What Competencies Should Undergraduate Engineering Programs Emphasize?

 

WhatCompetencies ShouldUndergraduate EngineeringProgramsEmphasize?

ASystematic Review

HonorJ.Passowa and ChristianH.Passowb

aDartmouthCollege, bCreare LLC

Abstract Background Under Washington Accord or ABET accreditation requirements, faculty must envision, collectively articulate, and prioritize the competencies that students should gain from their educational program to prepare for life and myriad career paths.

Purpose When faculty create specifications for designing a curriculum, they need to answer questions, including “Among generic engineering competencies, what is the relative impor- tance for professional practice across disciplines and work contexts?”

Scope/Method A search identified the intersection of four concepts (competence, engineering, practice, and importance) in engineering and education databases (8,232 reports, 1990–2012). This review integrates a quantitative synthesis inspired by meta-analytic techniques (27 studies, 14,429 participants) and a qualitative thematic analysis (25 studies, 2,174 participants plus 36,100 job postings) to establish a comprehensive list of generic engineering competencies, their relative importance, and rich descriptions highlighting interrelationships.

Conclusions Engineers’ technical work is inseparably intertwined with team-player collab- oration. The most crucial skill is coordinating multiple competencies to accomplish a goal. Six- teen generic competencies important for engineering practice are defined. Compared with Washington Accord graduate attributes, the evidence-based competencies re-envision “teamwork” as coordinate efforts, split “life-long learning” into gather information and expand skills, broaden “ethics” to take responsibility, expand “design experiments” to measure accurately and separate it from interpret data, apply “contemporary issues” and “impacts” in define con- straints, modify “manage projects” to devise process, and add important competencies (take ini- tiative, think creatively, and make decisions). Definitions are refined for communicate effectively, design solutions, apply knowledge, apply skills, and solve problems. Problem solving is the core of engineering practice.

Keywords workplace; competence; systematic review; accreditation; outcomes

Introduction Since the advent of ABET Engineering Criteria 2000, engineering programs in many coun- tries have been required to help students develop specific program outcomes (Lucena, Downey, Jesiek, & Elber, 2008) or competencies. The competencies on ABET’s list have been debated and differ by country as permitted in the Washington Accord (International

Journal of Engineering Education VC 2017 ASEE. http://wileyonlinelibrary.com/journal/jee July 2017, Vol. 106, No. 3, pp. 475–526 DOI 10.1002/jee.20171

 

 

Engineering Alliance, 2016). Yet, the relative emphasis among these competencies has been left for each program to determine. Under the Washington Accord paradigm, faculty need the ability to envision, collectively articulate, and prioritize the competencies that students should gain from their educational program in order to prepare for a myriad of career paths (Passow, 2008). Specifically, when faculty design a curriculum that “support[s] the integration of knowledge, skills . . ., and . . . values necessary for today’s professional practice” (Sheppard, Macatangay, Colby, & Sullivan, 2008, p. 5), they need to know the relative importance among the competencies for engineering practice in order to establish specifications. Although this need is listed as high priority by the United States National Engineering Edu- cation Research Colloquies (Steering Committee of the National Engineering Education Research Colloquies, 2006), only two small reviews have been published (Male, 2010; Passow, 2008). Engineering faculty should strongly feel the need as they apply product design principles to curriculum design. That is, before establishing specifications for product design, engineers make a list of “what the product has to do” and then determine the “relative importance” (Ulrich & Eppinger, 1995, p. 54) of items on that list.

We identified 52 studies (27 quantitative and 25 qualitative) that address what competen- cies engineers need and which are most important. Yet, limitations in each study – especially in sampling – put generalizability in question. No particular study’s results generalize across different engineering disciplines, different practice settings (such as industry sector, type of organization, and geographic area), or different experience levels (such as recent graduate, mid-career, or senior engineers). Nor does the existing literature settle questions about how much the relative emphasis among competencies changes with alternate wording of the com- petencies or changes over time (such as by year of data collection or by years of engineering experience).

This systematic review integrates qualitative and quantitative approaches. The purpose is to answer the practical question of curriculum design: What competencies should undergrad- uate engineering programs emphasize? The specific research question addressed by this study is “For engineering graduates, what is the relative importance for effective professional prac- tice among various competencies – both technical and professional?” This review answers this question for what Male (2010) calls “generic engineering competencies,” which are important across engineering disciplines and work contexts.

SearchMethod The search strategy (Figure 1) was adapted from the leading approach, the Cochrane Hand- book for Systematic Reviews of Medical Interventions (Cochrane Collaboration, 2011). An effective search depends on clear definitions because published studies use a variety of terms and typically define them only implicitly. In this study, competencies are defined as

the knowledge, skills, abilities, attitudes, and other characteristics that enable a person to perform skillfully (i.e., to make sound decisions and take effective action) in com- plex and uncertain situations such as professional work, civic engagement, and per- sonal life. (Passow, 2008)

In this definition, knowledge includes four types of knowledge defined by Anderson et al. (2001): factual knowledge, conceptual knowledge, procedural knowledge (knowing both how and when to use specific skills and methods), and metacognitive knowledge (self-knowledge and both how and when to use cognitive strategies for learning and problem solving). Thus,

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competencies – and the related terms “learning outcomes” and “graduate attributes” – are the skills and abilities that graduates should demonstrate at the end of their undergraduate program.

Competencies are distinct from inputs. Inputs are the subjects that are taught and the amount of class time spent on each subject. This study assumes that competencies, as opposed to educational credentials alone, are the foundation of successful professional practice, an assumption shared with agencies that grant licenses for individuals to practice professions (Larson, 1983; Office of the Professions, 2000).

We sought studies at the intersection of four concepts: competence, engineering, practice, and importance. Two independent librarians helped select databases and develop search strate- gies and terms. The final searches were conducted on June 15, 2012, and were restricted to

Figure 1 Flow diagram of the literature review process and the resulting 52 stud- ies used to answer the question, “For engineering graduates, what is the relative importance for effective professional practice among various competencies – both technical and professional?”

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studies published after January 1, 1990, because events in the early 1990s sparked a spirit of innovation, a torrent of national meetings and workshops, and a worldwide movement toward outcomes-based quality assurance in engineering education (Prados, Peterson, & Lattuca, 2005). The topic’s interdisciplinary nature required searches in engineering indexes (Compen- dex and Inspec), an education index (ERIC), and indexes that span both fields (Proquest’s Dissertation Abstracts and ISI Web of Science). Because this research question involves con- cepts that have no precise scientific vocabulary and typically are not indexed with controlled terms, we included multiple common terms (Appendix A). No language exclusions were used.

To be included in this review, a study must meet three requirements:

Assess competence applied by an individual in a job after graduation from an undergradu- ate level engineering program, whether or not they pursued advanced degrees. We excluded engineering technology graduates, “requirements engineering,” “knowledge engineering,” agricultural, forest, and food engineering. We call this criterion “on-the-job competence for engineering graduates.”

Address a comprehensive set of engineering competencies including both technical and professional competencies, not a focused subset of competencies such as only leadership skills or exclusively design-related competencies. We call this criterion “comprehensive competencies.”

Measure or evaluate importance in the workplace without reference to the educational background of the engineering graduate. That is, we excluded studies of the gap between what is required at work and the individual’s undergraduate preparation because gap measures cannot generalize to other programs. Evaluation approaches must be described, including the sample, the measurement approach (e.g., survey question asked), and the analysis approach. We call this criterion “evaluate importance in the workplace.”

For quantitative studies, there were two additional inclusion criteria: report ratings for all measured competencies and measure at least half of the ABET competencies to provide stable effect sizes.

As is customary in systematic reviews, we used unique studies as our data. A study is built on an original dataset but may be published in multiple reports. A study can also include mul- tiple samples, such as faculty and alumni whose opinions are analyzed separately. For exam- ple, our review identified research conducted by the CDIO group as a single study. They collected opinion data on paper surveys from multiple samples, which were analyzed sepa- rately: faculty, industry leaders, alumni five years after graduation, and alumni 15 years after graduation. They collected separate samples in three different countries and analyzed each sample separately. They published their results in two reports: a journal article (Bankel et al., 2003) and a book (Crawley, Malmqvist, Ostlund, & Brodeur, 2007).

The abstracts identified were pooled, and duplicates of any report were removed (Figure 1). The first author examined each of the 7,021 unique titles and abstracts against the inclusion criteria. For 135 ambiguous reports, this author examined the full text against the inclusion criteria. For 19 of the studies, we corresponded with the authors of the original studies. To avoid bias, every report that met the criteria was retained, regardless of methodo- logic quality. For every included report, the first author evaluated each listed reference. During June–December of 2014, the first author used ISI Web of Science and Google Scholar to evaluate each study citing included reports. The first author linked multiple reports

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of a single dataset because we chose the study – not the report – as our unit of analysis. Appendixes B to G itemize all 52 included studies and summarize their methods. The studies addressed six distinct but complementary research questions:

How important is each of these competencies for engineering work? This question was operationalized on surveys as a closed-form question, using the following instruc- tion above a list of competencies, “Rate how important each competency is for engi- neering work.” (Appendix B [1–28])

What competencies differentiate between outstanding and ordinary engineers? (Appendix C [29–32])

What competencies are exhibited by a good (or effective or exceptional) engineer? (Appendix D [33–35])

What competencies are needed for success in your employees’ engineering work? (Appendix E [36–41])

What competencies are important in your own engineering work? In general? In a specific episode of success or failure? (Appendix F [42–45])

What competencies characterize engineering practice? How do they interact? (Appen- dix G [46-54])

AnalyticalMethods The quantitative synthesis is based on closed-form research questions beginning with “Rate how important each competency is [in the list below]” while the qualitative thematic analysis is based on open-ended questions, beginning with “What competencies . . .”

Methodological Quality of Included Studies There is no existing tool for appraising methodological quality in cross-sectional opinion studies, whether they be surveys, interviews, or ethnographic observations (American Educa- tional Research Association, 2014; Sanderson, Tatt, & Higgins, 2007). Therefore, we devel- oped five indicators of study quality.

Comparison group Higher quality studies include a comparison group to control for study design and wording while varying practice context. Of the quantitative studies, 15 had comparison groups [1–4, 7–11, 15, 16, 22, 25, 27, 28]. Of the qualitative stud- ies, four included comparisons by addressing the question, “What competencies differ- entiate between outstanding and ordinary engineers?” [29–32]

Sampling Higher quality studies sample to minimize bias either by sampling at ran- dom from a comprehensive frame or seeking 100% census. Next, investigators attempt to determine the extent and direction of nonresponse bias (Lohr, 2008). Of the survey studies included in the quantitative analysis, only the studies by Passow [25] and Brunhaver et al. [26] assessed nonresponse bias. Qualitative studies are not subject to selection bias because their aim is rich description of a sample not inference from a sample to a population.

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Validated measures Higher quality studies validate measures for survey questions. Ideally, the validity of survey questions should be evaluated, by asking, “How repre- sentative of and relevant to the topic of interest is the survey as a whole; that is, does it have content validity?” and “Does each question measure what it is intended to mea- sure; that is, does it have construct validity?” (Sartori & Pasini, 2007). All of the 27 studies in the quantitative synthesis incorporated methods to achieve content validity, but none reported addressing construct validity.

Detailed accounts Higher quality studies provide detailed accounts of participants’ experiences. Detailed accounts of experiences are more reliable than respondents’ self- assessment or expert panel methods for competency research because the accounts mitigate the influence of beliefs, inaccurate self-assessment, and aspects of self-report bias (Walther, Kellam, Sochacka, & Radcliffe, 2011). Of the 52 studies included in this review, 21 were based on detailed accounts of participants’ experience [29–32, 34–38, 42–51, 53, 54], a method that exceeds the rigor of the expert panel process through which ABET’s learning outcomes were developed for accreditation of under- graduate engineering programs in the United States. The expert panel process was later used to adapt ABET’s learning outcomes to the international quality standard set forth in the Washington Accord’s graduate attributes.

External observation Higher quality studies involve external observation. Of the studies that provided detailed accounts of experience, seven studies additionally included external observation of engineers at work [34, 35, 47, 48, 50, 51, 53].

We accounted for varied methodologic quality among the 52 included studies by analyzing in phases. After synthesizing the aggregated quantitative studies, we analyzed quantitative studies with comparison groups. Subsequently, the qualitative thematic analysis extracted themes from the highest quality studies first, that is, studies with a comparison group or external observation of engineers at their work.

Quantitative SynthesisMethods Altogether, the 27 studies included in the quantitative synthesis addressed the question, “Rate the importance of each competency [in the list below]” (Appendix B) by collecting data from 60 samples composed of 14,429 respondents. These respondents were 6,063 practicing engi- neers, 7,934 alumni of undergraduate engineering programs (not all of whom work in engineering), and 432 engineering faculty. Mean ratings were reported for each included study, but standard deviations were available for only 24 out of the 60 samples. The absence of so many standard deviations prevented formal meta-analysis.

The second author identified and recorded the wording for each competency and all pub- lished ratings from the original studies. Together, we created common metrics. Metrics require common constructs and a common scale. We selected ABET’s 11 outcomes as the set of common constructs because they are familiar constructs among engineering faculty world- wide, are more specific than the Washington Accord (WA) graduate attributes, and were the tap root for developing the WA’s graduate attributes. The second author tentatively mapped each published competency onto ABET’s a–k outcomes, specifically ABET’s 2015–2016 Gen- eral Criteria for Baccalaureate Level Programs. Criterion 3. Student Outcomes (ABET, 2014):

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(a) an ability to apply knowledge of mathematics, science, and engineering [similar to WA 1; measured in 51 samples]

(b) an ability to design and conduct experiments, as well as to analyze and interpret data [similar to WA 4; 43 samples with any related wording, with 12 of those sam- ples specific to experiments and 15 specific to data]

(c) an ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability [similar to part of WA 3; 52 samples]

(d) an ability to function on multidisciplinary teams [similar to WA 9; 56 samples]

(e) an ability to identify, formulate, and solve engineering problems [similar to part of WA 3; 53 samples]

(f) an understanding of professional and ethical responsibility [similar to WA 8; 43 samples]

(g) an ability to communicate effectively [similar to WA 10; 58 samples]

(h) the broad education necessary to understand the impact of engineering solutions in a global, economic, environmental, and societal context [similar to WA 6 & 7; 51 samples]

(i) a recognition of the need for, and an ability to engage in life-long learning [similar to WA 12; 50 samples]

(j) a knowledge of contemporary issues [similar to WA 6 & 7; 17 samples]

(k) an ability to use the techniques, skills, and modern engineering tools necessary for engineering practice [similar to WA 5; 43 samples].

The Washington Accord’s graduate attributes for “problem analysis” (WA 2) and “project management and finance” (WA 11) have no counterparts in the ABET criteria. After tenta- tive mapping, we discussed every mapping until reaching consensus.

The first analysis compared importance ratings of the ABET-mapped competencies. With common constructs established, a common scale can be created. We needed a measure for comparing a specific competency’s rating to the typical importance rating for all compe- tencies in that sample. To accomplish this, we adapted Glass’s delta effect size (Ellis, 2010), which standardizes the measure of interest by subtracting the measure for a comparison group and dividing by the comparison group’s standard deviation. The ABET-mapped competen- cies in each sample were our comparison group. For example, for a variable such as “the ability to communicate” in the Lattuca et al. study [14], we started with the mean importance rating for all 1,622 participants (4.39). Then we focused on the mean importance ratings for all the ABET-mapped competencies in that study, calculating the average of the mean importance ratings (that is, the grand mean across competencies, which was 3.79) and the standard devia- tion around that grand mean (0.46). Finally, we calculated the standardized mean importance rating for communication as (4.39 – 3.79)/0.46 5 1.31. A standardized importance rating of zero denotes average importance in that study, a positive rating denotes above average impor- tance, and a negative rating denotes below average importance.

