History and philosophy

INVITED P A P E R

Five Major Shifts in 100 Years of Engineering Education The authors discuss what has reshaped, or is currently reshaping, engineering

education over the past 100 years up until the current emphasis on design,

learning, and social–behavioral sciences research and the role of technology.

By Jeffrey E. Froyd, Fellow IEEE, Phillip C. Wankat, and Karl A. Smith

ABSTRACT | In this paper, five major shifts in engineering education are identified. During the engineering science revo-

lution, curricula moved from hands-on practice to mathemat-

ical modeling and scientific analyses. The first shift was

initiated by engineering faculty members from Europe; accel-

erated during World War II, when physicists contributed mul-

tiple engineering breakthroughs; codified in the Grinter report;

and kick-started by Sputnik. Did accreditation hinder curricular

innovations? Were engineering graduates ready for practice?

Spurred by these questions, the Accreditation Board for

Engineering and Technology (ABET) required engineering

programs to formulate outcomes, systematically assess

achievement, and continuously improve student learning. The

last three shifts are in progress. Since the engineering science

revolution may have marginalized design, a distinctive feature

of engineering, faculty members refocused attention on cap-

stone and first-year engineering design courses. However, this

third shift has not affected the two years in between. Fourth,

research on learning and education continues to influence

engineering education. Examples include learning outcomes

and teaching approaches, such as cooperative learning and

inquiry that increase student engagement. In shift five, tech-

nologies (e.g., the Internet, intelligent tutors, personal compu-

ters, and simulations) have been predicted to transform

education for over 50 years; however, broad transformation

has not yet been observed. Together, these five shifts

characterize changes in engineering education over the past

100 years.

KEYWORDS | Accreditation; design; engineering education; engineering science; instructional technologies; learning

I . I N T R O D U C T I O N

In the 100 years since the founding of the Proceedings of

the IEEE, continual interest in engineering education has

led to five major shifts. Two of them have been completed.

First, following World War II and the formation of the

National Science Foundation (NSF), the engineering science revolution that changed the nature of engineering

curricula and the jobs of engineering professors occurred.

Second, in the late 1990s and early 2000s, based largely on

the actions of the Accreditation Board for Engineering and

Technology (ABET), engineering education and accredi-

tation became outcomes based. The three shifts that are

still in progress are: 1) a renewed emphasis on design; 2) the

application of research in education, learning, and social- behavioral sciences to curricula design and teaching methods;

and 3) the slowly increasing prevalence of information, com-

munication, and computational technologies in engineering

education.

In addition to marking the 100th anniversary of the

Proceedings of the IEEE, 2012 is the centennial of the

founding of the Institute of Radio Engineers (IRE), which

merged with the American Institute for Electrical Engi- neering (AIEE) to form the IEEE about 50 years ago. The

IRE Transactions on Education was founded in 1958 and

became the IEEE Transactions on Education in 1963.

What were concerns of electrical engineers when the

IRE Transactions on Education was founded in 1958?

Some concerns sound amusingly archaic, such as worry

about Russia’s superior education system [1], [2], low pay

of professors and their penury during retirement [2], [3], need for government research funds even though very few

engineering professors will be interested [2], and assuming

students are men. Some sound very familiar and easily fit

Manuscript received February 2, 2012; accepted February 8, 2012. Date of publication

April 17, 2012; date of current version May 10, 2012.

J. E. Froyd is with Texas A&M University, College Station, TX 77843-1372 USA (e-mail: [email protected]).

P. C. Wankat is with the School of Engineering Education, Purdue University, West Lafayette, IN 47907 USA (e-mail: [email protected]).

K. A. Smith is with Purdue University, West Lafayette, IN 47907 USA and the University of Minnesota, Minneapolis, MN 55455-0213 USA (e-mail: [email protected]).

Digital Object Identifier: 10.1109/JPROC.2012.2190167

1344 Proceedings of the IEEE | Vol. 100, May 13th, 2012 0018-9219/$31.00 �2012 IEEE

into Cheville’s snapshot of the current state of engineering education [4]. Familiar items include the importance of

fundamentals [1], the need for funds to replace lab equip-

ment [5], the inclusion of K-12 in educational interests [5],

the need to relate educational concepts to what a student

already knows [6], and the challenge of completing an

electrical engineering degree in four years [6]. Some still

appear visionary [7], which we will discuss later.

Since 1958, the IRE and then the IEEE Transactions on Education, the Proceedings of the IEEE and other

engineering education journals, such as the Journal of Engineering Education, have focused on many other issues that are important in engineering education, including

what content should be taught and how it should be taught,

accreditation, design, engineering education research, and

the use of technology in engineering education. Pedagog-

ical threads will be woven into the remainder of this paper. The five major shifts in engineering education that

have occurred during the past 100 years are:

1) a shift from hands-on and practical emphasis to

engineering science and analytical emphasis;

2) a shift to outcomes-based education and

accreditation;

3) a shift to emphasizing engineering design;

4) a shift to applying education, learning, and social- behavioral sciences research;

5) a shift to integrating information, computational,

and communications technology in education.

The first two shifts have already occurred, but they

continue to have implications for engineering education.

The latter three are still in process, and sustained in-

fluences on practice are difficult to forecast.

I I . F I R S T M A J O R S H I F T : E N G I N E E R I N G S C I E N C E , A N A L Y T I C A L E M P H A S I S

The first major shift in engineering education in the

United States occurred in the period 1935–1965 as

BStanford and other American engineering schools began replacing machine shop, surveying, and drawing classes

with science and mathematics courses[ [8]. Engineering curricula moved from hands-on, practice-based curricula

to ones that emphasized mathematical modeling and

theory-based approaches. Foundations for the shift were

established by many European engineers and engineering

faculty members, e.g., Timoshenko, von Karman, and

Westergard, who immigrated to the United States and

introduced European approaches to engineering education

[8]–[10]. This change toward more math and science was accelerated by experiences in World War II, when engi-

neers generally did not perform as well as physicists in

solving unusual problems [8]. For example, Seely noted

that BFrederick Terman, an electrical engineer who had specialized in radio and spent the war at the Radiation

Laboratory at MIT, was not the only engineer irritated that

physicists received most of the credit for wartime research

accomplishments. But he also recognized that many engi- neers had been ignorant of the science underlying electro-

nics and atomic weapons. As dean of engineering at

Stanford immediately after the war, Terman was deter-

mined engineers would not play second fiddle in the

future[ [8]. Responding to continued turbulence over curriculum, in May 1952, S. C. Hollister, the President of

the American Society for Engineering Education (ASEE),

appointed a Committee on Evaluation of Engineering Edu- cation chaired by Prof. L. E. Grinter with the goal to eval-

uate engineering education and suggest new approaches to

teaching engineering. The resulting 36-page report [11],

[12] was the most significant in the history of ASEE. En-

gineering curricula that emphasized mathematics and

science were codified in some, but not all, of the recom-

mendations in the Grinter report [11]–[13] that brought

engineering science courses into prominence. A further accelerator was the intercultural–political shock caused by

Sputnik. Suddenly the United States was behind, and

engineering education was partly to blame [13]. The shift

to more science and engineering science is the most sig-

nificant change in engineering education during the past

100 years and has been characterized in various ways:

BThe first draft of the so-called Grinter Report stressed the need for more science in engineering

curricula and then, more controversially, proposed

two tiers of engineering instruction. The committee

thought most students would be served by a

professional-general program that provided solid

training in fundamental science for jobs in industry.

