Posts Tagged ‘Human Factors in design’
Human Factors in Design
The term Design is all the rage.
Any professional in any field feels it imperative to add Design in the title.
Engineers, graphic professionals, photographers, dancers, environmentalists, climatologists, scientists… they all claim to be designers first.
And this is very refreshing.
Have you heard of this new field of Design Anthropology? https://adonis49.wordpress.com/2012/02/06/design-anthropology-why-are-there-designs-not-meant-for-human/
Dori Tunstall said in an interview with Debbie Millman:
“Design translate values into tangible experiences…Design can help make values such as equality, democracy, fairness, integration, connection…(values that we have lost to some extent), more tangible and express how we can use them to make the world a better place…”
Looks like Tunstall expanded the term design to overlap with the political realm of Congress jobs, law makers, political parties, election laws…
It is about time that everyone “think design” when undertaking any project or program
Anything we do is basically designed, explicitly or implicitly: Either we are generating products and programs for mankind, or it is mankind who is in charge of executing, controlling and managing what has been conceived.
So long as human are directly involved in using a product or a program, any design must explicitly study and research the safety, health, and mistakes that the operators and users will encounter.
Must as well that the design be as explicit in the attributes of health, safe usage, errors that might generate serious consequences, materially, mentally or physically.
Four decade ago, there was a field of study called Human Factors.
The term Human Factors was considered too general to be taken seriously in Engineering.
The implicit understanding was that “Of course, when an engineer designs anything, it is the human who is targeted….”
However, besides applying standards and mathematical formulas, engineers are the least concerned directly with the safety, health of users: The standards are supposed to take care of these superfluous attributes…
And who are the people concerned in setting standards?
Standards are arrived at in a consensus process between the politicians and the business people, and rarely the concerned users and consumers are invited to participate in the debate, except in later sessions when standards are already drafted…
And how explicitly experiments were designed to allow users to test, and give feedback to any kinds of standards, handed down from successive standard sets…?
Countless engineers and scientists are directly engaged in putting rovers on Mars and launching shuttles and… and the human in the project is taken for granted…
If you ask them whether they have human factors engineers in their teams, they don’t understand what you mean.
The project is supposed to be an engineering project, and “where the hell did you bring this human thing in the picture?”
Anything that is designed must consider the health, safety, and how a person from various ages, genders, and ethnic idiosyncracies might use the product or the program…
Take all the time in design process. People are not supposed to be used as ginea pigs for any redesigned process… after countless lawsuits, pains, suffering…
This is a preliminary draft. Any input and replies?
Note: https://adonis49.wordpress.com/2008/10/04/whats-that-concept-of-human-factors-in-design/
Fundamentals of controlled experimentation methods: What’s Human Factors in design?
Posted October 14, 2008
on:What is Human Factors in design? (Article #39, April 1st, 2006)
Fundamentals of controlled experimentation methods
An experiment is designed to study the behavior of the responses of subjects (dependent variables or what are measured as performance), as the values/stimuli of an independent variables or factors are changed, manipulated, or presented randomly or in fixed manner.
There are other factors that need to be controlled because they could have serious effects on the behavior of the selected dependent variables, and thus are held constant or fixed by appropriate techniques, procedures, instructions, experimental setting, and environmental conditions.
Controlled experimentation methods are versions of current simulations methods, but are essentially more structured and controlled.
In a nut shell, an experimental method is a series of controlled observations undertaken in an artificial situation with the deliberate manipulation of variables in order to answer specific hypotheses.
In general, a scientist plans, controls and describes all the circumstances surrounding his tests, in a way they can be repeated by anyone else, which offer dependability for validation.
The requisite of repeatability encourages artificial settings that can be controlled, especially because the participants/subjects in the experiment are not usually involved or engrossed in their tasks, and because it enables a scientist to try combinations of conditions that have not yet occurred.
Controlled experimentation are time-consuming, expensive, and require a staff of skilled researchers and investigators so that they are conducted for basic research, publishing scientific papers, and when sponsored by deep pockets private companies and well-funded public institutions.
There are different types of experiments, some are designed to extract cause and effects among the variables, and especially their interactions in the performance of a system.
Others experiments are not so well structured and are intended to explore a phenomenon at an initial phase.
Experiments varies in their design purposes and levels of control: there are experiments on inanimate objects or natural phenomena that follow fixed trends and do not change much with time.
Experiments using human subjects in order to select the better performing system or product, and experiments intended to study the cognitive concepts of people such as attitudes, mental abilities, problem solving aptitudes, attention span and the like are very complex, very intricate, highly time-consuming and expensive to conduct.
The next article entitled “Controlled experimentation: natural sciences versus people’s behavior sciences” is intended to compare the complexity, differences, and levels of difficulties among the various experiments.
This article is striving to establish the fundamental processes or necessary structured steps to conducting a controlled experiment.
In the spectrum of complexity, innovation, and difficulty the experiments in natural sciences are the easiest, and psychology the hardest; within that spectrum fall experiments in the disciplines of agriculture, econometrics, education, social sciences, and marketing.
