Vishnu Gopal

(This is unmarked coursework, part of my HCI course at UCLIC and is released with permission from Prof. Rachel Benedyk. Since this is not evaluated and hasn’t gone through any sort of peer review process, it will most certainly contain errors.)

This analysis uses static anthropometric data to find out inconsistencies of door measurements with the stature of the intended population and recommended positions of door artefacts such as push handles and see-through windows. It further uses dynamic anthropometry to find out if the restoring torque of the door is within recommended limits. The most common use case of a healthy adult is considered in detail as the target user group and the lack of wheelchair accessibility is also noted.

Figure 1: Approximate Measurement of doors

Static anthropometry does not reveal faults with the door width and height. According to data available, the width of the door at 93 cm (all measurements are described in detail in Figure 1) and height at 240 cm is adequately wide and high for the 95th percentile of the tallest man who at 180 cm tall (Pheasant 2003) serves as the limiting user. The recommendations for the door handle or push plate state that it should be 25-35 cm from the door edge and 100-150 cm above the floor (Chang & Drury 2007)—and we see that both the push plate and the door handle at 8 cm from the door has inadequate distance from the door edge. However, both have the requisite span since they are long vertical strips that have a length of 65 cm, making their total effective area close to 145 cm, well within the recommended space. Analysing the placement of the see-through door windows, a flaw is immediately obvious. In the case of a short woman as a limiting user (shorter than 140 cm), the window would be useless since it will not allow her to see an intended user on the other side. The major limitation of the static anthropometry method was that it did not consider the purpose of the door: i.e., it hypothesised a theoretical user and did not analyse the function of the door—to open and close and lead the user through.

We decided then to take a step back and use the doors ourselves and note down psychophysical observations. We also observed other people using the doors and noted down possible flaws in the door design. One problem was immediately obvious and unanimous: the doors were too heavy and couldn’t be pushed through easily. We noted an instance where a man walked in with a package, couldn’t use sufficient leverage to open the door with a single hand and instead kicked out with his leg to stabilise the door enough to move through. These observations made it evident that the heaviness of the door was a source of major ergonomic discomfort.

Taking into account Chang & Drury’s recommendations for restoring torque at 30 Nm, an analysis could be done after measuring the door width and the placement of the handle. However, the study was complicated by three factors: 1) the hinges on the door were badly in need of oiling, 2) the door had different resistances at different points in its axial opening and 3) the hinge was loose and at least a portion of the door was intersecting with the frame of the door causing added initial opening friction. Even ignoring these three factors, and calculating the torque of this door,

Moment = F r Sin a

Assuming a as 90 degrees, which means the user pushes the door at a right-angle,

Moment = F r

Since there was no way to measure the weight on the door, we assume a force ranging from 22 to 132 N as in Chang & Drury, moment at 22 N would then be: 22 N x 85 cm, which is 18.7 Nm. Assuming the upper limit of a 132 N force, moment would be 112.2 Nm.

We notice here that if the force on the door is beyond 35 N, we exceed the stated recommendations. The three subjective experiences noted above however, exceed any apparent weight of the door. The hinges of the door at the Malet Place end were so badly unmovable that they would not open beyond 70 degrees unless an exceedingly strong force was used. While any door is an interruption to the dynamic flow of walking of an individual, the successful doors try to stay out of the way by minimising resistance and being easy to open and close. The resistance of these doors makes even the strongest user take a cognitive break from his actions and use his will on the door to move through—this is especially evident when the user has his first experience since he does not expect the door mechanism to be so rusty.

Considering the operation of the door with normal users in mind, the biggest recommendation that can be made to ease the use of the door is to oil the hinges and position the door within the frame so that no part of the door impinges on the frame. The door could also be made lighter and conceivably transparent since it does not overlook into any sensitive areas. To ease wheelchair access, the door could be made powered. The placement of the door pads and the handle could be moved to be more conforming.

The doors would also probably require regular maintenance since they experience heavy traffic throughout the day. Because they connect two buildings with possibly separate and insulated heating systems, a heavier door might have been preferred, but the ergonomic cost add up after each use. Keeping in consideration cost requirements, an enclosed area between the two buildings could be constructed to serve the same purpose since the primary function of the door in this instance seems to be insulation.

