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OCR for page 17
INTRODUCTION
1
Considerable efforts have been undertaken in the United States to
improve the public understanding of engineering (PUE). A survey
by the National Academy of Engineering (NAE) in 2002 of 177 orga-
nizations involved in public understanding of engineering activities
revealed that they spend an estimated $400 million annually (NAE,
2002). However, the actual national investment can be assumed to be
much higher, because the survey is believed to have reached only a frac-
tion of the institutions that have PUE initiatives.
Despite these efforts, the impact of engineering on our daily
lives, the nature of what engineers do, and the opportunities available
through an engineering education are still largely unknown to most
Americans. Educational researchers have found that k–12 teachers
and students generally have a poor understanding of what engineers
do (Cunningham and knight, 2004; Cunningham et al., 2005, 2006).
Polling data comparing scientists and engineers show that the public
sees engineers as being more responsible for creating economic growth
and preserving national security than scientists, as well as more likely
to make strong leaders. However, engineers are not perceived to be as
engaged with societal and community concerns or to play as great a role
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CHANGING THE CONVERSATION
in saving lives (Table 1-1). And when the relative prestige of all profes-
sions is tallied, engineering falls in the middle of the pack, well below
medicine, nursing, science, and teaching (Table 1-2).
Although engineers, engineering educators, and the organizations
that represent them want people to have more accurate and positive
impressions of them, there are other, more important reasons for
improving the public understanding of engineering. Some knowledge
about how engineering work is done, for example, is fundamental to
technological literacy. To be fully capable and confident in a technol-
ogy-dependent society, every citizen should understand something of
the process of engineering and how engineering and science, among
TABLE 1-1 Comparative Characteristics Associated with Engineers
and Scientists, 2003 and 1998
Don’t Decline to
Engineers Scientists Neither Know Answer
Creates economic growth
2003 69% 25% 2% 3% *
1998 51% 25% — 5% 1%
Preserves national security
2003 59% 29% 5% 6% 1%
1998 36% 22% — 9% 2%
Would make a strong leader
2003 56% 32% 6% 5% *
1998 47% 28% — 8% 3%
Saves lives
2003 14% 82% 1% 2% *
1998 6% 65% — 3% 21%
Is sensitive to societal concerns
2003 28% 61% 5% 5% *
1998 47% 57% — 8% 3%
Cares about the community
2003 37% 51% 5% 6% 1%
1998 24% 46% — 9% 12%
NOTE: Numbers from 1998 do not add up to 100 because respondents chose from
three answers: engineers, scientists, and technicians. Some numbers from 2003 do
not add to 100 due to rounding.
*Less than 1 percent.
SOURCE: Adapted from Harris Interactive, 2004.
OCR for page 19
Introduction
TABLE 1-2 Percent of Americans Who Rate Selected Professions as
Having “Very Great Prestige,” 2006
Profession Percent Profession Percent
Firefighter 63% Architect 27%
Doctor 58% Athlete 23%
Nurse 55% Lawyer 21%
Scientist 54% Entertainer 18%
Teacher 52% Accountant 17%
Military officer 51% Banker 17%
Police officer 43% Journalist 16%
Priest 40% Union leader 12%
Farmer 36% Actor 10%
Engineer 34% Stock broker 11%
Member of Congress 28% Real estate agent 6%
SOURCE: Adapted from Harris Interactive, 2006.
other factors, lead to the development of technologies (NAE and NRC,
2002; AAAS, 1990).
A number of important public policy issues, from global warming
to the marketing of genetically modified foods, involve scientific and
technical issues. Decision making on these and other topics will involve
trade-offs, as we attempt to simultaneously manage limited resources
while sustaining quality of life. Public discourse and the democratic
process could be enhanced if citizens understood more about how
engineers are trained and what the practice of engineering entails.
Technological literacy also is important to consumer decision making.
Americans are often the first adopters of new technologies, and part
of that acceptance depends on understanding the engineering process.
Thus improved public understanding of engineering could enhance
consumer decision making.
