August 30, 2015

The dissemination of research in online learning: a lesson from the EDEN Research Workshop

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The Sheldonian Theatre, Oxford

The Sheldonian Theatre, Oxford

The EDEN Research Workshop

I’m afraid I have sadly neglected my blog over the last two weeks, as I was heavily engaged as the rapporteur for the EDEN 8th Research Workshop on challenges for research on open and distance learning, which took place in Oxford, England last week, with the UK Open University as the host and sponsor. I was also there to receive a Senior Fellowship from EDEN, awarded at the Sheldonian Theatre, the official ceremonial hall of the University of Oxford.

There were at the workshop almost 150 participants from more than 30 countries, in the main part European, with over 40 selected research papers/presentations. The workshop was highly interactive, with lots of opportunity for discussion and dialogue, and formal presentations were kept to a minimum. Together with some very stimulating keynotes, the workshop provided a good overview of the current state of online, open and distance learning in Europe. From my perspective it was a very successful workshop.

My full, factual report on the workshop will be published next week as a series of three blog posts by Antonio Moreira Texeira, the President of EDEN, and I will provide a link when these are available, but in the meantime I would like to reflect more personally on one of the issues that came out of the workshop, as this issue is more broadly applicable.

Houston, we have a problem: no-one reads our research

Well, not no-one, but no-one outside the close group of those doing research in the area. Indeed, although in general the papers for the workshop were of high quality, there were still far too many papers that suggested the authors were unaware of key prior research in the area.

But the real problem is that most practitioners – instructors and teachers – are blissfully unaware of the major research findings about teaching and learning online and at a distance. The same applies to the many computer scientists who are now moving into online learning with new products, new software and new designs. MOOCs are the most obvious example. Andrew Ng, Sebastian Thrun and Daphne Koller – all computer scientists – designed their MOOCs without any consideration about what was already known about online learning – or indeed teaching or learning in general, other than their experience as lecturers at Stanford University. The same applies to MIT’s and Harvards’s courses on edX, although MIT/Harvard are at least  starting to do their own research, but again ignoring or pretending that nothing else has been done before. This results in mistakes being made (unmonitored student discussion), the re-invention of the wheel hyped as innovation or major breakthroughs (online courses for the masses), and surprised delight at discovering what has already been known for many years (e.g. students like immediate feedback).

Perhaps of more concern though is that as more and more instructors move into blended and hybrid learning, they too are unaware of best practices based on research and evaluation of online learning, and knowledge about online learners and their behaviour. This applies not only to online course design in general, but also particularly to the management of online discussions.

It will of course be argued that MOOCs and hybrid learning are somehow different from previous online and distance courses and therefore the research does not apply. These are revolutionary innovations and therefore the rules of the game have changed. What was known before is therefore no longer relevant. This kind of thinking though misunderstands the nature of sustainable innovation, which usually builds on past knowledge – in other words, successful innovation is more cumulative than a leap into the dark. Indeed, it is hard to imagine any field other than education where innovators would blithely ignore previous knowledge. (‘I don’t know anything about civil engineering, but I have a great idea for a bridge.’ Let’s see how far that will get you.)

Who’s to blame?

Well, no-one really. There are several reasons why research in online learning is not better disseminated:

  • research into any kind of learning is not easy; there are just so many different variables or conditions that affect learning in any context. This has several consequences:
    • it is difficult to generalize, because learning contexts vary so much
    • clearly significant results are difficult to find when so many other variables are likely to affect learning outcomes
    • thus results are usually hedged with so many reservations that any clear message gets lost
  • because research into online learning is out of the mainstream of educational research it has been poorly funded by the research councils. Thus most studies are small scale, qualitative and practitioner-driven. This means interventions are small scale and therefore do not identify major changes in learning, and the results are mainly of use to the practitioner who did the research, so don’t get more widely disseminated
  • most research in online learning is published in journals that are not read by either practitioners or computer scientists (who publish in their own journals that no-one else reads). Furthermore, there are a large number of journals in the field, so integration of research findings is difficult, although Anderson and Zawacki-Richter (2104) have done a good job in bringing a lot of the research together in one publication – but which unfortunately is nearly 500 pages long, and hence unlikely to reach many practitioners, at least in a digestible form
  • online learning is still a relatively new field, less than 20 years old, so it is taking time to build a solid foundation of verifiable research in which people can have confidence
  • most instructors at a post-secondary level have no formal training in any form of teaching and learning, so there are difficulties in bringing research and best practices to their attention.

What can be done?

First let me state clearly that I believe there is a growing and significant body of evidence about best practices in online learning that is evidence-based and research-driven. These best practices are general enough to be applied in a wide variety of contexts. In fact I will shortly write a post called ‘Ten things we know from research in online learning’ that will set out some of the most important results and their implications for teaching and learning online. However, we need more attempts to pull together the scattered research into more generalizable conclusions and more widely distributed forms of communication.

At the same time, we need also to get out the message about the complexity of teaching and learning, without which it will be difficult to evaluate or appreciate fully the findings from research in online learning. It is understanding that:

  • learning is a process, not a product,
  • there are different epistemological positions about what constitutes knowledge and how to teach it,
  • above all, identifying desirable learning outcomes is a value-driven decision; and acceptance of a diversity of values about what constitutes knowledge is to be welcomed, not restricted, in education, so long as there is genuine choice for teachers and learners.
  • however, if we want to develop the skills needed in a digital age, the traditional lecture-based model, whether offered face-to-face or online, is inadequate
  • academic knowledge is different from everyday knowledge; academic knowledge means transforming understanding of the world through evidence, theory and rational argument/dialogue, and effective teachers/instructors are essential for this
  • learning is heavily influenced by the context in which it takes place: one critical variable is the quality of course design; another is the role of an expert instructor. These variables are likely to be more important than any choice of technology or delivery mode.