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With common metrics established, we began analysis. The dataset was a table with a col- umn for each of the 11 competencies and a row for each of the 60 samples. Each cell had a single entry, which was the standardized mean importance rating for that competency and sample. We calculated the grand mean of each column (that is, across samples). We graphed these grand means for each competency in descending order. For every competency, these unweighted values were close to the means weighted by their sample size. The grand mean importance ratings for the 11 competencies clearly differed. The question was, “Which of these apparent differences are statistically significant?” One-way ANOVA confirmed that there were differences in importance ratings across competencies, which were the repeated measures for the 60 samples. Results were the same whether the samples were unweighted (that is, each sample represents an observation, F(10, 446) 5 37.4, p < .0001), or weighted (that is, each respondent represents an observation, F(10, 151728) 5 22452.2, p < .0001).

To answer the question “Which ones differ?” we performed parametric tests for post hoc, balanced, all-pairwise comparison for practical equivalence. We compared statistical techni- ques (e.g., different multiple comparison tests, weighted and unweighted analysis, aggregated and subgroup analysis, and included or excluded outliers). It was Fisher’s least significant dif- ference test (studywise a 5 0.05) on the unweighted aggregated data of 60 samples with no data excluded that captured the essential pattern of differences that held true in the aggregate across various statistical techniques.

We also evaluated “the overall relationship . . . for different subdivisions of the data” (Glass, McGaw, & Smith, 1981, p. 80). Subgroups were available for survey year (1990– 1999 or 2000–2013), region of respondents (U.S./Canada, Europe, and Australia/New Zea- land), and role in engineering (currently practicing engineer, engineering alumni, and engi- neering faculty). Distinct facets of certain competencies defined other subdivisions of the data. For example, some surveys used the general term “communication,” while others speci- fied “listening,” “writing,” “oral communication,” or “graphical communication.” All subdivi- sions of competencies and subgroups were analyzed separately.

A second analysis compared importance ratings of the competencies that did not map to ABET outcomes. Each competency listed in a survey but not mapped onto an ABET compe- tency was analyzed thematically. This analysis was independent of the qualitative studies. The second author created tentative categories. Then we discussed every competency’s wording in its original study and its relationship to other items in its tentative category to establish themes that became additional common constructs. Any theme clearly represented in at least five distinct studies was designated an emergent competency, as was any theme in at least three studies that was also heavily represented in the qualitative studies. The themes are listed in the Results section. For each emergent competency, we calculated the standardized mean importance rating to allow comparison to the ABET-mapped competencies.

Qualitative Thematic AnalysisMethods Altogether, the 25 studies addressing the “What competencies . . . ” questions (Appendixes C–G) collected data from 36,100 job postings and more than 2,174 participants in studies of various types: 557 participants in interviews, case studies, and ethnographic shadowing; 206 participants in surveys in which supervisors separately classified the participants’ work habits; 976 respondents to open-ended survey questions; and 435 respondents to closed-ended survey questions about how work time is spent. The published findings in the text and graphics of these studies constituted the data for thematic analysis of the qualitative studies in this

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systematic review. We built themes from the original investigators’ interpretations of their data. To ensure a repeatable approach, we adhered to Braun and Clarke’s (2006) classic pro- cess for thematic analysis, which offers a sequence for analysis and emphasizes the importance of reporting how the analysis was conducted and why. We decided that the qualitative the- matic analysis would augment the quantitative synthesis, not stand on its own; therefore, we focused on two guiding questions:

What are the qualitative studies saying – if anything – that is not included in the quantitative synthesis?

What do the qualitative studies omit that the quantitative synthesis includes?

The goal was to identify themes across all the qualitative studies, not within a particular study. No theoretical framework was imposed. Instead, an inductive approach led to themes that are “strongly linked to the data” (Braun & Clarke, 2006, p. 83).

In the first stage, the first author read all 25 studies and demarcated all study findings related to the two guiding questions, creating the dataset. After repeated readings, the first author generated initial codes, that is, identified major ideas pertinent to the guiding ques- tions. Four ideas emerged for detailed investigation after extensive discussion by both authors. Primarily, the rich descriptions of specific competencies could enhance interpretation of the quantitative synthesis. In addition, three patterns were identified that had not been present in the quantitative synthesis:

One competency – something about the combination of vision and initiative – was frequently central in qualitative studies, yet was rare in quantitative studies.

In engineering practice, some competencies are typically coordinated that appear dis- tinct in the quantitative studies.

Actual engineering practice does not match the emphasis in engineering curricula.

In the second stage, the first author systematically searched for themes in three phases beginning with the highest quality studies. This search consisted of open coding all data and tentatively labeling any theme that was meaningful in the data. A decision in qualitative research is, “What counts as a theme?” (Braun & Clarke, 2006, p. 82). The goal was not a full description of the data. We sought prominent, key themes (as opposed to subtle ones) that would augment interpretation of the quantitative synthesis around the idea of generic engineering competencies. In addition to the three patterns identified in the first stage of qualitative analysis that had not been present in the quantitative synthesis, themes were sought in the following sequence to ensure primary reliance on the included studies of the highest methodological quality. Themes were defined as

competency concepts that differentiated between outstanding and ordinary engineers in any of the four high-quality studies that had a comparison group [included studies 29–32 based on data from 616 participants];

any concept emerging from the seven high-quality studies involving external observa- tion of engineers at work [included studies 34, 35, 47, 48, 50, 51, 53 based on data from 261 participants], as opposed to data exclusively from self-report interviews, open-ended survey questions, or job postings; and

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any additional concepts emerging in any of the other studies. Note that among these lower quality studies, a concept or competency needed to be explicitly described in at least five out of the 25 studies to qualify as a theme.

In a third stage, both authors reviewed and consolidated themes, taking a realist approach, not a constructionist approach. That is, our themes capture the meanings within the studies without considering external influences of society. The lower-inference, realist approach matched the spirit of our low-inference qualitative methodology. Then, in a confirmatory step beyond what is described by Braun and Clarke (2006), the first author systematically coded all data a second time to ensure that every instance of every theme was identified. When the data indicated it, that author refined theme definitions to capture all key concepts in the data. We then discussed changes in theme definitions until we reached consensus. Together, we examined themes for robustness across publication date and geographic region.

Quantitative Synthesis Results

AggregatedData The data and statistical results for the aggregated quantitative dataset appear in Figure 2. Each competency’s grand mean importance across all 60 samples is shown. A white diamond is a grand mean for all 60 samples, while a black diamond is a grand mean in which each sam- ple is weighted by its number of respondents (total N 5 14,429). The horizontal “tie lines” at the top of Figure 2 show the groups of competencies having unweighted mean importance that are not significantly different by the Fisher least significant difference test (studywise a 5 0.05).

Interpreting the graph, there are four statistically distinct levels of importance ratings. The top level consists of three competencies: problem solving, communication, and teamwork. The next lower level of importance consists of ethics and life-long learning. Then there are four competencies at the same level: math, science, and engineering knowledge; engineering tools; experiments and data analysis (combined); and design. The competencies deemed of least importance for work by the respondents are contemporary issues and understanding impacts of one’s work.

Unfortunately, the standardized measures necessary for the quantitative synthesis hide the fact that respondents’ lowest importance ratings tend to be at or above the middle rating on the original surveys’ absolute scales. Therefore, even the bottom cluster competencies are deemed valuable by respondents.

Subdivisions of the Data Results for all subdivisions of the data are in Figure 3, shown with the tie lines developed for the aggregated data. Subdivisions of the samples by survey year and by respondents’ geography and role revealed a few deviations from the aggregate results, yet the main result is a pattern that is robust across subdivisions, as follows. The competencies in a top cluster – problem solv- ing, communication, and teamwork – have top ratings in all subgroups. The competencies in a bottom cluster – contemporary issues and impact – have bottom ratings in all subgroups. No top cluster competency is statistically tied with a bottom cluster competency in any subgroup.

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Competencies in the intermediate cluster – ethics; life-long learning; math, science, and engineering knowledge; engineering tools; the combined “experiments & data analysis”; and design – sometimes deviate slightly from the aggregate pattern. Two statements summarize the small but statistically significant variations in the intermediate cluster. First, the

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Figure 2 Importance for work by ABET-mapped competency: data and statisti- cal results for the entire quantitative data set.

Note: The quantitative dataset consisted of 60 samples from 27 studies pub- lished 1990-2013 representing 14,429 respondents from around the world, a total of 6,063 practicing engineers, 7,934 alumni of undergraduate engineering programs (not all of whom work in engineering), and 432 engineering faculty.

Legend: Circles: A circle above zero denotes above-average importance among ABET-mapped competencies for a sample; a circle below zero denotes below- average importance. Diamonds: A white diamond is a grand mean for all 60 samples. A black diamond is a grand mean weighting each sample by its number of respondents. Lines: Horizontal tie lines “tie together” competencies whose unweighted grand means do not differ statistically (studywise a 5 0.05). Inter- pret as four levels of importance.

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competencies in the third tie line (math, science, and engineering; engineering tools; experi- ments and data analysis combined; and design) never tie with the top two competencies (problem solving and communication). Second, the competencies in the second tie line

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Figure 3 Importance for work by ABET-mapped competency: statistical tie lines for the entire quantitative dataset plus results for subdivisions of the data.

Note: The only subconstructs of a competency that deviate statistically from the aggregate pattern are “experiments & data analysis” and the distinct con- structs of “interpret data” and “design experiments.”

Legend: Diamonds: A diamond at 1.0 denotes a competency whose impor- tance – on average across all samples – is a whole standard deviation above the mean. A diamond at zero denotes a competency of average importance across all samples. Lines: Horizontal tie lines “tie together” competencies whose unweighted grand means do not differ statistically (studywise a 5 0.05). Interpret as four levels of importance. Ovals: Ovals denote the top and bottom clusters of competencies that remain statistically distinct across subdivisions of the samples, that is, all varia- bles related to survey year and respondent’s geography and role – practicing engi- neers, alumni of undergraduate engineering programs (not all of whom work in engineering), and engineering faculty.

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(ethics and lifelong learning) never tie with the bottom two competencies (issues and impacts). In short, we found that there are core competencies that are generically important for engineering, but patterns of importance are based on academic discipline and work envi- ronment. Our finding is also a common emphasis in three theories that cross professions: Holland’s (1997) theory of vocational personalities and work environments, Spencer and Spencer’s (1993) models for superior performance, and Stark, Lowther, and Hagerty’s (1986) framework for outcomes of professional programs.

Analysis of conceptual components of the competencies, called subconstructs, demonstrate that combining dissimilar constructs hides valuable distinctions. Within the life-long learning competency (0.20 mean standardized importance in 50 samples), the mean importance rating for gather information is highest (0.59 in 19 samples) followed by expand skills (0.25 in 13 samples). Even though these differences in ratings are not statistically significant, they indi- cate that subconstructs for life-long learning may clarify this vague competency. ABET’s out- come 3(b) “design and conduct experiments, as well as to analyze and interpret data” has subconstructs that deviate statistically from the aggregate pattern. Survey items that combine the concepts of experiments and interpreting data as ABET does are rated at a level statisti- cally tied in the intermediate cluster (20.29 in 25 samples in 11 studies; the gray diamond in Figure 3). The surveys containing interpret data alone, worded such as “demonstrated ability in data analysis and interpretation” (0.82 in 15 samples in six studies), have ratings equal to the top cluster of problem solving, communication, and teamwork (Figure 3). The surveys containing experiments alone, worded such as “ability to design and conduct experiments” (21.42 in 12 samples in six studies), have ratings below the bottom cluster of issues and impacts (Figure 3). In short, ABET’s outcome 3(b) “design and conduct experiments, as well as to analyze and interpret data” is not a valid single competency because “interpret data” rates with top cluster competencies, while “experiments” rates below bottom cluster competencies. Such dramatic differences in the ratings for subconstructs indicate that combining “experiments” and “interpreting data” hides a valuable distinction in the mind of practicing engineers.

ComparisonGroups within Studies Two studies compared alumni’s importance ratings across survey years [9, 25]. Both found a pattern that was consistent over time by several measures. Rooney and Puerzer’s (2004) results note the “striking” [9, pp. F3G–12] consistency in importance of competencies over time with the most important three and the least important two the same over graduation years while the middle ratings “show some variation in order around a relatively small range” [9, pp. F3G–12].

Ten studies compared importance ratings for respondent groups in different roles, such as practicing engineers, engineering alumni (not all of whom are practicing), and engineering faculty. The predominant finding of consistent importance ratings for competencies in top and bottom clusters with some variation for middle competencies is explicitly stated in six studies [1, 2, 4, 7, 8, 25] and evident in another three [3, 22, 26]. Notably, this predominant finding – which we depict in Figure 3 – is also an inference made by 26 authors of included studies. All four studies comparing recent engineering graduates to more experienced engi- neers [7, 8, 16, 25] showed that importance ratings do not change with level of experience. Five studies compared importance ratings across different wordings [3, 8, 10, 25, 28]. Some wording changes led to statistically significant changes in relative importance, while others

Undergraduate Engineering Competencies: A Sytematic Review 487

 

 

did not. Because wording is sometimes important, a synthesis that includes many variations of wording, such as this one, is far more valuable for informing curricular decision making than any single, primary study.

Wordings of Competencies in Survey Items Mapping survey writers’ competencies to ABET’s 11 learning outcomes led to two qualitative findings. First, the survey wordings were surprisingly diverse. The authors of 26 surveys were free to adopt ABET’s concepts and wording, but only one did not alter ABET’s wording or concepts. The diverse wordings lead to two inferences: wording matters to those making deci- sions about curricula, and ABET’s list as worded may seem vague or incomplete to many faculty.

Second, three terms warrant particular attention: teams, modeling, and analysis. While we mapped competencies to ABET’s outcome 3(d) “ability to function on multidisciplinary teams,” we discovered its flaws. Twenty-one studies used the word “team” without any con- cept related to interdisciplinarity, while only seven studies had a survey item that combined the concepts of teams and interdisciplinarity. In addition, concepts related to teamwork were included in many surveys, such as social or interpersonal skills (five studies), open- mindedness (five studies), negotiation/conflict management (four studies), networking (two studies), and others, while only four additional surveys included items pertaining to interdis- ciplinarity. The variety of survey items pertaining to different aspects of teamwork indicates that concepts related to teamwork, managing self and others, leading others, and people- related skills are overlapping, intertwined, and difficult to articulate. We mapped to ABET’s teamwork conservatively by including only items that had the word “team” in them or both the concept of teams and interdisciplinarity.

Seven surveys included “modeling” [8, 10, 13, 17, 19, 21, 22], which is not found in ABET’s student outcomes. Only one, limited meaning of “analysis” is included in ABET’s analyze and interpret data, which is outside the context of modeling. The Washington Accord obliquely mentions “prediction and modeling” in WA 5 with engineering tools. Yet, 12 studies included the term “analysis” or “analyze” in the context of modeling [1, 4, 6–8, 10, 11, 13, 18, 20, 22, 24], rather than as an activity that precedes interpreting data. For example, Bankel et al. [8], used terms in their surveys that are not found in ABET: “modeling of a sys- tem,” “estimation and qualitative analysis,” and “analysis with uncertainty.” Lang et al.’s [6] survey included two items using “analysis” with distinct connotations: “demonstrated ability in data analysis and interpretation” and “computer literacy in analysis tools used in engineer- ing specialty.” The qualitative thematic analysis confirmed the importance of modeling as dis- tinct from analysis.