Improved public understanding of engineering may also support
U.S. efforts to maintain our capacity for technological innovation,
an issue that has received considerable attention recently (Council
on Competitiveness, 2004; NAS et al., 2007; PCAST, 2004). Although
there are many aspects of this challenge, two important conditions for
sustaining U.S. innovative capacity are improving undergraduate engi-
neering education (NAE, 2005a) and increasing investment in basic
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0 CHANGING THE CONVERSATION
engineering research (NAE, 2005b). Effective action in both areas will
depend partly on how well policy makers and the public understand
what engineering is and how it contributes to economic development,
quality of life, national security, and health—information that could
be conveyed through effective messaging.
A related concern is the rapid increase in scientists and engineers in
other nations, particularly China and India. For example, the number
of graduates with four-year degrees in engineering, computer science
(CS), and information technology (IT) in China more than doubled
from 2000 to 2004 (Wadhwa et al., 2007). However, because of differ-
ences in methods of data collection and in defining engineering, it is
difficult to compare the absolute numbers of four-year engineering
degrees awarded in China and India to those awarded in the United
States. In the 2003–2004 academic year, for bachelor’s degrees in engi-
neering, CS, and IT combined, Wadhwa et al. (2007) estimate that the
United States graduated 137, 437, India 139,000, and China 361,270.
The overall number of engineering degrees granted in the United
States, which had been dropping, has gone up in recent years, although
not to its historic high in 1985 (Figure 1-1). According to one estimate,
80,000
75,000
70,000
65,000
60,000
55,000
50,000
1983 1985 1987 1989 1991 1993 1995 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006
NSF S&E Indicators ASEE Data w/o CS
FIGURE 1-1 Engineering bachelor’s degrees awarded in the United States,
1983–2006. 1-1.eps
NOTE: Bachelor’s degrees in computer science (CS) have been subtracted from the
original ASEE data (Gibbons) to ensure comparability with NSF data.
SOURCES: Gibbons, 2006; NSF, 2006a.
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Introduction
the U.S. engineering workforce is expected to increase by 13 per-
cent from 2004 to 2014 (CPST, 2006). However, the accuracy of this
projection will be affected by several factors, such as participation
levels of foreign-born individuals in the U.S. engineering enterprise,
the off-shoring of U.S. engineering jobs (NAE, 2008), and engineer
retirements in such sectors as defense and aerospace. Thus it is very
difficult to predict the long-term demand or supply of engineers in the
United States.
Although researchers and policy makers disagree on the nature and
extent of the engineering “shortage” in the United States, few dispute
the need to attract capable students, especially girls and certain minori-
ties, into technical careers. Women, African Americans, Hispanics,
Native Americans, and some Asian American groups are significantly
underrepresented in engineering, based on their proportions in the
population at large (Box 1-1). If current demographic trends continue,
by 2050 almost half the U.S. population will be non-white (U.S. Cen-
sus Bureau, 2002). In the future, engineering solutions will have to be
acceptable to this increasingly diverse population, and the engineering
profession will have to draw more heavily on underrepresented groups
for the country to maintain, let alone increase, its technological capa-
bility (NAE, 2004). Thus messages that effectively encourage girls and
underrepresented minorities to consider careers in engineering could
be crucial to U.S. success and leadership in the future.
