November 27, 2014

Contact North on Online Learning, Innovation, Flexibility and Open Educational Resources

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Contact North's humble office in Sudbury, Ontario

Contact North’s humble office in Sudbury, Ontario

Contact North continues to produce a range of interesting short pieces on different aspects of online learning. (Disclaimer: I am a Contact North research associate, and have contributed a few times.)

The April 9 edition of Contact North’s Online Learning News contains three such contributions (all these pieces are generally anonymously written):

The What, Why, Where, and How of Open Educational Resources (OER)

Dr. Rory McGreal, Contact North | Contact Nord Research Associate and the UNESCO/Commonwealth of Learning Chair in Open Educational Resources answers these fundamental questions in a series of 10 short, informative videos, Open Educational Resources (OER) – A Video Primer.

There are two available at the moment, with others coming:

  1. What are open educational resources?
  2. Comparing commercial and open educational resources.

How to Design an Innovative Course

This piece suggests some steps that can help faculty and instructors approach the issue of innovative teaching in a systematic way, including

  • being clear on the problem you are trying to solve
  • working in a team
  • applying technology appropriately to address the problem to be solved
  • evaluating and disseminating your innovation

Greater Flexibility as the New Mantra

I have recently visited a Canadian university developing a major strategy around flexible learning, and this short piece (by someone else) suggests a wide range of ways in which institutions can increase their flexibility, including:

  • course design and delivery options
  • learning recognition and credit granting
  • program completion
  • assessment
  • transition from apprenticeship through diploma to degrees to graduate work .

These and many more items can be found on Contact North’s ‘Ontario Online Learning Portal for Faculty and Instructors’, available both in English and French.

Click here if you wish to subscribe to Contact North’s newsletter.

Contact North on How to Design an Innovative Course

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Image © University of Ontario Institute of Technology, 2014

Image © University of Ontario Institute of Technology, 2014

Anon (2014) How to design an innovative course, Sudbury.Thunder Bay ON: Contact North

As reported in Contact North’s Online Learning News:

There is a lot of pressure these days on faculty and instructors to be ‘innovative’ in their teaching. But exactly what does being innovative mean? How do you go about designing and implementing an innovative course? What is the problem you are trying to solve? Will technology help? Learn a series of steps that can help you approach innovative teaching in a systematic way.

Comment

I found this article quite interesting. No author is given but they must be pretty smart to get this topic down to about 1,000 words….

How problem-based learning can help develop innovation skills

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© CTLT, UBC, 2013

© PBL Math, CTLT, UBC, 2013

Hoidn, S. and Kärkkäinen, K. (2014) Promoting Skills for Innovation in Higher Education A Literature Review on the Effectiveness of Problem-based Learning and of Teaching Behaviours Paris: OECD Education Working Papers, No. 100, OECD Publishing.

In a previous post, I discussed a report from the OECD that showed in a broad way the relationship between different pedagogies and the kinds of thinking associated with innovation. In particular it suggested that:

the emphasis of programmes on practical knowledge, on student-led projects and on problem-based learning are reflected in the level of creative skills, of oral communication skills and of teamwork and leadership skills of students.

Here I look at a second paper that explores in more detail the relationship between problem-based learning and skills found among innovators. In particular:

This report … reviews the current evidence on the effectiveness of problem-based learning compared with more traditional approaches in higher education teaching [and] explores the extent to which problem-based learning can be an effective way to develop different discipline-specific and transferable skills for innovation. 

Main results

  • Research, primarily from the field of medicine, shows that problem-based learning appears to be beneficial in fostering certain aspects of skills for innovation.
  • [In particular] …problem-based learning appears to be beneficial in fostering long-term retention and knowledge application, developing thinking and creativity skills, as well as social and behavioural skills (e.g. problem-solving, critical thinking, motivation, self confidence, team work).
  • By contrast, no clear difference between problem-based learning and traditional lecture-based teaching emerges as to performance in tests.
  • The benefits of PBL over traditional approaches seem to become more visible when examining higher education students’ long-term retention of knowledge. While PBL students may be slightly inferior to traditional students in overall knowledge and competence, they appear to be superior in long-term recall and retention.
  • Students in PBL appear to employ more productive approaches to study, have better interpersonal skills and appear to be more motivated than students in more traditional higher education programmes.
  • Despite the promising evidence linking problem-based learning and effective teaching in higher education to certain aspects of skills for innovation, more work is needed in this area. In reality there is no dichotomy between problem-based learning and “traditional” teaching and learning approaches  – policymakers and practitioners would benefit from a better understanding about which specific practices are effective for fostering different skill sets.
  • Faculty plays a pivotal role in enhancing student learning. Instructors can be trained to apply certain instructional behaviours that have been shown to be effective or to use student-centred forms of teaching and learning such as PBL and other methods that facilitate deep approaches to learning. Faculty can learn to give clear explanations and prompt feedback, present well-organised materials, ask students challenging questions, encourage student participation in the classroom and show concern and respect for students and student learning.

