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On the design of learning outcomes forthe undergraduate engineer's final yearprojectAshvin Thambyah aa Chemical and Materials Engineering , University of Auckland ,Auckland, New ZealandPublished online: 16 Feb 2011.

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European Journal of Engineering EducationVol. 36, No. 1, March 2011, 35–46

On the design of learning outcomes for the undergraduateengineer’s final year project

Ashvin Thambyah*

Chemical and Materials Engineering, University of Auckland, Auckland, New Zealand

(Received 22 June 2010; final version received 24 September 2010 )

The course for the final year project for engineering students, because of its strongly research-based,open-ended format, tends to not have well defined learning outcomes, which are also not aligned with anyaccepted pedagogical philosophy or learning technology. To address this problem, the revised Bloom’staxonomy table of Anderson and Krathwohl (2001) is utilised, as suggested previously by Lee and Lai(2007), to design new learning outcomes for the final year project course in engineering education. Basedon the expectations of the engineering graduate, and integrating these graduate expectations into the sixcognitive processes and four knowledge dimensions of the taxonomy table, 24 learning outcomes havebeen designed. It is proposed that these 24 learning outcomes be utilised as a suitable working template toinspire more critical evaluation of what is expected to be learnt by engineering students undertaking finalyear research or capstone projects.

Keywords: capstone project; revised Bloom’s taxonomy; rubric, taxonomy table

Introduction

In most universities around the world, an important milestone in the undergraduate engineeringprogramme is the final year project (FYP). Typically, the FYP involves design or research, or both,and runs over two semesters or a full year. The FYP course serves several purposes in terms of thegeneral requirements for an engineering degree programme. First, it serves as the ‘grand finale’ ofthe entire engineering undergraduate programme, where students are expected to utilise the skillsand knowledge gained from the first three years of taught-course work (Vitner and Rozenes 2009,Ku and Goh 2010). Second, the credits of the FYP course contribute significantly to a four-yearhonours degree programme, the length of time recommended for an undergraduate engineeringdegree (Kentish and Shallcross 2006). Third, the project results in the submission of a thesis thatsatisfies the requirement of an honours programme and, typically, graduates gain automatic entryto graduate membership of the local organisation that awards professional engineer status (e.g.in New Zealand it would be the Institution of Professional Engineers New Zealand (IPENZ)).Fourth, the research experience fulfils professional engineering accreditation requirements forengineering students to be able to achieve the standards or graduate attributes as defined by the

*Email: ashvin.thambyah@auckland.ac.nz

ISSN 0304-3797 print/ISSN 1469-5898 online© 2011 SEFIDOI: 10.1080/03043797.2010.528559http://www.informaworld.com

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Washington Accord. Signed in 1989, the Washington Accord is an international agreement amongbodies responsible for accrediting engineering degree programmes. It recognises the substantialequivalency of programmes accredited by those bodies and recommends that graduates of pro-grammes accredited by any of the signatory bodies be recognised by the other bodies as havingmet the academic requirements for entry to the practice of engineering.

The FYP is, therefore, a crucial component of the degree programme and, for many, a point ofintense interest when it comes to trying to improve the quality of engineering education (Ku andGoh 2010).

Of particular interest is the issue on what should be the learning outcomes for the FYP, which,across departments and institutions, appear to be fairly scattered, inconsistent and not necessarilyaligned with any fundamental pedagogical philosophy or learning technology (Teo and Ho 1998,Jenkins et al. 2002, Bovea and Gallardo 2006, Lee and Lai 2007, Wiley et al. 2008). The problemin setting specific learning outcomes for the FYP programme stems from the nature of the course,which requires an open-ended approach to problem solving. Such a viewpoint arises from theneed for engineers to be able to apply theoretical knowledge, and not necessarily in an overlystructured manner, to tackle practical problems in real life.The need for engineers to be fluid in theirapproach to problem solving, spontaneous and being able to ‘think on their feet’, makes the ideaof structured learning outcomes for the FYP a seemingly counter-productive endeavour. Further,it is arguably more difficult to design a standardised set of learning outcomes and assessmentsfor the FYP within the more subjective domain of research and design. (Likewise, it is easy toappreciate how student assessment on the FYP would also tend to be less well thought out.)

