July 30, 2016

Online learning for beginners: 5. When should I use online learning?

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Knowledge-based industries include entertainment, such as video games design

Most subject disciplines now require students to know how technology influences their field of study

This is the fifth of a series of a dozen blog posts aimed at those new to online learning or thinking of possibly doing it. The other four are:

This question ‘When should I use online learning?’ is difficult to answer in a short post because there are many possible reasons, and as always in education, the answers are absolutely dependent on the specific context in which you are working, but the reasons can be classified under three main headings: academic, market, and policy/administrative.

Academic reasons

These boil down to relevancy and the changing nature of knowledge in a digital age.

Curriculum requirements

Technology is affecting the content of curriculum in nearly all subject disciplines. It is increasingly difficult to think of an academic area that is not undergoing profound changes as a result of information and communications technologies (ICTs). For instance, any business program now needs to look at the impact of social media and the Internet on marketing and on the delivery of goods. How are ICTs going to change financial investments and advising? In science and engineering, to what extent would animation, simulations or the use of virtual reality enable better understanding of three-dimensional phenomena, equations or formulae? In humanities and fine arts, to what extent are ICTs changing the way we express ourselves? How do we ensure our students are digitally literate and responsible? How do we prepare our students for a world controlled by massive technology companies who track our every movement and expression? It is difficult to think how these issues can be addressed without students themselves going online to study such issues.

Skills development

Also, the skills that our students will need to develop in a digital age will often best be achieved through the use of ICTs. In Chapter 1.2 of Teaching in a Digital Age, I give more detailed examples of such skills. Many of these skills are not only best developed by, but may not even be possible without, students spending an extensive period studying online.

However, I want to focus on two ‘core’ 21st century skills: independent learning and knowledge management. In a knowledge-based society, students will need to go on learning throughout life and outside the formal academic curriculum. Jobs are constantly changing as the knowledge base changes, and even our social lives are increasingly dominated by technological change. Independent learning – or self-learning – is a skill that itself can be taught. Online learning in particular requires self-discipline and independent learning, because the instructor is often not physically ‘there’. Thus gradually introducing learners to online learning can help build their independent learning skills.

Perhaps the overarching ’21st century skill’ though is knowledge management: how to find, analyse, evaluate, apply and communicate knowledge, especially when much of this knowledge is Internet-based or located, and constantly undergoing change. Students then need many opportunities to practice such skills, and online learning often provides a means by which this can be done in a cost-effective manner.

Whether we like it or not, an understanding and management of the use of ICTs is becoming critical in almost any subject area. Students will need to go online to study such phenomena, and to practice core 21st century skills. To do this students will need to spend much more time than at present studying online. (Again, though, we need to ensure that the balance between online and face-to-face time is also properly managed.)

Market reasons

Not only is knowledge undergoing rapid change, so are demographics. In most economically advanced societies, the population is aging. Over time, this will mean fewer younger students coming straight from high school, and more lifelong learners, perhaps already with post-secondary qualifications, but wanting to upgrade or move to a new profession or job and hence needing new knowledge and skills.

Also, with mass education, our students are increasingly diverse, in culture, languages and prior knowledge. One size of teaching does not fit all. We need ways then to individualise our programs. In particular, there are many pedagogical problems with very large lecture classes. They do not meet the needs of an increasingly diverse student population. Online learning is one way to allow students to work at different speeds, and to individualise the learning with online options enabling some choice in topics or level of study.

The changing population base offers opportunities as well as challenges. For instance, your area of research may be too specialised to offer a whole course or program within your current catchment area, but by going online you can attract enough students nationally or globally to make the effort worthwhile. These will be new students bringing in extra tuition revenues that can cover the full costs of an online masters degree, for instance. At the same time, online learning will enable critically important areas of academic development to reach a wider audience, helping create new labour markets and expand new areas of research.

Policy/administrative

We all know the situation where a President or Vice Chancellor has gone to a conference and come back ‘converted’. Suddenly the whole ship is expected to make an abrupt right turn and head off in a new direction. Unfortunately, online learning often leads to enthusiastic converts. MOOCs are a classic example of how a few elite universities suddenly got the attention of university leaders, who all charged off in the same direction.

Nevertheless, there can also be good policy reasons for institutional leadership wanting to move more to blended or flexible learning, for instance. One is to improve the quality of teaching and learning (breaking up large lecture classes is one example); another reason is to expand the reach of the university or college beyond its traditional base, for demographic and economic reasons; a third is to provide more flexibility for full-time students who are often working up to 15 hours a week to pay for their studies.

