(Following is a paper I wrote a few months ago. The conference where I submitted it perhaps did not think much of it, but I hope you will!)
Introduction
Worldwide, there is immense concern on how we will meet the educational needs of a rapidly growing young population. The challenge is compounded by many other trends – growth of infrastructure, gender disparities, growing inequality, changing student needs, rapid technological change and the challenges of economic globalization. Current educational systems are based on an imposition of structure and the belief that scale challenges can be efficiently be met by imposing more order and structure, rather than a realization that a shift to more self-organized and adaptive systems may be more desirable. This paper argues that we must leverage scale to meet the challenges of scale.
The Challenges
There are some important challenges that need to be studied in order to understand the contours of the problems we are presented with.
Demographic challenges
Reports show that the young populations (5-24) are expanding rapidly in developing and less developed countries. Not only that, the base of the pyramid (primary school enrolment) is expanding very fast and Gross Enrolment Ratios (GER) at each stage up the pyramid are also increasing rapidly.
The 2009 figure for the number of students pursuing tertiary education was 165 mn, up from 28.6 mn in 1970. Sub-saharan Africa has the highest average regional growth rate. But their numbers are still behind the rates of growth experienced in China and India. [1]
In India, the Gross Enrolment Ratio (GER) is extremely low (12%), even as compared with other BRIC countries (Brazil is at 34% and China at 23%), despite having the third highest number of students in the world. In the last 25 years, Higher Education enrolments have been growing at a CAGR of 6% with the current tally of 16 mn students expected to be 40 mn by 2020. [2]
In more developed countries like the USA, GER is high (82% in 2007) and the number of students in higher education reached around 19 mn in 2009. So these countries are reaching their upper limit in terms of GER for tertiary education. They also have a much smaller young population (30%). In contrast, the population in the developing and less developed countries is very young. For developing countries, this figure stands at 48% (0-24 years) and for the less developed countries, this stands at 60% [3-4].
This poses severe stress of traditional investment driven educational systems – both from funding infrastructure and from the challenge of recruiting skilled teachers. In particular, as infrastructural and social conditions worsen going down the scale, the problems are exacerbated.
Gender and Income Inequalities
Gender disparities have also played a major role. In North America and Europe, the balance has shifted towards females whereas in sub-Saharan Africa, South and West Asia, the balance goes the other way. One of the factors is definitely the pressure to earn a livelihood which is perhaps greater for males than for females in these regions [4].
Economic disparities are known to be wide between the developed countries and the developing and less developed countries. What is worse is that models that have created havoc in developed countries such as student debt programs (the next bubble) and ad-hoc privatization, seem to be making their steady way into the much larger scale of developing and less developed countries.
Changing Student needs
The needs in developed countries have changed towards greater use of technology [5]. Learners are changing from passive receptors of information and training to active participants in their own learning. This is a viral change, so it is really fast. Today’s digital learners are part of communities. They share their interests with members of their community. They twitter. They blog. They rake in RSS feeds and bookmark their favorities on de.li.ci.ou.s. They share photos on Flickr and videos on YouTube. They share knowledge on Slideshare and Learnhub or Ning. They share ideas. They grow by meeting and engaging peers and gurus alike using the LinkedIn or Facebook. The collaborate using their laptops and on their mobile phones.
This change is sweeping across to the developing and less developed world depending on what kind of information, network and other resources they have access to. For these regions, the pressure is on being able to earn a livelihood and to do it from an institution that is of value when seeking employment.
Rapid technological change
Technology is proceeding at a rapid pace too. Joseph Licklider wrote about man-computer symbiosis in 1960 [6], extending from Norbert Weiner’s work on Cybernetics. Licklider wrote on the Computer as a communication device in 1968 [7] where he saw the universal network as a network of people, connected to each other, and producing something that no one person in the network could ever hope to produce. Lick’s efforts led to the creation of the first Internet.
The rest is history. The ARPANET emerged in 1969. By 1990, Tim Berners-Lee had created the hypertext transfer protocol (HTTP) which marked the birth of the web, and the internet started growing exponentially.