There are therefore multiple audiences for the dissemination of research in online learning:

  • practitioners: teachers and instructors
  • senior managers and administrators in educational institutions
  • computer scientists and entrepreneurs interested in educational services or products
  • government and other funding agencies.

I can suggest a number of ways in which research dissemination can be done, but what is needed is a conversation about

(a) how best to identify the key research findings on online learning around which most experienced practitioners and researchers can agree

(b) the best means to get these messages out to the various stakeholders.

I believe that this is an important role for organizations such as EDEN, EDUCAUSE, ICDE, but it is also a responsibility for every one of us who works in the field and believes passionately about the value of online learning.

Transforming university teaching and learning: UBC’s strategy for flexible learning

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UBC campus, Vancouver BC

UBC campus, Vancouver BC

Flexible Learning Implementation Team (2014) Flexible Learning – Charting a Strategic Vision for UBC (Vancouver Campus. Vancouver BC: Office of the Provost, University of British Columbia

The University of British Columbia is one of Canada’s premier research universities with almost 60,000 students. It usually features within the top 30 universities worldwide in university rankings.

For the last 18 months, UBC has been developing a comprehensive strategy for teaching and learning for the future, and last week issued a report on its vision and how it plans to implement that vision. Although Flexible Learning is the term UBC has chosen to describe this strategy, it is in fact far more comprehensive and wide ranging than just blended or fully online learning. It is really about the transformation of teaching and learning in response to local, regional and global changes and challenges, based on a substantial amount of prior research, internal discussion, and input from external consultants (declaration of interest: I played a very small part in some of the early discussions of strategy).

First, the breaking news, then a summary of the main points from the strategy document.

Breaking news

This really represents the first concrete actions resulting from this strategic initiative.

  1. Research report published on UBC’s first four MOOCs: These MOOCs were delivered through the Coursera platform. I will cover this report in a separate blog post.
  2. Moving from Coursera to edX: UBC has now joined edX as a Charter Member, giving it a seat on edX’s Academic Advisory Board. UBC will develop four new MOOCs for delivery on edX in 2014-2015.
  3. Revamping Continuing and Professional Education: UBC has established, within the Provost’s Office, a new unit to work in close partnership with Faculties in developing both applied and access programs. More on this and how it affects the current Division of Continuing Studies later in this post.
  4. Improving the learning technology ecosystem: basically a response to widespread faculty disenchantment with the implementation of the latest version of UBC’s LMS, Blackboard Connect.

However, these four developments are literally the tip of an iceberg, which is much larger and more significant.

The strategic vision

As always, I recommend a careful reading of the whole 22 page document, even though it is not the easiest of reads. Any summary diminishes the complexity of the discussion, because there are so many inter-related themes and developments to which the university is attempting to respond. I provide this summary though in the hope that it will spike your interest enough to make the effort, as I see this document as one of the most significant for the future of public higher education in Canada – and elsewhere.

What does the university mean by flexible learning?

From the document (p.2)

We define Flexible Learning as UBC’s response to the opportunities and challenges presented by rapid advances in information and communication technologies, informed by the results of learning research and motivated by the objectives of improving student learning, extending access to UBC and strengthening university operating effectiveness.

See below for more detail on what that actually means.

What’s driving the change?

  • learner and employer expectations: need for a flexible workforce, greater flexibility in delivery and offerings, and more emphasis on measurable outcomes
  • demographics: increased global demand, with the local population of students older and often working
  • policy of governments (generally): growing reliance on tuition revenue; a belief that online learning is cheaper
  • disruptive technologies: MOOCs, cloud, mobile, adaptive learning, automated assessment, learning analytics…..

Market segmentation

Different categories of learners:

  • traditional university students (65% of the market), younger, mainly ‘commuting': want rich campus-based learning experiences
  • convenience-driven degree-seekers: older, working, want blended/online learning
  • practitioners: seeking credentials for professional development; able to pay; under-represented to date at UBC
  • growth learners: seeking non-credentialed learning; a large and growing market segment.

All segments want more flexibility, both in delivery and range of content offerings.

Main objectives (for flexible learning)

  1. improved student learning
  2. expanded access to UBC content
  3. greater operating effectiveness

Main strategies

1. Strengthening UBC’s traditional role: through:

  • blended learning (including integration of MOOC content)
  • improving the campus experience and more personalization of learning through more modular programming
  • strategic academic program transformation

2. Revenue growth: through:

  • strategic expansion of continuing/professional education, especially applied master’s programs, certificates, badges
  • expanding access through ‘bridging’, e.g. PLA, MOOCs, summer programs

3. Academic partnerships (joining edX is one example)

Governance and management

The UBC Board and Executive approved the outline plan in 2013. Two teams were established within the Provost’s Office:

  • a leadership team, responsible for developing vision, strategy and policies, chaired by the Provost, with eight members
  • an implementation team, with another eight members, chaired by a Vice Provost.

Support is also provided by staff from the Centre for Teaching, Learning and Technology and from the IT Division, as well as designated contact people within each Faculty.

UBC has committed a total of $5 million ($1 million already spent) to support this initiative. (The total UBC annual operating budget is over $1 billion).

Comment

I’m watching this as someone completely outside the university. UBC is a very large and complex organization, once described by one former Provost as being managed by 12 barons all plotting to become king (although the climate is very different today). I cannot judge how far the reality of what’s happening on the ground differs from the vision, and in any case it is still very early days.

However, it is important to stress that this is a university-wide initiative (at least for the main Vancouver campus – UBC also has a semi-autonomous and much smaller campus in the interior of the province.) The strategy seems to have widespread support at the senior executive level, and a lot of momentum resulting from an infusion of significant money but more importantly as a result of widespread discussion and consultation within the university. Certainly the blended learning component is already getting a lot of traction, with some major re-designs of large undergraduate classes already in progress. How all this affects though the main body of the faculty and students at the hard edge of teaching and learning is impossible for me to judge.