MESSAGES TO PROMOTE ThE PUBLIC UNDERSTANDING
OF ENGINEERING
In the NAE report Raising Public Awareness of Engineering (2002),
“message,” in the context of public relations, was defined as “a state-
ment that helps convey a positive image, usually either of a company or
a specific product.” In well-designed communications strategies, mes-
sages are repeated over time, because public perceptions are influenced
most by repeated exposure to consistently expressed ideas. Although
neither engineering nor the public understanding of engineering
is a corporate entity or—strictly speaking—a product, messaging is
nevertheless germane in this context. Indeed, effective messaging is a
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CHANGING THE CONVERSATION
BOX 1-1
Selected Data for Women, African Americans,
Hispanics, and Native Americans in Engineering
Women
50.7 percent
Proportion of U.S. population, 2005 (est.):
Proportion enrolled in degree-granting
57.4 percent
institutions, 2004:
Proportion of bachelor’s degrees in engineering,
20.5 percent
2004:
Proportion of tenured/tenure-track appointments on
10.6 percent
U.S. engineering faculties, 2005:
11.0 percent
Proportion employed as engineers, 2003:
African Americans
12.8 percent
Proportion of U.S. population, 2004:
Proportion enrolled in degree-granting institutions,
12.5 percent
2004:
Proportion of bachelor’s degrees in engineering
5.3 percent
earned, 2004
Proportion of tenured/tenure-track appointments
2.3 percent
on U.S. engineering faculties, 2005:
3.1 percent
Proportion employed as engineers, 2003:
Hispanics
14.1 percent
Proportion of U.S. population, 2004:
Proportion enrolled in degree-granting institutions,
10.5 percent
2004:
Proportion of bachelor’s degrees in engineering, 2004: 7.4 percent
Proportion of tenured/tenure-track professors on
3.2 percent
U.S. engineering faculties, 2005:
4.9 percent
Proportion employed as engineers, 2003:
Native Americans
1.0 percent
Proportion of U.S. population, 2004:
Proportion enrolled in degree-granting institutions,
1.0 percent
2004:
Proportion of bachelor’s degrees in engineering,
0.6 percent
2004:
Proportion of tenured/tenure-track professors on
0.2 percent
U.S. engineering faculties, 2005:
0.3 percent
Proportion employed as engineers, 2003:
SOURCES: NSF, 2005a, b, 2006a, b; U.S. Census Bureau, 2002, 2005;
DOEd, 2006a, b.
OCR for page 23
Introduction
necessary—although not a sufficient—method of promoting public
understanding of engineering efforts.
The 2002 NAE report catalogs a large number of messages on a
variety of themes that organizations involved in public understanding
of engineering have used to promote their activities. The four major
themes are: the value and nature of engineering and engineers; the aca-
demic skills necessary to pursue engineering as a career; employment
opportunities in engineering; and the connection between engineering
and quality of life.
The number and variety of messages leads to several conclusions.
First, no apparent effort has been made in the engineering community
to develop consistent messages. Second, few organizations involved in
promoting public understanding of engineering have developed their
messages in a systematic, scientific way or tested the effectiveness of
their messages. Third, no convincing evidence shows that messaging
efforts to date have significantly improved public understanding of
engineering.
We know that a public image is not “everything,” as the advertise-
ment for Nikon cameras asserted more than a decade ago, but neither
is it inconsequential. In the case of engineering, data collected for this
project show that the public view of engineering is not strongly nega-
tive. At the same time, the data suggest that public perceptions of engi-
neering are based on a limited idea of what it takes to do engineering
(e.g., skill in mathematics and science) rather than what it means to be
an engineer (e.g., to work creatively in teams to develop technologies
that improve people’s lives).
PRIMER ON MARKET RESEARCh: LExICON AND METhODS
A professional marketing firm was hired to ensure that the com-
mittee took a professional approach to improving public understand-
ing of engineering. In addition, committee members were obliged to
learn marketing terminology. Learning the vocabulary for any subject
requires not only memorizing terms, but also acquiring an understand-
ing of the underlying concepts and methodology. In this section, we
outline the essential terms and marketing concepts the committee used
in preparing this report and recommendations.
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CHANGING THE CONVERSATION
Definition of a Brand
In this project, we were looking for the best way to brand engineer-
ing. Although the word brand seems familiar, it is used in a specific
way in this report. By brand we mean an association of specific traits
in a person’s mind that induces behavior. A simple way of understand-
ing this concept might be as a warranty—a promise to perform or
deliver. For example, the McDonald’s brand promises clean restau-
rants and food of a known quality. We use this brand as a shortcut
in decision making. For example, when traveling on the road, we rely
on McDonald’s promise to provide a quick, adequate meal. The same
thing happens with brands in a grocery or hardware store. As we shop,
we make quick judgments based on a brand’s promise or warranty.
Contemporary marketing practice and theory support brand-
ing that goes beyond traditional ideas of a product. For example,
entire industries have attempted to remake their public image using
branding techniques. The dairy industry’s “Got Milk” campaign
(www.bodybymilk.com) uses well-known sports and entertainment
figures to cultivate a wholesome brand image for milk drinkers.
