Human Factors from 30,000ft – Gime Feedback!

At Night from 30,000ft

I’m writing a final year undergraduate unit on Human Factors – it will be the first that that they have seen being that we are a hardcore engineering School – and I’d like your thoughts! Ignore the administrative stuff associated with work her in Manchester, but what about the unit content and the reading list (both at the bottom)? Any suggestions for units that have already proved effective will be greatly appreciated!

Human Factors from 30,000ft: Undergraduate Third Year Syllabus

Dr S Harper, School of Computer Science, University of Manchester, Oxford Road, Manchester, UK

COMPxxxxx: Human Factors from 30,000ft

Pre-Requisits

COMP23420: Software Engineering – or a demonstrable equivalence.

Introduction

‘The human mind …operates by association. With one item in its grasp, it snaps instantly to the next that is suggested by the association of thoughts, in accordance with some intricate web of trails carried by the cells of the brain.”

This idea, first proposed by Vannevar Bush in his 1945 Atlantic Monthly article ‘As We May Think’, is credited with being the inspiration, and precursor, for the modern World Wide Web. But for most of his article, Bush was not concerned with the technical aspects of his system. Instead, as with most computer visionaries, he was more focused on how the computer system and its interfaces could help humanity. He wanted us to understand that instead of fitting into the way a computer interacts and presents its data, the human cognitive and interactive processes should be paramount. In short, the computer should adapt itself to accommodate human needs; not the reverse.

Since the early days of computer science, with the move from punch cards to QWERTY keyboards, from Doug Englebart’s mouse and rudimentary hypertext systems, via work on graphical user interfaces at Xerox PARC, to the desire to share information between any computer (the World Wide Web), the human has been at the heart of the system. Human Factors – and more particularly Human Computer Interaction – has had a long history in terms of computer science, but is relatively young as a separate subject area. In some ways, its study is indivisible from that of the components which it helps to make usable, however, as we shall see in this unit, key scientific principles different from most other aspects of computer science, support and underlay the area.

‘Human Factors’ is not a simple subject to study for the Computer Scientist, it is an interdisciplinary subject which covers aspects of computer science, ergonomics, interface design, sociology and psychology. It is for this reason that human factors are often misunderstood, being classified by mainstream computer scientists as ‘soft’; a reference to their supposed lack of mathematical rigour. However, as we shall see, if human factors are to be understood and applied correctly an enormous amount of effort, mathematical knowledge, and understanding is required to both create new principles, and apply those principles in the real world. As with other human sciences, there are no 100% correct answers, everything is open to error because the human, and the environment they operate within, is incredibly complicated. It is difficult to isolate a single factor, and there are many extraneous hidden factors at work in any interaction scenario; in this case the luxury of a simple ‘yes’ or ‘no’ answer is not available. The ‘up–side’ is that this level of complexity makes the study of human factors incredibly interesting and incredibly challenging if done correctly; if you are up to this challenge then this is the unit for you.

Aims

Human Factors is ’the scientific discipline concerned with the understanding of interactions among humans and other elements of a computer system or
technology, and the profession that applies theory, principles, data and methods to design in order to optimise human well-being and overall system performance.’

This unit, therefore, covers interdisciplinary topics from HCI, Ergonomics and Human factors, to enable measurement and understanding of the computer, software, interfaces – and the human interactions associated with them – and the application of this understanding to improve its accessibility, usability, and systems dynamics. It introduces students to the factors which enable and affect the human aspects of the interface and provides an overview of the tools, techniques, and training for its study and modification.

Learning Outcomes

A2/A3/A5: Have an understanding of the domain, concepts, and important and upcoming aspects of Human Com- puter Interaction along with aspects of user interaction and cognition. In particular to have an understanding of the importance of Standards, Technologies, and Guidelines in the engineering process;

C1/C4: Have an understanding of the relevant research methods including experiment design, application, and the ethical issues surrounding such a design;

A1/D6: Have an understanding of, and be able to select and apply, the relevant descriptive and inferential statistical tests associated with Human Factors Engineering;

B1/C4: Be able to analyse and critique Human Factors research, experimental studies, and computer interfaces; and

B3/C4: Use analysis techniques associated with their knowledge of the domain to understand the problems associated with different designs, and suggests solutions for their resolution.

