Title: Anticipating future learning paradigms: Will mLearning survive? Author: Prof Dr Tom H Brown Associate Professor Institute for Open and Distance Learning College of Graduate Studies University of South Africa South Africa Address: IODL, Robert Sobukwe Building G02, Skinner Street, Pretoria
Email:
[email protected] Tel: +27 (0)12 337 6180 Mobile: +27 (0)82 882 4669
Abstract The adoption of mobile technologies - especially smartphones and tablets - into teaching and learning environments was very slow at the turn of the millennium. However, the rapid developments with regards to mobile and wireless technologies sparked, on a global scale, a growing interest in mLearning (mobile learning). By 2005, there were already a significant number of applications for mobile technologies. Recent market research reports that global smartphone sales have passed the 1 billion mark in 2013 (CCS Insight, 2013) and close to 220 million tablets were sold worldwide in 2013 (Statista, 2014). It clearly seems - from the number projects, research and keen adoption of mLearning in various educational environments - that mLearning is experiencing exponential growth and is thriving in contemporary learning paradigms. However, cognizance needs to be taken of the fact that ICT (information and communication technology) developments are impacting educational practice and that we will most probably, in the near future, experience shifts in learning paradigms. This paper explores what new learning paradigms may look like in future. It then, based on an analysis of what future learning paradigms and future learning skills may look like, explores whether mLearning would still thrive in these new learning paradigms. Keywords: mLearning; mobile learning; navigationism; connectivism; beyond constructivism; mobile technology; learning paradigms Highlights: • Defining mLearning • Why is mLearning growing so rapidly? • mLearning is thriving in contemporary learning paradigms • Paradigm shifts during the past few decades • A view into the near future • What will future learning paradigms look like? • Navigating skills required to survive in future mLearning environments • mLearning has caught the social constructivism wave and is enjoying the surfing on the crust of the current learning paradigm. • mLearning might be thriving at the moment, but it is still a long way from maturity. • mLearning, however, will continue to grow. • mLearning can reach maturity with innovative mLearning devices and mLearning applications designed for a navigationism paradigm. • mLearning will not just survive in future learning paradigms – it will thrive!
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Anticipating future learning paradigms: Will mLearning survive? Abstract The adoption of mobile technologies - especially smartphones and tablets - into teaching and learning environments was very slow at the turn of the millennium. However, the rapid developments with regards to mobile and wireless technologies sparked, on a global scale, a growing interest in mLearning (mobile learning). By 2005, there were already a significant number of applications for mobile technologies. Recent market research reports that global smartphone sales have passed the 1 billion mark in 2013 (CCS Insight, 2013) and close to 220 million tablets were sold worldwide in 2013 (Statista, 2014). It clearly seems - from the number projects, research and keen adoption of mLearning in various educational environments - that mLearning is experiencing exponential growth and is thriving in contemporary learning paradigms. However, cognizance needs to be taken of the fact that ICT (information and communication technology) developments are impacting educational practice and that we will most probably, in the near future, experience shifts in learning paradigms. This paper explores what new learning paradigms may look like in future. It then, based on an analysis of what future learning paradigms and future learning skills may look like, explores whether mLearning would still thrive in these new learning paradigms. 1.
Introduction
E-learning emerged as an educational concept in the 1990s due to the Internet, WWW and e-mail. Wireless communication received a steady boost when mobile phones reached the market. As the turn of the millennium approached, landline telephones and wired computers were beginning to be overtaken in popularity by wireless technologies. Recent statistics provided by the Central Intelligence Agency (CIA), USA, states that in 2012, 83.3% of the world’s population had a mobile phone (World FactBook, 2012). In some of the leading technology countries, like Finland, there are almost twice as many mobile phones as there are people (176.9%). And in Africa, countries like Botswana and South Africa has a ratio of 1.42 mobile phones towards population (142%). Recent market research reports that global smartphone sales have passed the 1 billion mark in 2013 (CCS Insight, 2013) and close to 220 million tablets were sold worldwide in 2013 (Statista, 2014). Since the early 2000s, educators started to experiment with wireless and mobile technologies and the concept of mLearning started to emerge. The adoption of mobile technologies into teaching and learning environments was very slow at first. However, the rapid developments with regards to mobile and wireless technologies sparked, on a global scale, a growing interest in mLearning (mobile learning). By 2005, there were already a significant number of applications for mobile technologies in education. During the past few years there has been a significant growth in the development of mLearning applications and resources. Multimedia content is but one example, with mobile video being estimated to increase fourteen-fold between 2013 and 2018 (Cisco, 2014). 2.