By 2005, Tim O’Reilly had marked another phase of the evolution of the Web and called it Web 2.0 [8]. While the earlier web was about connecting people to resources, this web was about people being able to create their own content, search it, share it and digitally collaborate around it. It was about harnessing collective intelligence ushered in by services such as Amazon and its recommendation service, and the rise of social networks such as Facebook.
There is an even greater change that is looming on the horizon – that of the Semantic Web. Web 2.0 is collapsing under its own weight. The gigantic amount of information that is being created every day is burying search. So instead, we are moving towards Web 3.0 – the promise of a ubiquitous, semantic, location aware and contextual web – one that Tim Berners-Lee originally envisaged and is working towards with his concept of Linked Data [9].
The implications for education are enormous. John Seely Brown and Paul Duguid, opine that institutions need to reinvent themselves stating that these technologies “offer new ways to think of producing, distributing and consuming academic material” [10].
Order vs. Chaos
We all like order. We love order. Order means getting dinner on time, flights without delays, people not jumping the queue, police to keep criminals in check, doctors to give the right medicine, politicians to govern responsibly, teachers to teach well….the list is endless.
On the other hand, we all hate chaos. Chaos is messy. It is unpredictable. It cannot be controlled. It creates confusion.
In the face of scale constraints, there are some vast over-simplifications that are made during the entire design process. We conceive of a “design” process that has the stereotype of a student, teacher, educational environment and process. We then proceed to hammer out a unifying certification and assessment system that actually drives all learning.
Why do we make such assumptions and over-simplifications? And, incidentally, these are not only found in education, these are everywhere.
My belief is that rather than wanting order from chaos, it’s time we started wanting more chaos from this order. I am not saying we address deficiencies in the system we have conceived. Rather I am saying that we ought to question our conception of what our educational system is and investigate alternate educational futures.
In fact, by the early 20th century, people started looking at phenomena that could not be described by this classical, ordered view of a system. There were many phenomena, they argued, that did not fit into this classical notion of order – there was an element of probability that threatened the concept of order and predictability.
It has become apparent that closed-loop systems like we have in education are just one form a system that exists in real life. All around us we have systems or models that are complex, open and distributed. They are made up of networks of elements that have strong relationships with each other and with the environment in which the system exists. Like the weather.
Fritjof Capra writes that “[T]he emergence of systems thinking was a profound revolution in the history of Western scientific thought…The great shock of twentieth century science has been that systems cannot be understood by analysis [11]. The properties of parts are not intrinsic properties, but can be understood only within the context of the larger whole.” This kind of thinking has caused a shift from analysing “basic building blocks” to understanding “basic principles of organization.”
These behaviors are in evidence when we think of education. As knowledge expands, as technology improves, as data becomes bigger, as problems become more complex, the system needs to adapt. Initial conditions have changed. For example, the number of students that the traditional systems need to “process” has increased exponentially. When we give our children the right to participate on discussions on what they want to learn and how, new behaviors do emerge. Not only that, based on events in the environment, for example the need to speak a particular type of English with the BPO boom, systems do tend to self-organize.
These systems exhibit certain very interesting phenomena. It is not possible to look at any one element in the system and make assumptions about the behavior of the system itself. For example, a gas particle is defined by its position and velocity. However the gas has properties like temperature and pressure. Not just that, under different environmental conditions, the gas may exhibit entirely different sets of properties i.e. new behavior may emerge.
Secondly they exhibit self-organization or the spontaneous emergence of order – “new structures and forms in open systems far from equilibrium, characterized by internal feedback loops and described mathematically by nonlinear equations.”[11] Look at the behavior of a flock of birds. You must have noticed how beautifully they fly in a self-organized formation even though there is no one bird that acts as the head.
Thirdly, scientists also found that very small changes in initial conditions for these systems could lead to very large differences in outcomes. This was first found when Edward Lorenz studied weather patterns and gave this phenomenon a new name – Chaos.
Fourthly, these complex systems are also adaptive. They change and are in turn changed by the environment they belong to.
Capra points out his synthesis of the three essential characteristics of a living system – pattern of organization (Maturana, Varela), dissipative structure (Prigogine) and cognition (Gregory Bateson, Maturana and Varela) as the process of life. In my opinion, education is just that – a living system.
