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TOPICS IN INCLUSIVE DESIGN FOR THE GRADUATE HUMAN
FACTORS ENGINEERING CURRICULUM
Clive D’Souza
Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, USA
The confluence of demographic trends in aging and disability prevalence, increased
expectations among workers and consumers with and without impairments, and greater reliance
on complex yet pervasive technologies (e.g., automation, internet of things) has resulted in an
increased emphasis on designing for human-system performance and accommodation across the
full spectrum of human abilities. Inclusive design or universal design (UD) is one of the few user-
centered design paradigms that advocate consideration for the full spectrum of human abilities,
including individuals with and without disabilities.
A graduate-level course was developed and implemented to introduce ergonomics and human
factors students to the UD paradigm and to UD goals and principles using select academic and
non-academic readings, and assignments related to multivariate statistics, field observations, and
design of experiments. The course placed an emphasis on the fundamentals and research base in
ergonomics in relation to UD research and practice, viz., topics related to variability in human
functioning and performance associated with anthropometry, biomechanics, perception and
cognition. Alongside the motivations for the course, this paper provides an overview of the course
objectives, topics covered, and some early lessons learned.
INTRODUCTION
A confluence of multiple factors in recent decades
has resulted in an emphasis on designing for human-
system performance across the full spectrum of human
abilities. Primary among these factors are demographic
trends in aging and disability prevalence. Better quality
and access to medical care, increased trauma survival,
and improved assistive device technologies have all
contributed positively to this effect.
Expectations for safe, accessible and equitable
products and environments have also increased as older
adults and individuals with disabilities have become
more independent and actively participate in
employment, educational and recreational opportunities.
Enforcement of federal accessibility legislation such as
the Americans with Disabilities Act has also been
instrumental in advancing the rights of vulnerable user
populations. Furthermore, complex technologies (e.g.,
automation, internet of things) have now become nearly
ubiquitous and instrumental in domains of employment,
education, healthcare, recreation, and successful aging.
Motivation
Ergonomics and human factors (E/HF) practitioners
today are expected to know how to quantitatively
evaluate artifacts and solutions to engineering design
problems across the full spectrum of human abilities,
including for people with diverse impairments.
Examples include domains of healthcare (e.g., home-
based care, medical device design, and patient safety
devices), transportation (e.g., older drivers, driverless
and autonomous vehicles) and occupational settings
(e.g., aging workforce issues, obesity and functional
work capacity).
The majority of E/HF courses on human
performance associated with anthropometry,
biomechanics, perception and/or cognition have focused
largely on the average, typical user (i.e., designing for
the norm; stemming from assumptions of homogenous
and normally distributed functional traits in users) or on
a specific sub-group such as older adults (e.g.,
gerontechnology) or persons with disabilities (e.g.,
assistive technology). E/HF graduate-level courses on
human variability and performance fail to provide a
unified framework for design accommodation that spans
occupational-, age-, and impairment-related factors (i.e.,
user groups such older adults, persons with sensory,
cognitive and physical impairments).
To address this gap in the graduate HFE curriculum,
a new course was developed and implemented titled
“Ergonomics for Inclusive Design” in an industrial
engineering (IE) program focusing on contemporary
ergonomics research and analysis methods relevant to
inclusive engineering design.
PRACTICE INNOVATION
Overview
Inclusive design or universal design (UD) is one of the
few user-centered design paradigms that advocates
consideration for the full spectrum of human abilities,
including individuals with and without disabilities
(Connell et al., 1997; Story, 1998). The course aimed to
prepare graduate students to critically analyze and
evaluate human and performance variability in the
context of E/HF and grasp its relationship to the UD
process. The emphasis on human variability from
occupational, aging, and impairment related influences
coupled with the blend of E/HF and inclusive design
research made the course unique from other graduate
courses in the HFE curriculum.
Course Content
The course introduced students to theoretical and
practical issues in human-system performance and
engineering design of products and environments that
arise when trying to accommodate human variability
resulting from occupational, aging, and impairment
related factors (i.e., older adults, persons with sensory,
cognitive and physical impairments).
The course content comprised modules that cover:
1) Ergonomics principles and fundamentals related to
inclusive design vs. design for the norm (Kroemer
2006; Steinfeld and Maisel, 2012).
2) Demographic and societal trends that necessitate
accommodating human performance variability
through engineering design.
3) Contemporary perspectives on aging and disability
as a social, cultural, historical and political
phenomenon. For example, the WHO’s
biopsychosocial model vs. the medical of disability.
4) Role of federal accessibility standards and
guidelines, and their strengths and limitations
(Salmen, 2011).
5) Survey of different engineering design paradigms to
accommodate human variability, viz.,‘design for the
norm’, UD, design for aging, assistive technology,
and lifespan design (e.g., Vanderheiden and Jordan,
2006).