While considering an evaluation of this nature, one thing that I thought could be done differently was to perform a contextual enquiry of people using the door—immediately after they went through the double doors. The users might be able to articulate what their material difficulty was, and provide clues to how to construct these doors better. The study could also have been better if it had more data to analyse: it would be relatively easy to set up video recording equipment and observe users interacting with the doors and analysing quantitative measures from the door as well, like the time it takes for a user to successfully complete the interaction. Perhaps grouped by gender, this can provide further insights.

(1047 words).

References:

Pheasant, Stephen (2003). Bodyspace. Anthropometry, Ergonomics and the Design of Work. Second Edition. p. 244.

Chang, Shih-Kai, Drury, Colin G. (2007) Task demands and human capabilities in door use. Journal of Applied Ergonomics Vol 38. pp. 325-355. 

(This is unmarked coursework, part of my HCI course at UCLIC and is released with permission from Prof. Ann Blandfod. Since this is not evaluated and hasn’t gone through any sort of peer review process, it will most certainly contain errors.)

Heuristics as an Aid to Training a Usability Evaluator’s Expertise

Vishnu Gopal

University College London

It is clear that heuristic evaluation as Nielsen envisioned it is a method meant for experts (Nielsen, 1992). Heuristics do not stand alone, and have to be moulded to fit any particular scenario: the general set of heuristics have been expanded into specific guidelines for different kinds of activities: accessibility, internationalization (Gonzalez, Granollers, Pascual, 2008), etc. are examples and these require evaluators who are trained and experienced in separate spheres. Experimental data also seems to suggest that the more experienced the evaluators, the more usability errors they find (Dumas and Redish, 2002). Given this scenario, I seek to explore if heuristics or other similar guidelines can serve as a tool to strengthen a beginning evaluator’s “experience”.

Without doubt, applying heuristics to usability evaluation gives a methodical structure to the task of analysing potential faults in a system. During a recent analysis of e-commerce websites, one major observation that I made was that without rules, it’s easy to miss the forest for the trees—i.e. one might speculate on possible faults: for e.g. the links on the right hand side navigation bar was not prominent or relevant enough, or the visual design was not attractive; but fail to gather the data into meaningful coherent suggestions. The aim, after all, of a successful usability evaluation is to find ways to rectify potential faults. When pitted against an evaluators raw instincts then, following a set of guidelines acts both as a reasonably exhaustive search space and a framework for assessing faults that have been found. It can also be argued that using a set of guidelines methodically can sensitise an evaluator to common errors.

On the other hand, I also observed that there might be faults found more easily not from a strict adherence to guidelines, but from an evaluator’s own prior experience. During the usability evaluation activity, my companion who is a trained visual designer found that much of the website’s apparent clutter was due to it not following a coherent “grid system” (see Chang, Dooley, Tuovinen, 2002). While it might be easy to slot this into either guideline 4 (consistency) or 8 (aesthetic design), it doesn’t cleanly fit into the heuristic framework provided, but is a crucial criticism nevertheless. I suspect that a strict adherence to guidelines without a broader background might harm rather than help a beginning evaluator’s progress, but this requires detailed investigation. It could also be too easy to be trained to look into a series of specific and common problems rather than try to evaluate a system based on its intent.

This is further imperilled by the fact that the minutiae of specific guidelines change often. An example of this debate is how the specific recommendation relating to websites displaying content above the fold (the initial viewable area) changed from 1994 to 1997, a short span of three years (Nielsen 1997).

When compared to other methods of user testing, heuristics pale further in this regard. They remove a vital component from usability evaluation: the serendipity (Stoskopf 2008) that observing a user adds to training an evaluator’s instincts. This is especially important in a field like usability evaluation where observation of real users continues to be stressed (Petrelli, Hansen et. al. 2004), and rightly so, for HCI evaluation has its roots in cognitive psychology and that is a science yet to attain adulthood (Miller 2003).

It would also be instructive to observe how HCI (and accordingly usability evaluation) is taught in University courses worldwide. Saul Greenberg of the University of Calgary remarks that a “fundamental tenant of HCI is that end-users should play an integral role in the design process” and that “performing usability studies in class hammers home the relevance of evaluation”—indeed his course description (Greenberg 1996) is filled with references that directly involve users in class. Interestingly, the course is structured so that “Designing Without the User” is a later event: where lessons learnt from these evaluations are then integrated to try to formulate a theory of user behaviour.

