document formats including PDfs, and
through the downloadable iBooks application, this technology provided multiple
options for users seeking mobile access to ebooks and electronic articles.
Upon deeper examination of the technology under consideration, it became clear
that the original iPads contained features that were similar to those found within
existing ereader technologies. Recognizing this convergence, and identifying ereader
affordances as important, led the project manager to consult existing literature about
how various ereaders had been implemented in university and classroom settings.
Ereaders had been commercially available in North America since as early as 2004,
while popular devices including the Sony Reader, Amazon’s Kindle, and Barnes &
Noble’s Nook ensured the adoption of ereader technology, and as such the project
team had little trouble identifying various examples of how ereaders had been
successfully implemented in classrooms and other academic settings. Now more
informed about how those ereader devices had impacted pedagogically on learners and
educators, particularly within the context of higher education settings and academic
libraries, the project team then looked for other convergences. for example, the team
recognized that some education institutions were using other Apple mobile devices,
such as the iPhone and iPod Touch, in their classroom settings. Examining the formal
and informal evidence base from those implementations provided additional insights
regarding what we might expect from the iPad project.
Environmental Scanning
The other recommended method for addressing the lack of research evidence,
conducting an environmental scan, proved invaluable for the success of the iPad
project. Despite the novelty of iPads, web-based environmental scanning was
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helpful in identifying other institutions that had implemented, or were in the
process of implementing, projects also using iPads in their academic settings. As
an information gathering process, this environmental scan relied upon general
Internet searching using keyword searches in a search engine (e.g., targeted to
find institutional materials, etc.), and returned an astounding number of hits that
were not always specific to the project. Sifting through and assessing the results
of this Internet search required patience on the part of those conducting the scan,
a potential shortcoming of this type of information seeking behaviour mentioned
above. However, by revealing where and how similar institutions were using iPads,
especially those in academic library and university settings, the environmental scan
itself was a worthwhile endeavour.
The compiled results of an environmental scan will look different for each
project, but generally speaking should seek to document and categorize each scan
result itself (and its source) for later reference, along with comments on the source’s
utility or application to the project at hand. As shown in Table 2, for the iPad project
scan, results were categorized into two main types: primary sources (e.g., a website
about an existing project) and secondary sources (e.g., a news site which mentioned
a project), accompanied by a note on general information included in the result, and
comments on the source’s overall usefulness for the project at hand.
Table 2. Example – Documenting results of the iPad project environment scan
Scan source Category

Information revealed

Useful for local project?

Project
website

Primary

Existing and current iPad project
at an academic institution;
identifies aims and outcomes;
logistical details outlined.

Yes, very. Logistical items
and aims are of relevance
to this project.

News story

Secondary

Mentions specific iPad project;
gives details of student reception.

Yes. Details of student
engagement especially
helpful.

News story

Secondary

Convergent technology; broad
discussion of ereaders in schools.

No. Not specific enough to
project context or learning
audience.

Academic
article

Secondary

Convergent technology; discusses
learning outcomes met by using
ereaders.

Yes. Educational outcomes
met by ereaders apply to
iPads.

Note: Table data has been adapted for the purposes of this chapter (e.g., sources
anonymized, etc.)