6) Ergonomics research methods used in the literature
for cross-disability studies including field studies,
laboratory experiments, physical mock-ups and
environment simulations (Goodman-Deane et al.,
2014; Steinfeld, 2004), impairment simulations
(Cardoso and Clarkson, 2012), and digital human
modeling and simulation (Marshall et al., 2010).
7) Common impairments and measurement methods
related to anthropometry (e.g., Feathers et al., 2015),
biomechanics (i.e., mobility and manipulation; e.g.,
Schultz, 1992), perception (vision and hearing), and
cognition (memory, decision making; e.g., Diehl et
al. 1995).
8) Methodological challenges when investigating
human performance variability relating to
anthropometry, biomechanics, perception and
cognition.
Course Structure
The course structure comprised written reviews and
in-class discussions of peer-reviewed research articles on
topics related to individual modules. Readings and
discussions were supplemented with:
1) Homework assignments focused on problems in
engineering design that were cross-disability and
could be grasped by students from different
disciplines. These included problems in multivariate
statistics (e.g., anthropometry for multivariate design
accommodation) to reinforce theoretical concepts
using a combination of experimental (anonymized
research) data (based on Feathers et al., 2015), large
publicly available datasets (e.g. NHANES), and
experimental data directly collected by students in
naturalistic (outdoor) settings. In another instance
teams of 2-3 students had to design and conduct a
field-based observational study and recommend time
durations for 3 different types of road crossings in
order to accommodate pedestrians using walkers,
powered wheelchairs, manual wheelchairs, and
students distracted on cellphones.
2) Occasional guest lectures from industry experts to
emphasize real-world challenges and opportunities
in the domain of human variability. The guest
lectures focused on the themes of aging workers,
bariatric patient care, and inclusive mobility and
transportation - given all the excitement surrounding
autonomous vehicles and driverless cars.
3) A mid-term exam that evaluated students on their
ability to critically analyze a problem and integrate
theoretical concepts.
4) A team project to integrate and apply concepts to a
particular real-world context. Examples include
proposing a study design to evaluate the usability of
a product (such as interactive maps, on-campus
transit vehicles, home-care medical devices) to
accommodate users from multiple diverse groups
such as people with visual impairments, users of
wheeled mobility devices and older adults.
Course Outcomes
By the end of the course, it was expected that
students would be able to:
1) Understand and appreciate variability in human
physical and cognitive abilities and its implications
for engineering design,
2) Develop a working knowledge of human subjects’
research design and data analysis involving diverse
end-users in terms of age and functional limitations,
3) Critically evaluate the research literature in human
performance variability associated with
anthropometry, biomechanics, perception and
cognition,
4) Identify and evaluate human factors problems and
solutions from an inclusive design perspective.
FINDINGS
This course has been offered thrice, with an average
of 10 graduate students per offering. Preliminary
feedback from students was positive. Median scores for
course evaluation questions such as “I gained a good
understanding of concepts/principles in this field” and “I
deepened my interest in the subject matter of this
course” ranged between 4.1 to 4.7 on a scale of 5 (where
5 = strongly agree; 1 = strongly disagree).
The course also drew students from non-IE
disciplines such as mechanical engineering, biomedical
engineering, computer science, and design science. This
suggested a growing awareness of and interest in UD.
However, this raised new challenges. Some non-IE
students had never taken a graduate-level ergonomics
course. In such cases, optional reading materials were
provided as a refresher on relevant E/HF fundamentals
(e.g., Drury, 2005). The course also required a graduate
level understanding of statistics and design of
experiments – which was a concern for some non-IE
students and was alleviated by have students work on
homework assignments in 2-3 person teams.
Following the first offering, students did express
concerns about the reading load. A few research papers
were withdrawn in lieu of online news articles to
demonstrate real-world significance, challenges and
success stories to spur in-class discussion.
CONCLUSIONS
A graduate-level course was developed and
implemented to introduce E/HF students to UD. UD
goals and principles were operationalized by discussing
relevant E/HF research methods and statistical analysis
techniques to address human performance variability
stemming from different impairment- and age-related
factors. The course drew students from multiple different
engineering disciplines, suggesting a growing awareness
of and interest in UD. Preliminary feedback from
students was positive. This paper presented an overview
of the topics covered and some early lessons learned.
The author hopes that this paper will encourage
discussion about strategies for enhancing the E/HF
curricula to address the growing demand for UD and the
evolving role of E/HF practitioners in achieving
inclusion through design.
ACKNOWLEDGEMENT
The contents of this paper were developed under a
grant from the National Institute on Disability,
Independent Living, and Rehabilitation Research
(NIDILRR grant number 90IF0094-01-00). NIDILRR is
a Center within the Administration for Community
Living (ACL), Department of Health and Human
Services (HHS). The contents of this paper do not
necessarily represent the policy of nor endorsement by
NIDILRR, ACL, HHS, or the Federal Government.
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