My Views on The Second Machine Age

With ‘The Second Machine Age‘, Erik Brynjolfsson and Andrew McAfee have written a fascinating book, which deservedly parks in many’s books of the year lists.  Written by two MIT scientists, it tracks the impact so far of the digital age and looks at the future.  The authors claim the impact of digital technology will be as big, or bigger than that of the first machine age, and will reinvent our lives and economy.

Some key points from the book:

  1. Although the PC was Time’s ‘Person’ of the year in 1982, the full impact of digital technologies has only recently reached full force.  There are different reasons for this:
    • Moore’s Law. First formulated in 1962, it roughly stated that the amount of computer power you can buy for one dollar would double each year.   This ‘law’ has proven remarkably correct for over 40 decades.  It has even proven to be correct for many digital technologies.  That continuous doubling has brought us in the ‘second half of the chessboard’ where the absolute amounts increase phenomenally.
    • Digitization of information.  More information is available in digital format.  With the ‘internet of things’ massive amounts of digital data are created.
    • Network effects.  The more people are online and using an particular platform, the stronger the benefits.
    • Organisational capital.  Companies investing in IT, typically spend about 10 times that amount on changes in the organisation of the company.  Using IT to do existing things faster does not increase productivity much.  It’s using IT to do things fundamentally different what makes the difference (a comment often formulated about using computers in classrooms as well).  Such fundamental rethinking of production processes usually takes several decades, as existing managers retire and are replaced by ‘digital natives’.
  2. Digital goods are fundamentally different from physical goods
    • They have a high cost to create, but are almost free to replicate unlimitedly;
    • They are not exhaustive, you can not ‘use up’ a digital good.
  3. These characteristics have profound effects on our economy
    • Job (and wage) polarisation.  Demand for routine manual and cognitive jobs has been falling, depressing wages.  Demand has been rising for skills that complement digital technologies (pattern recognition, assessing complex situations…).
    • “Winner takes all” markets.  We have been moving from markets with absolute advantages to markets where a small relative advantage leads to absolute dominance.  Being a slightly better writer 50 years ago would give you slightly higher scales, as the extent you could market and sell your writings would be limited.   There was a market for many writers, some slightly better or worse than others.  Today, a writer as JK Rowling can sell her books worldwide, dominating the market for fiction writing.
    • GDP as a measure of economic activity becomes less useful. GDP is based on physical reproduction of items.  When digital items are copied, people enjoy from ‘free’ digital services or produce intangibles such as intellectual property and human capital, these are not captured in GDP.
    • Traditionally, productivity growth has been linked to rising living standards.  The share of labour in GDP growth has fallen in recent years (to the expense of the share of capital).  This, together with the job polarisation, implies that rises in productivity do not longer automatically translate into broadly shared rises in welfare.  This explains the jobless recoveries after recent crises.

Whereas the authors are inherently optimistic about the digital age, they do see risks of high unemployment:

  • Job polarisation and “winner takes all” markets reduce demand for certain jobs.
  • Inelastic demand. Demand for goods may rise slower than prices fall as a result of technological progress.
  • Technological progress may be faster than the ‘adjustment time’ to re-skill workers for jobs that are in demand.

For the solutions, the authors look mainly at education.  This chapter is one of the weakest.  The authors advocate a re-think of the curriculum towards ’21st century skills’ and a stronger focus on entrepreneurship.  The authors put high hopes in MOOCs (only xMOOCs in fact, not the much more interesting cMOOCs), brushing aside the fact that they offer a sub-standard experience of what on-line learning can be.  They have a point that, as on-line learning becomes more mainstream, the characteristics of digital goods markets will impact education, such as job polarisation and ‘winner takes all’ markets. In South Korea, for example, lectures from ‘superstar’ teachers with  astronomical salaries are broadcast on-line, reducing the role of traditional teachers.

But nevertheless a great book on the analysis of how digital technologies have been affecting our lives, and are likely to disrupt it even a lot more.  For the part on how education could (and needs to) respond to our changing society, I would recommend other articles, books and blog posts.


