1. Abstract
Microcomputer Previous playfulness research has investigated
Playfulness: playfulness as both state and trait phenomena.
For example, Webster et aL (1993) examined
flow, the state of playfulness in a specific human-
Stable or i
computer interaction, while Martocchio and Web-
ster (1992) used a trait-based approach, con-
sidering playfulness a characteristic of individuals.
Dynamic Trait? This research extends the investigation of play-
fulness as an individual trait by using a longitudinal
study to examine its temporal and situational sta-
Susan E. Yager bility.
University of North Texas
The Computer Playfulness Scale (Webster &
Martocchio, 1992) was administered four times
Leon A. Kappelman over the course of a five-week summer session to
University of North Texas students enrolled in a computer-literacy course,
once at the beginning of the class and then
following completion of three milestones in the
Glenn A. Maples course work. The playfulness instrument was
University of North Texas assessed for internal consistency, unidimen-
sionality, and temporal and situational stability.
Victor R. Prybutok The evidence indicates that the measurement is
University of North Texas reliable. The primary question of trait stability
(stable versus dynamic) was examined in several
ways, supporting the conclusion that playfulness
is a stable trait. The implica~ons of these findings
and suggested further research are discussed.
Keywords: playfulness, longitudinal study, traits,
cognitive playfulness, cognitive spontaneity, com-
puter playfulness scale.
ACM Categories: H.1.2, J.4, K.6.1
Introduction
Increasingly, MIS designers are able to add
"playful" items to systems. Flying toaster screen
i
savers, Porky Pig's voicing of audible cues, and
desktops constructed in themes tied to Disney
characters inhabit a growing number of comput-
ers. Moreover, new multimedia capabilities and
the advent of virtual reality offer new methods to
further increase microcomputer playfulness. Con-
current with these new playfulness-enhancing
technologies, system designers have growing
abilities to customize and individualize systems.
i
Increasingly sophisticated individual agents have
begun to lurk in cyberspace. Application pack-
ages and operating systems have almost univer-
sally adopted user-adjustable graphical user inter-
faces (GUIs) which are frequently customizable.
These new capabilities underscore the need to
understand better the role of playfulness in
The DATA BASE for Advances in Information Systems - - Spring 1997 (Vol. 28, No. 2) 43

2. system design and training. Information systems conditions of personality traits are temporal sta-
professionals face a critical issue in understand- bility and cross-situational consistency (e.g.,
ing when playfulness augments the learning or Veenhoven, 1994).
operating of a system, when playfulness may
serve as a distraction, and how the appropriate In the MIS literature, traits are defined as static
use of playfulness may depend on individual and aspects of human information-processing charac-
system differences. teristics affecting a broad range of variables
(Bostrom, Olfman, & Sein, 1990). General traits
Previous playfulness research has investigated refer to comparatively stable characteristics of
playfulness as both state and trait phenomena. individuals that are relatively invariant to situ-
For example, Webster et al. (1993) examined ational stimuli (Webster & Martocchio, 1992).
flow, the state of playfulness in a specific human- Cognitive traits are based on processing prefer-
computer interaction, while Martocchio and ences and include cognitive styles (Bostrom,
Webster (1992) used a trait-based approach, OIfman, & Sein, 1990). The effect of individual
considering playfulness a characteristic of indivi- traits on computer usage has a rich history in the
duals. This research extends the investigation of IS literature, including recent work concentrating
playfulness as an individual trait by using a on computer self-efficacy (e.g., Compeau &
longitudinal study to examine its temporal and Higgins, 1995), computer anxiety (e.g., Fajou,
situational stability. 1996), and conscientiousness (e.g., Stewart,
Carson, & Cardy, 1996).
Background
MIS professionals seeking to match both the
The importance of individual differences in the
systems and the training methods for these
design and operation of information systems can
systems to individual differences should not only
be traced to the earliest frameworks of information
consider differences among individuals but also
systems. For example, "an information system
whether these differences are dynamic. In par-
consists of, at least, a PERSON of a certain
ticular, professionals should consider whether
PSYCHOLOGICAL T Y P E . . . "(Mason & Mitroff,
users' attitudes or behaviors might change as they
1972, p. 475) is one of the earliest frameworks for
gain exposure to a system. If the individual traits
defining information systems. In addition to other
are not stable (either temporally or situationally),
effects psychological types or traits have, indi-
the problem of matching these traits to system
vidual differences may affect users' learning about
characteristics becomes decidedly more difficult.
new software; and some researchers perceive a
critical need to match training methods to these
individual differences (e.g., Bostrom, Olfman, & Cognitive Playfulness
Sein, 1990).
