Transdisciplinary Design Education for Engineering Undergraduates: Mapping of Bloom’s Taxonomy Cognitive Domain Across Design Stages

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Transdisciplinary Design Education Undergraduates: 28th CIRP Design Conference, for May Engineering 2018, Nantes, France Transdisciplinary Design Education for Engineering Undergraduates: Mapping of Cognitive Domain Across Design Mapping of Bloom’s Bloom’stoTaxonomy Taxonomy Cognitive Domain Across architecture Design Stages Stages A new methodology analyze the functional and physical of Alyona Mehwish Butt, Ahmed Jawadfamily Qureshi*identification existing products forSharunova, an assembly oriented product Alyona Sharunova, Mehwish Butt, Ahmed Jawad Qureshi* Department of Mechanical Engineering, University of Alberta, Edmonton T6G 1H9, Canada Department of Mechanical Engineering, University of Alberta, Edmonton T6G 1H9, Canada

Paul Stief *, Jean-Yves Dantan, Alain Etienne, Ali Siadat

* Corresponding author. Tel.: +1-780-492-3609. E-mail address: [email protected]. * Corresponding Tel.:Supérieure +1-780-492-3609. address: Écoleauthor. Nationale d’Arts etE-mail Métiers, Arts et [email protected]. Métiers ParisTech, LCFC EA 4495, 4 Rue Augustin Fresnel, Metz 57078, France

* Corresponding author. Tel.: +33 3 87 37 54 30; E-mail address: [email protected]

Abstract Abstract

This the first first in in aa series series from from the the study study entitled entitled Transdisciplinary Transdisciplinary Design Design Education Education for for Engineering Engineering Undergraduates, Undergraduates, whose whose purpose purpose is is This paper paper is is the Abstract to review the current engineering design education at the University of Alberta and develop a first-year transdisciplinary design course, accounting to review the current engineering design education at the University of Alberta and develop a first-year transdisciplinary design course, accounting for students’ students’ cognitive cognitive development. development. This This paper presents presents the the results results of of aa cognitive cognitive game, game, designed to the design thinking designed to assess assess the thinking of of engineering engineering Infor today’s business environment, the trend paper towards more product variety andCognitive customization is unbroken. Due to design this development, the needand of professors. The results show the differences between cognitive levels of the Domain of Bloom’s Taxonomy and their distribution professors. The results show the differences between cognitive levels of the products Cognitiveand Domain of Bloom’s Taxonomy and their distribution and agile and reconfigurable production systems emerged to cope with various product families. To design and optimize production application at design stages. application at different different designthe stages. systems as well as to choose optimal product matches, product analysis methods are needed. Indeed, most of the known methods aim to © 2017 The Authors. Published by Elsevier B.V. © 2018 The Authors. Published by Elsevier Ltd. This islevel. an open accessproduct article under the however, CC BY-NC-ND license 2017a product or one product family B.V. analyze on the physical Different families, may differ largely in terms of the number and Peer-review under responsibility of the scientific committee of the 28th CIRP Design Conference 2018. (http://creativecommons.org/licenses/by-nc-nd/3.0/) Peer-review under responsibility of the scientific committee of the 28th CIRP Design Conference 2018.family combinations for the production nature of components. This fact impedes an efficient comparison and choice of appropriate product Peer-review responsibility of the scientific committee of the 28th Design 2018. system. A newunder methodology is proposed to analyze existing products in CIRP view of their Conference functional and physical architecture. The aim is to cluster Keywords: Engineering Design Education, Transdisciplinary Design, Engineering Design Process, Bloom's Taxonomy. Keywords: Engineering Design oriented Education, Transdisciplinary Design, Engineering Designassembly Process, lines Bloom's these products in new assembly product families for the optimization of existing and Taxonomy. the creation of future reconfigurable assembly systems. Based on Datum Flow Chain, the physical structure of the products is analyzed. Functional subassemblies are identified, and a functional analysis is performed. Moreover, a hybrid functional and physical architecture graph (HyFPAG) is the output which depicts the similarity between product families by providing design support to both,methodology, production system planners andPsychology. product designers. illustrative and These An elements are 1. Introduction methodology, and Cognitive Cognitive Psychology. elements 1. Introduction example of a nail-clipper is used to explain the proposed methodology. Anincorporated industrial caseinstudy on two product families ofThese steering columnsare of an Educational Framework for Undergraduate incorporated in an Educational Framework for Undergraduate thyssenkrupp Presta France is then carried out to give a first industrial evaluation of the proposed approach. Engineering Design Curriculum Curriculum Development, Development, which which we The shift shift of of contemporary contemporary product product design from from being being monomonoEngineering Design we The © 2017 The Authors. Published by Elsevierdesign B.V. recently proposed [3]. This framework serves as a guide for our our disciplinary to transdisciplinary as well as a need for wellrecently proposed [3]. This framework serves as a guide for disciplinary to transdisciplinary as well as a need for wellPeer-review under responsibility of the scientific committee of the 28th CIRP Design Conference 2018.