Towards defining mLearning
During the first decade of the 21st century much attention was given to defining mLearning, as well as the development of theoretical and pedagogical frameworks for mLearning. Nyiri stated it clearly and correctly that “communication is the source from which mLearning emerges” (Nyiri, 2002:1). Some argued that eLearning is the macro concept that includes online 2
and mLearning environments and therefore mLearning is a subset of e-learning. The following definition of Quin (2001) usefully described mLearning as follows in the early conceptional days of mLearning: “mLearning is e-learning through mobile computational devices: Palms, Windows CE machines, even your digital cell phone.” (Quin, 2001:1) A decade after this first definition, Quin confirmed that: “m-Learning is more significant than elearning, although retaining core e-learning features (Quinn, 2012). Moczarny, de Villiers and van Biljon added to this insight by stating that e-Learning and m-learning have shared, as well as independent, attributes (Moczarny, de Villiers and van Biljon, 2012). Another useful view is that of Sharples, Taylor and Vavoula (2007) when they suggest that an mlearning system includes, but is not limited to, three social factors – control (teachers, learners, technology), context (people, interactive technology, learning situation) and communication (via digital formats). One of the early definitions of mLearning that still remains the most simple and generally accepted, is the one by Parsons and Ryu: “mLearning is broadly defined as the delivery of learning content to learners utilizing mobile computing devices (Parsons & Ryu, 2006)” David Parsons (2014) took a new approach to defining mLearning by discussing a number of myths or misperceptions about mLearning, thereby stating what it is not in order to establish a meaningful description of hat mLearning actually is. In summary, reflecting on all the myths discussed and moving towards a suitable and contemporary definition of mLearning, I would like to echo the words of David Parsons (2014): "To ensure that future mLearning systems meet their full potential, it is necessary that our understanding of mLearning encompasses all of its unique characteristics, and that we recognize that any form of learning that takes pace using a mobile device is mLearning, whether on the move or static, whether in formal or informal settings, whether working collaboratively or alone."
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The exponential growth of mLearning
There was in the early 2000s globally a rapid rate in the development and application of wireless and mobile technologies in contemporary learning environments and learning paradigms. Statistics like the following from Empowering Technologies Incorporated (http://www.empoweringtechnologies.net/mobile.htm), cited by Kristiansen (2001:5), have been acknowledged and cited by numerous papers and articles: • “Over 50% of all employees spend up to half of their time outside the office. • More than 525 million web-enabled phones will be shipped by 2003. • World-wide mobile commerce market will reach $200 billion by 2004. • There will be more than 1 billion wireless Internet subscribers world-wide by 2005. • Multi-purpose handheld devices (PDA and telephone) will outsell laptop/desktop computers combined by 2005. • Most major US companies will either switch to or adopt wireless networks by 2008.” Most of these predictions were actually surpassed and many more predictions that followed between 2002-2012 were made and surpassed as well.
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mLearning grew (and is still growing) even more rapidly in rural Africa. Due to the lack of infrastructure for ICT in rural areas in Africa (cabling for Internet and telecom), the growth of wireless infrastructure was significant. Between 1997 and 2001, the number of mobile phone subscribers in Africa annually had a triple-digit growth rate (Shapshak, 2002). In 1999 Tokyo had more telecom connections than Africa combined. In 2003 Africa had twice as much as Tokyo (Gourley, 2004). Mobile subscribers in Africa have increased by over 1000% between 1998 and 2003 to reach 51.8m (ITU, 2004). This trend continued through the past decade. It is therefore clear that Africa is leapfrogging from an unwired, non-existent e-learning infrastructure to a wireless e-learning infrastructure. There are already many mLearning activities and projects in Africa – from the use of mobile devices (e.g. tablets and smartphones) in assessment strategies (e.g. the clinical assessment of medical students) and in wireless learning environments (e.g. engineering students for collaboration and coursework), to the use of text messaging (SMS) on the most basic mobile phones for learning support. For example: The University of Pretoria started using mobile phone support during 2002 in three paper-based distance education programs due to the fact that more than 99% of the ‘rural students’ had mobile phones (Brown, 2004). According to Brown (2004) we can differentiate between two ideal target markets for mLearning: • learners that are either without wired/fixed line infrastructure and access (i.e. 3rd world rural or remote area learners who have mobile phones, and • learners that are continually on the move (i.e. 1st world learners who are the workforce on the move with state of the art mobile devices). 4.
