Enhancement of Ideational Fluency by Means of Computer-Based Training

Creativity Research Journal ISSN: 1040-0419 (Print) 1532-6934 (Online) Journal homepage: http://www.tandfonline.com/loi/hcrj20 Enhancement of Ideational Fluency by Means of Computer-Based Training Mathias Benedek, Andreas Fink & Aljoscha C. Neubauer To cite this article: Mathias Benedek, Andreas Fink & Aljoscha C. Neubauer (2006) Enhancement of Ideational Fluency by Means of Computer-Based Training, Creativity Research Journal, 18:3, 317-328, DOI: 10.1207/s15326934crj1803_7 To link to this article: http://dx.doi.org/10.1207/s15326934crj1803_7 Published online: 08 Jun 2010. Submit your article to this journal Article views: 212 View related articles Citing articles: 26 View citing articles Full Terms & Conditions of access and use can be found at http://www.tandfonline.com/action/journalinformation?journalcode=hcrj20 Download by: [Wagner College] Date: 26 September 2017, At: 19:22

Creativity Research Journal 2006, Vol. 18, No. 3, 317 328 Copyright 2006 by Lawrence Erlbaum Associates, Inc. Enhancement of Ideational Fluency by Means of Computer-Based Training Mathias Benedek, Andreas Fink, and Aljoscha C. Neubauer University of Graz ABSTRACT: Training of divergent thinking, which is commonly regarded as an important component underlying creativity, often involves the administration of a large number of moderated sessions. This exploratory study examines a computer-based divergent thinking training program with respect to its effectiveness in enhancing ideational fluency and originality on the basis of practice. Two training versions were developed: (a) a training of verbal creativity and (b) a training of functional creativity. Both training versions consisted of 9 sessions with 8 divergent thinking tasks each. Two training groups (consisting of 11 participants each) and a control group (n = 14) were matched for creativity, intelligence, age, and gender; the groups were tested in a pre posttest design. The computer training was found to effectively enhance the intelligent independent aspect of ideational fluency (d = 0.54), whereas no training effects with respect to the originality of ideas were observed. The findings point to the usefulness of a computer-based training to enhance creativity-relevant abilities. Being creative is obviously associated with various advantages. It makes you attractive for companies trying to enhance their innovation capabilities (Sternberg & Lubart, 1999). At the same time, creativity is linked to mental health and emotional well-being (Runco, 2004; Simonton, 2000). Creativity is commonly considered as the second major field of human performance in differential psychology next to intelligence (e.g., Amelang & Bartussek, 1997). However, efforts in defining creativity as well as attempts toward a reliable and valid assessment of the multiple facets of creativity have not yet proved to be as successful as for intelligence (Krampen, 1993). Reasons for the difficulties in defining creativity may be seen in the ambiguous role of creativity within the field of differential psychology, either stressing its association with human performance (e.g., Guilford, 1950) or underscoring the relation to personality differences (e.g., Csikszentmihalyi, 1996). On the one hand, substantial correlations of creativity with psychometric intelligence are found (Rindermann & Neubauer, 2004; Schoppe, 1975; Torrance, 1966) that are attributed either to similarities of the testing conditions (e.g., timing of the tasks) or to similarities of the underlying constructs themselves (for an overview, see Sternberg & O Hara, 1999). On the other hand, significant associations are commonly found with personality traits such as extraversion, openness, or psychoticism (Feist, 1998; Fink & Neubauer, in press; King, McKee Walker, & Broyles, 1996; Wolfradt & Pretz, 2001). Even if the heterogeneity in this research field has often been an obstacle difficult to overcome with respect to conceptualizing creativity, its complex and multifaceted nature as well as its beneficial effects on several areas of our everyday life has, all the more, motivated researchers to delve into this mental ability domain. Assessment of Creativity Divergent thinking (i.e., the ability to produce a broad range of different associations to a given stimu- This research was supported by a grant from the Austrian Science Foundation (FWF -P16393). The authors wish to express their large gratitude to Beate Staudt and Silvana Weiss for their assistance in data collection, and to Roland H. Grabner and Anna Kanape for the valuable comments on the manuscript. Correspondence and requests for reprints should be sent to Mathias Benedek, Universitaetsplatz 2/III, A-8010 Graz, Austria. E-mail: mathias.benedek@uni-graz.at Creativity Research Journal 317

M. Benedek, A. Fink, and A. C. Neubauer lus) can be viewed as a useful estimate of the potential for creative thought (Runco, 1999). It is commonly seen in opposition to convergent thinking (i.e., the ability to find the one and only correct solution). Therefore, divergent problem solving might be best characterized by open problems (unstructured tasks involving little restrictions) with open solutions (Kaufmann, 2003). The psychometric assessment of divergent thinking goes back to Guilford (1950), who proposed to measure a number of variables including ideational fluency (i.e., number of ideas), novelty (or uniqueness and originality) of ideas, as well as the flexibility of thinking (i.e., the ability to produce different types of ideas). His suggestions have stimulated the development of various creativity (or divergent thinking, respectively) measures (e.g., Torrance Tests of Creative Thinking [TTCT]; Torrance, 1966; or in the German-speaking area, the Verbaler Kreativitätstest [VKT]; Schoppe, 1975). In these tests, the fluency aspect is usually quantified by the number of ideas produced within a given period of time. The flexibility aspect can be