trained engineering engineering design design specialists specialists with with interdisciplinary interdisciplinary trained competencies affects the job market, leading to stronger stronger Keywords: Assembly; Designthe method; identification competencies affects jobFamily market, leading to competition among potential employees. Transdisciplinarity competition among potential employees. Transdisciplinarity is is defined defined by by Ertas Ertas et et al. al. as as “the “the integrated integrated use use of of the the tools, tools, techniques, as it it is is techniques, and and methods methods from from various various disciplines” disciplines” [1] [1] as with what is “simultaneously between disciplines, 1.concerned Introduction concerned with what is “simultaneously between disciplines, across different different disciplines, disciplines, and and beyond beyond all all disciplines” disciplines” [2]. [2]. across This in educational Duenew to industrial the fast change development the domain of This new industrial change in turn turn inrequires requires educational institutions preparing their students for communication andsteps an in trend digitization and institutions to to take take steps inongoing preparing their of students for the the new new industrial, and challenges by digitalization, manufacturing enterprises are facing important industrial, professional professional and life-long life-long challenges by developing developing new educational pedagogy, methodologies and approaches. challenges in today’s market environments: a continuing new educational pedagogy, methodologies and approaches. This is the series the entitled This paper paper is reduction the first first in in series from from the study study entitled tendency towards of aaproduct development times and Transdisciplinary Design Education for Engineering Transdisciplinary Design In Education foris anEngineering shortened product lifecycles. addition, there increasing Undergraduates. This aims to review the current Undergraduates. This study study review demand of customization, beingaims at thetosame time the in a current global engineering design education at the University of Alberta to engineering with design education all at the Alberta to competition competitors overUniversity the world.ofThis trend, establish aa common understanding of the engineering design establish common understanding of the engineering design which is inducing the development from macro to micro processes taught each and develop aa first-year processesresults taughtinin in diminished each department department and due develop first-year markets, lotThe sizes to augmenting transdisciplinary design course. study incorporates the transdisciplinary design course. The study incorporates the product varieties (high-volume to low-volume production) [1]. results of industrial and educational research, teaching results of industrial and educational research, teaching To cope with this augmenting variety as well as to be able to identify possible optimization potentials in the existing 2212-8271 ©system, 2017 The Authors. Publishedtobyhave Elsevier B.V. knowledge production is important a precise 2212-8271 © 2017 The it Authors. Published by Elsevier B.V.

study and and addresses addresses the the following following concerns: concerns: 1. 1. What What approach approach study can be taken to better prepare our graduates for successful can be taken to better prepare our graduates for successful entrance and and performance performance in in the the contemporary contemporary workplace? workplace? 2. 2. entrance What methodology can be used to develop an educational What methodology can be used to develop an educational curriculum for for teaching teaching transdisciplinary transdisciplinary engineering engineering design design curriculum andthe developing interdisciplinary competencies in students? students? of product range and characteristics manufactured and/or and developing interdisciplinary competencies in assembled in this system. In this context, the main challenge in 1.1. Engineering Engineering design is in industry industry and education modelling and analysis now not and onlyeducation to cope with single 1.1. design in products, a limited product range or existing product families, Due toto tobe the the transdisciplinary nature products of contemporary contemporary but also able to analyze and to compare to define Due transdisciplinary nature of engineering practice, a collaboration of specialists from new product families. It can be observed that classical engineering practice, a collaboration of specialistsexisting from different engineering disciplines is required to develop efficient product are regrouped inisfunction or features. differentfamilies engineering disciplines requiredoftoclients develop efficient solutions assembly to interdisciplinary interdisciplinary problems of integrated integrated product However, oriented product families are hardlyproduct to find. solutions to problems of design [2,4]. Consider the example of an automobile, which is On the product family products differ mainlywhich in two design [2,4]. Consider the level, example of an automobile, is a transdisciplinary product designed by engineers from main characteristics: (i) the number of components and (ii) the a transdisciplinary product designed by engineers from mechanical, electrical, chemical and and otherelectronical). engineering mechanical, electrical, chemical other engineering type of components (e.g. mechanical, electrical, disciplines and and industrial industrial designers. designers. To To create the the most most optimal optimal disciplines Classical methodologies considering create mainly single products design these experts need to have a “shared understanding” of design these already experts need to have a “shared understanding” of or solitary, existing product families analyze the the design process and communicate effectively as the lack of the design process communicate effectively aslevel) the lack of product structure onand a physical level (components which causes difficulties regarding an efficient definition and comparison of different product families. Addressing this