Sources categorized as “primary” are those which yielded the best results related
to the iPad project, in that they typically identified existing and current iPad projects
in a similar university setting. While information contained in the secondary sources
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was less impactful to local implementation than primary sources, it was important
to document and consult secondary sources that identified similar projects using the
same technology or else a convergent technology, no matter whether those projects
were in progress or under development. As discussed below, both primary and
secondary sources may bear additional fruit. Information garnered from the iPad
project environmental scan results included general details (such as over-arching
project goals and desired outcomes), as well as project-specific details about other
institutional iPad lending programs (such as logistical solutions that had yet to
be resolved by the project team). These ES results proved to uncover unique and
useful insights for the local project. Generating this informal evidence base about
other, similar projects, also aided the team in developing successful implementation
criteria at the host institution.
Though not specifically discussed above, we suggest that an important part of
the environmental scan is to follow the most relevant sources as far as possible to
their root. In the case of the iPad project, this meant contacting those responsible for
the projects at similar institutions to informally discuss any methods and evaluation
techniques not explicitly revealed by the environment scan results. The project lead
contacted a number of institutions involved in similar iPad projects in an attempt
to learn more about how those projects were implemented, how they were received
by users, and what impact, if any, their respective projects had on the teaching
and learning process, on service levels, and how those impacts were evaluated or
assessed. Attempting contact in this manner had mixed results, as some respondents
were more than happy to share their experiences, while others declined to share
for various reasons. However, this measure is still worthwhile, since uncovering
additional information from the respondents who did share insights with the project
team in this case proved invaluable.
Overall, the small effort spent reaching out to other institutions paid large
dividends when the project team was able to rely on this connection for sharing
and discussing additional evidence. This extension of the environmental scan
certainly bore additional fruit: in one instance an external contact not only provided
information about their local project, but served as a secondary source, by pointing
toward yet another institution which had not been discovered during the online
search. Arguably, then, despite the ease of electronic environmental scanning via the
Internet, human connections and contexts are still an important component of the
environmental scan, and not to be ignored.
Case Study Summary
As this case study shows, the methods of identifying goals and affordances and
environmental scanning have great potential for building and applying a useful
informal evidence base, especially when also accounting for convergence. With
regard to the iPad project, when applied in tandem, the information gathered during
planning and early implementation more than accounted for the lack of formal
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research evidence, assisting the project team in launching a successful project, as
ultimately revealed by the measures used to evaluate the project. We recognize that
the case study used to support the strategies was based on a specific project with a
readily identifiable technology that would no longer be considered emergent (iPads
are now mainstream technology). Nevertheless, we propose that the case study serves
as a recent, practice-based example of how the methods discussed can be effective
techniques for evidence gathering when considering how best to implement a new,
emerging technology initiative in one’s own educational setting.
CONCLUSION