EdX IMF Course Financial Programming and Policies: Macroeconomic Accounts & Analysis: Final Notes

mooc_cartoonEdX is a non-profit MOOC platform provider, started up by Harvard University and MIT.  Its platform is used by a variety of universities and a few international organisations such as the World Bank and the IMF for delivering free on-line courses, inappropriately called MOOCs.   This course took place over 8 weeks and contained 6 modules.


1.  The Content

The main sectors of a country’s economy were discussed. The pedagogy was based on the usual behaviourist EdX model: lectures of approx. 10 minutes, followed by short practice questions and occasionally interspersed with a little reading or MS Excel exercise.  Content was challenging (for me, as a non-economist), with a clear progression from basic principles over simple applications to more advanced scenarios and case-studies. Ideas encountered earlier in the course were regularly revisited.  The bulk of the course consisted of explaining the main macro-economic balances (real sector, financial sector, external sector…).  The most interesting parts of the course were when these balances were related to real world examples (using thinly disguised pseudonyms such as ‘fiscalia’).  Part 2 of the course will hopefully continue with this more applied approach.

2. The exercises

Exercises were generally of an appropriate level. Some multiple choice questions required combining several concepts and revisiting the content from earlier weeks. There was an overall

imf1In order to remain eligible for a certificate of completion a weekly minimum score of 50% was required. Apart from multiple choice questions, the weekly assignment also contained an exercise, made extremely simple because of video tutorials explaining in detail how to do the exercise. I assume this aimed at allowing as many learners as possible to proceed to the next level.

Every week, learners were asked to analyse sector data for their country and publish this in the forum. This should have been the most interesting part of the course. Looking at how the monetary or government balances of various countries illustrated the effect of global evolutions or national policies. Unfortunately, very few learners engaged in this activity (me neither, I admit). I believe the main reason is time. The envisioned time per week was approx. 10 hours, leaving many people with little time left to do this exercise and explore others’ postings. Spreading the course over more weeks, or even allowing a separate week for this kind of exercises would be a solution. Also, in a more open and connectivist spirit, encouraging learners to post their writings on their websites or blogs would have allowed outsiders to read and comment. This may also have allowed bringing in some counterweights to the procedures and analyses of the IMF.

3. The Pedagogy

The forum was clearly the problem child of the course. Most interaction was limited to learners asking questions (duly answered by IMF staff). There was little discussion; in particular during the second half of the course. Given the international origin of participants (given introductions in week 1) this was a missed chance. Activities actively fostering discussion could help, as well as IMF staff taking a more tutoring rather than teaching approach.

It’s rather baffling how these courses still largely ignore what decades of experience and research on on-line learning have found. Salmon’s e-tivity model could be used to design on-line activity sequences, insights on communities of practice could be used to foster on-line collaboration and link course content to participants’ contexts. Web 2.0 tools could be used to let participants engage with course content and re-create materials, such as concept maps, blog posts, podcasts etc.   This neglect of existing expertise raises questions about the real intentions of the course.

These xMOOCs are quite far away from the original cMOOCs as they were introduced by Stephen Downes, Dave Cormier, George Siemens and others in 2008.  In fact, based on content and pedagogy, this MOOC could aptly be described as a ‘textbook with ambition’.  Moreover, these MOOCs are only open in the sense that they are free, not in the sense that their materials can be re-used or adapted.  Such a version of openness can hardly claim to be a social justice endeavour, as these MOOCs often claim to be.

4. Final verdict

A positive final verdict though. Unlike other MOOCs from the EdX/ Coursera/ Futurelearn school, this course offered more than a mere taster. It was a thorough and intensive introduction to the analysis of macro-economic accounts. However, I felt disappointed that the pedagogy still hasn’t improved since the last time I completed a xMOOC.  The IMF plans a few other courses on EdX. I’ll certainly give them a try.