Therefore, while learning outcomes for many of the typical taught-courses may be designedaccording to the numerous guides available, for the FYP it is different and more complex to simplydo the same. However, there are several good reasons to strive towards a structured set of learningoutcomes for the FYP course. For example, with many countries signed up to the WashingtonAccord, a common set of clear outcomes would potentially improve overall standardisation ofinternational engineering education whilst providing a guide to students and stakeholders onwhat is to be expected in terms of graduate attributes and competencies. Further, and maybe moreimportantly, the design of an ideal set of learning outcomes for the FYP will be beneficial to bothteachers and the students to be on the ‘same page’ when it comes to the assessment of what istruly a relatively vague ‘playing field’. So how does one go about designing learning outcomesfor such a course?

That there is a general lack of instruction on designing detailed learning outcomes for theFYP course follows from a relative dearth in the literature on the specifics on just how to designlearning outcomes for courses that teach the solving of non-structured-problems. This sentimentis expressed by Jonassen (1997), who discusses the issues facing problem-solving learning andreads as follows:

Because problem solving outcomes are not sufficiently acknowledged or articulated in the instructional-designliterature, little advice about how to design problem-solving instruction is available. Generic recommendationsabout using case instruction, simulations, Socratic dialogues, heuristics, and algorithms to engage and supportproblem solving are common, but no instructional-design models provide any prescriptions for designing thecomponents of instruction.

Jonassen (1997) goes on to present models for problem solving of ill-structured problems aswell as models for designing and engaging learners of such skills. So too do others, who havemore recently presented recommendations for practitioners on how to devise learning outcomesfor FYP courses (Jenkins et al. 2002, Wiley et al. 2008, Vitner and Rozenes 2009). From thesepapers it is clear that some common strategies used are those that align the learning outcomeswith:(1) the prescribed graduate attributes as determined by accreditation bodies (Jenkins et al.2002, Wiley et al. 2008); or (2) the expectations of graduate engineers in the workplace (Vitnerand Rozenes 2009).

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Knowledge

Knowledgedimension

Cognitiveprocessdimension

Separatedimension

Remember

Noun aspect

(A) (B)

Verb aspect

Understand

Apply

Factual

Remember Understand Apply Analyse Evaluate Create

Conceptual

Procedural

Meta-cognitive

Analyze

Evaluate

Create

Application

Analysis

Synthesis

Evaluation

Comprehension

Figure 1. (a) Summary of the main modifications to Bloom’s taxonomy in the revised Bloom’s taxonomy; (b) theconstruction of the taxonomy table from the revised taxonomy (Anderson and Krathwohl, 2001).Note: Anderson & Krathwohl, A TAXONOMY FOR LEARNING, TEACHING AND ASSESSMENT, © 2001 AddisonWesley Longman, Inc. Reproduced by permission of Pearson Education, Inc.

Both the above strategies are compelling; yet of interest is a third strategy, which involves theuse of accepted learning theories to help construct the learning outcomes of the FYP course andparticularly the revised Bloom’s taxonomy of Anderson and Krathwohl (2001). Such a proposalhas been put forth (Lee and Lai 2007) and appears, in the opinion of the present author, as a verypromising way forward to improve the approach to develop the student learning process in theFYP experience, primarily because it is based on a sound learning theory. That Bloom’s taxonomyis commonly used in engineering educational development is not new, but the revised Bloom’staxonomy introduces a fundamentally novel approach (as discussed below) and is the topic ofinterest in the present paper.

