Wednesday, January 30, 2013

One of those days

Fail Got into the office this morning and turned on the computer. No Internet. Ethernet wouldn't connect.

I like to think my IT use is fairly resilient but I can achieve little in my job on the average day without being online.

After a few meetings I managed to coax a little (slow) wifi access out of the system. But I couldn't send emails because SMTP didn't like the wifi.

The blank ink ran out and the replacement cartridge was the wrong one so I couldn't print.

Today was a bit of an eye opener.

Monday, January 28, 2013

Do you wanna make tea at the BBC?

The Clash In my career I am fortunate to have taught some of the very best students in the UK, a few of who have already gone on to far surpass my career achievements. But that's not always the case.

It's not uncommon that a student asks me for an reference - often at the last minute in a terse email - for a position that I know from experience they have little or no hope of getting. I have no wish to discourage student ambition, but this causes me a lot of difficulty. The best students are well aware of their capabilities and potential - but less gifted students often are not. Fueled by rising panic, they apply blindly for incredibly competitive positions their academic records and c.v.'s mean are well beyond their capacity to achieve.

If I have the luxury of sitting down with the student and discussing careers calmly with them (i.e. not the-deadline-is-today-because-I-left-it-too-late), I approach this problem along Plan A (optimistic targets) and Plan B (realistic experience collection) lines. I don't want to discourage any student, but I have real moral dilemmas when second rank students don't have an accurate assessment of their prospects. How should I advise them when I "know" they're being over ambitious? Is is my role to act as gatekeeper? What do you do in such circumstances?

Sunday, January 27, 2013


Embassytown For some reason, I've been putting off tackling China Miéville, and Embassytown has been sitting on my shelf for a year. I wrongly assumed that this was some sort of sequel to The City and The City, which it isn't. It didn't take me more than a couple of chapters to realise I shouldn't have left it so long.

The underlying plot device of Embassytown is linguistics. While this isn't unique, it was new for me. This is far from my comfort zone, but the playful way Miéville approaches the plot disarms much of the potential barrier, for example, dreaming up useful neologisms - such as floaking - I useful term I can see me applying to students and colleagues alike. It was good to read sci-fi not completely sequestered by tech (although I did feel the sub-plot about traveling the Immer is both unnecessary and abandoned in the latter part of the book). In general, the flaccid second half of the book is repetitive and about 100 pages too long.

So is Miéville a great writer, the equivalent of Philip K. Dick? No. He rivals Dick's imagination but lacks the discipline. But he's still one of the best current sci-fi authors around, and I won't be leaving it long before ploughing through his back catalog.

Wednesday, January 23, 2013

HEA STEM Retention and Success

Higher Education Academy All (i.e. snow), being well, when this is published I'll be on my way to the HEA STEM Summit on Skills in Mathematics and Statistics in the Disciplines and Tackling Transition in Durham today and tomorrow. Or not, depending on Cross-Country Trains.

What are we going to talk about? Well, the format is an unconference, so no-ones knows, but my money's on maths, statistics and transition to HE. We'll see. There's a blog. Is there a hashtag? We'll find out.

Tuesday, January 22, 2013

Measuring mumbo jumbo

"Leaders of the scientific community encourage scientists to learn effective science communication, including honing the skill to discuss science with little professional jargon. However, avoiding jargon is not trivial for scientists for several reasons, and this demands special attention in teaching and evaluation. Despite this, no standard measurement for the use of scientific jargon in speech has been developed to date. Here a standard yardstick for the use of scientific jargon in spoken texts, using a computational linguistics approach, is proposed. Analyzed transcripts included academic speech, scientific TED Talks, and communication about the discovery of a Higgs-like boson at CERN. Findings suggest that scientists use less jargon in communication with a general audience than in communication with peers, but not always less obscure jargon. These findings may lay the groundwork for evaluating the use of jargon."

Measuring mumbo jumbo: A preliminary quantification of the use of jargon in science communication. Public Understanding of Science, 21 January 2013 doi: 10.1177/0963662512469916

Monday, January 21, 2013



Time on Task

Time Since becoming a devotee of Graham Gibbs a couple of weeks ago, I've been thinking about time on task, so another paper from Ray Junco is of interest.