Only a few engineering schools needed to develop

advanced undergraduate and graduate programs in fundamental engineering science (professional-

scientific) to prepare students for government and

industrial research programs. Readers of the report

disagreed sharply, however, and the final version of

the Grinter Report settled for a strong endorsement

of the need for more science in engineering schools.

Why the protest? The key, again, was military re-

search funding. What engineering school would voluntarily cut itself off from military research

dollars, the key to building academic engineering

programs?[ [8].

BGrinter recommended that all engineering cur- ricula include the following common set of courses

in the Fengineering sciences_: Mechanics of Solids, Fluid Mechanics, Thermodynamics, Heat and Mass Transfer, Electrical Theory, Nature and Properties of

Material. The report also recommended that engi-

neering curricula include coursework in the social

humanities. This recommendation was clearly aimed

at helping engineers to develop skills in interacting

with people and to understand the social ramifica-

tions of technological development. This report had

Froyd et al.: Five Major Shifts in 100 Years of Engineering Education

Vol. 100, May 13th, 2012 | Proceedings of the IEEE 1345

a foundational impact upon engineering curricula and firmly rooted the study of engineering in the

sciences[ [14].

At the end of this shift, United States engineering cur-

ricula more closely resembled their European counter-

parts. Further, some of the emphases and excesses during

and after the shift generated rationale and momentum for

some of the shifts described below.

I I I . S E C O N D M A J O R S H I F T : O U T C O M E S - B A S E D A C C R E D I T A T I O N

Through ABET and its predecessors Baccreditation has provided quality control for engineering education in the

United States, seeking to assure that graduates of accre-

dited programs are prepared for professional practice[ [15]. By the late 1980s, as the Bnumber of accreditation visits multiplied. . .[and] the prospect of legal challenges to unfavorable accreditation decisions increased, ABET re-

view criteria became more quantitatively focused and less

dependent on professional judgment. Despite its best in-

tentions, the pre-1990 ABET could well be characterized

as a protector of the status quo[ [15]. Further, BPresident James J. Duderstadt of the University of Michigan and President Charles M. Vest of the Massachusetts Institute of

Technology, both engineers, stated publicly that engineer-

ing education must change significantly to support the new

quality-oriented environment and that ABET’s rigid, bean-

counting implementation of the accreditation criteria

created a significant barrier to needed innovations in

engineering education. These concerns were echoed by

members of the ABET Industry Advisory Council[ [15] as well as Bdeans from major engineering schools[ [15].

Based on educational research on student objectives

and outcomes (discussed later), the Engineering Accred-

itation Commission (EAC) of ABET developed a wholesale

change in accreditation of engineering programs, known

initially as Engineering Criteria 2000 (EC 2000) [15]. EC

2000 required assessment of student learning based on 11

criteria (3 a-k) for student outcomes (what students should be able to do on graduation day), assessment of graduate

achievement based on program developed objectives (what

graduates should be able to do a few years after gradua-

tion), and continuous program improvement. Criteria for

the current cycle are available at http://abet.org/.

Initially, most professors strongly resisted assessment,

but many eventually acquiesced after realizing that direct

instructor assessment for student outcomes, which satis- fies ABET, can take little additional time for the technical

criteria [16]. Rubrics are needed to assess the professional

criteria, and sample rubrics are available [17]. Communi-

cation (criterion 3g), understanding ethical standards

(criterion 3f), and teamwork (criterion 3d) are items

that industry and most professors believe are important,

can be taught, and can be assessed. Industry and faculty are

interested in ethical behavior, but criterion 3f says nothing about behavior. Criterion 3i, Ba recognition of the need for, and an ability to engage in lifelong learning,[ is widely believed to be important, but how to assess Ba recognition[ is not clear. Professional criteria 3h, Bthe broad education necessary to understand the impact of engineering solu-

tions in a global, economic, environmental, and societal

context,[ and 3j, Ba knowledge of contemporary issues,[ are considered by practicing engineers one to ten years after graduation to be less important [18] and have signi-

ficantly less faculty support than the other criteria [19].

Unfortunately, disconnects over globalization issues exist

between new engineers and most professors and many

experienced commentators who consider it to be critically

important [20]–[23]. Some ABET program evaluators pri-

vately state that as long as a program does anything to

teach and assess criteria 3i, 3h, and 3j, they accept it. An extensive analysis showed that EC 2000 clearly had

a positive effect on engineering education [19]. Writing

and disseminating course objectives, which are required by

EC 2000, improves courses [24]. Because outcomes-based

assessment is more flexible than the former method, ABET

EAC is more accepting of novel programs. Looking at in-

dividual outcome criteria and obtaining regular feedback

from graduates and employers makes it much easier to spot shortcomings and strengths in programs. Another result of

the EC 2000 criteria is that more professors have become

involved in assessment and accreditation. Explicit require-

ments to teach and assess the professional criteria have

improved graduates’ skills in these areas [19]. More pro-

fessors use active learning methods, although it is not

possible to determine to what degree EC 2000 was respon-

sible for this change [19]. Many engineering professors still oppose assessment, continuous improvement, and

data-based decision making [19], although these methods

improve engineering education. Lattuca et al.’s [19] major analysis of the effectiveness of EC 2000 relied on surveys

and self-reports, which they carefully benchmarked as

providing meaningful information. Ironically, surveys and

self-reports would not be allowed as the only assessments

of an engineering program [16], [25].

I V . T H I R D M A J O R S H I F T : R E N E W E D E M P H A S I S O N D E S I G N

The third major shift is increasing emphasis on design as a

major and distinctive element of engineering [26]. One

reason for the shift was the sense that the emphasis on

engineering science, science, and mathematics has gone too far [8], [9], [27]. For example, Kerr and Pipes [28]

wrote B[d]esign has fallen so low in the order of educa- tional priorities that many engineersVespecially young ones and studentsVdo not understand its meaning.[ By the current millennium, influences of the shift were

clearly evident. In 2005, over half the faculty and close to

3/4 of program chairs thought there was an increased

Froyd et al.: Five Major Shifts in 100 Years of Engineering Education

1346 Proceedings of the IEEE | Vol. 100, May 13th, 2012

emphasis on design in undergraduate curricula during the previous ten years [15]. Also, a study of how first-year and

senior engineering students address a design challenge

showed that engineering students do develop with respect

to design knowledge and skills over the course of four-year

engineering curricula [29].