Early researchers in the phenomenon of electricity had to experiment with simple methods of one dependent and one independent variable, rudimentary equipments, and to rely on an exploratory knowledge of how electricity works and what are the factors that cause definite change in the behavior of certain criteria.
For example, scientists observed that there are relationships among voltage/power, the intensity of the current and the material the current is flowing through, then a scientist set up an experiment to study how the voltage changes when the intensity of the current varies or when the resistance of a material varies. By conducting several experiments, first by working with a specific conducting material, thus fixing the resistance, and varying the intensity of the current and repeating this simple experiment many times and, second by fixing the current at a certain level and working with different kinds of conducting materials, then the scientist managed to observe a steady mathematical relationship among these three variables.
As the body of knowledge in electricity expanded and more experiments were undertaken, the physical science of electricity discovered many more factors that entered into the mathematical relationship with varying degrees of importance and consequences.
Obviously, physical scientists can now enjoy more powerful, time-saving, and effective experimental designs that can employ several independent variables and several dependent variables in the same experiment thanks to the development in statistical/mathematical modeling and the number crunching computers; these developments in controlled experimentation allow observations of the interactions among the various variables simultaneously, if physical scientists deign to apply them!
Controlled experimentation methods have a set of requisite structured steps that are common to both natural and social studies. Usually, an investigator has to review the research papers on the topic to be investigated, sort out the articles that are scientifically valid and experimentally sound, consider the variables that have been satisfactorily examined and those that were controlled, or not even considered. Or the scientist may explore the topic by systematic observation of the problem, then he has to propose a hypothesis that could be rejected, but never accepted no matter how often it was not rejected. He has to conceive a design for the experiment such as the types, numbers of variables, their levels, and how to manipulate the trials, then he has to decide on the best method for selecting the subjects, the materials, or products to be tested, the setting conditions, the procedures, the operations or tasks to be performed, the instructions, the equipments, the appropriate statistical model.
Then the scientist has to conduct the experiment, running the data, analyzing the results, interpreting the results, and finally providing guidelines or practical suggestions to be applied in engineering projects.
The motors of statistical packages used to analyze data are mathematical models or sets of algebraic equations with as many equations as unknown variables and relying on the two main statistical concepts of means and variances among data.
The purpose of controlled experimentation methods is to strictly control systematic errors due to biases and then to sort out the errors that are due to differences among the independent variables and those introduced randomly by human variability. Once the size of random errors is accounted for then it is possible to study the relationships among the independent variables and to claim that a hypothesis could or could not be rejected at a criterion level of statistical significance, set frequently at 5%. This criterion level of 5% of statistical significance, means that there is still a 5% chance that an amount of random error might be the cause in the differences of the results.
Types of errors and mistakes committed in controlled experimentation will be reviewed in article #45. However, it is important to differentiate between evaluation/testing methods and strictly controlled experimentation. In human factors discipline, evaluation methods are applied to compare the effectiveness of several products or systems by measuring end-users behaviors, like/dislike, acceptance/rejection, or satisfying rules and regulations with the purpose that management would be able to decide on the choice among the products offered within specifications.
Controlled experimental methods are mainly applied to study the cause and effects of the main factors on objective measurements that represents valid behaviors of representative samples of end-users with the purpose of reaching design guidelines for products or systems planned for productions.
Article 25, September 11, 2005
“My pet project for undergraduate engineering curriculum”
My aim is to produce hybrid scientists or engineers with Human Factors background in undergraduate curriculum. Undergraduate university students must enjoy a comprehensive curriculum initiating them to methods applied in both hard and soft sciences. Basically, students must be knowledgeable in the various ways of designing experiment, which is the common denominator methods, taught implicitly but never satisfactorily because the logic is not that straighforward unless exposed explicitly and trained.
Undergraduate engineering disciplines must require courses in experimental research and statistical analyses training and drawn from multidisciplinary social sciences so that they can be better positioned to handle research involving mathematical modeling of theories in sciences.
I believe that at least 6 courses should be included in any engineering field involved in system design, which are: “Human Factors” in 2 courses, “Design for inferential experiments” and “Structural linear equations modeling applying the statistical analytical package LISREL”, “Human performance”, “Systems risk assessments”, and “Occupational safety and health”.
It is advisable that engineering departments, architecture and any field involved in designing systems or subsystems, with the avowed mission of reducing errors committed by end users in the application and maintenance of their tasks, need to offer 3 required courses and three elective courses related to the factors that affect the performance of end users.
These courses are meant mainly to designing interfaces between systems and end users, whether the latter are engineers, operators, workers, technicians or consumers, but they are also important for the designers of the systems to be cognizant of the problems related to the capabilities, limitations and behavior of end users who will ultimately break or implement any well-intentioned and best designed systems from textbook standards and processes.
The first required Human Factors course would be an introduction to the basics in designing for people, the physical and cognitive capabilities and limitations of end users, the environmental and organizational factors that may affect performance and the physical/mental applications and methods for designing interfaces between systems and end users.
The second Human Factors course, which could be elective, would initiate designers to actually design an interface with the needed experiments relevant to validating the requirements and guidelines that foresee the compatibility of the system performance with the level of skills and training required by the end users. A designed interface would be accompanied by facilitating aids, procedures and functional booklets to enable end users for ready application.
