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Human Factors Engineering

Dr. Osama Al Meanazel

Lecture 3

(Continuing Lecture 2)

September 17, 2013

Functional Flow Diagram

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Operation Sequence Diagram

Step 4: Interface Design Involves the design of human-machine and human-software interface

(design of workspaces, displays, controls, computer dialog, etc.)

During the interface design HF members of design team will perform 3

primary activities to support the design effort:

1. Gathering and interpreting Human Factors data.

2. Conducting Attribute Evaluations.

3. Conducting Human Performance Studies.

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Step 4: Interface Design1. Gathering and interpreting Human Factors data

Quantitative data (anthropometry). Qualitative data (common sense). Based on principles (research results). Mathematical functions (certain simulation models). Graphical representation (Nomographs). Judgment of experts. Design standards (for displays, controls, etc).

Considerations in applying Human Factors data. Practical Significance. Extrapolation to different situations Consideration of Risks. Consideration of Trade-Off functions

Step 4: Interface Design2. Conducting Attribute Evaluation

Use of checklists.

Walk-through evaluations.

Computer-aided design and evaluation aids.

3. Conducting Human Performance studies When the literature cannot supply the solution to a design problem, usually small

experiments are carried out.

Measurement of human performance such as time and errors in completing a task.

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Step 5: Facilitator Design (Operator SupportSystem Design) Plan for materials that will promote acceptable human performance

Instruction manual (on-line and hard copy)

Performance aids

Training devices (embedded training)

Use of Illustrations - by providing pictures and symbols. Picture - a realistic photograph or drawing of an object about which information is

to be conveyed. Symbol - a photograph or drawing that represents something else

Step 6:Testing and Evaluation Verify that the system is doing what it is supposed to.

Selection of subjects and dependent variables could influence the conclusions.

Testing could be in a laboratory environment or in the field .

Advantage of testing in the lab: easier to collect data, one can perform acontrolled study on different variables without any fear

from noise corruption the data.

Disadvantage of lab testing is the lack of face validity, tests not beingconducted in the real world setting.

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Human Factors Engineering

Dr. Osama Al Meanazel

Lecture 3

(Human Factors Research Methodologies)

September 17, 2013

Introduction

A state legislator suffered an automobile accident when anotherdriver ran a stop sign while talking on a cellular phone. Theresulting concern about cell phones and driving safety led thelegislator to introduce banning the use of cellular phones while

the vehicle is in motion. But others challenged whether the oneindividuals experience could justifya ban on all others cellularphones. After all, a single personal experience does notnecessarily generalize to all, or even most others. To resolve thisdebate, a human factors company was contracted to provide theevidence regarding whether or not use of cellular phonescompromise driver safety.

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Introduction Human Factors is in large part an empirical science

The central approach of human factors is the application of relevantinformation about human capabilities and behavior to the design of objects,facilities, procedures, and environments that people use

This body of relevant information is largely based on experimentation andobservations

In addition to gathering empirically based information and applying it to thedesign of things, human factors specialists also gather empirical data toevaluate the goodness oftheir designs and design of others

Introduction Empirical data, and hence research, play a dual role in the development

of systems: At the front end -- a basis for the design

At the back end -- as a means of evaluating and improving the design

Therefore, the main objective here is to introduce some of the purposes,considerations, and trade-offs involved in the research process.

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Overview Human factors research -- generally -- involves the use of human beings

as subjects

Human factors research can be classified into one of three types: Descriptive studies

Experimental research

Evaluation research

Although each category has different goals and may involve the use of

slightly different methods, all involve the same basic set of decisions: Choosing a research setting, selecting variables, choosing a sample of subjects,

deciding how the data will be collected, and deciding how the data will be analyzed

Descriptive Studies Descriptive studies seek to characterize a population in terms of certain

attributes

Examples: Dimensions of peoplesbodies

Hearing loss among people of different ages Peoples expectations as to how a knob should be turned to increase the value on a display Weights of boxes people are willing to lift

Descriptive studies are not very exciting, but they are very important to thescience of human factors.

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Descriptive Studies Why are descriptive studies important?

They represent the basic data upon which many design decisions are based.

They are usually carried out to assess the magnitude and scope of a problem beforesolutions are suggested

Experimental Research

The purpose of experimental research is to test the effects of somevariables on behavior

The decision as to what variables to investigate and what behaviors to

measure are usually based on either a practical situation whichrepresents a design problem, or a theory that makes a prediction aboutvariables and behaviors

Example: comparing how well people can edit manuscripts with partial-line, partial-page, and full-page computer displays

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Experimental Research Experimental research is usually concerned in whether a variable has an

effect on behavior and the direction of that effect

Although the level of importance is of interest, usually only the relativedifference in performance between conditions is of concern

Example: Subjects missed, on average, 15 more signals under high noisethan under low noise

Note: Descriptive studies are usually interested in describing apopulation parameter (i.e., mean, standard deviation, percentile), ratherthan assessing the effect of a parameter

Experimental Research Steps in conducting an Experiment

Defining the problem and hypotheses Specify the experimental plan Conduct the study Analyze the data Draw conclusions

Experimental designs: The Two-Group Design Multiple Group Design Factorial Design Between-Subject Design Within-Subject Design Mixed Design Multiple Dependent Variables Designs

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Example of a Simple Factorial Design Driving while talking on the cell phone example

Hypothesis?