Since the elements of a system are networked, there is a huge value in deciphering patterns of behaviours in a network. For example, organizations are built hierarchically. But the way work gets done in the organization resembles a network. Stakeholders are connected to each other in multiple ways spanning across traditional silos in an attempt to get the job done. We observe that information has many cores of distribution, not just one. We observe that an individual when replaced in an organization changes the network structure and consequently some of the efficiencies in the system, especially if she is a link between multiple sub-networks.
Research into these patterns of relationships between elements in a network has also covered significant ground. Stanley Milgram, in 1967, undertook a project to research the quaint expression “it’s a small world”. His research proved that it was possible for one individual to connect to anyone else in the world in an average of only a few steps – popularised as the six degrees of separation [12].
Sociologist Mark Granovetter introduced the concept of weak ties – the conclusion that occasional interactions and loose connections between individuals are sufficient to generate strong social outcomes [12]. Social network theorists and analysts have extensively researched the form, structure and cognition (or dynamics) of networked structures. Not surprisingly, they have found a great deal in common with the work done in systems thinking.
But in our quest for order, we have consciously excluded precisely this kind of emergent, self-organizing, chaotic, adaptive behaviour. In principle, therefore, and we see enough evidence of this, we have managed to limit creativity and innovation and perhaps the birth of new knowledge.
Distributed Educational Systems
By Distributed Educational Systems (DES), I mean the ability of the educational system to distribute itself over its elements – students, teachers, content, technology, certification and placement.
Traditional educational systems have a tight integration of the components. Education policy sets down a certain set of powers and constraints for each and for the collective as a whole. When expansion is considered, these elements must move as a whole to a new setting. This is costly and time consuming.
Instead, what if these components were individually empowered? For example, could teachers also certify, like in the old gurukul system in India. The challenge would then shift to enabling teachers and providing shared infrastructure.
This poses grand challenges to policy makers because they would lose control, often couching arguments against such a system on grounds of quality and standardization. DES are anarchic in that respect.
Brown and Duguid discuss forces will enable DES. Their 6D notion has demassification, decentralization, denationalization, despacialization, disintermediation and disaggregation as forces that “will break society down into its fundamental constituents, principally individuals and information.” They suggest the formation of “degree granting bodies”, small administrative units with the autonomy to take on students and faculty, and performing the function of providing credentials (read “degrees”). They recommend that “[i]n this way, a distributed system might allow much greater flexibility for local sites of professional excellence.”
Ivan Illich, forty years ago, stated “The current search for new educational funnels must be reversed into the search for their institutional inverse: educational webs which heighten the opportunity for each one to transform each moment of his living into one of learning, sharing, and caring.”[13]
A significant development is the development of the theory of Connectivism as a new theory of learning for the digital age. Propounded by George Siemens (2004) with its epistemological roots in the theory of Connective Knowledge postulated by Stephen Downes [14-15], Connectivism stands contrasted to major existing theories of learning and knowledge by its emphasis on learning as the ability to make connections in a network of resources, both human and device and by the amalgamation of theories of self-organization, complexity and chaos as applied the process of learning.
Connectivism embraces and extends the following principles:
- Learning is the process of making new connections
- Connections are a primary point of focus and could be to people or devices
- Connections expose patterns of information and knowledge that we use (recognize, adapt to) to further our learning
- Networked learning occurs at neural, conceptual and social levels
- Types of connections define certain types of learning
- Strength and nature of connections define how we learn
- Networks are differentiated from Groups (by factors such as openness, autonomy, diversity, leadership and nature of knowledge)
- Knowledge is the network, learning is to be in a certain state of connectedness
- Chaos, complexity theory, theories of self-organization and developments in neurosciences are all extremely important contributors for us to understand how we learn in a volatile, constantly evolving landscape
Connectivism focuses on the distributed nature of learning and knowledge, the explicit focus on networks as the primary means of learning. As George Siemens states, “connectivism, as a networked theory of learning, draws on and informs emerging pedagogical views such as informal, social, and community learning.”