Playfulness is considered a multi-faceted con-
Over the last ten years, psychologists seeking to struct, encompassing five dimensions: cognitive
explain individual differences in personality and spontaneity, social spontaneity, physical spon-
behavior increasingly subscribe to trait theories. taneity, manifest joy, and sense of humor (Barnett,
Furthermore, the most popular of these psycho- 1990; Barnett, 1991; Lieberman, 1977). These
logical trait theories is the five factor model (FFM). five dimensions are illustrated as follows: cog-
This personality model (based on the dimensions nitive spontaneity is the imaginative play of young
of neuroticism, extraversion, openness, agree- children and the combinatorial play of creative
ableness, and conscientiousness) is charac- adults; social spontaneity is the ability to be
terized as "a basic discovery" (McCrae & John, comfortable in a group setting and to move freely
1992), the basis for the field of personality and in and out of such a social structure; physical
individual differences (Buss, 1989), and sufficient spontaneity is evident in unstructured play
to characterize both normal and abnormal activities such as jumping rope; manifest joy bears
behavior (Widiger, 1993). However, despite the different labels such as pleasure and happiness;
general acceptance of trait theory as key in and sense of humor results from surprising,
understanding human behavior, there is no incongruous, or novel events, whether the in-
generally accepted definition of the term "per- dividual is the producer or the consumer
sonality trait." Personality traits are generally (Lieberman, 1977). In recent publications and for
thought of as long-.term predispositions to certain this study, cognitive spontaneity in human-com-
behaviors or attitudes. Two generally accepted puter interactions is considered a surrogate for
44 The DATA BASE for Advances in Information Systems-- Spring 1997 (Vol. 28, No. 2)

3. "cognitive playfulness" (Martocchio & Webster, The Study
1992). Cognitive playfulness has been studied as
a trait that influences ease of microcomputer use Subjects and Measures
and resultant learning. "Employees higher in cog-
nitive playfulness demonstrated higher test The subjects were volunteer undergraduate
performance and more positive affective out- students enrolled in a computer-literacy course at
comes than those lower in cognitive playfulness" a moderately large southwestern university and
(Martocchio & Webster, 1992, p. 553). In addi- received course credit for their participation. Each
tion, those higher in playfulness are expected to of seventy-seven subjects was asked to complete
exercise and develop skills through exploratory four iterations of Webster and Martocchio's (1992)
behaviors (Miller, 1973), resulting in improved Computer Playfulness Survey instrument (see the
performance or increased learning (Martocchio & Appendix) over a five-week summer session, once
Webster, 1992). at the beginning of the course and again following
the completion of three milestones in the course
There are, however, potential drawbacks of
work. The administrations are referred to as 1)
playfulness, such as requiring a longer time to
initial administration, a baseline on the first day of
complete tasks (Sandelands, 1988), over-involve-
class; 2) Windows, following introduction to and
ment (Csikszentmihalyi, 1975), and increased
project completion using the Microsoft Windows
opportunities for non-productive play (Nash,
operating environment; 3) Word, following intro-
1990). Organizations must be aware that playful-
duction to and project completion using Microsoft
ness may result in wasted time; but it may also
Word; and 4) Excel, following introduction to and
result in more effective, more productive, and
project completion using Microsoft Excel.
higher-quality results (Starbuck & Webster, 1991 ).
Computer Playfulness Scale The playfulness score was determined by adding
together (i.e., a linear sum) the responses of each
The Computer Playfulness Scale (CPS) de- individual for the seven items identified by Web-
veloped by Webster and Martocchio (1992) is a ster and Martocchio (1992) as comprising the
self-reported instrument. It is designed to mea- playfulness construct: spontaneous, unimagin-
sure microcomputer playfulness, a situation- ative, flexible, creative, playful, unoriginal, and
specific individual characteristic which represents uninventive. This was done after adjusting for the
the degree of cognitive spontaneity in micro- three items that were reverse-scored, compen-
computer interactions (Webster & Martocchio, sating for yea-saying or nay-saying individuals
1992). Furthermore, microcomputer playfulness who have a more or less global tendency to agree
demonstrates higher predictive efficacy for train- or disagree (Alreck & Settle, 1995).
