August 21, 2014

Learning environments: a critical component of the design of online teaching

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Figure 5.1 A learning environment from the perspective of an instructor

Figure 5.1 A learning environment from the perspective of an instructor

I have now published the first four chapters of my open textbook ‘Teaching in a Digital Age’. These chapters have greatly benefited from your feedback.

I am now working on Chapter 5, ‘The design of teaching and learning.’

I’m offering you here my first thoughts on the design of teaching and learning, with a particular focus on creating and working with a rich learning environment that will support students’ learning.

Overview of the whole chapter

  • introduction to the design of teaching/learning design
  • learning environments
    • learner characteristics: digital natives and digital literacy; learning styles; family and work contexts
    • content: structure; sources; quantity/depth
    • skills: opportunities for skills development and practice; competency based learning,
    • learner support: activities; feedback;
    • resources: time; facilities;, technology
    • assessment: methods
  • learning design models (objectivist lectures/LMSs, ADDIE, online collaborative learning, communities of practice, flexible design models, PLEs/MOOC of One, AI approaches).
  • summary/conclusions

5.1 What is learning design?

It is one thing to have a good theory of learning and a choice of appropriate teaching method, but it is quite another to implement the chosen teaching method successfully. As noted in the previous chapter, teachers and instructors may need a mix of methods, depending on the circumstances. This means deliberately planning methods of teaching and a broad learning environment that will facilitate the development of the knowledge and skills that are needed.

Once again, though, there is extensive research and experience that point to the key factors to be taken into consideration in the successful implementation of teaching. In essence we are talking about using best practices in the design of teaching – sometimes called learning design.

We shall see that these principles may vary somewhat, depending on the chosen teaching method and the underlying epistemological position of each teacher, but a large number of the core principles in learning design extend across several of the teaching methods. These main principles can be summarised as follows:

  • know your students: identifying the key characteristics of the students you will be or could be teaching, and how that will/should influence your methods of teaching
  • know what you are trying to achieve: in any particular course or program what are the critical areas of content and in particular the particular skills or learning outcomes that students need to achieve as a result of your teaching? What is the best way to identify and assess these desired outcomes?
  • know how students learn: what drives learning for your students? How do you engage or motivate students? How can you best support that learning?
  • know how to implement this knowledge: what learning design model(s) will work best for you? What kind of learning environment do you need to create to support student learning?
  • know how to use technology to support your teaching: this is really a sub-set of the previous point, and will be discussed in much more detail in later chapters.

In order to implement these core principles of design, we need to construct effective learning environments for our students.

5.2 Learning environments

Definitions

Environment: ‘The surroundings or conditions in which a person, animal, or plant lives or operates.’

‘Learning environment refers to the diverse physical locations, contexts, and cultures in which students learn. Since students may learn in a wide variety of settings, such as outside-of-school locations and outdoor environments, the term is often used as a more accurate or preferred alternative to classroom, which has more limited and traditional connotations—a room with rows of desks and a chalkboard, for example.

The term also encompasses the culture of a school or class—its presiding ethos and characteristics, including how individuals interact with and treat one another—as well as the ways in which teachers may organize an educational setting to facilitate learning…..’

The Glossary of Educational Reform, 29 August, 2013

The latter definition recognises that students learn in many different ways in very different contexts. Since learners must do the learning, the aim is to create a total environment for learning that optimises the ability of students to learn.

There is of course no single optimum learning environment. There is an infinite number of possible learning environments, which is what makes teaching so interesting. Developing a total learning environment for students in a particular course or program is probably the most creative part of teaching.

There is a tendency in the literature to focus on either physical institutional learning environments (such as classrooms, lecture theatres and labs) or on the technologies used to to create online personal learning environments (PLEs), but as the definitions quoted above make clear, learning environments are broader than just the physical components. They include the goals for teaching and learning, what engages or motivates students to learn, what student activities will best support learning, and what assessment strategies best measure and drive student learning.

Thus one place to start in designing a learning environment for a course or program is to identify some of the key components.

Figure 5.1 A learning environment from the perspective of an instructor

Figure 5.1 A learning environment from the perspective of an instructor

Figure 5.1 illustrates one possible learning environment from the perspective of a teacher or instructor. It should be pointed out that this represents both a set of components that it may be difficult for an instructor to change (learner characteristics, resources, etc.), but which may nevertheless have important implications for how the course should be taught, and other components (content, skills to be taught, etc.) over which an instructor may have more choice or control. Within each of the main components there are a set of sub-components that will need to be considered. In fact, it is in the sub-components (content structure, practical activities, feedback, use of technology, assessment methods, etc.) where the real decisions need to be made.

I have listed just a few components in Figure 5.1 and the set is not meant to be comprehensive. For instance it could have included attitudes or social factors as well as content and skills, institutional factors (policies, priorities,etc.) and personal factors (being a part-time or adjunct faculty, a dual role as instructor and family carer, etc.), all of which might also affect the learning environment in which a teacher or instructor has to work. Creating a model of a learning environment then is a heuristic device that aims to provide a comprehensive view of the whole teaching context for a particular course or program, by a particular instructor or teacher with a particular view of learning. It is also not enough to list the components; they need to be organized, scheduled and integrated. The more detailed design of a course will then be built around and take best advantage of the learning environment.

Once again, our choice of components and their perceived importance will be driven to some extent by our personal epistemologies and beliefs about knowledge, learning and teaching methods. The preferred teaching method and epistemological position will influence which components of the learning environment get the most attention from a teacher or instructor. For instance, an instructor with a transmissive or objectivist view of teaching is likely to focus mainly on content and certain kinds of assessment tools, while a more constructivist or nurturing teacher will pay particular attention to learner characteristics (particularly their goals), and learner support.

Lastly, I have deliberately suggested a learning environment from the perspective of a teacher, as the teacher has the main responsibility for creating an appropriate learning environment, but it is also important to consider learning environments from the learners’ perspectives. Indeed, adult or mature learners are capable of creating their own, personal, relatively autonomous learning environments, and this will also be discussed in more depth later in the chapter.

The significant point here is that it is important to identify those components that need to be considered in teaching a course or program, and in particular that there are many components in addition to content or curriculum.  The key components of a learning environment will be discussed in more detail in later posts. After that, different learning design models will be discussed.

Up next

My next post will be on learner characteristics and their potential influence on the design of teaching – especially in a digital age.

Over to you

1. Is it legitimate to focus on a learning environment from a teacher’s perspective rather than a learner’s perspective?

2. What would you add (or remove) from the learning environment in Figure 5.1?

3. Does thinking about the whole learning environment overly complicate the teaching endeavour? Why not just get on with it?

Special edition on research on MOOCs in the journal ‘Distance Education’

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The University of Toronto is one of a number of institutions conducting research on MOOCs

The University of Toronto is one of a number of institutions conducting research on MOOCs; their results are still to come

The August 2014 edition of the Australian-based journal, Distance Education (Vol.35, No. 2.), is devoted to new research on MOOCs. There is a guest editor, Kemi Jona, from Northwestern University, Illinois, as well as the regular editor, Som Naidu.

The six articles in this edition are fascinating, both in terms of their content, but even more so in their diversity. There are also three commentaries, by Jon Baggaley, Gerhard Fischer and myself.

My commentary provides my personal analysis of the six articles.

MOOCs are a changing concept

In most of the literature and discussion about MOOCs, there is a tendency to talk about ‘instructionist’ MOOCs (i.e. Coursera, edX, Udacity, xMOOCs) or ‘connectivist’ MOOCs (i.e. Downes, Siemens, Cormier, cMOOCs). Although this is still a useful distinction, representing very different pedagogies and approaches, the articles in this edition show that MOOCs come in all sizes and varieties.

Indeed, it is clear that the design of MOOCs is undergoing rapid development, partly as a result of more players coming in to the market, partly because of the kinds of research now being conducted on MOOCs themselves, and, sadly much more slowly, a recognition by some of the newer players that much is already known about open and online education that needs to be applied to the design of MOOCs, while accepting that there are certain aspects, in particular the scale, that make MOOCs unique.

The diversity of MOOC designs

These articles illustrate clearly such developments. The MOOCs covered by the articles range from

  • MOOC video recorded lectures watched in isolation by learners (Adams et al.)
  • MOOC video lectures watched in co-located groups in a flipped classroom mode without instructor or tutorial support (Nan Li et al.)
  • MOOCs integrated into regular campus-based programs with some learner support (Firmin et al.)
  • MOOCs using participatory and/or connectivist pedagogy (Anderson, Knox)

Also the size of the different MOOC populations studied here differed enormously, from 54 students per course to 42,000.

It is also clear that MOOC material is being increasingly extracted from the ‘massive’, open context and used in very specific ‘closed’ contexts, such as flipped classrooms, at which point one questions the difference between such use of MOOCs and regular for-credit online programming, which in many cases also use recorded video lectures or online discussion and increasingly other sources of open educational materials. I would expect in such campus-based contexts the same quality standards to apply to the MOOC+ course designs as are already applied to credit-based online learning. Some of the research findings in these articles indirectly support the need for this.

The diversity of research questions on MOOCs

Almost as interesting is the range of questions covered by these articles, which include:

  • capturing the lived experience of being in a MOOC (Adams et al.; Knox)
  • the extent to which learners can/should create their own content, and the challenges around that (Knox; Andersen)
  • how watching video lectures in a group affects learner satisfaction (Nan Li et al.)
  • what ‘massive’ means in terms of a unique pedagogy (Knox)
  • the ethical implications of MOOCs (Marshall)
  • reasons for academic success and failure in ‘flipped’ MOOCs (Firmin et al.; Knox)

What is clear from the articles is that MOOCs raise some fundamental questions about the nature of learning in digital environments. In particular, the question of the extent to which learners need guidance and support in MOOCs, and how this can best be provided, were common themes across several of the papers, with no definitive answers.

The diversity of methodology in MOOC research

Not surprisingly, given the range of research questions, there is also a very wide range of methodologies used in the articles in this edition, ranging from

  • phenomenology (Adams),
  • heuristics (Marshall)
  • virtual ethnography (Knox; Andersen)
  • quasi-experimental comparisons (Nan Li et al.)
  • data and learning analytics (Firmin et al.)

The massiveness of MOOCs, their accessibility, and the wide range of questions they raise make the topic a very fertile area for research, and this is likely to generate new methods of research and analysis in the educational field.