Similarly, the cotton industry’s “Fabric of Our Lives” campaign (www.
thefabricofourlives.com) ties a broad range of cotton-based products to
aspects of daily life. Marketing has been used by public health officials
to brand desirable behaviors, such as healthy eating in adults (i.e., the
Food and Drug Administration’s “Calories Count” campaign; FDA,
2004) and exercise in children (i.e., the Centers for Disease Control and
Prevention’s “Verb, It’s What You Do” campaign; www.verbnow.com).
Some professions have a clear brand identity. Physicians, for
examples, are “healers.” Teachers are “educators.” For professions
that do not have a clear brand identity, the public may provide one.
Lobbyists and others operating in the political sector can be known as
“influence peddlers.” And for those in public relations, derisive terms
like “flack” and “spin doctor” are common. In the case of engineering,
although negative terms like “nerd” and “boring” are part of the brand
image, our research and research by others indicate the larger problem
is a lack of understanding of what engineers do rather than a negative
impression of the field. The actuarial field has a similar concern and has
undertaken branding efforts to better communicate to the public how
OCR for page 25
Introduction
actuaries add value (Beuerlein, 2006). Nurses in the United kingdom,
concerned about their relatively low status and poor image, recently
launched a “Nursing the Future” campaign (www.nursingthefuture.
org.uk/index.php). To attract students and counter the stuffy image of
accountants, the American Institute of Certified Public Accountants
developed the “Start Here Go Places” campaign (www.startheregoplaces.
com).
In this study, we considered the following brand attributes: brand
message, the promise the brand communicates; brand image, how the
brand is marketed; and brand experience, how the message is brought
to life and made concrete.
The Positioning Statement
A positioning statement is essential for creating a brand. It lays out
how one wants the brand to be perceived and provides the core mes-
sage to be delivered in every medium. A typical positioning statement
answers seven core questions about a brand:
1. Who are you?
2. What business are you in?
3. What people do you serve?
4. What are the special needs of the people you serve?
5. Who are your competitors?
6. What makes you different from your competitors?
7. What unique benefit does a user derive from your service or
product?
To illustrate how a position statement works, consider a high-end
store like Bloomingdale’s. The position statement (Beckwith, 1997)
reads:
Bloomingdale’s (who) is a fashion-focused department store (what
business) for trend-conscious, upper-middle-class shoppers (who served)
looking for high-end products (special needs). Unlike other department
stores (competitors), Bloomingdale’s provides unique merchandise in a
theatrical setting (the difference), which makes shopping entertaining
(unique benefit).
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CHANGING THE CONVERSATION
Note that this statement never appears explicitly in Bloomingdale’s
ads or marketing. The purpose of a positioning statement is to guide
decisions about how to deliver a brand message. A marketing firm
uses the statement to create the elements of a campaign. For example,
Bloomingdale’s highlights items in its ads and creates displays in its
stores that reinforce the idea of “shopping entertainment.”
A positioning statement, of course, applies not only to traditional
stores like Bloomingdale’s, but can also be a powerful tool, for example,
in a high-tech industry. In 1991, Intel Corporation launched a brand
campaign for its computer processors. At the time, few consumers had
any idea what a microprocessor was, let alone a strong brand identifica-
tion or preference for a particular type of processor. Most consumers
cared as much about who made their processors as they did about who
built the engines in their cars.
This presented a dilemma for Intel, which wanted to reap the
benefits of its advances in chip design. So, the firm decided to brand
its processors, thus linking Intel and its innovations. This was a revo-
lutionary idea, because at the time, consumers knew next to nothing
about microprocessors. A measure of the campaign’s success is that
today people discuss the speed of their processors, and even mention
their name.
We can imagine Intel using something like the following posi-
tioning statement, which we crafted based on the history of the Intel
Inside® Program (Intel Corporation, 2008), to create its brand:
Intel (who) produces microprocessors (what business) for end users of
personal computers (who served) looking for the best technology (special
need) linking words like “leading technology” and “reliability” (unique
benefit) with Intel microprocessors rather than other producers of micro-
processors (competitors).