Bloom’s taxonomy (1956) is a well-known and widely used learning theory and, in Andersonand Krathwohl’s (2001) revision, four main differences are observed as follows: (1) the knowledgedimension is expanded; (2) the categories in the original Bloom’s taxonomy are modified intoverbs; (3) the original terms ‘synthesis’ and ‘evaluation’ are switched and renamed ‘create’ and‘evaluate’; (4) the Bloom taxonomy is defined as the cognitive domain (see Figure 1a). In all,a taxonomy table (Anderson and Krathwohl 2001) is formed, which the practitioner can use toconstruct the specific learning outcomes, activities or objectives for the course (Figure 1b).

Therefore, the objective of the exercise described in this paper is to apply the suggestion of Leeand Lai (2007), which is to use the revised Bloom’s taxonomy, and construct a complete and opera-tionally ready taxonomy table for a FYP course. The specific aim is to build a table of learning out-comes, and an associated rubric, to aid in the student learning and assessment process for the FYP.

Constructing the taxonomy table

For the construction of the taxonomy table, the following was used or considered in the process:

1. The taxonomy table provided by Anderson and Krathwohl (2001) on the revised Bloom’staxonomy (Figure 1).

2. The description of the Cognitive Dimension by Anderson and Krathwohl (2001) (seeAppendix A).

3. The description of the major types and sub-types of the Knowledge Dimension by Andersonand Krathwohl (2001) (see Appendix B).

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4. The listed graduate competencies and attributes (as detailed by the New Zealand engineeringprogramme accreditation body, IPENZ (see Appendix C).

The proposed taxonomy table, with the actions and criteria for learning, is presented (see Table 1).The table aligns the range of efforts or action that is required by the student (the six column headers)with the range of knowledge types that can potentially be achieved or expressed (row headers).The recommended way of using this table is to apply the column headers, or cognitive process,to the four knowledge dimensions and use the learning outcomes within each cell as a checklist.The following case is a simulation to elucidate this important concept on using the taxonomytable.

Case 1

Students George and Michael have both submitted FYP reports. Although they have submittedindividually written reports, both these students have worked on a single research project as apaired team. The project is about the microstructure of cartilage and how it responds to loading.George, in his literature review of about eight pages, includes a detailed description of the previouswork done on cartilage biomechanics, describes the tissue structure right down to the ultra-scalarlevel (collagen fibril types and molecular structure), the well-known biphasic and porovisco elasticmodels for cartilage. Michael, in his review of also about eight pages, describes the knownmicro-architecture of cartilage, introduces the models, but does not go into detail about the tissueultrastructure. Instead, he includes a labelled paragraph that summarises the gaps in the literatureand what remains unknown.

In assessing the reviews of George and Michael, and in terms of the levels of cognitive andknowledge achievements listed in the taxonomy table (Table 1), George would have covered thelearning outcomes described in cells 1A, 1B, 1C and 2A. Michael, on the other hand, would haveaccomplished all of that, plus cells 2B and 2C. (Note that 1D, 2D and the rest of the cells of thetaxonomy table are not applied to this case as it is merely the eight pages of literature reviewthat are being assessed). Thus, by accomplishing more of the learning outcomes, Michael wouldrightfully receive a higher grade than George.

Therefore, the recommended assessment for the FYP course may similarly be carried out inrelation to the extent to which all 24 learning outcomes described in Table 1 have been achieved.

A recommended grading rubric is shown in Table 2. In order to derive a score, grades from 0to 6 (for the cognitive descriptors) could be obtained for each of the four knowledge dimensions.The grade is thus based on the level of achievement across the taxonomy table. Therefore, in termsof the learning outcomes shown in Table 1, a possible rubric for scoring student achievement maybe devised as shown in Table 2.

The marking rubric shown in Table 2 is merely an example and should be modified accordinglyto reflect any realistic difficulty in achieving the objectives stated in each cell of Table 1. Therefore,if a teaching team decides that row 6, ‘create’ (Table 1), should consist of a higher componentof the final grade, simply because it is felt that the objectives in this category are much harder toachieve, then the appropriate rubric should be designed to reflect this.