These policy shifts provide an excellent opportunity then to meet some of the academic rationales mentioned earlier. It is much easier to move into online learning if there is institutional support for this. This will include often extra money for release time for faculty to develop online courses, extra support in the way of instructional and media design, and even better chances of promotion or tenure.

Implications

  1. It can be seen that while market and policy reasons may be forcing you towards online learning, there are also excellent and valid academic reasons for moving in this direction.
  2. However, the extent to which online learning is a solution will depend very much on the particular context in which it will be used. It is essential that you think through carefully where it best fits within your own teaching context: blended learning for undergraduate students; masters programs for working professionals; skills development for applied learning; or all of these?
  3. Online learning is not going to go away. It will play a larger role in teaching in even the most campus-based institutions. Most of all, your students can benefit immensely from online learning, but only if it is done well.

Follow-up

Chapter 1, Fundamental Change in Education, of Teaching in a Digital Age, is basically a broader rationale for the use of online learning

Chapters 3 and 4 look at ways to individualise learning; see in particular:

Up next

‘How do I start?’

Your turn

If you have comments, questions or plain disagree, please use the comment box below.

 

Online learning for beginners: 2. Isn’t online learning worse than face-to-face teaching?

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Distance education: anyone sitting more than 10 rows from the front

Distance learning: anyone sitting more than 10 rows from the front

The short answer to this question is: no, online learning is neither inherently worse – nor better – than face-to-face teaching; it all depends on the circumstances.

The research evidence

There have been thousands of studies comparing face-to-face teaching to teaching with a wide range of different technologies, such as televised lectures, computer-based learning, and online learning, or comparing face-to-face teaching with distance education.

With regard to online learning there have been several meta-studies. A meta-study combines the results of many ‘well-conducted scientific’ studies, usually studies that use the matched comparisons or quasi-experimental method (Means et al., 2011; Barnard et al., 2014). Nearly all such ‘well-conducted’ meta-studies find no or little significant difference in the modes of delivery, in terms of the effect on student learning or performance. For instance, Means et al. (2011), in a major meta-analysis of research on blended and online learning for the U.S. Department of Education, reported:

In recent experimental and quasi-experimental studies contrasting blends of online and face-to-face instruction with conventional face-to-face classes, blended instruction has been more effective, providing a rationale for the effort required to design and implement blended approaches. When used by itself, online learning appears to be as effective as conventional classroom instruction, but not more so.

However, the ‘no significant difference’ finding is often misinterpreted. If there is no difference, then why do online learning? I’m comfortable teaching face-to-face, so why should I change?

This is a misinterpretation of the findings, because there may indeed within any particular study be large differences between conditions (face-to-face vs online), but they cancel each other out over a wide range of studies, or because with matched comparisons you are looking at only very specific, strictly comparable conditions, that never exist in a real teaching context.

For instance the ‘base’ variable chosen is nearly always the traditional classroom. In order to make a ‘scientific’ comparison, the same learning objectives and same treatment (teaching) is applied to the comparative condition (online learning). This means using exactly the same kind of students, for instance, in both conditions. But what if (as is the case) online learning better suits non-traditional students, or will achieve better learning outcomes if the teaching is designed differently to suit the context of online learning?

Asking the right questions

Indeed, it is the variables or conditions for success that we should be examining, not just the technological delivery. In other words, we should be asking a question first posed by Wilbur Schramm as long ago as 1977:

What kinds of learning can different media best facilitate, and under what conditions?

In terms of making decisions then about mode of delivery, we should be asking, not which is the best method overall, but:

What are the most appropriate conditions for using face-to-face, blended or fully online learning respectively? 

So what are the conditions that best suit online learning?

There are a number of possible answers:

  • learners:
    • fully online learning best suits more mature, adult, lifelong learners who already have good independent learning skills and for work and family reasons don’t want to come on campus
    • blended learning or a mix of classroom and fully online courses best suits full time undergraduate students who are also working part-time to keep their debt down, and need the flexibility to do part of their studies online
    • ‘dependent’ learners who lack self-discipline or who don’t know how to manage their own learning probably will do better with face-to-face teaching; however independent learning is a skill that can be taught, so blended learning is a safe way to gradually introduce such students to more independent study methods
  • learning outcomes:
    • embedding technology within the teaching may better enable the development of certain ’21st century skills’, such as independent learning, confidence in using information technologies within a specific subject domain, and knowledge management
    • online learning may provide more time on task to enable more practice of skills, such as problem-solving in math
    • redesign of very large lecture classes, so that lectures are recorded and students come to class for discussion and questions, making the classes more interactive and hence improving learning outcomes

Even this is really putting the question round the wrong way. A better question is:

What are the challenges I am facing as an instructor (or my learners are facing as students) that could be better addressed through online learning? And what form of online learning will work best for my students?

