Monthly Archives: February 2011

Back to Basics: Does Point-&-Click Hinder Innovation?

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Canon Cat Leap Keys

Canon Cat Leap Keys

Skipping to the end – the answer is I don’t know – but I think it’s worth considering!

I’ve recently been considering if point and click ‘desktop’ / ‘window’ interfaces stifle innovation because they seem to be all encompassing and universal on all modern operating systems. Even though we have some desktop variations the metaphor still seems to be pervasive for most everyday tasks. It may be that this is not a problem, just as we use a desk for most writing tasks and a pen and paper and a filing system – these are part of everyday life and are no longer questioned – these tools are familiar and comfortable and so are now just ‘invisible’ to us. However, what if our reliance on the desktop is misplaced – what happens if there are better ways of interacting with applications and their data. We can see that systems exist – like zigzag – but these is pretty complex and difficult to use and implement, showing no traction outside research.

I’m, not sure if a move back to text based systems or at least a complimentary system would not be a good thing. Point and click has a tendency to make developers in some way sloppy. As interfaces are visual and point and click is all that is required interfaces have become ever complex without much complexity being hidden behind a more simplistic GUI.

Things are not all bad – indeed the Web maybe where most of the novel interface work may be occurring. As an example take the Facebook status update which allow the user to type the @ symbol before a friends name is typed, which brings up a selection list. This means the user is not required to stop typing, select a listbox – scroll up and down what could be a hundred choices – and then select a friend – but just select using the cursor keys from a much shortened list. Indeed this reminds me in some ways of the Canon Cat ‘leap’ keys:

You moved through your data using two extra keys called Leap keys located in front of the spacebar key and by typing strings of characters. The Cat jumped to the next occurrence of that string. Raskin claimed that the Cat’s Leap-key search method to scroll from the top to the bottom of the page took 2 seconds, a mouse took 4 seconds, and cursor took 8 seconds. Larger documents increased these search ratios.

The Leap keys also controlled text selection (indicated by hilighting), deletion, copying, and moving. If the selected text was a mathematical formula one keystroke with a special key calculated the mathematical result and the answer appeared on the screen with a dotted underline overlaying the original formula. If the selected text was a computer program written in either FORTH or 68000 assembly language, then a special key let you execute the program (I don’t think many Cat users did any Cat programming). You performed mail merges by selecting columnar text data and pressing another special key. Repetitive command sequences could be automated by assigning commands and text strings to the Cat’s numeric keys. One special key let you dial a selected telephone number either for voice or modem communications. Data received from the built-in modem flowed into your text as if you had typed it.

I’m not sure if there really is an answer here, or if we should just consider hybrid solutions, but for me typing using symbols to enable special faster interactions seems logical, the less I take my keys and attention from the keyboard, the faster my interactions seem to be; especially when I am cognitively focused on a single task.

‘An Evening with Donald Knuth – All Questions Answered’ – 7th Annual Turing Lecture

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Professor Donald E. Knuth

Professor Donald E. Knuth

If you don’t know Knuth then you should:

Donald E. Knuth (B.S. and M.S., Case Institute of Technology 1960; Ph.D., California Institute of Technology 1963) is Professor Emeritus of The Art of Computer Programming at Stanford University, where he supervised the Ph.D. dissertations of 28 students since becoming a professor in 1968.

He is the author of numerous books, including three widely translated volumes (so far) of The Art of Computer Programming, recently augmented by a new hardback released as Volume 4A, five volumes of Computers & Typesetting, eight volumes of collected papers and a non-technical book entitled 3:16 Bible Texts Illuminated. His software systems TeX and METAFONT are extensively used for book publishing throughout the world.

He is a member of the American Academy of Arts and Sciences, the National Academy of Sciences and the National Academy of Engineering, and he is a foreign associate of the French, Norwegian, Russian and Bavarian science academies as well as the Royal Society of London.

He received the Turing Award from the Association for Computing Machinery in 1974; the National Medal of Science from President Carter in 1979; BCS Distinguished Fellowship in 1980; the Steele Prize from the American Mathematical Society in 1986; the Adelsköld Medal from the Royal Swedish Academy of Sciences in 1994; the Harvey Prize from the Technion of Israel in 1995; the John von Neumann Medal from the Institute of Electrical and Electronic Engineers in 1995; and the Kyoto Prize from the Inamori Foundation in 1996.

He holds honorary doctorates from Oxford University, the University of Paris, the Royal Institute of Technology in Stockholm, the University of St. Petersburg, the University of Marne-la-Vallée, Masaryk University, St. Andrews University, Athens University of Economics and Business, the University of Macedonia in Thessaloniki, the Universities of Tübingen, Antwerp, ETH, Oslo and Bordeaux, and at least eighteen colleges and universities in America.

Don hasn’t had an email address since January 1, 1990. As might be expected of a person who own a sixteen-rank 812 pipe Abbot and Sieker organ he is a member of the American Guild of Organists.

The University of Manchester, in partnership with the IET, BCS and IBM, hosted Professor Professor Knuth as the 7th annual Turing Lecture speaker.

7th Annual Turing Lecture

7th Annual Turing Lecture

Don Knuth, Computer Scientist and Professor Emeritus of the Art of Computer Programming at Stanford University, USA,  engaged with the audience in a question and answer session titled ‘An Evening with Donald Knuth – All Questions Answered’… and I’d expect my view to be incredibly bias.