Why is mLearning growing so rapidly?
Soloway remarked that: “For the first time in ICT history, we have the right time, the right place and the right idea to have a huge impact on education: handheld computing.” Soloway (2003) The increased access to mobile devices, the availability of support systems and the need for communication paved the way for learning to be available anytime, everywhere. The following technological developments and the rich capabilities of mobile technologies, together with the growing demand to provide learning opportunities on-the-go, are some of the key reasons why mLearning is thriving: • mLearning provides more mobility, flexibility and convenience than desktop-based online learning. • Life-long learning demands learn while you earn which is possible through e-learning. mLearning takes it further and makes it possible to learn while you earn on-the-go. • MMS makes it possible to deliver and receive multimedia content such as audio, images and video sequences. • m-LMSs (Learning Management Systems for mLearning) emerged during the mid to latter 2000s. • Interoperability with e-mail and the Internet is key to new developments. Web 2.0provides technologies without the user having to select or intervene. • Integrating EPSS (Electronic Performance Support Systems) into the mobile environment will take mLearning even further: mLearning with on-demand access to information, tools, learning feedback, advice, support, learning materials, etc. Keegan (2003) rightfully stated that the mixing of distance learning with mobile telephony to produce mLearning will provide the future of learning. The impact of mLearning does not, however, depend on technological developments only. The ability of educationists to design and develop didactical and pedagogical sound mLearning opportunities and mLearning environments that enhances learning is more important. In order to 4
optimize teaching and learning in the new mLearning environments, we need to properly understand contemporary learning theory and learning paradigms. 5.
mLearning is thriving in contemporary learning paradigms
The following words of wisdom from John Seely Brown is very applicable here: “If we could find a way to support and tap the community mind we might have a whole new way to accelerate learning and to capture and structure knowledge assets in the making…” Brown (1999:10) The role that communication and interaction plays in the learning process is a critical success factor in contemporary learning paradigms. Mobile technologies provide opportunities for the optimizing of interaction and communication between educators and learners, among learners and among members of communities of practice (COPs) . mLearning enhances collaborative, cooperative and active learning. mLearning thrives within the contemporary social constructivist paradigm because of its richness in terms of communication and interaction, both synchronous and asynchronous. In addition, mobile devices allow users an interactive, user-friendly and immediate access to social media through mobile apps. This makes mobile devices an extremely frequent tool in the daily lives of learners, contributing to the rapid growth of mLearning. 6.
Paradigm shifts during the past few decades
Traditionally, teaching and learning focused on the learner’s mastery of particular (pre)identified content. Lecturers were seen as the most significant source of knowledge and their role was to transfer their knowledge to the learners. In contrast, teaching and learning during the past few decades, were not focused on the mastery of content per se, but rather on the production of new knowledge - a constructivist approach. Educators (e.g. lecturers and teachers) form merely one spectrum of the sources of knowledge and their role is to facilitate learning and to assist learners in producing new knowledge. The paradigm shifts that we have experienced in the 20th century are well known to us. These are:
In the early 2000s, constructivist approaches were also making way for social constructivism. COPs or Communities of Practice (and Communities of Learning) were evolving and beginning to play a significant role in teaching and learning environments. The focus is on the effective and 5
productive use of existing, social and natural resources for learning. The real expert is not the lecturer, or any other person for that matter, but the community of practice (COP).
Although mLearning is experiencing exponential growth and is thriving in contemporary learning paradigms, cognizance needs to be taken of the fact that ICT developments are impacting educational practice and that we will, in the near future, experience shifts in learning paradigms. What will these new learning paradigms look like? Will mLearning still thrive in these new learning paradigms? Will mLearning survive at all? 7.