Messages and Taglines
The key elements of messaging campaigns, like Bloomingdale’s
and Intel’s, are messages and taglines, which are easily confused. The
message, the longer and more detailed of the two, is often a complete
sentence that clearly articulates a brand promise. For example, the mes-
sage of Anadin™, a pain killer, makes an explicit promise in, “Nothing
OCR for page 27
Introduction
acts faster than Anadin™.” In contrast, a tagline is a short phrase, rarely
a complete sentence, that creates an image in the consumer’s mind.
One committee member described taglines as “concretely vague,”
somewhat like a Madison Avenue haiku that resonates emotionally
with consumers.
Intel’s now-ubiquitous tagline is “Intel Inside,” which cleverly
draws attention to a tiny, rarely seen, but essential component of the
computer “brain.” Ford Motor Company’s tagline for its Lincoln Town
Car is “Signature of Success,” which taps into the self-image of con-
sumers who might purchase these luxury cars.
Two examples from this project can help clarify the differences
between messages and taglines. As noted above, we engaged a market-
ing firm to develop and test engineering messages and taglines. One
message we tested was:
Engineers make a world of difference. From new farming equipment and
safer drinking water to electric cars and faster microchips, engineers use
their knowledge to improve people’s lives in meaningful ways.
One of several taglines we tested reads:
Because dreams need doing
To develop and test messages and taglines, the marketing company
conducted research in the form of focus groups and surveys.
The Role of Research
Marketing research suggests reasonable actions to take in creating
a brand, rather than charting a definitive course to success. Much like
social science research, marketing research reveals trends that can sim-
plify a complex whole by breaking it into manageable parts. Research
does not tell us which branding elements to use, but it provides insights
that inform, rather than replace, decision making. Marketing research
serves two main purposes in creating a branding campaign.
First, marketing research reveals how prospective consumers per-
ceive a product or service. One might naively assume that a firm can
state a position and then broadcast that position in all of its marketing.
In reality, a marketer does not create a position de novo, but links a new
position to an old position that already exists in the consumer’s mind.
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CHANGING THE CONVERSATION
For example, in the 1960s, Avis wanted to let potential customers
know that it offered better service than Hertz, the top rental-car com-
pany, but research revealed that consumers did not find this claim
credible. In fact, consumers always thought of Avis as second to Hertz.
In an ingenious advertising campaign, Avis used the tagline, “We’re
number two, so we try harder.” Because this tagline connected to an
idea already in consumers’ minds, it instantly resonated with them, and
Avis’ revenues skyrocketed (Wall Street Journal, 1969). This is a clear
example of how a marketing firm used research to get a good picture
of the messaging landscape and created a tagline that linked a new
position to an old one.
The second way marketing firms use research is to test messages
and taglines. Testing can reveal the most popular or appealing brand
elements, but more important, it can reveal unanticipated problems.
For example, a tagline that appeals to a marketer and client may have
unintended negative connotations for the target audience.
In our research, we were particularly interested in developing an
exhaustive, fine-grained description of the perceptions of different
groups about engineering as a profession. This required the systematic
collection of data from well-defined sample groups using standardized
questionnaires that would provide a basis for making comparisons.
The paramount criteria for evaluating all social science research
are validity and reliability. Validity means that our results tap into the
underlying behaviors or attitudes we want to measure. Can a survey
questionnaire, for example, adequately assess people’s complex atti-
tudes toward engineering? Reliability, on the other hand, refers to con-
sistency of measurement. Can we administer the same questionnaire
consistently to a large number of respondents, for instance, without
contaminating our results because of differences in how the interviews
were conducted?
All researchers must make trade-offs between reliability and valid-
ity. Standardized surveys are very reliable in how they are administered
and in how they measure underlying constructs, such as attitudes and
behaviors. At the same time, their validity is limited, because they
reduce complex attitudes to short questions with answers that are often
forced into predefined numerical scales.
OCR for page 29
Introduction
The problem is often reversed for focus groups and other quali-
tative methods, which enable us to explore behaviors and attitudes
in great depth and include a good deal of contextual information.
Therefore, they produce more valid results than standardized surveys.