Peer-review under responsibility of the scientific committee of the 28th CIRP Design Conference 2018. Peer-review under responsibility of the scientific committee of the 28th CIRP Design Conference 2018. 2212-8271 © 2018 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/) 2212-8271 © 2017 The Authors. Published by Elsevier B.V. Peer-review under responsibility of scientific the scientific committee theCIRP 28thDesign CIRP Conference Design Conference Peer-review under responsibility of the committee of the of 28th 2018. 2018. 10.1016/j.procir.2018.02.042

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understanding may cause iterations in the design process or result in project failure [5]. Several empirical studies on the transdisciplinary engineering design process in industry revealed core similarities in the design processes between engineering disciplines. These studies showed that engineers in each domain perform similar steps when designing the product but address them from different perspectives. For example, Gericke and Blessing [6,7] compared several design process models from 9 engineering disciplines and discovered this set of common design stages: establishing a need, analysis of a task, conceptual design, embodiment design, detailed design, implementation, use and closeout. In an empirical study with industrial designers, Qureshi et al. [2] discovered shared elements of current industrial design practice and showed that engineering designers distinguish between different design stages as well as that the design process has an iterative nature. Another study on the stages of product lifecycle [4] supported these findings by showing that product lifecycle stages are similar across engineering domains. However, despite the presence of these commonalities in engineering design processes across disciplines, the engineering design curriculum remains focused on teaching discipline specific design practices. As a result, engineering graduates have a limited common basis to relate to the transdisciplinary engineering design process, causing a needless difficulty for students entering industry. Regarding interdisciplinary competencies, a series of empirical studies in industry comprising 17 organizations from 14 different countries on 4 continents, showed that experienced design professionals recognize and work with fundamental cognitive, creative and logical processes in engineering design [2,7]. However, recent research pointed out concerns that contemporary employers raise when looking for new employees: recent graduates lack professional skills such as communication, teamwork, creativity, and problem solving [810]. These studies suggest that development of both technical and general skills should be given equal attention, which in turn depends on students’ cognitive development. So far, the majority of studies on improving engineering education have been discipline specific, excluding the cross-analysis of all engineering domains and covering only one or two cognitive attributes but not the whole cognitive domain. Furthermore, limited research has been carried out on developing engineering curriculums which takes into account the transdisciplinary nature of the engineering design process and focuses on the development of interdisciplinary competencies. This motivated us to carry out a study which would establish a common understanding of the engineering design process between different engineering disciplines and consider the cognitive development of students.