The establishment of a new ‘hub’ within the Provost’s office for continuing and professional education (CPE) is particularly interesting since UBC has long had a strong and extensive Division of Continuing Studies, which offers a wide range of non-credit programming. However,

  • the ability to re-purpose existing content from credit courses into certificates, badges and non-credentialed offerings such as MOOCs,
  • the growing market for professional masters programs, especially online,
  • the increasing reconfiguration of higher education as a continuous lifelong learning escalator rather than a series of different, discrete floors (bachelors, masters, doctorates, non-credit),
  • the opportunities for revenue generation flowing directly back to the faculties,

all make essential a rethinking of the whole CPE activities of a university.

At the same time, the Division of Continuing Studies at UBC, as elsewhere, has many staff with a range of special skills and knowledge, such as

  • marketing,
  • direct access to employers and industry (often through the hiring of working professionals as part-time instructors),
  • the ability to identify and take risks with emerging content areas,
  • experience in operating in a highly market-driven, competitive cost-recovery/profit environment.

These are not attributes currently within the capacity or even interest of most academic departments. It will be an interesting challenge to see how the knowledge and experience of the Division of Continuing Studies can best be integrated with the new initiative, and how the new development in the Provost’s Office affects the operation of the Division of Continuing Studies.

Another critical factor is the appointment of a new President, who has pledged support for the strategy. However, he also said on his inauguration that the university will increase its base funding for research by at least $100-million. He did not specify though where the money would come from. I leave you to compare that to the $5 million allocated to this initiative and to judge how much impact finding another $100 million base funding for research might have on teaching and learning at UBC. I know, it’s not a zero sum game, but….

Overall, though, I find it heartening that UBC is showing such leadership and initiative in grappling with the major forces now impacting on public universities. It has a vision and a plan for teaching and learning in the future, that looks at teaching, technology, students and the changing external environment in an integrated and thoughtful manner, which in itself is a major accomplishment. It will be fascinating to see how all this actually plays out over time.

Learning theories and online learning

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Figure 3.3. Adults learning in groups in a constructivist manner - and assisted by technology

Figure 3.3. Adults learning in groups in a constructivist manner – and assisted by technology

Introduction

Chapter 3 of my open textbook on ‘Teaching in a Digital Age‘ is about theory and practice in teaching for a digital age, which I am still in the process of writing. I have to admit that I approached writing about learning theories with some dread. In particular I was concerned (in order of dread) that:

  • this will appear incredibly boring/lack originality, because it has been done so many times before by other, more qualified authors (but then those that already know this stuff can easily skip it)
  • I’m not sure that theories of learning actually drive teaching (although surely an understanding of how students learn should do so)
  • I would have to deal with connectivism somehow, and I am certainly not an expert on that topic – but maybe that might be an advantage in bringing it to the attention of people who have previously shown no interest in it, and how it differs from previous theories
  • it could be argued that past learning theories are made irrelevant by digital technologies (and I certainly don’t agree with that point of view.)

In the end, I can’t see how a discussion of learning theories can be avoided. Unless readers of the book have this basic understanding of the different views of learning, they will not be in a good position to make choices, especially regarding the use of technology for teaching and learning. In particular, I see a danger of becoming dogmatic and blinkered by unchallenged assumptions about the nature of learning that results from not exploring alternative theories. But lastly, as Kurt Lewin said, there is nothing more practical than a good theory. A good theory helps us make informed decisions in areas of uncertainty. So, I am sharing here my first draft with you. Please note this is just part of the whole chapter, which also includes the following:

  • Teaching and learning styles
  • Deep vs surface learning.
  • Learner-centered teaching, learner engagement.
  • What we know about skills development
  • Competency based learning.
  • Learning design models
  • learner characteristics: digital natives and digital literacy
  • are we right to fear the use of computers for teaching?
  • Summary of research on teaching.

Also, Chapter 2 discusses the nature of knowledge, and in particular different epistemologies that underpin different theories of learning. However, theories of learning are more than enough to chew on for the moment.

Theories of learning

…there is an impressive body of evidence on how teaching methods and curriculum design affect deep, autonomous, and reflective learning. Yet most faculty are largely ignorant of this scholarship, and instructional practices and curriculum planning are dominated by tradition rather than research evidence. As a result, teaching remains largely didactic, assessment of student work is often trivial, and curricula are more likely to emphasize content coverage than acquisition of lifelong and life-wide learning skills.”

Knapper, 2010, p. 229

“There is nothing so practical as a good theory.” Kurt Lewin, 1951, p. 169

Why an understanding of theories of learning is important

Most teachers in the k-12 sector will be familiar with the main theories of learning, but because instructors in post-secondary education are hired primarily for their subject experience, or research or vocational skills, it is essential to introduce and discuss, if only briefly, these main theories. In practice, even without formal training or knowledge of different theories of learning, all teachers and instructors will approach teaching within one of these main theoretical approaches, whether or not they are aware of the educational jargon surrounding these approaches. Also, as online learning, technology-based teaching, and informal digital networks of learners have evolved, new theories of learning are emerging.

With a knowledge of alternative theoretical approaches, teachers and instructors are in a better position to make choices about how to approach their teaching in ways that will best fit the perceived needs of their students, within the very many different learning contexts that teachers and instructors face. This is particularly important when addressing many of the requirements of learners in a digital age. Furthermore, the choice of or preference for one particular theoretical approach will have major implications for the way that technology is used to support teaching.

In fact, there is a huge amount of literature on theories of learning, and I am aware that the treatment here is cursory, to say the least. Those who would prefer a more detailed introduction to theories of learning could, for an obscene price, purchase Schunk (2011), or for a more reasonable price Harasim (2012). The aim of my book though is not to be comprehensive in terms of in-depth coverage of all learning theories, but to provide a basis on which to suggest and evaluate different ways of teaching to meet the diverse needs of learners in a digital age.