A view into the near future
We have already started to experience some interesting changes in the role of teaching and learning since the turn of the millennium. While the role of the teacher first shifted from ‘teaching’ to ‘learning facilitation’ during the latter part of the 20th century, the most recent shift is towards ‘facilitated and supported enquiry’. ''Inquiry into authentic questions generated from student experiences is [now] the central strategy for teaching’’ Soloway (2003) During the early 2000s the European Union identified a number of aims for teaching and learning by 2010. Here are some of the highlights taken from the European Union’s aims for 2010 (Oliveira, 2003):
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We should experience a shift from PC centeredness to ambient intelligence: o personalized and for all users o surrounding environment is the interface o technology is almost invisible o infinite bandwidth and full multimedia o almost 100% online community o focus on maximizing the learning process and its impact Innovations in learning that we should expect are: o personalized and adaptive learning o dynamic mentoring systems o integrating experienced based learning into the classroom o research on new methods and new approaches to learning with ICT We should experience the following changes with regards to learning resources: o dynamically adapt learning resources to individual needs and preferences o digital learning resources and professional learning for work o platforms supporting collaborative learning In terms of access the following should be important: o mLearning and interface technologies 6
•
o supported inquiry (guided research) [my version: facilitated and supported inquiry] o from courseware to performanceware The focus should be on: o Collaboration and discourse o Learning in context and task-sensitive o ICT an integrated part of learning process
It is interesting to note that many of these aims did in fact realize. And those aims that have not fully been achieved yet are already emerging or in development. Recent mLearning developments addresses a vast range of applications and innovations, including amongst other, the integration of formal and informal learning (e.g. Bull et al, 2008), audio-rich language learning (e.g. Nova et al, 2005), contextual and situated learning (e.g. Park, 2011), location awareness through the use of GPS functionalities (e.g. Chu et al, 2010), simulations and gaming (serious games)(e.g. Sanchez et al, 2011), augmented reality (e.g. Fitzgerald et al, 2012), collaborative learning and interactivity, social constructivism e.g. class-sourcing (Tsipursky, 2013), integrating social media affordances in learning environments (e.g. Mao, 2014), personalized learning and personal learning environments (e.g. Dabbagh & Kitsantas, 2012), as well personal publishing. The wealth (volume) and richness of contemporary mLearning environments, mLearning resources, mLearning applications and mLearning technologies are as exciting as much as it holds promise for the future ahead. 8.
What will future learning paradigms look like?
At the present point in time we are already experiencing demanding challenges in coping with the vast volumes of available information. Brown (2006) contemplates that: “It is difficult to imagine what it will be like when the knowledge economy is in its prime... “ Bontis (2002:22) provided the following alarming estimations with regards to the doubling of the world’s knowledge: “While the world’s codified knowledge base (i.e. all historical information in printed books and electronic files) doubled every 30 years in the earlier part of this century, it was doubling every seven years by the 1970s. Information library researchers say that by the year 2010, the world’s codified knowledge will double every 11 hours.” I do not think we reached the 11 hours milestone by 2010 as predicted, but we should probably be very close to that now in 2014. Brown (2006) challenges our thoughts by saying the following in reply to the estimation that the world’s knowledge would double every 11 hours: “Just imagine the extensive information overload we will experience in a situation where the world’s knowledge doubles every 11 hours! Not even to think about the growth after that...” This makes one to wonder about future learning paradigms and what they will look like. The knowledge economy and the accompanying commoditization of knowledge and available information, have prompted a further step in the process. Therefore contemporary educational paradigms focus not only on the production of knowledge, but are beginning to focus more and more on the effective application, integration and manipulation of existing information and knowledge. Restak (2003:57) posits that, within the modern age, we must be able to process information rapidly, function amidst chaotic surroundings, always remain prepared to shift quickly from one activity to another and redirect attention between competing tasks without losing time. A new type 7
of literacy emerged during the turn of the century, namely information navigation. Brown (1999:6) describes this as follows: “I believe that the real literacy of tomorrow will have more to do with being able to be your own private, personal reference librarian, one that knows how to navigate through the incredible, confusing, complex information spaces and feel comfortable and located in doing that. So navigation will be a new form of literacy if not the main form of literacy for the 21st century.” This notion of “information navigation” also relates to metaliteracy in the field of information and digital literacy. Mackey and Jacobson (2011) state that information-literate individuals require the ability to understand information using various forms of technology. We have already experienced significant challenges in coping with the abundance of available information. Simultaneously, our social lives and social interaction have been powered up a few gears through the rapid developments in social media and social networks. It is difficult to imagine what it will be like when the knowledge era and digital age is in its prime... The future scenario will have a serious impact on information processing and most definitely on our learning processes and learning paradigms that are currently still very much founded in a content and knowledge production paradigm. Over the past few decades, most of our teaching and learning activities were and still are based on a constructivist learning paradigm. What will future learning paradigms then look like? Figure 1 below, adopted from Brown (2006:114), summarizes the paradigm shifts we have experienced in the past and proposes a possible paradigm shift envisaged for the future. A discussion of the paradigm shifts as shown in Figure 1 is presented in Table 3 (Brown, 2006:115).