Origins of MOOCs

Some welcome antidote to the avalanche of – mainly US-centred – information assuming that MOOCs started with the 2011 AI (Artificial Intelligence) course at Stanford and the subsequent Silicon Valley fuelled start-up frenzy spearheaded by Coursera, edX and Udacity.

The graph below comes from a JISC CETIS publication and helpfully links the xMOOCs to the OER movement and the cMOOC’ers.


The figure below, from an excellent paper in Open Praxis from Sandra Peter and Markus Deimann, links MOOCs to much earlier developments such as the Public Lectures and the 17th century coffee houses.  Taking a historical perspective arguably has the advantage of countering the techno-utopian language that surrounds xMOOCs.  It also subtly dinstinguishes between MOOCs and the AI-offspring, rightly implying that these courses are no MOOCs (at least not as MOOCs were originally intended (YouTube video).


A historical form can bring a sense of perspective and yield a cautionary tale or two for the future of online education.  Peter and Deimann write: ‘ Historical forms of openness caution us against assuming that particular configurations will prevail, or that social aspects should be assumed as desired by default‘.

Such a cautionary tale may well refer to the xMOOCs, which seem to deliberately obscure the meaning of terms such as ‘open’ and ‘MOOCs’.  Looking for a viable business model, they intend to capture the emerging OER and MOOC movements before they become threatening, rather than strenghten them.  Their arguments reflect those made by Tim Wu in his excellent book ‘The Master Switch’, about which I blogged here, as they warn:

“After a period of open movements many times there have been slight but important shifts from “pure” openness towards “pretended” openness, i.e. some aspects have been modified to offer more control for producers and other stakeholders. For instance, the historic culture of the coffeehouses had been transformed to private clubs and closed, exclusive societies.”



#H809 Research on MOOCs

credit: Freedigitalphotos

credit: Freedigitalphotos

Week 12 in the H809 course and MOOCs – the official educational buzzword of 2012 – couldn’t remain absent.  The focus in this course is not so much on what MOOCs are, their history and the different types with their various underlying pedagogies and ideologies.  I blogged on MOOCs before, as a participant in LAK11, a connectivist MOOC on learning analytics.  In H809 the focus lies on issues such as:

  • What kind of information and research is available on MOOCs?
  • What kind of MOOC research would be interesting to do?
  • What are benefits and limitations of the type of information on MOOCs that is around?
  • What is the educational impact (rather than the press impact) of MOOCs?

Much information on MOOCs consists of the so-called grey literature.  Main information sources include:

  • blogs from practitioners and academics, with an overrepresentation of academics from Athabasca Un. and the OU.
  • blogs from participants in MOOCs, sharing their experiences
  • articles in open academic journals such as IRRODL, EURODL, Open Praxis
  • articles in more popular education magazines such as Inside Higher Education and The Chronicle of HE.
  • articles in the general press such as The Economist and The New York Times

Some comments on these sources:

  1. The term ‘grey literature’ may sound a bit disparagingly.  However, as Martin Weller writes, notions of scholarship and  academic publishing are evolving.  Blogs and open journals constitute alternative forms of scholarship with more interaction, less formality and shorter ‘turnaround’ times.
  2. Information and research on MOOCs is heavily Anglo-Saxon centred (or perhaps better Silicon Valley-centred?).  I couldn’t hardly find any articles on MOOCs in Dutch, although that might not be so surprising.  Although MOOCs (xMOOCs) are often touted as a ‘solution’ for developing countries, there are few perspectives from researchers from developing countries.  As Mike Trucano writes on the EdTech blog from the World Bank:

    “Public discussions around MOOCs have tended to represent viewpoints and interests of elite institutions in rich, industrialized countries (notably the United States) — with a presumption in many cases that such viewpoints and interests are shared by those in other places.”