However, the very fact that they take into account individual differences
and complexities diminishes their reliability for comparisons among
different groups. The fact that we used a semi-structured interview
protocol for the focus groups corrected somewhat for this limitation.
For our project, therefore, we “triangulated” these methods, com-
bining qualitative approaches, such as focus groups, with quantitative
data collection using systematic population surveys. This enabled us
to leverage the specific advantages of each method in terms of reli-
ability and validity and, at the same time, minimize their weaknesses
by comparing results. (The committee discusses other technical issues,
including factors that affect generalizability of data, in an annex to this
chapter.)
ThE NAE MESSAGING PROjECT
This project is based on the hypothesis that concise, effective
messaging can help correct misconceptions about, and improve the
image of, engineers and engineering. Effective messages will be a
compelling and consistent way for the engineering community to
promote itself to diverse audiences. NAE recognizes that effective mes-
sages are a critical (but not sufficient) element in cultivating greater
public awareness. Messaging must be a component in a sustained
engineering-community-wide campaign that also includes improving
undergraduate engineering education and increasing investment in
basic engineering research.
Goal and Objectives of the Project
The stated goal of this project, funded by the National Science
Foundation (NSF) and small, supplemental grants from the Georgia
Institute of Technology and the S.D. Bechtel, Jr. Foundation, is to
encourage coordinated, consistent, effective communication by the
engineering community about the role, importance, and career poten-
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0 CHANGING THE CONVERSATION
tial of engineering to a variety of audiences, including school children,
parents, teachers, and counselors. The project hopes to achieve three
specific objectives:
• Identify a small number of messages that appear likely to lead
to a better understanding of engineering.
• Test the effectiveness of these messages in a variety of audiences.
• Disseminate testing results to the engineering community.
This project did not have the goal of developing metrics for measur-
ing the effectiveness of messaging efforts. Nevertheless, it is reasonable
to ask what one might look for as evidence of “improvement” in public
understanding of engineering. One indicator of improvement would
be the number and diversity of organizations using this report to shape
their engineering outreach. Over time, we would hope to see growth in
this set of organizations, and that might be measured through surveys
of the engineering community. The committee believes that effective
messaging will equip people with a positive and authentic vocabulary
for describing and thinking about engineering. In addition, effective
messaging should have an impact on student views about engineering
as a career option. One approach for gathering this kind of informa-
tion would be a longitudinal study, combined with “dipstick” surveys
before, during, and after the deployment of new messages. Such a study
could determine the extent to which the public recognizes the new
messages or associates certain key words, such as creativity, with engi-
neering, and it could probe students for how messages are influencing
their views about career and college choice. Less direct evidence of
impact might be obtained by tracking changes in responses to periodic
national surveys, such as those on professional prestige conducted by
Harris Interactive; commissioning new surveys, for example, of high
school students views about engineering; or analyzing factors leading
to changes in enrollments in engineering schools.
OCR for page 31
Introduction
Public Outreach
During the course of this project, the committee solicited feedback
in two ways. First, committee members and project staff made presen-
tations about the project at meetings where the topic of public under-
standing of engineering was likely to resonate. These events included
the April 2007 meeting of the NAE Council; the annual Convocation
of Professional Engineering Societies and the NAE in May 2007, which
brought together the presidents, presidents-elect, and executive direc-
tors of major national engineering professional associations to discuss
issues of mutual interest; the May 2007 and April 2008 meetings of the
advisory committee to the Engineering Directorate of the NSF, which
funded the project; the June 2007 annual meeting of the American
Society for Engineering Education; and the January 2008 meeting of
the Association of Independent Technical Universities. At each event,
the goals and research findings of the project generated considerable
discussion.
To obtain feedback from a wider cross section of the engineering
community and the general population, in March 2007 the commit-
tee posted a report by the project consultants, Bemporad Baranowski
Marketing Group/Global Strategy Group, on the NAE website that
provided background material and summarized the findings of the
qualitative research and the survey’s initial sample. (Results of the
oversamples of African American and Hispanic teens and adults were
not available until June, too late to allow for public comment.)