Competencies Not Mapped to ABET’sOutcomes The standardized mean importance rating for each emergent competency was graphed along- side the means for the ABET competencies (Figure 4). Planning and time management (nine samples), which is an element of the Washington Accord’s “project management” (WA 11), is rated slightly above the entire top cluster of ABET competencies. Four competencies fall between the top cluster and the intermediate cluster: make decisions (seven samples), take ini- tiative (five samples), think creatively (16 samples), and focus on goals (six samples). System thinking (19 samples) rates near the average, in the middle of the intermediate cluster. Between the intermediate and bottom clusters are four emergent competencies: lead (18 samples),

488 Passow & Passow

 

 

Planning & �me management (9 samples)

Make decisions (7)

Take ini�a�ve (5)

Think crea�vely (16)

Focus on goals (6)

Interpret data (15)

Design experiments (12)

Lead (18)

Manage (25)

Interact with diverse people (20)

Understand business context (46)

Foreign language (20)

System thinking (19)

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Figure 4 Importance for work by competency: comprehensive results for all subdi- visions of the quantitative data on ABET-mapped competencies with comparison to non-ABET competencies.

Note: The quantitative dataset consisted of 60 samples from 27 studies published 1990–2013 representing 14,429 respondents from around the world, a total of 6,063 practicing engineers, 7,934 alumni of undergraduate engineering programs (not all of whom work in engineering), and 432 engineering faculty. Observe that the importance of interpret data falls between communication and teamwork in the top cluster, while the importance of design experiments falls below the importance of the bottom cluster competencies. The standardized measures hide the fact that respondent’s lowest importance ratings tend to be at or above the middle rating on the original surveys’ absolute scales. Therefore, even the bottom cluster competen- cies are deemed valuable by respondents.

Legend: Diamonds: A diamond at 1.0 denotes a competency whose importance – on average across all samples – is a whole standard deviation above the mean. A dia- mond at zero denotes a competency of average importance across all samples. Ovals: Ovals denote the top and bottom clusters of competencies that remain statistically distinct across all variables related to survey year and respondent’s geography and role – practicing engineers, alumni of undergraduate engineering programs, and engineering faculty.

Undergraduate Engineering Competencies: A Sytematic Review 489

 

 

manage (25 samples), interact with diverse people (20 samples), and understand business context (46 samples). Of these, manage and understand business context are elements of the Washington Accord’s “project management.” Noticeably below the bottom cluster is com- municate in a foreign language (20 samples).

Qualitative Thematic Analysis Results

The qualitative studies aimed to answer the “What competencies . . . ?” questions. The quali- tative studies – unlike the quantitative studies – explored interrelationships among competen- cies and the nature of the competencies themselves. Seven major findings emerged, each of which was still evident when studies published prior to 2000 were omitted and when particu- lar geographic regions were omitted.

Finding 1: Engineering competencies are tied to the life-cycle of a product, process, or system. Two of the qualitative studies described the nature of engineering work based on interviews and observations: Korte et al. [43] and Trevelyan [51]. Trevelyan’s [51] description of engineering work as progressing in six phases across disciplines and industries captures the essence of both studies’ findings, as summarized in the next four paragraphs.

The first three phases lead to the output of a project proposal that provides sufficient information for clients, investors, regulators, and contractors to decide whether to continue. If decision makers choose to move ahead, the last three phases of project execution end in delivering the products or services with the required performance and reliability. Note that the plural “engineers” in the following description implies collaborative work of multiple engineers who each bring their expertise to the table.

In Phase 1, engineers help clients articulate requirements through understanding and shaping clients’ perceptions of their needs in terms of engineering possibilities. In Phase 2, engineers design and evaluate alternatives; that is, they develop alternative solution concepts and assess how well they meet client requirements. In Phase 3, engineers predict performance, reliability, and risk for a proposed solution by imagining a host of uncontrolled events and collecting data, conducting experiments, and performing analysis and simulations. The deci- sion to proceed is based on these predictions [51].

In Phase 4, engineers conduct detailed design and planning, and then organize and mobi- lize resources. In Phase 5, engineers coordinate, monitor, and evaluate work while meeting safety, schedule, and budget constraints. They diagnose and correct deficiencies and adapt plans to circumstances. In complex systems, engineers lead ongoing operations and mainte- nance. In Phase 6, engineers decommission the product, process, or system by planning, coor- dinating, and monitoring the recycling, reuse, and remediation that comes at the end of the project’s life-cycle [51].

Trevelyan’s [51] six phases of the life cycle are compatible with the essence of the CDIO phases (conceive, design, implement, operate) [13, p. 8] and with fragments of descriptions in all the other studies in this review. According to Trevelyan (2014), “Any one engineer seldom performs all of these [phases in a single project] but may well perform all of them through the course of a long career” (pp. 48-49).

Korte, Sheppard, and Jordan [43] asked recently graduated engineers to describe “a project or problem assigned to them . . . which they had to use their technical expertise to resolve” [p. 5]. Four technical competencies emerged: “organize, define, and understand a problem; gather, analyze, and interpret data; document and present the results; and project-manage the

490 Passow & Passow

 

 

overall problem-solving process” [43, p. 6]. These correspond roughly to Phase 1 and Phase 3 in Trevelyan’s life-cycle description.

Finding 2: Technical competence is inseparably intertwined with effective collabora- tion. The most striking finding in this systematic review is that technical competence is inseparably intertwined with effective collaboration [35, 36, 43–54].

All engineering is, of necessity, both technical and social. . . . Good engineering (as in engineering which is effective) demands the thorough integration of these elements in ways that transcend conventional dichotomies [50, p. 351 emphasis in original]. The knowledge mobilized in the course of engineering . . . is never “just technical” with “the social” bolted on. Rather, these two dimensions are in a very practical sense insep- arable. . . . Since the two are inseparable in everyday engineering practice, the bound- aries drawn between them are inevitably arbitrary. [50, p. 336]

Multiple studies described the root cause of this inseparability; the systems surrounding the “technology-in-the-making” [53, p. 151] are too complex and interdisciplinary for one person to fully know or implement [29, 30, 34, 35, 42-44, 46–51, 53, 54]. In Trevelyan’s [51] words, “the foundation of engineering practice is distributed expertise enacted through social interactions between people: engineering relies on harnessing the knowledge, expertise, and skills carried by many people, much of it implicit and unwritten knowledge” [p. 175].

Engineering work . . . bridges the basic sciences and practical interests and concerns. It tends to be a collective work wherein individuals have a detailed understanding of subsystems and their various specialized procedures, but often lack a similar under- standing of the system on the aggregated level [53, p. 162]. [Engineering problem solving is] essentially a collective . . . practice . . . based on the co-workers’ . . . ability to share information and ideas and to engage in joint thinking about possible explana- tions . . . [generally not] during formal meetings but during the proverbial “corridor chats.” [53, p. 161]

Effective communication is so intimately intertwined with this problem-solving pro- cess that engineering cannot be done without it. Within the increasingly complex and distributed nature of many engineering projects, engineers must not only rely on tradi- tional communication skills of writing, speaking, and listening, but they must also understand how to effectively use organizational structures and sometimes subtle channels of communication. [35, p. 169]

Finding 3: Engineers spend more than half their work day (55%–60%) communicat- ing. Qualitative Finding 2 – that, for engineers, technical competence is inseparably inter- twined with effective collaboration – is corroborated by evidence from five studies that measured how engineers spend their work time. Engineers across experience levels spend 30% to 40% of their work time in social interactions featuring oral communication, such as formal meetings, informal corridor chats, and phone or video conferences [51, 52, 54], with “clients, peers, people in other parts of the same organization, superiors, contractors, and outsiders . . . [primarily in] one-on-one situations with little or no formal authority . . . [in which the goal is to secure] willing and conscientious cooperation” [51, p. 180]. In addition, engineers spend 15% to 30% of their time in written collaboration, such as text messages, emails, and reading, checking, and writing formal documents [51, 52, 54]. Four included studies [49, 51, 52, 54]

Undergraduate Engineering Competencies: A Sytematic Review 491

 

 

plus a study of engineers’ communication (Vest, Long, & Anderson, 1996) report that in total engineers spend 55% to 60% of their work day communicating as part of collaborations.

Finding 4: Engineering practice requires coordinating multiple competencies to accom- plish a goal. The interrelationships among generic engineering competencies extend beyond the inseparability of technical and collaborative activities. The complex results of the qualitative findings are best captured in a portrait of practice (Figure 5).

Within this global concept of coordination, 16 specific competencies for engineering prac- tice emerged in four categories. Table 1 contains detailed descriptions of these competencies, which were confirmed by the quantitative synthesis. Table 1 also highlights the relationships between competencies. We compared our description of engineering work plus our compe- tency list to a published review (Woollocott, 2009) that collected, but did not synthesize or prioritize, competencies in engineering practice. Our results encompass all concepts among those 54 competencies, except for one personal trait: seeks challenge.

Finding 5: Competencies important for engineering practice differ from required learn- ing outcomes and graduate attributes. We compared the specific competencies that emerged as important in this qualitative analysis to both ABET’s learning outcomes and the Washington Accord graduate attributes. The concept of coordinated competencies (Qualitative Finding 4) – and many of the competencies themselves – differ substantially from the required outcomes and attributes. By listing separate learning outcomes without a unifying portrait (as in Figure 5), required lists of outcomes and attributes lose the most important concept, which is that in engi- neering practice, competencies are intertwined and coordinated. Yet, the individual competencies are also essential. The following paragraphs examine specific competencies and concepts individually.

In the 25 studies in the qualitative thematic analysis, the evidence was consistent that interpreting data and measuring accurately are separate competencies. In the 14 studies that described measurement as an essential part of engineering practice, the essence was “writing test plans” [35, p. 159] and “use of empirical data derived from testing procedures” [53, p. 152]. Not a single study clearly indicated a controlled experiment. Four studies referred to interpreting data without mentioning measurement or experiments: “assimilate, analyze, and

Engineers work in technical contexts to create, implement, and maintain reliable

solu�ons that meet client needs within constraints such as those imposed by technical

and manufacturing feasibility, �me, budget, business context, codes, regula�on, ethics,

poli�cs, and impacts on safety, health, the environment, local community, and global

society. Engineering work requires technical competence intertwined with effec�ve

collabora�on because the systems surrounding the “technology-in-the-making” [53,

p. 151] are too complex for one person to fully know or implement, making “coordina�on

and overlap . . . both necessary and unavoidable” [47, p. 214]. Within a dynamic work

environment, effec�ve engineers maintain focus on the big-picture vision, make decisions

based on data, manage their projects even without formal authority, and take ini�a�ve

on what to do, what informa�on to gather, and whom to collaborate with, crossing

disciplines, organiza�onal levels, and organiza�onal boundaries as needed. Engineers

take responsibility for the impacts of their projects and expanding their skills [29-54].

Specific competencies are defined in Table 1.

Figure 5 A concise portrait of generic engineering practice.

492 Passow & Passow

 

 

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Undergraduate Engineering Competencies: A Sytematic Review 493

 

 

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494 Passow & Passow

 

 

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6) .

Undergraduate Engineering Competencies: A Sytematic Review 495

 

 

synthesize data” [34, p. 5], “organize and present data” [38, p. 11], “understand results” [52, p. 409], and “gather, analyze, and interpret data” [43, p. 6]. (“Gather” might mean measure- ment, but could also mean simply looking up data.) Therefore, interpret data and measure accu- rately emerged as separate competencies, in contrast with ABET’s combined and experimentally focused outcome 3(b) “design and conduct experiments, as well as to analyze and interpret data” and the Washington Accord’s “Conduct investigations of complex problems using research- based knowledge and research methods including design of experiments, analysis and interpreta- tion of data, and synthesis of information to provide valid conclusions” (WA 4).

ABET’s outcome 3(c) “design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability” was essentially present in the data as were the concepts from the analogous WA 3. However, define constraints emerged as a skill separate from design and one that also applies to problem solving.

Early engineers believed in, and worked in a society that believed in, technology for its own sake. The paradigm was that the engineer was an agent of technological change, carrying little or no responsibility for outcomes. Today, engineers . . . are expected to bring a combination of technology, economics, social consciousness and environmental awareness to engineering works to ensure the “most possible good” is derived for both present and future communities. [31, p. 325]

This representative quote demonstrates that two other ABET learning outcomes are criti- cal to defining constraints: (j) “knowledge of contemporary issues” (like WA 7) and (h) “understand the impact of engineering solutions in a global, economic, environmental, and societal context” (similar to WA 6). Making define constraints its own active competency that applies impacts and issues captures the essence of how ABET’s outcomes (h) and (j) are essen- tial to engineering practice. The emergent description of define constraints presented in Table 1 is “Define constraints imposed by technical and manufacturing feasibility, time, budget, business context, codes, regulation, ethics, politics, and impacts on safety, health, the environ- ment, local community, and global society.”

This sense of active responsibility applies both to defining constraints and to engineering outcomes. ABET’s outcome 3(f) “understanding of professional and ethical responsibility” is more passive and vague than the competency that was evident in the data [31, 35, 39, 40, 44– 46, 54], which emerged as take responsibility, specifically “Take professional and ethical responsibility for decisions and behavior; envision and manage impacts from multiple perspectives.” Our definition is more active and more specific than the Washington Accord’s “Apply ethical principles and commit to professional ethics and responsibilities and norms of engineering practice” (WA 8).

ABET’s outcomes (g) “communicate effectively” and (d) “function on multidisciplinary teams” pervaded the 25 qualitative studies, but with such different character that ABET’s wordings do not capture the essence of practice. As described above, technical competence is inseparably intertwined with effective collaboration [35, 36, 43–54]. The image of mere func- tioning falls dramatically short of the portrait of practice in the studies under review. The crit- ical competency is to coordinate efforts: “Create vision; build consensus; negotiate; secure and offer willing and conscientious collaboration to achieve goals shared with coworkers, clients, and suppliers; coordinate efforts; and assume joint responsibility [29–31, 33–54]. The modi- fying concept of “multidisciplinary” does not begin to capture the diverse roles and knowledge

496 Passow & Passow

 

 

bases of those with whom an engineer coordinates efforts. The Washington Accord uses “diverse teams and in multi-disciplinary settings” (WA 9). To enable the collaboration evi- dent in the data, effective communication is required across disciplines, levels, and organiza- tional boundaries and through multiple media [29, 31–54].

It is important to note that the concept of diversity pervaded the included studies’ findings pertaining to working with others. However, it was described quite differently than in engi- neering education circles. The included studies typically did not define diversity simply by attributes of people that exist outside the context of the work, such as gender and race/ethnic- ity. Instead, diversity was described in terms of diverse goals and backgrounds brought to the work at hand. In addition, diversity included disciplines, organizational levels, and different work organizations. This concept of diversity surprised us. We captured the concepts that were evident in the included studies in our generic competency, communicate effectively: “Communicate effectively with people that have diverse goals and backgrounds – across disci- plines, organizational levels, and organizational boundaries, through listening, oral, written, and graphical means.” Note that listening – which requires respect – is a critical element of communicate effectively. Among the included studies, goals, academic discipline, and organiza- tional level were the most prominent aspects of diversity. A person’s background was men- tioned much less often. When it was mentioned or implied, it was most frequently in terms of culture and nationality, less often in terms of race/ethnicity, and least often in terms of gender, socioeconomic status, and educational background. The qualitative studies clearly linked a comprehensive concept of diversity with communication.

Besides coordinating efforts, the major reason that practicing engineers communicate is to gather information. In practice, an engineer “seeks information and uses the art of question- ing . . . knows when to seek advice, . . . [and] validates facts, information, and assumptions” [34, p. 5]. Gathering information is motivated by the desire to exceed expectations in solving the problem, which is distinct from expanding one’s own skills. Neither gather information nor expand skills are captured in ABET’s passive outcome 3(i) “recognition of the need for, and an ability to engage in life-long learning” and the similarly passive WA 9.

Three competencies for engineering practice have no counterpart in ABET’s learning out- comes or WA’s graduate attributes: take initiative, think creatively, and make decisions. These themes were identified independently both in the qualitative thematic analysis and in the the- matic analysis of the non-ABET-mapped competencies among the quantitative survey items.

