Creativity in engineering 1 Fostering creativity in ... - CiteSeerX

Creativity in engineering

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Fostering creativity in engineering undergraduates

David H. Cropley University of South Australia

and

Arthur J. Cropley University of Hamburg

Address for reprint requests: Dr David Cropley School of Electrical and Information Engineering University of South Australia Mawson Lakes, SA 5095 Australia Fax: +61 8 8302 5344 Email: [email protected]


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Running head: Creativity in engineering

Fostering creativity in engineering undergraduates Summary

A total of 64 male engineering undergraduates received three lectures on creativity at the beginning of a course on engineering innovation. Some of them (N = 37) also completed a “creativity” test and were individually counselled on the basis of test scores. A separate control group (N = 21) took the test together with these students, but otherwise did not participate in any way in the study. Upon retesting six weeks later the counselled students were more innovative, whereas the control group were simply less inhibited. In addition, machines constructed by the counselled students were more elegant and creative than those of the 27 students who merely attended the lectures. Thus, the training was associated with changes in behaviour not only on the test, but in a practical activity too.


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Fostering creativity in engineering undergraduates

Almost from the beginning, modern research has demonstrated that although students with high IQs usually obtain good grades both at school and university, they are consistently outstripped by those with not only a high IQ but also high creativity (see Cropley & Urban, in press, for a recent summary). In the specific case of engineering, Facaoaru (1985) showed that engineers rated most highly by their colleagues displayed, among other things, factual knowledge, rapid recall, and logical thinking (central aspects of conventional intelligence) combined with properties such as having unusual ideas, tolerating the unconventional, and seeing unexpected implications (elements of creativity). Apparently, creativity adds something to intelligence. Indeed, Sternberg and Lubart (1992) concluded that “contrarianism” (going against the conventional way) is a characteristic of all gifted individuals. Hassenstein (1988) argued that Klugheit (literally cleverness, but used by Hassenstein as a label for a more encompassing concept of giftedness) incorporates both factual knowledge, accurate observation, good memory, logical thinking, and speed of information processing (e.g., intelligence) and inventiveness, unusual associations, fantasy, and flexibility (e.g., creativity). Following this approach, Cropley (1995) argued that creativity is indispensable for “true” giftedness. In the present paper, then, creativity will be regarded as an integral part of giftedness.


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The call for education to foster creativity in engineers was one of the main reactions to the “Sputnik shock” of 1957, when the then Soviet Union succeeded in launching the first successful earth satellite, and was widely regarded as having beaten the United States in the first event of the space race. This perceived failure of American science and engineering was attributed to lack of creativity, and judged to be the result of defects in education. University-level teaching of engineering was widely regarded as indifferent or even hostile to creativity, and empirical studies supported this view. Snyder (1967), for instance, showed that students at an American university who preferred trying new solutions dropped out of engineering courses three times more frequently than those who preferred conventional solutions. Gluskinos (1971) found no correlation between creativity as measured by a creativity test and GPA’s in engineering courses. Despite this, the literature over the years demonstrates the existence of a continuing interest in fostering the creativity of engineering students (e.g., Gawain, 1974; Masi, 1989; Olken, 1964). More recently, many corporations have rediscovered creativity: According to Munroe (1995), 70% of the cost of a product is determined by its design, so that creative design can lead to substantial cost savings. As a result, creativity training for employees is becoming widespread (Clapham, 1997; Thakray, 1995). According to the 1995 US Industry Report, corporations are now budgeting billions of US Dollars for creativity training programs, and demand for training is said to be outstripping the supply of trainers (Hequet, 1995).