Quality

However, the most important condition influencing the effectiveness of both face-to-face and online teaching is how well it is done. A badly designed and delivered face-to-face class will have worse learning outcomes than a well designed online course – and vice versa. Ensuring quality in online learning will be the topic of the last few blogs in this series.

Implications

  1. Don’t worry about the effectiveness of online learning. Under the right conditions, it works well.
  2. Start with the challenges you face. Keep an open mind when thinking about whether online learning might be a better solution than continuing in the same old way.
  3. If you think it might be a solution for some of your problems, start thinking about the necessary conditions for success. The next few blog posts should help you with this.

Follow up

Here is some suggested further reading on the effectiveness of online learning:

Up next

‘Aren’t MOOCs online learning?’ (to be posted later in the week July 18-22, 2016)

Comparing modes: horses for courses

Comparing modes: horses for courses

Building an effective learning environment

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Learning environment 2

I was asked by the Chang School of Continuing Studies at Ryerson University to do a master class on this topic at their ChangSchoolTalks on February 17, based on Appendix 1 in my open, online textbook, Teaching in a Digital Age.

I was a little surprised by the request. I had moved what had originally been the second chapter of the book to an appendix, as I thought it was rather obvious and most instructors would already be aware of the key factors in an effective learning environment, so I was somewhat nervous about doing a master class for faculty and instructors on this topic.

As it turned out, I need not have worried. The master class was the first to be fully booked and the way the master class developed suggested that participants found the topic both stimulating and challenging. I think the reason for this is that my approach to building an effective learning environment is driven by a particular philosophy of education that is not always understood in post-secondary education. For this reason I thought I would share with you my thoughts on this in this post.

Learning as a ‘natural’ human activity

One premise behind building an effective learning environment is that it is inbuilt in humans to learn. If we had not been reasonably good at learning, we would have been killed off early in the earth’s history by faster, bigger and more ferocious animals. The ability not only to learn, but to learn in abstract and conscious ways, is therefore part of human nature.

If that is the case, a teacher’s job is not to do the learning for the student, but to build a rich environment that facilitates the kind of learning that will benefit the learner. It is not a question of pouring knowledge into a student’s head, but enabling the learner to develop concepts, think critically, and apply and evaluate what they have learned, by providing opportunities and experiences that are relevant to such goals.

Learning as development

A second premise is that knowledge is not fixed or static, but is continually developing. Our concept of heat changes and becomes richer as we grow older and become more educated, from understanding heat through touch, to providing a quantitative way of measuring it, to understanding its physical properties, to being able to apply that knowledge to solving problems, such as designing refrigerators. In a knowledge-based society, knowledge is constantly developing and growing, and our understanding is always developing.

This is one reason why I believe that one negative aspect of competency-based education is its attempt to measure competencies in terms of ‘mastery’ and limiting them to competencies required by employers. The difference between a skill and a competency is that there is no limit to a skill. You can continually improve a skill. We should be enabling students to develop skills that will carry them through maybe multiple employers, and enable them to adapt to changing market requirements, for instance.

If then we want students to develop knowledge and skills, we need to provide the right kind of learning environments  that encourage and support such development. Although analogies have their limitations, I like to think of education as gardening, where the learners are the plants. Plants know how to grow; they just need the right environment, the right balance of sun and shadow, the right soil conditions, enough water, etc. Our job as teachers is to make sure we are providing learners with those elements that will allow them to grow and learn. (The analogy breaks down though if we think of learners as having consciousness and free will, which adds an important element to developing an effective learning environment.)

There are many possible effective learning environments

Teaching is incredibly context-specific so the learning environment must be suitable to the context. For this reason, every teacher or instructor needs to think about and build their own learning environment that is appropriate to the context in which they are working. Here are some examples of different learning environments:

  • a school or college campus
  • an online course
  • military training
  • friends, family and work
  • nature
  • personal, technology-based, learning environments
A personal learning environment Image: jason Hews, Flikr

A personal learning environment
Image: jason Hews, Flikr

Nevertheless I will argue that despite the differences in context, there are certain elements or components that will be found in most effective learning environments.