Take initiative was evident in 21 out of 25 qualitative studies [29–32, 34–46, 49–51, 53, 54]. Three of the 25 qualitative studies were based on job postings. All three job posting stud- ies included related concepts: “self-motivation, . . . minimal direction, . . . results oriented, . . . outcome and/or objective sensitive” [39, p. 91], “initiative, . . . realizing the vision” [40, p. 18], “continual improvement, . . . self-initiative, . . . [and] customer satisfaction” [41, p. 4]. Other representative findings are “attempt to influence the project direction” [30, p. 28], “have a vision/goals . . . [and] see beyond your part . . . understand impact on whole,” [42, p. 10], “identifying the requirements and desires of the customer and then being responsive to them” [42, p. 8], and “learning the ‘big picture’; understanding the non-engineering priorities and decisions of the organization” [43, p. 9]. Synthesizing these and other findings, we sum- marized take initiative as “Influence project direction; take multiple perspectives; seek ‘big- picture’ understanding of the client’s problem, its context, constraints, and impacts; and take goal-directed initiative to exceed expectations.”

In 20 out of 25 qualitative studies, concepts related to think creatively were discussed in a wide array of contexts using a variety of terms: creativity [29, 31, 34–37, 39, 42, 44, 45, 47,

Undergraduate Engineering Competencies: A Sytematic Review 497

 

 

48, 51, 52], innovation [30, 32, 36–38, 40, 42, 53], invention [40], lateral thinking [31, 33], being imaginative [39], thinking outside the box [35], challenging thinking [37], reframing the problem [54], and using creativity enhancing processes, such as TRIZ [52].

Make decisions was another competency evident in the qualitative studies that is not explicit in ABET’s learning outcomes. (The Washington Accord’s graduate attributes imply decision making in WA 2–5, 7 and 11.) Terms used were decision making [30, 34, 35, 38, 40, 43, 46, 49, 52, 54], decisiveness [31, 42], judgment or making judgments [31, 32, 42, 50, 51, 54], and making choices [47, 51]. In two other studies, decision making was implied in descrip- tions of engineers’ activity, but was not mentioned explicitly [45, 53]. The competency of making decisions is integrated with other competencies in practice.

[Synthesizing when creating something new] is a crucial and complex role, and often demands decisions about people, processes, economics, and facilities. These frequently need to be weighed and combined for a business plan. [46, p. 450]

One competency for engineering practice has no counterpart in ABET’s learning outcomes but is partially represented in the Washington Accord’s graduate attribute “project management and finance” (WA 11). The authors of 21 out of 25 qualitative studies reported findings pertaining to the competency devise process. Component concepts were to coordinate the following to accomplish a goal: estimate time and cost, plan, set priorities, schedule and monitor tasks, maintain standards, regulate own work commitments, and meet deadlines and budget [29–31, 34–36, 39–43, 45–54]. The main idea of managing the engineer’s own process is captured by Faulkner [50, p. 345]:

We see here the fluidity of boundaries within engineering. In practice, management and design are thoroughly overlapping activities in engineering, in spite of the distinc- tions frequently drawn between them.

Competence at devising and managing the engineering process requires coordination with other engineering competencies [43]. Our devise process competency was independently con- firmed in the thematic analysis of the non-ABET-mapped competencies among the survey items and in theory. Two component aspects are identified in theory: first, deciding when to apply principles and skills and how to take action on one’s own analysis (Stark et al., 1986) and, second, focusing on achieving goals (Spencer & Spencer, 1993). In addition, a review of models of professional development states that “the main characteristic of competent profes- sionals is that they choose a plan, [choose] goals, and [choose] strategies for when and how to apply rules and procedures” (Dall’Alba & Sandberg, 2006, p. 387).

Finding 6: Solving problems is the core of engineering practice, and eight competencies differentiate between outstanding and ordinary performance. Four studies aimed to answer the research question, “What competencies differentiate between outstanding and ordinary engi- neers?” (486 survey responses plus 130 interviews) [29–32]. Eight differentiating competencies were identified: the general concept of technical competence [30, 32], communicate effectively [29, 31, 32], coordinate efforts [29, 31], take initiative [29–32], gather information [29, 31], define con- straints [31], think creatively [31, 32], make decisions [30–32], and especially devise process [29–32]. Differentiation in these studies is strong evidence that a competency should be listed as impor- tant for engineering practice. It is essential to note that two of the four comparative studies explicitly found that academic performance did not differentiate between exceptional and nonexceptional engineers [29, 31].

We observed that none of the four differentiation studies mentioned problem solving in their results – as either differentiating or not differentiating – even though two of these

498 Passow & Passow

 

 

studies discussed solving problems throughout [29, 31]. This was particularly surprising because 21 of the 25 qualitative studies included problem solving, and most of these incorpo- rated it in their main findings. For example, Robinson’s [52] study of time usage concluded “Participants spent 20.3% of their time understanding information and 18.4% problem solv- ing, by far the two most used identifiable cognitive skills” [p. 415]. The main findings of other studies identified solving problems as a core activity for engineers. Korte et al. [43] found that most participants defined engineers as problem solvers and engineering as a method for solv- ing problems [p. 6]. Anderson et al.’s [35] abstract stated that engineers “saw their work as problem solving, almost always done in explicitly organized teams or in informal collabo- ration” [p. 153]. Their results vividly describe the coordination of other competencies in the central endeavor of solving problems.

By listening and remaining open to the ideas of others [while] acting as . . . translators of their technical specialties, [engineers are] . . . able to gather better information and solve problems more effectively. . . . As an offshoot of collaboration, . . . [the] ability to creatively “think outside the box” and defend ideas . . . [is] a notable skill that made an engineer a more valuable problem solver. [35, p. 163]

From the nature of this competency’s prominence in the qualitative studies, it appears that problem solving did not differentiate between ordinary and outstanding engineers because all engineers solve problems as the core activity of their practice, and therefore, effective coordi- nation of other competencies improves the quality and timeliness of engineers’ solutions. Thus, problem solving is core for all engineers; it is the other competencies that differentiate between ordinary and outstanding solutions.

Finding 7: Engineering education could better coordinate competencies as in engi- neering practice. The qualitative thematic analysis revealed three principles for curriculum design pertaining to coordinating competencies as in engineering practice. We summarize them in the integrated quantitative and qualitative results below.

IntegratedQuantitative andQualitative Results

When we initiated this systematic review, we knew of quantitative studies and anticipated that the results of the quantitative synthesis would be the central findings. We were surprised to identify a large body of relevant qualitative studies that reshaped our perspective. In light of the nature of engineering work, which requires thorough integration of competencies to succeed (Qualitative Findings 2, 4, and 5), we realized that the discrete competencies as rated in the quantitative synthesis (Figure 4) are critical, but are only supporting details in a larger picture.

TheNature of Generic Engineering work Engineering work is typically project based; therefore, engineering tasks and the required competencies are tied to the life-cycle of a product, process, or system (Qualitative Finding 1). In this project context, technical competence is inseparably intertwined with effective col- laboration because “engineering relies on harnessing the knowledge, expertise and skills car- ried by many people, much of it implicit and unwritten knowledge” [51, p. 175] (Qualitative Finding 2). What may be surprising is how communication dominates engineers’ time: across experience levels, engineers spend more than half their work day (55% to 60%) communicating,

Undergraduate Engineering Competencies: A Sytematic Review 499

 

 

which is composed of about a third of their time in oral communication and a quarter in written communication (Qualitative Finding 3).

The interrelationships among generic engineering competencies extend beyond the insep- arability of technical and collaborative activities. The complex results of the qualitative find- ings emphasize the importance of coordinating competencies as described in our concise portrait of generic engineering practice (Qualitative Finding 4 in Figure 5).

Important Generic Competencies Within the global concept of coordination, 16 specific competencies for engineering practice emerged from synthesizing findings from Figure 4 and Qualitative Findings 4–6 (presented in Table 1). These 16 generic competencies are the essence of engineering practice. Relative importance was evaluated by triangulating the results of studies employing different methods:

Solve problems was rated with top importance in the quantitative synthesis (Figure 4) and emerged as the core activity of engineering practice in the qualitative analysis (Qualitative Finding 6). Eight other competencies differentiated between ordinary and outstanding engineering performance: the general concept of technical compe- tence, communicate effectively, coordinate efforts, take initiative, gather information, define constraints, think creatively, and make decisions. (Academic performance did not differ- entiate.) The overarching result is that effective coordination of competencies (a com- ponent of devise process) increases the quality and timeliness of an engineer’s solutions.

Devise process encompasses several highly important components. Coordinating multiple competencies to accomplish a goal was the most dominant finding on competencies in the qualitative thematic analysis (Qualitative Finding 4) and differentiated between ordinary and outstanding engineering performance (Qualitative Finding 6). Maintaining a focus on goals was rated just below the top cluster in the quantitative synthesis, and planning and time management was the top rated competency in the quantitative synthesis (Figure 4).

Communicate effectively and coordinate efforts, the collaborative competencies, were each identified as highly important in both the quantitative synthesis (Figure 4) and the qualitative studies that differentiated between ordinary and outstanding engineering (Qualitative Finding 6).

Take initiative, think creatively, and make decisions each differentiated between ordinary and outstanding engineers (Qualitative Finding 6) and also were rated just below the top cluster competencies in the quantitative synthesis (Figure 4).

Gather information and define constraints both differentiated between outstanding and ordinary engineers (Qualitative Finding 6), as did the vague concept of technical com- petence, for which there is insufficient detail in the qualitative studies for mapping onto any specific competencies in Table 1.

Interpret data was rated with top importance in the quantitative synthesis (Figure 4).

Other competencies in the table, such as measure accurately and design solutions, are com- monly required in engineering practice, but their importance is dependent on practice area. For example, in the quantitative synthesis, design solutions was rated highest in a mechanical engineering sample and lowest in a chemical engineering sample. Thus, they are not

500 Passow & Passow

 

 

generically important across all practice areas, but are highly important in some practice areas. The quantitative synthesis showed that the aggregate pattern of importance ratings does not change across survey years [9, 25], with years of experience in engineering [7, 8, 16, 25], or across graduation years of respondents [25]. We infer from the results of individual included studies that the pattern of importance ratings indicated in Table 1 has remained stable for more than two decades and for various levels of engineering experience.

The competency concepts as worded in Table 1 summarize this systematic review’s find- ings and provide an evidence-based alternative to accreditors’ wordings. Note that the con- cepts of understanding contemporary issues and the impacts of one’s work are not lost, but are woven into define constraints. When the impact competency was stated simply as under- standing impacts – which was common in the studies in the quantitative synthesis – it was typically rated lower than other competencies. However, in the qualitative studies, ordinary and outstanding engineers were differentiated by their ability to define constraints through evaluating impacts. Competencies worded with action verbs – and with clear objects for the actions – better capture engineering practice.

Findings Pertaining to Engineering Education Qualitative Finding 7 revealed three simple, yet paradigm-shifting principles for curriculum design pertaining to coordinating competencies as in practice:

In engineering education, “engineers are trained to do [what they call] real engineer- ing [that is, solitary technical problem solving and design] and not the rest of their jobs” [48, p. 234]; engineering work extends far beyond science-based tasks to activi- ties, both technical and social, that are critical to project success, such as controlling scope, error checking in design, and communication. [35, 43, 48, 50, 51]

“Non-technical skills cannot be taught in isolation from the technical context in which they will be used, and . . . integrated projects are a crucial tool for achieving such ends.” [49, p. 179]

Engineering education needs a greater connection to practice from the first day [35, 42–44], including hands-on problem solving of authentic, ill-structured problems within constraints [35, 42-44], iteration [42, 43], working toward a big picture goal [35, 44], and realistic social elements [35, 42–44], such as working with clients, gath- ering information, coordinating technical work, work-like writing and speaking, and demonstrating professional behavior.

Limitations, Strengths, and Triangulation The systematic search was performed on June 15, 2012. From June through December of 2014, citation searches identified several studies published since that date: two quantitative studies [26, 28] and four qualitative studies [41, 52–54]. However, like other extensive sys- tematic reviews, this one does not thoroughly review all relevant literature between the search date and its own publication date.

The quantitative synthesis had limitations. For example, the quantitative synthesis could not be conducted as a formal meta-analysis because standard deviations were available for only 24 out of 60 samples. In addition, only a few of the survey studies included ratings of

Undergraduate Engineering Competencies: A Sytematic Review 501

 

 

every ABET outcome (which we chose as our common constructs). In other words, each study’s set of competencies was different. These features of the quantitative studies created challenges at two levels. First, the studywide mean and standard deviation used to calculate standardized mean importance ratings were based on a slightly different set of competencies for each study. Second, for each competency, there was a different number of samples that could contribute the importance measure. These limitations in the quantitative analysis made triangulation with other research methods imperative.

The qualitative thematic analysis also had limitations. Specifically, using published reports of previous findings as the data is less ideal than using the raw data for each included study. However, using published reports meant that 72 other authors contributed to our interpreta- tion of the qualitative studies.

In order to ensure consistency across the large number of studies reviewed, we chose to develop each analytic process together and then have a single author execute that process on every related study. Afterward, we discussed every theme and result until we reached consen- sus. Although this approach maximized consistency, it prevented us from evaluating agree- ment between independent raters.

This systematic review has particular strengths for its purpose of supporting faculty in making decisions about curricula. In the absence of evidence, such as provided by this review, about what competencies are important for engineering practice, faculty must rely on either expert panel statements, primary studies, or their own speculations about what competencies are important in different practice settings in which they have no work experience. Each fac- ulty member’s perspective on wording of competencies will also be limited. This systematic review robustly addresses faculty needs in three ways.

First, the methods in over one-third of the included studies exceed the rigor of the expert panel process used to develop ABET’s learning outcomes, Washington Accord’s graduate attributes, and committee reports such as The Engineer 2020: Visions of Engineering in the New Century (National Academy of Engineering, 2004). Detailed accounts of participants’ experiences analyzed by others are more reliable than respondents’ self-assessment or expert panel methods for competency research because accounts mitigate the influence of beliefs, inaccurate self-assessment, and aspects of self-report bias (Walther et al., 2011).

Second, Saunders-Smits [15] found that asking respondents to rate the importance of competencies for their own work is more accurate than asking them to rate for a role that is not their own. Therefore, to support curricular decision making, it is valuable to inform fac- ulty with practitioners’ ratings of importance of competencies for engineering practice, as in this systematic review.

Third, some changes in wording affected the results of surveys, while others did not [3, 8, 10, 25, 28]. Because wording is sometimes important in evaluation of competencies, a quanti- tative synthesis that includes many variations of wording is far more valuable for informing curricular decision making than any single primary study. In addition, the experience of those directly engaged in engineering practice contributes to “the identification of consistencies and mismatches between multiple perspectives of what engineering work is” (Sheppard, Colby, Macatangay, & Sullivan, 2006, p. 430).

Other strengths were the results of the methods used for the systematic review. We made concerted efforts to avoid each of the nine types of errors common when synthesizing research in education (Dunkin, 1996): excluding research within the declared scope of the review with- out explanation, not discriminating with respect to research quality, inaccurately extracting details of research methods, including multiple reports of the same research as different

502 Passow & Passow

 

 

studies, failing to critically appraise the original authors’ findings, claiming that studies yield findings that they do not, ignoring contradictory findings, making flawed generalizations due to one of the first seven errors, and failing to recognize that a study contains evidence relevant to a generalization.

Both authors are registered professional engineers. The second author has extensive prac- tice experience, while the first author, a Ph.D. in the social sciences, has extensive experience with mixed methods research.

The review offers a rich picture of generic engineering competencies and their relative impor- tance. The picture is generalizable because of the variety among the 52 studies which were pub- lished over a span of 24 years. The review includes six categories of research question and triangulates results from myriad, complementary designs, specifically, surveys, interviews, differ- entiating studies, external observations, and job postings.