ing effectiveness (learning or understanding),
compared to previously utilized computer anxiety Two primary goals of this research were to test
and computer attitudes (Webster & Martocchio, the temporal stability and situational consistency
1992). Test-retest reliability has proven strong of the playfulness construct. Psychologists
(correlation .85, p<.001) in previous studies using evaluating the temporal stability of other person-
the CPS (Webster & Martocchio, 1992). ality traits have selected periods as short as
several days or as long as several years in
The Problem evaluating trait stability. Since the focus of this
research was playfulness during microcomputer
Because of the growing ability to manipulate the
training, a five-week training period was used. In
playfulness of computer systems and training, the
addition to being similar in length to other trait
Computer Playfulness Scale measure represents
studies (e.g., Stewart, Carson, & Cardy, 1996),
a potentially powerful tool allowing system design-
this period meets or exceeds the length of time of
ers to address the interaction of system and
training in most industry training environments.
individual playfulness. However, before system
designers can accommodate the construct of play- End-user microcomputer training is subject to
fulness, its trait nature must be more fully ex- constraints that make microcomputer playfulness
plored. In particular, this research seeks to estab- less subject to environmental variation than many
lish the temporal stability and situational consis- other personality constructs. One of the most
tency of the playfulness construct. important variants in computer training is task,
The DATA BASE for Advances in Information Systems - - Spring 1997 (Vol. 28, No. 2) 45

4. more specifically the type of software to be playfulness scores over time or across situations.
learned. Three of the most common software First this hypothesis was tested by examining the
groups are operating systems, word processing, correlations among scores obtained by the same
and spreadsheets (e.g., Jones & Berry, 1995). person on multiple administrations of the same
This research tests across these software groups instrument (Anastasi, 1988). This is the same
as cross-situational variables. statistical procedure used to perform test-retest
reliability of instruments. Reliability coefficient (r)
Instrument Reliabillity: Intemal Consistency values of at least 0.70 indicate that the results are
and Unidimensionality stable over time (Litwin, 1995). However, caution
must be exercised when interpreting these results.
Internal consistency for the seven-item play-
Practice effect may falsely inflate the correlations
fulness instrument was assessed with Cronbach's
(Litwin, 1995). As individuals become familiar
(1951) coefficient alpha, "probably the best es-
with the items on a survey, they may simply an-
timate of internal consistency" (Crano & Brewer,
swer based on their memory of how they
1973, p. 230). The results are shown in Table 1
answered previously (Litwin, 1995). The length of
below. Based on the greater than 0.80 rule-of-
the instrument, which included at least three other
thumb (Crano & Brewer, 1973; Nunnally, 1978;
instruments in each administration, was designed
Blau, 1988), these coefficients indicate that the
in part to minimize this problem.
seven-item playfulness instrument appears to
have high internal consistency. Test-retest reli-
To confirm further that the learning effect was not
ability was also examined and is discussed under
a serious threat to the experiment, the authors
hypothesis testing.
analyzed the change in variance by individuals
across administrations. In the event of a sig-
Another method for assessing internal consis-
nificant learning bias, one would expect de-
tency is to determine whether items "share only
creasing variance as answers became ~more pat"
one common focus" (Crano & Brewer, 1973, p.
(that is, individual's responses would increasingly
231). The unidimensionality of the scale was
mirror the previous set of responses). The data
evaluated by means of the factorial validity
showed a slight increase in variance from the first
(Kappelman, 1995) of the seven-item scale using
inter-item variance measure (based on individual
the SPSS/PC+ FACTOR procedure (SPSS, Inc.,
differences between administrations 1 and 2) to
1993). Each of the four administrations of the
the last (based on differences between admin-
playfulness instrument resulted in all seven items
istrations 3 and 4). Although this analysis does
loading on e single factor. The first eigenvalues, not preclude a learning effect between the first
percent of variance explained by the first eigen- and second administrations, in the opinion of the
value, ratio of the first eigenvalue to the second,
authors if such an effect was significant it would
and range of factor Ioadings are shown in Table 2
likely increase in subsequent administrations.
for each administration. Eigenvalues (3.888 to
Thus, learning effect did not appear to be a sig-
5.143) and percent of variance (55.5% to 73.5%)
nificant threat to this investigation.