Implications for online learning

Although this paper does not discuss online learning or technology-based approaches to PBL, online learning can provide more flexibility and opportunities for problem-based learning, although to date, where problem-based learning and online learning have been combined, it is usually in a hybrid model. A common design is for students to gather in class for the definition of the problem, and instruction on the key steps to be taken, then to work collaboratively in small groups online on problem solution, returning to class for presentation and discussion of each group’s conclusions. However, there are also examples of fully online courses using a problem-based or inquiry-based learning approach.

In either hybrid or online learning modes, though, it is critical to give clear guidelines and structured steps to be taken to solving problems, especially for students who are new to this teaching approach. It is also important to ensure that assessment actually measures skills in problem-solving and critical thinking, and is not just a test of comprehension. Once again, it is not so much the mode of learning that matters as the quality of the teaching methods and assessment within that mode.

Comment

The study provides a pretty good overview of new developments in teaching in higher education, and where some of them are taking place. Indeed the paper recognizes that PBL started at MacMaster University in Canada in the 1960s. As the report notes:

[At that time] medical students lacked clinical reasoning, problem-solving, and critical thinking skills. There was concern that medical schools put a too heavy emphasis on memorisation of potentially irrelevant or soon-to-be-outdated facts instead of skills necessary to practice medicine. At the same time, medical students themselves seemed to be disenchanted and bored with their education because they had to absorb vast amounts of information of which much was perceived to have little relevance to medical practice.

The paper is worth reading, not so much for its conclusions, which are not startling, but because it provides an excellent summary on the research on how students learn at a higher education level, and the implications for the training of faculty. In essence, problem-based learning is valuable but depends on the learner having sufficient ‘foundational’ knowledge to enable them to tackle problems. This foundational learning may benefit from more traditional or formal approaches to teaching. The main value though of the paper is that it provides evidence-based guidelines for effective teaching.

 

Producing ‘innovative’ graduates and how online learning can help

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© Heath Robinson 1939

© Heath Robinson 1939 – it’s not just engineers needed

Avvisati, F., Jacotin, G., and Vincent-Lacrin, S. (2013) Educating Higher Education Students for Innovative Economies: What International Data Tells Us, Tuning Journal for Higher Education, No. 1

Hoidn, S. and Kärkkäinen, K. (2014) Promoting Skills for Innovation in Higher Education A Literature Review on the Effectiveness of Problem-based Learning and of Teaching Behaviours Paris: OECD Education Working Papers, No. 100, OECD Publishing.

Innovation, higher education and online learning

OECD’s Centre for Educational Research and Innovation (CERI) has recently published two interesting papers which while not specifically about online learning, address issues that are very relevant for teaching in higher education. These papers give some useful directions for the design of online learning for developing the skills and knowledge that lead to innovation.

In this post, I will discuss the paper by Avvisati et al, and in another post the paper by Hoidn and Kärkkäinen.

The paper’s goal and methodology

Avvisati et. set out to address the following question:

What is the broad mix of skills needed in innovative societies and sectors, and how can higher education institutions and innovation policies contribute to fostering this mix?

Avvisati et al. analysed the responses to two OECD surveys of tertiary graduates five years after their graduation, namely the twin surveys Reflex and Hegesco.

Avvisati et el. define “highly innovative” professionals as those working in innovative organisations and involved in the introduction of innovations; they represents on average 56% of tertiary-educated professionals in the 24 or so mainly European countries that were surveyed.