quantified by the number of different predefined categories touched by the ideas. The originality of the ideas can either be assessed by the uncommonness (i.e., statistical infrequency) of the categories or ideas or by judgments of external raters (expert ratings). Some creativity tests such as the TTCT also allow for assessing the elaboration of the ideas by quantifying the number of details involved. To date, many measures have been developed and empirically tested (see Plucker & Renzulli, 1999). On the whole, they allow a reliable and valid measurement of some aspects of creativity especially in the verbal creativity (VC) domain. Enhancement of Creativity Many research efforts were undertaken to address the need of an effective actualization or enhancement of a person s creative abilities. In this context, different training procedures were developed and empirically tested. Most of these training programs typically aim at enhancing the divergent thinking component of creativity. A recent meta-analysis by Scott, Leritz, and Mumford (2004a) shed further light on the efficacy of creativity trainings. To this end, 70 studies that report on training programs in the academic and the economic context were taken into account and analyzed for their average efficacy on four dependent criteria (viz., divergent thinking, problem solving, performance, and attitude behavior). The meta-analysis yielded an overall effect size of Cohen s = 0.64, which is in line with the findings of prior meta-analyses by Lipsey and Wilson (1993) or Rose and Lin (1984). Within the criteria of divergent thinking, effects were found for fluency ( = 0.67), flexibility ( = 0.75), originality ( = 0.81), and were somewhat smaller for elaboration ( = 0.54). Moreover, for this meta-analysis, 11 training types were distinguished by means of a cluster analysis (Scott, Leritz, & Mumford, 2004b). This analysis revealed that training programs involving idea production and cognitive-oriented trainings proved particularly effective, whereas other commonly applied techniques (e.g., imagery training) turned out to be less effective. Creativity and Computers In the meta-analysis reported earlier (Scott et al., 2004b) only 3 (2%) out of 154 studies dealt with computer-based production trainings, which proved to be quite effective ( = 0.77). These studies dealt with training of divergent thinking abilities of kindergarten children (Cliatt, Shaw, & Sherwood, 1980) or school children by means of computer programs (e.g., the theoretically based Logo programming environment for picture design; Clements, 1991). The small number of available computer-based trainings may originate from the popular point of view that computers can only support noncreative thinking and production. Computers by nature algorithmic and logical may seem to require convergent thinking and not to encourage original ideation. Recently, however, computers are increasingly appreciated as valuable tools for creative work (Clements, 1995; Yamamoto & Nakakoji, 2005). This goes along with the trend to use electronic group support systems (e.g., electronic brainstorming) for group creativity processes to avoid the process losses usually found in groups interacting face to face (e.g., DeRosa, Smith, & Hantula, in press). Working with computers enables individuals to document ideas in the moment they arise, to work anonymously if preferred, and to obtain additional information on request; thus, avoiding process losses like production blocking, cognitive interference, or evaluation apprehension, which are typically observed in face-to-face creativity en- 318 Creativity Research Journal

Ideational Fluency Training hancement techniques (e.g., classic brainstorming; Diehl & Stroebe, 1987, 1991; Pinsonneault, Barki, Gallupe, & Hoppen, 1999). may contribute to a better understanding of the bases of more complex training programs. This Study Although creativity trainings, in general, prove to be effective in enhancing creativity, the underlying mechanisms of these training effects remain mostly unclear. Many training programs involve multiple treatments making use of cognitive, social, and motivational factors to establish a reliable enhancement of creativity (cf. Nickerson, 1999), which, however, complicates the ascription of training effects to a specific treatment. Therefore, in this study, an attempt was made to avoid confounding influences by multiple treatments and to focus on the impact of practice on divergent thinking. Moreover, the concept of VC is examined in more detail by differentiating verbal divergent tasks with regard to whether the resulting creative ideas are verbal products by nature (e.g., nicknames) or simply verbally expressed ideas (e.g., an unusual use for a common object). To address this question, two different training variants were realized: one focusing on divergent tasks requesting creative ideas within the verbal domain (e.g., generating nicknames or slogans; in the following referred to as VC training) and the other focusing on divergent tasks requesting creative ideas not necessarily associated with the verbal content modality, but still verbally expressed (e.g., generating unusual uses for objects; in the following referred to as functional creativity [FC] training). Training programs can be quite time consuming and extensive as they involve a large number of sessions and often necessitate the presence of a trainer or moderator. Unlike this, the employment of computer-based training procedures is associated with several advantages: (a) The training can be conducted efficiently and in a highly economic way, (b) it allows for a high objectivity in conducting the training, and (c) enables the experimenter to monitor and objectively document a variety of training activities that may contribute to any training effects observed. Therefore, the computer-based training setting realized in this study shall assess the effect of test-analogous practice on the enhancement of ideational