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At the level of the individual engineer, considerations of the global marketplace and the creative skills regarded as essential for a successful career in engineering (Dekker, 1995) have also raised the issue of fostering creativity in engineering education (e.g., Steiner, 1998). A recent survey in Australia (Government of Australia, 1999), however, suggests that this training is not taking place, or is ineffective if it is. According to employers in the survey, threequarters of new graduates in Australia are “unsuitable” for employment because of “skill deficiencies” in creativity, problem-solving, and independent and critical thinking. Attempts in the past to train engineering students to be more creative have produced mixed results. Rubinstein (1980) and Woods (1983) reported some success in training them in problem-solving. More recently, in a pretest-posttest study, Basadur, Graen and Scandura (1986) showed that a program emphasizing divergent thinking increased the preference of manufacturing engineering students for generating new solutions, although the study did not report any changes in actual performance. Clapham and Schuster (1992) administered creativity tests to engineering students from a variety of majors. About half of them then received creativity training that emphasized deferment of judgement, brainstorming, incubation and idea-getting techniques, while the remainder acted as controls. The statistical analysis showed that the test scores of the trained students had increased significantly more than those of the controls.


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Clapham (1997) reviewed possible mechanisms through which beneficial effects of training might occur, and concluded that they can be attributed to programs’ ability to foster: (a) development of appropriate thinking skills; (b) acquisition of positive attitudes to creativity and creative performance; (c) motivation to be creative; (d) perception of oneself as capable of being creative; (e) reduction of anxiety about creativity; (f) experience of positive mood in problem-solving situations. It is apparent that this list goes beyond simply thinking skills, and encompasses attitudes, motivation, self-image, and similar factors. Despite a certain degree of success, as just reported, comprehensive analyses of the effects of short-term training on creativity (e.g., Mansfield, Busse & Krepelke, 1978) indicated that effects do not persist over time and do not transfer to situations markedly different from the original training. Nonetheless, Feldhusen and Goh (1995) concluded that it is possible to teach students to be “creative,” for instance to seek new ideas and try novel approaches. In a discussion of creativity and motivation Eisenberger and Armeli (1997) made a further important point by emphasizing that creativity can be fostered, even via external rewards (extrinsic motivation), provided that it is made clear to students what it is that they are required to do differently or better, and that they are given specific feedback based on their own behaviour. This is inconsistent with Amabile’s (1983) widely accepted conclusion that extrinsic motivation is inimical to creativity.


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In the present study an attempt was made to encourage engineering undergraduates to come up with innovative ideas, not simply in a paper and pencil test situation, however, but also in a practical exercise (“Build a wheeled vehicle powered by the energy stored in a mouse trap”). The course the students attended emphasized not merely thinking, but also noncognitive aspects of creating novelty such as image of the successful engineer, the need for courage, and tolerance of unusual or unexpected ideas. This was done both by offering three lectures specifically on creativity as well as by incorporating case studies of creative breakthroughs in engineering into the remaining lectures. The students also received specific, individual, psychological feedback on their own performance, in the form of “creativity counselling” based on test scores, something that has seldom occurred in earlier projects (see below for more details). The “creativity” test employed in the study (see below) was a multidimensional instrument that made it possible to differentiate between novelty produced by unconventional elaboration of existing ideas and novelty resulting from production of new ideas. Finally, the project was carried out within the framework of a course taken for credit as a normal part of the participants’ undergraduate program. The students’ received grades in this course, and their machines were assigned marks (i.e., there was a strong element of extrinsic motivation, theoretically fatal to creativity). Thus, the material reported here possesses the potential to extend understanding of a number of issues in the training of creativity in higher education settings.


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Method Instruments Data were collected by means of two procedures: a “creativity” test, on the one hand, ratings of the creativity of a working machine constructed by students, on the other. The key difference between the two assessments is that scores on creativity tests are an abstraction, whereas a machine actually built by participants is a behavioural measure bearing some relation to the real-life work of engineers. The test. Urban and Jellen’s (1996) Test for Creative Thinking—Drawing Production (TCT—DP) was used to assess creative potential. The wisdom of referring to procedures such as this one as “creativity” tests is unclear (i.e., their validity has been questioned). Recently, Helson (1999) distinguished between “creative potential” and “creative productivity,” and pointed out that the former— measured by tests—may or may not lead to the latter. For this reason, we prefer to write “creativity” in quotation marks (as above) when referring to the tests, or to label them “tests of creative potential.” According to the manual, this instrument is suitable for use with a very wide range of ages, including tertiary students, and for several purposes over and above simple assessment, including counselling. At its core is what the test constructors call “image production.” Persons taking the test are required to complete figural fragments, as in several other creativity tests. However, scoring is not based on statistical uncommonness of the figures produced but on a number of criteria derived from Gestalt psychology. In all, the test yields 14