Lessons learned

Readers are likely to draw a variety of conclusions from these studies. Here are mine:

  • the social aspect of learning is extremely important, and MOOCs offer great potential for exploiting this kind of learning, but organizing and managing social learning on a massive scale, without losing the potential advantages of collaboration at scale, is a major challenge that still remains to be adequately addressed. The Knox article in particular describes in graphic detail the sense of being overwhelmed by information in open connectivist MOOCs. We still lack methods or designs that properly support participants in such environments. This is a critical area for further research and development.
  • a lecture on video is still a lecture, whether watched in isolation or in groups. The more we attempt to support this transmissive model through organized group work, ‘facilitators’, or ‘advisors’ the closer we move towards conventional (and traditional) education and the further away from the core concept of a MOOC.
  • MOOCs have a unique place in the educational ecology. MOOCs are primarily instruments for non-formal learning. Trying to adapt MOOCs to the campus not only undermines their primary purpose, but risks moving institutions in the wrong direction. We would be better re-designing our large lecture classes from scratch, using criteria, methods and standards appropriate to the goals of formal higher education. My view is that in the long run, we will learn more from MOOCs about handling social learning at scale than about transmitting information at scale. We already know about that. It’s called broadcasting.
  • lastly, there was surprisingly little in the articles about what actual learning took place. In some cases, it was a deliberate research strategy not to enquire into this, relying more on student or instructor feelings and perceptions. While other potential benefits, such as institutional branding, stimulating interest, providing a network of connections, and so on, are important, the question remains: what are participants actually learning from MOOCs, and does this justify the hype and investment (both institutionally and in participants’ time) that surrounds them?

Cultural and ethical issues

The Marshall paper provides an excellent overview of ethical issues, but there is almost no representation of perspectives on MOOCs from outside Western contexts. I would have liked to have seen more on cultural and ethical issues arising from the globalization of MOOCs, based on actual cases or examples. Given the global implications of MOOCs, other perspectives are needed. Perhaps this is a topic for another issue.

Happy reading

I am sure you will be as fascinated and stimulated by these articles as I am. I am also sure you will come away with different conclusions from mine. I am sure we will see a flood of other articles soon on this topic. Nevertheless, these articles are important in setting the research agenda, and should be essential reading for MOOC designers as well as future researchers on this topic.

How to get the articles

To obtain access to these articles, go to: http://www.tandfonline.com/toc/cdie20/current#.U-1WqrxdWh1

Choosing teaching methods for a digital age

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 Video games designer 2

Introduction

I’m going to try to pull together here the main conclusions following my discussion of epistemologies, learning theories and methods of teaching that I’ve been covering as the ‘foundations’ for my open textbook on ‘Teaching in a Digital Age.’

What I’m focusing on in this post are the teaching methods that appear to best fit the needs of learners in a digital age, and in particular those that have the best chance of developing the knowledge and skills that they will need after graduation.

Epistemologies

I discussed very briefly in Chapter 2 the following epistemologies:

  • objectivism
  • constructivism
  • connectivism

Learning Theories

I discussed very briefly in Chapter 3 the following learning theories:

  • behaviourism
  • (social) constructivism
  • learning by doing
  • connectivism.

Methods of teaching

I discussed very briefly in Chapters 3 and 4 the following methods of teaching

  • transmissive lectures, including xMOOCs
  • teaching machines
  • computer-assisted learning
  • computer-based training
  • adaptive learning
  • interactive lectures, including flipped learning
  • seminars and tutorials
  • online collaborative learning
  • cMOOCs
  • labs, workshops and field trips
  • traditional and cognitive apprenticeship
  • experiential learning
  • nurturing
  • social reform

Again, the aim has not been to cover all epistemologies, theories of learning and methods of teaching, but to look at a wide range that have implications for developing the knowledge and skills identified in Chapter 1.

Relating epistemology, learning theories and teaching methods

Although there is often a direct relationship between a method of teaching, a learning theory and an epistemological position, this is by no means always the case. It is tempting to try to put together a table and neatly fit each teaching method into a particular learning theory, and each theory into a particular epistemology, but unfortunately education is not as tidy as computer science, so it would be misleading to try to do a direct ontological classification. For instance a transmissive lecture might be structured so as to further a cognitivist rather than a behaviourist approach to learning, or a lecture session may combine several elements, such as transmission of information, learning by doing, and discussion.

Purists may argue that it is logically inconsistent for a teacher to use methods that cross epistemological boundaries (and it may certainly be confusing for students) but teaching is essentially a pragmatic profession and teachers will do what it takes to get the job done. If students need to learn facts, principles, standard procedures or ways of doing things, before they can start an informed discussion about their meaning, or before they can start solving problems, then a teacher may well consider behaviourist methods to lay this foundation before moving to more constructivist approaches later in a course or program.

Similarly we have seen that technology applications such as MOOCs or video recorded lectures may replicate exactly a particular teaching method or approach to learning used in the classroom. In many ways these methods of teaching, theories of learning and epistemologies are independent of a particular technology or medium of delivery, although we shall see in Chapter 6 that technologies can be used to transform teaching, and a particular technology will in some cases further one method of teaching more easily than others, depending on the characteristics or ‘affordances’ of that technology.

Thus, teachers who are aware of not only a wide array of teaching methods, but also of learning theories and their epistemological foundation will be in a far better position to make appropriate decisions about how to teach in a particular context. Also, as we shall see, having this kind of understanding will also facilitate an appropriate choice of technology for a particular learning task or context.

Relating teaching methods to the knowledge and skills needed in a digital age

The main purpose of this whole exercise has been to enable you as a teacher to identify the teaching methods that are most likely to support the development of the knowledge and skills that students or learners will need in a digital age. We still have a way to go before we have all the information and tools needed to make this decision, but we can at least have a stab at it from here, while recognising that such decisions will depend on a wide variety of factors, such as the nature of the learners and their prior knowledge and experience, the demands of particular subject areas, the institutional context in which teachers and learners find themselves, and the likely employment context for learners.

First, we can identify a number of different types of skills needed:

  • conceptual skills, such as knowledge management, critical thinking, analysis, synthesis, problem-solving, creativity/innovation, experimental design
  • developmental or personal skills, such as independent learning, communications skills, ethics, networking, responsibility and teamwork
  • digital skills, embedded within and related to a particular subject or professional domain
  • manual and practical skills, such as machine or equipment operation, safety procedures, observation and recognition of data, patterns, and spatial factors.

There are several key points for a teacher or instructor to note:

  • the teacher needs to be able to identify/recognise the skills they are hoping to develop in their students within a particular course or program
  • these skills are often not easily separated but tend to be contextually based and often integrated
  • teachers need to identify appropriate methods and contexts that will enable students to develop these skills
  • students will need practice to develop such skills.
  • students will need feedback and intervention from the teacher and other students to ensure a high level of competence or mastery in the skill
  • an assessment strategy needs to be developed that recognises and rewards students’ competence and mastery of such skills

One thing that becomes clear here is that just choosing a particular teaching method such as seminars or apprenticeship is not going to be sufficient. We have to provide a rich learning environment for students to develop such skills that includes contextual relevance, and opportunities for practice, discussion and feedback. As a result, we are likely to combine different methods of teaching. It is unlikely that one method, such as transmissive lectures, or seminars, will provide a rich enough learning environment for a full range of skills to be developed within the subject area.

So it would be foolish at this stage to say that seminars, or apprenticeship, or nurturing, is the best method for developing this range of skills. At the same time, we can see the limitations of transmissive lectures, especially if they are used as the dominant method for teaching.

In order to better answer the question, we need to look more closely at the design of teaching, which means deliberately planning methods of teaching and a broad learning environment that will facilitate the development of the knowledge and skills that our students need. This will be the subject of my next chapter, which I will also share through further blog posts.

Key takeaways from Chapter 4

This list of teaching methods is not meant to be exhaustive or comprehensive. The aim is to show that there many different ways to teach, and all are in some ways legitimate in certain circumstances. Most instructors will mix and match different methods, depending on the needs of both the subject matter and the needs of their students at a particular time (a topic covered in Chapter 5.). There are though some core conclusions to be drawn from this comparative review of different approaches to teaching.

  1. No single method is likely to meet all the requirements teachers face in a digital age.
  2. Nevertheless, some forms of teaching fit better with the development of the skills needed in a digital age. In particular, methods that focus on conceptual development, such as dialogue and discussion, and knowledge management, rather than information transmission, and experiential learning in real-world contexts, are more likely to develop the high level conceptual skills required in a digital age.
  3. It is not just conceptual skills though that are needed. It is the combination of conceptual, practical and personal and social skills in highly complex situations that are needed. This again means combining a variety of teaching methods.
  4. Nearly all of these teaching methods are media or technology independent. In other words, they can be used in classrooms or online. What matters from a learning perspective is not so much the choice of technology as the efficacy and expertise in appropriately choosing and using the teaching method.
  5. Nevertheless, we shall see later in this book that new technologies offer new possibilities for teaching, including offering more practice or time on task, reaching out to new target groups, and increasing the productivity of both teachers and the system as a whole.
  6. In order though to fully exploit the benefits of new technologies, changes to the way we teach will be necessary, making some methods, such as transmissive lectures, almost redundant, at least as far as developing skills for a digital age are concerned.
  7. It is not enough to look just at teaching methods; we need to look at designing an appropriate learning environment to help foster and develop the knowledge and skills that students will need. We shall see that technology can be particularly helpful in providing such rich learning contexts.

Lastly, the full first draft of Chapter 4, Methods of Teaching in a Digital Age, is now complete and can be accessed here - subject, of course, to any feedback I get from you on this post!

The nurturing and social reform models of teaching and their relevance to connectivist online learning

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Counselling face-to-face 2 A counsellor and student at Empire State College, New York, which has a mentoring approach to adult education

These are the last of the teaching models discussed in Chapter 4 of my open textbook, ‘Teaching in a Digital Age.’ (I thought I had covered all five of Pratt’s perspectives on teaching in my last blog post, but realised I had accidentally left out these two important approaches to teaching. I have also added a scenario to introduce the Chapter.)

What both these models, identified by Pratt (1998), have in common is a focus on the individual rather than on the teacher, the institution, or state. They are both in a sense attempts at liberating learners from the restrictions of formal and institutional types of education.

The nurturing approach

A nurturing approach to teaching can best be understood in terms of the role of a parent. Pratt (1998) states:

We expect ‘successful’ parents to understand and empathize with their child; and that they will provide kind, compassionate, and loving guidance through content areas of utmost difficulty….The nurturing educator works with other issues…in different contexts and different age groups, but the underlying attributes and concerns remain the same. Learners’ efficacy and self-esteem issues become the ultimate criteria against which learning success is measured, rather than performance-related mastery of a content body.

There is a strong emphasis on the teacher focusing on the interests of the learner, on empathizing with how the learner approaches learning, of listening carefully to what the learner is saying and thinking when learning, and providing appropriate, supportive responses in the form of ‘consensual validation of experience‘. This theory is driven partly by the observation that people learn autonomously from a very early age, so the trick is to create an environment for the learner that encourages rather than inhibits their ‘natural’ tendency to learn, and directs it into appropriate learning tasks, decided by an analysis of the learner’s needs.

The social reform model

Pratt (1998, p. 173) states:

Teachers holding a social reform perspective are most interested in creating a better society and view their teaching as contributing to that end. Their perspective is unique in that it is based upon an explicitly stated ideal or set of principles linked to a vision of a better social order. Social reformers do not teach in one single way, nor do they hold distinctive views about knowledge in general…these factors all depend on the particular ideal that inspires their actions.’