Making decisions regarding the introduction of emerging educational technologies in
learning environments is not always an easy task. However, the challenges presented
with a perceived lack of up-to-date evidence regarding emerging technologies in
educational practice may be mitigated through a reframing of these issues as wicked
problems. There is value to be gained in widening the paradigmatic approaches to
issues of evidence-based decision making beyond traditional positivistic lenses,
to include alternative frameworks and viewpoints that are relational, iterative,
and flexible, and take into account a range of viewpoints, contextually. We offer
one example of an information gathering framework via the iPad case study,
demonstrating a proposed approach that: (a) identifies aims and affordances, and
(b) employs information seeking via environmental scanning to widen the available
range of useful evidence and support informed decisions regarding emerging
technologies.
As the case study illustrates, environmental scanning can take various forms
depending on the goals, approaches, and disciplinary foci. for the purposes of
integrating emerging technologies into pedagogical practice in the face of problems
of evidence, the environmental scan is a carefully planned search to discover
other instances where the new technology under consideration has been applied
in a similar scenario, or failing that, instances where non-identical but similar
technological affordances have been adopted in a pedagogical setting similar to
that under consideration. Moreover, the environmental scan should be meaningful,
taking into account the educator’s original purpose for integrating the technology
into practice. finding an ideal or exact match is itself a challenge given the large
amount of information available via multiple channels, such as the Internet. This
is why it is of utmost importance to go beyond the extant formal research (or lack
thereof), to carefully plan a wider analysis and engagement of additional empirical
sources and observations, including sharing of information between institutions and
educators.
As we look forward to the wicked problems posed by the educational and
technological opportunities and issues of the future, a deeper discussion of the nature
of technological or media convergence may broadly help to further build responsive
and flexible approaches to such problems of evidence. Greater discussion of whether
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there is, in fact, convergence apparent in the technologies at hand also works to
widen our understanding of a long lineage of scholarship in instructional design and
e-learning that can be leveraged today and in the future, including the rigorous and
established research on similar affordances and patterns of interaction that are so
often reflected in those technologies viewed as new or emerging.
REfERENCES
Alderman, L., Towers, S., & Bannah, S. (2012). Student feedback systems in higher education: A focused
literature review and environmental scan. Quality in Higher Education, 18(3), 261–280. Retrieved
from http://dx.doi.org/10.1080/13538322.2012.730714
AppleInsider. (2013, October 28). Apple’s education sales breached $1B for first time ever in
Q3, iPad share at 94%. AppleInsider. Retrieved from http://appleinsider.com/articles/13/10/28/
apples-education-sales-breached-1b-for-first-time-ever-in-q3-ipad-share-at-94
Baker, B., & Welner, K. G. (2012). Evidence and rigor: Scrutinizing the rhetorical embrace of
evidence-based decision making. Educational Researcher, 41(3), 98–101. Retrieved from
http://dx.doi.org/10.3102/0013189X12440306
Bennett, S., Maton, K., & Kervin, L. (2008). The ‘digital natives’ debate: A critical review of
the evidence. British Journal of Educational Technology, 39(5), 775–786. Retrieved from
http://dx.doi.org/110.1111/j.1467-8535.2007.00793.x
Brown, J. (2006). New learning environments for the 21st century: Exploring the edge. Change: The
Magazine of Higher Learning, 38(5), 18–24.
Brown, J. S., & Adler, R. P. (2008). Minds on fire: Open education, the long tail, and learning 2.0.
EDUCAUSE Review, 43(1), 16–32. Retrieved from http://www.educause.edu/ero
Buckingham, D. (2011). foreword. In M. Thomas (Ed.), Deconstructing digital natives: Young people,
technology and the new literacies (pp. iv–xi). New York, NY: Routledge.
Cheng, R. (2013, October 28). Apple CEO: We’ve locked up 94% of education tablet market. CNET
News. Retrieved from http://news.cnet.com/8301-13579_3-57609699-37/apple-ceo-weve-locked-up94-of-education-tablet-market/
Choo, C. W. (2001). Environmental scanning as information seeking and organizational learning.
Information Research, 7(1). Retrieved from http://www.informationr.net/ir/
Chrusciel, D. (2011). Environmental scan: Influence on strategic direction. Journal of Facilities
Management, 9(1), 7–15. Retrieved from http://dx.doi.org/10.1108/14725961111105691
Clark, R. C., & Mayer, R. E. (2011). E-learning and the science of instruction: Proven guidelines for
consumers and designers of multimedia learning (3rd ed.). San francisco, CA: Pfeiffer.
Dahlstrom, E., & Bichsel, J. (2014). ECAR study of undergraduate students and information technology.
Retrieved
from
http://www.educause.edu/library/resources/study-students-and-informationtechnology-2014
Dahlstrom, E., Walker, J. D., & Dziuban, C. (2013). ECAR study of undergraduate students and
information technology. Louisvile, CO: EDUCAUSE Center for Analysis and Research. Retrieved
from http://www.educause.edu/ecar
Davies, P. (1999). What is evidence-based education? British Journal of Educational Studies, 47(2),
108–121. Retrieved from http://dx.doi.org/10.1111/1467-8527.00106
Day, D., & Lloyd, M. (2007). Affordances of online technologies: More than the properties of the
technology. Australian Educational Computing, 22(2), 17–21. Retrieved from http://acce.edu.au/
journal/
Einsiedel, E. f. (2009). Introduction: Making sense of emerging technologies. In E. f. Einsiedel (Ed.),
Emerging technologies: From hindsight to foresight (pp. 3–9). Vancouver, BC: UBC Press.
Garrison, D. R., & Anderson, T. (2003). E-learning in the 21st century: A framework for research and
practice. New York, NY: Routledgefalmer.