Assessment of Learning Outcomes

Learning outcomes are variously assessed by Examination (1×50%), Laboratory Reports (2×10%), and Open Book Term Papers (6×5%):

A2/A3/A5: Examination;

A1/C1/C2/C4: Laboratory Report – in the form of a full ethical application (this will take the form of a graded ethical application based the students final year project – students will be assigned a faux project if their final year project is not suitable) – an understanding of research methods will also be tested via Examination;

B1/C4: Open Book Term Papers – papers and texts will serve as discussion topics which will give rise to concise 200 word essays analysing and/or critiquing the topic under discussion – an understanding of the most important topics which arise from these analysis will also be tested via Examination; and

B3/C2/C4/D6: Laboratory Report – a student will select a previous software engineering project, which they will critique from the new knowledge, understanding, and perspectives gaining in this unit.

Contribution to Programme Learning Outcomes

A1, A2, A3, A5, B1, B3, C1, C2, C4, D2, D4, D5, D6.

Syllabus

The unit comprises twenty-two teaching sessions with one extra for the covering of revision topics. Students will be expect to devote further time for their own study, for report creation, and for the completion of the open book term papers – this is expected for all units and is detailed in the course / programme handbook.

Fifteen traditional lectures will be interspersed with seven discussion lectures in which the material for the term papers will be discussed. The majority of this material will be covered by directed reading followed by group discussion. Practical work will take the form of two laboratory reports based on the creation of an application for research ethics approval for the students third year project, along with a critique of the students previous Software Engineering HCI focused work. The unit will progress as follows:

Introductions:
1. What are Human Factors? Why are they Important? What is the Scientific Method? What does the Human Factors landscape look like?
2. Man-Computer Symbiosis, Licklider JCR, 1960.
3. People, Perception, Cognition, and Barriers; and
4. Society.?
5. Discussion Topic: The Information Capacity of the Human Motor System in Controlling the Amplitude of Movement, Fitts PM, 1954.

Engineering:
6. Requirements Elicitation & Analysis;
7. Modelling User Requirements: Use Cases, Scenarios, and Personas;
8. Discussion Topic: Evaluation of mouse, rate-controlled isometric joystick, step keys, and text keys for text selection on a CRT, Card, S. K, 1978.
9. Interface Design and Prototyping; and
10. Developing the Interface / Standards and Guidelines.11. Discussion Topic: Smith, D. C., E. F. Harslem, C. H. Irby, R. B. Kimball, and W. L. Verplank. ”Designing the Star User Interface.” Byte, April 1982.

Experimentation:
12. Planning Experiments: formative and summative investigations, and research ethics;
13. Qualitative and Quantitative Methods;
14. Sampling, Participant selection and recruitment, Participant Homogeneity, Cross-Disciplinary Issues and ‘Hot- Spots’;
15. Discussion Topic: The Magical Number Seven Plus or Minus Two: Some Limits On Our Capacity for Pro- cessing Information, Miller GA, 1956.
16. Laboratory, Naturalistic, and ‘In the Wild’ Studies; and
17. Human Factors for Real.
18. Discussion Topic: Voice loops as cooperative aids in space shuttle mission control, Watts, Jennifer C. and Woods, David D. and Corban, James M. and Patterson, Emily S. and Kerr, Ronald L. and Hicks, LaDessa C., 1996.

Analysis:
19. Qualitative and Quantitative Analysis Techniques;
20. Descriptive Statistics;
21. Inferential Statistics; and
22. Writing and Reporting.

Revision and Variance:
23. The Unit Revision Lecture; and
24. Variance: Just in case something goes wrong or we take longer than expected to cover the topics.