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Exploring and anticipating learning paradigms beyond constructivism
Past
Present
Future
Knowledge Adoption
Knowledge Production
Knowledge Navigation
rote learning
active and productive learning
navigating, connecting, evaulating, integrating, problem solving and communicating
behaviourism
constructivism
navigationism social constructivism
teaching / instruction
learning facilitation
mentoring and coaching guided research / supported inquiry
The teacher is the primary source of knowledge [source of the WHAT]
The teacher is one of the sources of knowledge [source of the WHAT and assisting with the HOW]
Knowledge creation is for some elites and knowledge is already in place
Knowledge creation / production is the central issue
The focus of learning is on gaining knowledge
The focus of learning is on creating knowledge
The teacher is the source of skills and competencies required to navigate [source of the HOW] Knowledge creation is a side/implied issue. The central issue is to be able to navigate within the enormous knowledge explosion The focus of learning is on navigating in the ocean of available knowledge
Figure 1: Exploring and anticipating learning paradigms beyond constructivism (Brown, 2006)
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It is as sad as it is worrying to observe that we, as educationists, are still operating within a ‘content-driven’ paradigm. We provide our learners with preselected, and carefully designed and developed content. It seems as if the purpose of our teaching and learning activities are still rooted in the mastery of (preselected) content instead of the achievement of learning outcomes. Not even mentioning the importance of empowering our learners to be able to function successfully in their demanding world of work and life, underpinned with information and knowledge navigation. (Brown, 2006) In this regard, I fully support Barber, Donnelly & Rizvi (2013) that “an avalanche is coming” and I echo that there lies a “revolution ahead”. I argue (Brown, 2006) that navigationism might be the new learning paradigm that lies ahead, beyond constructivism. In fact, I would argue that it is already here and it is maturing fast! In a navigationist learning paradigm, learners should be able to find, identify, manipulate and evaluate information and knowledge, to integrate this knowledge in their world of work and life, to solve problems and to communicate this knowledge to others. Now let’s summarize the preceding discussion and the paradigm shifts in education. Tables 4 and 5 (Brown, 2006:118) provide a concise summary of the past and envisaged educational paradigm shifts, as well as the past and envisaged role changes of role players within teaching and learning environments.
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I would like to argue, as in Brown (2006), that ‘navigationism’ might be the new learning paradigm that lies beyond constructivism. We are also convinced that constructivism is a big step we took over a long period of time though [about 70 years] in the development of learning theory as we know it now. I also believe that we are at the brink of a new learning paradigm breakthrough. Constructivism has been the learning paradigm during the past few decades. And social constructivism is also in our mind an intermediate or sub-step forward towards the new learning paradigm. ICT developments are impacting educational practice and we will, in the near future, experience shifts in learning paradigms. 9.