fluency, which, consequently, Method Participants Out of a larger pool of participants who were recruited through local newspaper advertisement, 36 individuals (19 women) were randomly selected for this training study. Participants age ranged from 19 to 51 years (M = 31.39, SD = 8.22). In an initial screening, they were tested for intelligence (by means of the Intelligenz Struktur Test 2000 R; Amthauer, Brocke, Liepmann, & Beauducel, 2001) and personality (by means of the NEO-FFI by Costa & McCrae, 1992; German version by Borkenau & Ostendorf, 1993). The participants were paid for participation and, in addition, received individual feedback on all measures. Experimental Design and Material The experiment was based on a pretest training posttest design including two experimental groups (VC and FC training) and a control group (which received no training between pre- and posttest). Participants were matched with regard to creativity (pretest), intelligence and personality (initial screening), age and gender (see the following), and randomly assigned to one of the three experimental groups. The VKT (Schoppe, 1975) is a well-known German creativity test comprising nine subscales: (a) word beginnings (generate words with a given prefix), (b) word endings (generate words with a given suffix), (c) four-word sentences (generate sentences of 4 words starting with the 4 letters given), (d) name invention (generate names to a given 3- or 4-letter abbreviation), (e) same property (generate objects having a given property in common), (f) similarities (generate synonyms to a given adjective), (g) unusual uses (generate unusual uses for a given everyday object, (h) utopian situations (generate consequences to a given utopian situation), (i) nicknames (generate nicknames for common objects). For each of the nine subscales, the participants were prompted to generate as many and as unusual ideas as possible. In total, the administration of the VKT took 40 min. Following the scoring guidelines given in the VKT test manual, a fluency score was Creativity Research Journal 319

M. Benedek, A. Fink, and A. C. Neubauer obtained for each subscale by counting the number of ideas; and, in addition to this, a total score of fluency was calculated by aggregating the scores of the nine subscales. Trait anxiety was assessed by means of the trait version of the State Trait Anxiety Inventory (STAI; Spielberger, Gorsuch, & Lushene, 1970; German version by Laux, Glanzmann, Schaffner, & Spielberger, 1981). Quantification of Idea Originality The test manual of the VKT only provides information on the quantification of ideational fluency. To additionally obtain a qualitative measure of creativity, four trained raters were asked to assess the originality of each single idea on a three-point rating scale ranging from 1 (common, trivial idea) to3(uncommon, original idea). For this purpose, a list comprising all ideas for one test item (pre- and posttest of all participants) was compiled and sorted in alphabetical order, thus providing the raters with no information about the experimental condition the ideas came from. Due to economical reasons, this procedure was only performed for those two subscales (utopian situations and nicknames) that displayed the highest factor loadings on the creative ideational fluency factor extracted from the VKT scales (see analysis of criterion in the Result section). The four raters (2 women, 2 men) displayed satisfying internal consistency in their originality ratings (Cronbach s alphas ranging between.80 and.91). The originality ratings were averaged over all four raters. The ideational originality score was finally computed by averaging over all items of the two tasks. The correlation between idea originality and fluency was not significant (r =.21, p =.23), indicating that with idea originality an additional, independent measure could be obtained. Training A direct training approach (Klauer, 2001) was chosen, suggesting that the performance can be improved by practicing a large number of exercises structurally similar to the task used to assess the performance. As noted earlier, the training was realized in two different training variants: VC and FC. The tasks selected for the VC training requested participants to generate divergent solutions by explicitly handling verbal stimulus material such as finding slogans, nicknames, original descriptions, or word associations. The tasks selected for the FC training required participants to generate divergent solutions dealing with characteristics of objects and situations such as identifying similarities and differences between objects, thinking of possible improvements, or finding explanations and consequences of given situations. Both training versions comprised nine differenttasktypeswithatotalof72exercises.afulldescription of all training tasks can be found in the appendix. A sequence plan compiled the exercises into nine training units, each taking approximately ½ hr. The task sequences of the first four and of the last four training units were exactly the same, resulting in two comparable training halves before and after a middle training unit (Training Unit 5). The sequence of the training halves was randomly exchanged. Based on previously collected data, the sequence plan for each training half reflected increasing task difficulty (i.e., number of ideas produced within 3 min). An additional training schedule requested the participants to complete not more than one training unit per day, as well as not less than one within 2 days. These restrictions were set up to establish comparable, good training conditions. The training was realized as a computer training using the mathematical programming language MATLAB R13. It was finally provided on CD-ROM allowing easy installation on any home computer. It was delivered to the participants with a manual explaining the installation procedure and the schedule of the training units. The installation required a password triggering the training