A. Capstone Design Courses Although not recent, the most widespread artifact of

the shift is the capstone design course (or courses)

present in many U.S. engineering curricula [30], [31].

Their existence has been encouraged by the EAC within

ABET through its Engineering Criteria. In the 1970s,

one-half year of engineering design became the standard

requirement with the further stipulation that there had to

be at least one course, preferably in the senior year, which

was mainly design and which incorporated material from other courses [32]. The latter requirement is often inter-

preted as Bcapstone design,[ although the Engineering Criteria do not use this language. The one-half year of

design requirement increased the amount of design, but it

also caused endless arguments during accreditation visits

over what was included as design. Current Engineering

Criteria stipulate that students Bmust be prepared for en- gineering practice through a curriculum culminating in a major design experience based on the knowledge and skills

acquired in earlier course work and incorporating ap-

propriate engineering standards and multiple realistic

constraints[ [33]. Capstone design courses were also Bde- veloped recently in an effort to bring the practical side of

engineering design back into the engineering curriculum[ [34] and address concerns that graduates were unprepared

for industrial practice upon graduation. Several studies and reports have articulated employer expectations for engi-

neering graduates [20], [22], [33], [35]–[37]. Reviewing

these expectations and comparing them with the learning

goals for capstone design courses reveals considerable

alignment.

Early models for the capstone design course included

the senior project component of the Harvey Mudd Design

Clinic [38], which was implemented in the mid-1960s, and the Major Qualifying Project in the WPI Plan [39], which

was implemented in the late 1960s. Individuals who have

played important roles in the Harvey Mudd Design Clinic,

Clive L. Dym, M. Mack Gilkeson, and J. Richard Phillips,

were recognized with the 2012 Bernard M. Gordon Prize

for Innovation in Engineering and Technology Education.

The state of capstone design courses has been docu-

mented in two surveys, one done in 1994 [31] and the second in 2005 [30], [40]. The second survey provided

data on the age of the capstone design courses in their current form. From the 400 responses, 33% were five or less years old, 25% were 6–10 years old, 17% were

11–15 years old, 10% were 16–20 years old, and 14% were

first offered 21 or more years ago [30]. Since over 50% of

the capstone design courses were less than ten years old,

the responses suggest that faculty continue to restructure and/or fine-tune courses and curricula.

Both surveys found that the vast majority of the

capstone project courses organized students from one

department in teams. As far as team size, 49% of 1994

respondents indicated that teams were composed of four to

six students, while 60% of 2005 survey respondents indi-

cate team sizes in this range [30]. The more recent survey

found a noticeable increase in the prevalence of design teams populated by students from more than one depart-

ment. In the 1990s, the SUCCEED Engineering Education

Coalition, one of the six NSF-supported Engineering Edu-

cation Coalitions [41]–[43] focused a significant percent-

age of its efforts on capstone design courses with student

teams consisting of members from more than one depart-

ment [44], [45]. In some cases, SUCCEED student teams

were composed of only engineering students; in other cases, departments from outside engineering participated.

Since 2000, the trend toward interdisciplinary capstone

project courses appears to be continuing [46], [47], and

courses often include students from majors other than

engineering such as business and industrial design

(http://eeic.osu.edu/capstone). Competitions such as the

solar house or solar-powered car, which are inherently in-

terdisciplinary and offer opportunities for participation from nonengineering fields as well, fit well into design courses

and are strong motivators of many students [48], [49].

Assessment of student learning in capstone design pro-

jects [50] varies considerably. Respondents to the 2005

survey indicated that the following methods provided data

for part or the entire final grade:

• individual deliverables throughout the term: 53%; • group deliverables throughout the term: 67%; • final group deliverable: 86%; • evaluations by other team members: 57% [30].

Howe [30] reported some interesting findings: BPeer eval- uations, as well as evaluations of individual and group

deliverables throughout the term were each used by about

half of programs. The reportedly common practice of eval-

uating intermediate and final group deliverables is con-

sistent with findings by McKenzie et al. [12], but a notable finding is that 14% of respondent programs in 2005 did not

use evaluations of final group deliverables at all. A surpris- ing theme shown in the pie charts is the number of programs that gave full weight to a single factor. Some based final grades on only group deliverables, while 2% based grades solely on group evaluations [emphasis added].[ Divergence among assessment methods suggests continued evolution as prog-

rams continue to mine approaches from other programs and develop new approaches.

B. First-Year or Cornerstone Engineering Design Courses

A second artifact of the shift toward increasing em-

phasis on design is the first-year engineering design course

or cornerstone course [26], [27], [51]. In Bthe 1970s and

Froyd et al.: Five Major Shifts in 100 Years of Engineering Education

Vol. 100, May 13th, 2012 | Proceedings of the IEEE 1347

early 1980s freshman design courses and course segments were common at ABET-accredited institutions,[ as evi- denced by the activity in the annual Creative Engineering

Design Display held at the ASEE Annual Conference &

Expositions during these years [27]. However, during the

1980s, pressures to introduce computer programming into

engineering curricula tended to squeeze out first-year

design content so that by 1987 the Creative Engineering

Design Display was canceled [27]. In the 1990s, there was a resurgence of first-year design activity, led in part by the

NSF-supported Engineering Education Coalitions [41]–[43],

particularly the ECSEL Coalition, with its emphasis on

first-year engineering design [52], [53], the Synthesis

Coalition [27], [54], the Gateway Coalition and implemen-

tations of the Enhanced Educational Experience for Engi-

neers program [55], [56] on its various campuses, and the

Foundation Coalition, with its emphasis on integrated first-year engineering curricula [57].

First-year engineering design courses have been shown

to have positive influences on student development and

retention. For example, first-year engineering design

courses have been shown to positively influence intellec-

tual development of students [58]. Students who chose to

participate in the first-year engineering design course at

the University of Colorado Boulder, with its Integrated Teaching & Learning Program and Laboratory (ITL), were

retained at a statistically significantly higher rate than

similar groups of engineering students who chose a differ-

ent first-year engineering experience [59]. Incidentally,

the prime movers in creating the ITL and courses it sup-

ports, Jacquelyn F. Sullivan and Lawrence E. Carlson, were

recognized for their contributions to engineering educa-

tion with the 2008 Bernard M. Gordon Prize for Innova- tion in Engineering and Technological Education. BOther studies of first-year engineering courses also reported im-

provements in retention [60]–[62][ [63]. Data on first-year engineering design courses are avail-

able through a survey of first-year programs conducted in

2005 [64]. The survey found that 13 respondents (from

N ¼ 68, 19.1%) of the first-year engineering courses were described as design courses, while 21 (from N ¼ 47 re- spondents, 44.7%) indicated that their first-year engineer-

ing courses integrated design with other topics [64]. A

survey to determine the extent to which engineering prog-

rams were aware and had adopted seven innovations in

engineering education whose efficacy was well-established

in the literature found that 92% (of 197 respondents) were

aware of first-year engineering design courses, while 65%

(of 197 responded) had implemented first-year design courses in their programs [63]. To support first-year engi-

neering design courses, some institutions have found it

very helpful to create physical spaces that support achieve-

ment of the educational goals and objectives that the in-

stitutions have established. At Purdue University, the Ideas

to Innovation (i2i) Learning Laboratory is an experiential,

collaborative, reconfigurable learning environment, which

supports interactive technologies and team-based activities

(see Fig. 1). Another helpful source of information is a

review of first-year design education in Canada and the

United States conducted by a member of the Canadian Design Engineering Network [65]. Bazylak and Wild noted

that compared Bwith engineering science subjects, in which methods of instruction are remarkably uniform

from university to university, the wide variation in [first

year] engineering design instruction methods is striking.