Navigating skills required to survive in future mLearning environments
Now that the new learning paradigm of navigationism has been briefly discussed, it will be useful to explore the type of skills that are required within such a paradigm. Technological developments continuously introduce new and alternative views about our interaction with information and people, and about the skills and competencies we require to survive in the knowledge era, or, as coined by Barber et al. (2013), to survive the “revolution ahead”. They talk about the sheer quantity of information that has grown exponentially, and state that “content is ubiquitous” (Barber et al. 2013:16). Some of the underlying or fundamental skills required are problem solving skills, digital literacy skills, information literacy, visual media literacy, as well as psychological and emotional competence. Let us draw from the work of some researchers in the field in order to identify the type of skills and competencies that is required in the knowledge era. George Siemens describes connectivism as: “the integration of principles explored by chaos, network, and complexity and self-organization theories.” (Siemens, 2004:5). This is a very useful definition to describe the complex learning environments in the knowledge era. By 9
analyzing the elements and principles of connectivism as described by Siemens, we are able to identify several important skills that learners require within a navigationist learning paradigm. Siemens (2004:5) continues with his description of connectivism by saying that the learning process: “...is focused on connecting specialized information sets, and the connections that enable us to learn are more important than our current state of knowing.” He also states that: “connectivism is driven by the understanding that decisions are based on rapidly altering foundations. New information is continually being acquired. The ability to draw distinctions between important and unimportant information is vital. The ability to recognize when new information alters the landscape based on decisions made yesterday is also critical.” All these skills required in a connectivist learning paradigm are also essential navigating skills for the knowledge era. In addition to these skills, the following are some examples of the skills and competencies required in a navigationist paradigm (Brown, 2006): • The ability - know-how and know-where - to find relevant and up-to-date information, as well as the skills required to contribute meaningfully to the knowledge production process. This includes the mastery of networking skills and skills required to be part of and contribute meaningfully to communities of practice and communities of learning. This implies that the basic communication, negotiation and social skills should be in place. • The ability to identify, analyze, synthesize and evaluate connections and patterns. • The ability to contextualize and integrate information across different forms of information. • The ability to reconfigure, re-present and communicate information. • The ability to manage information (identify, analyze, organize, classify, assess, evaluate, etc.). • The ability to distinguish between meaningful and irrelevant information for the specific task at hand or problem to be solved. • The ability to distinguish between valid alternate views and fundamentally flawed information. • Sense making and chaos management. • Information literacy and metaliteracy (Mackey & Jacobson, 2011). Mackey and Jacobson (2011) postulates that social media and collaborative online communities require metaliteracy that supports multiple literacy types. “Social media environments are transient, collaborative, and free-flowing, requiring a comprehensive understanding of information to critically evaluate, share, and produce content in multiple forms.” (Mackey & Jacobson, 2011:62). “They apply information knowledge gained from a wide range of verbal, print, media, and online sources and continuously refine skills over time.” (Mackey & Jacobson, 2011:70) The following list is a selection of Siemens’ principles of connectivism (Siemens, 2004). It provides a summary of the connectivist learning skills and principles required within a navigationist learning paradigm: • Learning is a process of connecting specialized nodes or information sources. • Capacity to know more is more critical than what is currently known. • Nurturing and maintaining connections is needed to facilitate continual learning. • Ability to see connections between fields, ideas, and concepts is a core skill. • Currency (accurate, up-to-date knowledge) is the intent of all connectivist learning activities. • Decision-making is in itself a learning process. Choosing what to learn and the meaning of incoming information is seen through the lens of a shifting reality. While there is a right answer now, it may be wrong tomorrow due to alterations in the information climate affecting the decision. David Passig (2001) explores ICT mediated future thinking skills. His work traces the basic nature of future society and proposes a relevant taxonomy of future cognitive skills with 10
appropriate tools to succeed in the future. Passig states that in the knowledge era there is a need for unique cognitive skills in order to process information successfully in real time. He continues by saying that those who will have the skills of collecting information in real time, as well as the ability to analyze, classify, and organize it, will be those to achieve a social, cultural and economic advantage. (Passig, 2001) It is important to note from his statement that most of the intellectual activity will be to “amplify the value of available information” (Passig, 2001). The knowledge age acknowledges the fact that the rate of information overflow will be accelerated, and that the main role of people will be to add value to the exchange of information (Harkins 1992 & O'Dell, 1998, in Passig, 2001). Passig (2001) explores further and uses Bloom’s taxonomy as a working platform, and then expands the categories to reflect the needs of the future. Passig’s work provides very useful suggestions and insight into the new type of cognitive skills that learners requires and will more so require in the near future. The following is a meaningful list of navigating skills that can be drawn from the work of Passig: • To know where to find useful information and to master search strategies. • To develop new symbols, codes and conventions. • To expand existing models of thinking and to create inferences and analogies. • To analyze pieces of information in various ways and to make new connections. • To distinguish relationships between fragments of information and to create new relations. • To evaluate the reliability of information keeping in mind the influence of time, context and personal interpretation. • To locate a separate element out of the pieces of information that it was taken from in order to create a new meaning. • To choose the suitable combination of information and implement it in problem solving in different situations. • To create consonance - an agreement/harmony/accord/personal new logical connection between two domains that seemed distant from each other. • To create association - the mental notion of connection or relation between thoughts, feelings, ideas or sensations. The list of navigating skills and competencies required within a navigationist paradigm that is provided in the preceding paragraphs, and adopted from Brown (2006), is far from complete. What is provided here should be regarded as examples. Much research is required to refine the definition of navigationism and the description of a navigationist learning paradigm. The list of navigationist skills and competencies should be further developed and refined. 10.