Main results

  1. Innovation requires a broad mix of academic subject domains. For instance:
    • in manufacturing industries, 50% of ‘highly innovative professionals’ have an engineering/science degree
    • in business and finance industries, the bulk of the highly innovative workforce is formed by business graduates, social sciences graduates, and law graduates
    • a significant proportion from all fields [of study] work in a highly innovative job: 60% of engineering/science graduates; 58% of arts/agriculture graduates; 50% of education graduates

This conclusion has important policy implications, as innovation policies concerned with human resources tend to have a narrow focus on scientists and engineers (and sometimes entrepreneurship). An overly exclusive focus on the training of scientists and engineers to promote innovation is largely misplaced, given that other graduates do also contribute significantly to innovation and that the relative importance of the manufacturing sector, where STEM graduates predominate, [is] decreasing in most OECD economies.

2. The critical skills that distinguish innovators from non-innovators the most are:

    • creativity (“come up with new ideas and solutions” and the “willingness to question ideas”), followed by
    • the “ability to present ideas in audience”,
    • “alertness to opportunities”,
    • “analytical thinking”,
    • “ability to coordinate activities”, and the
    • “ability to acquire new knowledge”

3. ‘Highly innovative professionals’ tend to agree that universities developed mostly their thinking and learning skills (analytical thinking and the ability to rapidly acquire new knowledge) as well as their domain-specific expertise (mastery of their own field or discipline).

4. At the same time, respondents were dissatisfied with the level of social and behavioural skills acquired through their university programme; ‘presenting ideas’ and ‘coming up with new ideas and solutions’ were not considered to be a particularly strong point of university education.

5. Respondents also reported that their progress as students was consistently and significantly associated with the quality of teaching and learning inputs:

    • graduates are more likely to participate in innovation processes after having attended …programmes stressing practical knowledge, such as student-led projects and problem-based learning
    • theory-based forms of instruction, such as lectures and the learning of theories and paradigms, have a positive, but weaker association with innovation
    • the emphasis on theoretical knowledge and conceptual understanding are particularly associated with … analytical thinking, in acquiring new knowledge, and in writing
    • the emphasis of programmes on practical knowledge, on student-led projects and on problem-based learning are reflected in the level of creative skills, of oral communication skills and of teamwork and leadership skills of students
    • thus a diverse offer of pedagogies is the most effective way to foster all skills for innovation in the working population.

6. The mastery of one’s own field is not among the very top skills that differentiate the most highly innovative from less innovative professionals. Many of the critical skills for innovation can be fostered in all domains, even though it could take a different shape from one subject to the other.

7. There is overall no strong evidence of a shortage (or coming shortage) of tertiary education graduates in STEM disciplines in the OECD area.

Comment and discussion

Some care is needed in interpreting these results. It should be noted that they reflect the views of ‘innovative workers’ five years into post-degree employment, not employers or more senior executives or managers, and most of the responders would have been European. Innovation itself is not clearly defined other than it’s what people in the survey say it is. For most of us, these results will not appear surprising, and will reinforce beliefs that are held by many – but not all – academics. However, the results of this study do challenge conventional wisdom sometimes found among policy-makers and the general public.

I draw the following conclusions from this study:

  • we need to continue to support a wide variety of disciplines and subject domains in our universities if we really want innovation across our society and economy; STEM subjects are important for innovation in many but by no means all areas of innovation in work and society
  • as always in pedagogy, it is not a question of either theory or practice, of information transmission or knowledge management. We need diverse approaches to pedagogy/teaching methods, and these need to be fine tuned within different subject domains
  • more empirical work needs to be done on the link between productive innovation, intellectual skills development, content, and teaching methods
  • nevertheless, it seems clear to me that knowledge management, independent learning and lifelong learning will become increasingly important skills for the promotion and development of innovation in work and society
  • learning technologies and in particular online learning can contribute significantly to developing skills that will foster innovation, but the technology must also be wedded to appropriate teaching methods
  • teaching for innovation is still more art than science, but it is not totally a shot in the dark.

Next

I will review the other OECD paper that is a literature review of the effectiveness of problem-based learning for promoting skills for innovation in higher education, and what that might mean for online learning.

 

 

Productivity and online learning redux

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If only it was this simple: Image© Course Gateway, 2013

If only it was this simple: Image© Course Gateway, 2013

Summarizing the previous posts

In previous posts (see end of this post), I tried to identify a range of areas where online learning might enable productivity gains. In this post I will bring them together and state what I believe are the areas that offer the potential for the greatest gains, given current knowledge. At this stage my conclusions are very subjective but I hope they will provide a framework for further studies and for better and more systematic data collection.