164

DECISION MAKING AND PROBLEMS Of EVIDENCE
Garrison, D. R., Anderson, T., & Archer, W. (2000). Critical inquiry in a text-based environment: Computer
conferencing in higher education. Internet and Higher Education, 2(2/3), 87–105. Retrieved from
http://dx.doi.org/10.1016/S1096-7516(00)00016-6
Garrison, D. R., Anderson, T., & Archer, W. (2010). The first decade of the community of inquiry
framework: A retrospective. Internet and Higher Education, 13(1/2), 5–9. Retrieved from
http://dx.doi.org/10.1016/j.iheduc.2009.10.003
Gibbs, A. (1996). The role of environmental scanning in effective fundraising. New Directions for Higher
Education, 94, 57–67. Retrieved from http://dx.doi.org/ 10.1002/he.36919969408
Grummon, P. H. (2012). A primer on environmental scanning in higher education. Planning For Higher
Education, 41(1), 69–74.
Hayman, R., & Smith E. E. (2015). Sustainable decision making for emerging educational technologies
in libraries. Reference Services Review, 43(1), 7–18. Retrieved from http://dx.doi.org/10.1108/
RSR-08-2014-0037
Jenkins, H. (2006). Convergence culture: Where old and new media collide. New York, NY: New York
University Press.
Johns Hopkins University Center for Data-Driven Reform in Education. (n.d.). Best evidence encyclopedia.
Retrieved from http://www.bestevidence.org/
Johnson, L., Adams Becker, S., Cummins, M., Estrada, V., freeman, A., & Ludgate, H. (2013). NMC
horizon report: 2013 higher education edition. Austin, TX: The New Media Consortium. Retrieved
from http://www.nmc.org/pdf/2013-horizon-report-HE.pdf
Johnson, L., Adams Becker, S., Estrada, V., & freeman, A. (2014). NMC horizon report:
2014 Higher education edition. Austin, TX: The New Media Consortium. Retrieved from
http://www.nmc.org/publication/nmc-horizon-report-2014-higher-education-edition/
Johnson, L., Adams Becker, S., Estrada, V., & freeman, A. (2015). NMC horizon report:
2015 higher education edition. Austin, TX: The New Media Consortium. Retrieved from
http://www.nmc.org/publication/nmc-horizon-report-2015-higher-education-edition/
Kaldis, B. (2010). Converging technologies. In D. Guston (Ed.), Encyclopedia of nanoscience
and
society
(pp.
126–131).
Thousand
Oaks,
CA:
Sage.
Retrieved
from
http://dx.doi.org/10.4135/9781412972093.n71
Kanuka, H. (2008). Understanding e-learning technologies-in-practice through philosophies-in- practice.
In T. Anderson (Ed.), The theory and practice of online learning (2nd ed., pp. 91–118). Edmonton: AU
Press. Retrieved from http://www.aupress.ca/index.php/books/120146
Kregor, G., Breslin, M., & fountain, W. (2012). Experience and beliefs of technology users at an
Australian university: Keys to maximising e-learning potential. Australiasian Journal of Educational
Technology, 28(8), 1382–1404. Retrieved from http://ascilite.org.au/ajet/
Leckart, S. (2012, March 20). The Stanford education experiment could change higher learning forever.
Wired. Retrieved from http://www.wired.com/wiredscience/2012/03/ff_aiclass/3/
Mayer, R. E. (2005). The Cambridge handbook of multimedia learning. Cambridge, UK: University of
Cambridge.
McLuhan, M. (2002). Understanding media: The extensions of man. Cambridge, MA: MIT Press.
Mintzberg, H., Raisinghani, D., & Théorêt, A. (1976). The structure of “unstructured” decision processes.
Administrative Science Quarterly, 21(2), 246–275.
Olson, D. R. (2004). The triumph of hope over experience in the search for “what
works”: A response to Slavin. Educational Researcher, 33(1), 24–26. Retrieved from
http://dx.doi.org/10.3102/0013189X033001024
Pirrie, A. (2001). Evidence-based practice in education: The best medicine? British Journal of Educational
Studies, 49(2), 124–136. Retrieved from http://dx.doi.org/10.1111/1467-8527.t01-1-00167
Prensky, M. (2001a). Digital natives, digital immigrants part 1. On the Horizon, 9(5), 1–6. Retrieved from
http://dx.doi.org/10.1108/10748120110424816
Prensky, M. (2001b). Digital natives, digital immigrants part 2: Do they really think differently? On the
Horizon, 9(6), 1–6. Retrieved from http://dx.doi.org/10.1108/10748120110424843