Over the past 4 years, efforts to test this theory has led to the emergence of the Massive Open Online Course (MOOC) format. These are environments which are open, autonomous, self-regulated and adaptive. There are now multiple MOOC instances led by different communities (e.g. CCK, Critical Literacies, Educational Futures, LAK, eduMOOC and MobiMOOC). Thousands of people from across the world have joined these “courses”.
Other theories and frameworks such as Jay Cross’s Informal Learning, Lave and Wenger’s Communities of Practice (CoP) and Brown and Duguid’s Network of Practice build upon the networked and distributed nature of learning.
For example, defined by knowledge rather than the task, CoPs are different from social networks or teams because they are not only about relationships or tasks. Rather they are about the shared learning and interest of its members [16].
In Connectivism, learning becomes the process of making connections and knowledge is the network. As Stephen explains “Just as the activation of the pixels on a television screen form an image of a person, so also the bits of information we create and we consume form patterns constituting the basis of our knowledge, and learning is consequently the training our own individualized neural networks – our brains – to recognize these patterns.”[17]
Connectivism applied to contemporary challenges facing educators creates nothing short of an inflection point. In an appeal to end course-o-centrism, Siemens writes “What is really needed is a complete letting go of our organization schemes and open concepts up to the self/participatory/chaotic sensemaking processes that flourish in online environments.”[18]
In this context, let us identify what DES would have as essential components.
Dis-aggregation
The first attribute of a DES would be its disaggregated nature. In the traditional system, we are used to the concept of courses – a slow evolving, closely bounded collection of resources, with a temporal performance monitoring and assessment mechanism built in. This format requires that there be a design process and the presence of experts who would provide authenticity. Courses are a hegemonistic element of the traditional system – the raw elemental form of structure upon which institutions are based. Associated with these courses are certifications or degrees – proof that students are performing or have performed. DES would move from courses to un-courses – loosely defined collections of content brought together and grown through participant activity to answer a competency need. This is not reusability redefined because the premise of design itself needs to be deconstructed in this new context.
Decentralization
The second attribute is decentralization – but not in the sense of delegation of a control structure – but in sense of agency to the decentralized entities. DES would empower and support agents of the system – teachers, students, experts and employers – to impart high quality learning at local and global scales. What DES will do is to allow units lesser than the institution, howsoever organized, to engage in educational activities. In this sense, DES could represent local networks of practice. Closely linked to decentralization is also the concept of disintermediation – the removal of administrative and legal/policy barriers in the operation and powers of such local networks.
The state’s role (or that of private education providers) would then be to provide these networks or clusters with adequate access to technology and shared infrastructure. It would also be to bring about cohesion in the interests of regional and national vision and goals.
Open-ness and Autonomy
The third attribute of DES would be its open-ness. The term open can have many connotations. It could mean transparency and accountability. It could mean adaptive to change and open to critique. It could mean barrier-less to different genders or income parameters. It could mean autonomous in the sense that they would be self-organized and self-regulated. Open-ness and autonomy are two crucial factors in enabling local networks to become self-sustaining and valuable.
For example, a local carpenter’s guild could potentially serve the learning and livelihood needs of the young to engender competencies enough to meet local needs and challenges, without having to go through legal structures of legislation or even the attitude of privatization. Similarly, information systems could record and share learning activity and resources globally across similar such guilds across the world. Units of the DES, howsoever defined, could act as curators of this information for their audience.
This is really a democratization of the process of and the systems for education by individuals and small glocalized networks [19].
Distributed Networks
This fourth attribute of a DES is its distributed networked nature. While going local, it is necessary to connect globally. Information access is the first enabler; infrastructure and resource availability comes second. When information flows seamlessly and without constraints, when networks become open to connections and collaboration, innovation allows indigenization and assimilation of knowledge. The challenge of DES will be one of discoverability – how does information travel to those who need it? – a reverse search of sorts.
These networks of education could be local, seeded by local communities, their skills and needs, at the same time could be federated to align with regional and national goals and connected with a global environment. We need to allow these networks to self-organize and self-regulate. Instead of funding centralized initiatives, we need to fund and empower local initiatives.
Instead of building cadres of educational bureaucrats and technocrats to staff superstructures, we need to invest in building an architecture of participation across these networks so that they are equipped to take decisions about how education should be.