The committee notified a number of groups about the posting,
including NAE members; the National Academies Teacher Advisory
Council; a number of engineering societies (e.g., American Society of
Mechanical Engineers, Institute for Electrical and Electronics Engineers,
American Society of Civil Engineers, National Society of Professional
Engineers, National Society of Black Engineers, Society of Women
Engineers, American Society of Engineering Education); the Inter-
national Technology Education Association, which represents k–12
technology education teachers; the Association of Science-Technology
Centers, which represents many science and technology museums; and
the National Association for College Admission Counseling.
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CHANGING THE CONVERSATION
From March through June 2007, the committee received com-
ments on the consultants’ report from more than 80 organizations
and individuals. The great majority of these were from engineers,
including 10 NAE members, three deans of schools of engineering, and
individual engineers who teach in universities or work in industry. The
committee also received comments from a handful of k–12 teachers,
mostly teachers of technology, mathematics, and science.
The comments included a number of suggestions for using the
messages, arguments in favor of particular messages, and proposals
for conducting a large-scale campaign to improve public understand-
ing of engineering. There were also a number of insightful comments
on issues not directly considered in this project, such as the lack of
opportunities for k–12 students to study engineering and the quality of
post-secondary engineering education. Where appropriate, references
to these comments are included in the committee’s report.
The Report
Chapter 2 describes the committee’s efforts to develop a position-
ing statement and preliminary message themes as guidelines for the
research phase of the project. Chapter 3 presents the results of that
research. Chapter 4 provides the committee’s conclusions and rec-
ommendations. Appendix A contains short biographies of commit-
tee members, Appendix B is the moderator’s guide for the in-depth
interviews, Appendix C is the moderator’s guide for the parent focus
groups, Appendix D is the moderator’s guide for the teen focus groups,
Appendix E is the moderator’s guide for the youth triads, and Appendix
F is the online survey. A separate CD contains complete data tables for
the online survey and a PDF version of the full report.
REFERENCES
AAAS (American Association for the Advancement of Science). 1990. Chapter 3,
The nature of technology, and Chapter 8, The designed world in Science for All
Americans. New York: Oxford University Press.
Beckwith, H. 1997. Selling the Invisible: A Field Guide to Modern Marketing. New York:
Warner Books.
OCR for page 33
Introduction
Beuerlein, R. 2006. One voice, one brand. Presidential address. The Actuary Maga-
zine. April/May 2006. Available online at http://www.soa.org/library/newsletters/
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ANNEx
GENERALIZABILITy OF SURvEy DATA
Generalizability, the capability of making inferences from a sample
to the target population, is an essential aspect of survey research. The
most commonly used inferential statistic is sampling tolerance, often
called the margin of error. We prefer the former term, because the
margin of error suggests, incorrectly, that there is something wrong
with the data, whereas sampling tolerance refers to the difference
between results from the sample and results anticipated in the target
population as a whole.
Sampling tolerance varies by the size of the sample (the larger the
sample, the smaller the tolerance) and the reported percentage response
to a particular survey question (the closer the response percentage is
to 50 percent, the larger the sampling tolerance). Table 1-3 illustrates
how these factors affect tolerance for individual data points. Sampling
tolerances are often expressed as plus or minus values (+/–), or ranges,
around the data point of interest.
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CHANGING THE CONVERSATION
TABLE 1-3 Sampling Tolerances for Single Samples
Reported Percents
Sample Size 10% or 90% 20% or 80% 30% or 70% 40% or 60% 50%
100 5.9 7.8 9.0 9.6 9.8
200 4.2 5.5 6.4 6.8 6.9
300 3.4 4.5 5.2 5.5 5.7
400 2.9 3.9 4.5 4.8 4.9
500 2.6 3.5 4.0 4.3 4.4
600 2.4 3.2 3.7 3.9 4.0
700 2.2 3.0 3.4 3.6 3.7
800 2.1 2.8 3.2 3.4 3.5
900 2.0 2.6 3.0 3.2 3.3
1000 1.9 2.5 2.8 3.0 3.1
1500 1.6 2.0 2.4 2.5 2.6
2000 1.3 1.8 2.1 2.2 2.2
5000 0.8 1.1 1.3 1.4 1.4
SOURCE: ICR, 2007.
