O'Really?

March 23, 2021

Join us to discuss learning sciences for computing education on Monday 12th April at 2pm BST

Scientist icon made by Eucalyp via flaticon.com

Learning sciences aims to improve our theoretical understanding of how people learn while computing education investigates with how people learn to compute. Historically, these fields existed independently, although attempts have been made to merge them. Where do these disciplines overlap and how can they be integrated further? Join us to discuss learning sciences for computing education via a paper by Lauren Margulieux, Brian Dorn and Kristin Searle, from the abstract:

This chapter discusses potential and current overlaps between the learning sciences and computing education research in their origins, theory, and methodology. After an introduction to learning sciences, the chapter describes how both learning sciences and computing education research developed as distinct fields from cognitive science. Despite common roots and common goals, the authors argue that the two fields are less integrated than they should be and recommend theories and methodologies from the learning sciences that could be used more widely in computing education research. The chapter selects for discussion one general learning theory from each of cognition (constructivism), instructional design (cognitive apprenticeship), social and environmental features of learning environments (sociocultural theory), and motivation (expectancy-value theory). Then the chapter describes methodology for design-based research to apply and test learning theories in authentic learning environments. The chapter emphasizes the alignment between design-based research and current research practices in computing education. Finally, the chapter discusses the four stages of learning sciences projects. Examples from computing education research are given for each stage to illustrate the shared goals and methods of the two fields and to argue for more integration between them.

There’s a 5 minute summary of the chapter ten minutes into the video below:

All welcome. As usual, we’ll be meeting on zoom, see sigcse.cs.manchester.ac.uk/join-us for details. Thanks to this months paper suggestions from Sue Sentance and Nicola Looker.

References

  1. Margulieux, Lauren E.; Dorn, Brian; Searle, Kristin A. (2019). “Learning Sciences for Computing Education“: 208–230. doi:10.1017/9781108654555.009. in In S. A. Fincher & A. V. Robins (Eds.) The Cambridge Handbook of Computing Education Research. Cambridge, UK: Cambridge University Press

May 26, 2020

Join us to discuss blended learning, Monday 1st June at 11am on Zoom

Filed under: education,Uncategorized — Duncan Hull @ 2:41 pm
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7704609288_14d335dd87_cAt our next journal club, on Monday 1st June at 11am, we’ll be discussing blended learning. We’ve picked a subject, but we haven’t picked a paper yet. So, if you know interesting papers on blended learning, post them to the “paper suggestions” channel at  uk-acm-sigsce.slack.com – there are a few suggestions up there already for starters.

If you’ve not got access to the workspace yet, ping me or Alcywn Parker and we’ll add you to the group. Journal Club is part of the Association for Computing Machinery (ACM) Special Interest Group (SIG) on Computer Science Education (CSE) – all welcome!

April 28, 2020

Join us to discuss learning programming languages: Monday 4th May at 11am #sigcsejclub

Filed under: education,engineering,Uncategorized — Duncan Hull @ 10:17 am
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Hieroglyphs_from_the_tomb_of_Seti_I

Hieroglyphs from the tomb of Seti I, by Jon Bodsworth via Wikimedia Commons and the Egypt archive

ACM SIGCSE Journal Club returns Monday 4th May at 11am. The paper we’re discussing this month is “Relating Natural Language Aptitude to Individual Differences in Learning Programming Languages” by Chantel Prat et al published in Scientific Reports. [1] Here’s the abstract:

This experiment employed an individual differences approach to test the hypothesis that learning modern programming languages resembles second “natural” language learning in adulthood. Behavioral and neural (resting-state EEG) indices of language aptitude were used along with numeracy and fluid cognitive measures (e.g., fluid reasoning, working memory, inhibitory control) as predictors. Rate of learning, programming accuracy, and post-test declarative knowledge were used as outcome measures in 36 individuals who participated in ten 45-minute Python training sessions. The resulting models explained 50–72% of the variance in learning outcomes, with language aptitude measures explaining significant variance in each outcome even when the other factors competed for variance. Across outcome variables, fluid reasoning and working-memory capacity explained 34% of the variance, followed by language aptitude (17%), resting-state EEG power in beta and low-gamma bands (10%), and numeracy (2%). These results provide a novel framework for understanding programming aptitude, suggesting that the importance of numeracy may be overestimated in modern programming education environments.

The paper describes an experiment which investigates the relationship between learning natural languages and programming languages and draws some interesting conclusions that provide some good discussion points. Does being good at learning natural languages like English make you good at learning programming language like Python? Do linguists make good coders? We’ll be meeting on Zoom, details will be sent to anyone who registers at sigman2.eventbrite.co.uk

References

  1. Prat, C.S., Madhyastha, T.M., Mottarella, M.J. et al. (2020) Relating Natural Language Aptitude to Individual Differences in Learning Programming Languages. Scientific Reports 10, 3817 (2020). DOI:10.1038/s41598-020-60661-8

 

October 27, 2017

Mirror, mirror on the wall, who is the most viewed of them all?