  • Students (and, I'd be willing to bet staff) over-report time on task.
  • Anecdote is not a substitute for data.

Comparing actual and self-reported measures of Facebook use. (2013) Computers in Human Behavior. 29: 626–631
Numerous studies exist examining how college students use Facebook and how this affects aspects of their college experience; however, all of these studies have relied on self-report measures of Facebook use. Research in other areas of human behavior has shown that self-report measures are substantially inaccurate when compared to actual behaviors. This study provides the first test of the criterion validity of measures of Facebook frequency by comparing self-reported time spent on the site and number of logins against actual usage as measured by computer monitoring software. A sample of 45 college students installed software that monitored their computer usage for 1 month. There was a strong positive correlation between self-reported and actual time spent on Facebook; however, there was a significant discrepancy between the two. Students spent an average of 26 min (SD = 30) per day on Facebook, significantly lower than the average of 145 (SD = 111) minutes per day obtained through self-report. There was a moderate relationship between number of logins and actual time spent on Facebook. Although there are some limitations of monitoring computer usage, researchers are encouraged to attempt to relate their self-report measures to actual behaviors in order to improve external validity.

Friday, January 18, 2013

Why does commenting suck?

Google Captcha In response to repeated complaints for readers of this blog, I changed the comments settings here yesterday, removing the anti-spam captcha. Immediately (within minutes), there was an upsurge in machine-generated spam comments. I'm currently figuring out the best way to deal with this and whether I can feasibly leave the captcha off. (Lack of the Akismet spam filter is one of the few ways Blogger still lags behind WordPress currently.)

I have always attributed comment spam to simple commercial motives, but interesting remarks by Clay Shirky reported by David Weinberger have made me think again about the motivations behind "spam".

Thursday, January 17, 2013

The long and the short of it

Optical illusion Deep down inside me something curls away from finding out why I write, in fear that whatever "gift" I occasionally seem to possess will be lost if the light hits it. On the surface, I can reel off a list of reasons as long as your arm.

Some days this blog is a multimedia scrapbook of things that interest me, other days it is a noticeboard, but most often it is a notebook where I jot down things I think I may later want to remember. (I refer to these notes several times a day on average.) Occasionally my writings here delve a little deeper as I try to work through some temporary existential crisis or feel the need to sound off about some egregious wrong that needs illumination.

On MicrobiologyBytes I deliberately try to abstract and explain the content of scientific papers in an accessible form. On AoB Blog we highlight content from Annals of Botany journals, interspersed with slightly longer commentary articles from a range of commentators. I infrequently write these posts, partly because I am not a plant scientist, but also because it's easy to find an excuse not to - such as the infallible "too busy".

This week, two interesting events coincided. The LSE Impact of Social Sciences blog published my article on MOOCs which they had commissioned (in the sense of not paying), and I also read Why Content Goes Viral: the Theory and Proof. I was quite proud of my "heavyweight" 1000+ word MOOC effort, although I don't believe that the technical architecture of blogs is usually the right place for true long form writing. But the combination of these two recent experiences has promoted me ask myself if I could spend my limited time more wisely.

I can't afford to lose the notebook aspect of this blog so it is likely to continue in much the same way as previously, but occasionally I feel the need to be more discursive. Specifically, I am asking myself whether the limited time I have available for MicrobiologyBytes these days would be better spent as less frequent longer format articles rather than the very short pointers I put there now. In academic terms, should I devote my long form efforts to more "worthy" channels, i.e. more conventional publication? That risks siphoning off my limited supply of Cognitive KarmaCard points I could spend on the grant applications and formal papers my line managers crave. More importantly, I worry that infrequent publication puts me at risk of stopping publishing altogether, particularly with a hectic few months teaching coming up where time to write is going to be under particular pressure, whereas hurried moments scribbling can be squeezed in the gaps. It is most important to me that I maximize the value I am able to add to what I write about. The thought of content going viral and reaching a wider audience could be part of achieving that aim.