This then in some ways is less a theory of teaching and more an epistemological position, that society needs change, and the social reformer knows how to bring about this change.

History, and relevance for connectivism

These approaches to teaching again have a long history, with echoes of

  • Jean-Jacques Rousseau (1762) (‘education should be carried out, so far as possible, in harmony with the development of the child’s natural capacities by a process of apparently autonomous discovery‘ (Stanford Encyclopedia of Philosophy)
  • Malcolm Knowles (1984) ‘As a person matures his self concept moves from one of being a dependent personality toward one of being a self-directed human being.’
  • Paulo Freire (2004) (‘education makes sense because women and men learn that through learning they can make and remake themselves, because women and men are able to take responsibility for themselves as beings capable of knowing—of knowing that they know and knowing that they don’t.’)
  • Ivan Illich (1971) in his criticism of the institutionalization of education (‘The current search for new educational funnels must be reversed into the search for their institutional inverse: educational webs which heighten the opportunity for each one to transform each moment of his living into one of learning, sharing, and caring.’

The reason why the nurturing and social reform approaches to teaching are important is because they reflect many of the assumptions or beliefs around connectivism. Indeed, as early as 1971, Illich made this remarkable statement for the use of advanced technology to support “learning webs.”

The operation of a peer-matching network would be simple. The user would identify himself by name and address and describe the activity for which he sought a peer. A computer would send him back the names and addresses of all those who had inserted the same description. It is amazing that such a simple utility has never been used on a broad scale for publicly valued activity.’

Well, those conditions certainly exist today. Learners do not necessarily need to go through institutional gateways to access information or knowledge, which is increasing available and accessible through the Internet. MOOCs help to identify those common interests and connectivist MOOCs in particular aim to provide the networks of common interests and the environment for self-directed learning. The digital age provides the technology infrastructure and support needed for this kind of learning.

The roles of learners and teachers

Of all the models of teaching these two are the most learner centred. They are based on an overwhelmingly optimistic view of human nature, that people will seek out and learn what they need, and will find the necessary support from caring, dedicated educators and from others with similar interests and concerns, and that individuals have the capacity and ability to identify and follow through with their own educational needs. It is also a more radical view of education, because it seeks to escape the political and controlling aspects of state or private education.

Within each of these two models, there are differences of view about the centrality of teachers for successful learning. For Pratt, the teacher plays a central role in nurturing learning; for others such as Illich or Freire, professionally trained teachers are more likely to be the servant of the state than of the individual learner. Volunteer mentors or social groups organised around certain ideals or social goals provide alternative forms of support for learners.

Strengths and weaknesses of these two approaches

There are, as always, a number of drawbacks to these two approaches to teaching:

  • The teacher in a nurturing approach needs to adopt a highly dedicated and unselfish approach, putting the demands and needs of the learner first. This often means for teachers who are experts in their subject holding back the transmission and sharing of their knowledge until the learner is ‘ready’, thus denying to many subject experts their own identity and needs to a large extent;
  • Pratt argues that ‘although content is apparently neglected, children taught by nurturing educators do continue to master it at much the same rate as children taught by curriculum-driven teaching methodologies‘, but no empirical evidence is offered to support this statement, although it does derive in Pratt’s case from strong personal experience of teaching in this way;
  • like all the other teaching approaches the nurturing method is driven by a very strong belief system, which will not necessarily be shared by other educators (or parents or even students, for that matter);
  • a nurturing approach is probably the most labour-intensive of all the teaching models, requiring a deep understanding on the part of the teacher of each learner and that learner’s needs; every individual learner is different and needs to be treated differently, and teachers need to spend a great deal of time identifying learners’ needs , their readiness to learn, and building or creating supportive environments or contexts for that learning;
  • there is likely to be a conflict between what the learner identifies as their personal learning needs, and the demands of society in a digital age. Dedicated teachers may be able to help a learner negotiate that divide, but in situations where learners are left without professional guidance learners may end up just talking to other individuals with similar views that do not progress their learning (remembering that academic teaching is a rhetorical exercise, changing the way learners view the world.)
  • social reform depends to a large extent on learners and teachers embracing similar belief systems, and can easily descend into dogmatism without challenges from outside the ‘in-community’ established by self-referential groups.

Nevertheless, there are aspects of both models that have significance for a digital age:

  • both nurturing and social reform approaches seems to work well for many adults in particular, and the nurturing approach also works well for younger children.
  • nurturing is an approach that has been adopted as much in advanced corporate training in companies such as Google as in informal adult education.
  • connectivist MOOCs strongly reflect both the nurturing approach and the ability to create webs of connections that enables the development of self-efficacy and attempts at social reform
  • both methods seem to work well when learners are already fairly well educated and already have good prior knowledge and conceptual development.
  • such approaches that focus on the needs of individuals rather than institutions or state bureaucracies can liberate thinking and learning and thus make the difference between ‘good’ and ‘excellent’ in creative thinking, problem-solving, and application of knowledge in complex and variable contexts.

Over to you

Once again, your feedback on this analysis of the two teaching models will be invaluable. In particular:

  • Do you have experience of teaching in one or both of these ways? If so, do you agree with the analysis of the strengths and weaknesses of each component?
  • Do you think that connectivism is a modern reflection of either of these models of teaching - or is connectivism a distinct and unique method of teaching in itself? If so, what distinguishes it as a teaching method from all the other methods I have covered?

It’s always great to hear from readers.

Up next

Although I posted some key takeaways at the end of Chapter 4, I will be doing an extended reflection on all the models described with a particular focus on their suitability for developing the knowledge and skills needed in a digital age.

References

Freire, P. (2004). Pedagogy of Indignation. Boulder: CO, Paradigm

Illich, I. (1971) Deschooling Society, (accessed 6 August, 2014)

Knowles, M. (1984) Andragogy in Action. Applying modern principles of adult education, San Francisco: Jossey Bass.

Pratt, D. (1998) Five Perspectives on Teaching in Adult and Higher Education Malabar FL: Krieger Publishing Company

Rousseau, J.-J. (1762) Émile, ou de l’Éducation  (Trans. Allan Bloom. New York: Basic Books, 1979)

Models for teaching by doing (labs, apprenticeship, etc.)

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 apprentices 2

Context

I am gradually working my way through Chapter 4 on different models of teaching for my open textbook, ‘Teaching in a Digital Age.’

First drafts of the following Chapters are now already published and can be accessed here:

Chapter 1: Fundamental Change in Education

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

Chapter 3: Theories of Learning for a Digital Age

Chapter 4: Methods of Teaching

The purpose of Chapter 4 is:

  • to describe several different approaches to the design of teaching
  • to discuss the general strengths and weaknesses of each approach
  • to identify the extent to which each approach meets the needs of learners in a digital age
  • to provide a framework for considering the choice and use of new technologies for teaching in later chapters

I have already done blog posts on transmissive lectures (Why lectures are dead) and another on conversational methods of teaching (seminars, etc.).

I am now offering you my first draft on ‘Models of teaching by doing.’

Models for teaching by doing

There are a number of different models that focus on helping learners to learn by doing things, such as co-op or workplace programs, field trips or internships,usually under the supervision of more experienced mentors or instructors. Here I will touch briefly on only two, the use of laboratory classes/workshops/studios, and apprenticeship programs.

Lab or workshop teaching

Concordia wood shop 2

Today, we take almost for granted that laboratory classes are an essential part of teaching science and engineering. Workshops and studios are considered critical for many forms of trades training or the development of creative arts. Labs, workshops and studios serve a number of important functions or goals, which include:

  • to give students hands-on experience in choosing and using common scientific, engineering or trades equipment appropriately,
  • to develop motor skills in using scientific, engineering or industrial tools or creative media
  • to give students an understanding of the advantages and limitations of laboratory experiments
  • to enable students to see science, engineering or trade work ‘in action’
  • to enable students to test hypotheses or to see how well concepts, theories, procedures actually work when tested under laboratory conditions
  • to teach students how to design and/or conduct experiments
  • to enable students to design and create objects or equipment in different physical media.

An important pedagogical value of laboratory classes is that they enable students to move from the concrete (observing phenomena) to the abstract (understanding the principles or theories that are derived from the observation of phenomena). Another is that the laboratory introduces students to a critical cultural aspect of science and engineering, that all ideas need to be tested in a rigorous and particular manner for them to be considered ‘true’.

One major criticism of traditional educational labs or workshops is that they are limited in the kinds of equipment and experiences that scientists, engineers and trades people need today. As scientific, engineering and trades equipment becomes more sophisticated and expensive, it becomes increasingly difficult to provide students in schools especially but increasingly now in colleges and universities direct access to such equipment. Furthermore traditional teaching labs or workshops are capital and labour intensive and hence do not scale easily, a critical disadvantage given rapidly expanding educational demand.

Because laboratory work is such an accepted part of science teaching, it is worth remembering that teaching science through laboratory work is in historical terms a fairly recent development. In the 1860s neither Oxford nor Cambridge University were willing to teach empirical science. Thomas Huxley therefore developed a program at the Royal School of Mines (a constituent college of what is now Imperial College, of the University of London) to teach school-teachers how to teach science, including how to design laboratories for teaching experimental science to school children, a method that is still the most commonly used today, both in schools and universities.

At the same time, scientific and engineering progress since the nineteenth century has resulted in other forms of scientific testing and validation that take place outside at least the kind of ‘wet labs’ so common in schools and universities. Examples are nuclear accelerators, nanotechnology, quantum mechanics and space exploration. It is also important to be clear about the objectives of lab, workshop and studio work. There may now be other, more practical,more economic, or more powerful ways of achieving these objectives through the use of new technology, such as remote labs, simulations, and experiential learning. These will be examined in more detail in later chapters.

Apprenticeship

© BBC, 2014

© BBC, 2014

It is useful to remember that apprenticeship is not an invisible phenomenon. It has key elements: a particular way of viewing learning, specific roles and strategies for teachers and learners, and clear stages of development, whether for traditional or cognitive apprenticeship. But mostly it’s important to remember that in this perspective, one cannot learn from afar. Instead, one learns amid the engagement of participating in the authentic, dynamic and unique swirl of genuine practice.

Pratt and Johnson, 1998

Apprenticeship is a particular way of enabling students to learn by doing. It is often associated with vocational training but it should be pointed out that apprenticeship is the most common method used to train post-secondary education instructors in teaching (at least implicitly), so there is a wide range of applications for an apprenticeship approach to teaching.

A key feature of apprenticeship is that it operates in ‘situations of practice that…are frequently ill-defined and problematic, and characterized by vagueness, uncertainty and disorder‘ (Schön, 1983). Learning in apprenticeship is not just about learning to do (active learning), but also requires an understanding of the contexts in which the learning will be applied. In addition there is a social and cultural element to the learning, understanding and embedding the accepted practices, customs and values of experts in the field.