Reading List
There is no single book covering all material and there is no need for the students taking the course to buy any book, however, the following give a good introduction to the area:
1. Rosenberg, A. Philosophy of science: a contemporary introduction, 2nd ed ed. Routledge, New York, 2005.
2. Dix, A., Finlay, J., Abowd, G., and Beale, R. Human Computer Interaction, 2 ed. Prentice Hall, London, UK, 2002.
3. Nielsen, J., Weiss, S., Kearns, S., and Eberhardt, J. Understanding what users want. New Riders Publishing, Indianapolis, IN, 2001.
4. Raskin, J. The humane interface: new directions for designing interactive systems. Addison Wesley, Reading, Mass., 2000.
5. Shneiderman, B., and Plaisant, C. Designing the User Interface : Strategies for Effective Human-Computer Interaction (4th Edition). Addison Wesley, 2004. ISBN – 0321197860.
6. Bryman, A. Social research methods, 3rd ed ed. Oxford University Press, Oxford, 2008. 7. Forshaw, M. Easy statistics in psychology: a BPS guide. Blackwell Pub., Malden, MA, 2007.

Visual Complexity Rankings and Accessibility Metrics – #accessibility #a11y

Visual Complexity Scores - Trendlines

Visual Complexity Scores - Trendlines

Eleni Michailidou passed here PhD defence with flying colours and now her work ‘Visual Complexity Rankings and Accessibility Metrics’ is published. I’ll let her abstract tell the story but this is some really interesting work.

The World Wide Web (Web) has become the major means of distribution and use of information by individuals around the world. Web page designers focus on good visual presentation to implicitly help users navigate, understand, and interact with the content. The rapid and constant advancement of technology introduced new ways to present information that leads to visually complex Web pages. Problems arise, though, for people with disabilities, especially those who are visually impaired, because implicit visual cues presented on a Web page can- not be accessed and used.
We assert that, identifying the areas that are complex for sighted users will have direct benefits for blind and visually impaired users. We theorise that by understanding sighted users’ visual perception of Web page complexity we can understand the cognitive effort required for interaction with that page. This is an important contribution to the Web accessibility area because by using visual complexity, an identifiable measure, as an implicit marker of cognitive load, Web pages can be designed that are easier to interact with.
Results from user evaluations provided statistical models that, based on the density and diversity of Web page structural elements (such as text, tables, and images), can significantly predict sighted users’ perception of Web page visual complexity. The framework is then implemented into the ACTF Eclipse frame- work by extending the aDesigner accessibility tool to the ViCRAM tool. The tool automatically analyses a Web page with respect to its visual complexity. For each Web page a complexity score, that determines the page’s level of visual complex- ity, and an overlay heatmap, that mimics a user’s visual complexity perception by noting the areas that are most visually complex, are generated.
A user and technical evaluation support our assertions and show that the tool can significantly predict the level of visual complexity of a Web page. Therefore, users can have an initial perception of the visual layout of the page and designers can use this framework to balance Web page visual complexity with usability and accessibility.

Be careful, her PhD Thesis is a 250 page – 30Mb brute – but everything is in there! Thanks to Prof Stephen Brewster and Dr Steve Pettifer for the viva examination.

ResearchBlogging.org
Eleni Michailidou (2010). Visual Complexity Rankings and Accessibility Metrics PhD Thesis

ASSETS 2010 Picks – #assets10

ResearchBlogging.orgWe did present at ASSETS 2010 as I previously said and I must say that I think this years conference was solid. Maybe the work presented was not completely within my frame of interest; indeed, there was Rehabilitation Engineering, Assistive Technology, Educational, and advocacy work there which are interesting but for me not directly relevant. However, there were a couple of papers that did in principle offer the promise (if not yet realised) of being transformative, and providing some good solid scientific understanding.