So here's the plan. This blog - steady as she goes, although I will try to focus on longer format pieces occasionally. MicrobiologyBytes - I'm thinking about a weekly longer article in the model of the admirable Ed Yong. This will be topped up by quick hits pushed through from the MicrobiologyBytes Google+ page to the blog and on to Twitter and Facebook. But that's not going to happen for a couple of months, until the teaching pressure dies down again. AoB Blog is the difficult one. I need a sit down for a strategic chat with my colleagues about the road ahead.

In general, I'm looking to play the longer game rather than chasing the validation of immediate gratification. But this requires serious planning and discipline because one thing I am convinced about above all other - the value of blogging to me is too high to risk damaging it.

Wednesday, January 16, 2013


MOOC Try as I might, I can't get ways from MOOCs this week. We had a fascinating discussion at our local PedR meeting on Tuesday. OK, it was more I talked, they tried to get a word in edgeways, but I get animated when the subject comes up. I hope the outcome of that particular discussion will be fruitful, and it left me feeling in a more positive state of mind than when I was asked to write about MOOCs for the LSE Impact of Social Sciences blog, where this post has just been published.

After the Gold Rush

I was hoping for replacement
When the sun burst through the sky.
Neil Young

MOOCS, Massive Online Open Courses, is the most hyped educational buzzword of the last year. Alan Cann reflects on what still needs to be done after the hysteria dies down. You can read more about his adventures in the land of MOOC at:

Who put the mooc in the mooc, mooc, mooc, mooc, mooc?
MOOCs have had a reasonably long history, although the term itself is newer than the idea. In 2001 and 2002 the William and Flora Hewlett Foundation in the USA funded the Carnegie Mellon University Open Learning Initiative and the MIT Open Courseware project which made course materials from these institutions freely available online under Creative Commons licences. The term MOOC was invented by David Cormier and Bryan Alexander at the University of Manitoba in Canada in 2008. In 2011 MIT OCW morphed into MITx and in 2012, MIT and Harvard joined together to form edX. Not wishing to be left out, a group of UK universities headed by the Open University announced Futurelearn late in 2012.

Show me the money
The course that really grabbed widespread attention was the Stanford University Artificial Intelligence course by Peter Norvig and Sebastian Thrun in the autumn of 2011 which attracted 160,000 registered students. 20,000 from 190 countries completed the course and received a “statement of accomplishment” from Stanford University [see Update below]. On the back of this, Thrun spun out the private company Udacity in 2012 and has subsequently raised over US$15 million in venture capital for the venture. Stanford professors Andrew Ng and Daphne Koller established Coursera shortly after, and have now attracted over US$22m venture capital. This is not a cottage industry. Rather, it reflects the market driven system of higher education in the USA, and increasingly, in the UK.

The Great Schism
The term MOOC reflects the educational philosophy of the early pioneers. Although free (as in free beer) is not part of the etymology, this is implicit, reflecting the origins of the movement in open source software and online distribution. While the offerings of private companies such as Udacity and Coursera remain freely available at the point of use, these are free as in free speech (which has to be paid for). As is the way with Internet companies, business models during the early rounds of capitalization consist of plentiful smoke, mirrors and optimism. Realistic business models are slowly beginning to emerge (WSJ, 2013). Udacity led the way by offering to match “graduates” of its computer science courses with selected employers, including Google, and more recently, by developing employer-sponsored courses with partners such as Microsoft, NVIDIA and Wolfram. Coursera is developing similar employer-matching services and recently announced that it will begin charging students $30 to $100 for “verified certificates”.
More importantly, the privateers have departed from the original conception of MOOCs as “open”, meaning that there is unrestricted access to course materials under Creative Commons licences. The development of early MOOCs was strongly influenced by connectivism, based on concepts of networked knowledge and social learning (Siemens, 2008). They were deliberately platform agnostic in contrast to the closed platforms developed and trumpeted by commercial players. To underline this distinction, Stephen Downes is credited with proposing the terms "cMOOC" and "xMOOC" to distinguish the two strands evolving from the early origins.