type and sequence of the training halves to be realized for each participant. After installation of the software, two introductory exercises had to be completed, accompanied by instructions from the manual. Then, the training units could be started in a predetermined sequence. Each task presentation consisted of a short introduction illustrated by an example. This was followed by the instruction to generate as many, as various, and as original ideas as possible within a time period of 3 min. On confirmation (via mouse click) of both information pages, the exercise started. The task item was presented centered in the upper part of the window; right below, an input box was displayed where ideas could be typed in and added to an idea list placed at the bottom part of the window. At any time the user (trainee) could change or delete entries from the list. An inconspicuous time button at the right side of the window was provided to display the elapsed time of this exercise on demand (mouse click) 320 Creativity Research Journal

Ideational Fluency Training for 2 sec. This was intended to help the user to terminate the exercise within approximately 3 min, but at the same time avoid stress or distraction that might arise when a clock is visible all the time. When the user decided to terminate the exercise, the training time and idea quantity for this exercise were displayed before continuing. After completing all eight exercises of a training unit, the user was prompted to give feedback on how interesting, exhausting, and entertaining the training unit was. Responses could be given by shifting sliders (preset in the middle position) on a visual analogue scale between labeled poles. Moreover, individual feedback (thoughts, remarks, or noticed interruptions during that training unit) could be entered in an editable field below. After that, the user returned to the main window where the overall training time and idea quantity was displayed for each training unit completed so far. On completion of all training units, the user received information on where to find the stored training data on the computer hard disk and was asked to send it via e-mail to the instructor or bring it in for the posttest session. Procedure Participants took part in one out of four pretest sessions within the range of 10 days that were held as a group test in a university lecture hall. They randomly received one of the two parallel versions of the creativity test (VKT). Finally, the STAI was completed. At the end of the session, participants received a CD-ROM containing the training software and a manual. They were told that they would soon be informed about when to start the training and that they would then be given a code for activating the software. In some cases the training would not be started until after the posttest session due to experimental reasons. However, all participants were promised to receive the same feedback based on their tests and training data. Overall, the first test session took about 1 hr. Members of one of the training groups received an activation code that triggered the software to activate the corresponding training in either one of the training-half sequences (A-B or B-A). They were told to complete the training before the posttest session and to send the training data before then or to bring it with them. Members of the control group were asked to understand that their training would be postponed until after the posttest session. The posttest session was structured parallel to the pretest session. Again, four possible dates were provided within the range of 10 days. Participants then worked on the parallel version of the creativity test. After the posttest was finished, members of the control group received their activation codes. They were thanked and paid for their participation. As soon as the complete data were collected, all participants received individual feedback on their test and training data. Results Analysis of the Criterion In Table 1, descriptive statistics as well as intercorrelations (Spearman s rho) of the creativity test scores are presented. The means of the VKT subscales (SC) ranged between 7.61 (SC4: inventing names) and 23.31 (SC1: word beginnings). Intercorrelations between the subscales ranged from.06 up to.57. Considering the rather broad range of means as well as the variable correlative associations between the VKT subscales, calculating a total score by aggregating over all nine subscales seems to be inappropriate. Therefore, as a next step a principal component analysis (PCA) was performed on the VKT subscales. The PCA yielded two factors with eigenvalues larger than 1, accounting for 59.94% of the variance. 1 In Table 2, the communalities as well as the varimax-rotated factor loadings are presented. It can be seen that the first factor is marked exclusively by factor loadings of Subscales 5 through 9, whereas the second factor is characterized by high factor loadings of Subscales 1 and 2. Subscales 3 and 4 show moderate loadings on both factors and, thus, can not clearly be associated with either the first or the second factor. To obtain more information about the meaning of the two PCA extracted factors, the factor scores were correlated with external criteria such as intelligence and personality variables (see Table 3). The analyses showed that Factor 1 was not associated with intelligence (r =.00, p >.99), whereas Factor 2 was highly correlated with the intelligence test score (r =.48, p =.002). On 1 It is generally not recommended to calculate factor analyses with small samples (N < 150). However, with a Kaiser Meyer Olkin coefficient =.75 and high loading marker variables (>.80) smaller sample sizes may be acceptable (Tabachnik & Fidell, 2001). Creativity Research Journal 321