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dimensions including “Boundary Breaking,” “Unconventionality,” and “New Elements.” There is also a “Total” score, the sum of the various subdimensions. The test has two forms, A and B, that can be regarded as equivalent. The authors reported validity coefficients of about 0.80 for correlations of test scores with teacher ratings, and test-retest reliabilities of the order of 0.70. In the present study, correlating Form A “Total” of the control group with Form B six weeks later yielded a test-retest reliability of .75 (N = 21, p = .01), a satisfactory level in view of Hocevar and Bachelor’s (1989) report that test-retest reliabilities of about .70 are typical for creativity tests. Interrater reliability was estimated by having 36 randomly chosen Form A protocols rescored by a second rater (without knowledge of the scores assigned by the first). An interrater reliability of 0.94 was obtained (N = 36, p = 0.01). The creative product. Almost from the beginning of the modern era of creativity research, raters’ assessments of products of various kinds have been employed as a way of measuring creative productivity. This approach has been supported in principle by recent theorizing and research. Hennessey (1994) emphasized that a product can be regarded as creative when competent judges apply this label, and suggested the method of “consensual assessment.” When judges agree that it is, a product is creative. In Hennessey’s study, untrained undergraduates were able to make consistent judgements about the creativity of products by simply applying their own subjective understanding of creativity.


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Interrater agreements were up to .93, and reliabilities of the ratings ranged from .73 to .93. In the present study, the vehicles were rated on four dimensions according to the subjective judgement of the rater: Effectiveness (distance travelled), Novelty (originality and surprisingness), Elegance (understandability and workmanlike finish), and Germinality (usefulness, ability to open up new perspectives). These four dimensions are a fusion of the scales of Taylor’s (1975) Creative Product Inventory, that includes scales for “Generation,” “Reformulation,” “Originality,” “Relevance,” “Hedonics,” ‘Complexity,” and “Condensation,” and the dimensions of Besemer and O’Quin’s (1987) Creative Product Analysis Matrix, including “Novelty,” “Resolution,” and “Elaboration and Synthesis.” In addition, each vehicle was awarded points for the Overall Impression it made, bearing in mind that the students had been urged to make their vehicles as creative as possible (see below). In all five categories, a vehicle could receive from 0 to 5 points, with intervals of 0.25 points between ratings being possible (i.e., scores such as 3.50 or 2.75 could occur). The machines were assessed blind (without knowledge of the group to which a particular student belonged) by an engineering instructor. Unfortunately, because the models were part of the students’ exams and had to be returned to them quickly, there was only time for a single rater to assess them, so that the level of agreement between raters (interrater reliability) could not be determined. Procedure


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Recruiting participants. All participants were enrolled in a second-year course “Engineering Innovation and Practice” (EIP). Because of the well-known gender differences in creativity test scores and effects of creativity training, possible confounding by gender needed to be controlled. The small number of female students in EIP meant that this could only be done by confining the study to males. During the first week of semester, the purpose of EIP was explained to the students enrolled in it, as well as the various activities involved in the course. Of particular interest here are the creativity testing, the creativity counselling, the creativity lectures and the construction of the mousetrap-powered vehicle. In the second week the students were given the opportunity of taking the TCT—DP and receiving the counselling. It was emphasized that participation was voluntary. About 60% of the 64 male students in the course did in fact volunteer (N = 37). They are referred to in the following as the “experimental” group. Of these people, 3 did not submit the model, leaving a reduced experimental group of 34.The remaining EIP students (N=27) attended the lectures and submitted the vehicle, but did not do the test or receive counselling. They comprise the “lecture” group. In the same week, male volunteers were also recruited in a different engineering course that included none of the elements of EIP. These students (N = 21) did the test with the EIP students, but neither attended EIP lectures nor received counselling, and formed the “control” group. The 85 men in the three groups ranged in age from 18—25. It is important to note that the experimental and control groups consisted of volunteers (i.e., they were self-