Is this a bubble I see before me?
Clearly it is, as defined by such large speculative cash inflows into non-profit making ventures. Although there have not yet been any public MOOC provider flotations following the ill-fated Facebook IPO, those of us who have been around this particular block before are haunted by the expensive and embarrassing failure of UKeU at a cost to the public purse of over £50m. This time around governments on both sides of the Atlantic are happy for private companies to bear the risk, and presumably to reap any future gains. Massive online courses imply global audiences, probably to the detriment of overseas student recruitment by public universities. Amazon and Starbuck illustrate how well successive UK governments have been able to recoup taxation on UK economic activity carried out by multinationals.

Never mind the quality, feel the width
No UK university and few schools now operate without an online virtual learning environment and no-one in their right mind doubts the value of online delivery in leveraging the efforts of academic staff and minimising costs. In spite of years of experience, the thorny issue of measuring quality in online education (and in higher education in general, Gibbs, 2010), remains substantially unresolved. Although there is much to be gleaned from the smorgasbord of free courses that online providers offer, irate blog posts from many users show there is still much to be learned in this field in terms of both pedagogy and “customer” service.
Udacity has developed an in house platform consisting of live mini-lectures via screen capture videos with integrated MCQs. By focussing on a limited range of courses spanning maths and computer science and by developing in house Udacity has managed to present a fairly uniform interface to users (or students, if you will). Coursera faces a much bigger problem because it spans a wide range of content including humanities and arts courses (Knox et al, 2012). In response, it has developed an online peer grading model, although this has received criticism due to game playing and inappropriate behavior by some course participants. The bigger problem Coursera faces is that its courses are poorly-adapted versions of content originally developed elsewhere by its partner institutions, lured in by fears of missing the boat and by Coursera’s promised revenue sharing model.

MOOCs as cargo cults
Far from the hype that MOOCs will replace traditional universities, anyone who studies the evidence soon sees that MOOCs are augmentation rather than replacement of formal educational models. It is fitting that universities should contribute to improving public knowledge by offering free online courses. But connectivism in particular is a step too far for most learners - particularly less experienced learners - who fail without the scaffolding provided by traditional degree structures and support. Across the board completion rates are low, typically less than 10%. While this may be a consequence of free (as in disposable), does it matter why people fail, only that they do? Doug Holton has notably skewered the MOOC hype as a cargo cult which fails to understand how education works (Holton, 2012). MOOCs are yet another example of the Innovator’s Dilemma - that new technologies displace rather than replace earlier technologies (Christensen, 2011). Think newspapers - radio - television - Internet. Think private tutors - public universities - Internet. MOOCs are here to stay. But we all need to calm down and carry on. And a more thoughtful approach to pedagogical effectiveness wouldn’t hurt either.

Christensen, C. (2011). The Innovator's Dilemma: The Revolutionary Book That Will Change the Way You Do Business. HarperBusiness. ISBN 0062060244.
Daniel, J. (2012). Making Sense of MOOCs: Musings in a maze of myth, paradox and possibility. Journal of Interactive Media in Education, 3.
Gibbs, G. (2010). Dimensions of quality. York: Higher Education Academy.
Holton, D. (2012)
Knox, J., Bayne,, S., MacLeod, H., Ross, J. and Sinclair, C. (2012) MOOC pedagogy: the challenges of developing for Coursera. ALT-N
Siemens, G. (2008). Connectivism: a learning theory for the digital age.
WSJ. Online Courses Look for a Business Model. 01 January 2013

Helpful correction from Seb Schmoller:  "The AI course Statement of Accomplishment was not from Stanford University. It was issued as a secure PDF of some kind, signed by Sebastian Thrun and Peter Norvig, and headed “Introduction to Artificial Intelligence”. It has the following disclaimer: “This online offering of Introduction to Artificial Intelligence does not affirm that you were enrolled as a Stanford student in any way; it does not confer a Stanford grade; it does not confer Stanford credit; and it does not confer a Stanford degree or certificate.”"