In part, this variation is due to the different resource con-

straints and priorities at each university[ [65]. Faculty members teaching many engineering science subjects fre- quently choose from one of a small set of textbooks. For

first-year engineering courses, a small set of dominant

textbooks has yet to emerge. Whether this is a cause or an

effect of the difference in variation between engineering

science and first-year engineering courses is a debate left

to the readers.

C. Engineering Design in the Sophomore and Junior Years

Although the shift toward increasing emphasis on en-

gineering design has resulted in changes to engineering curricula in the first and senior years, design content and

experiences in the second and third years of the engineer-

ing curricula have not changed significantly. As a result,

there is a gulf between student experiences with engineer-

ing design in the first year and the capstone culminating

experience. The impact on student learning and presence

of this gulf were documented in a study at the University of

Colorado at Boulder that concluded, Bthere is deteriora- tion in student confidence in both professional and tech-

nical skills between the end of the first year and the

beginning of the senior year . . . and the decline is statis- tically significant for all the assessed categories[ [66]. An exception to this nationwide pattern can be found in the

engineering curricula introduced at Rowan University, in

which students work on their learning with respect to

Fig. 1. The Ideas to Innovation (i2i) First-Year Engineering Learning Laboratory at Purdue University.

Froyd et al.: Five Major Shifts in 100 Years of Engineering Education

1348 Proceedings of the IEEE | Vol. 100, May 13th, 2012

engineering design in each of their eight semesters [67]. Recognizing this gulf, a multiyear study by the Carnegie

Foundation for the Advancement of Teaching recom-

mended a thick spine spanning the four years of the engi-

neering curriculum to provide Bexperience with and reflect on the demands of professional practice, linking

theory and practice. . .This emphasis on professional prac- tice would give coherence and efficacy to the primary task

facing schools of engineering: enabling students to move from being passive viewers of engineering action to taking

their place as active participants or creators within the

field of engineering[ [68].

V . F O U R T H M A J O R S H I F T : A P P L Y I N G E D U C A T I O N , L E A R N I N G , A N D S O C I A L - B E H A V I O R A L S C I E N C E S R E S E A R C H

Influences of research in education, learning, and social-

behavioral sciences are continuing to evolve [69].

• Behavioral psychology research has resulted in learning objectives (or outcomes), formative and

summative assessment, and mastery model re-

search outcomes and objectives. Student learning

outcomes are now an integral part of the ABET Engineering Criteria and many other accreditation

models.

• Social psychology research has resulted in adoption by many faculty members of approaches to teach-

ing that increase student engagement and have

been characterized as active learning, interactive

learning, and especially cooperative learning, to-

gether with approaches that emphasize building communities, such as learning communities and

communities of practice.

• I n q u i r y - b a s e d l e a r n i n g m e t h o d s i n c l u d i n g problem-based and project-based learning, ap-

proaches to promote conceptual understanding,

and integrated course design approaches are pro-

ducts of research in cognitive psychology, educa-

tion, and the learning sciences. The extent to which research in education, learning,

and social-behavioral sciences has and continues to

influence engineering education is changing, and difficult

to determine. Boyer [70] found that 7% of engineering

professors are most interested in research and 43% lean

toward research instead of teaching. In a 2009 survey

studying extent to which seven innovations in engineering

education had been recognized and/or adopted in engi- neering departments, Borrego et al. found the following awareness and adoption levels directly related to the focus

of this section:

• student-active pedagogies (awareness: 82%, adop- tion: 71%, N ¼ 197 respondents);

• learning communities (awareness: 85%, adoption: 44%, N ¼ 197 respondents);

• curriculum-based engineering service learning projects (awareness: 79%, adoption: 28%,

N ¼ 197 respondents) [63]. Over the years, many workshops for engineering fa-

culty members have emphasized teaching approaches de-

rived from educational research, including the National

Effective Teaching Institute (NETI) [71] and faculty devel-

opment workshops offered by one or more of the Engi-

neering Education Coalitions [72], [73]. Participants in the NETI workshop reported that their experiences have

moderately or substantially increased their use of the

following practices:

• learning objectives: 75%; • Bloom’s taxonomy: 55%; • active learning: 74%; • cooperative learning: 65%; • problem-based learning: 55%; • inquiry-based learning: 34% [71].

These results are congruent with the University of

California Los Angeles (UCLA) Higher Education Re-

search Institute Faculty Survey results, which indicate that

59% of faculty surveyed report using cooperative learning

in all or most classes [74]. Workshops, courses, and prog-

rams on teaching for engineering and science graduate and

postdoctoral students will likely influence teaching ap- proaches by these potential faculty members [75].

Section V-A and B describe learning outcomes and

student engagement, where there seems to be agreement

among engineering educators in terms of the practice of

engineering education. Then, Section V-C–F highlight

areas where there is some emerging support among engi-

neering educators.

A. Educational Objectives, Mastery, and Student Learning Outcomes

Educational objectives, especially student learning out-

comes because of ABET EAC requirements, are now part of

the fabric of the engineering education community, other

professional communities, and university accreditation.

Before ABET adopted outcomes, the work and publications

of Jim Stice, University of Texas at Austin, and Richard Felder, North Carolina State University, were very in-

fluential in introducing engineering faculty to objectives

and the educational literature on objectives [76]. Through

a series of articles, workshops and follow-up conversations

[77]–[82], Stice, and later Felder, provided convincing

arguments for the importance of carefully identifying and

specifying objectives. Heywood [83] provides an excellent

summary of the development of educational objectives in his extraordinary synthesis of work in engineering

education.

Often faculty members find taxonomies of learning

objectives useful in that they reveal richness and diversity

in how learning objectives may be written [84]. This re-

view of taxonomies of learning objectives shows that

Bloom’s taxonomy [85] has many effective characteristics.