Discussion

It is envisaged that the specific taxonomy table presented here would evolve, with further consid-erations and iterations, and thus contribute as a useful template of prospective learning outcomesfor the FYP. The value of the taxonomy table in the present paper is in the new content in eachcell of the table, derived from an integration of the requirements of the cognitive process, the

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Table 1. Taxonomy table

(1) Remember (2) Understand (3) Apply (4) Analyse (5) Evaluate (6) Create

A. Factual Able to showknowledge ofthe literature, theimportant authors,related terminologyand key findings

Shows ability toclassify, summariseand explain thebasic informationfrom the literaturereview.

Has the basicskills to carryout establishedprocedures orexperiments.

Verifies data are good.(e.g. checks forerrors)

Interprets new data,together withrelevant data thathave been publishedbefore.

New knowledge isobtained fromthe findings usingestablished methodsof interpretation.

B. Conceptual Shows knowledge ofspecific informationon relevant theories,models, structures,principles, etc.

Able to infer theinter-topicalrelationshipsrelevant to theproject. ‘Sees thebig picture’.

Demonstrates theability to puttogether differentprocedures orexperiments inrelation to theresearch question.

Able to differentiatedata into relevantgroups andmajor and minorcomponents.

Able to articulatethe validity orinappropriatenessof the data in termsof addressing theresearch question.

Able to add a newlevel or dimensionof interpretationto provide newknowledge.

C. Procedural Describes clearly thepreviously usedtechniques, meth-ods, algorithmsand/or equationsrelevant to theproject.

Able to competentlycritique theprevious methodsand techniques usedand identify gaps incurrent knowledge.

Shows ability toproficiently carryout the differentexperiments, givingconsiderationsto safety issuesand statisticalsignificance.

Able to performstatistical analysisand organise dataappropriatelyinto spreadsheets,graphs.

Shows clearunderstandingof statisticalsignificance, powerand whether or notto accept or rejectthe hypothesis.

Provides a new‘revelation’ ora meaningfulinterpretationthrough the useof clever writingor presentationtechniques,e.g. analogies,illustrations, etc.

D. Metacognitive Able to list the keyissues from theliterature reviewin order to helpdefine the problemstatement orresearch question.

Able to discern thecritical issuesand synthesisean exemplaryproblem statementor research questionfor the project.

Exhibits a highlevel of skilland good safetypractice in carryingout complexexperiments andproducing highquality data.

Shows ability toreduce complexdata into valid andeasy-to-understandcharts, diagrams orexplanations.

Demonstrates anexcellent ability toself-critique, ableto list limitationsof the data andexperiment designand make newrecommendations.

Able to show akeen sense ofwhat knowledgeis known vs.unknown, and whythe nature of theknowledge is such.

Note: The column headers (1–6) represent the cognitive process and rows (A–D) are the knowledge aspects.

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Table 2. Marking rubric (the total score (maximum 24) may becalibrated against a typical 0–100 marks scale)

Number of cognitive skillsKnowledge aspect (enter an integer from 0–6) Remarks

FactualConceptualProceduralMetacognitive

Note: The remarks section allows the assessor to indicate how well the stu-dent expressed each of the cognitive skills; thus, for the purpose of the scoringmechanism, providing a means to improve the resolution of the grading.

knowledge dimensions and, a third dimension, that of the attributes and competencies expectedof a graduating engineer. The 24 learning outcomes described here are specifically for a FYP thatis largely a research project. The present author’s department is one where students experience twocapstone projects in their final year, one on design and one involving a purely research project.It is the latter type for which the taxonomy table presented here is most suited. Likewise, thetaxonomy table may also be modified appropriately to serve the requirements of a FYP coursethat is mostly for design learning.