Access

There are fairly strong arguments (but little hard data) to suggest that online learning can help governments boost participation rates more effectively than by building more campuses and funding more campus-based education. Productivity is increased by eventually getting more graduates than would otherwise have been possible without online learning and the flexibility it allows.

The reasons to support this argument are as follows:

  • Particularly in jurisdictions where there is already a high participation rate, increasing that rate further means reaching out to groups that have to date been largely excluded from post-secondary education. Since existing data indicates that online learning appeals particularly to lifelong learners, working adults and older learners, online learning is more likely to appeal to this target group. To date though there has been little attempt to measure the impact of reaching otherwise excluded groups through online learning. More hard data is needed to support this argument.
  • there is some evidence to suggest that online learning has lower overhead costs than campus-based education. If this is correct, it may be more productive to expand online learning rather than build new campuses when attempting to increase participation rates. Again though there are few studies that provide hard data to show that overhead costs are indeed lower for online learning.
  • it has been argued that hybrid and online learning provides existing students with more flexibility, allowing them to combine work with part-time study, thus allowing them either to complete studies they could not afford without part-time work, or to complete more quickly than they would without the flexibility that online learning provides. Of course the argument could work in reverse. By providing more flexibility, students may take longer to graduate. Once again, it should be possible to test either argument empirically, but again there are few if any studies that have looked at this.

Thus online learning offers the promise of increasing productivity through increasing participation and speed to graduation  at less cost, but there are few studies to date to either support or refute these claims. It should be noted though that in most cases, the data to test these arguments is within institutional databases; it has just not been extracted and analyzed for this purpose.

Wilfred Laurier University is proposing a campus in Milton Ontario - but would it be more productive to use online learning?

Wilfred Laurier University is proposing a campus in Milton Ontario – but would it be more productive to use online learning?

Free or massively scalable content

Nowhere in online learning is there such potential for increases in educational productivity as in content development and delivery. Once learning materials are created, they can be stored, accessed, delivered and used by an unlimited number of learners, thus potentially achieving large economies of scale and thereby reducing costs per learner (see graph at beginning of this post).

Another important factor contributing to economies of scale in online learning is the increasing availability of open educational resources. Particularly in foundational courses and many ‘standard’ undergraduate courses, ‘open’ material is already available and does not have to be re-created. The main cost is selecting and organizing existing open source materials, but this is likely to be less time-consuming for faculty than creating materials from scratch. Open online textbooks can have a direct and immediate impact on reducing student costs.

Nevertheless there are many impediments to achieving productivity gains through free or massively scalable content:

  • faculty often see themselves as  creating unique and original material in their teaching; this is true occasionally and needs to be respected, especially where faculty are teaching about their own and related research. Often though faculty are merely repackaging prior knowledge. That prior knowledge is increasingly being made available and open for anyone to use.
  • the shelf life of much academic material is increasingly short; thus content needs to be constantly maintained and updated
  • there may not be a massive market for many specialist online courses thus preventing economies of scale from being achieved. However, there are many ways to increase market reach with online learning, including going global, collaborating and sharing materials, courses and programs with partner institutions in the same or other jurisdictions, repackaging content for different markets (e.g. for casual learners, certificates, or degrees). Such strategies though will also require reviewing and often changing admission policies, intellectual property agreements and other practices that restrict access to ‘institutional’ content.
  • the quality of open educational resources developed by faculty working alone, without applying best course design practices, is often very low and such ‘open’ resources are often not considered suitable for re-use
  • content development and delivery is a relatively small proportion of the cost of credit-based online learning (from 15-20%); the main costs are in learner support.

Despite these impediments, in certain circumstances (i.e. where there is a large market and best practices are applied to content design), online content development and delivery is already resulting in increased productivity in post-secondary education, although it has yet to be well measured.

Course design based on sound pedagogical principles

One important reason for the success of many for-credit online courses and programs has been the introduction of best practices in course design, drawing on cognitive science research, best teaching practices, and prior experience of teaching students at a distance. These practices include situated learning, drawing on learners’ own work and life experiences, student time-management support, collaborative learning, student activities resulting in greater time on task, and regular and constructive feedback to students through continuous assessment.