The strengths of triangulating different measurement approaches bear further explanation. Quantitative synthesis of surveys allowed direct comparison of relative importance for a large number of respondents across disciplines, practice areas, time, and wordings. Qualitative the- matic analysis supported examination of the wordings and concepts embodied in the compe- tencies. Two types of studies had designs that greatly reduced the potential for bias: the studies that asked supervisors to identify individual engineers as ordinary or outstanding and then blinded participants, interviewers, and coders from this designation; and the studies that synthesized interviews with observations of engineers in action. Contrasting job postings, which typically list minimum requirements, with the competencies that differentiate between ordinary and outstanding engineers, allowed us to distinguish between competencies that are necessary for an engineer to function adequately in practice and competencies that character- ize outstanding performance. The risk of bias in this systematic review was greatly reduced by the synthesis of many studies conducted by geographically diverse research teams in different contexts, each having their own biases.

Conclusions and Implications

This systematic review aims to inform the design of engineering curricula, especially for under- graduates. We synthesized a large, diverse evidence base of 52 studies that gathered informa- tion from 16,603 participants and 36,100 job postings. Our review provides a succinct synthesis of extensive evidence to support decision making. This review (1) describes the nature of engineering work in one paragraph (Figure 5); (2) establishes a comprehensive list of 16 generic engineering competencies that are important across disciplines and practice areas, their relative importance for engineering work (which is stable over time), and rich descriptions that highlight their relationships (Table 1); and (3) presents three simple, paradigm-shifting princi- ples for curriculum design pertaining to coordinating competencies as in practice:

Engineering work extends far beyond science-based tasks to activities – both technical and social – that are critical to project success.

“Non-technical skills cannot be taught in isolation from the technical context in which they will be used.” [49, p. 179]

Engineering education needs a greater connection to practice from the first day.

Undergraduate Engineering Competencies: A Sytematic Review 503

 

 

Individual faculty members could consider their teaching in light of our results. The por- trait of engineering practice could help faculty better articulate the nature of engineering work for their students, giving them the words to share the big-picture vision of the world in which many of the students will apply their competencies. Individual faculty members could adopt the competencies that are generically important for engineering practice as their learn- ing outcomes, using the mapping to requirements in Table 1 for accreditation purposes. They could also design individual courses around the principles pertaining to coordinating compe- tencies as in engineering practice.

Yet, we envision these results can be useful at the system-level, as well. The Carnegie Foundation for the Advancement of Teaching sponsored a group of studies regarding prepa- ration for the professions. The Carnegie study on engineering resulted in the report Educating Engineers: Designing for the Future of the Field (Sheppard, Macatangay, Colby, & Sullivan, 2009). The report described the shortcomings of engineering education and set the goal that future curricula prepare students for practice. Sheppard et al. (2008) summarized the findings:

The central lesson that emerged from our study is the imperative of teaching for pro- fessional practice – with practice understood as the complex, creative, responsible, con- textually grounded activities that define the work of engineers at its best; and professional understood to describe those who can be entrusted with responsible judg- ment in the application of their expertise for the good of those they serve. (p. 7)

Their description of the shortcomings of engineering education sets the goal that future cur- ricula prepare students for practice. However, the Carnegie study did not describe that prac- tice. Defining the nature of engineering work and the generic competencies required in engineering practice is the contribution of this systematic review.

We recommend that future work set aside additional measurement of the importance of competencies, and focus on how to remake, or redesign, undergraduate engineering programs to better prepare students for life and work after graduation, and on how to assess students’ development of generic engineering competencies. As groups of faculty establish design speci- fications for the clean-sheet redesign of curricula endorsed by Educating Engineers, they will find evidence to support their decisions in our results: the concise portrait of engineering practice (Figure 5), generic engineering competencies (Table 1), and the three paradigm- shifting principles for curriculum design pertaining to coordinating competencies as in engi- neering practice. Furthermore, policy makers and accreditation bodies could use our evidence in their deliberations, such as current considerations of the proposed changes to ABET’s Cri- terion 3 Student Outcomes. The evidence in this systematic review supports movement in the direction urged by Educating Engineers.

504 Passow & Passow

 

 

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Undergraduate Engineering Competencies: A Sytematic Review 505

 

 

A pp en di x B

St ud ie sI nc lu de d in th e Q ua nt ita tiv e Sy nt he sis

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506 Passow & Passow

 

 

A pp en di x B (c on tin ue d)

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S

17 2

d ev

el op

ed by

co m

m it

te e

R at

e im

po rt

an ce

fo r

en tr

y- le

ve le

n gi

n ee

rs

5- po

in t

sc al

e: “l

ow ”

to “h

ig h

T h

is su

rv ey

ci rc

a 19

98 h

ad on

e sa

m pl

e: en

gi ne

er s

an d

en gi

ne er

in g

m an

ag er

s fr

om 15

ae ro

sp ac

e an

d de

fe ns

e- re

la te

d fi

rm s

(U .S

., N

5 42

0, R

R 5

no t

re po

rt ed

).

[7 ]

S ir

iz zo

tt i

(2 00

0) S

� C

om pa

re d

tw o

gr ou

ps an

d tw

o ex

pe ri

en ce

le ve

ls 70

(5 6

fr om

A S

M E

’s P

ro d

uc t

R ea

li za

ti on

P ro

– ce

ss pl

us 14

fr om

in te

rv ie

w s)

R at

e im

po rt

an ce

fo r

“n ew

B .S

.g ra

d ua

te s”

an d

“e xp

er ie

n ce

d m

ec h

an ic

al en

gi n

ee rs

5- po

in t

sc al

e: “v

er y

un im

po rt

an t”

to “v

er y

im po

rt an

t”

T h

is su

rv ey

ci rc

a 19

99 h

ad tw

o sa

m pl

es :p

ra ct

ic in

g en

gi n

ee rs

of al

le xp

er ie

n ce

le ve

ls fr

om 28

co m

pa n

ie s

in va

ri ou

s in

du st

ri es

(C an

ad a,

N 5

46 ,R

R 5

41 %

); an

d m

ec h

an ic

al en

gi ne

er in

g fa

cu lt

y (C

an ad

a, N

5 20

, R

R 5

80 %

).

[8 ]

B an

ke l,

B er

gg re

n ,B

lo m

,C ra

w le

y, W

ik lu

n d,

& O

st lu

n d

(2 00

3) R

� C

om pa

re d

fo ur

gr ou

ps in

ea ch

co un

tr y

(U .S

.& S

w ed

en )

13 fr

om th

e C

D IO

S yl

la bu

s R

at e

pr ofi

ci en

cy ex

pe ct

ed of

gr ad

ua ti

n g

en gi

n ee

rs

6- po

in t

sc al

e: “n

o kn

ow le

dg e

of ,”

“b ee

n ex

po se

d to

,” “p

ar ti

ci pa

te in

,” “u

n de

rs ta

n d

an d

ex pl

ai n

,” “s

ki lle

d in

th e

pr ac

ti ce

,” or

“a bl

e to

le ad

or in

n ov

at e”

F ou

r sa

m pl

es fr

om ci

rc a

20 02

re la

te d

to th

re e

S w

ed –

is h

un iv

er si

ti es

’e le

ct ri

ca l,

m ec

h an

ic al

,a n

d ve

h ic

le en

gi ne

er in

g: 64

fa cu

lt y,

28 m

id -t

o- up

pe r-

le ve

li nd

us –

tr y

le ad

er s,

57 al

um n

ifi ve

ye ar

s af

te r

gr ad

ua ti

on ,3

9 al

um n

i1 5

ye ar

s af

te r

gr ad

ua ti

on (S

w ed

en ,R

R n

ot re

po rt

ed ).

Undergraduate Engineering Competencies: A Sytematic Review 507

 

 

A pp en di x B (c on tin ue d)

S tu

dy C

om pe

te n

ci es

M ea

su re

of re

la ti

ve im

po rt

an ce

in th

e su

rv ey

M et

h od

s fo

r sa

m pl

e se

le ct

io n

an d

da ta

co lle

ct io

n w

it h

re sp

on se

ra te

(R R

)

F ou

r sa

m pl

es fr

om ci

rc a

20 03

re la

te d

to M

IT ’s

ae ro

– sp

ac e

en gi

n ee

ri n

g pr

og ra

m :2

2 fa

cu lt

y, 16

m id

-t o-

u p

p er

-l ev

el in

d u

st ry

le ad

er s,

3 4

al u

m n

i fi

ve ye

ar s

af te

r g

ra d

u at

io n

, 1

7 al

u m

n i

1 5

ye ar

s af

te r

g ra

d u

a- ti

o n

(U .S

., R

R n

o t

re p

o rt

ed ).

[9 ]

R oo

n ey

& P

ue rz

er (2

00 4)

C �

C om

pa re

d ov

er ti

m e

an d

th re

e gr

ou ps

12 fr

om A

B E

T pl

us bu

si n

es s

R at

e im

po rt

an ce

fo r

yo ur

jo b

5- po

in t

sc al

e of

im po

rt an

ce

T h

e 1

9 9

9 su

rv ey

h ad

th re

e sa

m p

le s:

en gi

n ee

ri n

g al

um n

il es

s th

an si

x ye

ar s

af te

r gr

ad ua

ti on

fr om

H of

– st

ra U

n iv

er si

ty (U

.S .,

N 5

28 fr

om el

ec tr

ic al

,N 5

2 4

fr o

m m

ec h

an ic

al ,a

n d

N 5

4 4

fr o

m in

d u

st ri

al ,

bi om

ed ic

al ,e

n vi

ro n

m en

ta l,

an d

ci vi

l, R

R 5

46 %

).

T h

e 20

03 su

rv ey

h ad

on e

sa m

pl e:

al um

n il

es s

th an

fo ur

ye ar

s af

te r

gr ad

ua ti

on fr

om H

of st

ra in

el ec

tr ic

al ,

m ec

h an

ic al

,i nd

us tr

ia l,

bi om

ed ic

al ,e

nv ir

on m

en ta

l, an

d ci

vi l

en gi

n ee

ri n

g (U

.S .,

N 5

52 ,R

R 5

48 %

).

[1 0]

W ol

fe (2

00 4)

R �

C om

pa re

d tw

o qu

es ti

on s

25 m

od ifi

ed fr

om B

an ke

l( 20

03 )

R at

e h

ow co

m pe

te n

t th

os e

in yo

ur li

n e

of w

or k

an d

ca re

er st

ag e

ar e

ex pe

ct ed

to be

6- po

in t

sc al

e: “n

o kn

ow le

dg e

of ,”

“b ee

n ex

po se

d to

,” “p

ar ti

ci pa

te in

,” “u

n d

er st

an d

an d

ex pl

ai n

,” “s

ki ll

ed in

th e

pr ac

ti ce

,” or

“a bl

e to

le ad

or in

n ov

at e”

R at

e h

ow fr

eq ue

n tl

y yo

u us

e th

is co

m pe

te n

cy

6- po

in t

sc al

e: “n

ev er

,” “a

fe w

ti m

es a

ye ar

,” “a

t le

as t

on ce

a m

on th

,” “a

t le

as t

w ee

kl y,

” “o

n m

os t

d ay

s, ”

“f or

m o

st ev

er yt

h in

g I

d o”

T h

is 20

04 su

rv ey

h ad

on e

sa m

pl e:

m ec

h an

ic al

en gi

– n

ee ri

n g

al um

n ie

ig h

t to

12 ye

ar s

af te

r gr

ad ua

ti on

fr om

M IT

(U .S

., N

5 30

8, R

R 5

46 %

).

508 Passow & Passow

 

 

A pp en di x B (c on tin ue d)

S tu

d y

C om

pe te

n ci

es M

ea su

re of

re la

ti ve

im po

rt an

ce in

th e

su rv

ey M

et h

od s

fo r

sa m

pl e

se le

ct io

n an

d d

at a

co lle

ct io

n w

it h

re sp

on se

ra te

(R R

)

[1 1]

W or

ld C

h em

ic al

E n

gi n

ee ri

n g

C ou

n ci

l( 20

04 )R

� C

om pa

re d

se ve

n co

un tr

ie s

26 (s

ou rc

e n

ot re

po rt

ed )

R at

e re

le va

n ce

to yo

ur w

or k

5- po

in t

sc al

e: “v

er y

lo w

” to

“v er

y h

ig h

T h

is 20

03 su

rv ey

h ad

se ve

n sa

m pl

es of

ch em

ic al

en gi

n ee

rs w

it h

le ss

th an

fi ve

ye ar

s w

or k

ex pe

ri en

ce fr

om A

us tr

al ia

(N 5

77 ),

C h

in a

(N 5

48 3)

,F ra

n ce

(N 5

1 5

2 ),

G er

m an

y (N

5 1

9 6

), M

ex ic

o (N

5 22

9) ,U

n it

ed K

in gd

om (N

5 25

2) ,a

n d

U .S

. N

5 40

6) .C

on ve

n ie

n ce

sa m

pl e.

[1 2]

R ob

in so

n ,S

pa rr

ow ,C

le gg

,& B

ir di

(2 00

5) S

49 fr

om li

te ra

tu re

R at

e im

po rt

an ce

to yo

ur cu

rr en

t jo

b

9- po

in t

sc al

e: “n

ot at

al li

m po

rt an

t” to

“e xt

re m

el y

im po

rt an

t”

T h

is su

rv ey

ci rc

a 20

04 h

ad on

e sa

m pl

e of

de si

gn en

gi n

ee rs

pr ac

ti ci

n g

in on

e ae

ro sp

ac e

fi rm

(U n

it ed

K in

gd om

,N 5

58 ,R

R 5

32 %

).

[1 3]

C ra

w le

y, M

al m

qv is

t, O

st lu

n d,

& B

ro d

eu r

(2 00

7) R

13 fr

om th

e C

D IO

S yl

la bu

s R

at e

im po

rt an

ce of

ea ch

co m

pe te

n cy

(n ot

st at

ed w

h o

fo r)

5- po

in t

sc al

e: “o

f n

o im

po rt

an ce

” to

“e ss

en ti

al ”

T h

is su

rv ey

ci rc

a 20

04 h

ad on

e sa

m pl

e of

m ec

h an

ic al

an d

m an

uf ac

tu ri

n g

en gi

n ee

ri n

g al

u m

n i

fi ve

to 30

ye ar

s af

te r

gr ad

ua ti

on fr

om Q

ue en

’s U

n iv

er si

ty B

el –

fa st

(I re

la n

d ,N

5 20

0, R

R 5

25 %

).

[1 4]

L at

tu ca

,T er

en zi

n i,

& V

ol kw

ei n

(2 00

6) R

A B

E T

’s 11

ou tc

om es

– ve

rb at

im R

at e

im po

rt an

ce of

ea ch

co m

pe te

n cy

fo r

“n ew

en gi

– n

ee ri

n g

gr ad

ua te

s”

5- po

in t

sc al

e: “u

n im

po rt

an t”

to “e

ss en

ti al

T h

is su

rv ey

ci rc

a 20

0 5

h ad

on e

sa m

pl e:

pr ac

ti ci

n g

en gi

n ee

rs w

h o

h ad

ev al

u at

ed re

ce n

t en

gi n

ee ri

n g

gr ad

ua te

s fo

r se

ve n

or m

or e

ye ar

s in

ae ro

sp ac

e, ch

em i-

ca l,

ci vi

l, co

m pu

te r,

el ec

tr ic

al ,i

nd us

tr ia

l, an

d m

ec ha

ni ca

l (U

.S .,

N 5

1, 62

2 w

ei gh

te d

to re

pr es

en t

al l

ex pe

ri –

en ce

le ve

ls ,

R R

n ot

re po

rt ed

).