Froyd et al.: Five Major Shifts in 100 Years of Engineering Education

Vol. 100, May 13th, 2012 | Proceedings of the IEEE 1349

Although the 1956 version of Bloom’s Taxonomy of Educa- tional Objectives [85] is widely used by engineering edu-

cators, we recommend considering the adoption of the

updated and revised taxonomy [86].

Use of educational objectives, and, more broadly, stu-

dent learning outcomes and Bloom’s Taxonomy (original

or revised) is an indication that research in psychology,

education, and learning science is having a noticeable

influence on the engineering education community. How- ever, in the case of Bloom’s taxonomy, there are, of course,

as noted by Shulman [87], drawbacks to using taxonomies,

which highlight differences, and like all tools we need to

use them with care.

B. Student Engagement Student engagement or involvement in learning is the

second area for which there is evidence of the influence of research in psychology, education, and learning science on

the practice of engineering education. The idea of the im-

portance of student involvement was advanced by many,

including John Dewey, and in the 1980s and 1990s was

supported by research by Astin [88], Light [89], and many

others. A 1984 U.S. Department of Education report made

a very strong case for the importance of student

involvement [90]. One of the most common ways that engineering faculty

members have embraced student involvement is through

the use of cooperative learning. Cooperative learning and

its underlying theoretical framework, social interdepen-

dence theory, have been systematically studied in engi-

neering education for over 50 years; the first study with

engineering students was conducted at the Massachusetts

Institute of Technology (MIT) in 1948 [91]. Engineering faculty began embracing cooperative learning shortly after

it was introduced by Karl Smith in engineering education

conferences and journals in 1981 [92], [93], and its use

continues to grow, both in engineering [94]–[97] and

physics [98]–[100] and in higher education in general

[101]–[110]. For example, the University of Minnesota

Active Learning Classrooms (ALCs) are designed to foster

interactive, flexible, student-centered learning experi- ences, and operate using central teaching stations and

student-provided laptops. ALC is a modification of the

Student Centered Activities for Large Enrollment Under-

graduate Program (SCALE-UP) concept that originated at

North Carolina State University [98] and the Technology

Enhanced Active Learning (TEAL) concept at MIT [100],

and uses an adaptation of the projection capable class-

rooms (PCC) technology system (see Fig. 2). The empirical and theoretical evidence supporting the efficacy of coope-

rative learning and, to a lesser extent, active learning in

engineering is vast [95], [111], [112]. Cooperation among

students typically results in 1) higher achievement and

greater productivity; 2) more caring, supportive, and com-

mitted relationships; and 3) greater psychological health,

social competence, and self-esteem [96], [102], [104].

The National Survey of Student Engagement (NSSE)

[113] has deepened understanding of how students per-

ceive classroom-based learning, in all its forms, as an ele-

ment in the bigger issue of student engagement in their

college education. The annual survey of first-year students

and seniors asks them how often they have participated in

learning activities in which they have been actively en- gaged, for example, projects that required integrating ideas

or information from various sources. Approaches that em-

phasize building communities, such as learning commu-

nities [114], [115] and communities of practice [116], also

foster more student engagement. As shown by these and

other studies, engaged students learn, are retained, and

graduate. However, most students do not start in engi-

neering as highly motivated, engaged students [4]Vit is up to the faculty to engage them.

C. Inquiry The idea of inquiry was articulated by John Dewey, who

saw it as part of an ideal school [117]:

• a Bthinking[ curriculum aimed at deep under- standing;

• cooperative learning within communities of learners;

• interdisciplinary and multidisciplinary curricula; • projects, portfolios, and other Balternative assess-

ments[ that challenged students to integrate ideas and demonstrate their capabilities.

Inquiry and inquiry-based or guided approaches focus first

on the question, problem, challenge, or goal to be ad-

dressed. Then, students learn content, concepts, and pro-

cesses while addressing the question, problem, challenge, or goal. Inquiry approaches and evidence that they are

effective are evident in problem-based learning [96], [118],

[119]; project-based learning [96], [118]–[120]; model-

eliciting activities [121]–[123]; challenge-based learning,

including an entire NSF-supported Engineering Research

Center [VaNTH] that focused on using ideas from How People Learn [124] to redesign biomedical engineering

Fig. 2. Active Learning Classroom (ALC) at the University of Minnesota.

Froyd et al.: Five Major Shifts in 100 Years of Engineering Education

1350 Proceedings of the IEEE | Vol. 100, May 13th, 2012

curricula [125]–[127]; and problem-based service learning [128], [129], including the Engineering Projects in Com-

munity Service (EPICS) model [130], for which Ed Coyle,

Leah Jamieson, and Bill Oakes were recognized by the

2005 Bernard M. Gordon Prize for Innovation in Engi-

neering & Technology Education. Prince and Felder [131],

[132] provide a comprehensive framework for analyzing

these inductive instructional methods, and a National

Research Council report [133] provides guidance for teaching and learning using an inquiry approach.

D. Integrated Approach to Course and Program Design

Understanding by Design (UbD) is an increasingly

popular tool for educational planning focused on teaching

for understanding. The emphasis of UbD is on Bbackward design,[ the practice of first looking at the outcomes in order to design curriculum units, performance assess-

ments, and classroom instruction. UbD is defined by

Wiggins and McTighe as a Bframework for designing cur- riculum units, performance assessments, and instruction

that lead your students to deep understanding of the con-

tent you teach[ [134]. An engineering version of the UbD approach was presented by Felder and Brent [135], who

describe how the UbD approach can help engineering de- partments address the ABET EAC Engineering Criteria. An

integrated engineering approach has been enthusiastically

embraced in the Purdue Engineering Education Ph.D.

program and by faculty in numerous national and

international workshops facilitated by Ruth Streveler and

Karl Smith [136]. This approach is gaining acceptance in

engineering education for course and program design

[137]–[139]. Duderstadt [140] claims, BIt could well be that faculty members of the twenty-first century college or

university will find it necessary to set aside their roles as

teachers and instead become designers of learning expe-

riences, processes, and environments.[

E. Importance of a Broader Range of Knowledge, Skills, and Attributes

Evidence of increased emphasis on a broader range of knowledge, skills, and attributes (or habits of mind and

modes of thinking) for engineering graduates abounds.

Several studiesVBoeing and RPI’s The Global Engineer [141], NAE’s Engineer of 2020 [23], Purdue Future Engi-

neer [142], The 21st-Century Engineer [143], Engineering

for a Changing World [140]Vhave begun to articulate the knowledge, skills, and habits of mind that are needed for

students to perform satisfactorily in an interdependent world [144].