as lower levels of thinking and the last three are referred to as higher levels of thinking [14]. The learning processes corresponding to each level can be briefly summarized as: 1. Knowledge - an ability to recall and remember information; 2. Comprehension – an ability to understand and explain concepts; 3. Application – an ability to use information in a new setting; 4. Analysis – an ability to analyze and distinguish parts; 5. Synthesis – an ability put things together and develop a new product; and 6. Evaluation – an ability to judge and justify a decision or point of view. Given its unique educational features and relation to the cognitive abilities, Bloom’s Taxonomy can be applied in any discipline. Multiple studies attempted to integrate and apply Bloom’s Taxonomy to the curriculum design to enhance engineering courses or evaluate students’ learning [15,16]. In many cases Bloom’s Taxonomy is applied to the development of course learning outcomes. The CDIO Initiative, for example, which is implemented by more than 100 engineering schools worldwide aiming to enhance engineering education and maintain it in line with industrial demands, implements and recommends Bloom’s Taxonomy for the curriculum and learning outcome development [17]. The reason why we use Bloom’s Taxonomy in our study is because it is a powerful tool for teaching as it provides a common language to compare and discuss two different subject areas and helps the understanding how these subjects overlap or can deliver conceptual and practical knowledge concurrently [3]. It also helps to assess the cognitive aspects of the design activities as the application of Bloom’s Taxonomy in education is strongly linked to the development of both high and low levels of thinking, problem solving, creative and critical thinking skills, which are all a part of the cognitive design activity. This makes this taxonomy a perfect tool for the development of a transdisciplinary design curriculum with emphasis on cognitive development. Since engineering design education is mostly based on teaching students the basics of engineering and then combining this knowledge in design projects at later stages, a successful synthesis of knowledge from first-year to last year courses is essential and can be achieved through application of Bloom’s Taxonomy as a common language or unifying foundation. In our case we aim to develop a first-year engineering design course that incorporates Bloom’s taxonomy and knowledge from other engineering disciplines in order to be applicable to all departments’ curriculums and facilitate students’ success in engineering design throughout the later years of their undergraduate studies. In our study we also use Bloom’s Taxonomy as a tool to assess how engineering professors think about the design process which reflects their teaching approaches.

1.2. Bloom’s Taxonomy in engineering education

1.3. Research hypotheses

Bloom’s Taxonomy, developed by Benjamin Bloom and later revised by his students and followers, is a set of taxonomies in three domains of learning, namely the cognitive, affective and psychomotor [11,12]. In this study we focus on the Cognitive Domain which involves conscious intellectual activity [13]. It consists of 6 cognitive levels of complexity: Knowledge, Comprehension, Application, Analysis, Synthesis and Evaluation. The first three levels are generally referred to

As mentioned above, we aim to establish a common understanding of the universal processes in engineering design by looking at similarities between departments. In order to do so, we need to understand how engineering professors think and teach the design process and for that reason we developed a tool based on Bloom’s Taxonomy – the cognitive game. This game has three purposes: 1. To assess and collect the names of design stages which are used in different engineering



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disciplines; 2. To identify the amount and variety of design activities performed at each stage; and 3. To build a base of nouns for an engineering design ontology to establish the common engineering design process. This game links the Bloom’s Taxonomy to the engineering design process. In this paper we explore the second purpose of this game, in particular, the distribution and application of the Cognitive Domain of Bloom’s Taxonomy across different engineering design stages. We hypothesize that 1. the cognitive load, in particular the amount of design activities necessary to carry the product design, differs from stage to stage and gradually shifts from lower to higher levels of thinking along the design process, 2. different cognitive levels are significant at different stages, and 3. that the majority of design activities happen at the beginning of the design process during the first 3 stages. 2. Methods 2.1. Participants 71 professors from the Faculty of Engineering at the University of Alberta who have taught design courses since 2014 were contacted via emails. Of those contacted, 34 of them agreed to participate, out of which 3 professors were females and the rest were males. The sample included 6 representatives of academic leadership from different departments, i.e. Deans and Associate Chairs, who are involved in planning and organizing the undergraduate curriculum, 4 out of which did not teach a design course before but were invited to provide their opinion on teaching design within departments. Table 1 shows the number of participants from each department. Before the data collection, 5 pilot trials were conducted with the randomly selected participants and project collaborators, whose data was excluded from the analysis. Participants were invited for a 1-hour interview, where they filled out a short questionnaire about the course they teach and were asked to describe the design method and process they use for teaching students. After that all participants were asked to play our cognitive game and provide a feedback about how they did in the game. Table 1. Number of participants selected from each department. The presence of academic leadership representatives is shown with *. Department Number of people Mechanical Engineering* 13 Chemical and Materials Engineering* 8 Electrical and Computer Engineering* 7 Civil and Environmental Engineering 6 Total 34

2.2. Design courses Canadian Engineering Accreditation Board (CEAB), a regulatory body responsible for accreditation of all engineering programs in Canada, distinguishes engineering design courses from engineering science courses. According to CEAB, engineering design “integrates mathematics, natural sciences, engineering sciences and complementary studies in order to develop elements, systems, and processes to meet specific needs” [18]. CEAB distinguishes between different engineering design courses based on the course content. We divided design courses from non-relevant to level 3, which