  3. It’s interesting to see how many of the more general news sources seem to have ‘discovered’ MOOCs only after the Stanford AI course and the subsequent influx of venture capital in start-ups such as Coursera, Udacity and edX.  The ‘original’ connectivist MOOCs, that have been around since 2008, let alone open universities are hardly mentioned in those overviews.  A welcome exception is the Open Praxis paper from Peter and Deimann that discusses historical manifestations of openness such as the coffee houses in the 17th century.
  4. The advantage of this grey literature is that it fosters a tremendously rich discussion on the topic. Blog posts spark other blog posts and follow-up posts. Course reflections are online immediately after the course. Events such as a failing Coursera MOOC or an OU MOOC initiative get covered extensively from all angles. This kind of fertile academic discussion can hardly be imagined with the closed peer-review publication system.
  5. The flipside of this coin is that there are a lot of opinions around, a lot of thinly-disguised commercialism and a lot of plain factual mistakes (TED talks!).  MOOCs may be heading for a ‘trough of disappointment’ in Gartner’s hype cycle.  Rigorous research would still be valuable.  For example, most research is descriptive rather than experimental and is based on ridiculously small samples collected in a short time.  Interrater reliability may be a problem in much MOOC research .  Longitudinal studies that investigate how conversations and interactions evolve over time are absent.
  6. Sir John Daniel’s report ‘Making Sense of MOOCs‘ offers a well-rounded and dispassionate overview of MOOCs until September 2012.

Interesting research questions for research on MOOCs could be:

  • What constitutes success in a MOOC for various learners?
  • How do learners interact in a MOOC? Are there different stages?  Is there community or rather network formation? Do cMOOCs really operate according to connectivist principles?
  • What are experiences from MOOC participants and perspectives of educational stakeholders (acreditation agencies, senior officials, university leaders) in developing countries?
  • Why do people choose not to participate in a MOOC and still prefer expensive courses at brick-and-mortar institutions?
  • What factors inhibit or enhance the learning experience within a MOOC?
  • How to design activities within a MOCO that foster conversation without causing information overload?
  • How do MOOCs affect hosting institutions (e.g. instructor credibility and reputation) and what power relations and decision mechanisms are at play (plenty of scope for an activity theoretical perspective here).

A few comments:

  • High drop-out rates in MOOCs have caught a lot of attention.  Opinions are divided whether this is a problem or not.  As they are free, the barrier to sign up is much lower.  Moreover, people may have various goals and may just be interested in a few parts of the MOOC.
  • MOOCs (at least the cMOOCs) are by its nature decentralized, stimulating participants to create artefacts using their own tools and networks, rather than a central LMS.  cMOOCs remain accessible online and lack the clear start and beginning of traditional courses. This complicates data collection and research.
  • Although MOOCs are frequently heralded as a solution for higher education in developing countries, it would be interesting to read accounts from learners from developing countries for whom a MOOC actually was a serious alternative to formal education. The fact that MOOCs are not eligible for credits (at the hosting institution) plays a role, as well as cultural factors, such as a prevalent teacher-centred view on education in Asian countries.


Overview of posts on MOOCs from Stephen Downes:

Overview of posts on MOOCs from George Siemens:

OpenPraxis theme issue on Openness in HE:

IRRODL theme issue on Connectivism, and the design and delivery of social networked learning:

Armstrong, L. (2012) ‘Coursera and MITx – sustaining or disruptive? – Changing Higher Education’,

Peter, S. and Deimann, M. (2013) ‘On the role of openness in education: A historical reconstruction’, Open Praxis, 5(1), pp. 7–14.
Daniel, J. (2012) ‘Making sense of MOOCs: Musings in a maze of myth, paradox and possibility’, Journal of Interactive Media in Education, 3, [online] Available from:

2012, Year of the MOOC?

funny-farm-animals-04In various places (such as the New York Times) 2012 has been heralded as the year of the Massive Open & Online Course, also called MOOC.  Although MOOCs have been around since 2008 or so, developed by researchers like Stephen Downes, David Courmier, George Siemens, Jim Groom and others.