F. Scholarly Approach to Engineering Education through the Scholarship of Teaching and Learning (SoTL) and Engineering Education Research

Boyer’s [70] report Scholarship Reconsidered drama- tically expanded the language for conversations about

scholarship in higher education. Boyer argued for expand- ing scholarship beyond discovery to include integration,

application, and teaching. Hutching and Shulman [145]

contrasted Bteach as taught[ with three levels on inquiry within education, and Streveler et al. [146] expanded on the list by adding a fourth level, engineering education

research:

• teach as taught (Bdistal pedagogy[); • level 1: effective teacher; • level 2: scholarly teacher; • level 3: scholarship of teaching and learning

(SoTL);

• level 4: engineering education research. Borrego et al. [147] described these levels of inquiry in more detail.

Emergence of increased emphasis on a scholarly ap-

proach to engineering education is indicated by numerous developments, including the ASEE Year of Dialogue, the

National Academy of Engineering’s Center for the Ad-

vancement of Engineering Education and especially the

Annals of Research on Engineering Education [148], the

rigorous research in engineering education project [146],

[147], [149], the repositioning of the Journal of Engineering Education Bto serve as an archival record of scholarly re- search in engineering education[ [150], the global empha- sis on engineering education research [151], and the heavy

emphasis in the NAE (2005) report on the use of research

to convince faculty to change their teaching methods.

Building on these initiatives, two ASEE reports have at-

tempted to address a core question: BHow can we create an environment in which many exciting, engaging, and em-

powering engineering educational innovations can flourish

and make a significant difference in educating future engineers?[ [152], [153].

G. Summary Although there is agreement on many educational

research-based aspects of engineering education, we

need to be mindful that panaceas do not exist. Mastery,

inquiry, and student engagement are good ideas, but

educators have a tendency to take good ideas and try to universalize them [154], [155]. The push to extremes of

mastery and inquiry almost destroyed these good ideas,

and many have similar worries currently about student

engagement. Bruner argued for making inquiry an

integral part, but not the sole part, of a student’s

education [156].

In a new challenge, Boyer [157] encouraged all of us to

make connections across all forms of scholarship by embracing the scholarship of engagement, writing, BThe scholarship of engagement means connecting the rich

resources of the university to our most pressing social,

civic and ethical problems, to our children, to our schools,

to our teachers and to our cities.[ Finally, Ramaley argues that we also need to bring a

scholarly approach to change:

Froyd et al.: Five Major Shifts in 100 Years of Engineering Education

Vol. 100, May 13th, 2012 | Proceedings of the IEEE 1351

BAchieving transformational change is a scholarly challenge best dealt with by practicing public scho-

larship, which is modeled by the leader and encour-

aged in other members of the campus community.

Like all good scholarly work, good decision making

by campus leadership begins with a base of scholarly

knowledge generated and validated by higher edu-

cation researchers[ [158, p. 75].

V I . F I F T H M A J O R S H I F T : I N F L U E N C E O F I N F O R M A T I O N , C O M M U N I C A T I O N , A N D C O M P U T A T I O N A L T E C H N O L O G I E S ( I C C T ) O N E N G I N E E R I N G E D U C A T I O N

Starting with the second issue of the IRE Transactions on Education, electrical and computer engineers have empha- sized application of information, communication, and com-

putational technologies (ICCT) in engineering education.

In a surprisingly accurate futuristic 1958 article, Ramo [7]

described a future educational enterprise that heavily used

unspecified machines for routine teaching. His statement,

BThe whole objective . . . is to raise the teacher to a higher level . . ., and remove from his [sic] duties that kind of effort which does not use the teacher’s skill to the fullest,[ is echoed by many current papers. Ramo also essentially

predicted the rise of engineering education as a separate

discipline, BThere is probably a new profession known as Fteaching engineer,_ that kind of engineering which is concerned with the educational process and with the

design of the machines, as well as the design of the

material.[ Perhaps because he was not an academic, Ramo underestimated the time required for these changes. In addition to their positive aspects, potentially disruptive

aspects of ICCT are delineated by Cheville [4].

Some of the principal instructional technologies and

their applications have been:

• content delivery: television, videotape, and the Internet;

• programmed instruction: individualized student feedback;

• personal response systems (Bclickers[); • computational technologies; • intelligent tutors: second phase of individualized

student feedback;

• simulations; • games and competitions; • remote laboratories; • grading. MIT has offered one of their visions for classrooms that

support combinations of a subset of these technologies

through their Technology Enhanced Active Learning

(TEAL) [100], which incorporates collaborative learning,

networked laptops to desktop experiments that students

perform and analyze, and media-rich software for visual-

ization (see Fig. 3). In teaching electromagnetics, MIT

faculty members have provided visualization materials in

five categories: vector fields, electrostatics, magneto-

statics, Faraday’s law, and light.

A. Content Delivery: Television, Videotape, and the Internet

In the 1950s, 1960s, and 1970s, many educators thought that television and videotape were the instructional method

of the future [7], [159]–[161]. Television and videotape did

prove very useful in distance education as a method for

distributing content. Controlled experiments at Stanford

University showed no significant difference in student

learning between students in a live classroom and students

taught by a tutored videotape method [161]. After the

Internet became ubiquitous, distance learning was rede- fined to be online learning, most often through content

delivery, and studies showed Bno significant differences in learning outcomes for online and on-campus students

as measured by test scores[ [162]. Internet delivery can also include intelligent tutoring systems and remote

laboratoriesVboth of which are discussed later.

B. Programmed Instruction: Individual Student Feedback

Initially, technological methods were used solely for

content delivery. Probably the first paper in an engineering

education journal with data on providing individual

student feedback with a teaching machine was a reprint

[163] of a paper from Science by famed psychologist B. F. Skinner [164]. Skinner noted B[t]he machine itself, of course, does not teach. It simply brings the student into

contact with the person who composed the material it

presents. It is a laborsaving device because it can bring one

programmer into contact with an indefinite number of

students. This may suggest mass production, but the effect

upon each student is surprisingly like that of a private

tutor.[ Two years later engineering applications included

Fig. 3. TEAL classroom for teaching electromagnetics at MIT.

Froyd et al.: Five Major Shifts in 100 Years of Engineering Education

1352 Proceedings of the IEEE | Vol. 100, May 13th, 2012

programmed learning of Kirchhoff’s laws [165] and devel- opment of the PLATO teaching machine [166]. It was

quickly understood that immediate, individual feedback to

students was the main reason for the effectiveness of the

method [165]. However, as Dunn notes, BUsed alone [programmed instruction], students could and did learn

the Fortran language, but the course was somewhat stale

and motivation was lacking for some students[ [167]. As long as the student got everything right, these tutors worked quite smoothly [168]. The approach was objectiv-

ist, and there was no individualization of the responses.

C. Personal Response Systems (BClickers[) Personal response systems (colloquially known as

Bclickers[) have rapidly become quite popular on cam- puses [169]–[172], including in engineering [173]–[175].