In particular a focus in online courses on ’21st century skills’ development, such as knowledge management and independent learning, would have two benefits. It would improve outputs (turning out graduates with the skills needed). Second, content development and delivery becomes subsidiary to helping students find, analyze, organize and apply content themselves. Thus less time would be spent by instructors on course development and delivery.

Such practices of course could be be used in classroom teaching, but good online course design templates are more easily scaled and reproduced, and the technology lends itself to such approaches to learning. Productivity is improved through application of such quality course design because more students achieve higher levels of learning and more students complete courses and programs. Thus although it is not the technology itself that results in better outcomes, the technology facilitates the change to more effective teaching methods.

Once again though, while teachers and students who have been engaged in such new designs often claim better outcomes, there is still a lack of convincing empirical research to support these beliefs. Nevertheless, a focus on better design replicated on a large scale through online learning should have a major impact on improving productivity.

Learner support

What little research that has been done on costs of credit-based online learning indicates that course delivery (which includes both learner support and student assessment) accounted for the largest overall cost of an online program (37%), almost three times more than course development, over the life of an online program (Bates and Sangra, 2011).

Instructional MOOCs (xMOOCs) have basically removed learner support, at least in terms of human (instructor) support, but this has resulted in a very low number of MOOC learners passing end-of-course assessments of learning. Indeed, prior research into credit-based learning has established that instructor online ‘presence’ is a critical factor in retaining students. So far, it has proved difficult to scale up learner support on a massive scale, except through the use of computer technology, such as automated feedback. However, Carey and Trick (2013) and indeed faculty at elite institutions who are offering xMOOCs (see Thrun and ‘the Magic of the Campus‘) have argued that such computer support does not support ‘the learning that matters most’.

Although computer-based feedback and adaptive learning facilitate comprehension and technical mastery outcomes, computer-based approaches to learner support to date has been inadequate for formal assessment of higher order learning skills such as original, critical or strategic thinking, evaluation of strategies or alternative explanations. To assess such forms of learning, deep expertise and qualitative assessment is required, and to date not only human instructors, but instructors with a deep subject understanding and high levels of expertise, are needed to both develop and assess such high level skills. Given the long history of trying to apply artificial intelligence to instruction, immediate and major breakthroughs seem unlikely, at least in the short term.

A l'école, Jean Marc Cote, 1901.

A l’école, Jean Marc Cote, 1901.

However, there are other ways in which the productivity of learner support might be improved. In cMOOCs that are more like communities of practice and thus contain many participants with already high levels of expertise, that expertise and judgement can be provided by the participants themselves. (The issue then is how do people get to such high levels of expertise in the first place – we need more research/experience with cMOOCs to know whether they are also good for learners with initially low levels of knowledge in a particular subject domain. Some combination of expert/instructors plus a community of practice approach might be necessary for such learners, but might still operate successfully with much higher instructor:learner ratios than in conventional, credit-based learning.)

Also, credit-based online learning has achieved some economies of scale and scope by re-organizing the learner support process, through the hire and training in online learner support of lower-paid contact adjuncts who still have high level academic qualifications, under the supervision of a senior faculty member. In other words, team teaching approaches, with the senior academic working more as a teaching consultant, setting curriculum, designing assessments and creating rubrics, and supervising the learner support provided by a team of adjuncts, can help not only reduce costs but also achieve modest economies of scale in learner support, especially when combined with best practices in course design.

Innovation vs standardization

In industry, innovation is often another way of saying ‘investment in technology’. However, there is more to innovation than just replacing a human activity with a computer-based activity. What the technology usually brings about is a change in process at the same time.

Thus there is a natural tension between ‘best practice’, based on experience of doing things in an ‘old’ way, and innovation, which means doing something differently. Indeed Christensen (2008) distinguished between ‘sustaining’ innovation, which builds and improves on best practices, and ‘disruptive’ innovation, where a new technology results in sweeping away old ways of doing something. Real, sustainable innovation occurs then when new technology is combined with new processes.

In education, perhaps the main ‘process’ that we need to examine is the instructional model, particularly that based around the lecture system. I am not arguing that lectures no longer have a purpose. However, the teaching model based on three lectures a week over 13 weeks used primarily to deliver information to students is now redundant, given that information is ubiquitous and if not free, increasingly available at low cost over the Internet. Thus knowledge management becomes more important than mere access to knowledge. If we look at xMOOCs though we have taken a new technology – video lecture capture and Internet transmission – and applied it to an outdated model of teaching. True innovation requires a change of process or method as well as a change of technology.