Our surveys had a 95 percent confidence level, the industry stan-
dard. This means that we can be 95 percent certain that the value for
the true population falls somewhere within the margin of error around
what we observed in our sample. For example, as Table 1-3 shows, for
a sample of 600 people, if 20 percent chose a particular answer choice,
the sampling tolerance would be +/– 3.2 percent, and the answer range
would be between 17.8 percent and 23.2 percent. This means that we
can predict with 95 percent certainty that the percentage of individuals
in the population we drew our sample from fall within the calculated
range. The same principle applies when two data points are compared,
although the calculation is more involved, particularly if the sample
sizes vary. In this case, the difference between the numbers is consid-
ered statistically significant if it exceeds the sampling tolerance.
The correct calculation of inferential statistics depends on each
respondent having the same, known chance of being selected into the
sample. For example, to survey the opinions of the U.S. population as
a whole, the survey sample would include representative numbers of
people, in terms of age, gender, race or ethnicity, and geographic loca-
tion, just to name the most obvious demographic markers. Such sam-
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Introduction
ples are usually referred to as probability samples. Because we relied on
respondents who were members of volunteer survey panels, we could
not control who chose to take part in our survey. Thus our responses
do not reflect exactly the demographics of the populations we were
sampling, and our samples are technically not probability samples.
This is a common occurrence in surveys that is typically handled by
weighting, or propensity scoring, a process by which survey responses
are adjusted upward or downward to match the actual demographic
variable of interest. Weighting is often based on population data from
the U.S. Census Bureau. For instance, if there were only 25 women
in a sample of 100 people and we were interested in comparing the
answers of women and men, the value of women’s responses would
be adjusted upward to reflect their true proportion in the population,
slightly more than 50 percent in the United States; the men’s responses
would be adjusted downward. Because most leading market research
firms use pre-recruited panels, post-survey weighting is almost always
necessary.
There are several aspects of our survey method that might affect
generalizability. First, because our survey required respondents to have
Internet access, we could not include people who did not have access.
Currently, about 73 percent of American adults report having regular
access to the Internet (Madden, 2006). The number of teen users is
higher, 87 percent in 2005 (Lenhart et al., 2005). We recognize that
people who do not have Internet access might have different views
about engineering than those who do have access.
A second aspect of our survey method that might affect generaliz-
ability involves the participation of minorities in general-population
surveys. Minorities have traditionally been less likely to respond to
sample surveys. Factors that may explain their underrepresentation
include disengagement from the issues, lower levels of literacy, and
inadequate contact information, which makes it less likely that they will
be included in sampling frames (Sheldon et al., 2007). Although the
minority gap is closing (Crocket and Ante, 2007), it remains a problem
for survey researchers.
Because one of our major goals is to develop messages that tar-
get traditionally underrepresented groups, we adopted a two-step
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CHANGING THE CONVERSATION
approach to overcoming the minority gap. The first step was to conduct
an initial survey of the age groups of interest. Not surprisingly, African
Americans and other minorities were underrepresented in this sample,
as compared to the general population.
We, therefore, secured funding to field our survey in oversamples
of African American and Hispanic respondents. The additional sam-
ples provided us with comparison groups to the general population.
There were enough respondents in each group to make statistically
valid inferences.
A third issue that may have affected generalizability was that NAE
was identified as the sponsor of the research in the materials provided
to survey respondents at the beginning of the questionnaire. This was
necessary for securing fully informed consent from respondents, but it
may also have influenced the responses to one or more questions. All
of our results are interpreted with this caveat in mind.
Finally, in any survey, some people choose not to participate. The
reasons for non-responses vary but can include disinterest in or aver-
sion to the survey topic or discomfort with the survey methodology
(e.g., keyboarding in an Internet-based survey). Because non-responses
change the representativeness of a sample, the rate of non-response can
affect generalizability. Some surveys—but not ours—try to correct for
non-responses by contacting non-responders outside of the survey
process to determine their reasons for not participating. Couper (2000)
provides a good overview of this and other issues related to Web-based
surveys.