Clickers provide immediate feedback in lecture, help keep students from being overly passive, and are easy to incor-

porate in a lecture. Properly used with appropriate ques-

tions and required student peer instruction, clickers help

students understand what they do not know [175] and

result in increased student learning [176]. Unfortunately,

clickers, like any other tool, can be misusedVfor example, by exclusively using questions at the knowledge level of

Bloom’s taxonomy. Beatty et al. offer guidelines for creat- ing effective questions [177]. Another advantage of clickers

is that they lower the resistance of traditional teachers in

transforming to a more student-oriented pedagogy [169].

D. Computational Technologies It is easy to forget that the electronic calculator, intro-

duced in 1972, had a major effect on engineering education

since it allowed students to solve realistic problems within time-constrained classroom settings that were almost

impossible with a slide rule [178]. Today, the computa-

tional power that can be provided in a device about the size

of a calculator is impressive: graphing, equation solving,

and symbolic manipulation are some of the capabilities

available in a handheld device. However, debates continue

over which and how much computational power (and

memory) students should be allowed to use, especially in testing situations. The Fundamentals of Engineering (FE)

examination places strict limits on the computational de-

vices students can use. Mathematics courses in many in-

stitutions do not permit students to use calculators during

examinations. Questions about what students will be asked

to do and what can be off-loaded onto computational

technologies continue to be debated.

Personal computers (PCs), on the other hand, had a slower rate of penetration and less early impact than ex-

pected [179], perhaps because they were an order of

magnitude more expensive than calculators. Shifting PC

ownership to students made them an ordinary cost of

education that could be paid for by student loans or

scholarships. This innovation plus the reduced cost of PCs

eventually increased the impact of PCs in engineering

education. Spreadsheets [180]–[182] and equation solving programs such as MATLAB [183]–[185] are probably the

most common uses of the computer in engineering educa-

tion. Currently, tablet PCs with interactive software [186]

and tablets are being tried as waves of the future.

E. Intelligent tutors: Second Phase of Individualized Student Feedback

Through the 1960s and 1970s, programmed instruction and teaching machines slowly became more sophisticated

and reflected a constructivist approach to student learning.

BThe questioning program must be capable of adjusting itself to the particular needs and problems of each user,[ wrote Bestougeff et al. [187]. These programs are known as intelligent tutor systems (ITS) or computer-aided instruc-

tion (CAI) or computer-aided learning (CAL). Antao et al. [188] developed a program to teach simulation (e.g., with SPICE) that monitors student learning and reconfigured

the order of presentation based on the student’s answers.

An extension of this idea was to have students take the

Index of Learning Styles [189] and use this information to

make the ITS adaptive [190]. To prevent students from

passively turning the electronic pages and not trying the

exercises, tutors may require a correct answer before al-

lowing the student to move forward [191]. Immediate feedback and explanations for incorrect

answers can help students learn. Tutoring is effectiveVan untrained human tutor can produce about 0.4 sigma in-

crease in learning [192] while a trained human tutor can

produce about 2 sigma increase. A typical ITS can produce

about 1 sigma increase and in some cases with natural lan-

guage dialog built into the tutor up to 1.5 sigma [192]. If

time is available, students will repeat the tutor to obtain mastery [193]. ITSs that provide hints are more effective

than systems that do not, and a comparison of a hinting ITS

with professors providing hints found no significant differ-

ence [194]. Initial development of ITS was slow partially

because the estimated construction time without dialog was

about 100 hours per hour of instruction [168]. Currently,

development time has been reduced since developers can use

authoring tools such as Authorware [195] or platforms such as AutoTutor [192]. The experimental evidence is clear that

CAI increases student learning. However, this is true only if

students use the computer, and many students will not

unless strongly encouraged to do so [196]. Despite their

advantages, ITS systems do not appear to be widely used in

engineering education [197].

F. Simulations Simulations have proved to be very useful in both en-

gineering practice and in engineering education. Simula-

tors can be public domain programs such as SPICE [198],

[199], homegrown programs [200], or commercial pro-

ducts such as Aspen Plus, which is widely used as a process

simulator in chemical engineering [201]. Simulation,

which can be considered a third way to obtain knowledge

Froyd et al.: Five Major Shifts in 100 Years of Engineering Education

Vol. 100, May 13th, 2012 | Proceedings of the IEEE 1353

along with theory and experimentation, has become ubi- quitous in engineering education. Simulation has the ad-

vantage of being an active learning method that is easily

coupled with intelligent tutoring programs. Real effects

such as measurement errors and stiction can be prog-

rammed into simulations [202], but simulations do not

replace the need for experiments. Combining simulation

(aka virtual laboratories) with real laboratories provides

benefits to both. BAnalyses of metacognitive statements of students show enhanced awareness of experimental design,

greater references to critical thinking and higher order

cognition in the virtual laboratory and an enhanced

awareness of laboratory protocol in the physical labora-

tories[ [203]. A rigorous study of the effect of 3-D simula- tions showed that the simulations benefited male students

more than female students, and international students

struggled perhaps due to language or IT difficulties [204]. Because practicing engineers use simulations and because

simulations are considerably less expensive than adding

laboratories, they are widely used in engineering education.

G. Games and Competitions Educational games are similar to simulations except

that games have goals [205]. A review of the few available

studies shows that video games can satisfy many of the requirements necessary for learning, such as increased

time on task, and result in more learning than occurs in

lectures [205]. Honey and Hilton [206] noted that while

simulations and games have great potential for learning

science particularly through inquiry, the research litera-

ture on the effectiveness of simulations and games is very

limited. They recommended an extended research pro-

gram on learning from simulations and games. Although cooperative learning is an extremely effective

learning strategy, competitions are also effective motiva-

tors, particularly when cooperative teams compete. An

early software game was the Bsoftware hut game,[ which asked student groups to develop software and improve

another team’s software [207]. If the contest ties into the

students’ competitiveness and they believe they have the

chance to win, students will work extremely hard [49]. Other programming competitions have also been devel-

oped [208]–[210]. Various robotic contests have proven to

be excellent vehicles for involving high school and college

students [211]–[215].

H. Remote Laboratories Remote laboratories, a method that can at least par-

tially replace live experimentation, was first developed by Aktan et al. [216]. In a remote laboratory students use a computer to control an actual experiment that is in a dif-

ferent physical space. Students can use a remote-controlled

camera to observe the experiment and direct modifications

[183]. Remote labs can easily be used with other tools such

as SPICE and MATLAB [184]. Remote laboratories allow

institutions to share expensive equipment, and equipment

downtime is reduced. Since many industrial facilities are controlled remotely, use of remote laboratories provides

students with experiences that can transfer to work settings.

Remote experiments are used in addition to hands-on

experimentation and demonstrations in Slovenia in high

schools and universities [217]. A very recent modification

of remote labs is augmented reality, which combines real

content with computer integrated virtual content [218].

Since remote and in-person labs are not fully fungible [219], it is doubtful remote labs will fully replace in-person

labs, even though remote labs can be more cost effective.

Although remote labs are not yet common in engineering

education, their economic advantages will probably lead to

increased use.