“In the summer of 2008 I invited George Siemens and Stephen Downes to come to edtechtalk and tell us about the new course they were teaching. They had 25 people registered (paid), at the university of Manitoba, but they had opened the class for online registration to whomever wanted to come along. Hundreds (and then a couple thousand) people took them up on it. We started talking about what it meant to have lots and lots of people learning together… somewhere in there, i called them a massive open online course… for which i have been often chastised :)” (from Dave Courmier’s blog)

They are based on a connectivist pedagogy, characterised by distributed content, network formation, creation of artefacts outside course-related structures and superfluous course boundaries.  MOOCs based on these principles are often dubbed cMOOCs, to distinguish them from their less salubrious nephews.

The main in change in 2012 has been the entering of Ivy League institutions in the MOOC fray.  As OU vice-chancellor Martin Bean notes, the arrival of great brands, lots of (venture capital) money has vastly increased the forces of disruption.  The entrance of Silicon Valley in MOOCs has been spearheaded by Coursera, Udacity (both offshoots from an open Artificial Intelligence course at Stanford University) and edX (grown from MITx after investment and participation from Harvard University and UC Berkeley).  Online courses from these providers routinely attract tens of thousands of people (although drop-out rates are stratospheric).  Mass media have picked up the phenomenon (New York Times, The Economist, Financial Times).  Coursera has been gradually expanding its offer to non-US universities and currently offers more than 200 courses from 62 universities and 14 countries, including France, The Netherlands, Hong Kong and Italy (no, not from Belgium yet, no surprises there).  It’s interesting to note that these institutions have largely missed out the evolution to online learning so far and their  Silicon-centredness and lack of regard for 40 years of research in distance and online learning has been derided by researchers.  In the UK the Open University (OU) has recently announced its own MOOC platform, Futurelearn – here is a worthwhile reflection from OU researcher Doug Clow – and in March a ‘regular’ online course (h817) will be offered partly as a free open course.

Dubbing 2012 the ‘year of the MOOC’ may seem condescending to institutions and researchers who have been active on the topic for years.  However, there’s no denying in the worldwide appeal of the Ivy League institutions and their disruptive power.  Many challenges remain, in terms of business models, learner interaction, accreditation and quality.  It will be interesting to watch if also this disruptive innovation, like radio and television before, will evolve from an open, bottom-up structure full of creativity towards a commercialised and closed system, as described so beautifully by Tim Wu in ‘The Master Swith’ (blog post on the book).

Reinventing Education with Khan Academy and AI Class

The Khan Academy and the Introduction to AI course at Stanford University are two examples of innovative use of the internet to increase access to quality education and challenge traditional educational  models.  Khan Academy is centered around a library of short videos on (mostly) science and mathematics.  The AI course from Peter Norvig and Sebastian Thrun at Stanford University attracted more than 58.000 students and 175 countries.

In this interesting 45’ video they discuss their experiences with online learning and how they see the future of education.  George Siemens, a lecturer from Athabasca University and pioneer of open courses such as the LAK11 course, provides some thoughts on the video discussion on his blog.

Elements that stood out for me were:

They expect a (further) decoupling of the teaching and the accreditation.  People will pay for rigorous assessment and subsequent accreditation, but they will have more options on how to prepare themselves.  They may enroll into a formal course, learn from work experience or use Open Educational Resources (OER).  This reminds me of the TOEFL test, which offers an internationally recognized accreditation for the level of English, but you can learn English in a variety of ways, not limited to the courses offered by the credentialing institute.  This tendency will force institutions to rethink their roles and business models, as their oligopoly on education and accreditation will be challenged.

One-shot high-stake game
Online learning opens up opportunities and removes stigmas for non-traditional student groups.  Many of the AI students and Khan Academy users are adults (as at the OU, btw).  Online learning enables combining learning with other commitments of life.  Also, online learning allows them revisiting concepts and asking questions that they might find embarrassing in a traditional classroom.  According to Sal Khan, traditional learning often is a one-shot high-stake game.  If you’re a bit too rebellious at 18 or have some personal problems, you may miss out on a degree with lifelong consequences.  Online learning makes that people can always start pursuing a degree, even if they-re 80 (as are some participants at the AI course!)