Behaviourism

Although initially developed in the 1920s, behaviourism still dominates approaches to teaching and learning in many places, particularly in the USA.

Behaviourist psychology is an attempt to model the study of human behaviour on the methods of the physical sciences, and therefore concentrates attention on those aspects of behaviour that are capable of direct observation and measurement. At the heart of behaviourism is the idea that certain behavioural responses become associated in a mechanistic and invariant way with specific stimuli. Thus a certain stimulus will evoke a particular response. At its simplest, it may be a purely physiological reflex action, like the contraction of an iris in the eye when stimulated by bright light.

However, most human behaviour is more complex. Nevertheless behaviourists have demonstrated in labs that it is possible to reinforce through reward or punishment the association between any particular stimulus or event and a particular behavioural response. The bond formed between a stimulus and response will depend on the existence of an appropriate means of reinforcement at the time of association between stimulus and response.  This depends on random behaviour (trial and error) being appropriately reinforced as it occurs.

This is essentially the concept of operant conditioning, a principle most clearly developed by Skinner (1968). He showed that pigeons could be trained in quite complex behaviour by rewarding particular, desired responses that might initially occur at random, with appropriate stimuli, such as the provision of food pellets. He also found that a chain of responses could be developed, without the need for intervening stimuli to be present, thus linking an initially remote stimulus with a more complex behaviour. Furthermore, inappropriate or previously learned behaviour could be extinguished by withdrawing reinforcement. Reinforcement in humans can be quite simple, such as immediate feedback for an activity or getting a correct answer to a multiple-choice test.

Skinner and his machine 2

Figure 3.1 YouTube video/film of B.F. Skinner demonstrating his teaching machine, 1954

You can see a fascinating five minute film of B.F. Skinner describing his teaching machine in a 1954 YouTube video, either by clicking on the picture above or at: http://www.youtube.com/watch?v=jTH3ob1IRFo

Underlying a behaviourist approach to teaching is the belief that learning is governed by invariant principles, and these principles are independent of conscious control on the part of the learner. Behaviourists attempt to maintain a high degree of objectivity in the way they view human activity, and they generally reject reference to unmeasurable states, such as feelings, attitudes, and consciousness. Human behaviour is above all seen as predictable and controllable. Behaviourism thus stems from a strongly objectivist epistemological position.

Skinner’s theory of learning provides the underlying theoretical basis for the development of teaching machines, measurable learning objectives, computer-assisted instruction, and multiple choice tests. Behaviourism’s influence is still strong in corporate and military training, and in some areas of science, engineering, and medical training. It can be of particular value for rote learning of facts or standard procedures such as multiplication tables, for dealing with children or adults with limited cognitive ability due to brain disorders, or for compliance with industrial or business standards or processes that are invariant and do not require individual judgement.

Finally, it should be noted that behaviourism, with its emphasis on rewards and punishment as drivers of learning, and on pre-defined and measurable outcomes, is the basis of populist conceptions of learning among many parents, politicians, and, it should be noted, computer scientists interested in automating learning. It is not surprising then that there has also been a tendency until recently to see technology, and in particular computer-aided instruction, as being closely associated with behaviourist approaches to learning, although we shall see that this does not necessarily follow.

Cognitivism

An obvious criticism of behaviourism is that it treats humans as a black box, where inputs into the black box, and outputs from the black box, are known and measurable, but what goes on inside the black box is ignored or not considered of interest. However, humans have the ability for conscious thought, decision-making, emotions, and the ability to express ideas through social discourse, all of which may be highly significant for learning. Thus we will likely get a better understanding of learning if we try to find out what goes on inside the black box. Cognitivists therefore have focused on identifying mental processes – internal and conscious representations of the world – that they consider are essential for human learning. Fontana (1981) summarises the cognitive approach to learning as follows:

The cognitive approach … holds that if we are to understand learning we cannot confine ourselves to observable behaviour, but must also concern ourselves with the learner’s ability mentally to re-organize his psychological field (i.e. his inner world of concepts, memories, etc.) in response to experience. This latter approach therefore lays stress not only on the environment, but upon the way in which the individual interprets and tries to make sense of the environment. It sees the individual not as the somewhat mechanical product of his environment, but as an active agent in the learning process, deliberately trying to process and categorize the stream of information fed into him by the external world.’ (p. 148)

Thus the search for rules, principles or relationships in processing new information, and the search for meaning and consistency in reconciling new information with previous knowledge, are key concepts in cognitive psychology. Cognitive psychology is concerned with identifying and describing mental processes that affect learning, thinking and behaviour, and the conditions that influence those mental processes.

© Agile Development Blog, 2013

© Agile Development Blog, 2013

Figure 3.2: Some of the areas covered by cognitivism, based on Bloom’s taxonomy (1956). Note that this becomes a reductionist exercise, as psychologists delve deeper into each of these cognitive activities to understand the underlying mental processes.

Cognitive approaches to learning cover a very wide range. At one end, the objectivist end, cognitivists consider basic mental processes to be genetic or hard-wired, but can be programmed or modified by external factors, such as new experiences. Early cognitivists in particular were interested in the concept of mind as computer, and more recently brain research has led to a search for linking learning to the development and reinforcement of neural networks in the brain. In terms of practice this concept of mind as computer has led to several technology-based developments in teaching, including:

  • intelligent tutoring systems, a more refined version of teaching machines, based on analysing student responses to questions and redirecting them to the appropriate next steps in learning. Adaptive learning is the latest extension of such developments;
  • artificial intelligence, which seeks to represent in computer software the mental processes used in human learning (which of course if successful would result in computers replacing many human activities – such as teaching, if learning is considered in an objectivist framework.)
  • pre-determined learning outcomes, based on an analysis and development of different kinds of cognitive activities, such as comprehension, analysis, synthesis, and evaluation
  • certain instructional design approaches that attempt to manage the design of teaching to ensure successful achievement of pre-determined learning outcomes or objectives.