In developing an effective learning environment, there are two issues I need to address up front:

  • First, it is the learner who has to do the learning.
  • Second, any learning environment is much more than the technology used to support it.

With regard to the first, teachers cannot do the learning for the learner. All they can do is to create and manage an environment that enables and encourages learning. My focus then in terms of building an effective learning environment is on what the  teacher can do, because in the end that is all they can control. However, the focus of what the teacher does should be on the learner, and what the learner needs. That of course will require good communication between the learners and the teacher.

Second, many technology-based personal learning environments are bereft of some of the key components that make an effective learning environment. The technology may be necessary but it is not sufficient. I suggest below what some of those components are.

Key components

These will vary somewhat, depending on the context. I will give examples below, but it is important for every individual teacher to think about what components may be necessary within their own context and then on how best to ensure these components are effectively present and used. (There is a much fuller discussion of this in Appendix 1 of my book)

Learner characteristics

This is probably the most important of all the components: the learners themselves. Some of the key characteristics are listed below:

  • what are their goals and motivation to learn what I am teaching them?
  • in what contexts (home, campus, online) will they prefer to learn?
  • how diverse are they in terms of language, culture, and prior knowledge?
  • how digitally capable are they?

Given these characteristics, what are the implications for providing an effective learning environment for these specific learners?

Content

  • what content do students need to cover? What are the goals in covering this content?
  • what sources of content are necessary? Who should find, evaluate, and apply these sources: me or the students? If the learners, what do I need to provide to enable them to do this?
  • how should the content be structured? Who should do this structuring: me or the learners? If learners, what do I need to provide to help them?
  • what is the right balance between breadth and depth of content for the learners in this specific context?
  • what activities will learners need in order to acquire and manage this content?

Skills

  • what skills do students need to develop?
  • what activities will enable learners to develop and apply these skills? (e.g. thinking, doing, discussing)
  • what is the goal in skill development? Mastery? A minimal level of performance? How will learners know this?

Learner support

  • what counselling and/or mentoring will learners need to succeed?
  • how will learners get feedback (particularly on skills development)?
  • how will learners relate to other learners so they are mutually supporting?

Resources

  • how much time can I devote to each of the components of a learning environment? What’s the best way to split my time?
  • what help will I get from other teaching staff, e.g. teaching assistants, librarians? What is the best way to use them?
  • what facilities will the learners have available (e.g. learning spaces, online resources)?
  • what technology can the learners use; how should this be managed and organized?

Assessment

  • what types of assessment should be used? (formative, essays, e-portfolios, projects)?
  • how will these measure the content and skills that learners are expected to master?

These questions are meant mainly as examples. Each teacher needs to develop and think about what components will be necessary in their context and how best to provide those components.

For instance, I did not include culture as a component. In some contexts, cultural change is one of the most important goals of education. Negative examples of this might include the culture of privilege encouraged in private British boarding schools, or the attempt to replace indigenous cultures with a western culture, as practiced in Canada with aboriginal residential schools. More positive cultural components may be to encourage inclusivity or ethical behaviour. Again, each teacher should decide on what components are important for their learners.

Necessary but not sufficient

Thinking about and implementing these components may be necessary, but they are not sufficient in themselves to ensure quality teaching and learning. In addition effective teaching still needs:

  • good design
  • empathy for the learners
  • teacher competence (e.g. subject knowledge)
  • imagination to create an effective learning environment.

Conclusions

The learners must do the learning. We need to make sure that learners are able to work within an environment that helps them do this. In other words, our job as teachers is to create the conditions for success.

There are no right or wrong ways to build an effective learning environment. It needs to fit the context in which students will learn. However, before even beginning to design a course or program, we should be thinking of what this learning environment could look like.

Technology now enables us to build a wide variety of effective learning environments. But technology alone is not enough; it needs to include other components for learner success. This is not to say that self-managing learners cannot build their own effective, personal learning environments, but they need to consider the other components as well as the technology.

Questions

  1. What other components would you add to a successful learning environment?
  2. Could you now design a different and hopefully better learning environment for your courses or programs? If so, what would it look like?
  3. Is this a helpful way to approach the design of online learning or indeed any other form of learning?

 

Automation or empowerment: online learning at the crossroads

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Image: Applift

Image: AppLift, 2015

You are probably, like me, getting tired of the different predictions for 2016. So I’m not going to do my usual look forward for the year for individual developments in online learning. Instead, I want to raise a fundamental question about which direction online learning should be heading in the future, because the next year could turn out to be very significant in determining the future of online learning.