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selected), while the men in the lecture group, who simply submitted the model, were “refusers.” Thus, the possibility cannot be discounted that the experimental and control groups contained men particularly receptive to material on creativity, the lecture group men particularly unreceptive. Indeed, the mean TCT-DP scores of experimentals and controls that are reported below were considerably higher than scores for similar groups given in the test manual. Measuring creative potential. Members of both groups of volunteers took Form A of the TCT—DP in the second week of the semester. Their protocols were scored by three female graduate students of psychology according to the procedures outlined in the test manual (Urban & Jellen, 1996). These raters had been trained to score the test in a half-day workshop. Protocols were identified by code numbers only, and the raters were not informed which group the men whose work they were rating belonged to. In the eighth week of semester the students took Form B of the test, and their protocols were once again scored blind by the same raters. Creativity counselling. On the basis of scores on 13 of the subtests of the TCT—DP (time taken was excluded), a profile was constructed for each of the 37 EIP students who had taken the test. The profiles focused on three dimensions: “Productivity,” “Originality,” and “Unconventionality.” Initially, these dimensions were established by means of an intuitive grouping of subscales that experience with the TCT-DP suggested belong together. Subsequently, however, the dimensions were empirically confirmed by a factor analysis of the Form A


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protocols of 111 male, second-year engineering students (the men who completed Form A in connection with the present study, regardless of the group they belonged to or whether they also completed Form B, plus additional students who took EIP in the next semester). The factor analysis (principal-axis method followed by rotation of factors with eigenvalues greater than unity to the Varimax criterion of simple structure) yielded three “significant” factors, as anticipated. The first (eigenvalue = 2.30, 17.7% of total variance) was defined by Boundary Breaking, Continuations, and Completions, and was labelled “Productivity,” the second (eigenvalue = 1.98, 15.2% of total variance) by New Elements, Thematic Connections, and Perspective, and labelled “Novelty.” The third factor (eigenvalue = 1.40, 10.8% of total variance) was defined by Humour, Symbol-Figure Combinations, Symbolic/Abstract/Fictional, and NonStereotypical Utilization of the Given Fragments. It was labelled “Unconventionality.” Bearing in mind that the reliabilities of the individual subtests were on average about 0.70, these three factors accounted for about 90% of the accountable variance of the TCT-DP. In the third week of semester, each student was individually counselled by one of the three psychologists already mentioned, the sessions typically taking about 15 minutes. The counsellors had received training in using the test for creativity counselling in the workshop mentioned above. Each participant was shown his own profile, and attention was drawn to areas of relative strength and weakness, not in a normative but in an ideographic fashion. This was done without reference


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to the actual test or to scoring criteria. To take a concrete example that illustrates what the procedure was like, a student might be advised, “You produced plenty of ideas. However, only a few of them were novel or unconventional.” The student might then specifically thematize issues such as unwillingness to risk doing something “foolish,” whereupon the counsellor would encourage the participant to distinguish between prudence and excessive caution. The creativity lectures. In the second, third, and fourth weeks of semester the students enrolled in EIP received three lectures from a psychology specialist (the second author) on (a) What has creativity got to do with engineering students? (b) Why do engineers have problems with creativity? (c) What are the psychological elements of creativity? (d) What are the characteristics of a creative product? (e) How can you solve problems creatively? (f) What blocks creativity? Lectures emphasized the importance of creativity in modern engineering practice and as a factor in developing a career in the field, and attempted to provide students with an understandable, practical model of creativity that stressed cognitive, motivational, affective, and social aspects. It emphasized that creative products must not only be novel and germinal, but must also reflect a high level of engineering knowledge (be effective and relevant). As will be discussed below, this stress on building a model that really worked caused difficulty for some students. The behavioural measure . The course outline indicated that one of the assignments to be completed and scored as part of the assessment for the course