I. Grading A number of other ICCT applications may be useful for

specialized educational functions. Because grading is one

of the most tedious activities of faculty, automation of

grading was first studied with punch cards [220]. Also, in

some ways grading is a natural extension of intelligent

tutors that provide feedback. Tutors provide formative as-

sessment, while programs that score or grade student work

provide summative assessment. Later computer software

for automatic generation and grading of different multiple choice tests to avoid cheating in large classes was

developed [221]. Similar methods are used in intelligent

tutoring systems to generate assessment questions. Spread-

sheets are commonly used for keeping grade records [180].

Cheating in the form of plagiarism can be detected auto-

matically in papers [222] (now available in commercial

systems such as Turnitin and iThenticate) and in code [223].

The thought process students go through when committing plagiarism is discussed in a thoughtful paper [224].

V I I . C O N C L U S I O N

As illustrated in both the first and third major shifts, there

are continuing healthy debates about goals for undergrad-

uate engineering education, e.g., how important are design

skills, how important are analytical and modeling skills, how important are professional skills, especially in compa-

rison to content of a particular engineering discipline. In

addition to debates about content for engineering prog-

rams, there are continuing healthy debates about how to

achieve these goals. For example, engineering education

journals, conferences, and reports have explored ap-

proaches to teaching engineering. Research on learning

and teaching has developed new approaches (fourth major shift) for achieving goals established for engineering edu-

cation. Research has shown that students learn more with

methods such as cooperative learning, problem-based

learning, and inquiry-based learning when compared to

approaches that emphasize information delivery through

presentation. Finally, the use of technologies to achieve

educational goals is growing, but in most cases growth has

Froyd et al.: Five Major Shifts in 100 Years of Engineering Education

1354 Proceedings of the IEEE | Vol. 100, May 13th, 2012

been slower than expected. Growth is faster when the technology is inexpensive and easy to use (e.g., clickers) or

is used extensively in industry (e.g., spreadsheets and

simulators). h

A c k n o w l e d g m e n t

The authors would like to thank J. Lohmann and

L. Tally for insightful comments and editing.

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A B O U T T H E A U T H O R S

Jeffrey E. Froyd (Fellow, IEEE) received the B.S.

degree in mathematics from Rose-Hulman Insti-

tute of Technology, Terre Haute, IN, in 1975 and

the M.S. and Ph.D. degrees in electrical engineer-

ing from the University of Minnesota, Minneapolis,

in 1976 and 1979, respectively.

He is a TEES Research Professor at Texas A&M

University, College Station. Prior to this, he was an

Assistant Professor, Associate Professor, and

Professor of Electrical and Computer Engineering

at Rose-Hulman Institute of Technology. He served as Project Director for

the Foundation Coalition, a National Science Foundation (NSF) Engineer-

ing Education Coalition in which six institutions systematically renewed,

assessed, and institutionalized their undergraduate engineering curric-

ula, and extensively shared their results with the engineering education

community. His research interests include faculty development, curric-

ular change processes, curriculum redesign, and assessment.

Prof. Froyd is a member of the American Society for Engineering

Education, an Accreditation Board for Engineering and Technology

(ABET) Program Evaluator, and a Senior Associate Editor for the Journal

of Engineering Education. He co-created the Integrated, First-Year

Curriculum in Science, Engineering and Mathematics at Rose-Hulman

Institute of Technology, which was recognized in 1997 with a Hesburgh

Award Certificate of Excellence.

Phillip C. Wankat received the B.S.Ch.E. degree

from Purdue University, West Lafayette, IN, in

1966, the Ph.D. degree in chemical engineering

from Princeton University, Princeton, NJ, in 1970,

and the M.S.Ed. degree from Purdue University in

1982.

He joined Purdue University in 1970, where he

has held a variety of positions. He is currently the

Clifton L. Lovell Distinguished Professor of Chem-

ical Engineering and the Director of Undergradu-

ate Degree Programs in the School of Engineering Education, Purdue

University. His technical research is in separation processes, and he has

published two textbooks: Separation Process Engineering (Englewood

Cliffs, NJ: Prentice-Hall, 3rd ed., 2012) and Rate-Controlled Separations

(New York, NY: Springer-Verlag, 1994). He has been active in teaching

graduate students how to teach. He is the coauthor of the book Teaching

Engineering (available free at https://engineering.purdue.edu/ChE/

AboutUs/Publications/TeachingEng/index.html), and author of The Ef-

fective, Efficient Professor: Teaching, Scholarship and Service (Boston,

MA: Allyn & Bacon, 2002).

Prof. Wankat is a Fellow of the American Institute of Chemical

Engineers (AIChE) and the American Society for Engineering Education

(ASEE), and a member of the Text and Academic Authors Association. He

won the Chester F. Carlson and George Westinghouse awards from ASEE.

Froyd et al.: Five Major Shifts in 100 Years of Engineering Education

Vol. 100, May 13th, 2012 | Proceedings of the IEEE 1359

Karl A. Smith received the B.S. and M.S. degrees

in metallurgical engineering from Michigan Tech-

nological University, Houghton, in 1969 and 1972,

respectively, and the Ph.D. degree in educational

psychology from the University of Minnesota,

Minneapolis, in 1980.

He is the Morse-Alumni Distinguished Teaching

Professor and Emeritus Professor of Civil Engi-

neering at the University of Minnesota, where is

currently affiliated with the STEM Education

Center and the Technological Leadership Institute. Since 2006, he has

served part-time as Cooperative Learning Professor of Engineering

Education, School of Engineering Education, Purdue University, West

Lafayette, IN. He has been actively involved in engineering education

research and practice for over 30 years and has worked with thousands

of faculty all over the world on pedagogies of engagement, especially

cooperative learning, problem-based learning, and constructive contro-

versy. He has co-written eight books including How to Model It: Problem

Solving for the Computer Age (Edina, MN: Burgess International Group,

1994); Active Learning: Cooperation in the College Classroom (Edina, MN:

Interactive Books, 3rd ed., 1991); Cooperative Learning: Increasing

College Faculty Instructional Productivity (San Francisco, CA: Jossey-

Bass, 1991); Strategies for Energizing Large Classes: From Small Groups

to Learning Communities (San Francisco, CA: Jossey-Bass, 2000); and

Teamwork and Project Management (New York, NY: McGrow-Hill, 3rd ed.,

2005).

Prof. Smith is a Fellow of the American Society for Engineering

Education (ASEE), past Chair of the Educational Research and Methods

Division, and recipient of the Chester F. Carlson award. He also received

the Ronald J. Schmitz Award for outstanding continued service to

engineering education through contributions to the Frontiers in Educa-

tion Conference, ERM Division of ASEE and Education Society of IEEE.

Froyd et al.: Five Major Shifts in 100 Years of Engineering Education

1360 Proceedings of the IEEE | Vol. 100, May 13th, 2012