The first was Shari Trewin’s [1] work which undertook a study of screen reader users and then attempted to add that model to the CogTool system. This means that it may become useful for user prediction in the future, but more rigours models are currently still required. The work puts me in mind of IBMs aDesigner which is now part of the eclipse AcT Framework, but Trewin’s work seems to lend itself far more to task based analysis of user behaviour…

Designers often have no access to individuals who use screen reading software, and may have little understanding of how their design choices impact these users. We explore here whether cognitive models of auditory interaction could provide insight into screen reader usability. By comparing human data with a tool- generated model of a practiced task performed using a screen reader, we identify several requirements for such models and tools. Most important is the need to represent parallel execution of hearing with thinking and acting. Rules for placement of cognitive operators that were developed for visual user interfaces may not be applicable in the auditory domain. Other mismatches between the data and the model were attributed to the extremely fast listening rate and differences between the typing patterns of screen reader usage and the model’s assumptions. This work in- forms the development of more accurate models of auditory inter- action. Tools incorporating such models could help designers create user interfaces that are well tuned for screen reader users, without the need for modeling expertise.

BumpTop Desktop View

BumpTop Desktop View

Next up was some work on desktop metaphors for older users by Nic Hollinworth and Faustina Hwang [2]. This work is still at an early stage but it does seem to have some potential, a fact which is not lost on Google – as they have just purchased BumpTop; which is a 3D representation of a desktop using real life metaphors to help organise the work. Now Nic’s work has some difference to BumpTop and seems to be far more like the real world, making interaction by older users more intuitive…

Routine computer tasks are often difficult for older adult computer users to learn and remember. People tend to learn new tasks by relating new concepts to existing knowledge. However, even for ‘basic’ computer tasks there is little, if any, existing knowledge on which older adults can base their learning. This paper investigates a custom file management interface that was designed to aid discovery and learnability by providing interface objects that are familiar to the user. A study was conducted which examined the differences between older and younger computer users when undertaking routine file management tasks using the standard Windows desktop as compared with the custom interface. Results showed that older adult computer users requested help more than ten times as often as younger users when using a standard windows/mouse configuration, made more mistakes and also required significantly more confirmations than younger users. The custom interface showed improvements over standard Windows/mouse, with fewer confirmations and less help being required. Hence, there is potential for an interface that closely mimics the real world to improve computer accessibility for older adults, aiding self-discovery and learnability.

References

  1. Shari Trewin, Bonnie E. John, John Richards, Cal Swart, Jonathan Brezin and John Thomas (2010). Towards a Tool for Keystroke Level Modeling of Skilled Screen Reading Proceedings of the 12th International ACM SIGACCESS Conference on Computers and Accessibility, 1 (1)
  2. Nic Hollinworth and Faustina Hwang (2010). Relating Computer Tasks to Existing Knowledge to Improve Accessibility for Older Adults Proceedings of the 12th International ACM SIGACCESS Conference on Computers and Accessibility, 1 (1)

Web, Art, Science Camp: Broadly a Success! #webartsci

Web, Art, Science Camp - Conference Grid

Web, Art, Science Camp - Conference Grid

So I recently attended the Web, Art, Science Un-conference / Camp and I must say it was pretty good. While it was a small affair attracting about 35 participants, the bulk being Web Scientists from Southampton, it was refreshing to see different literary work and analysis in a scientific context. I’d say that for the next one a greater effort needs to be made to attract practising artists and writers as opposed to scientist and academics studying literature. My only real problem with an event of this type is the lack of archival records which enable attendees and non-attendees to revisit the event and point to it in their papers; even if this is argumentation and opinion.

Paul de Bra’s un-keynote was really interactive and enlightening – with a history of hypertext, and then focusing on the current developments in the adaptive domain looking at the GALE System.

After the planning session I attended what seemed to be the more concrete session presenting work on groupware and planning support – but maybe this was a mistake. The two systems where also presented in the Demo session after lunch and the Web Science session – with its focus on human factors – would have been more useful – but without a transcript it’s difficult to follow the discussion post-hoc.

Demo’s followed lunch and every system out-there seemed to be onto something in it’s implementation – I liked them all and I think we’ll be here good things about each of them in the future.

The final session was a discussion on literary themes firstly their identification, and secondly their automated detection. Interesting work but not immediately of use in my work.

So on the whole a quality and interesting event.