The Road Ahead
What will this take? Firstly it will take awareness building. Secondly, it will take capability building (not only leadership for the community, but also the vital skills deemed fit to make education a high quality practice). Thirdly, it will take creation of formal structures or spaces where communities can be seeded and supported. Fourthly, it will take a shift of control and a corresponding alteration of the power structures. Fifthly, it will take the loosening of barriers – legal or procedural – to promote freer flow of resources through the local systems.
This would be a strategic shift in policy. From being responsible for implementation, to being responsible for coordinating, supporting and training local communities to support the national needs and vision.
And, of course, it will not happen overnight.
Conclusions
Change is inevitable. One possible alternative education future is described in this paper and many more need to be researched and evaluated contextually. It is my hope, that through the thoughts in this paper and worldwide research in alternate educational futures, policy makers, educationists, designers and entrepreneurs alike, will embrace change.
Acknowledgments
This paper would not have been possible without the insights of great thinkers referenced in this article and the support of the worldwide MOOC and informal communities from whom I learn every moment. In particular, I would like to profusely thank George Siemens and Stephen Downes for their support and continued inspiration.
References
[1] OECD (2011). Education at a Glance 2011: OECD Indicators, OECD Publishing, 2011
[2] Ernst & Young. Making Indian Higher Education Future Ready, E&Y-FICCI, http://education.usibc.com/wp-content/uploads/2010/09/EY-FICCI-report09-Making-Indian-Higher-Education-Future-Ready.pdf, 2009
[3] Press Release. World Population to exceed 9 billion by 2050, UN Population Division/DESA, 2009
[4] UNESCO Institute for Statistics. Global Education Digest 2009, UNESCO, 2009
[5] Lenhart, Amanda, Madden Mary, Macgill Alexandra R. and Smith Aaron. Teens and Social Media, Pew / Internet, http://www.pewinternet.org/PPF/r/230/report_display.asp, 2007
[6] Licklider, J.C.R.. Man-computer symbiosis, 1960
[7] Licklider, J.C.R. and Taylor, R.,The Computer as a Communication Device, 1968
[8] O’Reilly, Tim. What is Web 2.0, 2005
[9] Berners-Lee, Tim. Linked Data, http://www.w3.org/DesignIssues/LinkedData.html, July, 2006
[10] Brown, John S. and Duguid, Paul. The Social Life of Information, Harvard Business School Press, http://www.amazon.co.uk/Social-Life-Information-Seely-Brown/dp/0875847625/ref=sr_1_1?ie=UTF8&s=books&qid=1229549494&sr=8-1, 2000
[11] Capra, Fritjof. The Web of Life – A New Synthesis of Mind and Matter, Harper Collins, 1996
[12] Watts, Duncan. Six Degrees – The Science of a Connected Age, Norton, 2004
[13] Illich, Ivan. Deschooling Society, Harper and Row, 1976
[14] Siemens, George. Connectivism: A Learning Theory for the Digital Age, elearnspace, http://www.elearnspace.org/Articles/connectivism.htm, December 12, 2004
[15] Downes, Stephen. An Introduction to Connective Knowledge, Hug, Theo (ed.) (2007): Media, Knowledge & Education – Exploring new Spaces, Relations and Dynamics in Digital Media Ecologies. Proceedings of the International Conference held on June 25-26, 2007, November 27, 2007
[16] Wenger, Etienne. CoP: Best Practices, Systems Thinker, http://www.co-i-l.com/coil/knowledge-garden/cop/lss.shtml, June, 1998
[17] Downes, Stephen. The Future of Online Learning: Ten Years On , Half an Hour, http://halfanhour.blogspot.com/2008/11/future-of-online-learning-ten-years-on_16.html, November, 2008
[18] Siemens, George. Time to end “courseocentricism”, elearnspace, http://www.elearnspace.org/blog/2009/01/14/time-to-end-courseocentricism/, January 14, 2009
[19] Wellman, Barry. Little Boxes, Glocalization and Networked Individualism, http://www.chass.utoronto.ca/~wellman/publications/littleboxes/littlebox.PDF
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