To me Don’s answers were a call for Human Factors and cross-disciplinary work. Why, what, how? I hear you splutter – Don does algorithms and computational logic with a bit of big-number theory doesn’t he? All true, all true – but let me justify this…

When asked:

  1. Why he got into Computer Science Don replied that – it was because the documentation on a machine he was working on didn’t have usable documentation;
  2. What would he  use the 1948 SME ‘Baby’ for – generating music;
  3. How would he turn children on to computing – highly interactive applications such as  A/V and mixed media/modalities;
  4. What took him the longest time – Metafont, getting the fonts to be usable and accessible in document preparation and typesetting; and
  5. Where is computing headed – more interactivity.

Now while I may be pushing-it to assert his responses where all about human factors (they weren’t) go have a look at the video on the University of Manchester Computer Science site, or the BCS site – listen carefully to his answers – there is so much human factors work in his answers you’d be silly not to take notice.

Computational Thinking

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Old Skool Datasette

Old Skool Commodore Datasette

We use the term ‘Computational Thinking’ in one of our visit day slides – the day prospective students come the School to find out more and get their offer – but we don’t really go into it in any more detail on the Website or explicitly in the Undergraduate Programme; as far as I’m aware. It was hot a year or so ago but in reality I never saw the point, it seemed obvious or as though Computer Scientists wanted to cling to this all encompassing concept – think the Web Science ‘Flower’ – to justify our interdisciplinary existence. However, it is probably not a good idea to dismiss something out of hand – especially when its main proponents are at Carnegie Mellon [1].

They tell us that “Computational thinking is a way of solving problems, designing systems, and understanding human behaviour that draws on concepts fundamental to computer science. To flourish in today’s world, computational thinking has to be a fundamental part of the way people think and understand the world.”

The key part here is “concepts fundamental to computer science” so what are these concepts? Well culled from some the the literature and reformatted they seem to mostly be:

  • Abstraction: “making use of different levels of abstraction, to understand and solve problems more effectively”;
  • Algorithmic Thinking;
  • Application of Mathematical concepts;
  • Inductive Reasoning; and
  • Scalability: “for reasons of efficiency but also for economic and social reasons”.

CMU give examples along the line of “Computational thinking makes it possible for transplant surgeons to realize that more lives can be saved by optimizing the exchange of organs among pools of donors and recipients. It enables new drug designs to be analysed so that they are less likely to create drug-resistant strains of diseases. Artists, when given the tools to think and express themselves computationally, can create totally new modes of human experience. Users of the Internet, when empowered with computational thinking, can demystify privacy technologies and surf the web safely.” The main building blocks of their studies seem to be around what they call PROBES1 or PROBlem-oriented Exploration’s. But to me these all sound real similar to SE Use Cases in Requirements Analysis and Elicitation – and scenarios in HCI Engineering work.

Where really does the novelty lay, how useful are these PROBES, and why have we not seen large scale uptake of the tools and techniques around Computational Thinking – I’m tempted to say “because there is nothing new here” but I’ve a niggling feeling I’m wrong…

Maybe it is because they are just so second nature to any good computer scientist / engineer – we think about these things all the time, and apply them even more, to move knotty real world problems to a domain that makes them more amenable to the application of logic, structure, and computational processes. Maybe, this stuff is second nature (and in some cases quite pedestrian) to CS people but really ‘WOW’ to people from other domains. Logically thinking about (and solving) complex problems from multiple heterogeneous domains and coming up with something half sensible may very well be a key trait of the CS domain. I’m still not sure – it would be good to see a real book on this subject just so we can identify it is really ground breaking – or really vapourwear.

References:

  1. http://www.cs.cmu.edu/~CompThink/

Notes:

  1. A PROBE develops and applies novel computing concepts in ways that vividly illustrate the value of computational thinking while advancing basic research in computer science. Some PROBEs involve applying new research concepts to nontraditional problems, to show how computational thinking can improve our world. Other PROBEs explore new educational concepts, to teach computational thinking. Often a PROBE involves a collaboration between a computer science researcher and a domain expert.

Social Aggregation and ‘Information Blindness’ – #accessibility

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Social Networks

'Social Snow' / 'Information Blindness'?

Seems to me like the new work in information management is social aggregation. It also seems like that thorny problem of information overload is now being applied to social networks as the number of presences an individual has increase to un-manageability. Aggregation seems to be the answer to some – with Sony Ericsson’s Timescape and Mediascape, Spindex, and applications like the Moblin/ Maemo / MeeGo aggregator seeming to provide a solution – but as we already know cognitive overload is a critical problem when navigating large information resources, aggregated or not.

Overload is further increased if the ‘narrative’ is non-linear and may switch context unexpectedly, and this is just what aggregators do. Preview through summaries is key to improving the cognition of users in large heterogeneous resources but complex, comprehensive summaries can often overload the reader with extraneous information.

People, reading1 at speed by scanning for just appropriate information tend to fixate less often and for a shorter time, however, they can only remember the ‘gist’ of the information they have read; and are not able to give a comprehensive discourse on the information encountered. This means that comprehensive summaries for users quickly scanning aggregated content can increase the amount of information that is not actually used in the decision making process of the reader. This information only adds to a users information overload – or perception of their overload.

Once again we see that ‘mainstream’ technology will fast be needing our accessibility ‘edge cases’. Orchestration of multiple dynamic content by aggregators means that most users will start to become ‘information blind’ with the same problem visually disabled users have – too much information delivered in slow serial streams.

Notes:

  1. People read text by using jerky eye movements (called Saccades) which then stop and fixate on a keyword for around 250 milliseconds. These fixations vary and last longer for more complex text, and are focussed on forward fixations with regressive (backward) fixations only occurring 10-15 percent of the time when reading becomes more difficult.