Undergraduate Engineering Competencies: A Sytematic Review 509

 

 

A pp en di x B (c on tin ue d)

S tu

d y

C om

pe te

n ci

es M

ea su

re of

re la

ti ve

im po

rt an

ce in

th e

su rv

ey M

et h

od s

fo r

sa m

pl e

se le

ct io

n an

d d

at a

co lle

ct io

n w

it h

re sp

on se

ra te

(R R

)

[1 5]

S au

n de

rs -S

m it

s (2

00 8)

R �

C om

pa re

d tw

o gr

ou ps

an d

th re

e ro

le s

12 (9

fr om

li te

ra tu

re pl

us 3

fr om

pa n

el is

ts )

20 04

:R at

e th

e im

po rt

an ce

of ea

ch co

m pe

te n

cy fo

r an

en gi

n ee

r [s

pe ci

al is

t or

m an

ag er

] to

at ta

in pr

of es

– si

on al

su cc

es s

20 06

:R at

e th

e im

po rt

an ce

of ea

ch co

m pe

te n

cy in

yo ur

cu rr

en t

jo b,

fo r

an en

gi n

ee ri

n g

sp ec

ia li

st ,a

n d

fo r

an en

gi n

ee ri

n g

m an

ag er

5- po

in t

sc al

es of

im po

rt an

ce

T h

e su

rv ey

ci rc

a 20

04 h

ad tw

o sa

m pl

es of

pr ac

ti ci

n g

ae ro

sp ac

e en

gi n

ee rs

in in

d us

tr y

an d

go ve

rn m

en t-

fu n

d ed

o rg

an iz

at io

n s

(N et

h er

la n

d s,

N 5

9 se

lf –

cl as

si fi

ed sp

ec ia

li st

s an

d N

5 1

0 se

lf -c

la ss

ifi ed

m an

ag er

s, co

n ve

n ie

n ce

sa m

p le

s) .

T he

su rv

ey ci

rc a

20 06

ha d

on e

sa m

pl e

of ae

ro sp

ac e

en gi

– ne

er in

g al

um ni

fi ve

to 30

ye ar

s af

te r

gr ad

ua ti

on fr

om D

el ft

U ni

ve rs

it y

(N et

he rl

an ds

,N 5

66 2,

R R

5 40

% ).

[1 6]

B an

ik (2

00 8)

S �

C om

pa re

d tw

o gr

ou ps

17 2

m ap

pe d

on to

A B

E T

H ow

im po

rt an

t is

th is

sk il

li n

co n

st ru

ct io

n en

gi n

ee r-

in g

fo r

n ew

gr ad

ua te

s? F

or th

os e

w it

h th

re e

to fi

ve ye

ar s’

ex pe

ri en

ce ?

5- po

in t

sc al

es :“

ve ry

lo w

im po

rt an

ce ”

to “v

er y

h ig

h im

po rt

an ce

T h

e su

rv ey

ci rc

a 20

07 h

ad on

e sa

m pl

e of

m an

ag er

s of

co n

st ru

ct io

n pr

oj ec

ts or

co n

st ru

ct io

n fi

rm s

w it

h an

av er

ag e

of 13

ye ar

s’ ex

pe ri

en ce

w it

h un

de rg

ra du

at e

m aj

or s

in ci

vi l,

co n

st ru

ct io

n ,m

ec h

an ic

al ,a

n d

el ec

tr i-

ca l(

U .S

., N

5 35

,c on

ve ni

en ce

sa m

pl e)

.

[1 7]

M al

e, B

us h

,& C

h ap

m an

(2 01

1) C

64 fr

om li

te ra

tu re

R at

e im

po rt

an ce

fo r

d oi

n g

yo ur

jo b

w el

l

5- po

in t

sc al

e: “n

ot n

ee de

d” to

“c ri

ti ca

l”

T h

e su

rv ey

ci rc

a 20

08 h

ad on

e sa

m pl

e of

pr ac

ti ci

n g

en gi

ne er

s re

st ri

ct ed

to fi

ve to

20 ye

ar s

of ex

pe ri

en ce

fr om

un de

rg ra

du at

e m

aj or

s in

ci vi

l, el

ec tr

ic al

,m ec

h an

– ic

al ,m

et al

lu rg

ic al

,c h

em ic

al ,e

n vi

ro n

m en

ta l,

co m

– pu

te r,

an d

ot h

er s

(A us

tr al

ia ,N

5 30

0, R

R 5 �

14 %

).

[1 8]

N ai

r, P

at il

,& M

er to

va (2

00 9)

S

23 fr

om li

te ra

tu re

R at

e im

po rt

an ce

fo r

re ce

n t

gr ad

ua te

s in

th ei

r w

or k

5- po

in t

sc al

e: “l

ow im

po rt

an ce

” to

“h ig

h im

po rt

an ce

T h

e 20

07 su

rv ey

h ad

on e

sa m

pl e

of em

pl oy

er s

w h

o h

ad re

cr ui

te d

at le

as t

on e

en gi

ne er

in g

gr ad

ua te

of M

o n

as h

U n

iv er

si ty

in th

e pa

st th

re e

ye ar

s fr

o m

va ri

ou s

d is

ci pl

in es

(A us

tr al

ia ,N

5 10

9, R

R n

ot re

po rt

ed ).

510 Passow & Passow

 

 

A pp en di x B (c on tin ue d)

S tu

d y

C om

pe te

n ci

es M

ea su

re of

re la

ti ve

im po

rt an

ce in

th e

su rv

ey M

et h

od s

fo r

sa m

pl e

se le

ct io

n an

d d

at a

co lle

ct io

n w

it h

re sp

on se

ra te

(R R

)

[1 9]

B ay

ti ye

h &

N aj

a (2

01 0)

S

27 fr

om li

te ra

tu re

R at

e h

ow im

po rt

an t

th is

co m

pe te

n cy

is fo

r yo

ur pr

of es

si on

5- po

in t

sc al

e: la

be ls

n ot

re po

rt ed

T h

e su

rv ey

ci rc

a 20

09 h

ad on

e sa

m pl

e of

en gi

n ee

ri n

g al

um ni

up to

10 ye

ar s

af te

r gr

ad ua

ti on

fr om

th e

un i-

ve rs

it ie

s of

L eb

an on

in va

ri ou

s m

aj or

s: ci

vi l,

m ec

h an

i- ca

l, el

ec tr

ic al

,c om

pu te

r, an

d en

gi n

ee ri

n g

m an

ag e-

m en

t (L

eb an

on ,N

5 18

8, R

R 5

21 %

).

[2 0]

G oe

l( 20

10 )S

23 fr

om li

te ra

tu re

R at

e im

po rt

an ce

fo r

so ft

w ar

e d

ev el

op m

en t

w or

k

11 po

in t

sc al

e of

cr it

ic al

it y

T h

e 20

0 4

su rv

ey h

ad on

e sa

m p

le of

en gi

n ee

rs an

d m

an ag

er s

at 15

in fo

rm at

io n

te ch

n ol

og y

co m

pa n

ie s

w it

h 1

.5 to

3 5

ye ar

s’ ex

p er

ie n

ce ,

m ea

n 7

.5 ye

ar s

(I n

d ia

, N

5 5

4 ,

co n

ve n

ie n

ce sa

m p

le ).

[2 1]

R ee

d (2

01 0)

S

62 fr

om li

te ra

tu re

P ro

fi ci

en cy

in th

e fo

llo w

in g

ar ea

s ar

e cr

it ic

al fo

r en

vi ro

n m

en ta

le n

gi n

ee rs

5- po

in t

sc al

e: “s

tr on

gl y

di sa

gr ee

” to

“s tr

on gl

y ag

re e”

T h

e su

rv ey

ci rc

a 20

0 9

h ad

on e

sa m

pl e

of en

vi ro

n –

m en

ta l

en gi

n ee

rs em

pl oy

ed in

C al

if or

n ia

’s D

ep ar

t- m

en t

of T

ox ic

S ub

st an

ce s

C on

tr ol

w it

h on

e to

ov er

25 ye

ar s

of ex

pe ri

en ce

(U .S

., N

5 11

1, R

R 5

23 %

).

[2 2]

W ar

d &

T h

ir ie

t (2

01 0)

S �

C om

pa re

d th

re e

gr ou

ps 32

fr om

th e

T un

in g

m et

h od

ol og

y fo

r el

ec tr

ic al

en gi

n ee

ri n

g R

at e

im po

rt an

ce fo

r w

or k

in yo

ur ar

ea in

yo ur

or ga

n iz

at io

n

[f or

ac ad

em ic

s, R

at e

im po

rt an

ce fo

r w

or k

yo u

ex pe

ct yo

ur gr

ad ua

te s

to ge

t]

4- po

in t

sc al

es :“

n on

e, ”

“w ea

k, ”

“c on

si d

er ab

le ,”

“s tr

on g”

T h

e cr

os s-

E ur

op ea

n su

rv ey

ci rc

a 20

08 h

ad th

re e

sa m

pl es

in el

ec tr

ic al

an d

in fo

rm at

io n

en gi

n ee

ri n

g: fa

cu lt

y (N

5 18

5) ,p

ra ct

ic in

g en

gi ne

er s

(N 5

11 2)

, an

d al

u m

n i

(N 5

32 6)

(F ra

n ce

, G

re ec

e, S

lo va

k R

ep ub

lic ,S

pa in

,T ur

ke y,

G er

m an

y, P

ol an

d, Ir

el an

d, B

ul ga

ri a,

R R

no t

re po

rt ed

).

[2 3]

W ar

n ic

k (2

01 1)

S

15 fr

om li

te ra

tu re

“H ow

im po

rt an

t is

it fo

r m

ec h

an ic

al en

gi n

ee rs

h ir

ed by

yo ur

co m

pa n

y w

h o

w il

lw or

k. ..

in a

gl ob

al en

vi –

ro n

m en

t to

h av

e_ __

__ ?”

5- po

in t

sc al

e: “u

n im

po rt

an t”

to “v

er y

im po

rt an

t”

T h

e su

rv ey

ci rc

a 20

09 h

ad on

e sa

m pl

e of

m ec

h an

ic al

en gi

n ee

ri n

g al

um n

iu p

to 60

ye ar

s af

te r

gr ad

ua ti

on fr

om B

ri gh

am Y

ou n

g U

n iv

er si

ty in

vo lv

ed in

h ir

in g

n ew

en gi

n ee

rs an

d cu

rr en

tl y

w or

ki n

g fo

r a

co m

pa n

y th

at op

er at

es in

at le

as t

tw o

co un

tr ie

s (U

.S .,

N 5

14 9,

R R

5 21

% ).

Undergraduate Engineering Competencies: A Sytematic Review 511

 

 

A pp en di x B (c on tin ue d)

S tu

d y

C om

pe te

n ci

es M

ea su

re of

re la

ti ve

im po

rt an

ce in

th e

su rv

ey M

et h

od s

fo r

sa m

pl e

se le

ct io

n an

d d

at a

co lle

ct io

n w

it h

re sp

on se

ra te

(R R

)

[2 4]

Y uz

ai n

ee ,Z

ah ar

im ,&

O m

ar (2

01 1)

S

10 fr

om li

te ra

tu re

,e ac

h co

m po

se d

of 5

sk il

ls ra

te d

se pa

ra te

ly R

at e

im po

rt an

ce of

ea ch

sk il

lf or

en gi

n ee

ri n

g gr

ad ua

te s

5- po

in t

sc al

e: “e

xt re

m el

y n

ot re

qu ir

ed ”

to “e

xt re

m el

y re

qu ir

ed ”

T h

e 20

09 su

rv ey

h ad

on e

sa m

pl e

of se

ni or

en gi

ne er

s, m

an ag

er s,

an d

ch ie

f of

fi ce

rs in

co m

pa ni

es fr

om di

ve rs

e in

du st

ry se

ct or

s th

at em

pl oy

en gi

ne er

s (M

al ay

si a,

N 5

30 0,

R R

5 60

% ).

[2 5]

P as

so w

(2 01

2) S

� C

om pa

re d

tw o

w or

di n

gs an

d th

re e

al um

n iy

ea rs

12 fr

om A

B E

T “R

at e

h ow

im po

rt an

t th

e co

m pe

te n

c[ y.

.. h

as ]

be en

in yo

ur pr

of es

si on

al ex

pe ri

en ce

5- po

in t

sc al

e: “n

ot at

al li

m po

rt an

t” to

“e xt

re m

el y

im po

rt an

t”

T h

e su

rv ey

co n

d uc

te d

an n

ua ll

y fr

om 19

99 to

20 05

h ad

on e

sa m

pl e

of al

um n

i tw

o, si

x, or

10 ye

ar s

af te

r gr

ad ua

ti on

fr om

U ni

ve rs

it y

of M

ic h

ig an

fr om

va ri

– ou

s en

gi n

ee ri

n g

m aj

or s:

ae ro

sp ac

e, ch

em ic

al ,c

iv il

, co

m pu

te r,

el ec

tr ic

al ,i

n du

st ri

al an

d op

er at

io n

s, m

at e-

ri al

s, m

ec h

an ic

al ,m

ar in

e, an

d n

uc le

ar (U

.S .,

N 5

42 25

,R R

5 21

% ).

[2 6]

B ru

n h

av er

,G il

m ar

ti n

,G ra

u, S

h ep

pa rd

,& C

h en

(2 01

3) C

(p lu

s 20

15 da

ta fr

om th

e au

th or

s) �

C om

pa re

d th

re e

oc cu

pa ti

on gr

ou ps

[2 7]

B ru

n h

av er

20 15

� A

n in

de pe

n de

n t

an al

ys is

bu t

n ot

a se

pa ra

te st

ud y

20 fr

om A

B E

T an

d T

he E

ng in

ee r

of 20

20 (N

A E

, 20

04 )

R at

e im

po rt

an ce

to cu

rr en

t w

or k

5- po

in t

sc al

e: “n

ot im

po rt

an t”

to “e

xt re

m el

y im

po rt

an t”

T h

e 2

01 1

su rv

ey h

ad o

n e

sa m

pl e

o f

en gi

n ee

ri n

g pr

ac ti

ti o

n er

s, co

n su

lt an

ts an

d m

an ag

er s

w h

o w

er e

al um

ni fo

ur ye

ar s

af te

r gr

ad ua

ti on

fr om

fo ur

di ve

rs e

re se

ar ch

un iv

er si

ti es

in va

ri ou

s en

gi n

ee ri

n g

m aj

or s:

m ec

h an

ic al

, el

ec tr

ic al

, co

m pu

te r,

ch em

ic al

, ci

vi l,

ae ro

sp ac

e, an

d ot

h er

(U .S

., N

5 41

7 w

ei gh

te d

to a

sa m

pl e

of 2,

24 9

,R R

5 30

% ).

[2 8]

W al

cz ak

,U zi

ak ,O

la di

ra n

,B ae

za ,&

P ae

z (2

01 3)

C �

C om

pa re

d tw

o qu

es ti

on s

16 ba

se d

on va

ri ou

s ac

cr ed

it at

io n

ou tc

om es

H ow

re le

va n

t is

th e

at tr

ib ut

e fo

r a

m ec

h an

ic al

en gi

– n

ee r

in yo

ur co

m pa

n y?

4- po

in t

sc al

e: “n

ot re

le va

n t”

to “e

xt re

m el

y re

le va

n t”

H ow

of te

n do

m ec

h an

ic al

en gi

n ee

rs us

e th

e sk

il la

t yo

ur co

m pa

n y?

4- po

in t

sc al

e: “n

ev er

” to

“a lw

ay s”

T h

e 20

11 su

rv ey

h ad

on e

sa m

pl e

of em

pl oy

er s

of m

ec h

an ic

al en

gi n

ee ri

n g

gr ad

ua te

s (C

h ile

,N 5

10 2,

R R

5 16

% ).

S 5

id en

ti fi

ed in

th e

sy st

em at

ic se

ar ch

.R 5

id en

ti fi

ed in

th e

re fe

re n

ce li

st of

an in

cl ud

ed st

ud y.

C 5

id en

ti fi

ed be

ca us

e it

ci te

d an

in cl

ud ed

st ud

y.