Tuesday, January 15, 2013

Why I didn't sign up for #oldsmooc

xxx I would like to have signed up for the OU's learning design MOOC, but I have a list of reasons why I didn't:
  • I'm trying to be sensible about the MOOCs I register for. Come next week I'll be participating in three and another one would be too much. Way too much.
  • 10th January to 13th March 2013 is very bad timing for me, my busiest time of year. I couldn't commit to anything that long and that structured (3-10 hours a week or 10 weeks) as I know I would not have any chance of actively participating in it.
  • I've tried to love learning design, really I have. But it just doesn't float my boat. I prefer teaching to designing teaching. Before you comment on that, it means I'm an action research kinda guy.
  • Cloudworks. I'm not resident there and I don't find it attractive. You may well feel differently but I don't have the time for another destination at present. If it ran in Google+ I wouldn't be able to stay away.

So y'all have fun now and let me know how it goes.

Why email rules the DarkSocial

"Email has been found to be an important personal information management (PIM) tool in the personal archiving of documents and in task management (Whittaker et al 2006), and studies within information science note that an increasingly popular strategy in PIM is actually “to do nothing” (Bruce et al 2004). This is normally because saving and filing information can prove cognitively onerous..."

Macgregor, G., Spiers, A., and Taylor, C. (2011) Exploratory evaluation of audio email technology in formative assessment feedback. Research in Learning Technology, 19(1).

Sunday, January 13, 2013

The Fast Diet

The fast Diet Although I don't agree with the term "diet" used to label this approach to health - it's a lifestyle rather than a diet - I have been following the advice in this book for the last 5 months and it has had a major effect positive on my health. I would urge you to consider doing the same.

Thursday, January 10, 2013

Coursera Computing for Data Analysis, Week 2

Coursera Confusion surrounds the week 1 programming assignment (which was just a set of MCQs). At least the instructor is trying his best on the communication front:
"Unfortunately, my attempt to fix Question 9 last week caused more problems and confusion than it fixed. Therefore, I've decided to delete the original Question 9 from the Quiz. Now the Quiz for the first Programming Assignment only has 9 questions total instead of 10. I have adjusted the grading for this Quiz and have issued a regrade. If you have already taken this Quiz, you should NOT have to take it again.")

It's clear the Coursera does a crap job of road testing units before they offer them to students. Anyhow, on to week two.
"A few facts about the class so far. There are currently 40,211 people enrolled in the class and about 31,000 active users in the past week. There were about 14,000 who submitted the Week 1 Quiz and about 1,300 people participating in the forums."

The course was a bit rough this week, (Control structures, Functions, Loop functions, Debugging) - full on programming, no statistics. I'm going to stick it out for for one more week because I want to get to week 3 (Simulation, Plotting, Visualizing data, Principles of data graphics). After that I will bail because this module is about programming not stats so it doesn't really fulfill my learning objectives, and because I'm away the following week. Also, Coursera Data Analysis and Google Advanced Power Search both start that week and they will take up all my time.

Wednesday, January 09, 2013

Google Advanced Power Searching

Google MOOC
Of all the MOOCs I have participated in, Google's free online Power Searching course was by far the best. The search interface has changed over the past few months and I don't feel I'm getting as much out of it as I used to, so hopefully this "advanced" course will be even better. Starts January 23rd for two weeks(?), sign up now.

Tuesday, January 08, 2013

The Information

The Information Among my holiday reading was James Gleick's The Information. Blurb: "a chronicle that shows how information has become the modern era’s defining quality".

Ever since I read Everything Is Miscellaneous, I have been looking for another book which would have a similar impact on me in terms of explaining and clarifying the digital world. The Information is not  that book. Not unexpectedly for an English graduate, there's a book in here about linguistics struggling to get out.