However, in its use as a list of learning outcomes for a research FYP course, the taxonomytable could aspire to provide the indicators for assessing a notoriously difficult attribute, that ofcreativity. The question of whether creativity could be taught in the engineering curriculum isan important one. The answer relies heavily on how well the culture of engineering education isable to transform itself out of its current narrow view of creativity and outdated learning theories(Tornkvist 1998). The revised Bloom’s taxonomy and its associated taxonomy table attempts tocover both breadth and depth of cognitive and knowledge-related issues and may thus be an idealframework for the design of specific learning outcomes to help ‘teach’ creativity to engineers. Inthe taxonomy table presented in this paper (Table 1), the learning outcomes listed in the ‘create’column provides, for both the teacher and the student, indicators of what would be involved in thecognitive process for expressing creativity. Further, the ‘metacognitive’ domain also contributesto the creative cognitive process by instigating activities of reviewing and reflection, which arealso critical to developing creativity in the student (Blicblau and Steiner 1998).

The proposed taxonomy table can improve the facilitation of assessment. By careful consider-ation of both the cognitive processes and the knowledge dimensions, the framework allows theconstruction of specific ‘language’ defining the necessary learning outcomes. It is the importanceof such language, in which the assessment criteria are embedded, that a better shared understand-ing may be achieved between teachers, students and other stakeholders (Woolf 2004). In additionto assessment, each cell of the taxonomy table, like a learning outcome, is also a checkpoint forthe level of student learning. For example, cells 4C and 4D (refer to Table 1) cover statistical dataanalysis and presentation, with the latter calling for the student to take the activity to a new levelof interpretation and illustration. The extent to which the student is able to perform this activitycompetently is therefore not only an objective for the student, but also an assessment criterion forthe grader. The rubric (Table 2) allows the grader to determine achievement using very clear andquantifiable metrics based on the extent to which the learning outcomes have been successfullyattained.

Conclusion

This paper presents a first-cut taxonomy table of learning outcomes and assessment criteria tobe applied to a FYP course. The next step is to carry out a detailed study on how this table may

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facilitate a better learning experience for students doing their FYP, and assessors grading suchprojects, in the author’s department. It is envisaged that the present taxonomy table, with itspurposefully structured learning outcomes, will contribute positively to not only FYP courses butalso to the quality of many research projects, where, more often than not, such guidelines are notavailable or remain ambiguous.

Acknowledgements

The author wishes to acknowledge Barbara Kensington-Miller and Matiu Ratima for valuable feedback during the writingof this paper.

References

Anderson, L.W. and Krathwohl, D.R., eds., 2001. A taxonomy for Learning, teaching, and assessing: A revision of Bloom’staxonomy of educational objectives. New York: Addison Wesley Longman.

Blicblau, A. and Steiner,J.,1998. Fostering creativity through engineering projects. European Journal of EngineeringEducation, 23(1), 55–65.

Bloom, B.S.,et al., 1956. Taxonomy of educational objectives: Handbook I: Cognitive domain. New York: David McKay.Bovea, M.D. and Gallardo, A., 2006. Work placements and the final year project: a joint experience in the industrial

engineering degree. International Journal of Engineering Education, 22 (6), 1319–1324.Jenkins, S.R., et al., 2002. Capstone course in an integrated engineering curriculum. Journal of Professional Issues in

Engineering Education and Practice, April, 75–82.Jonassen, D.H., 1997. Instructional design models for well-structured and ill-structured problem-solving learning

outcomes. Educational Technology Research and Development, 45(1), 65–94.Kentish, S.E. and Shallcross, D.C., 2006. An international comparison of final-year design project curricula. Chemical

Engineering Education, 40(4), 275–280.Ku, H. and Goh, S., 2010. Final year engineering projects in Australia and Europe. European Journal of Engineering

Education, 35 (2), 161–173.Lee, L.S. and Lai, C.C., 2007. Capstone course assessment approaches and their issues in the engineering programs in

Taiwan. International conference on engineering education & research, 2–7 December 2007, Melbourne, Australia.NEER 2007. Available from: http://eric.ed.gov/PDFS/ED507760.pdf [Accessed 25 January 2011].