M. Benedek, A. Fink, and A. C. Neubauer Table 1. Descriptive Statistics and Intercorrelations (Spearman s rho) of the Creativity Subscales (SC) Creativity Subscales Variable SC1 SC2 SC3 SC4 SC5 SC6 SC7 SC8 SC9 SC1: Word Beginnings 23.31 (6.15).50.37.57.44.30.22.11.26 SC2: Word Endings 13.86 (5.28).14.32.16.10.21.07.06 SC3: 4-Word Sentences 10.17 (3.52).51.27.53.14.29.32 SC4: Name Invention 7.61 (3.09).38.50.34.35.40 SC5: Same Property 20.86 (6.70).26.46.46.55 SC6: Similarities 12.58 (6.11).25.27.27 SC7: Unusual Uses 13.86 (5.69).37.57 SC8: Utopian Situation 18.14 (4.89).51 SC9: Nicknames 10.86 (5.47) Note. N = 36. Correlation coefficients equal or higher than.34 (.43) reach statistical significance at.05 (.01) level. Table 2. Factor Loadings and Communalities of the Creativity Subscales (SC1 SC9) for the Two Orthogonal (Varimax-Rotated) Factors SC1 SC2 SC3 SC4 SC5 SC6 SC7 SC8 SC9 Factor 1.45.56.66.66.54.83.78 Factor 2.83.83.54.60 h 2.70.62.53.49.48.69.71.68.50 Note. Factor loadings <.30 are not displayed. Table 3. Correlation (Spearman s rho) of the Verbaler Kreativitätstest Factor Scores With Intelligence and Personality Structure Factor Intelligence Neuroticism Extraversion Openness Agreeableness Consciousness Anxiety 1.00.18.56*.27.22.03.11 2.48*.14.24.19.10.08.07 *p <.01. the other hand, Factor 1 was found to be highly associated with extraversion (r =.56, p <.001), whereas Factor 2 was not (r =.24, p =.16). This clear differentiation with regard to their relation to psychometrically determined intelligence and extraversion further strengthens the discriminant validity of both factors. Hence, in the further analyses, the first factor is referred to as creative ideational fluency and the second factor as intelligent ideational fluency. Matching of Experimental Groups The matching of experimental groups was realized with respect to all available variables with special focus on creativity and intelligence. No significant mean differences between the experimental groups were found with respect to creativity: ideational fluency total score, F(2, 33) = 0.27, p =.76; creative ideational fluency, F(2, 33) = 0.94, p =.40; intelligent ideational fluency, F(2, 33) = 0.98, p =.39; and originality, F(2, 33) =.13, p =.88; or intelligence: F(2, 33) = 1.17, p =.32. No group differences were found for any of the personality factors neuroticism, extraversion, openness, agreeableness, and conscientiousness: F(2, 33) = 0.48, 0.16, 0.52, 0.23, 0.73, respectively; p =.62,.85,.60,.80,.49, respectively. For trait anxiety, the group difference was close to reaching statistical significance, F(2, 33) = 2.69, p =.08, η 2 =.14; with the VC training group tending to be more anxious than the other two groups. Furthermore, there was no group difference with respect to age, F(2, 33) = 0.35, p =.71; or gender, χ 2 (2, N = 36) = 0.80, p =.67. Mean group dif- 322 Creativity Research Journal

Ideational Fluency Training ferences with respect to the intertest interval just failed to reach statistical significance, F(2, 33) = 2.60, p =.09, η 2 =.14; with the control group having a slightly shorter time span between pretest and posttest (M = 22.57 days) than the training groups (M = 27.27 and 26.36 days for VC and FC training, respectively). Training Activities Participants equally for both trainings spent on average 23.78 min (SD = 4.41) on a training unit, F(1, 20) = 0.00, p >.99; resulting in a total training time of 214.02 min (SD = 39.71). However, training time slightly decreased in the course of the training from 24.40 min per unit (SD = 4.47) in the first training half to 23.01 min (SD = 4.74) in the second half, F(1, 20) = 4.92, p =.04, η 2 =.20). To compare productivity (i.e., ideas entered per training unit) between both training variants as a function of training time,a2 2ANOVA forrepeated measures was calculated considering the between-subject variable training type and the within-subjects variable training half. Results indicate that in the VC training more ideas were generated (93.4 ideas per training unit, SD = 28.5) than in the FC training (65.5 ideas per training unit, SD = 16.4), F(1, 20) = 8.54, p =.008, η 2 =.30. This implies that the exercises used in the VC training were easier (i.e., allowing for more answers within the same time). The analysis also yielded a significant interaction, F(1, 20) = 6.38, p =.02, η 2 =.24; indicating that idea productivity increased for the VC training, whereas it decreased for the FC training. However, these mean differences failed to reach statistical significance in the posttest (Tukey s test). The decrease of the productivity of the FC training may be due to the decrease of training time in the second half as reported earlier. With that in mind, the idea rate as a relative measure (namely the number of ideas per time in minutes) was calculated and used as a dependent variable in the ANOVA for repeated measures. In the VC training, generally more ideas per minute were generated (M = 3.97, SD = 1.17) than in the FC training (M = 2.80, SD = 0.64), F(1, 20) = 9.22, p =.007. Again, the interaction reached statistical significance, F(1, 20) = 8.33, p =.008, η 2 =.29; and Tukey s posttests revealed that the idea rate increased within the training for the VC training, whereas it did not for the FC training (see Figure 1). This signifies that in the course of the VC training, Figure 1. Idea rate (ideas per minute) in the course of the two training halves for the verbal creativity (VC) and the functional creativity (FC) training. participants produced an increasingly larger number of ideas per time (+11.2%), whereas the idea rate remained fairly constant for the FC training. Training Feedback The feedback on the training units by the participants on each of the three feedback dimensions (interesting, exhausting, and entertaining) was analyzed with a2 2ANOVA fortraining type and training half. For the dimensions interesting and entertaining, the same result pattern was obtained. The ANOVA for repeated measures yielded a significant main effect of training half: interesting, F(1, 20) = 7.81, p =.01, η 2 =.28; entertaining, F(1, 20) = 4.80, p =.04, η 2 =.19; and a significant interaction of training half with training type: interesting, F(1, 20) = 15.37, p =.001, η 2 =.44; entertaining, F(1, 20) = 9.23, p =.006, η 2 =.32. Tukey s posttests revealed that interactions accounted for the main effects. Both trainings were perceived equally interesting and entertaining in the beginning (first half), but the FC training was perceived less interesting or entertaining in the end (second half). Furthermore, the FC training was perceived slightly more exhausting than the VC training, F(1, 20) = 3.68, p =.07, η 2 =.16. Summing up, the VC training unlike the FC training did not lead to a decreasing motivation in the Creativity Research Journal 323