The key question we face is whether online learning should aim to replace teachers and instructors through automation, or whether technology should be used to empower not only teachers but also learners. Of course, the answer will always be a mix of both, but getting the balance right is critical.

An old but increasingly important question

This question, automation or human empowerment, is not new. It was raised by B.F. Skinner (1968) when he developed teaching machines in the early 1960s. He thought teaching machines would eventually replace teachers. On the other hand, Seymour Papert (1980) wanted computing to empower learners, not to teach them directly. In the early 1980s Papert got children to write computer code to improve the way they think and to solve problems. Papert was strongly influenced by Jean Piaget’s theory of cognitive development, and in particular that children constructed rather than absorbed knowledge.

In the 1980s, as personal computers became more common, computer-assisted learning (CAL or CAD) became popular, using computer-marked tests and early forms of adaptive learning. Also in the 1980s the first developments in artificial intelligence were applied, in the form of intelligent math tutoring. Great predictions were made then, as now, about the potential of AI to replace teachers.

Then along came the Internet. Following my first introduction to the Internet in a friend’s basement in Vancouver, I published an article in the first edition of the Journal of Distance Education, entitled ‘Computer-assisted learning or communications: which way for IT in distance education?’ (1986). In this paper I argued that the real value of the Internet and computing was to enable asynchronous interaction and communication between teacher and learners, and between learners themselves, rather than as teaching machines. This push towards a more constructivist approach to the use of computing in education was encapsulated in Mason and Kaye’s book, Mindweave (1989). Linda Harasim has since argued that online collaborative learning is an important theory of learning in its own right (Harasim, 2012).

In the 1990s, David Noble of York University attacked online learning in particular for turning universities into ‘Digital Diploma Mills’:

‘universities are not only undergoing a technological transformation. Beneath that change, and camouflaged by it, lies another: the commercialization of higher education.’

Noble (1998) argued that

‘high technology, at these universities, is often used not to ……improve teaching and research, but to replace the visions and voices of less-prestigious faculty with the second-hand and reified product of academic “superstars”.

However, contrary to Noble’s warnings, for fifteen years most university online courses followed more the route of interaction and communication between teachers and students than computer-assisted learning or video lectures, and Noble’s arguments were easily dismissed or forgotten.

Then along came lecture capture and with it, in 2011, Massive Open Online Courses (xMOOCs) from Coursera, Udacity and edX, driven by elite, highly selective universities, with their claims of making the best professors in the world available to everyone for free. Noble’s nightmare suddenly became very real. At the same time, these MOOCs have resulted in much more interest in big data, learning analytics, a revival of adaptive learning, and claims that artificial intelligence will revolutionize education, since automation is essential for managing such massive courses.

Thus we are now seeing a big swing back to the automation of learning, driven by powerful computing developments, Silicon Valley start-up thinking, and a sustained political push from those that want to commercialize education (more on this later). Underlying these developments is a fundamental conflict of philosophies and pedagogies, with automation being driven by an objectivist/behaviourist view of the world, compared with the constructivist approaches of online collaborative learning.

In other words, there are increasingly stark choices to be made about the future of online learning. Indeed, it is almost too late – I fear the forces of automation are winning – which is why 2016 will be such a pivotal year in this debate.

Automation and the commercialization of education

These developments in technology are being accompanied by a big push in the United States, China, India and other countries towards the commercialization of online learning. In other words, education is being seen increasingly as a commodity that can be bought and sold. This is not through the previous and largely discredited digital diploma mills of the for-profit online universities such as the University of Phoenix that David Noble feared, but rather through the encouragement and support of commercial computer companies moving into the education field, companies such as Coursera, Lynda.com and Udacity.

Audrey Watters and EdSurge both produced lists of EdTech ‘deals’ in 2015 totalling between $1-$2 billion. Yes, that’s right, that’s $1-$2 billion in investment in private ed tech companies in the USA (and China) in one year alone. At the same time, entrepreneurs are struggling to develop sustainable business models for ed tech investment, because with education funded publicly, a ‘true’ market is restricted. Politicians, entrepreneurs and policy makers on the right in the USA increasingly see a move to automation as a way of reducing government expenditure on education, and one means by which to ‘free up the market’.