On the other hand, many other cognitivists, coming from a more constructivist epistemological perspective, would argue that mental states or even processes are not fixed but constantly evolving as new information is integrated with prior knowledge, and new strategies for seeking meaning are developed by the individual. Thus teachers who place a strong emphasis on learners developing personal meaning through reflection, analysis and construction of knowledge through conscious mental processing would represent much more of a constructivist epistemological position. It is here that the boundaries between cognitivist and constructivist learning begin to break down.

Cognitive approaches to learning, with a focus on comprehension, abstraction, analysis, synthesis, generalization, evaluation, decision-making and creative thinking, seem to fit much better with higher education than behaviourism,  but even in k-12 education, a cognitivist approach would mean for instance focusing on teaching learners how to learn, on developing stronger or new mental processes for future learning, and on developing deeper and constantly changing understanding of concepts and ideas.

Put simply, brains have more plasticity, adaptability and complexity than current computer software programs, and other factors, such as emotion, motivation, self-determination, values, and a wider range of senses, make human learning very different from the way computers operate, at least at the moment. Education would be much better served if computer scientists tried to make software to support learning more reflective of the way human learning operates, rather than trying to fit human learning into the current restrictions of behaviourist computer programming.

Nevertheless, cognitivists have increased our understanding of how humans process and make sense of new information, how we access, interpret, integrate, process, organize and manage knowledge, and have given us a better understanding of the conditions that affect learners’ mental states.

Constructivism

Both behaviourist and some elements of cognitive theories of learning are deterministic, in the sense that behaviour and learning are believed to be rule-based and operate under predictable and constant conditions over which the individual learner has no or little control. However, constructivists emphasise the importance of consciousness, free will and social influences on learning. Carl Rogers (1969) stated that: ‘every individual exists in a continually changing world of experience in which he is the center.’ The external world is interpreted within the context of that private world. The belief that humans are essentially active, free and strive for meaning in personal terms has been around for a long time.

Constructivists argue that individuals consciously strive for meaning to make sense of their environment in terms of past experience and their present state. It is an attempt to create order in their minds out of disorder, to resolve incongruities, and to reconcile external realities with prior experience. The means by which this is done are complex and multi-faceted, from personal reflection, seeking new information, to testing ideas through social contact with others. Problems are resolved, and incongruities sorted out, through strategies such as seeking relationships between what was known and what is new, identifying similarities and differences, and testing hypotheses or assumptions. Reality is always tentative and dynamic.

For many educators, the social context of learning is critical. Ideas are tested not just on the teacher, but with fellow students, friends and colleagues. Furthermore, knowledge is mainly acquired through social processes or institutions that are socially constructed: schools, universities, and increasingly these days, online communities. Thus what is taken to be ‘valued’ knowledge is also socially constructed. Thus knowledge is not just about content, but also values. One set of values are those around the concept of a liberal education. According to this ideology, one of the principal aims of education is that it should develop a critical awareness of the values and ideologies that shape the form of received knowledge. This then suggests a constant probing and criticism of received knowledge.

One consequence of constructivist theory is that each individual is unique, because the interaction of their different experiences, and their search for personal meaning, results in each person being different from anyone else. Thus behaviour is not predictable or deterministic, at least not at the individual level. The key point here is that learning is seen as essentially a social process, requiring communication between learner, teacher and others. This social process cannot effectively be replaced by technology, although technology may facilitate it.

It can be seen that although constructivist approaches can be and have been applied to all fields of knowledge, it is more commonly found in approaches to teaching in the humanities, social sciences, education, and other less quantitative subject areas.

Online collaborative learning

The concurrence of both constructivist approaches to learning and the development of the Internet has led to the development of a particular form of constructivist teaching, originally called computer-mediated communication (CMC), but which has developed into what Harasim (2012) now calls online collaborative learning theory (OCL). She describes OCL as follows (p. 90):

OCL theory provides a model of learning in which students are encouraged and supported to work together to create knowledge: to invent, to explore ways to innovate, and, by so doing, to seek the conceptual knowledge needed to solve problems rather than recite what they think is the right answer. While OCL theory does encourage the learner to be active and engaged, this is not considered to be sufficient for learning or knowledge construction……In the OCL theory, the teacher plays a key role not as a fellow-learner, but as the link to the knowledge community, or state of the art in that discipline. Learning is defined as conceptual change and is key to building knowledge. Learning activity needs to be informed and guided by the norms of the discipline and a discourse process that emphasises conceptual learning and builds knowledge.

This approach to the use of technology for teaching is very different from the more objectivist approaches found in computer-assisted learning, teaching machines, and artificial intelligence applications to education, which primarily aim to use computing to replace at least some of the activities traditionally done by human teachers. With online collaborative learning, the aim is not to replace the teacher, but to use the technology primarily to increase and improve communication between teacher and learners, with a particular approach to the development of learning based on knowledge construction assisted and developed through social discourse. This social discourse furthermore is not random in OCL, but managed in such a way as to ‘scaffold’ learning, by assisting with the construction of knowledge in ways that are guided by the instructor, that reflect the norms or values of the discipline, and that also respect or take into consideration the prior knowledge within the discipline.