are relatively large for all of the four adminis-
trations, indicating a consistently high percentage These reliability coefficients between adminis-
of variance explained by the first factor. The ratio trations of the same instrument represent cor-
of the first to the second eigenvalues is also relations between the linear sums. Since it may
substantial, ranging from 4.260:1 to 7.649:1. The be possible for two consecutive administrations to
factor loading should attain a minimum of 0.50
exhibit little difference while cumulative dif-
(Straub, 1989) to be considered as part of a ferences over several administrations may indi-
factor. Each of the administrations surpasses that cate a substantial difference, each result was
level on all seven items. Unidimensionality is compared with all other administrations (see
supported by these results, especially by the large
Table 3). The playfulness scores remained
factor Ioadings. substantively invariant across the four adminis-
Hypothesis Testing trations, supporting the stable trait charac-
terization of the playfulness construct.
Previous research has stated that playfulness is
a trait. This study tested the hypothesis that play- The correlations appeared to weaken between
fulness is a trait and there will be no change in non-consecutive administrations over time,
46 The DATA BASE for Advances in Information Systems-- Spring 1997 (Vol. 28, No. 2)

5. Administration Cronbach's Alpha
Initial (n = 60) .9029
Windows (n = 62) .8825
Word (n = 60) .8656
Excel (n = 49) .9383
Table 1. Intemal Consistency Coefficients
Administration Eigenvalue Percent of Ratio of Range of Factor
Variance First:Second Loadings
Initial 4.454 63.6 5.643:1 .65400 - .90428
Windows 4.182 59.7 4.377:1 .61597 -. 85471
Word 3.888 55.5 4.260:1 .70640 -. 81484
Excel 5.143 73.5 7.649:1 .68962 - .88752
Table 2. Evidence of Unidimensionality (Factor Analysis)
Administration Correlation Significance
Initial with Windows (n = 52) .842 .000
Initial with Word (n = 50) .767 .000
Initial with Excel (n = 41 ) .669 .000
Windows with Word (n = 54) .822 .000
Windows with Excel (n = 45) .783 .000
Word with Excel (n = 44) .901 .000
Table 3. Correlations between Administrations
bringing into question either the test-retest that the results were changing. If the playfulness
reliability over short time periods or raising the trait is dynamic, one would expect to see changes
possibility that playfulness is dynamic and not a occur over time. However, if it is stable, one
stable trait. Comparisons were made of the means would expect to see the effect by subject. The
and standard deviations (see Table 4) using a participants themselves (SUBJECTS) accounted
one-way analysis of variance (ANOVA), and no for the variance (F = 13.178, p = .000), while
significant difference in playfulness was found for different administrations (TIME) did not have a
any of the four administrations (p = 0.867). These significant effect (F = 1.300, p = 0.276). The vari-
results indicate that playfulness meets both of the ation in an individual's results can be attributed to
stability requirements for personality traits - the individual's playfulness trait, not the timing of
stability across both time and situations. the administration.
To test the playfulness-as-stable-trait hypothesis, Conclusions
a two-way ANOVA (see Table 5) was computed to The results of this longitudinal study indicate that
determine whether it was by subject or by time playfulness is a stable trait. The playfulness
The DATA BASE for Advances in Information Systems w Spring 1997 (Vol. 28, No. 2) 47

6. Administration N Mean St. Dev.
Initial 60 21.767 9.039
Windows 62 22.339 8.248
Word 60 22.250 8.171
Excel 49 21.061 9.355
Table 4. Means and Standard Deviations of all Administrations
Sourceof Sum of Squares DF Mean Square F Significance
Vadation off
Main Effects 14762.725 75 196.836 12.698 .000
Time 60.469 3 20.156 1.300 .276
Su~ects 14707.905 72 204.276 13.178 .000
Explained 14762.725 75 196.836 12.698 .000
Residual 2402.781 155 15.502
To~l 17165.506 230 74.633
Table 5. ANOVA Results
score is consistent, measures a single factor, and and knowledge of a representative spectrum of
remains somewhat static. Moreover, means and software applications.
standard deviations were stable over time..This
study also supports; the reliability of Webster and The resulting stable trait characterization of the
Martocchio's (1992) operationalization of the playfulness construct has important implications
playfulness construct. Their seven-item Computer to both IS academics and researchers. Although
Playfulness Scale demonstrated internal con- prior research associates playfulness with in-
sistency, unidimen:sionality, and temporal and creased learning and performance, our research
situational stability as evidenced by Cronbach's suggests that the stability of the playfulness trait
alpha, factor validity, and test-retest correlations. will make attempts to manipulate individual play-
fulness unlikely to succeed. We would suggest
Previous researchers have suggested adapting that the playfulness construct may best be
training methods based on trainee characteristics accommodated by matching system and individual
(e.g., Bostrom, Olfman, & Sein, 1988; Bostrom, playfulness.