Teo, C.Y. and Ho, D.J., 1998. A systematic approach to the implementation of FYP in an electrical engineeringundergraduate course. IEEE Transactions on Education, 41, 25–30.

Tornkvist, S., 1998. Creativity: Can it be taught? The case of engineering education. European Journal of EngineeringEducation, 23 (1), 5–8.

Vitner, G. and Rozenes, S., 2009. Final-year projects as a major element in the IE curriculum. European Journal ofEngineering Education, 34, (6), 587–592.

Willey, K., Jarman, R. and Gardner, A.P., 2008. Redeveloping capstone projects in UTS Faculty of Engineering: Hasintegrating Engineers Australia competencies into the process improved learning? In: P. Howard, ed. Proceedings ofthe 2008 AaeE conference, December 2008. Yeppoon, Queensland:Engineers Australia, 1–6.

Woolf, H., 2004. Assessment criteria: reflections on current practices. Assessment & Evaluation in Higher Education, 29(4), 479–493.

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Appendix A: The Cognitive Process Dimension

(From Anderson and Krathwohl 2001)

Categories

& Cognitive Alternative

Processes Names Definitions and Examples

1. remember—Retrieve relevant knowledge from long-term memory

1.1 recognizing Identifying Locating knowledge in Long-term memory that is consistent withpresented material (e.g., Recognize the dates of important events inU.S. history)

1.2 recalling Retrieving Retrieving relevant knowledge from long-term memory (e.g., Recallthe dates of important events in U.S. history)

2. understand—Construct meaning from instructional messages, including oral, written, and graphic communication

2.1 interpreting Clarifying,paraphrasing,representing,translating

Changing from one form of representation (e.g., numerical) to another(e.g., verbal) (e.g. Paraphrase important speeches and documents)

2.2 exemplifying Illustrating,instantiating

Finding a specific example or illustration of a concept or principle (e.g.,Give examples of various artistic painting styles)

2.3 classifying Categorizing,subsuming

Determining that something belongs to a category (e.g., conceptor principle) (e.g., Classify observed or described cases of mentaldisorders)

2.4 summarizing Abstracting,generalizing

Abstracting a general theme or major point(s) (e.g., Write a shortsummary of the events portrayed on a videotape)

2.5 inferring Concluding,extrapolating,interpolating,predicting

Drawing a logical conclusion from presented information (e.g.,In learning a foreign language, infer grammatical principles fromexamples)

2.6 comparing Contrasting,mapping,matching

Detecting correspondences between two ideas, objects, and the like(e.g., Compare historical events to contemporary situations)

2.7 explaining Constructingmodels

Constructing a cause-and-effect model of a system (e.g., Explain thecauses of important 18th-century events in France)

3. apply—Carry out or use a procedure in a given situation

3.1 executing Carrying out Applying a procedure to a familiar task (e.g., Divide one whole numberby another whole number, both with multiple digits)

3.2 implementing Using Applying a procedure to an unfamiliar task (e.g., Use Newton’s SecondLaw in situations in which it is appropriate)

Note: Anderson & Krathwohl, A TAXONOMY FOR LEARNING, TEACHING AND ASSESSING, © 2001 Addison Wesley Longman,Inc. Reproduced by permission of Pearson Education, Inc.

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Appendix B: The major types and subtypes of the Knowledge Dimension

(From Anderson and Krathwohl 2001)