512 Passow & Passow

 

 

A pp en di x C

St ud ie sI nc lu de d in th e Q ua lit at iv e A na ly sis

Th at D iff er en tia te be tw ee n G oo d an d O rd in ar y En gi ne er s

D es

cr ip

ti on

s of

th e

fo ur

st ud

ie s

in cl

ud ed

in th

e sy

st em

at ic

re vi

ew ’s

qu al

it at

iv e

th em

at ic

an al

ys is

, ad

dr es

si ng

th e

qu es

ti on

, “W

h at

co m

pe te

nc ie

s di

ff er

en ti

at e

be tw

ee n

go od

an d

or di

na ry

en gi

ne er

s? ”

(4 86

su rv

ey re

sp on

de nt

s pl

us 13

0 in

te rv

ie w

s)

S tu

d y

R es

ea rc

h qu

es ti

on an

d co

n te

xt M

et h

od s

fo r

sa m

pl e

se le

ct io

n ,d

at a

co lle

ct io

n ,a

n d

an al

ys is

[2 9]

K el

le y

& C

ap la

n (1

99 3)

R

W h

at is

th e

di ff

er en

ce be

tw ee

n to

p an

d av

er ag

e pe

rf or

m er

s? (E

ac h

to p

pe rf

or m

er w

as hi

gh ly

va lu

ed by

bo th

th ei

r m

an ag

er s

an d

th ei

r pe

er s.

) “I

f yo

u w

er e

st ar

ti ng

a ne

w co

m pa

ny an

d co

ul d

h ir

e on

ly te

n kn

ow le

dg e

pr of

es si

on al

s fr

om yo

ur pr

es en

t st

af f,

w h

om w

ou ld

yo u

h ir

e? ”

In te

rv ie

w ed

so ft

w ar

e en

gi n

ee rs

(i n

di vi

d ua

lly an

d in

fo cu

s gr

ou ps

) at

A T

& T

’s B

el lL

ab or

at or

ie s.

C om

pa re

d to

p an

d m

id d

le pe

rf or

m er

s’ d

es cr

ip ti

on s

pr od

uc –

ti vi

ty ,h

ow th

ey kn

ew w

h en

th ey

w er

e pr

od uc

ti ve

,a n

d w

h at

ex ac

tl y

it w

as th

ey di

d to

be pr

od uc

ti ve

.A ft

er th

e w

or k

de sc

ri pt

io n

s w

er e

su m

m ar

iz ed

fo r

th em

es ,

pa rt

ic ip

an ts

ra nk

ed st

ra te

gi es

in or

de r

of im

po rt

an ce

.S tu

dy le

d to

a tr

ai ni

ng pr

o- gr

am of

60 0

ou t

of 50

00 en

gi n

ee rs

th at

yi el

de d

d ra

m at

ic pr

od uc

ti vi

ty im

pr ov

e- m

en t

as d

et er

m in

ed by

bo th

m an

ag er

s an

d en

gi n

ee rs

(N n

ot re

po rt

ed ,U

.S .)

.

[3 0]

T ur

le y

& B

ie m

an (1

99 5)

S

W h

at sk

ill s,

te ch

ni qu

es ,a

nd at

tr ib

ut es

di ff

er en

ti at

e ex

ce pt

io na

la nd

no ne

xc ep

ti on

al so

ft w

ar e

en gi

ne er

in g

pe rf

or m

an ce

? In

te rv

ie w

ed 10

su pe

rv is

or -d

es ig

n at

ed ex

ce pt

io n

al an

d 10

n on

-e xc

ep ti

on al

so ft

– w

ar e

en gi

n ee

rs (N

5 20

). In

te rv

ie w

ed m

an ag

er s

(N 5

5) on

co m

pe te

n ci

es th

at di

ff er

en ti

at e

ex ce

pt io

n al

an d

n on

-e xc

ep ti

on al

en gi

n ee

rs .S

ur ve

ye d

so ft

w ar

e en

gi –

n ee

rs w

h o

Q -s

or te

d 38

co m

pe te

n ci

es (d

ev el

op ed

fr om

an ex

te n

si ve

in te

rv ie

w st

ud y)

fr om

“m os

t li

ke m

y be

h av

io r”

to “l

ea st

li ke

m y

be h

av io

r. ”

R at

in gs

w er

e co

m pa

re d

be tw

ee n

tw o

bl in

d ed

gr ou

ps –

su pe

rv is

or d

es ig

n at

ed “e

xc ep

ti on

al ”

(t op

30 %

) an

d “n

on -e

xc ep

ti on

al ”

(o th

er 70

% )

(N 5

12 9,

U .S

., si

n gl

e F

or tu

n e

50 0

co m

pa n

y) .

Undergraduate Engineering Competencies: A Sytematic Review 513

 

 

A pp en di x C (c on tin ue d)

S tu

dy R

es ea

rc h

qu es

ti on

an d

co n

te xt

M et

h od

s fo

r sa

m pl

e se

le ct

io n

,d at

a co

lle ct

io n

,a n

d an

al ys

is

[3 1]

N ew

po rt

& E

lm s

(1 99

7) C

W h

at tr

ai ts

ar e

es se

nt ia

lt o

ef fe

ct iv

e en

gi n

ee rs

an d

h ow

is ef

fe ct

iv en

es s

m ea

su re

d? D

ev el

o pe

d li

st of

tr ai

ts th

ro ug

h in

te rv

ie w

s (N

5 16

, N

ew Z

ea la

n d

,c h

em ic

al ,

ci vi

l, el

ec tr

ic al

,e n

vi ro

n m

en ta

l, m

ec h

an ic

al ,f

ou r

in d

us tr

y se

ct or

s) .C

or re

la te

d an

en gi

n ee

r’ s

le ve

lo f

ex h

ib it

in g

a tr

ai t

w it

h th

ei r

le ve

lo f

ef fe

ct iv

en es

s m

ea su

re d

in se

pa ra

te su

rv ey

s of

th e

en gi

n ee

r an

d h

is /h

er su

pe rv

is or

(N 5

77 en

gi n

ee r-

su pe

rv is

or pa

ir s,

n o

re p

or t

of sa

m p

le se

le ct

io n

,N ew

Z ea

la n

d ).

(E ff

ec ti

ve n

es s

sc al

e: 7-

po in

t, “n

ot at

al le

ff ec

ti ve

,” “m

od er

at el

y ef

fe ct

iv e”

.. .

“v er

y ef

fe ct

iv e,

” w

it h

15 %

ra te

d “v

er y

ef fe

ct iv

e” ).

[3 2]

G ro

w h

ow sk

i- N

ic om

et o,

N at

h an

s- K

el ly

,& A

n de

rs on

(2 00

9) S

A n

ea rl

y re

po rt

an d

in de

pe n

de n

t an

al ys

is of

A n

de rs

on (2

00 9)

,n ot

a se

pa ra

te st

ud y

W h

at tr

ai ts

do yo

u va

lu e

in ot

h er

en gi

n ee

rs ?

D es

cr ib

e an

in ef

fe ct

iv e

en gi

n ee

r. S

ur ve

ye d

en gi

n ee

ri n

g al

um n

if ro

m U

n iv

er si

ty of

W is

co n

si n

pr ac

ti ci

n g

in va

ri –

ou s

fi el

ds an

d si

ze s

of or

ga n

iz at

io n

w it

h op

en -e

n de

d qu

es ti

on s

(N 5

28 0,

U .S

.) .

In te

rv ie

w ed

to p-

pe rf

or m

in g

en gi

n ee

rs in

fo ur

or ga

n iz

at io

n s

(N 5

34 ,U

.S .)

. In

te rv

ie w

ed pr

ac ti

ci n

g en

gi n

ee rs

(c on

du ct

ed by

fr es

h m

en en

gi n

ee ri

n g

st ud

en ts

) (N

5 60

,U .S

.) C

om pa

re d

de sc

ri pt

io n

s of

va lu

ed an

d in

ef fe

ct iv

e en

gi n

ee rs

in em

er ge

n t

th em

at ic

an al

ys is

.

S 5

id en

ti fi

ed in

th e

sy st

em at

ic se

ar ch

.R 5

id en

ti fi

ed in

th e

re fe

re n

ce li

st of

an in

cl ud

ed st

ud y.

C 5

id en

ti fi

ed be

ca us

e it

ci te

d an

in cl

ud ed

st ud

y.

514 Passow & Passow

 

 

A pp en di x D

St ud ie sI nc lu de d in th e Q ua lit at iv e A na ly sis

D es cr ib in g G oo d En gi ne er s

D es

cr ip

ti on

s of

th e

th re

e st

ud ie

s in

cl ud

ed in

th e

sy st

em at

ic re

vi ew

’s qu

al it

at iv

e th

em at

ic an

al ys

is ,a

dd re

ss in

g th

e qu

es ti

on ,“

W h

at co

m pe

te nc

ie s

ar e

ex h

ib it

ed by

a go

od (o

r ef

fe ct

iv e

or ex

ce pt

io na

l) en

gi ne

er ?”

(6 96

su rv

ey re

sp on

de nt

s pl

us 38

in te

rv ie

w s)

S tu

d y

R es

ea rc

h qu

es ti

on an

d co

n te

xt M

et h

od s

fo r

sa m

pl e

se le

ct io

n ,d

at a

co lle

ct io

n ,a

n d

an al

ys is

[3 3]

B ai

le y,

Jo h

n so

n ,A

lo n

so ,&

O rz

ec h

ow sk

i (2

00 7)

S

W h

at ch

ar ac

te ri

st ic

s de

fi ne

a go

od de

si gn

er in

th e

st ru

ct ur

al en

gi ne

er in

g co

n te

xt ?

S u

rv ey

ed re

sp o

n d

en ts

ge n

er at

ed th

e fi

ve m

ai n

ch ar

ac te

ri st

ic s

th at

d es

cr ib

e a

go od

d es

ig n

er .R

es po

n d

en ts

w er

e m

ai n

ly ci

vi l

an d

st ru

ct ur

al en

gi n

ee rs

w it

h tw

o le

ve ls

of ex

pe ri

en ce

:e xp

er ie

n ce

d en

gi n

ee rs

ag e

46 to

60 ye

ar s

(N 5

39 9

re p-

re se

n ti

n g

19 0

or ga

n iz

at io

n s)

an d

re ce

n t

gr ad

ua te

s ag

e 21

to 25

ye ar

s (N

5 29

7 fr

om 66

U .K

.u n

iv er

si ti

es an

d re

pr es

en ti

n g

79 or

ga n

iz at

io n

s) .A

n al

ys is

ta lli

ed th

em es

th en

ra n

ke d

by fr

eq ue

n cy

.

[3 4]

D er

ro &

W ill

ia m

s (2

00 9)

S

W h

at co

m pe

te n

ci es

ar e

ex h

ib it

ed by

“h ig

h ly

re ga

rd ed

” sy

st em

s en

gi n

ee rs

an d

h ow

im po

rt an

t is

ea ch

of th

es e

fo r

pr oj

ec t

su cc

es s?

In te

rv ie

w ed

an d

ob se

rv ed

h ig

h ly

re ga

rd ed

sy st

em s

en gi

n ee

rs at

m ul

ti pl

e N

A S

A ce

n te

rs (N

5 38

,U .S

.) .A

pr io

ri th

eo ry

sh ap

ed th

em at

ic an

al ys

is to

yi el

d co

m pe

te n

ci es

. [3

5] A

n de

rs on

,C ou

rt er

,M cG

la m

er y,

N at

h an

s- K

el ly

,& N

ic om

et o

(2 01

0) S

W h

at is

th e

w or

k of

“e ff

ec ti

ve ”

en gi

n ee

rs an

d w

h at

sk il

ls d

oe s

it re

qu ir

e? C

as e

st ud

ie s

of en

gi n

ee rs

an d

en gi

n ee

ri ng

gr ou

ps de

em ed

“e ff

ec ti

ve ”

by m

an ag

– er

s at

en gi

n ee

ri n

g fi

rm s

(N 5

6) th

at va

ri ed

by si

ze an

d in

du st

ry in

th e

n or

th er

n M

id w

es t

(U .S

.) us

in g

qu al

it at

iv e

et h

n og

ra ph

ic m

et h

od s,

in cl

ud in

g in

te rv

ie w

s (N

n o

t re

po rt

ed )

an d

o b

se rv

at io

n s

(N n

o t

re po

rt ed

) an

d m

em b

er ch

ec k

in g.

C ro

ss -c

as e

an al

ys is

of si

m il

ar it

ie s

an d

d if

fe re

n ce

s ac

ro ss

si te

s, su

pp or

te d

by n

ar –

ra ti

ve ex

am pl

es .

S 5

id en

ti fi

ed in

th e

sy st

em at

ic se

ar ch

.R 5

id en

ti fi

ed in

th e

re fe

re n

ce li

st of

an in

cl ud

ed st

ud y.

C 5

id en

ti fi

ed be

ca us

e it

ci te

d an

in cl

ud ed

st ud

y.

Undergraduate Engineering Competencies: A Sytematic Review 515

 

 

A pp en di x E

St ud ie sI nc lu de d in th e Q ua lit at iv e A na ly sis

D es cr ib in g C om

pe te nc ie sN

ee de d fo rS uc ce ss

D es

cr ip

ti on

s of

th e

si x

st ud

ie s

in cl

ud ed

in th

e sy

st em

at ic

re vi

ew ’s

qu al

it at

iv e

th em

at ic

an al

ys is

, ad

d re

ss in

g th

e qu

es ti

on ,

“W h

at co

m pe

te n

ci es

ar e

n ee

d ed

fo r

su cc

es s

in yo

ur em

pl oy

ee s’

en gi

n ee

ri n

g w

or k?

” (5

7 in

te rv

ie w

s pl

us 36

,1 00

jo b

po st

in gs

)

S tu

d y

R es

ea rc

h qu

es ti

on an

d co

n te

xt M

et h

od s

fo r

sa m

pl e

se le

ct io

n ,d

at a

co lle

ct io

n ,a

n d

an al

ys is

[3 6]

W at

so n

(1 99

9) S

W h

at ch

ar ac

te ri

st ic

s do

re ce

n t

gr ad

ua te

s (u

p to

th re

e ye

ar s

ou t)

n ee

d to

su cc

ee d

as an

en gi

n ee

r? In

te rv

ie w

ed su

pe rv

is or

s of

si x

to ei

gh t

en gi

n ee

rs (i

n cl

ud in

g at

le as

t on

e re

ce n

t gr

ad ua

te );

su pe

rv is

or s

w er

e en

gi n

ee rs

at co

m pa

n ie

s th

at re

cr ui

t at

M ic

h ig

an S

ta te

U n

iv er

si ty

(N 5

3, U

.S .,

th re

e di

ff er

en t

or ga

n iz

at io

n s)

.C on

st an

t co

m –

pa ri

so n

an al

ys is

yi el

de d

em er

ge n

t th

em es

.

[3 7]

S pi

n ks

,S il

bu rn

& B

ir ch

al l(

20 07

)S

W h

at sk

il ls

an d

at tr

ib ut

es do

n ew

ly gr

ad ua

te d

en gi

n ee

rs n

ee d

to su

cc ee

d on

th e

jo b?

In te

rv ie

w ed

in d

iv id

ua ls

w it

h fi

rs t-

h an

d kn

ow le

d ge

of th

ei r

co m

p an

y’ s

sk il

ls de

m an

ds fo

r ne

w ly

gr ad

ua te

d en

gi ne

er s,

h um

an re

so ur

ce s

pe rs

on ne

la n

d se

ni or

m an

ag er

s (N

5 27

,U .K

., m

an y

in du

st ri

es ,2

1 fi

rm s)

.A na

ly ze

d em

er gi

ng th

em es

.

[3 8]

V er

ga ra

,M ar

k, D

re se

n ,C

ox en

,M ac

F ar

la n

e, F

ra zi

er ,e

t al

.( 20

09 )S

W h

at sk

il ls

ar e

n ee

de d

in co

re en

gi n

ee ri

n g

po si

ti on

s? W

h at

ar e

th e

m aj

or en

gi –

n ee

ri n

g ch

al le

n ge

s in

th os

e po

si ti

on s?