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was to build “a wheeled vehicle powered by a mousetrap.” This had to be submitted in the 8th week of semester. It was emphasized to the students that the creativity of their vehicle would be an important source of points, although they were also reminded that it would have to be capable of propelling itself. When students asked for clarification of either “a wheeled vehicle,” or “powered by a mousetrap,” they were advised that the words in question were a sufficient definition of the task, and would not be elaborated upon by the instructor. They were, however, reminded that the course was about creativity, and were also reminded of the four dimensions on which their products would be evaluated (Effectiveness, Novelty, Elegance, and Germinality—see below). Results The results are presented in two parts: Those relating to TCT—DP scores and involving comparisons of the experimental group (N = 37) with the control group (N = 21), and those relating to the assessment of the vehicle and involving comparison of the reduced experimental group (N = 34) with the lecture group (N = 27).

Changes in test scores The first results are derived from a comparison of the test scores of the experimental group with those of the control group. The members of both groups were tested with the TCT—DP and retested six weeks later. At the time of the second testing the experimental group’s members had received counselling based


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on their creativity profiles (see above) and had attended the lectures on creativity. The control group had simply waited six weeks. Both groups consisted of volunteers, a fact that is likely to have reduced the possible confounding effects of self-selection. Indeed, since the controls were not even in EIP, but responded to a general appeal in second-year courses, the volunteer effect may well have been stronger in their case than in that of the experimentals, and would thus be conservative (i.e., it would reduce the chance of creativity differences in favour of the experimentals). The TCT—DP scores of the groups, both total scores and also scores on the various dimensions, were compared using a two-way analysis of variance, the dimension “experimental group vs. control group“ (counselled versus not counselled) defining one independent variable, the dimension “first testing versus second testing” the other. Naturally, there were repeated measures on the time of testing factor, since the same people were tested on two occasions. This design permitted both between-group and within-group comparisons. The analyses of variance indicated that there was already a significant difference between the total score of the experimentals (M = 40.92, SD = 12.26) and that of the controls (M = 36.76, SD = 9.78) at the time of the first testing, F(1, 56) = 6.15, p = .02, i.e., even before the lectures and counselling. There was a significant interaction between group and time of testing, F(1,56) = 4.94, p = .03. This was caused by a large increase in the mean (M = 47.27, SD


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= 10.56) of the experimentals (40.92 vs. 47.27), whereas the mean of the controls (M = 37.33, SD = 12.89) had remained almost constant (36.76 vs. 37.33). Thus, it can be argued that whereas simply waiting six weeks for the second testing had no effect on the mean score of the controls, lectures and counselling led to a statistically significant increase in the scores of the experimentals. This greater increase in total scores of experimentals than of controls was largely attributable to significant increases in three of the subdimensions of the TCT—DP, New Elements, F(1,56) = 7.51, p = .01, Boundary Breaking (Fragment Dependent), F(1,56) = 5.72, p = .02, and Unconventionality via Manipulation of the Materials, F(1,56) = 5.65, p = .02. Although there were numerical increases in scores of the experimentals on several other subdimensions, unaccompanied by correspondingly large increases for the controls, these differences were not statistically significant and are thus to be regarded as tendencies rather than significant differences. The most notable example is Boundary Breaking (Fragment Independent), where the mean of the experimental group increased from 2.43 (SD = 2.99) to 4.38 (SD = 2.41), as against the control group, where the increase was from 1.71 (SD = 2.78) to 2.57 (SD = 2.87). In the case of Continuations and Completions, there were actually numerical decreases in scores of both groups on the second testing (see later comment). Creativity of the product