M. Benedek, A. Fink, and A. C. Neubauer course of training time, as it may result from exhausting exercises. Training Effect on Ideational Fluency The training effects were analyzed by means of an analysis of covariance (ANCOVA) using the posttest score as dependent variable and the pretest score as a covariate; a common procedure for computing pretest posttest comparisons (Tabachnik & Fidell, 2001). The intertest interval served as a further covariate as it tended to differ between the groups (see matching section) and might be responsible for an incomparable influence of the practice effect between the groups. To assess the effects of training on ideational fluency, an ANCOVA for the VKT total fluency score (i.e., sum score, aggregated over the 9 VKT subscales) as well as a multivariate analysis of covariance (MANCOVA) for the extracted factors creative and intelligent ideational fluency were computed. The factor scores for the posttest were calculated by means of the coefficient matrix that resulted in the analysis of the criterion (pretest). The ANCOVA for ideational fluency just failed to reach statistical significance, F(2, 30) = 2.83, p =.07, η 2 =.15; but, however, the means appear to indicate a slight increase for the VC training as compared to the control group (see Figure 2; in other Figure 2. Ideational fluency (Verbaler Kreativitätstest total score) at pre- and posttest for the verbal creativity (VC) training, the functional creativity (FC) training, and the control group. words, after the VC training participants produced 11.4% more ideas on the tasks of the creativity test). The MANCOVA for the two fluency factors slightly failed to reach significance at the multivariate level, F(4, 60) = 2.49, p =.053, η 2 =.14. At the univariate level, significant training effects were found only for creative ideational fluency, F(2, 29) = 4.35, p =.02, η 2 =.23, Cohen s d = 0.54 (see Figure 3a). Tukey s posttests revealed an increase of creative ideational fluency for the VC training but not for the FC training as compared to the control group. For intelligent ideational fluency, no significant training effects were observed, F(2, 29) = 0.82, p =.45 (see Figure 3b). Training Effect on Ideational Originality In a next step, we analyzed whether training effects also emerge with respect to the originality of responses. To this end, an ANCOVA was performed on the originality scores. Neither of the trainings had a significant impact on the originality of the ideas, F(2, 30) = 1.16, p =.59. Nevertheless, it can be remarked that posttest originality rather tended to rise compared to the control group. Discussion This exploratory study aimed at investigating the extent to which divergent thinking might be enhanced on the basis of practice realized by means of a computer-based training. Therefore, a variety of divergent thinking tasks that are typically used for the assessment of creativity were implemented into a training software that could easily be installed and used on any home computer. Guided by the observation that VC usually involves a broad range of demands that considerably differ with respect to the involvement of language or speech (ranging from word completions, generating nicknames, to producing original responses in utopian situations), two training variants capturing a verbal (explicitly handling with verbal material) and a functional facet of creativity (speech is only used as medium to express the ideas) were realized. The criterion (i.e., creativity test subscales) was analyzed for dimensionality, and two underlying factors could be identified. One factor turned out to be highly correlated with intelligence (hence intelligent ideational fluency), whereas the other (creative ideational fluency) has 324 Creativity Research Journal

Ideational Fluency Training Figure 3. (a) Creative ideational fluency and (b) intelligent ideational fluency (factor scores) at pre- and posttest for the verbal creativity (VC) training, the functional creativity (FC) training, and the control group. shown to be related to individuals personality (particularly extraversion), although completely unrelated to intelligence. The extraversion creativity relation is in line with some empirical research showing that extraversion is positively related to verbal creative ability (King et al., 1996; Martindale & Dailey, 1996), to self-reported creativity as measured by the creative personality scale (Wolfradt & Pretz, 2001), or to creativity-generating thinking styles (Zhang & Huang, 2001). Basically, the results of this training study indicate that ideational fluency might be enhanced by means of a divergent thinking training, herewith demonstrating the usefulness and the efficacy of the computer-based training program in general. However, this study allows for more specific conclusions. Analyses revealed that the VC training that required participants to exercise with verbal material (e.g., word completion, word composition, or inventing names) has proven to be more effective than the functional training variant, aiming at enhancing creative ideation in a more abstract sense. For the VC training, the increase of the idea rate (+11.2%) already observed in the course of the training nicely matches the increase of ideational fluency (+11.4%) found in the pre posttest comparison. Two possible reasons may account for the lower