I was very impressed with the first few chapters which explore the significance of coding information. I was particularly interested in the discussion of the movement from oral traditions to written information, and I originally intended to do this review as a talking head video to camera in homage to that - but hey, who's got time to fiddle about with video (or watch it) when I can just tap out notes? Soon after that the book starts to get bogged down in excessive extraneous detail, for example too much biographical information about Charles Babbage and Ada Lovelace, too many anecdotes about the telegraph. I enjoyed this chapter a lot, but this book is not the place for it because it detracts from the mass market mission statement. Subsequent chapters plunge into the mathematical basis for information theory and become increasingly arcane (to a non-mathematician like me) before finally wandering off into the mists of quantum physics. Chapter 14 gets back on track with the best discussion about Wikipedia I have read, but ultimately the book fizzles out in an insipid fog.

Ultimately, this is a very well written and a disappointing book, around 100 pages too long. From this we learn that a decent editor is worth many thousand words.

Sunday, January 06, 2013

Loss aversion

Loss aversion I suffer from loss aversion - technically defined as disproportionate anxiety about losses. I've always felt that playing "safe" is a better option than being reckless. But loss aversion distorts your world view and makes you draw the line in the wrong place. This is a bad thing, as Tim Hartford points out.

This year, I'm planning on being slightly reckless.

Friday, January 04, 2013

Bloody amateurs?

HEA report Traditionally, HE teachers in the UK have been amateurs, in the sense that they are not trained teachers. Is this a good thing? If you believe in research-led teaching rather than simply reading from a textbook, it has to be. But the sad reality is the amateur model came from a time which was very different to the pile-it-high model of HE which now operates. With the system at breaking point, it cannot continue much longer. Professionalization of HE teaching is an inevitability.

HEA recently published a report on Impact of teaching development programmes in higher education. This is going to happen whether you like it or not. HEA is currently asking for comments on the report. So if you care about the future of UK HE teaching, get off your lardy post-Christmas ass and get involved.


Thursday, January 03, 2013

Facilitating productive use of feedback in higher education

I don't always find the research literature on student feedback very helpful in formulating practical strategies, but this meta analysis of feedback research is clear, sensible and well worth a read:

Anders Jonsson (2012) Facilitating productive use of feedback in higher education. Active Learning in Higher Education 10 December 2012. doi: 10.1177/146978741246712
Although feedback has a great potential for learning, students do not always make use of this potential. This article therefore reviews research literature on students’ use of feedback in higher education. This is done in order to find answers as to why some students do not use the feedback they receive and which factors are important in influencing students’ use of teacher feedback. Findings show that utility is not only a key feature for students’ use of feedback but also that some factors, such as lack of strategies for productively using feedback or lack of understanding of academic discourse, may hinder students’ possibilities to use the information formatively.

Wednesday, January 02, 2013

Let the MOOCing restart

Coursera After a break, I'm starting two new Coursera MOOCs this month:
  • Computing for Data Analysis: In this course you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment, discuss generic programming language concepts as they are implemented in a high-level statistical language. The course covers practical issues in statistical computing which includes programming in R, reading data into R, creating informative data graphics, accessing R packages, creating R packages with documentation, writing R functions, debugging, and organizing and commenting R code. Topics in statistical data analysis and optimization will provide working examples.
  • Data Analysis: This course will focus on how to plan, carry out, and communicate analyses of real data sets. While we will cover the basics of how to use R to implement these analyses, the course will not cover specific programming skills.
While I may not have time to complete either of these courses once my teaching starts at the end of the month, I hope to pick up some useful skills along the way. Previously, I found it a good idea to set personal learning objectives for MOOCs as this helps with engagement and ongoing commitment. For both of these courses, my planned learning outcomes are fairy straightforward:
  • To improve my statistical knowledge and ability.
  • As I tend to use R in bursts rather than constantly, to revise my existing/previous R skill set.
  • To improve my knowledge of R and related software such as RStudio. 

Computing for Data Analysis, Week 1:
This is coming (as advertised) from a programming perspective rather than a statistics/R angle. I'll have to see how this goes for a couple of weeks. At the moment, I suspect I won't be recommending this to my students or colleagues. Based on Week 1, I have a feeling I won't be completing this course as it doesn't mesh with my desired learning outcomes.