Chan, et. al. exploring issues integrating HCI in master-level MIS programs also stresses the emphasis on users and “empirical testing” and recommends a curriculum that largely ignores heuristics. Faulkner and Culvin in “Integrating HCI and Software Engineering” condenses it well and also explains a crucial difference with software engineering:
“Some HCI practitioners seem to believe that if HCI can be reduced to guides and checklists that anyone can apply to anything, then all will be well. This is tantamount to designing HCI out of software engineering as it is providing rules to be followed without the requisite theoretical under-pinning. Students trained in this way will be chanting mantras and will be woefully unable to deal with problems that have not been solved elsewhere or are not covered by style guides and checklists. Software engineers on the other hand are either keen to embrace these checklists or are unwilling to accept that the age of users having to adapt themselves to systems has gone. Users want systems to work for them and not the other way round.” (Faulkner & Culvin, 2000)

Furthermore, in a study examining how guidelines and patterns might be effective in HCI teaching, Hvannberg et al. “found very little hard evidence” supporting the importance of using patterns or guidelines in HCI teaching. However, they also noted “a desperate need to conduct studies on a suitable scale on the use” of patterns and guidelines in teaching HCI concepts.

There is no doubt that Nielsen’s basic heuristics have stood the test of time as a way to find usability errors. However, as a tool to train a beginning evaluator, they should certainly be supplemented by other evaluation methods.
(1045 words).

References:

Chan, S.S, Wolfe, R. J., Fang, X. (2003), Issues and strategies for integrating HCI in masters level MIS and e-commerce programs, International Journal of Human-Computer Studies, Volume 59, Issue 4, Zhang and Dillon Special Issue on HCI and MIS, October 2003, Pages 497-520, ISSN 1071-5819, DOI: 10.1016/S1071-5819(03)00110-1.(http://www.sciencedirect.com/science/article/B6WGR-4938JRM-1/2/498d2855a23d35c7524dd9c4201b5d4e)

Chang, D., Dooley, L. Tuovinen, L.E. (2002), Gestalt theory in visual screen design: a new look at an old subject, ACM International Conference Proceeding Series; Vol. 26 Proceedings of the Seventh world conference on computers in education conference on Computers in education: Australian topics – Volume 8

Dumas, J.S., Redish J. A Practical Guide to Usability Testing. (1999), Oregon. Intellect Books. pp 67.

Faulkner, X. Culwin F. (2000), Enter the Usability Engineer: Integrating HCI and Software Engineering, ACM SIGCSE Bulletin

González, M.P, Granollers, T., Pascual, A. (2008), Testing Website Usability in Spanish-Speaking Academia through Heuristic Evaluation and Cognitive Walkthroughs, Journal of Universal Computer Science, vol. 14, no. 9.

Greenberg, S (1996), Teaching Human Computer Interaction to Programmers. Technical Report 96/582/02. University of Calgary.

Hvannberg, E.T., Read, J.C., Bannon, L. Kotzé, P. & Wong W. (2006), Patterns, anti-patterns and guidelines: Effective aids to teaching HCI principles? In, Inventivity: Teaching theory, design and innovation in HCI – Proceedings of HCIEd2006-1 (First Joint BCS/IFIP WG 13.1/ICS /EU CONVIVIO HCI Educators Workshop (pp. 115–120). Limerick, University of Limerick.

Miller, G. A. (2003), The cognitive revolution: a historical perspective. Trends in Cognitive Sciences, vol.7 no.3.

Nielsen, J. (1992), Finding usability problems through heuristic evaluation. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Monterey, California, United States, May 03 – 07, 1992). P. Bauersfeld, J. Bennett, and G. Lynch, Eds. CHI ‘92. ACM, New York, NY, 373-380. DOI= http://doi.acm.org/10.1145/142750.142834

Nielsen, J. (1997), Scrolling Now Allowed. Blog post at http://www.useit.com/alertbox/9712a.html

Petrelli, D., Hansen, P., Beaulieu, M., Sanderson, M., Demetriou, G. and Herring, P. (2004), Observing Users – Designing clarity a case study on the user-centred design of a cross-language information retrieval system. Journal of the American Society for Information Science and Technology, 55 (10). pp. 923-934.

Stoskopf, M. K. (2008), How Serendipity Provides the Building Blocks of Scientific Discovery. ILar Journal. vol. 46.