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signifies that the course of design relevance 3 has an extensive design component in it and non-relevant means no design component. The total of 46 design courses of design relevance 3 as per CEAB regulations from year 2016 were identified at the Faculty of Engineering, out of which 23 design courses were covered in this study. Only professors who teach courses of design relevance 3 and representatives of academic leadership were invited for an interview. Some courses were taught by two or more different professors, which is reflected in the higher number of participants than the number of courses covered in the study. Table 2 shows the disciplines and number of design courses covered out of total number of design courses in each department, noting the number of repeated courses. There were four 2nd year courses, five 3rd year courses, and twenty-one 4th year courses, out of which 7 were the capstone design projects. A second year CAD drafting course, which had a design relevance 1, was included as an exception because it is a co-requisite of the 2nd year current introductory mechanical design course. The majority of departments had 3rd and 4th year courses, except for the Department of Mechanical Engineering which has 2nd, 3rd and 4th year design courses. Table 2. Number of design courses covered in the study from each discipline out of total design courses in each department. The number in brackets shows extra time when some courses are taught by more than one professor. Course Number of design Total number of disciplines courses covered design courses Electrical 4 (+1) 15 Computer 1 2 Chemical 2 (+1) 2 Materials 5 7 Civil 3 8 Mining 2 3 Petroleum 1 3 Mechanical 5 (+5) 6 Total 23 46

2.3 Cognitive game The cognitive game was developed based on action verbs from the Cognitive Domain of the original Bloom’s Taxonomy. The game had 3 steps: 1. All participants were given a game board with 6 general design stages placed along an arrow representing the design process and 6 corresponding empty columns. The design stages were suggested based on the Ulrich and Eppinger’s stages [19]. The design stages used are Planning (PL), Concept Development (CD), System Level Design (SLD), Detailed Design (DD), Implementation and Testing (IT), and Production (PR). All participants were asked to rename the proposed stages as per their discipline or they could choose to use the stages we provided. 2. All participants were given 42 randomly mixed stickers with 7 unique verbs from each of the cognitive levels as shown in Table 3 [20]. They were asked to fill up all stickers with a noun while thinking about the design process from their engineering discipline, forming the design activities. For example, to define “problem”, to list “requirements” or “specifications”. 3. Participants had to place all 42 stickers into 6 columns with the corresponding design stages based on what they think is the best place for those activities to happen in the design process. While placing the stickers into the columns, all

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participants were asked to think about the design process in their discipline. Participants were told to place each sticker in one column only and not into two or more. There was no time limit for this activity but the time spent on the game ranged from 15 to 40 mins. Table 3. The Action verbs of the Cognitive Domain of Bloom’s Taxonomy. Cognitive Domain Action Verbs Knowledge (Kn) Define, Describe, Identify, List, Name, Order, Recognize Comprehension (Cm) Application (Ap)

Classify, Discuss, Distinguish, Estimate, Extend, Indicate, Review

Knowledge 90 60 30 0

PL

CD

SLD

DD

IT

PR

Fig. 2. Distribution of Knowledge action verbs each design stage Comprehension 90

Apply, Choose, Compute, Illustrate, Modify, Practice, Solve

60

Analysis (An)

Analyse, Calculate, Compare, Criticize, Infer, Model, Test

Synthesis (Sn)

Combine, Create, Design, Develop, Generate, Prepare, Synthesize

Evaluation (Ev)

Conclude, Defend, Evaluate, Explain, Justify, Interpret, Predict

30 0

PL

CD

SLD

DD

IT

PR

Fig. 3. Distribution of Comprehension action verbs at each design stage

Application

3. Results

90

The number of stickers with action verbs from the Cognitive Domain were used to determine the number of design tasks at each design stage. There were total of 1427 stickers placed out of 1428 as one sticker from Application level was not placed by one participant by mistake. The data was analyzed using Microsoft Office Excel 2016 and IBM SPSS Statistic 24. Table 4 shows the distribution of verbs at each design stage and each cognitive level. Table 5 shows the distribution of each cognitive level in percentages. Figure 1 shows the total distribution of the Cognitive Domain along the design process. Figures 2 to 7 show number of verbs at each stage for each cognitive level separately. Table 6 maps cognitive levels across the design stages based on the cognitive load of each level, ascending from low cognitive load to high cognitive load. Table 4. Distribution of the Cognitive Domain at each design stage. Design stages / PL CD SLD DD IT Cognitive Domain Knowledge 105 52 24 19 22

