HEA Bioscience pedR event

The HEA Centre for Biosciences ran a session on pedagogic research at University of Leicester on 24 March 2009. Our twittering fraternity were out in force (@cjrw, @ajcann, @cwells1, @jon_scott) were all there and I am sure there will be other blog entries from some of them on the meeting. Unfortunately you will only get half the story here, as I had to leave just as it was getting interesting to collect the kids.

We had presentations on a wide range of topics, from the mysteries of social science research methodologies by Bonnie Green, with surely some made up terms in there (bemtology anyone?!) to case studies of practitioners looking at their own work in pedr in the biosciences. We tagged the meeting (#cfbres on delicious and twitter) and Alan invited the other participants to join our community of practice online.

As with most face to face events, the main benefit was in the networking and talking with people at the meeting. One of the feelings I was left with, was how can we harness this community of practice to greater effect? And what effect do we want to have? Is it solely to improve the teaching and learning for our students, or is part of it to improve the status of teaching and learning for ourselves?

There were two other home truths that beginning to dawn on me. Firstly, we need to stop moaning about educational research being impenetrable and just get on and get to grips with it (Paul Orsmond thought that we could do it if his second year undergraduates could!) and secondly, we need to write some grants and get in some money.  Unfortunately end-of-term-itis has hit and I need to make a calendar note to come back and read this post and put these into action when vim and vigor return!

QR codes starting to make sense

photo credit: Flickr derivadow

We had our first online meeting with the other partners involved in the JISC LTIG QR code project today. It was good to put some names and faces together with institutions (even if the faces were only there for while until we had turn the video off!).

We mainly reported that following up on the substantial number of projects that we thought we could do had been a little dispiriting in that we had met with a number of barriers to adoption. it was good to know that other people were sharing some of our problems and that Andy Ramsden was keen for us to document barriers as much as the successes (phew!). We will definitely write these experiences up as one of our three case studies.

The session gave us some good contacts to follow up and some ideas to inspire us. We will talk to Graham at Sheffield about our tentative ideas for using QR codes in museums. We liked the idea of an audio induction linked to a floor plan and are thinking about if we could do this within our School of Biological Sciences for first year students arriving in October. A treasure-hunt style tour could direct them to the main places of the three buildings that the School works within, showing them the locations of the main teaching labs, departmental offices for handing in work and the open access computing facilities.

Another idea resulting from the session was for us to think about working with a social media postgraduate student we know to promote the use of QR codes via a charity event she is involved in.

Alan and I suggested that we start to use a tag (on blogs/twitter/delicious) for the project, to bring the various discussions together, so #jiscqr (twitter RSS, delicious RSS, blog rss) was born and is now in use.

We are now looking forward to kicking off some new projects and meeting everyone face to face in June.

Data-intensive science

A really interesting post, especially given it’s source, Prof Kell is the Chief Exec of BBSRC. I agree that data mining or processing has become something in it’s own right. Makes me think about ‘everything is miscellaneous’ and how we need to process on the out. But will scientists have the foresight to do this processing in an open and distributed online way?

 

 

The fourth paradigm of scientific knowledge generation – data-intensive science

via Professor Douglas Kell's blog by DKell on 3/17/09

We arguably recognise three main approaches to generating new knowledge: experimental and theoretical research are classically the first two, while more recently computer simulations of natural phenomena (and of engineering artefacts) have contributed a third. Now Bell, Hey and Szalay have proposed a fourth – data-intensive science.

Like any other major shift in scientific thinking – as Kuhn’s re-coined term ‘paradigm’ is intended to signify – data-intensive science both represents and is driven by a change in the scientific landscape. It is not just a re-statement of the significance of data-driven rather than hypothesis-dependent science. In this case, it is the ability of modern instrumentation to generate data at rates 100-1000-fold that of the devices they are replacing. In biology, an obvious set of examples is represented by the so-called next-generation sequencing methods for nucleic acids. Mardis and Shendure & Ji give recent reviews of these.

As the need for cost-effective computation on non-specialist hardware developed, Beowulf clusters of commodity PCs became a de facto standard in University laboratories and elsewhere. However, these were designed more for parallel computation than for accessing and analysing huge datasets, and rarely included database software. As data volumes grow to petabytes and beyond, it becomes infeasible (for reasons of bandwidth) to transport such large amounts of data frequently over a Grid or the interweb (or even the Cloud), and localised processing is to be preferred. A team of collaborators including Szalay have consequently realised a computer architecture, the Graywulf (named after Jim Gray), suitable for data-intensive science. It won the award for best storage solution at Supercomputing08. Bell and colleagues gives an example using a Graywulf of the execution of a query over a large astronomical database, the Sloan Digital Sky Survey, that took 12 minutes (compared with 13 days on a non-parallel database). We have exploited other parallel architectures such as the Condor pool, but as with the Beowulf they are unsuitable for very large datasets.

As mentioned in my first blog, Sydney Brenner has remarked (Nature, June 5, 1980) that “Progress in science depends on new techniques, new discoveries, and new ideas, probably in that order.” Bell and colleagues conclude in a similar vein: “In the future, the rapidity with which any given discipline advances is likely to depend on how well the community acquires the necessary expertise in database, workflow management, visualization and cloud computing technologies.” Workflows (e.g. using Taverna) for data integration have proved useful for many purposes, including for systems biology and for bio-statistical analyses of microarray data. Big databases with fast access and information visualisation look like being the next important areas for biology.