What is the criterion measure in this case?

Experimental design?

How many groups?

Hypothetical scenario

Conclusions

Evaluation Research Evaluation research is similar to experimental research in that its

purpose is to assess the effect/goodness of something, and makerecommendations for improvement based on information collected

However, in evaluation research the something is usuallya system or aproduct

Evaluation research is also similar to descriptive research in that it seeksto describe the performance and behaviors of the people using thesystem or product

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Evaluation Research Evaluation research is generally more global and comprehensive than

experimental research: A system/product is evaluated by comparison with its intended goals

(both intended consequences and unintended outcomes).

It usually includes a benefit-cost analysis.

Evaluation research is the area where human factors specialists assess thegoodness of any design -- make recommendations for improvements

Examples: Evaluating new training program Evaluating new software package Evaluating an ergonomically designed life jacket

Choosing Research Setting Descriptive studies: the primary goal of descriptive studies is to generate data

that describes a particular population of interest Go to the real world -- however, actual data collection maybe done in a lab (often mobile

lab)

Experimental Research -- the choice of research settings here requirescomplex tradeoffs. Advantage: realism (in terms of task variables, environmental constraints, subjects

characteristics -- there is a better chance that the results obtained can be generalized tothe real-world operational environment.

Disadvantages: cost, safety hazards for subjects, and lack of experimental control

Combine the benefits of both laboratory and field research use simulationsof the real world (Physical/computer simulations)

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Choosing a Research Setting Evaluation Research -- as with descriptive studies, choosing a research

setting is somewhat moot

For a true test of the goodness of a system or device, the test should be conductedunder conditions representative of those under which the thing being tested willultimately be used

Example: a computerized map display of an automobile should be tested in anautomobile while driving over various types of roads and in different trafficconditions.

Selecting Variables Descriptive Studies -- two basic classes of variables are measured

criterion variables, and stratification (or prediction) variables

Criterion variables: grouped as physical characteristics (i.e., arm reach),performance data (i.e., reaction time), subjective data (i.e., opinion), and

physiological indices (i.e., heart rate).

Stratification variables: the use of stratified samples (samples that areproportionately representative of the population in terms of such characteristicsas: age, sex, education, etc).

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Selecting Variables Experimental Research -- independent variables (IVs) and dependent

variables (DVs)

IVs -- classified as task-related variables (size of boxes, work-rest cycles),environmental variables (noise), and subject-related variables (age)

DVs -- similar to criterion variables discussed earlier (performance, subjective, orphysiological)

Selecting Variables Evaluation Research:

Selecting variables for evaluating research requires the researcher to translate thegoals and objectives of the system/product being evaluated into specific criterionvariables that can be measured

The criterion variables are essentially the same as those used in descriptive studiesand experimental research, as discussed earlier

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Choosing Subjects Descriptive studies:

Sample should be representative (or unbiased) of a population

Sample should be selected randomly from the population

You can use some formulas to determine the number of subjects to use sample

size (based on the degree of accuracy desired, variance in the population, andstatistics being estimated)

Choosing Subjects Experimental Research:

The objective is to randomly select subjects that are representative of the people towhom the results will be generalized

Extra care should be taken into consideration while choosing sample size effect ofIVs on DVs -- it has been observed that the number of subjects is usually less thanwhat is used in descriptive studies

Evaluation Research -- the same considerations discussed before applyfor evaluation research.

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Data Collection Descriptive studies -- surveys and interviews are often used and data can

be collected in the field or in a lab

Experimental Research -- same as in descriptive, except for usingcomputer-based methods when conducting experiments in a controlledlaboratory environment

Evaluation Research -- often difficult, but the principle method is theobservation of users by researchers and interviewing users regardingproblems encountered and their opinion of the system/product

Data Analysis Descriptive studies -- fairly basic statistics are compared (standard

deviation, correlation, percentiles)

Experimental Research -- inferential statistical techniques are usually

required (ANOVA / MANOVA). We are usually concerned aboutstatistical significance

Evaluation Research -- depending on the amount of information andcomplexity of the system/evaluation process different statistical analysisare necessary.

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Criterion Measures In Research Criterion measures are the characteristics and behaviors measured in

descriptive studies, the DVs in experimental research, and the basis forjudging the goodness of a design in an evaluation research

Three types of criteria can be distinguished in the human factorsdomain:

System-Descriptive Criteria (reliability, cost of operation, weight) Task Performance Criteria (quality and quantity of output, performance time)

Human Criteria (Performance, subjective, and process)

Criterion Measures In Research Among the different types of criteria discussed earlier, there are usually

problems with those measures related to how human responds. Thosemeasures are as follows:

Performance measures (intensity, latency, duration measures, and reliability)

Physiological measures (cardiovascular like heart rate, respiratory like oxygenconsumption, nervous like muscle activity, and sensory like blink rate)

Subjective (opinions, ratings, or judgments)

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Requirements for Research Criteria Criterion measures used in research investigations generally should

satisfy certain requirements:

Practical requirements: a criterion measure should be objective,quantitative, unobtrusive, easy to collect with no special data collectiontechniques/instruments, and cost as little as possible

Psychometric requirements: are those of reliability, validity, freedomfrom contamination, and sensitivity.