efficacy of the FC than the VC training variant. First, the obviously more exhausting and less interesting or entertaining FC training (as a function of training time) that has also turned out to be more difficult than the VC training (as reflected in a lower productivity) might have negatively affected training motivation and, accordingly, also the performance in the posttest. Besides the decrease in training motivation, also the content of the training may account for the inefficacy of the training. The apparently more abstract FC training was composed of exercises that demanded participants to think of functions, features, or attributes of given objects or situations skills that may less easily be trained and that are hardly captured by conventional creativity tests. Possibly, the trained basic skills could not be transferred into content-related (test) performance that easily. In this case, future trainings including basic FC training could be followed by a second phase of content-related training guiding the trainee how to convert abstract divergent thinking skills into creative performance under the given circumstances. Attempts to detect training effects with respect to the originality of ideas have although the means conform to our expectations also failed. However, interpretations concerning the training efficacy on ideational originality should be treated more cautiously because originality assessments were only obtained for two (out of 9) subscales. This study also showed that training effects appear to be specific to the more divergent or free-associative demands of creativity (referred to as creative ideational fluency); whereas on the rather convergent, intelligence-related facet of creativity (referred to as intelligent ideational fluency), no training effects were Creativity Research Journal 325

M. Benedek, A. Fink, and A. C. Neubauer found. The specific effect of the VC training on creative ideational fluency corresponds to an effect size index of d = 0.54 similar to those typically reported in creativity training literature (see Rose & Lin, 1984; Scott et al., 2004a). Unlike the majority of training procedures that usually involve multiple treatments ranging from cognitive, to social, to motivational factors, the results of this study suggest that creative ideational fluency can be effectively enhanced already on the basis of practice. As conventional training programs often are quite time consuming and extensive, training via computers may represent a valuable and powerful alternative. Such trainings can be conducted more objectively and in a more economical, less time-consuming way (also in a geographical sense). Furthermore, the employment of computer-based training programs may also offer a neutral environment; diminishing evaluation apprehension when generating unusual, original, or even exceptional ideas. In this sense, computer-based divergent thinking trainings may be effective and valuable for research as well as for employment in practice. References Amelang, M., & Bartussek, D. (1997). Differentielle Psychologie und Persönlichkeits-forschung [Differential psychology and personality research, 4th ed.]. Stuttgart, Germany: Kohlhammer. Amthauer, R., Brocke, B., Liepmann, D., & Beauducel, A. (2001). Intelligenz Struktur Test 2000 R (I S T 2000 R) [Intelligence-Structure-Test]. Göttingen, Germany: Hogrefe. Borkenau, P., & Ostendorf, F. (1993). NEO Fünf Faktoren Inventar (NEO FFI) nach Costa und McCrae [NEO Five-Factor Inventory]. Göttingen, Germany: Hogrefe. Clements, D. H. (1991). Enhancing creativity in computer environments. American Educational Research Journal, 28, 173 187. Clements, D. H. (1995). Teaching creativity with computers. Educational Psychology, 7, 141 161. Cliatt, M. J., Shaw, J. M., & Sherwood, J. M. (1980). Effects of training on the divergent thinking abilities of kindergarten children. Child Development, 51, 1061 1064. Costa, P. T., Jr., & McCrae, R. R. (1992). Revised NEO Personality Inventory and NEO Five Factor Inventory Professional Manual. Odessa, FL: Psychological Assessment Resources. Csikszentmihalyi, M. (1996). Creativity: Flow and the psychology of flow and invention. New York: HarperCollins. DeRosa, D. M., Smith, C. L., & Hantula, D. A. (in press). The medium matters: Mining the long-promised merit of group interaction in creative idea generation tasks in a meta-analysis of the electronic group brainstorming literature. Computers in Human Behavior. Diehl, M., & Stroebe, W. (1987). Productivity loss in brainstorming groups: Toward the solution of a riddle. Journal of Personality and Social Psychology, 53, 497 509. Diehl, M., & Stroebe, W. (1991). Productivity loss in idea generating groups: Tracking down the blocking effect. Journal of Personality and Social Psychology, 61, 392 403. Feist, G. J. (1998). A meta-analysis of personality in scientific and artistic creativity. Personality and Social Psychology Review, 2 (4), 290 309. Fink, A., & Neubauer, A. C. (in press). EEG alpha oscillations during the performance of verbal creativity tasks: differential effects of sex and verbal intelligence. International Journal of Psychophysiology. Guilford, J. P. (1950). Creativity. American Psychologist, 5, 444 454. Jäger, A. O., Süß, H.-M., & Beauducel, A. (1997). Berliner Intelligenzstruktur Test [Berlin Intelligence Structure Test]. Göttingen, Germany: Hogrefe. Kaufmann, G. (2003). What to measure? A new look at the concept of creativity. Scandinavian Journal of Educational Research, 47, 235 251. King, L. A., McKee Walker, L., & Broyles, S. J. (1996). Creativity and the Five-Factor Model. Journal of Research in Psychology, 30, 189 203. Klauer, K. J. (2001). Handbuch Kognitives Training [Handbook of cognitive training, 2nd ed.]