60 30 0

PL

CD

67

35

41

41

15

Application

23

53

49

68

35

9

Analysis

13

49

55

44

73

4

Synthesis

35

61

41

51

22

28

Evaluation

17

55

41

35

61

29

Total

232

337

245

258

254

101

IT

PR

Analysis 90 60 30 0

PL

CD

SLD

DD

IT

PR

Fig. 5. Distribution of Analysis action verbs at each design stage

16

39

DD

Fig. 4. Distribution of Application action verbs at each design stage

PR

Comprehension

SLD

Synthesis 90 60 30 0

PL

CD

SLD

DD

IT

PR

Fig. 6. Distribution of Synthesis action verbs at each design stage 90

Evaluation

60

90

30

60

0

PL CD Knowledge Analysis

SLD DD Comprehension Synthesis

IT PR Application Evaluation

Fig. 1. Distribution of the Cognitive Domain along the design process

30 0

PL

CD

SLD

DD

IT

PR

Fig. 7. Distribution of Evaluation action verbs at each design stage



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Table 5. Percentage of each cognitive level’s load at each design stage. Design stages / PL CD SLD DD IT PR Cognitive Domain Knowledge 44.1 21.8 10.1 8.0 9.2 6.7 Comprehension

16.4

28.2

14.7

17.2

17.2

6.3

Application

9.7

22.3

20.6

28.6

14.7

3.8

Analysis

5.5

20.6

23.1

18.5

30.7

1.7

Synthesis

14.7

25.6

17.2

21.4

9.2

11.8

Evaluation

7.1

23.1

17.2

14.7

25.6

12.2

Table 6. Mapping of the Cognitive Domain across the design stages. PL CD SLD DD IT PR Less cognitive load An

An

Kn

Kn

Kn

An

Ev

Kn

Cm

Ev

Sn

Ap

Ap

Ap

Sn

Cm

Ap

Cm

Sn

Ev

Ev

An

Cm

Kn

Cm

Sn

Ap

Sn

Ev

Sn

Kn

Cm

An

Ap

An

Ev

More cognitive load

4. Discussion The Cognitive Domain of Bloom’s Taxonomy is hierarchical and a progression from Knowledge to Evaluation levels is necessary to completely master a skill or a piece of knowledge. We hypothesized that the cognitive load, in particular the amount of design activities necessary to carry the product design, differs from stage to stage and gradually shifts from lower to higher levels of thinking, along the design process. If there was no difference between cognitive loads at each stage, we would expect to see similar patterns in Figures 1 to 7. However, Figure 1 shows that all cognitive levels are in use at each design stage and peak at different stages. In particular, Figure 2 shows that Knowledge level prevails at the Planning stage and then gradually decreases as other cognitive levels come into play. As can be seen from Figures 3 to 7, Comprehension level peaks at Concept Development stage, Application level peaks at the Detailed Design stage, Analysis level peaks at the Implementation and Testing stage, Synthesis level peaks at Concept Development stage, and Evaluation level peaks at Implementation and Testing stage but is also high at Concept Development stage. There is also a clear difference in distribution of each cognitive level, which is reflected in uneven loads allocation as shown in Table 5. Also, Table 6 maps the cognitive levels based on their relevance at each design stage from low to high, where the most demanded cognitive levels gradually shift from Knowledge to Evaluation. These results support our hypothesis that the cognitive load shifts from lower to higher levels of thinking along the design process. We also hypothesized that different cognitive levels are significant at different stages. First, all cognitive levels are in use at all design stages as show in Table 4. Second, if we consider two most dominating levels at each stage from Table 6, we can see that the cognitive load and abilities necessary to carry out the design of a product are consistent with the most common design activates of each design stage: 1. Knowledge level clearly dominates at the Planning stage followed by Comprehension, which suggests that all the