Another development that threatens the public education model is the move by very rich entrepreneurs such as the Gates, the Hewletts and the Zuckerbergs to move their massive personal wealth into ‘charitable’ foundations or corporations and use this money for their pet ‘educational’ initiatives that also have indirect benefits for their businesses. Ian McGugan (2015) in the Globe and Mail newspaper estimates that the Chan Zuckerberg Initiative is worth potentially $45 billion, and one of its purposes is to promote the personalization of learning (another name hi-jacked by computer scientists; it’s a more human way of describing adaptive learning). Since one way Facebook makes its money is by selling personal data, forgive my suspicions that the Zuckerberg initiative is a not-so-obvious way of collecting data on future high earners. At the same time, the Chang Zuckerberg initiative enables the Zuckerberg’s to avoid paying tax on their profits from Facebook. Instead then of paying taxes that could be used to support public education, these immensely rich foundations enable a few entrepreneurs to set the agenda for how computing will be used in education.

Why not?

Technology is disrupting nearly every other business and profession, so why not education? Higher education in particular requires a huge amount of money, mostly raised through taxes and tuition fees, and it is difficult to tie results directly to investment. Surely we should be looking at ways in which technology can change higher education so that it is more accessible, more affordable and more effective in developing the knowledge and skills required in today’s and tomorrow’s society?

Absolutely. It is not so much the need for change that I am challenging, but the means by which this change is being promoted. In essence, a move to automated learning, while saving costs, will not improve the learning that matters, and particularly the outcomes needed in a digital age, namely, the high level intellectual skills of critical thinking, innovation, entrepreneurship, problem-solving , high-level multimedia communication, and above all, effective knowledge management.

To understand why automated approaches to learning are inappropriate to the needs of the 21st century we need to look particularly at the tools and methods being proposed.

The problems with automating learning

The main challenge for computer-directed learning such as information transmission and management through Internet-distributed video lectures, computer-marked assessments, adaptive learning, learning analytics, and artificial intelligence is that they are based on a model of learning that has limited applications. Behaviourism works well in assisting rote memory and basic levels of comprehension, but does not enable or facilitate deep learning, critical thinking and the other skills that are essential for learners in a digital age.

R. and D. Susskind (2015) in particular argue that there is a new age in artificial intelligence and adaptive learning driven primarily by what they call the brute force of more powerful computing. Why AI failed so dramatically in the 1980s, they argue, was because computer scientists tried to mimic the way that humans think, and computers then did not have the capacity to handle information in the way they do now. When however we use the power of today’s computing, it can solve previously intractable problems through analysis of massive amounts of data in ways that humans had not considered.

There are several problems with this argument. The first is that the Susskinds are correct in that computers operate differently from humans. Computers are mechanical and work basically on a binary operating system. Humans are biological and operate in a far more sophisticated way, capable of language creation as well as language interpretation, and use intuition as well as deductive thinking. Emotion as well as memory drives human behaviour, including learning. Furthermore humans are social animals, and depend heavily on social contact with other humans for learning. In essence humans learn differently from the way machine automation operates.

Unfortunately, computer scientists frequently ignore or are unaware of the research into human learning. In particular they are unaware that learning is largely developmental and constructed, and instead impose an old and less appropriate method of teaching based on behaviourism and an objectivist epistemology. If though we want to develop the skills and knowledge needed in a digital age, we need a more constructivist approach to learning.

Supporters of automation also make another mistake in over-estimating or misunderstanding how AI and learning analytics operate in education. These tools reflect a highly objectivist approach to teaching, where procedures can be analysed and systematised in advance. However, although we know a great deal about learning in general, we still know very little about how thinking and decision-making operate biologically in individual cases. At the same time, although brain research is promising to unlock some of these secrets, most brain scientists argue that while we are beginning to understand the relationship between brain activity and very specific forms of behaviour, there is a huge distance to travel before we can explain how these mechanisms affect learning in general or how an individual learns in particular. There are too many variables (such as emotion, memory, perception, communication, as well as neural activity) at play to find an isomorphic fit between the firing of neurons and computer ‘intelligence’.

The danger then with automation is that we drive humans to learn in ways that best suit how machines operate, and thus deny humans the potential of developing the higher levels of thinking that make humans different from machines. For instance, humans are better than machines at dealing with volatile, uncertain, complex and ambiguous situations, which is where we find ourselves in today’s society.