Online learning permits more easily ‘flipping’ the classroom. Students watch lectures at home, then work on problem sets in class, where the teacher can assist them one on one. More importantly though, students can work at their own pace. Khan is convinced that most students want to learn, as long as it is adapted to their pace and needs.

Both the AI course and the Khan Academy are creating tremendous possibilities for learning analytics.  The effect of small changes in content, learning experience or other motivating factors can be analysed or preference different explanations of a concept.

Science videos
I liked how Khan recalled the origins of Khan Academy and muses that the non-professional look-and-feel of the videos might actually be an important reason for their success.  The videos feel like it’s their elder brother explaining a concept to them.  Khan admits that if he would have received a million dollar grant to develop the videos, they would probably have looked like sleek McGraw-Hill videos with a polished voice-over.  In Cambodia VVOB has developed 185 short science videos, in which science teacher trainers explain low-cost science experiments.  In the programme we have given priority to quantity and content, rather than to production quality.  It would be great if some teacher trainers could continue the work and make their own short videos, explaining concepts or experiments, just as Salman Khan has done for his cousin and is now doing for thousands of students.

#LAK11 – A MOOC’s End

The LAK11 course is not yet completely over – the last week even looks busy and interesting, with various lectures on the future of learning analytics -, but why not make a short round-up already?

A MOOC (or OOC, since MOOC apparently sounds similar to the Catalan word for mucus) is a massive, open and online course. This earlier blog post outlines the characteristics of the genre.

1. The pluses

a. The participation at the course of experts from a wide range of domains guaranteed interesting forum posts and a range of contacts and resources outside the regular course materials.  Learning learning analytics by joining with the learner analysts, in real connectivist tradition.  These “expert participants” formulated critical questions and comments, and thus helped avoid the “group thinking” pitfall in online courses.

b. The course facilitators were excellent in moderating the discussions.  They managed to make the guest lectures and the round-ups interesting for both experts and non-experts.

c. The materials were high quality, with a lot of variation in content and in media and a series of software tools.  The materials were complemented by suggestions from participants. (materials will stay online and available after the course)

d. The open character of the course gives you the freedom to contribute how and when you want.  If you have a lot of time, you can do all the readings and create a summary.  If you’re too busy, you can limit yourself to reading a summary from a fellow learner.  A daily e-mail with a short round-up and a few links is sent out daily by the course facilitators.

e. The online character is perhaps an evident point, but I keep finding it amazing that you can participate from Phnom Penh in a course on learning analytics, organized from Canada with speakers from Canada, the US and Europe.

Courtesy Zigazou76

2. The minuses

a. How can such a MOOC be economically sustainable.  Preparing and facilitating the course takes a lot of time, and nobody is paying a course fee.  Offering accreditation on demand (and for payment) could be an option, but I don’t think this was an option for this course.  Improved positioning of the organizing university could bring economic benefits maybe?

b. Forum activity decreased strongly after a few weeks.  I’m not sure (since this was my first MOOC) whether this is a recurring trend or because of the more specialized course content during those weeks.  To complete a MOOC however, intrinsic motivation needs to be strong (and remain strong). 

The minuses are much shorter than the pluses, what indicates (correctly) that I found this MOOC a very interesting experience.  As a tool for continuous professional development (CPD) it’s excellent. I’m looking forward to other ones…

#LAK11 Learning Analytics – Week 1

The first week of the LAK11 course was spent on exploring the field of learning analytics.  Its relations with domains such as business intelligence and web analytics were outlined (Elias, 2011) and its close relationship with academic analytics and educational data mining (EDM).
Learning analytics could be defined as the use of educational data to improve learning.  Course facilitator George Siemens (TEKRI, Athabasca University) puts it this way:
Learning analytics is the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs”

Online learning produces a wealth of student data, such as time spent on certain modules, number of logins, number of posts on forums and their social interactions with other students and tutors.  Academic institutions can use these data to improve learning.  For example, they can provide an “early warning system” and predict which students are likely to fail their exams.  These students could then get extra support (McFadden & Dawson, 2010).  By coupling learning data with socio-economic data and demographics, predictions about student success can be made.  Purdue University’s Signals Project is a flagship case in this regard.