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necessary data about the problem should be gathered or recalled first before any ideas or concepts can be generated. For example, problem definition, specifications, constraints, regulations, budget, and other criteria should be given or defined at this stage. 2. Comprehension and Synthesis levels dominate at the Concept Development stage, which implies that the problem understanding and brainstorming are required for an idea and concept generation process, which must be synthesized together before the technical design is performed. For example, all possible ideas should be discussed with their pros and cons. 3. Application and Analysis levels dominate at System Level Design stage, suggesting that an ability to apply the knowledge about the problem to a new situation is required to start on the whole system design and its different parts. For instance, at this stage different constraints, specifications and regulations should be put together into the technical drawings. 4. Application and Synthesis levels dominate at the Detailed Design stage, pointing to the fact that more attention should be given to the development of a product details, parts and components and how they are integrated into the full system. 5. Analysis and Evaluation levels dominate at the Implementation and Testing stage, which in turn suggests that the design of the product should be analyzed, tested and evaluated before it is ready to go for the mass production. 6. Lastly, Synthesis and Evaluation levels dominate at the Production stage, which can be explained by the fact that all details should be synthesized in the final product, which should be fully evaluated in terms of its creativity, quality, novelty, safety, etc. In addition, Concept Development stage has more design activities than other stages and Production stage has the least. These results show that all cognitive levels play different roles at different design stages, depending on the type and number of activates performed at each stage. These patterns are consistent with our assumptions that different cognitive levels are more important at different stages than others. Lastly, we hypothesized that the majority of design activities happen at the beginning of the design process, in particular during the first 3 stages. Table 4 shows the distribution of the design activities at each design stage and cognitive level. As can be seen, the majority of design activities fall onto the first half of the design process, which supports our hypothesis and suggests that the first steps in the design process are more important as they define the flow of the design process and mistakes at the beginning of the process may cause process iterations or a project failure. Given the novelty of this study, its limitations should be considered, in particular the use of the original Bloom’s Taxonomy, the limited set of action verbs, and pre-defined number of design stages. In future work it would be interesting to replicate this study with students, use the revised Bloom’s Taxonomy, increase the number of action verbs to manipulate the cognitive levels, and see the difference in responses between different engineering departments. It would also be interesting to replicate this game with industrial designers to investigate their design thinking. The departmental differences and discipline-specific breakdown of the results of our Cognitive game shall be revealed and discussed in future publications.

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5. Conclusion Based on our findings we conclude that design activities and underlining cognitive processes are connected to the design stages. The majority of design activities fall onto the beginning of the design process, where the more important activities occur. In particular, the Concept Development stage should be given special attention as more design activities occur at this stage and the nature of these activities, i.e. idea generation, may have significant impact on the rest of design steps. We have also shown that the cognitive work load necessary to carry out product design shifts from lower to higher levels of thinking of Bloom’s Cognitive Domain and that each cognitive level is important at different design stages based on the activities and decisions that must be performed. It is important to note that all cognitive levels were in use at each design stage, suggesting that at each stage it is essential to pass though the cycle from Knowledge to Evaluation to ensure the successful completion of a stage. This in turn links Bloom’s Taxonomy to the design process and proves its applicability to engineering design. In this paper we explored the design thinking of engineering professors, in particular the amount and variety of design activities performed at different design stages, and showed the connection between Bloom’s Taxonomy and teaching engineering design. Given that the results of this study incorporate the data from professors from different engineering departments, who teach courses from multiple disciplines, this makes Bloom’s Taxonomy a useful tool for the development of the transdisciplinary design curriculum which would account for the cognitive development of students. Since Bloom’s Taxonomy was showed to be linked to learning engineering design education and the cognitive design activity, these findings are important to consider while developing an engineering design curriculum. Bloom’s Taxonomy can be used for teaching design processes and transdisciplinary design courses as well as its proper application can have a positive impact students’ learning, cognitive abilities, and development of interdisciplinary competencies. Acknowledgements The authors gratefully acknowledge the support of the Center for Teaching and Learning at the University of Alberta and all project collaborators: Dr. Suzanne Kresta, Dr. Jason P. Carey, Dr. Loren Wyard-Scott, Dr. Samer Adeeb, and Dr. Lucienne M. Blessing. References [1] Ertas A, Maxwell T, Rainey VP, Tanik MM. 2003. Transformation of higher education: the transdisciplinary approach in engineering. In IEEE Transactions on Education 4(2), p. 289–295.

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