Pratt and Johnson (1998) identify the characteristics of a master practitioner, whom they define as ‘a person who has acquired a thorough knowledge of and/or is especially skilled in a particular area of practice‘. Master practitioners:

  1. possess great amounts of knowledge in their area of expertise, and are able to apply that knowledge in difficult practice settings
  2. have well-organized, readily accessible schemas (cognitive maps) which facilitate the acquisition of new information
  3. have well-developed repertoires of strategies for acquiring new knowledge, integrating and organizing their schemas, and applying their knowledge and skills in a variety of contexts….
  4. …are motivated to learn as part of the process of developing their identities in their communities of practice. They are not motivated to learn simply to reach some external performance goal or reward
  5. frequently display tacit knowledge in the form of:
    • spontaneous action and judgements
    • being unaware of having learned to do these things
    • being unable or having difficulty in describing the knowing which their actions reveal

Pratt and Johnson further distinguish two different but related forms of apprenticeship: traditional and cognitive. A traditional apprenticeship experience, based on developing a motor or manual skill, involves learning a procedure and gradually developing mastery, during which the master and learner go through several stages:

  • observation of both the master and other learners performing the same procedure: this helps provide a conceptual model for the apprentice to follow and an ‘advanced organizer for their initial attempts at performing skills’
  • modelling: explicit demonstration by the master of what to do, followed by the learner copying/practising the task
  • scaffolding: the support and feedback provided to the learner by the master as the learner works on a task
  • coaching: an overall approach of the master in choosing appropriate tasks, evaluating work and diagnosing problems.

An intellectual or cognitive apprenticeship model is somewhat different because this form of learning is less easily observable than learning motor or manual skills. Pratt and Johnson argue that in this context, master and learner must say what they are thinking during applications of knowledge and skills, and must make explicit the context in which the knowledge is being developed, because context is so critical to the way knowledge is developed and applied. Pratt and Johnson suggest five stages for cognitive and intellectual modelling (Figure 5.1, p. 99):

  1. modelling by the master and development of a mental model/schema by the learner
  2. learner approximates replication of the model with master providing support and feedback (scaffolding/coaching)
  3. learner widens the range of application of the model, with less support from master
  4. self-directed learning within the specified limits acceptable to the profession
  5. generalizing: learner and master discuss how well the model might work or would have to be adapted in a range of other possible contexts.

Pratt and Johnson provide a concrete example of how this apprenticeship model might work for a novice university professor (pp. 100-101).

The apprenticeship model of teaching can work in both face-to-face and online contexts, but if there is an online component, it usually works best in a hybrid format. For instance, Vancouver Community College in Canada offers a 13 week semester course for car body repair apprentices that delivers 10 weeks of the program online for unqualified workers across the province who are already working in the industry. VCC uses online learning for the theoretical part of the program, plus a large number of simply produced video clips of practices and procedures in car body repairs. Because all the students are apprentices already working under supervision of a master journeyman, they can practice some of the video procedures in the workplace under supervision. The last three weeks of the program requires students to come to the college for specific hands-on training for the last three weeks of the course. They are tested, and those that have already acquired the skills are sent back to work, so the instructor can focus on those that need the skills most. The partnership with industry that enables the college to work with ‘master’ tradespeople in the workplace is critical for this semi-distance program, and is particularly useful where there are severe skills shortages, helping to bring unskilled workers up to the level of full craftspeople.

The main advantages of an apprenticeship model of teaching can be summarised as follows:

  • teaching and learning are deeply embedded within complex and highly variable contexts, allowing rapid adaptation to real-world conditions
  • it makes efficient use of the time of experts, who can integrate teaching within their regular work routine
  • it provides learners with clear models or goals to aspire to
  • it acculturates learners to the values and norms of the trade or profession

On the other hand, there are some serious limitations with an apprenticeship approach, particularly in non-traditional apprenticeship:

  • much of a master’s knowledge is tacit, partly because their expertise is built slowly through a very wide range of activities,
  • experts often have difficulty in expressing consciously or verbally the schema and ‘deep’ knowledge that they have built up and taken almost for granted, leaving the learner often to have to guess or approximate what is required of them to become experts themselves,
  • experts often rely solely on modelling with the hope that learners will pick up the knowledge and skills from just watching the expert in action, and don’t follow through on the other stages that make an apprenticeship model more likely to succeed.
  • there is clearly a limited number of learners that one expert can manage, given that the experts themselves are fully engaged in applying their expertise in often demanding work conditions which may leave little time for paying attention to the needs of novice learners in the trade or profession
  • vocational apprenticeship programs have a very high attrition rate: for instance, in British Columbia, more than 60 per cent of those that enter a formal campus-based vocational apprenticeship program withdraw before successful completion of the program. As a result, there are large numbers of experienced tradespeople in the workforce without full accreditation, limiting their career development and slowing down economic development where there are shortages of fully qualified skilled workers
  • in trades or occupations undergoing rapid change in the workplace, the apprenticeship model can slow adaptation or change in working methods, because of the prevalence of traditional values and norms being passed down by the ‘master’ that may no longer be as relevant in the new conditions facing workers. This limitation of the apprenticeship model can be clearly seen in the post-secondary education sector, where traditional values and norms around teaching are increasingly in conflict with external forces such as new technology and the massification of higher education.

Nevertheless, the apprenticeship model, when applied thoroughly and systematically, is a very useful model for teaching in highly complex, real-world contexts.

Over to you

Your feedback on this will be invaluable. In particular:

  • do you agree that the time is now ripe to look at other ways of achieving the goals of science and engineering lab classes? Can you give examples of where this is already happening, besides remote labs?
  • do you agree that the main method of teaching college and university professors how to teach is a cognitive apprenticeship model? If so, how well does this work? Would another approach be better? If so, what’s preventing this?
  • for those of you with experience in traditional apprenticeship programs: how well is this working in a digital age? What could be done to improve it?

References

Pratt, D. and Johnson, J. (1998) The Apprenticeship Perspective: Modelling Ways of Being in Pratt, D. (ed.) Five Perspectives on Teaching in Adult and Higher Education Malabar FL: Krieger Publishing Company

Schön, D. (1983) The Reflective Practitioner: How Professionals Think in Action New York: Basic Books

Up next

The final section of this chapter (at last!) looks at a very interesting and important approach for teaching in a digital age, of which connectivism is just one example: a nurturing approach to teaching.

 

Dialogue and discussion: critical for 21st century skills development

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Tutorial 2

Introduction

First of all, thanks to the numerous people who commented on  my earlier posts on Why Lectures are Dead, and on Learning Theories and Online Learning. These were previews of chapters for my open textbook, Teaching in a Digital Age.

This feedback was particularly helpful, because several people commented that there are lots of different kinds of lectures. I fully accept that criticism, and although I did define ‘lecture’ quite narrowly in the actual post (some of the comments picked up quotes from the article in the form of tweets or LinkedIn comments that did not include the narrow definition I used.) That definition was really about lectures that were focused primarily or entirely on the transmission of knowledge. I have therefore changed the heading of that section in the book to ‘Transmissive Lectures.’

In the next section, I discuss another important method of teaching based on discussion and argument that reflects a more constructivist approach to teaching and learning. Here is the first draft.

Interactive lectures, seminars, tutorials and MOOCs

In this section, I will examine a number of different ways in which teaching can help develop conceptual knowledge. There is a particular emphasis on conceptual learning at a post-secondary level, but in recent years conceptual learning has become an increasing focus in the school or k-12 systems in many jurisdictions.

The theoretical and research basis for social learning

In the previous section, I wrote that research on lectures showed that:

‘in order to understand, analyze, apply, and commit information to long-term memory, the learner must actively engage with the material. In order for a lecture to be effective, it must include activities that compel the student to mentally manipulate the information.’

This is a cognitive approach to learning, but constructivists go beyond interaction between student and learning materials. They believe, as I wrote earlier, 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. 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…knowledge is mainly acquired through social processes or institutions that are socially constructed.’

Researchers have identified a distinction, often intuitively recognised by instructors, between meaningful and rote learning (Asubel et al, 1978). Meaningful learning involves the learner going beyond memorization or surface comprehension of facts, ideas or principles, to a deeper understanding of what those facts, ideas or principles mean to them. Marton and Saljö, who have conducted a number of studies that examined how university students actually go about their learning, make the distinction between deep and surface approaches to learning (see, for instance, Marton and Saljö, 1997).

Students who adopt a deep approach to learning tend to have a prior intrinsic interest in the subject. Their motivation is to learn because they want to know more about a topic. Students with a surface approach to learning are more instrumental. Their interest is primarily driven by the need to get a pass grade or qualification.

Subsequent research (e.g. Entwistle and Peterson, 2004) showed that as well as students’ initial motivation for study, a variety of other factors also influence students’ approaches to learning. In particular, certain learning environments, such as an emphasis in the teaching on information transmission, tests that rely mainly on memory, and a lack of interaction and discussion, encourage surface approaches to learning, while a focus on analytical or critical thinking or problem-solving, in-class discussion, and assessment based on analysis, synthesis, comparison and evaluation tends to drive students more to a deeper approach to learning. It should also be noted that approaches to learning are not always consistent or stable, even for the same student in the same course. Nevertheless, the teaching environment is critical in establishing expectations and methods that are more likely to engage students and hence lead to more conceptual and deeper learning

In addition, others, such as Laurillard (2001) and Harasim (2010), have emphasised that academic knowledge requires students to move constantly from the concrete to the abstract and back again, and to build or construct knowledge based on academic criteria such as logic, evidence and argument. This in turn, it is argued, requires a strong teacher presence within a dialectical environment, in which argument and discussion within the rules and criteria of the subject discipline are encouraged and developed by the instructor or teacher. Laurillard calls this a rhetorical exercise, an attempt to get learners to think about the world differently.

Lastly, connectivist approaches to learning place heavy emphasis on networking learners, with all participants learning through interaction and discussion between each other, driven both by their individual interests and the extent to which these interests connect to the interests of other participants. The very large numbers participating means that there is a high probability of converging interests for all participants, although those interests may vary considerably over the whole group.

The combination of theory and research here suggests the need for frequent interaction between students, and between teacher and students, for the kinds of learning needed in a digital age. This interaction usually takes the form of semi-structured discussion. I will now examine the very wide range of ways in which this kind of learning is facilitated by educators.

Interactive lectures

Definition: An interactive lecture is a lecture where at least 25% of the time is taken up with questions and discussion from students and responses from the lecturer to points raised by students

Many lecturers deliberately design a large lecture experience to encourage interaction with and between students, even though the focus of the lecture is still mainly on information transmission, such as facts, concepts, procedures and ideas. The most common format is to allow at least 15 to 20 minutes at the end of the presentation for questions and discussion, where the instructor may well take the lead in putting questions to students and requiring particular students to provide a response, to get discussion going. However, the research suggests that a better way to ensure comprehension and the development of conceptual thinking is to break the session into small chunks of perhaps 10 minutes presentation, followed by five to ten minutes of questions and discussion.

© Center for Teaching and Learning, University of Washington, 2014

© Center for Teaching and Learning, University of Washington, 2014

More recently, instructors have started to record their lectures through lecture capture then use class time for discussion of the contents of the lecture. This model is called the ‘flipped’ classroom. Again, this is still a mainly transmissive way of teaching requiring students to respond to instructor-led presentation, and there are sometimes problems in getting students to view the lecture in advance of the class time. Clickers and Twitter back-chat channels are other ways in which technology has been used to increase student interaction.