. Göttingen, Germany: Hogrefe. Krampen, G. (1993). Diagnostik der Kreativität [Diagnostics of creativity]. In G. Trost, K. Ingenkamp, & R. S. Jäger (Eds.), Tests und trends (jahrbuch der pädagogischen diagnostik) (Vol. 10, pp. 11 39). Weinheim, Germany: Beltz. Laux, L., Glanzmann, P., Schaffner, P., & Spielberger, C. D. (1981). Das State Trait Angstinventar. Theoretische Grundlagen und Handanweisung [The State-Trait-Anxiety Inventory: Theoretical basics and manual]. Weinheim, Germany: Beltz. Lipsey, M. W., & Wilson, D. B (1993). The efficacy of psychological, educational, and behavioral treatment. Confirmation from meta-analysis. American Psychologist, 48, 1181 1209. Martindale, C., & Dailey, A. (1996). Creativity, primary process cognition and personality. Personality and Individual Differences, 20, 409 414. Nickerson, R. S. (1999). Enhancing creativity. In R. J. Sternberg (Ed.), Handbook of creativity (pp. 392 430). Cambridge, England: Cambridge University Press. Pinsonneault, A., Barki, H., Gallupe, R. B., & Hoppen, N. (1999). Electronic brainstorming: The illusion of productivity. Information Systems Research, 10, 110 133. Plucker, J. A., & Renzulli J. S. (1999). Psychometric approaches to the study of human creativity. In R. J. Sternberg (Ed.), Handbook of creativity (pp. 35 61). Cambridge, England: Cambridge University Press. Rindermann, H., & Neubauer, A. C. (2004). Processing speed, intelligence, creativity, and school performance: Testing of causal hypotheses using structural equation models. Intelligence, 32, 573 589. Rose, L. H., & Lin, H. J. (1984). A meta-analysis of long-term creativity training programs. Journal of Creative Behavior, 18, 11 22. 326 Creativity Research Journal

Ideational Fluency Training Runco, M. A. (1999). Divergent thinking. In M. A. Runco & S. R. Pritzker (Eds.), Encyclopedia of creativity (p. 577 582). San Diego, CA: Academic. Runco, M. A. (2004). Creativity. Annual Review of Psychology, 55, 657 687. Schoppe, K. (1975). Verbaler Kreativitätstest (V K T) [Test of verbal creativity]. Göttingen, Germany: Hogrefe. Scott, G., Leritz, L. E., & Mumford, M. D. (2004a). The effectiveness of creativity training: A quantitative review. Creativity Research Journal, 16, 361 388. Scott, G., Leritz, L. E., & Mumford, M. D. (2004b). Types of creativity training: Approaches and their effectiveness. Journal of Creative Behavior, 38, 149 179. Simonton, D. K. (2000). Creativity. Cognitive, personal, developmental, and social aspects. American Psychologist, 55, 151 158. Spielberger, C. D., Gorsuch, R. L., & Lushene, R. E. (1970). Manual for the State Trait Anxiety Inventory. Palo Alto, CA: Consulting Psychologists Press. Sternberg, R. J., & Lubart, T. I. (1999). The concept of creativity: Prospects and paradigms. In R. J. Sternberg (Ed.), Handbook of creativity (pp. 3 15). Cambridge, England: Cambridge University Press. Sternberg, R. J., & O Hara, L. (1999). Creativity and intelligence. In R. J. Sternberg (Ed.), Handbook of creativity (pp. 251 272). Cambridge, England: Cambridge University Press. Tabachnik, B. G., & Fidell, L. S. (2001). Using multivariate statistics (4th ed.). Needham Heights, MA: Allyn & Bacon. Torrance, E. P. (1966). Test of creative thinking. Princeton, NJ: Personnel Press. Wolfradt, U., & Pretz, J. E. (2001). Individual differences in creativity: Personality, story writing, and hobbies. European Journal of Personality, 15, 297 310. Yamamoto, Y., & Nakakoji, K. (2005). Interaction design of tools for fostering creativity in the early stages of information design. International Journal of Human Computer Studies, 63, 513 535. Zhang, L.-F., & Huang, J. (2001). Thinking styles and the five-factor model of personality. European Journal of Personality, 15, 465 476. Creativity Research Journal 327

M. Benedek, A. Fink, and A. C. Neubauer Appendix Verbal Creativity Training Task Example Exercise (Example Solution) Items Word Completion a Generate words starting with/containing/ending with the syllable DE (destruction) 12 Word Composition b Generate word compositions with H-M (hangman, home-monster) 8 Anagrams a Generate words out of the letters ENGLAND (gland, gel) 8 Object Description a Describe orange without using the words: fruit, juice, color (looks similar to a grapefruit) 8 Thematic Associations b Generate associations to the theme nature (wood, climate) 8 Slogans b Find slogans to the new product orange-ice (fruit bomb out of the freezer) 4 Name Invention a Invent names that might belong to the abbreviation ABC (American Business Club) 8 Three-Word Sentences a Generate sentences containing the three words car fish book (I read in a book about fish 8 that can become as large as a car) Nicknames a Find nicknames for coffee (drinkable alarm clock) 8 Total 72 a Task is based on tasks of existing creativity tests (BIS, Jäger, Süß, & Beauducel, 1997; Verbaler Kreativitätstest, Schoppe, 1975) or other well-known divergent thinking tasks. b Task was constructed by the authors. Functional Creativity Training Task Example Exercise (Example Solution) Items Job Characteristics a Name characteristics a judge should have (unbiased, experienced) 8 Basic Features b Name all basic features of an apple (skin, eatable, grows on trees) 10 Similarities a Find possible similarities of knife scissors (sharp, metal) 8 Two Features b What can be red & round (tomato, traffic light) 6 Alterations b What can become yellow (old photos, lemons, traffic light) 8 Abstract Situation a Why does person A wear designer clothes (A is a model) 8 Product Improvement a How could a bicycle be improved (automatic tire pressure control) 8 Unusual Uses a What would be the consequences of a new ice age (Olympic summer games would be 8 abolished) Differences a Find possible differences of apple melon (eatable skin) 8 Total 72 Note. The instructions of the listed example exercises are shortened and translated from German. a Task is based on tasks of an existing creativity tests (BIS, Jäger, Süß, & Beauducel, 1997; Verbaler Kreativitätstest, Schoppe, 1975; Torrance Tests of Creative Thinking, Torrance, 1974) or other well-known divergent thinking tasks. b Task was constructed by the authors. 328 Creativity Research Journal

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