Earlier though I argued that we need to apply best practices in course design to the use of technology. By definition, best practices are based on tried and true methods. However, in post-secondary education, these ‘best practices’ are not the prevailing teaching method on most campuses (except perhaps the very elite, where they can be applied on a face-to-face basis to small classes.). As public post-secondary education has become massified, the lecture has become the default model, because in a classroom based system, it has proved the only way to ‘scale up.’ Online learning offers an opportunity to break out of this redundant and increasingly less productive lecture model of teaching, as it does not develop the skills needed in the 21st century.

There are then really two routes to innovation. The least risky is the sustainable development approach, finding ways to incorporate and more importantly adapt ‘best practices’ on a massive scale through online learning. This will mean increasing productivity in relatively small steps. The advantage of this approach is that it is more likely to preserve and protect the core values of ‘higher’ education. The other route is ‘disruptive’ innovation – jumping into an entirely different way of doing something based around a new or emerging technology. This is more likely to bring much greater productivity gains, but the risks are much higher. It could well result in throwing the baby out with the bathwater.

In reality, institutions, and individuals within those institutions, cannot control disruptive innovation – it comes from outside. However, institutions can control sustainable innovation. Indeed if they do not they are much more vulnerable to disruptive innovation. Thus it is important to find new best practices that are easily scalable, while meeting the needs of 21st century learners at high quality. This is probably the most sensible way to bring about radically better productivity. But it’s not going to be easy.

Conclusions

So here are my personal views on online learning and productivity, based on this analysis.

1. Government and institutional leaders need to set improved productivity as a key goal for investment in learning technologies. This means setting benchmarks and implementing means of measuring success or otherwise in improving productivity through learning technologies/online learning. Data analytics now make this measurement more feasible than in the past, but it also requires models or a theoretical framework for assessing what constitutes productivity in a post-secondary educational setting.

2. Understanding the basic cost structures of online learning, compared to the costs of classroom teaching, is an essential first step to increasing productivity in post-secondary education. It is risky to assume that online learning is always more cost-effective or productive; the circumstances need to be right.

3.Content is only one component of teaching (and an increasingly less important component); other components such as learner support and assessment are even more important. Care is needed then because changes in methods of online content development and delivery could have negative knock-on cost and productivity consequences in other areas of course delivery, such as learner support and assessment. In looking at productivity issues, all these factors need to be examined together.

4. Any attempts at scaling or increasing economies of scope in content development and delivery need to be balanced by ensuring quality does not suffer. However, online course development has the potential, through good course design, to improve quality rather than reduce it.

5. The ‘learning that matters most’ mainly addresses university teaching, but also increasingly technical, vocational and corporate training; the aim is to develop the knowledge and skills needed in a knowledge-based society. Online learning can handle the ‘learning that matters most’ as well, in most cases, as on-campus teaching, although there will always be some exceptions.

6. However, there are major difficulties in scaling up the learner support and assessment activities that are needed for the learning that matters most, both online or on campus. The danger in scaling up is the loss of quality in terms of learning outcomes.

7. Adaptive learning software that helps individualize learning, and learning analytics, may help to a small degree in enabling instructors to handle slightly more students without loss of quality, but cannot as yet replace a skilled instructor, and probably never will. Higher education requires expertise and qualitative assessment for the learning that matters most, and that will need human instructors.

8. New online course designs built around the use of new technologies have greater potential for increases in productivity – through producing better learning outcomes – for the learning that matters most, than through scaling up, i.e. by increasing teacher:student ratios.

9. We need more empirical research on the relationship between teaching methods, mode of delivery, costs, and the type of learning outcomes that constitute the ‘learning that matters most’ (not to mention better definitions).

Now it’s your turn

As I’ve said, this has been a struggle for me to work through the issues of online learning and productivity. The whole purpose of this arduous exercise is to promote debate and discussion about productivity and online learning. So I’d really welcome your comments. It would be great to hear from people with experience in productivity in other areas besides education, and to hear from those in education about the potential or dangers of applying the thinking around productivity to online learning.

So go for it!

Other posts in the series

© Ann Helmond 2009

© Ann Helmond 2009