Filed under: Uncategorized — Duncan Hull @ 6:42 am

Wikipedia is mirror that reflects the world around it. Sometimes the reflections are accurate, other times they get distorted. [1] Either way, we can look at the data in Wikipedia to see which reflections are being looked at the most using powerful analytics tools that are part of the platform.

Two weeks ago, as part of Physiology Friday, I gave a talk examining how biographies of scientists are viewed in Wikipedia, using the crude measure of PageViews.

Melissa Highton from the University of Edinburgh also gave a talk about the Edinburgh Seven, changing the way stories are told and their Wikipedian in Residence scheme.

Our convenor, Andy Mabbett (normally found on a Brompton) gave a talk introducing Wikimedia since our reason for being there was to recruit and train new editors of Wikipedia.

Thanks to the Physiological Society for having us and Anisha Tailor for putting the program together.

References

  1. Samoilenko, Anna; Yasseri, Taha (2014). “The distorted mirror of Wikipedia: a quantitative analysis of Wikipedia coverage of academics”. EPJ Data Science. Springer Publishing. 3 (1). arXiv:1310.8508 doi:10.1140/epjds20

 

December 16, 2015

Review of 2015 @csmcr, anticipating 2016

Filed under: Uncategorized — Duncan Hull @ 11:41 am

23159833313_4f787129da_o2015 has been a busy year in the School of Computer Science at the University of Manchester (@csmcr). Here is a brief summary of some key activities during 2015 that will be of interest to employers and alumni, with a quick look ahead at what is coming in 2016 including:

  1. Industrial mentoring in software engineering
  2. Industrial experience
  3. Competitions & hackathons
  4. Guest lectures
  5. Careers fairs
  6. Research
  7. Alumni
  8. Keeping in touch

Find out more in our December 2015 newsletter.

Hackathons have continued to gain popularity during 2015 here in the UK, with lots of help from Major League Hacking (mlh.io). There are so many events to choose from, it isn’t always obvious which are the best (and why). The Economist published an interesting piece arguing that Hackathons have entered the corporate mainstream and are no longer just for techies. (Hat tip, thanks Antonio Marino) Which sounds about right.

IMHO, generally hackathons are a good thing, especially for students, but there are some thorny issues around Intellectual Property and unpaid labour that many people brush under the carpet. So if you’re organising or attending a hackathon in 2016, make sure you are clear about who owns the IP.

 

July 6, 2009

Fabio Rinaldi on OntoGene

Filed under: Uncategorized — Duncan Hull @ 8:26 am
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Fabio RinaldiFabio Rinaldi is currently visiting Manchester from the University of Zurich, he will be doing a seminar on Monday 6th July, the details of which are below.

Title : OntoGene in the BioNLP shared task and in BioCreative II.5

Speaker: Dr Fabio Rinaldi, University of Zurich

Date: Monday 6th July 2009

Time: 14:00

Location: Lecture Theatre – MLG.001, MIB building

Abstract In this talk I will describe our participation to the BioNLP shared task and the BioCreative II.5 competitions [1]. Our approach is based on a common core: a pipeline of NLP tools and a dependency parser. The adaptation for the BioNLP shared task consisted of suitable input filters and a transformation-based approach which maps syntactic dependencies to event structures. Despite the very simple approach, results were satisfactory (34.78 F-score). The adaptation for BioCreative requires the detection and disambiguation of domain entities, while candidate interactions are proposed on the basis of a simple learning approach.

If time allows I will then describe our approach to finding the ‘focus organisms’ i.e. the organisms in which the experiments have been conducted or which are the source of the interacting proteins. This information is of crucial importance for the correct disambiguation of other entities mentioned in the article.

References

  1. Rinaldi, F., Kappeler, T., Kaljurand, K., Schneider, G., Klenner, M., Clematide, S., Hess, M., von Allmen, J., Parisot, P., Romacker, M., & Vachon, T. (2008). OntoGene in BioCreative II Genome Biology, 9 (Suppl 2) DOI: 10.1186/gb-2008-9-s2-s13

June 19, 2008

Sixteen (Yes 16!) PhD studentships available in Computer Science

Filed under: Uncategorized — Duncan Hull @ 3:45 pm
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EinstongueThe School of Computer Science of the University of Manchester has up to 16 studentships to offer to highly motivated research students who wish to start a PhD in September 2008 (in exceptional circumstances the start date can be deferred until April 2009). The studentships pay tuition fees and a stipend to cover living expenses for 3 years.