Connectivism

Connectivism is a relatively new theory of learning or epistemology (there’s not even agreement about which it is), it is still being refined and developed, and it is currently highly controversial, with many critics. Siemens, Downes and Cormier constructed the first massive open online course (MOOC), Connectivism and Connective Knowledge 2011, partly to explain and partly to model a connectivist approach to learning. More recently, Downes (2014) has spelled out, in a presentation called The MOOC of One, some of the relationships between individual learning, the contribution of individuals to knowledge and its flow, and networks of learners, within a broad interpretation of connectivist theory. In this presentation Downes sets out some design principles for  connectivist ‘courses’ or cMOOCs, such as:

  • learner autonomy, in terms of choice of content and how they choose to learn
  • openness, in terms of  access to the course, content, activities and methods of assessment
  • diversity: varied content, individual perspectives and multiple tools, especially for networking learners and creating opportunities for dialogue and discussio
  • interactivity: ‘massive’ communication between learners and co-operative learning, resulting in emergent knowledge
Figure 2.1: A map of connectivism, © Stephen Downes, 2011 (accessed via pkab.wordpress.com)

Figure 2.1: A map of connectivism, © Stephen Downes, 2011 (accessed via pkab.wordpress.com)

Connectivists such as Siemens and Downes tend to be somewhat vague about the role of teachers or instructors, as the focus of connectivism is more on individual participants, networks and the flow of information and the new forms of knowledge that result.. The main purpose of a teacher appears to be to provide the initial learning environment and context that brings learners together, and  to help learners construct their own personal learning environments to enable them to connect to ‘successful’ networks, with the assumption that learning will automatically occur as a result, through exposure to the flow of information and the individual’s autonomous reflection on its meaning. There is no need for formal institutions to support this kind of learning, especially since such learning often depends heavily on social media readily available to all participants.

There are numerous criticisms of the connectivist approach to teaching and learning, which include:

  • there is no control on the quality of content, or on contributions from participants;
  • assessment strategies, such as peer assessment, are primitive and unreliable, thus making reliable or valid recognition of achievement more difficult;
  • the kinds of learning that take place in connectivist MOOCs or courses are not necessarily academic, in the sense of meeting the requirements for academic knowledge, as defined in Chapter 2;
  • many participants struggle with the lack of structure and are overwhelmed by the volume of content generated by other learners;
  • most students need a high level of explicit support in learning from an ‘expert’ teacher and this is lacking in connectivist courses
  • this kind of learning requires learners already to have at least some level of more formal or traditional education before they participate if they are to fully benefit from this kind of learning experience (and there is substantial evidence that MOOC participants tend to have an already high level of post-secondary education).
  • thus this kind of learning is more appropriate for non-formal learning or communities of practice than for formal education.

Some of these criticisms may be overcome as practice improves, as new tools for assessment, and for organizing co-operative and collaborative work with massive numbers, are developed, and as more experience is gained. More importantly, connectivism is really the first theoretical attempt to radically re-examine the implications for learning of the Internet and the explosion of new communications technologies.

Conclusion

Different theories of learning reflect different positions on the nature of knowledge. With the possible exception of connectivism, there is some form of empirical evidence to support each of the theories of learning outlined here.

However, while the theories suggest different ways in which all people learn, they do not automatically tell teachers or instructors how to teach. Indeed, theories of behaviourism, cognitivism and constructivism were all developed outside of education, in experimental labs, psychology , neuroscience, and psychotherapy respectively. Educators have had to work out how to move from the theoretical position to the practical one of applying these theories within an educational experience. In other words, they have had to develop teaching methods that build on such learning theories. The next section of the book examines a range of teaching methods that have been developed, their epistemological roots, and their implications for teaching in a digital age.

Over to you

Your feedback on this will be invaluable. In particular:

  • are theories of learning still relevant in a digital age? Is it important to discuss these?
  • is the description of the various theories accurate and useful; if not, what should be changed?
  • are there important theories or theoretical positions that have been missed?

References

Bloom, B., Englehart, M., Furst, E., Hill, W. and Krathwohl, D. (1956) Taxonomy of Educational Objectives, Handbook I: The Cognitive Domain, Longmans Green, New York, 1956

Downes, S. (2014) The MOOC of One, Stephen’s Web, March 10

Fontana, D. (1981) Psychology for Teachers London: Macmillan/British Psychological Society

Harasim, L. (2012) Learning Theory and Online Technologies New York/London: Routledge

Knapper, C. (2010) ‘Changing Teaching Practice: Barriers and Strategies’ in Christensen Hughes, J. and Mighty, J. eds. Taking Stock: Research on Teaching and Learning in Higher Education Toronto ON: McGill-Queen’s University Press

Lewin, K. (1951) Field theory in social science; selected theoretical papers. D. Cartwright (ed.). New York: Harper & Row.

Rogers, C. (1969) Freedom to Learn Columbus, OH: Charles E. Merrill Publishing Co.

Schunk, D. (2011) Learning Theories: An Educational Perspective (6th edition) New York: Pearson

The nature of knowledge and the implications for teaching

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© LifeSun, 2013

© LifeSun, 2013

Teaching in a Digital Age

I’ve now just published Chapter 2 of my open textbook, Teaching in a Digital Age.

Chapter 1 looks at the fundamental changes that are happening in our digital age, and the broad implications these changes have for teaching and learning.

The book examines the underlying principles that guide effective teaching in an age when everyone,and in particular the students we are teaching, are using technology.

The Preface spells out in more detail the reasons why I decided to publish the book, and the reasons for choosing an open format.

Chapter 2: The nature of knowledge and the implications for teaching

This chapter discusses the relationship between our views on the nature of knowledge and the way we decide to teach. It’s about epistemology, but don’t be frightened off by the term: its basically about what makes us believe something is ‘true.’ This has fundamental implications for how we decide to teach. The chapter covers the following:

1. A dinner party scenario showing a clash of fundamental beliefs about the nature of knowledge between an engineer and a writer.

2. Art, theory, research and best practices in teaching: what guides (or should guide) the way we teach.

3. A brief introduction to epistemology and why it’s important. In particular it very briefly describes three currently popular epistemological positions in education, objectivism, constructivism and connectivism, and their implications for teaching and learning.

4. Academic knowledge. I make the distinction between academic knowledge and everyday knowledge, and then discuss whether new digital technologies change the nature of knowledge, ending with a justification for academic knowledge in a digital age, while also arguing that other forms of knowledge can be equally important, depending on the circumstances.