Even interactive lectures can be criticised as being mainly behaviouristic, with a defined body of knowledge to be learned and assimilated by the student. Often discussion is cut short because ‘there is too much content to get through’ to cover the curriculum, and consequently students adopt surface rather than deep approaches to learning. Problems often appear later, when for instance students who need mathematical concepts and procedures in later engineering courses struggle because they have forgotten or been unable to conceptualise fully concepts, formulae and methods taught in earlier courses.

The main reason though why the interactive lecture is still so common is because it is one way to build some form of interaction into very large classes with 200 students or more. It should be noted though that even in interactive classes, it is unlikely that over the whole length of a thirteen week semester, more than ten per cent of the students will have the chance to ask a question or make a comment if the class size is large. (Research again has indicated that it tends to be the same ten or so students who always ask unprompted questions.)

Seminars and tutorials

Definitions:

seminar is a group meeting (either face-to-face or online) where a number of students participate at least as actively as the teacher, although the teacher may be responsible for the design of the group experience, such as choosing topics and assigning tasks to individual students.

tutorial is either a one-on-one session between a teacher and a student, or a very small group (five or less) of students and an instructor, where the learners are at least as active in discussion and presentation of ideas as the teacher.

Socrates and his student: Johann Friedrich Greuter, 1590: (San Francisco, Achenbach Foundation for Graphic Arts 

Socrates and his students: Painter: Johann Friedrich Greuter, 1590: (San Francisco, Achenbach Foundation for Graphic Arts)

Seminars can range from six or more students, up to 30 students in the same group. Because the general perception is that seminars work best when numbers are relatively small, they tend to be found more at graduate level or the last year of undergraduate programs, or anywhere where class size is around 25-30.

Seminars and tutorials again have a very long history, going back at least to the time of Socrates. Plato, the philosopher, was a student or follower of Socrates, although Socrates denied he was a teacher, rebelling against the idea common at that time in ancient Greece that ‘a teacher was a vessel that poured its contents into the cup of the student’. Instead, according to Plato, Socrates used dialogue and questioning ‘to help others recognize on their own what is real, true, and good.’ (Stanford Encyclopedia of Philosophy.) 

The format of seminars can vary a great deal. One common format, especially at graduate level, although similar practices can be found at the school/k-12 level, is for the teacher to set advance work for a selected number of students, and then have the selected students present their work to the whole group, for discussion, criticism and suggestions for improvement. Although there may be time for only two or three student presentations in each seminar, over a whole semester every student gets their turn. Another format is to ask all the students in a group to do some specified advanced reading or study, then for the teacher to introduce questions for general discussion within the seminar that requires students to draw on their earlier work.

Tutorials are a particular kind of seminar that are identified with Ivy League universities, and in particular Oxford or Cambridge. There may be as few as two students and a professor in a tutorial and the meeting often follows closely the Socratic method of the student presenting his or her findings and the professor rigorously questioning every assumption made by the student – and also drawing in the other student to the discussion.

Both these forms of dialogical learning can be found not only in classroom contexts, but also online. Online discussion forums go back to the 1970s, but really took off after the introduction of the WorldWide Web and high band telecommunications enabled the development of learning management systems, most of which now include an area for online discussions. These online discussion forums have some differences though with classroom seminars:

  • first,they are text based, not oral
  • second, they are asynchronous: participants can log in at any time, and from anywhere with an Internet connection, but this can cause some difficulties in following or participating in a particular argument or discussion
  • thus, third, many discussion forums allow for ‘threaded’ connections, enabling a response to be attached to the particular comment which prompted the response, rather than just displayed in chronological order. This allows for dynamic sub-topics to be developed, with sometimes more than ten responses within a single thread of discussion. This enables participants to follow multiple discussion topics over a period of time.

However, in general, the pedagogical similarities between online and face-to-face discussions are much greater than the differences. For academic and conceptual development, discussions need to be well organized by the teacher, and the teacher needs to provide the necessary support to enable the development of ideas and the construction of new knowledge for the students. There are several ways this can be done:

  • set clear goals for the discussions that are understood by the students, such as: ‘to explore gender and class issues in selected novels’ or ‘to compare and evaluate alternative methods of coding.’
  • set clear guidelines about expectations of students, such as ‘you should log in at least once a week to each discussion topic and make at least one substantive contribution to each topic each week.’
  • set clear, written codes of conduct for participating in discussions, and ensure that they are enforced
  • set topics for discussion that complement and expand issues in the study materials, and are relevant to answering assessment questions
  • provide the appropriate scaffolding or support, such as comments that help students develop their thinking around the topics, refer them back to study materials if necessary, or explain issues when students seem to be confused or misinformed
  • monitor the discussions to prevent them getting off topic or too personal
  • provide encouragement for those that are making real contributions to the discussion,  head off those that are trying to hog or dominate the discussions, and track those not participating, and help them to participate.

MOOCs

Massive, open, online courses usually include opportunities for discussion among students. The importance of discussion and the methods for organizing it, vary considerably within MOOCs. In instructionist MOOCs, based on video-recorded lectures, the discussion is usually ancillary, and is added to enable mainly clarification of concepts covered in the lectures. Because of the number of participants in instructionist MOOCs, it is unusual for the instructor responsible for the content of the MOOC to become heavily engaged in the discussions, although frequently teaching assistants may be asked to monitor the overall discussion and direct significant issues back to the main instructor for a general response.

In connectivist MOOCs, the interaction between participants is the core of the MOOC, and various methods and technologies are used to connect participants together. Thus hash tags may be used to enable participants to share in tweets from other participants, individuals may create their own blogs for their comments and reflections on the topics under discussion, with the blog urls being collected together and shared with other participants, or there may, less frequently, be a common discussion forum or area where all comments are posted. Even connectivist MOOCs though tend to have some form of loose central structure, with perhaps a variety of ‘experts’ being invited to start off conversations with some form of transmissive communication, such as a webcast or a reading, then the experts continue to participate in the following discussions.

These of course are two extremes, and as MOOCs develop, we are seeing some convergence, but for nearly all MOOCs, discussion between participants is seen as crucial for facilitating and developing learning. Nevertheless, there are some strong criticisms of the effectiveness of the discussion element of MOOCs for developing the high-level conceptual development required for academic learning. I have suggested that to develop deep, conceptual learning, there is a need in most cases for intervention by a subject expert, to clarify misunderstandings or misconceptions, to provide accurate feedback,  to ensure that the criteria for academic learning, such as use of evidence, clarity of argument, etc., are being met, and to ensure the necessary input and guidance to seek deeper understanding. Indeed, there has been a great deal of research into credit-based online courses that show instructor presence is a key factor in ensuring high completion rates for online courses. Firmin et al. (2014) have shown that when there is some form of instructor ‘encouragement and support of student effort and engagement’, results improve for all participants in MOOCs.

Furthermore, the more massive the course, the more likely participants are to feel ‘overload, anxiety and a sense of loss’, if there is not some instructor intervention or structure imposed (Knox, 2014). Without a structured role for subject experts, participants are faced with a wide variety of quality in terms of comments and feedback from other participants. There is again a great deal of research on the conditions necessary for the successful conduct of collaborative and co-operative group learning (see for instance, Dillenbourg, 1999, Lave and Wenger, 1991), and these findings certainly have not been applied to the management of MOOC discussions to date. (We will return to this topic in a later chapter.)

The counter argument is that MOOCs develop a new form of learning based on networking and collaboration that is essentially different from academic learning, and MOOCs are thus more appropriate to the needs of learners in a digital age. Adult participants in particular, it is claimed, have the ability to self-manage the development of high level conceptual learning.  MOOCs are ‘demand’ driven, meeting the interests of individual students who seek out others with similar interests and the necessary expertise to support them in their learning, and for many this interest may well not include the need for deep, conceptual learning but more likely the appropriate applications of such learning in specific contexts.

MOOCs do appear to work best for those who already have a high level of education and therefore bring many of the conceptual skills developed in formal education with them when they join a MOOC, and therefore contribute to helping those who come without such skills. Over time, as more experience is gained, MOOCs are likely to incorporate and adapt  for large numbers some of the findings from research on smaller group work. Indeed, MOOCs are likely to develop new ways to manage discussion effectively in very large groups. In the meantime, though, there is much work still to be done if MOOCs are to provide the support and structure needed to ensure deep, conceptual learning where this does not already exist in students.

Summary

For many faculty, the ideal teaching environment is Socrates sitting under the linden tree, with a small group of dedicated and interested students. Unfortunately, the reality of mass higher education makes this impossible for all but the most elite and expensive institutions. However, seminars for 25-30 students are not unrealistic, even in public undergraduate education. More importantly, seminar models enable the kind of teaching and learning that are most likely to facilitate the types of skills needed from our students in a digital age. Seminars are flexible enough to be offered in class or online, depending on the needs of the students. They are probably best used when students have done individual work before the seminar. Of upmost importance, though, is the ability of teachers to teach successfully in this manner, which requires different skills from transmissive lecturing.

We saw in Chapter 1 that although expansion of student numbers in higher education is part of the problem, it’s not the whole problem. Other factors, such as senior professors teaching less, and focusing mainly on graduate students, results in larger classes at undergraduate level, using transmissive lecturing. These classes are often taught by teaching assistants who have little more knowledge than the students they are teaching. And if more senior or experienced instructors switched from transmissive lectures, and instead required students to find and analyse content for themselves, this would free up more time for the instructors to spend on seminar-type teaching. So it as much an organizational issue, a matter of choice and priorities, as an economic issue. The more we can move towards a seminar approach to teaching and learning and away from large, transmissive lectures, the better, if we are to develop students with the skills needed in a digital age.

Over to you

Your feedback on this will be invaluable. In particular:

  • Do you agree that the kind of teaching conducted in seminar-type contexts is more appropriate for today’s learners than transmissive lectures? If so, why (or conversely, why not?)
  • is the description of the way dialogue and discussion operate to enhance learning accurate and if not, what should be changed?
  • are there important ways of teaching built around dialogue or discussion that have been missed and should be included?
  • do you agree with my comments about the current limitations of MOOCs for engendering the kind of discussions that lead to deep, conceptual learning? What could or do MOOCs do to help the development of such knowledge?
  • how realistic is it to move away from large, transmissive lecture classes to smaller, seminar-type teaching? What is preventing this from happening more often in our educational systems? Is it just a money issue, or are there other factors at work?