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The second set of results was derived from a comparison of the creativity of the mouse trap-powered vehicles submitted by the members of the experimental group (who had taken the test, been counselled and received the lectures) with that of the vehicles constructed by the lecture group—who had not taken the test and had not been counselled. All participants succeeded in constructing a vehicle that met the minimum formal requirements (it had wheels and was capable of moving itself). Several of the resulting models were elegantly designed and well-finished. However, most students assumed that the vehicle had to be four-wheeled and had to run on the ground like a car or truck. In addition, most focused on the energy stored in the trap’s spring as the source of power, as well as consciously opting for a vehicle that was effective in that it could cover a metre or more, and was socially acceptable in that it looked like existing vehicles. Only a few were able to achieve a dramatic breakaway from conventional thinking, for instance by constructing an aeroplane launched by a catapult powered by the mousetrap’s spring (the plane had wheels and covered a considerable distance), or by building a large hollow wheel set rolling by a weight mounted in its interior and wound into position by the mousetrap’s spring. More radical in some ways was a wheeled cart attached to the mousetrap by a string. When the mousetrap was thrown off the table on which the vehicle stood, its weight pulled the vehicle along as the trap fell to the floor, thus using the gravitational force acting on the mousetrap’s mass as the source of energy. The only limit on the distance this method could propel the


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vehicle was the height of the surface from which the mousetrap was thrown. One group set fire to the mousetrap and used the heat generated by the flames to generate steam that moved the vehicle a short distance, thus using the chemical energy stored in the wood. A final group thought of using the mousetrap’s spring to compress a bellows and inflate a balloon, that would then deflate violently and drive the vehicle by its jet action, but abandoned this approach as too risky, since it might not propel the vehicle sufficiently far to be judged effective. Correlations among the five dimensions showed that Effectiveness and Elegance correlated substantially with each other, r = 0.54, N = 61, p = .00, not surprising in view of the fact that both dimensions emphasized whether or not the vehicle worked. Novelty correlated substantially with Germinality, r = 0.92, N = 61, p = .00, but not with Effectiveness, r = -0.11, N = 61, ns, or Elegance, r = 0.12, N = 61, ns, while Germinality had only low correlations with Effectiveness, r = -0.09, N = 61, ns, or Elegance r = 0.26, N = 61, p = .05. In other words, ratings defined two relatively independent dimensions, one characterized by Effectiveness and Elegance, the other by Novelty and Germinality. The Overall Impression score correlated substantially with Novelty, r = 0.87, N = 61, p = .00, and Germinality, r = 0.89, N = 61, p = .00, but far less with Effectiveness, r = 0.16, N = 61, ns, or Elegance, r = 0.38, N = 61, p = .01, so that the rater’s subjective impression was formed on the basis of Novelty and Germinality, scarcely surprising in view of the fact that the rater formed an overall impression based on perceived creativity of the vehicles.


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Comparison of the means of the two groups showed that the mean of the experimental group on Elegance (M = 3.46, SD = 0.39) was significantly different from the mean (M = 3.15, SD = 0.48) of the lecture group, t(59) = 2.80, p = .00. The difference between the mean of the experimentals on Overall Impression (M = 3.59, SD = 0.43) and that of the lecture group (M = 3.34, SD = 0.46) was also statistically significant, t(59) = 2.18, p = .04. In all other cases (Novelty, Germinality and even Effectiveness), the means of the experimentals were numerically higher than those of the lecture group (i.e., it is possible to speak of a tendency for the counselled group to surpass the group without counselling on the various assessments of their vehicles). Discussion The subdimensions of the TCT—DP on which the experimentals obtained significantly greater increases than the controls were in essence tasks requiring either production of something new (as against extending or altering something that already existed), or using the materials in a radically unconventional way, for instance by rotating or folding the answer sheet (as against retaining the usual spatial orientation, even though in some cases giving unexpected answers). The controls sometimes constructed more unconventional figures, but tended to stick within the conventional framework. For instance, on the retest they elaborated existing figures in a more ingenious fashion than before. This can be attributed to the fact that on the second occasion the test materials were familiar and the unstructured nature of the task less inhibiting. By contrast, the experimentals went