In te

rv ie

w ed

th e

h ea

d of

en gi

n ee

ri n

g or

h um

an re

so ur

ce s

ex ec

ut iv

e or

bo th

at co

m pa

n ie

s ch

os en

to re

pr es

en t

tw el

ve in

du st

ri es

(s of

tw ar

e, po

w er

ge n

er at

io n,

m an

uf ac

tu ri

n g

in ei

gh t

se ct

or s,

ar ch

it ec

tu ra

le n

gi n

ee ri

n g,

an d

go ve

rn m

en t)

an d

fo ur

en gi

n ee

ri n

g di

sc ip

lin es

:c h

em ic

al ,m

ec h

an ic

al ,c

iv il,

an d

el ec

tr ic

al (N

5 27

, U

.S .,

va ri

ou s

in du

st ri

es ).

A n

al ys

is w

as th

em at

ic in

th re

e a

pr io

ri ca

te go

ri es

.

[3 9]

H en

sh aw

(1 99

1) S

W h

at ch

ar ac

te ri

st ic

s do

em pl

oy er

s lis

t in

ad ve

rt is

em en

ts fo

r en

gi ne

er in

g po

si ti

on s?

O ve

r a

pe ri

od of

52 w

ee ks

,a n

al yz

ed en

gi n

ee ri

n g

em pl

oy m

en t

ad ve

rt is

em en

ts fo

r fr

eq ue

nc y

of m

en ti

on of

co m

pe te

nc ie

s fr

om th

e A

us tr

al ia

n ca

pi ta

lc it

y da

ily n

ew sp

ap er

s an

d te

ch n

ic al

m ag

az in

es (N

5 27

,0 00

n ew

ad s,

A us

tr al

ia ).

A n

al ys

is w

as by

ta lly

in g

th em

es .

516 Passow & Passow

 

 

A pp en di x E (c on tin ue d)

S tu

dy R

es ea

rc h

qu es

ti on

an d

co n

te xt

M et

h od

s fo

r sa

m pl

e se

le ct

io n

,d at

a co

lle ct

io n

,a n

d an

al ys

is

[4 0]

A co

st a

(2 01

0) S

W h

at ch

ar ac

te ri

st ic

s d

o em

pl oy

er s

li st

in jo

b po

st in

gs ?

A n

al yz

ed en

gi n

ee ri

n g

em pl

oy m

en t

po st

in gs

fo r

fr eq

ue n

cy of

m en

ti on

of 47

co m

p et

en ci

es in

M IT

’s ca

re er

se rv

ic es

d at

ab as

e (N

5 8

0 0

0 p

o st

in gs

, U

.S .)

. A

n al

ys is

w as

b y

ta ll

yi n

g th

em es

.

[4 1]

A bd

E la

ll, R

am ah

i, &

S el

in ge

r (2

01 2)

C

W h

at ch

ar ac

te ri

st ic

s do

em pl

oy er

s lis

t in

ad ve

rt is

em en

ts fo

r en

gi ne

er in

g po

si ti

on s?

A n

al yz

ed en

gi n

ee ri

n g

em pl

oy m

en t

ad ve

rt is

em en

ts fr

om on

li n

e jo

b d

at ab

as es

(s uc

h as

w w

w .m

on st

er .c

om ,w

w w

.jo bs

ea rc

h .c

o. uk

(n ow

w w

w .fi

sh 4.

co .u

k) ,a

n d

w w

w .b

ay t.

co m

) d

ur in

g th

e fi

rs t

qu ar

te r

of 20

11 (N

5 1,

10 0

ad s,

va ri

ou s

co un

– tr

ie s,

m an

uf ac

tu ri

n g

en gi

n ee

ri n

g) .A

n al

ys is

w as

by ta

ll yi

n g

th em

es th

ro u

gh co

m pu

te r

al go

ri th

m s.

S 5

id en

ti fi

ed in

th e

sy st

em at

ic se

ar ch

.R 5

id en

ti fi

ed in

th e

re fe

re n

ce li

st of

an in

cl ud

ed st

ud y.

C 5

id en

ti fi

ed be

ca us

e it

ci te

d an

in cl

ud ed

st ud

y.

Undergraduate Engineering Competencies: A Sytematic Review 517

 

 

A pp en di x F

St ud ie sI nc lu de d in th e Q ua lit at iv e A na ly sis

D es cr ib in g C om

pe te nc ie sI m po rt an ti n En gi ne er in g W or k

D es

cr ip

ti on

s of

th e

fo ur

st ud

ie s

in cl

ud ed

in th

e sy

st em

at ic

re vi

ew ’s

qu al

it at

iv e

th em

at ic

an al

ys is

,a dd

re ss

in g

th e

qu es

ti on

,“ W

h at

co m

pe te

nc ie

s ar

e im

po rt

an t

in yo

ur ow

n en

gi ne

er in

g w

or k?

In ge

ne ra

l? In

a sp

ec ifi

c ep

is od

e of

su cc

es s

or fa

ilu re

?” (1

04 su

rv ey

re sp

on de

nt s

pl us

88 in

te rv

ie w

s)

S tu

d y

R es

ea rc

h qu

es ti

on an

d co

n te

xt M

et h

od s

fo r

sa m

pl e

se le

ct io

n ,d

at a

co lle

ct io

n ,a

n d

an al

ys is

[4 2]

K im

bl e-

T h

om ,T

h om

,& C

ro ss

le y

(2 00

5) S

W h

at sk

ill s

ar e

n ec

es sa

ry to

su cc

es sf

ul ly

de si

gn a

co m

pl ex

sy st

em ?

(T h

at is

,a sy

s- te

m th

at re

qu ir

es tr

ad e-

of fs

be tw

ee n

co nt

ra di

ct or

y ne

ed s

an d

re qu

ir es

kn ow

le dg

e of

at le

as t

th re

e in

di vi

du al

s or

di sc

ip lin

es .)

In te

rv ie

w ed

de si

gn pr

ac ti

ti on

er s

fi ve

or m

or e

ye ar

s ou

t of

sc h

oo lw

h o

de sc

ri be

d pe

rs on

al ex

pe ri

en ce

s w

h er

e la

ck of

a sk

il lr

es ul

te d

in a

pr ob

le m

(N 5

11 ,U

.S .,

m an

y in

du st

ri es

). C

ro ss

-c as

e an

al ys

is fo

r em

er gi

n g

th em

es .

[4 3]

K or

te ,S

h ep

pa rd

,& Jo

rd an

(2 00

8) R

R ec

al lt

w o

pr oj

ec ts

or pr

ob le

m s

th at

re qu

ir ed

yo ur

te ch

n ic

al ex

pe rt

is e.

H ow

d id

yo u

re so

lv e

ea ch

pr ob

le m

? In

te rv

ie w

ed m

ec h

an ic

al an

d el

ec tr

ic al

en gi

n ee

rs w

it h

le ss

th an

tw o

ye ar

s’ ex

pe –

ri en

ce si

n ce

gr ad

ua ti

on w

it h

a gl

ob al

m an

uf ac

tu re

r (N

5 17

,U .S

., h

ig h

te ch

pr od

uc t

in du

st ry

). T

ag ge

d al

ld at

a re

le va

n t

to pr

ob le

m so

lv in

g fo

r gr

ou n

de d

th e-

or y

an al

ys is

.

[4 4]

A n

de rs

on ,C

ou rt

er ,M

cG la

m er

y, N

at h

an s-

K el

ly ,&

N ic

om et

o (2

00 9)

S

W h

at sk

ill s

ar e

im po

rt an

t in

yo ur

w or

k? In

a n

ot ab

le ev

en t

fr om

yo ur

w or

k th

at gi

ve s

a go

od pi

ct ur

e of

en gi

n ee

ri n

g, w

h ic

h sk

ill s

w er

e m

os t

im po

rt an

t? W

h y

do es

yo ur

no ta

bl e

ev en

t gi

ve a

go od

de sc

ri pt

io n

of en

gi n

ee ri

n g?

In te

rv ie

w ed

pr ac

ti ci

n g

en gi

n ee

rs (N

5 45

, U

.S .,

on e

ve ry

la rg

e, in

te rn

at io

n al

m an

uf ac

tu ri

n g

co rp

o ra

ti on

); su

rv ey

ed en

gi n

ee ri

n g

al um

n i

of U

n iv

er si

ty of

W is

co n

si n

-M ad

is on

(N 5

10 4

an al

yz ed

re sp

o n

se s,

U .S

., va

ri o

us in

d u

st ri

es ).

A n

al ys

is of

em er

gi n

g th

em es

su pp

o rt

ed by

n ar

ra ti

ve ex

am p

le s

fo r

al l

op en

– en

d ed

re sp

o n

se s;

d es

cr ip

ti ve

st at

is ti

cs fo

r cl

os ed

-e n

d ed

re sp

o n

se s.

[4 5]

N iu

& W

an g

(2 01

1) S

W h

at is

th e

di ff

er en

ce be

tw ee

n go

od an

d or

di n

ar y

sa le

s en

gi n

ee rs

? G

iv e

an ex

am –

pl e

of su

cc es

s (o

r fa

ilu re

). W

h at

w er

e th

e re

as on

s fo

r th

e ou

tc om

e? W

h at

sk ill

s do

yo u

n ee

d in

yo ur

jo b?

In te

rv ie

w ed

sa le

s en

gi n

ee rs

(N 5

15 ,T

ai w

an ,s

em ic

on du

ct or

in du

st ry

,v ar

io us

co m

pa n

ie s

an d

in du

st ry

se gm

en ts

– de

si gn

,m an

uf ac

tu re

,p ac

ka gi

n g,

an d

te st

– in

g) .C

on te

n t

an al

ys is

.

S 5

id en

ti fi

ed in

th e

sy st

em at

ic se

ar ch

.R 5

id en

ti fi

ed in

th e

re fe

re n

ce li

st of

an in

cl ud

ed st

ud y.

C 5

id en

ti fi

ed be

ca us

e it

ci te

d an

in cl

ud ed

st ud

y.

518 Passow & Passow

 

 

A pp en di x G

St ud ie sI nc lu de d in th e Q ua lit at iv e A na ly sis Th at C ha ra ct er iz e En gi ne er in g Pr ac tic e

D es

cr ip

ti on

s of

th e

n in

e st

ud ie

s in

cl ud

ed in

th e

sy st

em at

ic re

vi ew

’s qu

al it

at iv

e th

em at

ic an

al ys

is ,a

d dr

es si

n g

th e

qu es

ti on

,“ W

h at

co m

pe te

n ci

es ch

ar ac

te ri

ze en

gi n

ee ri

n g

pr ac

ti ce

? H

ow d

o th

ey in

te ra

ct ?”

(4 35

su rv

ey re

sp on

d en

ts pl

us 27

8 in

te rv

ie w

s an

d et

h n

og ra

ph y

pa rt

ic ip

an ts

)

S tu

dy R

es ea

rc h

qu es

ti on

an d

co n

te xt

M et

h od

s fo

r sa

m pl

e se

le ct

io n

,d at

a co

lle ct

io n

,a n

d an

al ys

is

[4 6]

S ol

om on

& H

ol t

(1 99

3) R

W h

at d

o en

gi n

ee rs

d o?

In te

rv ie

w ed

pr ac

ti ci

n g

m ec

h an

ic al

en gi

n ee

rs em

pl oy

ed in

a ra

n ge

of or

ga n

iz a-

ti on

s an

d in

du st

ry se

ct or

s. F

ou r

ca re

er st

ag es

:“ ap

pr en

ti ce

,” “c

ol le

ag ue

,” “m

en to

r, ”

an d

“s po

n so

r” (N

5 21

,A us

tr al

ia ).

T h

em at

ic an

al ys

is in

fo ur

a pr

io ri

ca te

go ri

es ex

pa n

d ed

to si

x ca

te go

ri es

an d

em er

gi n

g th

em es

.

[4 7]

B uc

ci ar

el li

& K

uh n

(1 99

7) R

W h

at ar

e th

e co

m m

on fe

at ur

es of

en gi

n ee

ri n

g w

or k?

E th

n og

ra ph

ic st

ud y

in cl

ud in

g in

te rv

ie w

s an

d ob

se rv

at io

n s

of en

gi n

ee ri

n g

de si

gn pr

oj ec

ts (N

5 10

fi rm

s, U

.S .)

.A n

al ys

ed em

er gi

n g

th em

es .

[4 8]

P er

lo w

& B

ai ly

n (1

99 7)

R

W h

at d

o en

gi n

ee rs

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Undergraduate Engineering Competencies: A Sytematic Review 519

 

 

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y.

520 Passow & Passow

 

 

Acknowledgments Janice Chapman Allen, Curator of Visual Resources at Dartmouth’s Visual Resource Center, provided valuable expertise in preparing the images for publication.

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Undergraduate Engineering Competencies: A Sytematic Review 525

 

 

Authors Honor J. Passow, a registered engineer, is a research project director and lecturer in the

Geisel School of Medicine at Dartmouth College, One Medical Center Drive, WTRB Level 5, Lebanon, NH 03766, honor.j.passow@dartmouth.edu.

Christian H. Passow, a registered engineer, is manager of design services and a design engineer at Creare LLC, 16 Great Hollow Road, Hanover, NH, 03755, chp@creare.com.

526 Passow & Passow

 

 

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Our essay writers are graduates with diplomas, bachelor’s, masters, Ph.D., and doctorate degrees in various subjects. The minimum requirement to be an essay writer with our essay writing service is to have a college diploma. When assigning your order, we match the paper subject with the area of specialization of the writer.

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How It Works

1.      Place an order

You fill all the paper instructions in the order form. Make sure you include all the helpful materials so that our academic writers can deliver the perfect paper. It will also help to eliminate unnecessary revisions.

2.      Pay for the order

Proceed to pay for the paper so that it can be assigned to one of our expert academic writers. The paper subject is matched with the writer’s area of specialization.

3.      Track the progress

You communicate with the writer and know about the progress of the paper. The client can ask the writer for drafts of the paper. The client can upload extra material and include additional instructions from the lecturer. Receive a paper.

4.      Download the paper

The paper is sent to your email and uploaded to your personal account. You also get a plagiarism report attached to your paper.

 

 


Get Professional Assignment Help Cheaply

fast coursework help

Are you busy and do not have time to handle your assignment? Are you scared that your paper will not make the grade? Do you have responsibilities that may hinder you from turning in your assignment on time? Are you tired and can barely handle your assignment? Are your grades inconsistent?

Whichever your reason may is, it is valid! You can get professional academic help from our service at affordable rates. We have a team of professional academic writers who can handle all your assignments.

Our essay writers are graduates with diplomas, bachelor's, masters, Ph.D., and doctorate degrees in various subjects. The minimum requirement to be an essay writer with our essay writing service is to have a college diploma. When assigning your order, we match the paper subject with the area of specialization of the writer.

Why Choose Our Academic Writing Service?

  • Plagiarism free papers
  • Timely delivery
  • Any deadline
  • Skilled, Experienced Native English Writers
  • Subject-relevant academic writer
  • Adherence to paper instructions
  • Ability to tackle bulk assignments
  • Reasonable prices
  • 24/7 Customer Support
  • Get superb grades consistently

How It Works

1.      Place an order

You fill all the paper instructions in the order form. Make sure you include all the helpful materials so that our academic writers can deliver the perfect paper. It will also help to eliminate unnecessary revisions.

2.      Pay for the order

Proceed to pay for the paper so that it can be assigned to one of our expert academic writers. The paper subject is matched with the writer’s area of specialization.

3.      Track the progress

You communicate with the writer and know about the progress of the paper. The client can ask the writer for drafts of the paper. The client can upload extra material and include additional instructions from the lecturer. Receive a paper.

4.      Download the paper

The paper is sent to your email and uploaded to your personal account. You also get a plagiarism report attached to your paper.

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