References

Asubel, D. et al. (1978) Educational Psychology: A Cognitive View New York: Holt, Reinhart and Winston

Dillenbourg, P. (ed.) (1999) Collaborative-learning: Cognitive and Computational Approaches. Oxford: Elsevier

Entwistle, N. and Peterson, E. (2004) Conceptions of Learning and Knowledge in Higher Education: Relationships with Study Behaviour and Influences of Learning Environments International Journal of Educational Research, Vol. 41. pp. 407-428

Firmin, R. et al. (2014) Case study: using MOOCs for conventional college coursework Distance Education, Vol. 35, No. 2

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

Knox, J. (2014) Digital culture clash: ‘massive’ education in the e-Learning and Digital Cultures Distance Education, Vol. 35, No. 2

Laurillard, D. (2001) Rethinking University Teaching: A Conversational Framework for the Effective Use of Learning Technologies New York/London: Routledge

Lave, J. and Wenger, E. (1991). Situated Learning: Legitimate Peripheral Participation. Cambridge: Cambridge University Press

Marton, F. and Saljö, R. (1997) Approaches to learning, in Marton, F., Hounsell, D. and Entwistle, N. (eds.) The experience of learning: Edinburgh: Scottish Academic Press (out of press, but available online)

Next up

Experiential learning (learning by doing): labs, field trips, apprenticeships and workplace/co-op training

Main lessons for developing skills for a digital age.

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

Why lectures are dead (or soon will be)

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Artist: Laurentius de Voltolina; Liber ethicorum des Henricus de Alemannia; Kupferstichkabinett SMPK, Berlin/Staatliche Museen Preussiischer Kulturbesitz, Min. 1233

Artist: Laurentius de Voltolina;
Liber ethicorum des Henricus de Alemannia; Kupferstichkabinett SMPK, Berlin/Staatliche Museen Preussiischer Kulturbesitz, Min. 1233

As part of my open textbook on Teaching in a Digital Age, I am working my way through theories of learning and methods of teaching. I will post shortly my initial draft on theories of learning and their relevance for a digital age. In this post I want to discuss the lecture and its relevance for a digital age. Comments as always are more than welcome.

Definition:

‘[Lectures] are more or less continuous expositions by a speaker who wants the audience to learn something.’

Bligh, 2000

History

Lectures go back as far as ancient Greece and Roman times, and certainly from at least the start of the European university, in the 13th century. The term ‘lecture’ comes from the Latin to read. This was because in the 13th century, most books were extremely rare. They were painstakingly handcrafted and illustrated by monks, often from fragments or collections of earlier and exceedingly rare and valuable scrolls remaining from more than 1,000 years earlier from ancient Greek or Roman times, or were translated from Arabic sources, as much documentation was destroyed in Europe during the Dark Ages following the fall of the Roman empire. As a result, a university would often have only one copy of a book, and it may have been the only copy available in the world. The library and its collection therefore became critical to the reputation of a university, and professors had to borrow the only text from the library and literally read from it to the students, who dutifully wrote down their own version of the lecture.

The illustration at the head of this post from a thirteenth-century manuscript shows Henry of Germany delivering a lecture to university students in Bologna, Italy, in 1233. What is striking is how similar the whole context is to lectures today, with students taking notes, some talking at the back, and one clearly asleep. Certainly, if Rip Van Winkle awoke in a modern lecture theatre from his 800 years of sleeping, he would know exactly where he was and what was happening.

Lectures themselves belong to an even longer oral tradition of learning, where knowledge is passed on by word of mouth from one generation to the next. In such contexts, accuracy and authority (or power in controlling access to knowledge) are critical for ‘accepted’ knowledge to be successfully transmitted. Thus accurate memory, repetition and a reference to authoritative sources become exceedingly important in terms of validating the information transmitted. The great sagas of the ancient Greeks and much later, of the Vikings, and even today,the oral myths and legends of many indigenous communities, are examples of the power of the oral transmission of knowledge.

Nevertheless, the lecture format has been questioned for many years. Samuel Johnson (1709-1784) long ago produced his own straightforward critique of lectures:

People have nowadays…got a strange opinion that everything should be taught by lectures. Now, I cannot see that lectures can do as much good as reading the books from which the lectures are taken…Lectures were once useful, but now, when all can read, and books are so numerous, lectures are unnecessary.’

What is remarkable is that even after the invention of the printing press, radio, television, and the Internet, the lecture, characterised by the authoritative instructor talking to a group of students, still remains the dominant methodology for teaching in many institutions, even in a digital age, where information is available at a click of a button.

It could be argued that anything that has lasted this long must have something going for it. On the other hand, we need to question whether the lecture is still the most appropriate means of teaching, given all the changes that have taken place in recent years, and in particular given the kinds of knowledge and skills needed in a digital age.

What does research tell us about the effectiveness of lectures?

Whatever you may think of Samuel Johnson’s opinion, there has indeed been a great deal of research into the effectiveness of lectures, going back to the 1960s, and continued through until today. The most authoritative analysis of the research on the effectiveness of lectures remains Bligh’s (2000). He summarized a wide range of meta-analyses and studies of the effectiveness of lectures compared with other teaching methods and found consistent results:

  1. The lecture is as effective as other methods for transmitting information (the corollary of course is that other methods – such as video, reading, independent study - are just as effective as lecturing for transmitting information)
  2. Most lectures are not as effective as discussion for promoting thought
  3. Lectures are generally ineffective for changing attitudes or values or for inspiring interest in a subject
  4. Lectures are relatively ineffective for teaching behavioural skills.

It should be noted that are are also many studies that suggest that it makes little difference to the learning effectiveness of a lecture if it is live (with the lecturer and the audience together at the same place and time), if it is transmitted in real time across distance (such as via a webcast or video-conference) or is viewed once on a recording as a continuous event. Thus merely by transmitting a MOOC in the form of a video lecture makes it no more or less effective in terms of an individual’s learning than if it was delivered in a classroom (although of course the MOOC will reach a lot more learners). Thus the medium of transmission makes no difference to an individual’s learning if the form of the lecture remains the same.

However, my research colleagues and I at the U.K. Open University, as early as 1984, established that making a lecture available in a recorded format (either on video or audio) increased the learning effectiveness, because it increased students’ time on task, by enabling them to review and repeat the material. We also found that recorded video or audio was even more effective than a recorded lecture if the program was re-designed to break the transmission of information into small chunks, and if the stop-start facility of recordings was used to build in student activities and feedback following each chunk of information. Proponents of Coursera-style MOOCs are just beginning to rediscover this thirty years later.

Bligh also examined research on student attention, on memorizing, and on motivation, and concluded (p.56):

We see evidence… once again to suppose that lectures should not be longer than twenty to thirty minutes – at least without techniques to vary stimulation.’

These research studies have shown that in order to understand, analyze, apply, and commit information to long-term memory, the learner must actively engage with the material. In order for a lecture to be effective, it must include activities that compel the student to mentally manipulate the information. Many lecturers of course do this, by stopping and asking for comments or questions throughout the lecture – but many do not.

Again, although these findings have been available for a long time, and You Tube videos now last approximately eight minutes and TED talks 20 minutes at a maximum, teaching in many educational institutions is still organized around a standard 50 minute lecture session, with, if students are lucky, a few minutes at the end for questions or discussion. Indeed in some institutions it is not uncommon to find even longer lecture sessions.

There are two important conclusions from the research:

1. Even for the sole purpose for which lectures may be effective – the transmission of information – the 50 minute lecture needs to be well organized, with frequent opportunities for student questions and discussion. (Bligh provides excellent suggestions on how to do this in his book.)

2. For all other important learning activities, such as developing critical thinking, deep understanding, and application of knowledge – the kind of skills needed in a digital age – lectures are ineffective. Other forms of teaching and learning – such as opportunities for discussion and student activities – are necessary.

Does new technology make lectures more relevant?

Over the years, institutions have made massive investments in ‘technologising’ the lecture. Powerpoint presentations, multiple projectors and screens, clickers for recording student responses, even ‘back-chat’ channels on Twitter, enabling students to comment on a lecture – or more often, the lecturer – in real time (surely the worse form of torture), have all been tried. Students have been asked to bring tablets or lap-tops to class, and universities in particular have invested millions of dollars in state of the art lecture theatres.

Nevertheless, all this is just lipstick on a pig. The essence of a lecture remains the transmission of information, all of which is now readily and, in most cases, freely available in other media and in more learner-friendly formats.

I worked in a college where in one program all students had to bring laptops to class. At least in these classes, there were some activities to do related to the lecture that required the students to use the laptops during class time. However, in most classes this took less than 25 per cent of the lesson time. Most of the other time, students were talked at, and as a result used their laptops for other, mainly non-academic activities, especially playing online poker.

Faculty often complain about students use of technology such as mobile phones or tablets, for ‘non-relevant’ multitasking in class, but this misses the point. If most students have mobile phones or laptops, why are they still having physically to come to a lecture hall? Why can’t they get a podcast of the lecture? Second, if they are coming, why are the lecturers not requiring them to use their mobile phones, tablets, or laptops for study? Why not break them into small groups and get them to do some online research then come back with group answers to share with the rest of the class? If lectures are to be offered, the aim should be to make the lecture engaging in its own right, so the students are not distracted by their online activity. If lecturers can’t do this, perhaps they should give up lecturing and find more interactive ways of engaging students.

Is there then no role for lectures in a digital age?

I do believe that lectures have their uses. As an example, I have attended an inaugural lecture for a newly appointed research professor. In this lecture, he summarised all the research he and his team had done, resulting in treatments for several cancers and other diseases. This was a public lecture, so he had to satisfy not only other leading researchers in the area, but also a lay public with often no science background. He did this by using excellent visuals and analogies. The lecture was followed by a small wine and cheese reception for the audience.

The lecture worked for several reasons:

  • first of all, it was a celebratory occasion bring together family, colleagues and friends.
  • second, it was an opportunity to pull together nearly 20 years of research into a single, coherent narrative or story.
  • third, the lecture was well supported by an appropriate use of graphics and video.
  • lastly, he put a great deal of work into preparing this lecture and thinking about who would be in the audience – much more preparation than would be the case if this was just one of many lectures in a course.

More importantly, though, that lecture is now publicly available via You Tube for anyone to view.

McKeachie and Svinicki (2006, p. 58) believe that lecturing is best used for:

  • providing up-to-date material that can’t be found in one source
  • summarizing material found in a variety of sources.
  • adapting material to the interests of a particular group.
  • initially helping students discover key concepts, principles or ideas
  • modelling expert thinking.

The last point is important. Faculty often argue that the real value of a lecture is to model for students how the faculty member, as an expert, approaches a topic or problem. Thus the important point of the lecture is not the transmission of content (facts, principles, ideas), which the students could get from just reading, but an expert way of thinking about the topic. The trouble with this argument for lectures is three-fold:

  • students are rarely aware that this is the purpose of the lecture, and therefore focus on memorizing the content, rather than the ‘modelling’ of expert thinking
  • faculty themselves are not explicit about how they are doing the modelling (or fail to offer other ways in which modelling could be used, so students can compare and contrast)
  • students get no practice themselves in modelling this skill, even if they are aware of the modelling.

So, yes, there are a few occasions when lectures work very well. But they should not be the default model for regular teaching. There are much better ways to teach that will result in better learning over the length of a course or program, and that lectures, whether live, or on MOOCs, YouTube videos or TED talks, are a poor way to prepare learners for a digital age.