Olfman, & Sein, 1990; Wexley, 1984). Past
studies of training methods have been incon- MIS designers or trainers who wish to utilize the
clusive; and external effects of those methods on playfulness trait should be able to do so by
training effectiveness were posited to depend on performing a one-time playfulness assessment
other factors, including characteristic attributes of rather than conducting longitudinal measures on
the trainees (Tannenbaum & Yukl, 1992). More individuals. This is good news both to prac-
research is needed to develop and understand titioners who are trying to build effective systems
training method adaptations that best utilize the and to researchers trying to further investigate the
stable trait nature of playfulness. playfulness construct. In particular, it greatly
simplifies playfulness experimental design as it
Contributions and Limitations of the Work renders individual playfulness traits stable rather
than dynamic.
This research supports the temporal stability and
situational consistency of the playfulness con- The research limitations include those traditionally
struct. The subjects of this study demonstrated a acknowledged in conjunction with the use of
marked stability in the playfulness trait as they student subjects. More to the point, this research
gained experience in their computing environment investigates the stability of the playfulness trait in
48 The DATA BASE for Advances in Information Systems-- Spring 1997 (Vol. 28, No. 2)

7. a training environment of intermediate duration Bostrom, R. P., Olfman, L., and Sein, M. K.
(five weeks) and varying software to test stability (1988). "End-User Computing: A Research
across situations. Further investigation is war- Framework for Investigating the Train-
ranted into the stability of the playfulness trait ing/Learning Process," Human Factors in
across longer periods (as might be encountered Management Information Systems, Norwood,
by end-users of systems) and across alternative NJ: Ablex Publishing Corporation.
situations. For instance, training type and style Bostrom, R. P., Olfman, L., and Sein, M I~
could influence individual playfulness. (1990). "The Importance of Learning Style in
End-User Training," MIS Quarterly, Vol. 14,
Further research should build on the stability of No. 1, pp. 101-119.
the playfulness trait by examining the outcomes of Buss, A. H. (1989). "Personality as Traits,"
manipulating playfulness in training. For instance, American Psychologist, Vol. 44, pp. 1378-
the authors are currently using treatments 1388.
differing by playfulness items to investigate the Compeau, D. R., and Higgins, C.A. (1995).
interaction between individuals' playfulness traits "Computer Self-Efficacy: Development of a
and the playfulness of the computing environment Measure and Initial Test," MIS Quarterly, Vol.
in determining outcomes such as training satis- 19, No. 2, pp. 189-211.
faction, user satisfaction, and individual perfor- Crano, W. D., and Brewer, M. B. (1973).
mance measures. Principles of Research in Social Psychology,
Further research should be conducted into mech- New York: McGraw-Hill.
anisms by which playfulness enhances training or Cronbach, L. J. (1951). "Coefficient Alpha and
system performance. The proper matching of the Internal Structure of Tests, ~ Psychometrika,
system and user playfulness to manipulate user Vol. 16, pp. 297-334.
mood offers one interesting avenue of research. Csikszentmihalyi, M. (1975). Beyond Boredom
A continuous stream of research has associated and Anxiety, San Francisco: Josey-Bass.
mild mood elevation with enhanced creative Eckblad, M., and Chapman, L. J. (1986).
thinking (e.g., Richards, 1993; Eckblad & Chap- "Development and Validation of a Scale for
man, 1986; Schuldberg, 1990), improved problem Hypomanic Personality," Journal of Abnormal
solving (Greene & Noice, 1988), and better Psychology, Vol. 3, pp. 214-222.
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Proper matching of system and/or training play- www.edfac.usyd.edu.au/projects/comped/Fa-
fulness with individual playfulness characteristics jou.html>
may offer an opportunity to manipulate user mood Greene, T. R., and Noice, H. (1988). "Influence
with a potential outcome of better system per- of Positive Affect Upon Creative Thinking and
formance. Problem Solving in Children," Psychological
Reports, Vol. 63, pp. 895-898.