In 2008/09, the stipend will be £12940 per year for students who were UK residents in the 3 years before the start of the PhD, or between £10352 and £12940 per year for students who were not UK residents in the same period and cannot demonstrate a relevant connection to the UK. The stipend is expected to rise in subsequent years. Because of conditions associated with this funding, these studentships are open to students eligible for home fees only; this includes UK and EU nationals. (more…)

January 18, 2008

One Thousand Databases High (and rising)

StampsWell it’s that time of year again. The 15th annual stamp collecting edition of the journal Nucleic Acids Research (NAR), also known as the 2008 Database issue [1], was published earlier this week. This year there are 1078 databases listed in the collection, 110 more than the previous one (see Figure 1). As we pass the one thousand databases mark (1kDB) I wonder, what proportion of the data in these databases will never be used?

R.I.P. Biological Data?

It seems highly likely that lots of this data is stored in what Usama Fayyad at Yahoo! Research! Laboratories! calls data tombs [2], because as he puts it:

“Our ability to capture and store data has far outpaced our ability to process and utilise it. This growing challenge has produced a phenomenon we call the data tombs, or data stores that are effectively write-only; data is deposited to merely rest in peace, since in all likelihood it will never be accessed again.”

Like last year, lets illustrate the growth with an obligatory graph, see Figure 1.

Figure 1: Data growth: the ability to capture and store biological data has far outpaced our ability to understand it. Vertical axis is number of databases listed in Nucleic Acids Research [1], Horizontal axis is the year. (Picture drawn with Google Charts API which is OK but as Alf points out, doesn’t do error bars yet).

Another day, another dollar database

Does it matter that large quantities of this data will probably never be used? How could you find out, how much and which data was “write-only”? Will Biologists ever catch up with the physicists when it comes to Very Large stamp collections Databases? Biological databases are pretty big, but can you imagine handling up to 1,500 megabytes of data per second for ten years as the Physicists will soon be doing? You can already hear the (arrogant?) Physicists taunting the Biologists, “my database is bigger than yours”. So there.

Whichever of these databases you are using, happy data mining in 2008. If you are lucky, the data tombs you are working will contain hidden treasure that will make you famous and/or rich. Maybe. Any stamp collector will tell you, some stamps can become very valuable. There’s Gold in them there hills databases you know…

  1. Galperin, M. Y. (2007). The molecular biology database collection: 2008 update. Nucleic Acids Research, Vol. 36, Database issue, pages D2-D4. DOI:10.1093/nar/gkm1037
  2. Fayyad, U. and Uthurusamy, R. (2002). Evolving data into mining solutions for insights. Communications of the ACM, 45(8):28-31. DOI:10.1145/545151.545174
  3. This post originally published on nodalpoint (with comments)
  4. Stamp collectors picture, top right, thanks to daxiang stef / stef yau

October 17, 2007

The Luxuriant Flowing Hair Club for Scientists (LFHCfS)

Filed under: Uncategorized — Duncan Hull @ 9:18 pm
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Falk Schuch, Andreas Linsner and Kai Jung
Calling all Scientists, is your hair luxuriant and flowing? Perhaps you’re a bouffant bioinformatician, a hairy hacker or share a lab with somebody who is? If this is you, its high-time you joined the Luxuriant Flowing Hair Club for Scientists.

To propose somebody for membership, send email to Marc Abrahams at Harvard University marca /ate/ chem2.harvard.edu. Your email needs to include evidence of your luxuriant, flowing hair (a photo) and your credentials as a scientist. Some current members have impressive hair, see Simon Gregory, Carlisle Landel and Sterling Paramore for examples. Honorary and historical members include Dr. Brian May (Queen guitarist / astrophysicist), Dimitry Mendleyev and Albert Einstein, “Physicist. Bon vivant. A bold experimentalist with hair”.

So, if you are a scientist with a copius coiffure, ask yourself, will you ever get another chance to be in such distinguished company?

September 5, 2007

Semantic Biomedical Mashups with Connotea


Mashup or Shutup

The Journal of Biomedical Informatics (JBI), will soon be publishing their special issue on Semantic Biomedical Mashups (can you fit any more buzzwords into a Call For Papers?!). Ben Good and friends have submitted a paper on their Entity Describer which extends connotea using some Semantic Web goodness. They’d appreciate your comments on their submitted manuscript over at i9606. As Ben says, their pre-publication turns out to be an interesting experiment “figuring out how blogging might fit into the academic publishing landscape”. If this interests you, get commenting now!

Update: Just spotted this interesting graphic of the Elsevier / Evilsevier logo (snigger), who are the publishers of JBI…

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