Major Types and Subtypes Examples

A. Factual knowledge—The basic elements students must know to be acquainted with a disciplinie or solve

problems in it

Aa. Knowledge of terminology Technical vocabulary, musical symbols

Ab. Knowledge of specific details andelements

Major natural resources, reliable sources of information

B. Conceptual Knowledge—The interrelationships among the basic elements within a larger structure that enable

them to function together

Ba. Knowledge of classifications andcategories

Periods of geological time, forms of business ownership

Bb. Knowledge of principles andgeneralizations

Pythagorean theorem, law of supply and demand

Bc. Knowledge of theories, models,and structures

Theory of evolution, structure of Congress

C. Procedural Knowledge—How to do something, methods of inquiry, and criteria for using skills, algorithms,

techniques, and methods

Ca. Knowledge of subject-specific skills andalgorithms

Skills used in painting with watercolors, whole-numberdivision algorithm

Cb. Knowledge of subject-specific techniquesand methods

Interviewing techniques, scientific method

Cc. Knowledge of criteria for determiningwhen to use appropriate procedures

Criteria used to determine when to apply a procedureinvolving Newton’s second law, criteria used to judgethe feasibility of using a particular method to estimatebusiness costs

D. Metacognitive Knowledge—Knowledge of cognition in general as well as awareness and knowledge of

one’s own cognition

Da. Strategic knowledge Knowledge of outlining as a means of capturing thestructure of a unit of subject matter in a text-book,knowledge of the use of heuristics

Db. Knowledge about cognitive tasks,including appropriate contextualand conditional knowledge

Knowledge of the types of tests particular teachersadminister, knowledge of the cognitive demands ofdifferent tasks

Dc. Self-knowledge Knowledge that critiquing essays is a personal strength,whereas writing essays is a personal weakness;awareness of one’s own knowledge level

Note: Anderson & Krathwohl, A TAXONOMY FOR LEARNING, TEACHING AND ASSESSING, © 2001 Addison Wesley Longman,Inc. Reproduced by permission of Pearson Education, Inc.

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Appendix C: List of graduate competencies and attributes from Institution of Professional Engineers of New Zealand (IPENZ)(Available from the IPENZ website.)

Professional Engineer Engineering Technologist Engineering Technician

Attribute (Washington Accord) (Sydney Accord) (Dublin Accord) Explanatory notes

Technical Foundations

1 Academic Education Educational depth andbreadth

Four year BE degree Three year BEng Techdegree

Two year DipEng (Level6 on NQF)

2. Knowledge ofEngineering Sciences

Understands and canapply the mathematicaland engineering sciencesrelevant to;

One or more of the broad,general engineering disciplinese.g. mechanical, civil orelectrical

One or more practiceareas within a specificengineering disciplinee.g. construction,manufacturing or roading

One or more specialisedfields of engineeringactivity e.g. aircraftmaintenance, civilcontracting or HVAC

3. Analysis and ProblemSolving

Able to formulate andsolve models whichpredict the behaviour ofpart or all of:

Complex engineering systemsusing first principles of thefundamental engineeringsciences and mathematics

Broadly defined engi-neering systems usinganalytical tools appropri-ate to their discipline orarea of specialisation

Well defined engineeringsystems using codifiedmethods of analysisspecific to their field ofengineering activity

4. Design and Synthesis Able to synthesise anddemonstrate the suitabilityand efficacy of solutionsto part or all of:

Complex engineering problems Broadly definedengineering problems

Well defined engineeringproblems

5. Investigation andResearch

Able to recognise whenfurther information isneeded and be able to findit by;

Identifying, evaluating anddrawing conclusions fromall pertinent sources ofinformation. Designing andcarrying out experiments

Locating, searching andselecting relevant datafrom codes, data bases andliterature. Designing andcarrying out experiments

Locating and searchingrelevant codes andcatalogues. Carrying outstandard tests

6. Risk Management Understands the acceptedmethods of dealing withuncertainty (such assafety factors) and thelimitations of applicabilityof methods of design andanalysis by being able to:

Identify, evaluate and managephysical risks in complexengineering problems

Identify, evaluate andmanage physical risksin broadly definedengineering problems

identify, evaluate andmanage physical risks inwell defined engineeringproblems

Confines risk managementto the management ofphysical risk. Risks to bedealt with include bothknown and unforeseenrisks

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7. Team work Function effectively in ateam by being able to:

Work cooperatively with thecapability to lead or manage ateam

Work cooperativelyand understand teamdynamics

Work cooperativelyand understand teamdynamics

8. Communication Communicate clearly bybeing able to:

Comprehend and produceeffective reports and designdocumentation, summariseinformation, make effective oralpresentations and to give andreceive clear oral instructions

Comprehend and produceeffective reports anddesign documentation,make effective oralpresentations and to giveand receive clear oralinstructions

Interpret reports anddesign documentation;effectively document theirown work; and give andreceive clear instructions

Supporting Knowledge

9. The Engineer and Society Be aware of the roleof engineers and theirresponsibility to societyby:

Demonstrating understandingof the general responsibilitiesof a professional engineer

Demonstrating under-standing of the generalresponsibilities of anengineering technologist

Demonstrating under-standing of the generalresponsibilities of anengineering technician

There is no level statementin these definitionsexcept that inherent inthe word ‘professional’,‘technician’ etc becausethe extent of responsibilityrequired is defined by thework being done

10. Management and financial Understands, selects andapplies:

appropriate project and businessmanagement principles andtools to complex engineeringproblems

appropriate projectmanagement and costingmethods to broadlydefined engineeringproblems

appropriate projectmanagement and costingmethods to well definedengineering problems

11. Practical Knowledge Demonstrates competencyin the practical art ofengineering in their areaof specialisation by:

Being able to show in design anunderstanding of the practicalmethods for the constructionand maintenance of engineeringproducts and being able to usemodern calculation and designtools competently for complexengineering problems

Being able to interpretthe general designs ofothers to provide detailed,practical designs forconstruction/productionand/or managementof construction ormaintenance and beingable to apply appropriatetechniques, resourcesand current engineeringtools for broadly definedengineering problems

Being able to applyappropriate techniques,resources and currentengineering tools towell-defined engineeringactivities with anawareness of theirlimitations

In the case of softwareengineering ’construction’does not necessarily meanphysical construction

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Definitions:Complex engineering problems means engineering problems which cannot be resolved without in-depth engineeringknowledge and having some or all ofthe following characteristics:

• Involve wide-ranging or conflicting technical, engineering and other issues• Have no obvious solution and require originality in analysis• Involve infrequently encountered issues• Are outside problems encompassed by standards and codes of practice for professional engineering• Involve diverse groups of stakeholders with widely varying needs• Have significant consequences in a range of contexts

Broadly defined engineering problems means engineering problems having some or all of the following characteristics:

• Can be solved by application of well-proven analysis techniques• Are parts of, or systems within complex engineering problems• Involve a variety of factors which may impose conflicting constraints• Belong to families of familiar problems which are solved in well-accepted ways• May be partially outside those encompassed by standards or codes of practice• Involve several groups of stakeholders with differing and occasionally conflicting needs• Have consequences which are important locally, but may extend more widely

Well defined engineering problems means engineering problems having some or all of the following characteristics:

• Can be solved in standardised ways• Are discrete components of engineering systems• Involve several issues, but with few of these exerting conflicting constraints• Are frequently encountered and thus familiar to most practitioners in the practice area• Are encompassed by standards and/or documented codes of practice• Involve a limited range of stakeholders with differing needs• Have consequences which are locally important and not far-reaching• Can be resolved using limited theoretical knowledge but normally requires extensive practical knowledge

General responsibilities of an engineer include:

• Social responsibilities including ethics, health and safety and other legislation• Cultural responsibilities including, in New Zealand, the Treaty of Waitangi• Environmental responsibilities including the need for sustainable development and design and legislative responsibilities• Life long learning

About the author

Ashvin Thambyah obtained his PhD from the National University of Singapore and is currently a Senior Lecturer at theFaculty of Engineering, The University of Auckland. He teaches fluid mechanics and mechanics of materials and hisresearch area is in muscuoloskeletal tissue mechanics.

Ashvin recently completed a Postgraduate Certificate in Academic Practice with the University of Auckland.

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