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Richards, R. (1993). "Seeing Beyond: Issues of North Texas. Her dissertation research focuses
Creative Awareness and Social Respon- on the use of technology to enable virtual organi-
sibility," Creativity Research Journal, Vol. 6, zations. In addition to her twenty years of industry
pp. 165-183. experience, she has taught information systems
Sandelands, L. E. (1988). "Effects of Work and courses, served as an academic advisor and
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Schuldberg, D. (1990). "Schizotypal and Hypo- partmental, college, university, and regional
manic Traits, Creativity, and Psychological levels. E-mail: yager@cobaf.unt.edu
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218-230. Leon Kappelman, is an associate professor of
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and Information Technology, Vol. 1, No. 1, pp. sity of North Texas. His professional expertise
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Stewart, G. L., Carson, K. P., and Cardy, R. L. information systems development and main-
(1996). "The Joint Effects of Conscien- tenance, change management and technology
tiousness and Self-Leadership Training on transfer, project management, and information
Employee Self-Directed Behavior in a Service systems assessment and benchmarking. He has
Setting," Personnel Psychology, Vol. 49, No. 1, published dozens of articles and several books
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2, pp. 147-169. E-mail: kapp@unt.edu
Tannenbaum, S. I., and Yukl, G. (1992). "Training
and Development in Work Organizations," Glenn Maples, is an associate professor at Our
Annual Review of Psychology, Vol. 43, pp. Lady of the Lake University. He earned his Ph.D.
399-441. at the University of North Texas. His dissertation
Veenhoven, R. (1994). "Is Happiness a Trait? examines quality measurement issues in informa-
Tests of the Theory That a Better Society Does tion systems. He is an ASQC Certified Quality
Not Make People Any Happier," Social Indi- Engineer. Active areas of research include MIS
cators Research, Vol. 32, No. 2, pp. 101-160. quality, database security and computation of
Webster, J., and Martocchio, J. J. (1992). "Micro- control process standards.
computer Playfulness: Development of a E-mail: maplg@lake.ollusa.edu
50 The DATA BASE for Advances in Information Systems-- Spring 1997 (Vol. 28, No. 2)

9. Victor Prybutok is professor of management sci-
ence and the Director of the Center for Quality
and Productivity at the University of North Texas.
He is a Senior Member of the American Society
for Quality Control (ASQC), an ASQC Certified
Quality Engineer, and an ASQC Certified Quality
Auditor. He has published over 35 journal articles
and 50 proceedings in journals that include Oper-
ations Research, the American Statistician, Com-
munications in Statistics, and the Journal of Pro-
duction and Inventory Control.
E-mail: prybutok@unt.edu
The DATA BASE for Advances in Information Systems - - Spring 1997 (Vol. 28, No. 2) 51

10. Appendix
The following questions ask you how you would characterize yourself when using microcomputers. For each
adjective below, please circle the number on the answer sheet that best matches a description of yourself
when you interact with a microcomputer.
Strongly agree 1 2 3 4 5 6 7 Strongly Disagree
Spontaneous 1 2 3 4 5 6 7
Conscientious 1 2 3 4 5 6 7
Unimaginative 1 2 3 4 5 6 7
Experimenting 1 2 3 4 5 6 7
Serious 1 2 3 4 5 6 7
Bored 1 2 3 4 5 6 7
Flexible 1 2 3 4 5 6 7
Mechanical 1 2 3 4 5 6 7
Creative 1 2 3 4 5 6 7
Erratic 1 2 3 4 5 6 7
Curious 1 2 3 4 5 6 7
Intellectually Stagnant 1 2 3 4 5 6 7
Inquiring 1 2 3 4 5 6 7
Routine 1 2 3 4 5 6 7
Playful 1 2 3 4 5 6 7
Investigative 1 2 3 4 5 6 7
Constrained 1 2 3 4 5 6 7
Unoriginal 1 2 3 4 5 6 7
Scrutinizing 1 2 3 4 5 6 7
Uninventive 1 2 3 4 5 6 7
Inquisitive 1 2 3 4 5 6 7
Questioning 1 2 3 4 5 6 7
52 The DATA BASE for Advances in Information Systems-- Spring 1997 (Vol. 28, No. 2)