The third course called “Design of experiments” is to initiate designers on efficient designed experiments that would save time, effort and money with the additional result of accounting for the interactions among all the factors under study and providing designers with facts that they could readily apply in their design endeavors. This course is not meant to dwell heavily on the mathematical basis for the statistical analysis, which requires another follow-up course, but to form scientific minds which can critically analyze research papers and the experimental procedures that encourage designers to start reading research papers and appreciating the materials that would form the basis for their continuing education.
The fourth course called “Systems risk assessments” would initiate designers to the trade-off decisions of the safety and health risks on the users, environment and organizational structures in societies and the financial cost from the adoption of technologically complex alternative designs.
The fifth course called “Occupational safety and health”, in addition to initiating the engineers on the laws and processes for a safe work place, will also encompass the concept of consumer’s product liability and forensic engineering. A designer needs to be familiar with the problems and consequences of his designs to the end users, their idiosyncrasies and cultural differences in using any product or manufacturing process design in an occupational setting. The knowledge of the standards and applicable laws and guidelines for a safe and healthy manufacturing or processing plant can make a substantial difference among graduating engineers not only in their people communication skills and designing performance but also for later promotions in any administrative or organizational positions.
The sixth course “Human performance” is designed to providing the skills and training necessary to designing and evaluating the performance of interfaces. Examples of these skills include the development of written instructions, designing relevant questionnaires to assess the characteristics and training skills of target users and how well the interface is performing, designing performance aids to helping the short-term memory of operators, formatting instructions and information, input data display formats, output formats, coding design, personnel selection, determining qualifications and any written or verbal technique or method necessary to testing, evaluating and quantifying operators’ performance.
An informed engineering designer, who can define the limitations, skills and needs of the target users for his interface and who is trained early on in his academic years to the consequences of his tasks, may save end users from committing many foreseeable errors, greatly alleviate their physical and mental anguish, suffering, pain and inefficiency and thus save his sponsors time and money for later redesign undertaking.
The afore-mentioned courses, if offered in the first 2 years of the curriculum, might provide the undergraduate students with a different perspective toward the remaining core courses that enhance the seriousness of his responsibilities and the importance of his profession.
I frankly cannot conceive of an engineer pursuing higher graduate studies without being exposed to the fundamental necessity of designing to target users. Engineering is an applied science for practical human needs and not knowing the needs and behavior of target users then the engineer’s design endeavor might be flawed from the start.
What’s that concept of Human Factors in design? Article 21
“How engineering curriculums can be restructured to respond to end users demands?” (Written in April 19, 2005)
In 1987 Alphonse Chapanis, a renowned Human Factors professional, urged that published Human Factors research papers target the practical design need of the various engineering disciplines so that the research data be readily used by engineers. Chapanis was trying to send a clear message that Human Factors sin qua was to design interfaces between systems and end users. And thus, research papers have to include sections directing the engineers as to the applicability of the results of the paper to design purposes.
In return, it is appropriate to send the message to all engineering disciplines that research papers should include sections orienting the engineering practitioners to the applicability of the results of the papers to the end users and how Human Factors professionals can judiciously use the data in their interface designs.
As it was difficult for the Human Factors professional to send the right message to the engineering practitioners, and still has enormous difficulty disseminating the proper purpose and goals, it would be a steep road for the engineers to send the right message that “what they design is actually targeting the needs and new trends of the end users“.
As long as the engineering curriculums fail to include the Human Factors field as an integral part in their structures it would not be realistic to contemplate any shift in their designs toward the end users. Systems would become even more complex and testing and evaluation more expensive in order to make end users accept any system and patronize it.
Instead of recognizing from the beginning phases that reducing errors and risks to the safety and health of end users are the best marketing criteria for encouraging end users to adopt and apply a system systems are still being designed by different engineers who cannot relate to the end users because their training is not directed explicitly toward them.
What is so incongruous with the engineering curriculums to include course that target end users?
Why would not these curriculums include courses in occupational safety and health, consumer product liability, engineers as expert witnesses, the capabilities and limitations of human, marketing, psychophysics and experimental design?
Are the needs and desires of end users beneath the objectives of designing systems?
If that was true then why systems are constantly being redesigned, evaluated and tested in order to match the market demands?
Why do companies have to incur heavy expenses in order to rediscover the wheel that the basis of any successful design ultimately relies on the usefulness, acceptability and agreement with the end users desires and dreams?
Why not start from the foundation that any engineering design is meant for human and that designed objects or systems are meant to fit the human behavior and not vice versa?
What seem to be the main problems for implementing changes in the philosophy of engineering curriculums?
Is it the lack to find enough Human Factors, ergonomics and industrial psychologist professionals to teaching these courses?
Is it the need to allow the thousands of psychologists, marketing and business graduates to find debouche in the market place for estimating users’ needs, desires, demands and retesting and reevaluating systems after the damages were done?
May be because the Human factors professionals failed so far to make any significant impact to pressure government to be part and parcel of the engineering practices?