Lastly, both AI and adaptive learning depend on algorithms that predict or direct human behaviour. These algorithms though are not transparent to the end users. To give an example, learning analytics are being used to identify students at high risk of failure, based on correlations of previous behaviour online by previous students. However, for an individual, should a software program be making the decision as to whether that person is suitable for higher education or a particular course? If so, should that person know the grounds on which they are considered unsuitable and be able to challenge the algorithm or at least the principles on which that algorithm is based? Who makes the decision about these algorithms – a computer scientist using correlated data, or an educator concerned with equitable access? The more we try to automate learning, the greater the danger of unintended consequences, and the more need for educators rather than computer scientists to control the decision-making.

The way forward

In the past, I used to think of computer scientists as colleagues and friends in designing and delivering online learning. I am now increasingly seeing at least some of them as the enemy. This is largely to do with the hubris of Silicon Valley, which believes that computer scientists can solve any problem without knowing anything about the problem itself. MOOCs based on recorded lectures are a perfect example of this, being developed primarily by a few computer scientists from Stanford (and unfortunately blindly copied by many people in universities who should have known better.)

We need to start with the problem, which is how do we prepare learners for the knowledge and skills they will need in today’s society. I have argued (Bates, 2015) that we need to develop, in very large numbers of people, high level intellectual and practical skills that require the construction and development of knowledge, and that enable learners to find, analyse, evaluate and apply knowledge appropriately.

This requires a constructivist approach to learning which cannot be appropriately automated, as it depends on high quality interaction between knowledge experts and learners. There are many ways to accomplish this, and technology can play a leading role, by enabling easy access to knowledge, providing opportunities for practice in experientially-based learning environments, linking communities of scholars and learners together, providing open access to unlimited learning resources, and above all by enabling students to use technology to access, organise and demonstrate their knowledge appropriately.

These activities and approaches do not easily lend themselves to massive economies of scale through automation, although they do enable more effective outcomes and possibly some smaller economies of scale. Automation can be helpful in developing some of the foundations of learning, such as basic comprehension or language acquisition. But at the heart of developing the knowledge and skills needed in today’s society, the role of a human teacher, instructor or guide will remain absolutely essential. Certainly, the roles of teachers and instructors will need to change quite dramatically, teacher training and faculty development will be critical for success, and we need to use technology to enable students to take more responsibility for their own learning, but it is a dangerous illusion to believe that automation is the solution to learning in the 21st century.

Protecting the future

There are several practical steps that need to be taken to prevent the automation of teaching.

  1. Educators – and in particular university presidents and senior civil servants with responsibility for education – need to speak out clearly about the dangers of automation, and the technology alternatives available that still exploit its potential and will lead to greater cost-effectiveness. This is not an argument against the use of technology in education, but the need to use it wisely so we get the kind of educated population we need in the 21st century.
  2. Computer scientists need to show more respect to educators and be less arrogant. This means working collaboratively with educators, and treating them as equals.
  3. We – teachers and educational technologists – need to apply in our own work and disseminate better to those outside education what we already know about effective learning and teaching.
  4. Faculty and teachers need to develop compelling technology alternatives to automation that focus on the skills and knowledge needed in a digital age, such as:
    • experiential learning through virtual reality (e.g. Loyalist College’s training of border service agents)
    • networking learners online with working professionals, to solve real world problems (e.g. by developing a program similar to McMaster’s integrated science program for online/blended delivery)
    • building strong communities of practice through connectivist MOOCs (e.g. on climate change or mental health) to solve global problems
    • empowering students to use social media to research and demonstrate their knowledge through multimedia e-portfolios (e.g. UBC’s ETEC 522)
    • designing openly accessible high quality, student-activated simulations and games but designed and monitored by experts in the subject area.
  5. Governments need to put as much money into research into learning and educational technology as they do into innovation in industry. Without better and more defensible theories of learning suitable for a digital age, we are open to any quack or opportunist who believes he or she has the best snake oil. More importantly, with better theory and knowledge of learning disseminated and applied appropriately, we can have a much more competitive workforce and a more just society.
  6. We need to educate our politicians about the dangers of commercialization in education through the automation of learning and fight for a more equal society where the financial returns on technology applications are more equally shared.
  7. Become edupunks and take back the web from powerful commercial interests by using open source, low cost, easy to use tools in education that protect our privacy and enable learners and teachers to control how they are used.

That should keep you busy in 2016.

Your views are of course welcome – unless you are a bot.