Recommender systems, such as used by e-commerce firms as Amazon are regularly mentioned as one of the potential applications of learning analytics.  For example, based on the sources accessed or links in the social network, students could get recommendations about potentially interesting articles, blogs or people.

Looking for meaningful patterns in large sets of educational data is called educational data mining.  Learning analytics, however, includes using these data to intervene in the learning process, like altering the course content, the provision of support or the use of tools.

 Siemens, 2010

Learning analytics could (should) also be student-centered.  This means that students could be granted access to course data. For instance, they see how much time they’ve spent on various course activities and compare it with their peers.  The question what students want generated discussion on the course forums.  The idea, outlined by John Fritz in his presentation was that students take more responsibility for their own learning and strengthen their meta-cognitive abilities.  They could get access to the data, but it would be their responsibility to interpret it and act upon it.  However, most institutions are still in the phase of collecting heaps of data and analyzing them, without really predicting and modeling behavior, or using it to optimize learning.

“Institutions can’t “absolve” students from “at least partial responsibility for their own education. To do so denies both the right of the individual to refuse education and the right of the institution to be selective in its judgments as to who should be further educated. More importantly, it runs counter to the essential notion that effective education requires that individuals take responsibility for their own learning” (p. 144)  

Vincent Tinto, Leaving College: Rethinking the causes and cures of student attrition (1993)

Interesting discussion focused on the issue of distributed analytics.  It is easier to collect data when all student activity is concentrated in one platform or Learning Management System (LMS).  However, when students are stimulated to use a variety of tools, sources and interaction platforms, gathering meaningful data becomes more difficult.  A second issue is the discussion of privacy, in particular when other students also get access to the data.

My first impressions on the MOOC are overwhelming, chaos and quality.  The amount of e-mails and forum posts is staggering and different discussion are taking place simultaneously.  However, it is not really the purpose of a MOOC to participate in everything but rather to be selective.  In that way, a MOOC is a great way to get lectures, information and feedback of some of the leading researchers in the field.  You are stimulated to read the materials and try to make sense of it at your own pace and on your own knowledge level.  A next step is then to create something (like a forum post), share it and get into contact with “likeminded souls”.  We’ll see how that plays out.

What a MOOC is like

A MOOC is a Massive (in various degrees of massiveness), Open and Online Course.  One MOOC has started this week on Learning Analytics & Knowledge (LAK11).  Another one, on Connectivism & Connective Knowledge (CCK11) is starting next week.  MOOCs are offered in various domains from education to ICT to biology.  MOOCs are definitely on the rise.  
MOOCs, what are they and where do they come from?

In 2008, Stephen Downes was teaching a class on learning theory at the University of Manitoba. Rather than limit access to his lectures to the 25 students registered for his course, he allowed the general public to attend virtually. The result was that more than 2300 people participated in his course.

First, they are massive.  They tend to attract hundreds or, for some courses, even more than thousand of participants, although some may participate only passively or drop out before the end of the course.
Second, they are open.  This means that they are free, that there are no entry requirements, that there is no formal trajectory that needs to be followed and that all activity is voluntary.  Besides, there is also no accreditation, apart from the appreciation from fellow learners. Taking a course for credits is sometimes offered optionally for a fee. The courses are very participatory, without fixed assignments, but with an invitation to engage in discussions and build networks.  
Finally, they are online.  All activity takes place online, usually through a combination of synchronous (online lectures, discussions etc. using software platforms through Elluminate) and asynchronous activity (blog posts, forums, e-mail newsletters, twitter messages, status updates).   Software programmes like Moodle and tools like Netvibes allow keeping track of all the activity going on.  
Below a short video from Dave Courmier on the essence of a MOOC.

Are they successful?  I’m trying it out, and keeping you posted.