• Bell, G., Hey, T. & Szalay, A. (2009). Beyond the data deluge. Science 323, 1297-8
• Kell, D. B. & Oliver, S. G. (2004). Here is the evidence, now what is the hypothesis? The complementary roles of inductive and hypothesis-driven science in the post-genomic era. Bioessays 26, 99-105
• Kuhn, T. S. (1996). The structure of scientific revolutions. Chicago University Press, Chicago
• Li, P., Oinn, T., Soiland, S. & Kell, D. B. (2008). Automated manipulation of systems biology models using libSBML within Taverna workflows. Bioinformatics 24, 287-289. Full text
• Li, P., Castrillo, J. I., Velarde, G., Wassink, I., Soiland-Reyes, S., Owen, S., Withers, D., Oinn, T., Pocock, M. R., Goble, C. A., Oliver, S. G. & Kell, D. B. (2008). Performing statistical analyses on quantitative data in Taverna workflows: an example using R and maxdBrowse to identify differentially expressed genes from microarray data. BMC Bioinformatics 9, 334. Full text
• Mardis, E. R. (2008). Next-generation DNA sequencing methods. Annu Rev Genomics Hum Genet 9, 387-402
• Shendure, J. & Ji, H. (2008). Next-generation DNA sequencing. Nat Biotechnol 26, 1135-45
• Simmhan, Y., Barga, R., Ingen, C. v., Nieto-Santisteban, M., Dobos, L., Li, N., Shipway, M., Szalay, A. S., Werner, S. & Heasley, J. (2009). GrayWulf: scalable software architecture for data intensive computing. 42nd Hawaii International Conference on System Sciences, 1-10
• Sterling, T. L., Salmon, J., Becker, D. J. & Savarese, D. F. (1999). How to Build a Beowulf: A Guide to Implementation and Application of PC Clusters. The MIT Press, Cambridge, MA
• Ware, C. (2000). Information visualization. Morgan Kaufmann, San Francisco
• Wedge, D. & Kell, D. B. (2008). Rapid prediction of optimum population size in genetic programming using a novel genotype – fitness correlation. GECCO 2008 (M. Keizer et al., eds), 1315-1322

Livescribe: a new way to take notes?

credit: Amit Gupta (flickr)

This is one of those bits of kit I’ve seen around in a few places recently, MacWorld 09 awards, I saw that Howard Rheingold bookmarked it on delicious, but it wasn’t until I saw Michael Wesch tweet about his use of it that the penny dropped.

Livescribe Smartpen is a pen that you can use to take notes which also records what you are listening to. It has a camera under the nib and is triggered to record by using special note paper (you can print your own for free or buy the expensive notebooks from livescribe!). The cool part comes when you connect the pen to a computer and upload the recoding. It produces a flash movie of your handwritten scribble which is clickable. Click on a section of the notes and you get to listen to the part of the recording you made whilst you were taking those notes. What’s more you can share these notes online (as Micheal Wesch did), in a livescribe community, or presumably anywhere you can embed flash movies.

One of the main problems of recording lectures has been that an hour’s worth of talking is a lot to wade through if you can’t understand what you wrote on page 3 of your notes. This provides a quick way to skip to the exact part of the recording you need, listen again and make some sense of what you heard. The notes are searchable too. For non-native english speakers, or dyslexics, this could also help them to understand their own notes after the lecture.

Sharing your notes online is a really interesting area, and I wonder how many of the students who have already shared their work have thought about whether they have or need their lecturer’s permission to publish their lectures online?

I think using one of these pens would make me think more carefully about how I took notes, perhaps drawing more diagrams and making short bullet points and notes to myself to listen again. I like the idea that you get double benefit from taking notes this – first, the act of writing notes helps me to remember and listen actively to what is being said, and second, I get an electronic copy of my notes as back-up that I can move around digitally without having to type them up later.

I wonder how many students or teaching staff will weigh up the cost of a netbook (£200) against the cost of a livescribe pen (£129)? Carrying a 37 g pen is going to be easy on the pocket in other ways too.

reflecting on eVoting

Following the launch meeting of the EVAF 4ALL JISC project in Edinburgh last week, I got to thinking about our uses of eVoting. The EVAF 4ALL offers two important features:

1. It will allow students to track their own progress in answering voting question, thereby giving the potential for a large amount of personalised feedback.
2. It will allow staff to review the questions they have asked and find out which ones are potentially useful for future use. The system allows the identification of questions which are ‘easy’ (everyone gets it right), banana skins (where the majority all get the same wrong answer, useful for correcting misunderstandings of key concepts) and scatter gun answers (no-one knows the answer and there is a spread of responses, useful for using in peer instruction scenarios).

Electronic voting encourages interaction and engagement in the lecture, which is just another way to reform lectures from one way transmission of information to a meaningful conversation. Students are told to expect to assimilate content OUTSIDE the lecture and look forward to interaction and understanding during the hour lecture period instead.

Surely this is something we should be aiming for and gives us a reason to get up in the morning?

Will electronic voting tick all the boxes on our pedagogic wish list?

• students reading content outside the lecture in their own time
  
• better engagement in the lecture
• direct personal (automated) electronic feedback on progress
• staff reflecting on student understanding and changing their teaching to address any issues raise