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further. As a group, they were more prepared to introduce new material out of their own heads or change the existing structure. The untrained students increased their scores to be sure, but did this by being less inhibited, whereas the people in the experimental group increased theirs by being more innovative. This interpretation is supported by the fact that the variance of the experimental group decreased at the second testing, whereas that of the control group increased. In the “treated” group weaknesses were reduced, thus homogenizing performance, whereas in the “untreated” group those with higher initial scores became more adept with experience of the test, whereas those with lower scores to start with remained limited in their answers. Thus, the quantitative differences between the counselled students and the control group seem to reflect a qualitative effect of counselling on behaviour. The results show that, in addition to producing more novelty in the test setting, the experimentals transferred this to the actual building of a vehicle. This finding is of considerable interest, because it involves a criterion intuitively resembling the actual work of engineers, raising the hope that the effects obtained in this study might persist in real-life settings. This was achieved despite the fact that the students were working for grades (extrinsic motivation), and supports the position of Eisenberger and Armeli (1997) rather than Amabile (1983). The “counselling” described here gives practical hints on implementing Eisenberger and Armeli’s recommendation for clear feedback to students on what they need to do differently in order to behave more creatively.


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When their instructors ask engineering students to create novelty, they expose them to a dilemma. Engineering requires high levels of expertise— mastery of basic knowledge, skills and techniques. The public wants machines to work and bridges to continue standing. Mastery of what already exists thus has a high value for students, and production of novelty runs directly counter to this tradition. Paradoxically, however, it is highly prized. Somehow, a compromise must be found between two apparently contradictory ways of behaving. Focusing on people who had achieved high public acclaim for their expertise, Root-Bernstein (1989) described the “novice effect”: This is seen in experts who display high command of orthodoxy, but are still able to break out of the straitjacket of their own expertise and look at their subject with the openness and freshness of beginners. The present study can be seen as looking at this issue from the other end of the scale: It is concerned with how to encourage students to seek to develop expertise, but at the same time to remain capable of creating novelty.

Ericsson and Smith (1991) pointed out that expertise is typically conceived of as arising from a combination of primarily inherited attributes (such as intelligence, personality, or special abilities) and primarily acquired attributes such as special cognitive strategies or domain-specific knowledge. It is scarcely conceivable that the brief training provided in the present study would bring about profound and longlasting changes in participants’ ability or personality structure (i.e., in the sense of Helson [1999] in their fundamental psychological potential to be


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creative). However, it was possible to show them a different way that they found enjoyable of solving an engineering problem, as well as to give them a convincing demonstration of their own ability to come up with ideas. In this sense, the study offers hints about how to influence the emergence of acquired attributes, in the present case specific knowledge about creativity, divergent cognitive strategies, and a positive attitude to novelty. However, there seems little likelihood that such attributes will persist unless they are further developed by appropriate followup activities.


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Biographical Notes David H. Cropley completed undergraduate studies at the University of Salford, UK and obtained his PhD in Australia. He is lecturer in electronic engineering at the University of South Australia and is particularly interested in information, systems engineering and measurement. As a result of his interest in fostering creativity in engineers he has conducted research on innovative approaches to university teaching and the development of a model of creativity in systems engineering.

Arthur J. Cropley was initially a schoolteacher in Australia, England and Canada. He completed his PhD at the University of Alberta and has since been a university teacher in Canada, Australia and Germany. In 1999 be became professor emeritus. He has published extensively on creativity and learning in adults, and is now combining these areas in studies of creativity in engineering education.