Why are lectures still the main form of educational delivery?

Given all of the above, some explanation needs to be offered for the persistence of the lecture into the 21st century. Here are my suggestions

  1. in fact, in many areas of education, the lecture has been replaced, particularly in many elementary or primary schools (although parents often are unhappy about this, because a lecture represents their understanding of what teaching is all about); online learning (usually avoiding recorded lectures) and open education is also increasing more rapidly than classroom based learning
  2. a false assumption that the lecture is economically efficient. It is true it is efficient in the use of an instructor’s time, in that increasing student numbers in a lecture is no more work for the instructor for each student added to a class. However, efficiency needs to take into account output. If the output is to transfer information both less effectively per individual learner and in terms of providing the knowledge and skills in demand, then large lecture classes are a false efficiency;
  3. architectural inertia: a huge investment has been made by institutions in facilities that support the lecture model. What is to happen to all that real estate if it is not used?
  4. the Carnegie unit of teaching, which is based on a notion of one hour per week of classroom time per credit over a 13 week period. It is easy then to divide a three credit course into 39 one hour lectures over which the curriculum for the course must be covered. It is on this basis that teaching load and resources are decided.
  5. faculty in post-secondary education have no other model for teaching. This is the model they are used to, and because appointment is based on training in research or work experience, and not on qualifications in teaching, they have no knowledge of how students learn or confidence or experience in other methods of teaching.
  6. many experts prefer the oral tradition of teaching and learning, because it enhances their status as an expert and source of knowledge: being allowed an hour of other people’s time to hear your ideas without major interruption is very satisfying on a personal level (at least for me).

Is there a future for lectures in a digital age?

That depends on how far into the future one wants to look. Given the inertia in the system, I suspect that lectures will still predominate for another ten years, but after that, in most institutions, courses based on three lectures a week over 13 weeks will have disappeared. There are several reasons for this.

  • the first is that all content can be easily digitalized and made available on demand at very low cost.
  • second, institutions will be making greater use of dynamic video (not talking heads) for demonstration, simulations, animations, etc. Thus most content modules will be multi-media.
  • third, open textbooks incorporating multi media components and student activities will provide the content, organization and interpretation that are the rationale for most lectures.
  • lastly, and most significantly, the priority for teaching will have changed from information transmission and organization to knowledge management, where students have the responsibility for finding, analyzing, evaluating, sharing and applying knowledge, under the direction of a skilled subject expert. Project-based learning, collaborative learning and situated or experiential learning will become much more widely prevalent. Also many instructors will prefer to use the time they would have spent on a series of  lectures in providing more direct, individual and group learner support, thus bringing them into closer contact with learners.

This does not mean that lectures will disappear altogether, but they will be special events, and probably multi-media, synchronously and asynchronously delivered. Special events might include a professor’s summary of his latest research, the introduction to a course, a point mid-way through a course for taking stock and dealing with common difficulties, or the wrap-up to a course. A lecture will provide a chance for an instructor to makes themselves known, to impart their interests and enthusiasm, and to motivate learners, but this will be just one, relatively small, but important component of a much broader learning experience for students.

 In the meantime, institutions should be looking at their building plans, and deciding if the money they are thinking of in terms of classrooms and lecture theatres may not be better spent on digitizing the curriculum and making it openly available.

References

Bates, A. (1985) Broadcasting in Education: An Evaluation. London: Constable

Bligh, D. (2000) What’s the Use of Lectures? San Francisco: Jossey-Bass

Boswell, James (1986), Hibbert, Christopher, ed., The Life of Samuel Johnson, New York: Penguin Classics, ISBN 0-14-043116-0.

McKeachie, W. and Svinicki, M. (2006) McKeachie’s Teaching Tips: Strategies, Research, and Theory for College and University Teachers, 13th Edition Independence KY: Cengage

Guest blog: MOOCs: Disruptor or Indicator of Something Deeper?

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Guest blogger: Nicole Christen

Guest blogger: Nicole Christen

Introduction

I don’t usually do guest blogs, and when I do it’s always because I know they will be of the highest quality – and I NEVER accept unrequested guest blogs from people I don’t know.

However, I was a participant in a study on MOOCs by Nicole Christen for a paper as part of her Master in Educational Technology program at the University of British Columbia. She kindly sent me a copy of her final paper. I was so struck by the quality of this paper and its significance that I immediately asked her if she would be willing to provide a summary in the form of a blog post. Here is the summary of her paper. I found no need to change it. I strongly recommend though that you read the paper in full, which is available here.

Nicole Christen

MOOCs: Disruptor or Indicator of Something Deeper?

Why have massive open online courses, known as MOOCs, established a stronghold in the educational marketplace? Are they responsible for disrupting the traditional system of higher education? And, how can post-secondary institutions survive the changes taking place?

In the summer of 2013, amidst the early hype surrounding MOOCs, I conducted a qualitative research project. My objective was to explore the motivations driving institutions to launch MOOCs and join MOOC consortiums. MOOCs have been labeled as a disruptive force to the traditional system of post-secondary education; however, my research argues otherwise. MOOCs, themselves, are not the source of disruption. Deeper forces are at work.

About My Research Project

In order to understand the reasons behind the rapid implementation of MOOCs by post-secondary institutions, I interviewed educational technology thought leaders from around the world whose areas of expertise included distance learning and open learning at the post-secondary level. During each 30 minute interview, I asked a series of questions designed to help me identify common underlying themes surrounding MOOCs and the overall concept of open learning. The themes extrapolated from my interview data provide a solid overview of fundamental shifts that have occurred as a result of the technological revolution and remain relevant regardless of any changes to MOOCs that have taken place since this research was conducted.

Forces Driving the MOOC Movement

Media hype that portrays MOOCs as an all-powerful disruptive force overlooks the underlying factors behind the adoption of MOOCs. In particular, the post-secondary marketplace is becoming increasingly driven by learner desires. Self-directed, distance education at the post-secondary level has existed for decades; however, the relative ease with which people around the world can now access the Internet, has created a tipping point. In many cases, learners are no longer as limited by geographical boundaries or technological limitations. Open learning initiatives, such as MOOCs, remove financial barriers as well. Instead, learners can (and do) go where their needs will best be met. The educational marketplace is becoming learner-driven.

Interpretations and Implications

Why, then, are MOOCs significant? Because MOOCs are a clear indicator that the realm of post-secondary education is changing as a result of advances in technology. The shift from a top-down, institution driven marketplace to one where a learner can use technology to create a  personalized, piecemeal learning experience from multiple institutions requires institutions to ask themselves what they offer learners that is unique. If one institution meets a unique need, and can fulfill this need on a mass scale for learners better than any other institution, then other institutions need to find a different competitive edge.

Furthermore, if MOOCs become a viable educational option (viable in the sense that employers begin to value emerging credentialing systems created by MOOC providers), then there is a real risk that MOOCs will encroach upon the territory of undergraduate education. Post-secondary institutions rely on heavy enrollment of first and second year students to fund their operations and programs. Losing first and second year students to MOOCs will be detrimental to any institutions.

With that said, according to many of the people I interviewed, there will always a be place for research universities and Ivy league schools. These research-based schools fulfill a market need for an element of prestige attached to credentials, networking opportunities with leaders in the field of study, and the opportunity to conduct innovative research. The institutions most at risk of losing students to online and open learning initiatives are those that simply disseminate information generated elsewhere (typically from prestigious research-based institutions).

Given the potential impact of MOOCs, they can certainly be classified as disruptive; however, they are not a disruptor. The shift toward a learner-directed marketplace, widespread access to high-speed Internet, and the ever-increasing global network of information are the true disruptive forces. If MOOCs had not emerged, then some other form of open learning would have emerged to meet the need for low-cost access to educational resources.

Additionally, MOOCs may not be a lasting phenomenon, especially because a sustainable model for operation has yet to be proven; however, if their popularity fades, another innovative open learning opportunity will arise. Things will not go back to the way they were. The demand for open learning will not disappear.

How can institutions survive the disruption taking place in post-secondary education?

My hope is that my research can provide a starting point for institutions to explore the ways in which they can withstand the changes taking place within post-secondary learning by exploring new niches to fill and discovering which specific learner needs they are best equipped to meet. For example, open learning programs (such as MOOCs) often provide information in a way that can be considered akin to a free, interactive textbook. Certain institutions can build on MOOCs by providing classes that help students understand the material being presented to them. In essence, the institutional programs would complement MOOCs.  The most important take-away from my research is that the conditions which have lead to the rise of MOOCs have also created new gaps in the educational marketplace, opening the door for many other innovative approaches to adult education.

My formal research report is titled Open Online Learning: This Changes Everything and can be found at http://nicolechristen.com/wp-content/uploads/2014/03/Open-Online-Learning.pdf

Bio: Nicole Christen is a digital media strategist and a recent graduate from the Master of Educational Technology program at UBC. Read more about Nicole’s professional background and areas of interest at www.nicolechristen.com/portfolio.

Submitting a doctoral thesis on online learning? Some things to keep in mind

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© Relativity Media, 2011

© Relativity Media, 2011

Old people often complain that the world is going to hell in a hand-basket, that standards are falling, and it used to be better in our day. Having examined over 40 doctoral students over the last 45 years, often as the external examiner, it would be easy for me to fall into that trap. On the contrary, though, I am impressed with the quality of theses I have been examining recently, partly because of the quality of the students, partly because of the quality of the supervision, and partly because online learning and educational technology in general have matured as a field of study.

However, one advantage of being old is that you begin to see patterns or themes that either come round every 10 years or so or never go away, and that certainly applies to Ph.D. theses in this field. So I thought I might offer some advice to students as to what examiners tend to look for in theses in this field, although technically it should be the supervisors doing this, not me.

Who’s being examined: student or supervisor?

When I have failed a student (which is rare but has happened) it’s ALWAYS been because the standard of supervision was so poor that the student never stood a chance. Somewhat more frequently (although still fairly uncommon), the examiners’ recommendation was pass with substantial revision, or ‘adequate’ in some European countries. Both these classifications carry a significant message to the academic department that the supervisor(s) weren’t doing their job properly. (Although to be fair, in at least one case the thesis was submitted almost in desperation by the department, because the student had exhausted all his many different supervisors, and was running out of the very generous time allowed to submit.)

So the good news, students, is that, despite what might appear to be the opposite, by the time it comes to submitting your thesis for exam, the university is (or should be) 100 per cent behind you in wanting to get you through. (In recent years, this pressure from the university on examiners to pass students sometimes appears to be almost desperate, because a successful Ph.D. may carry a very significant weight towards the performance indicators for the university.)

Criteria for success

So at the risk of over-simplification, here is my advice for students, in particular, on what I, as an examiner, tend to look for in a thesis, starting with the most important. My comments apply mainly, but not exclusively, to traditional, research-based theses.

Level 1.

I have three main criteria which MUST be met for a pass:

  • is it original?
  • does it demonstrate that the student is capable of conducting independent research?
  • does the evidence support the conclusions drawn in the thesis?