The key takeaways from the chapter are as follows:

1. Teaching is a highly complex occupation, which needs to adapt to a great deal of variety in context, subject matter and learners. It does not lend itself to broad generalizations. Nevertheless it is possible to provide guidelines or principles based on best practices, theory and research, that must then be adapted or modified to local conditions.

2. Our underlying beliefs and values, usually shared by other experts in a subject domain, shape our approach to teaching. These underlying beliefs and values are often implicit and are often not directly shared with our students, even though they are seen as essential components of becoming an ‘expert’ in a particular subject domain.

3. It is argued that academic knowledge is different from other forms of knowledge, and is even more relevant today in a digital age.

4. However, academic knowledge is not the only kind of knowledge that is important in today’s society, and as teachers we have to be aware of other forms of knowledge and their potential importance to our students, and make sure that we are providing the full range of contents and skills needed for students in a digital age.

Comments and criticisms are welcome, either as comments to this blog post, or as comments directly to the chapter (but see below).

Technical challenges with open publishing

As I reported in an earlier post, I’m trying to push the boundaries with open publishing. I want to make the book as interactive as possible but to date the open publishing technology ironically is very restraining. I’m getting tremendous help from the open textbook team at BCcampus, but the platform, PressBooks, is still very much designed in the mode of a traditional book.

So far, BCcampus has been able to add functions for learning objectives, tables, activities, and key takeaways, which have been very helpful. A moderated comment  function has just been added for the end of each chapter (I’m still trying to work out how to moderate this – I’m bloody useless with the technology!)

Here’s what I’m still trying for at the moment:

1. A comment facility that an author can add to each section, as well as the whole chapter.

2. To find a neat way for me as author to provide feedback on readers’ responses to the activities.

3. To find a good, robust, reliable, secure open source, free threaded discussion forum that will allow me to manage discussion forums on different topics covered by the book – or another way to integrate an asynchronous discussion function within the book. (Yes, I AM a social constructivist!)

Any suggestions welcome – we are actively exploring options at the moment. There are probably good solutions already out there. As I said, I’m not primarily a technologist but an educator, so help is definitely needed.

Next chapter: Theory and practice in teaching for a digital age: 

  • Summary of current learning theories and teaching approaches
  • Teaching and learning styles
  • Deep vs surface learning.
  • Learner-centered teaching, learner engagement, motivation.
  • What we know about skills development
  • Competency based learning
  • Learning design models (ADDIE, communities of practice, flexible design models, personalized learning environments).
  • Digital natives and digital literacy
  • Summary of research on teaching.

I still have more work to do on this outline: suggestions welcome.

Your homework

In the meantime, please take a look at Chapter 2 and send me your comments. In particular:

1. Is it too theoretical or abstract?

2. Have I accurately represented objectivism, constructivism and connectivism?

3. Do you agree that academic knowledge is different from everyday knowledge, and that it is an important distinction?

4. Does the scenario work for you?

5. Would you recommend this chapter to your teaching colleagues as worthwhile reading?

Hey – it IS an open textbook, and there’s no more World Cup football after Sunday.

Are universities teaching the skills needed in a knowledge-based economy?

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Knowledge worker 2

I’ve been on holiday the last two and a half weeks, but also doing some writing for my open textbook on teaching in a digital age.

Are universities teaching the skills needed in a knowledge-based economy?

This is one of the questions I have been asking myself, and there of course a couple of ways to respond to this:

1. Of course – we teach critical thinking, problem solving, research skills, and encourage original thinking: just the skills needed in today’s work force.

2. That’s not our job. Our job is the pure exploration of new knowledge and ideas and to pass that love of knowledge on to the next generation. If some of that rubs off in the commercial world, well and good, but that’s not our purpose.

I have a little bit of sympathy for the second answer. Universities provide society with a safe way of gambling on the future, by encouraging innovative research and development that may have no immediate apparent short-term benefits, or may lead to nowhere, without incurring major commercial or social loss. Another critical role is the ability to challenge the assumptions or positions of powerful agencies outside the university, such as government or industry, when these seem to be in conflict with evidence or ethical principles or the general good of society. There is a real danger in tying university and college programs too closely to immediate labour market needs. Labour market demand can shift very rapidly, and in particular, in a knowledge-based society, it is impossible to judge what kinds of work, business or trades will emerge in the future.

However the rapid expansion in higher education and the very large sums invested in higher education is largely driven by government, employers and parents wanting a work-force that is employable, competitive and if possible affluent. Indeed, this has always been one role for universities, which started as preparation and training for the church, law and much later, government administration.

So it’s the first response I want to examine more closely. Are the skills that universities claim to be developing (a) actually being done and (b) if they are being done, are they really the skills needed in a knowledge-based economy.

The characteristics of knowledge-based workers

To answer that question let’s attempt to identify the characteristics of knowledge-based workers. Here’s my view on this (somewhat supported by bodies such as the Canadian Chamber of Commerce and the OECD – I’m searching for the actual references.)

  • they usually work in small companies (less than 10 people)
  • they sometimes own their own business, or are their own boss; sometimes they have created their own job, which didn’t exist until they worked out there was a need and they could meet that need
  • they often work on contract, so they move around from one job to another fairly frequently
  • the nature of their work tends to change over time, in response to market and technological developments and thus the knowledge base of their work tends to change rapidly
  • they are digitally smart or at least competent digitally; digital technology is often a key component of their work
  • because they often work for themselves or in small companies, they play many roles: marketer, designer, salesperson, accountant/business manager, technical support, for example
  • they depend heavily on informal social networks to bring in business and to keep up to date with current trends in their area of work
  • they need to keep on learning to stay on top in their work, and they need to manage that learning for themselves
  • above all, they need to be flexible, to adapt to rapidly changing conditions around them.