References

Bates, A. (1986) Computer assisted learning or communications: which way for information technology in distance education? Journal of Distance Education Vol. 1, No. 1

Bates, A. (2015) Teaching in a Digital Age Victoria BC: BCcampus

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

Mason, R. and Kaye, A (Eds).(1989)  Mindweave: communication, computers and distance education. Oxford: Pergamon

McGugan, I. (2015)Why the Zuckerberg donation is not a bundle of joy, Globe and Mail, December 2

Noble, D. (1998) Digital Diploma Mills, Monthly Review http://monthlyreview.org/product/digital_diploma_mills/

Papert, S. (1980) Mindstorms: Children, Computers and Powerful Ideas New York: Basic Books

Skinner, B. (1968)  The Technology of Teaching, 1968 New York: Appleton-Century-Crofts

Susskind, R. and Susskind, D. (2015) The Future of the Professions: How Technology will Change the Work of Human Experts Oxford UK: Oxford University Press

Watters, A. (2015) The Business of EdTech, Hack Edu, undated http://2015trends.hackeducation.com/business.html

Winters, M. (2015) Christmas Bonus! US Edtech Sets Record With $1.85 Billion Raised in 2015 EdSurge, December 21 https://www.edsurge.com/news/2015-12-21-christmas-bonus-us-edtech-sets-record-with-1-85-billion-raised-in-2015

Another perspective on the personalisation of learning online

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To see the video recording click on the image

To see the video recording click on the image

I gave a keynote presentation last week at a large educational conference in the Netherlands, Dé Onderwijsdagen’ (Education Days). I was asked to talk about the personalisation of learning. I agreed as I think this is one of many potential advantages of online learning.

However, the personalisation of learning tends to be looked at often through a very narrow lens. I suggest that there are in fact at least seven ways in which online learning can facilitate the personalisation of learning. This is a blog post version of my keynote, which can be seen in full here.

Why personalisation?

Personalisation is one of the buzzwords going around these days in educational circles, like experiential learning or competency-based learning. Sometimes when I look more closely at some of the current buzzwords I end up thinking: ‘Oh, is that what it is? But I’ve always done that – I just haven’t given it that name before.’

However, I think there are good reasons why we should be focusing more on personalisation in post-secondary education:

  • the need to develop a wide range of knowledge and skills in learners for the 21st century;
  • as the system has expanded, so has the diversity of students: in age, language ability, prior learning, and interests;
  • a wider range of modes of delivery for students to choose from (campus, blended, fully online);
  • a wider range of media accessible not only to instructors but also to learners themselves;
  • the need to actively engage a very wide range of preferred learning styles, interests and motivation.

Clearly in such a context one size does not fit all. But with a continuously expanding post-secondary system and more pressures on faculty and instructors, how can we make learning more individualised in a cost-effective manner?

Seven roads to personalisation

I can think of at least seven ways to make learning more personal. In my keynote I discuss the strengths and weaknesess of each of these approaches:.

  • adaptive learning;
  • competency-based learning;
  • virtual personal learning environments;
  • multi-media, multi-mode courses and learning materials;
  • modularisation of courses and learning materials;
  • new qualifications/certification (badges, nanodegrees, etc.);
  • disaggregated services.

There are probably others and I would be interested in your suggestions. However I recommend that you look at the video presentation, as it provides more ‘flesh’ on each of these seven approaches to personalisation.

An overall design approach to personalisation

Personalisation of learning will work best if it is embedded within an overall, coherent learning design, In my keynote I suggest one approach that fully exploits both the potential of online learning and the personalisation of learning:

  • the development of the core skill of knowledge management within a particular subject domain (other skills development could also be included, such as independent learning, research, critical thinking, and 21st century communication)
  • the use of open content by students, guided and supported by the instructor
  • student-generated multi-media content through online project work
  • active online discussion embedded within and across the different student projects
  • assessment through personal e-portfolios and group project assessment.

Such an ‘open’ design allows for greater choice in topics and approaches by learners while still developing the core skills and knowledge needed by our learners in a digital age. Other designs are also of course possible to reach the same kind of overall learning goals.

The role of the instructor though remains crucial, both as a content expert, guiding students and ensuring that they meet the academic needs of the discipline, and in providing feedback and assessment of their learning.

Conclusion

With knowledge continuing to rapidly grow and change, and a wide range of skills as well as knowledge needed in a knowledge-based society, we need new approaches to teaching that address such challenges.

Also because of increased diversity in our students and a wide range of different learning needs, we need to develop more flexible teaching methods and modes of delivery. This will also mean understanding better the differences between media and using them appropriately in our teaching.

Making learning more personal for our students is increasingly important, but it is only one element in new designs for learning. There are in fact many possibilities, limited only by the imagination and vision of teachers and instructors.