165

E. E. SMITH & R. HAYMAN
Rabinowitz, M., & Shaw, E. J. (2005). Psychology, instructional design, and the use of technology:
Behavioral, cognitive, and affordances perspectives. Educational Technology, 45, 49–53.
Rittel, H. W. J., & Webber, M. M. (1973). Dilemmas in a general theory of planning. Policy Sciences,
4(2), 155–169.
Saeed, N., Yun, Y., & Sinnappan, S. (2009). Emerging web technologies in higher education: A case of
incorporating blogs, podcasts and social bookmarks in a web programming course based on students’
learning styles and technology preferences. Journal of Educational Technology & Society, 12(4),
98–109.
Schuman, R. (2013, November 19). The king of MOOCs abdicates the throne: Sebastian Thrun and
Udacity’s “pivot” toward corporate training. Slate. Retrieved from http://www.slate.com/articles/
life/education/2013/11/sebastian_thrun_and_udacity_distance_learning_is_unsuccessful_for_most_
students.html
Siemens, G. (2005). Connectivism: A learning theory for the digital age. International Journal of
Instructional Technology & Distance Learning, 2(1). Retrieved from http://www.itdl.org/index.htm
Slavin, R. E. (2002). Evidence-based education policies: Transforming educational practice and research.
Educational Researcher, 31(7), 15–21. http://dx.doi.org/10.3102/0013189X031007015
Slavin, R. E. (2008). Perspectives on evidence-based research in education—What works? Issues in
synthesizing educational program evaluations. Educational Researcher, 37(1), 5–14. Retrieved from
http://dx.doi.org/10.3102/0013189X08314117
Smith, E. E. (2012). The digital native debate in higher education: A comparative analysis of
recent literature. Canadian Journal of Learning and Technology, 38(3). Retrieved from
http://cjlt.csj.ualberta.ca/index.php/cjlt/index
Smith, E. E. (2013). Are adult educators and learners ‘digital immigrants’? Examining the evidence and
impacts for continuing education. Canadian Journal of University Continuing Education, 39(1).
Retrieved from http://ejournals.library.ualberta.ca/index.php/cjuce-rcepu/index
Tapscott, D. (1998). Growing up digital: The rise of the net generation. New York, NY: McGraw-Hill.
Tapscott, D. (2008). Grown up digital: How the net generation is changing your world. New York, NY:
McGraw-Hill.
Thomas, M. (2011). Technology, education, and the discourse of the digital native: Between evangelists
and dissenters. In M. Thomas (Ed.), Deconstructing digital natives: Young people, technology and the
new literacies (pp. 1–11). New York, NY: Routledge.
Veletsianos, G. (2010). A definition of emerging technologies for education. In G. Veletsianos (Ed.),
Emerging technologies in distance education (pp. 3–22). Edmonton: Athabasca University Press.
Retrieved from http://www.aupress.ca/index.php/books/120177
Wan, G., & Gut, D. M. (2008). This issue. Theory into Practice, 47(3), 175–177. Retrieved from
http://dx.doi.org/10.1080/00405840802153700
Wenger, E. (1998). Communities of practice: Learning, meaning, and identity. Cambridge, UK:
Cambridge University Press.
Willcockson, I. U., & Phelps, C. L. (2010). Keeping learning central: A model for implementing
emerging technologies. Medical Education Online, 15. Retrieved from http://dx.doi.org/10.3402/
meo.v15i0.4275
Zhang, X., Majid, S., & foo, S. (2010). Environmental scanning: An application of information
literacy skills at the workplace. Journal of Information Science, 36(6), 719–732. Retrieved from
http://dx.doi.org/10.1177/0165551510385644

166