It can be seen then that it is difficult to predict with any accuracy what many graduates will actually be doing ten or so years after graduation, except in very broad terms. Even in areas where there are clear professional tracks, such as medicine, nursing or engineering, the knowledge base and even the working conditions are likely to undergo rapid change and transformation over that period of time. However, we shall see that it is possible to predict the skills they will need to survive and prosper in such an environment.

Content and skills

Knowledge involves two strongly inter-linked but different components: content and skills. Content includes facts, ideas, principles, evidence, and descriptions of processes or procedures.

The skills required in a knowledge society include the following (Conference Board of Canada, 1992):

  • communications skills: as well as the traditional communication skills of reading, speaking and writing coherently and clearly, we need to add social media communication skills. These might include the ability to create a short YouTube video to capture the demonstration of a process or to make a sales pitch, the ability to reach out through the Internet to a wide community of people with one’s ideas, to receive and incorporate feedback, to share information appropriately, and to identify trends and ideas from elsewhere;
  • the ability to learn independently: this means taking responsibility for working out what you need to know, and where to find that knowledge. This is an ongoing process in knowledge-based work, because the knowledge base is constantly changing. Incidentally I am not talking here necessarily of academic knowledge, although that too is changing; it could be learning about new equipment, new ways of doing things, or learning who are the people you need to know to get the job done;
  • ethics and responsibility: this is required to build trust (particularly important in informal social networks), but also because generally it is good business in a world where there are many different players, and a greater degree of reliance on others to accomplish one’s own goals;
  • teamwork and flexibility: although many knowledge workers work independently or in very small companies, they depend heavily on collaboration and the sharing of knowledge with others in related but independent organizations. In small companies, it is essential that all employees work closely together, share the same vision for a company and help each other out. The ‘pooling’ of collective knowledge, problem-solving and implementation requires good teamwork and flexibility in taking on tasks or solving problems that may be outside a narrow job definition but necessary for success;
  • thinking skills (critical thinking, problem-solving, creativity, originality, strategizing): of all the skills needed in a knowledge-based society, these are some of  the most important. Businesses increasingly depend on the creation of new products, new services and new processes to keep down costs and increase competitiveness. Universities in particular have always prided themselves on teaching such intellectual skills, but we have seen that the increased move to larger classes and more information transmission, especially at the undergraduate level, challenges this assumption. Also, it is not just in the higher management positions that these skills are required. Trades people in particular are increasingly having to be problem-solvers rather than following standard processes, which tend to become automated. Anyone dealing with the public needs to be able to identify needs and find appropriate solutions;
  • digital skills: most knowledge-based activities depend heavily on the use of technology. However the key issue is that these skills need to be embedded within the knowledge domain in which the activity takes place. This means for instance real estate agents knowing how to use geographical information systems to identify sales trends and prices in different geographical locations, welders knowing how to use computers to control robots examining and repairing pipes, radiologists knowing how to use new technologies that ‘read’ and analyze MRI scans. Thus the use of digital technology needs to be integrated with and evaluated through the knowledge-base of the subject area;
  • knowledge management: this is perhaps the most over-arching of all the skills. Knowledge is not only rapidly changing with new research, new developments, and rapid dissemination of ideas and practices over the Internet, but the sources of information are increasing, with a great deal of variability in the reliability or validity of the information. Thus the knowledge that an engineer learns at university can quickly become obsolete. There is so much information now in the health area that it is impossible for a medical student to master all drug treatments, medical procedures and emerging science such a genetic engineering, even within an eight year program. The key skill in a knowledge-based society is knowledge management: how to find, evaluate, analyze, apply and disseminate information, within a particular context. This is a skill that graduates will need to employ long after graduation.

Most faculty, at least in universities, are well trained in content and have a deep understanding of the subject areas in which they are teaching. Expertise in skills development though is another matter. The issue here is not so much that faculty do not help students develop skills – they do – but whether these intellectual skills match the needs of knowledge-based workers, and whether enough emphasis is given to skills development within the curriculum.

Embedding skills in the curriculum

We know a lot from research about skills and skill development (again, references to come):

  • skills development is relatively context-specific. In other words, these skills need to be embedded within a knowledge domain. For example, problem solving in medicine is different from problem-solving in business. Different processes and approaches are used to solve problems in these domains (for instance, medicine tends to be more deductive, business more intuitive; medicine is more risk averse, business is more likely to accept a solution that will contain a higher element of risk or uncertainty);
  • learners need practice – often a good deal of practice – to reach mastery and consistency in a particular skill;
  • skills are often best learned in relatively small steps, with steps increasing as mastery is approached;
  • learners need feedback on a regular basis to learn skills quickly and effectively; immediate feedback is usually better than late feedback;
  • although skills can be learned by trial and error without the intervention of a teacher, coach, or technology, skills development can be greatly enhanced with appropriate interventions, which means adopting appropriate teaching methods and technologies  for skills development.
  • although content can be transmitted equally effectively through a wide range of media, skills development is much more tied to specific teaching approaches and technologies.

What should we do?

So here are some questions to discuss at the next departmental meeting discussing curriculum:

  • what are the skills we are trying to develop in this program? Are they explicitly stated and communicated to students?
  • how well do they match the skills required by knowledge-based workers? Do we need to add or adapt  existing skills to make them more relevant? If so, would this have a negative or a positive effect on the academic integrity of the program and particularly on the choice of content?
  • what teaching methods are most likely to lead the development of such skills?
  • what opportunities should we provide for practice and feedback on the development of the skills we have chosen?
  • how do we assess such skills?

Your feedback requested

1. Have I covered the main skills needed in a knowledge-based society? What have I missed?

2. Do you agree that these are important skills? If so, should universities explicitly try to develop them?

3. What are you or your university doing (if anything) to ensure such skills are taught, and taught well?

4. What roles if any do you think technology, and in particular online learning, can play in helping to develop such skills?

5. Any other comments on this topic