Conclusion
Now let us get back to the question: Will mLearning survive in future learning paradigms? mLearning has caught the social constructivism wave and is enjoying the surfing on the crust of the current learning paradigm. However, the questions at hand are: Are we ready to take the leap to the next learning paradigm? Will mLearning surf the next wave or be washed out on shore? Are we planning for and anticipating the future? What is the quality of learning in current mLearning environments? Is technology driving learning or are we adapting and using technology to optimize learning? Are we slapping new technological tools onto old teaching methods or are we focusing on the innovative and transformative use of technology in new teaching and new learning paradigms? mLearning might be thriving at the moment, but it is still a long way from maturity. mLearning, however, will continue to grow. Mobile technologies and new mobile tools geared towards accessing and manipulating information will provide new opportunities for knowledge navigation. mLearning can reach maturity with innovative mLearning devices and mLearning applications designed for a navigationism paradigm. mLearning will not just survive in future 11
learning paradigms – it will thrive! The important issue to highlight is that mLearning technologies and devices provide learning environments in which teaching and learning that enhances navigationist and connectivist learning, can be optimized. It provides fertile soil in which navigating and connectivist skills and competencies can flourish. Our first challenge as educators is to design and develop appropriate learning environments, based on sound pedagogical and didactical principles that will ensure the optimization of learning in navigationist mLearning environments. Our second challenge as mLearning and educational technology experts is to keep abreast of developments in learning theory and to identify and anticipate shifts in learning paradigms to be able to adopt and adapt educational technologies that will ensure the optimization of learning in the knowledge era. References Barber, M., K. Donnelly and S. Rizvi. (2013). An avalanche is coming: Higher education and the revolution ahead. Paper published by the Institute for Public Policy Research, London, UK. http:/www.ippr.org/publications/an-avalanche-is-coming-highereducation-and-the-revolution-ahead Bontis, N. (2002). The rising star of the Chief Knowledge Officer. Ivey Business Journal, March/April 2002:20-25. Brown, J. S. (1999). Learning, Working & Playing in the Digital Age. Paper delivered at the 1999 Conference on Higher Education of the American Association for Higher Education, March 1999, Washington, USA. Brown, T. H. (2004). The role of mLearning in the future of e-learning in Africa? Chapter in the book: Distance Education and Technology: Issues and Practice. Open University of Hong Kong Press, Hong Kong, China. Brown, T.H. (2006). Beyond constructivism: Navigationism in the knowledge era. On the Horizon, 14(3):108-120, Emerald Group Publishing limited, Bradford, UK. http://www.emeraldinsight.com/journals.htm?articleid=1567661&show=abstract Bull, G., Thompson, A., Searson, M., Garofalo, J., Park, J., Young, C. & Lee, J. (2008). Connecting Informal and Formal Learning Experiences in the Age of Participatory Media. Contemporary Issues in Technology and Teacher Education, 8(2):100-107. AACE. CCS Insight, (2013). 4G Gathers Momentum as Smartphones Smash One Billion Units in 2013. Available at: http://www.ccsinsight.com/press/company-news/1724-4ggathers-momentum-as-smartphones-smash-one-billion-units-in-2013. Chu, H., Hwang, G., Tsai, C., Tseng, J.C.R. (2010). A two-tier test approach to developing location-aware mobile learning systems for natural science courses, Computers & Education, 55(4):1618-1627. Doi: 10.1016/j.compedu.2010.07.004. Cisco, (2014). Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update, 2013–2018, Available at: http://www.cisco.com/c/en/us/solutions/serviceprovider/visual-networking-index-vni/index.html. Fitzgerald, E., Adams, A., Ferguson, R., Gaved, M., Mor, Y. & Thomas, R. (2013). ‘Augmented reality and mobile learning: the state of the art’, International Journal of Mobile and Blended Learning, 5(4):43–58. 12
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