Originality

The minimum a doctoral thesis must do is tell me something that was not already known in the field. Now this can still be what students often see as a negative outcome: their main hypothesis is found to be false. That’s fine, if it is a commonly held hypothesis in the field. (Example: digital natives are different from digital immigrants: no evidence was found for this in the study.) If it disproves or questions current wisdom, that’s good, even if the result was not what you were expecting. In fact, that’s really good, because the ‘null hypothesis’ – I’m trying to prove my hypothesis is false - is a more rigorous test than trying to find evidence to support something you actually thought to be true before you started the research (see Karl Popper (1934) on this).

Competence in research

For students, there are three good reasons for doing a Ph.D.:

  • because you want an academic position in a university or college
  • because you want to work as a full-time researcher outside the university
  • because you have a burning question to answer (e,.g.: what’s best done face-to-face, and what online, when teaching quantum physics?)

However, the main purpose of a Ph.D. (as distinct from other post-graduate qualifications) from a professional or institutional perspective is to enable students to conduct independent research. Thus the thesis must demonstrate this competency. In a sense, it is a trust issue: if this person does research, we should be able to trust him or her to do it within the norms and values of the subject discipline. (This is why it is stupid to even think of cheating by falsifying data or plagiarism: if found out, you will never get an academic job in a university, never mind the Ph.D.)

Evidence-based conclusions

My emphasis here is on ensuring that appropriate conclusions are drawn from whatever evidence is used (which should include the literature review as well as the actual data collected). If for instance the results are contrary to what might be expected from the literature review, some explanation or discussion is needed about why there is this difference. It may have to be speculative, but such contradictions need to be addressed and not ignored.

Level 2

Normally (although there will be exceptions) a good thesis will also meet the following criteria:

  • there is a clear narrative and structure to the thesis
  • there is a clear data audit trail, and all the raw/original data is accessible to examiners and the general public, subject to normal privacy/ethical requirements
  • the results must be meaningfully significant

Narrative and structure

Even in an applied thesis, this is a necessary component of a good thesis. The reader must be able to follow the plot – and the plot must be clear. The usual structure for a thesis in our field is:

  • identification of an issue or problem
  • review of relevant previous research/studies
  • identification of a research question or set of questions
  • methodology
  • results
  • conclusions and discussion.

However, other structures are possible. In an applied degree, the structure will or should be different, but even so, the reader in the main body of thesis should be able to follow clearly the rationale for the study, how it was conducted, the results, and the conclusions.

Data audit

Most – but not all – theses in the educational technology field have an empirical component. Data is collected, analysed and interpreted. All these steps have to be competently conducted, whether the data is mainly quantitative, qualitative or both. This usually means ensuring that there is a clear trail linking raw data through analysis into conclusions that can be followed and checked easily by a diligent reader (in this case, the examiners). This is especially important with qualitative data, because it is easy to cherry-pick comments that support your prior prejudices or assumptions while ignoring those that don’t fit. As an examiner, I do want access to raw data, even if it’s in an appendix or an online database.

However, I am also willing to accept a thesis that is pure argument. Nevertheless, this is a very risky option because this means offering something that is quite original and which can be adequately defended against the whole collective wisdom of the field. In the field of educational technology, it is hard to see how this can be done without resorting to some form of empirical evidence – but perhaps not impossible.

Significance of the research question and results

This is often the best test of how much the thesis is mainly the work of the supervisor and how much the student. A good supervisor can more or less frogmarch a student through the various procedural steps in doing a doctoral thesis, but what the supervisor cannot – or should not – provide is the original spark of a good research question, and the ability to see the significance of the study for the field as a whole. This is why orals are so important – this is the place to say why your study matters, but it also helps if you address this at the beginning and end of your written thesis as well.

Too often I have seen students who have asked questions that inevitably produce results that are trivial, already known, or are completely off-base. Even more tragic is when the student has an unexpected but important, well-founded set of data, but is unable to see the significance of the data for the field in general.

The problem is that supervisors quite rightly drill it into students that they must chose a research question that is manageable by an individual working mainly alone, and that their conclusions must be based on the data collected, but this does not mean that the research question needs to be trivial or that once the conclusions have been properly drawn, there should be no further discussion of their significance for the field as a whole. This is the real test of a student’s academic ability.

Tips for success

There are thousands of possible tips one could give to help Ph.D. students, but I will focus on just a few issues that seem to come up a lot in theses in this area:

1. Do a masters degree on online learning first

This will give you a good overview of the issues involved in online learning and should provide some essentially preparatory skills, such as an introduction to research methods and extensive writing.

Do this prior to starting a Ph.D. See: Recommended graduate programs in e-learning for a list of appropriate programs.

Do it online if possible so you know what its’s like to be an online student.

At a minimum, take a course on research methods in the social sciences/online learning.

2. Get a good supervisor

The trick is to find a supervisor willing to accept your proposed area of research. Try to find someone in the local Faculty of Education with an interest in online learning and try to negotiate a research topic of mutual interest. This is really the hardest and most important part. Getting the right supervisor is absolutely essential. However, there are many more potential students than education faculty interested in research in online learning.

If you find a willing and sympathetic local faculty member with an interest in online learning but worried they don’t have the right expertise to supervise your particular interest, suggest a committee with an external supervisor (anywhere in the world) who really has the expertise and who may be willing to share the supervision with your local supervisor. Again, though, your chances of getting either an internal or external supervisor is much higher if that person already knows you or is aware of your work. Doing an online masters might help here, since some of the instructors on the course may be interested in supervising you for a Ph.D., especially if they know your work through the masters. But again, good professors with expertise in online learning are already likely to have a full supervision load, so it is not easy. (And don’t ask me – I’m retired!)

This means that even before applying for a Ph.D., you need to do some homework. Identify a topic with some degree of flexibility, have in mind an internal and an external supervisor, and show that you have done the necessary courses such as research methods, educational theory, etc., that will prepare you for a Ph.D. (or are willing to do them first).

3. Develop a good research question

See above. Ideally, it should meet the following requirements:

a. The research is likely to add something new to our knowledge in the field

b. The results of the research (positive, negative or descriptive) are likely to be significant/important for instructors, students or an institution

c. You can do the research to answer the question on your own, within a year or so of starting to collect data.

d. It can be done within the ethical requirements of research

It is even better if you can collect data as part of your everyday work, for example by researching your own online teaching.

4. Get a good understanding of sampling and the level of statistics that your study requires

Even if you are doing a qualitative study, you really need to understand sampling – choosing subjects to participate in the study. The two issues you need to watch out for are:

1. Bias in the initial choice of subjects, especially choosing subjects that are likely to support any hypotheses or assumptions you may already have. (Hence the danger of researching your own teaching – but you can turn this to advantage by taking care to identify your prior assumptions in advance and being careful not to be unduly influenced by them in the design of the research).

2. Focusing too much on the number of respondents and not on the response rate, especially in quantitative studies. Most studies with response rates of 40 per cent or less are usually worthless, because the responders are unlikely to be representative of the the whole group (which is why student evaluation data is really dangerous, as the response rate is usually biased towards successful students, who are more likely to complete the questionnaires than unsuccessful students.) When choosing a sample, try to find independent data that can help you identify the extent of the likely bias due to non-responders. For instance, if looking at digital natives, check the age distribution of your responders with the age distribution of the total of the group from which you drew the sample, if that is available. If you had a cohort of 100 students, and 20 responded, how does the average age of the responders compare with the average age of the whole 200? If the average age of responders is much lower than non-responders, what significance does this have for your study?

Understanding statistics is a whole other matter. If you intend to do anything more complicated quantitatively than adding up quantitative data, make sure you understand the necessary statistics, especially what statistically different means. For instance, if you have a very large sample, even small differences are likely to be statistically significant, but they may not be meaningfully significant. Small samples increase the difficulty of getting statistically significant results, so drawing conclusions even when differences look large can be very dangerous from small samples.

5. Avoid tautological research design or quantitative designs with no independent variables

Basically, this means asking a question, stating a hypothesis, or designing research in such a way that the question or  hypothesis itself provides the answer. To elaborate, research question” “What is quality in online learning?’ ‘Answer: “It is defined by what educators say makes for quality in online courses and my research shows that these are clear learning objectives, accessibility, learner engagement, etc..” There is no independent variable here to validate the statements made by educators. (An independent variable might be exam results, participation rates of disabled people, etc.). Education is full of such self-justifications that have no clear, independent variables against which such statements have been tested. Merely re-iterating what people currently think is not original research.

For this reason, I am very skeptical of Delphi studies, which merely re-iterate already established views and opinions. I always ask: ‘Would a thorough literature review have provided the same results?’ The answer is usually: ‘No, you get a far more comprehensive and reliable overview of the topic from the literature review.’

6. Write well

Easily said, but not  easily done. However, writing that is clear, well-structured, evidence-based, grammatically correct and well argued makes a huge difference when it comes to the examination of the thesis. I have seen really weak research studies get through from the sheer quality of the writing. I have seen other really good research studies sent back for major revision because they were so badly written.

Writing is a skill, so it gets better with practice. This usually means writing the same chapter several times until you get it right. Write the first draft, put it away and come back to it several days later. Re-read it and then clarify or improve what you’ve written. Do it again, and again, until you are satisfied that someone who knows nothing about the subject beforehand can understand it. (Don’t assume that all the examiners will be expert in your particular topic.) If you can, get someone such as a spouse who knows nothing about the subject to read through a chapter and ask them just to put question marks alongside sentences or paragraphs they don’t understand. Then re-write them until they do.

The more practice and feedback you can get on your writing, the better, and this is best done long before you get to a final draft.

Is the Ph.D. process broken?

A general comment about the whole Ph.D. process: while not completely broken, it is probably the most costly and inefficient academic process in the whole university, riddled with bureaucracy, lack of clarity for students, and certainly in the non-quantitative areas, open to all kinds of challenges regarding the process and standards.

This is further complicated by a move in recent years to applied rather than research theses. In an applied thesis, the aim is to come up with something useful that can be applied in the field, such as the design of an e-portfolio template that can be used for an end of course assessment, rather than the traditional research thesis. I believe this to be a step in the right direction. Unfortunately though education departments often struggle to provide clear guidance to both students and examiners about the criteria for assessing such new degrees, which makes it even more of a shot in the dark in deciding whether a thesis is ready for submission.

Other suggestions or criticisms

These are (as usual) very personal comments. I’m sure students would like to hear from other examiners in this field, particularly if there is disagreement with my criteria and advice. And I’d like to hear from doctoral students themselves. Suggestions for further readings on the Ph.D. process would also be welcome.

I would also like to hear from those who question the whole Ph.D. process. I must admit to mixed feelings. We do need to develop good quality researchers in the field, and I think a research thesis is one way of doing this. I do feel though that the whole process could be made more efficient than it is at the moment.

In the meantime, good luck to all of you who are struggling with your doctoral studies in this field – we need you to succeed!

Reference

Popper, K. (1959) The Logic of Scientific Discovery London: Routlege