Facilitating creative thinking in the classroom: Investigating
the effects of plants and the colour green on visual and verbal
Sylvie Studente a, Nina Seppala b, Noemi Sadowska a
a) Regent’s University London, United Kingdom
b) University of Lincoln, United Kingdom
We report upon a study concerned with the effect of exposure to live plants, views to nature and the
colour green upon visual and verbal creativity. The study reported in this paper was undertaken with
108 business students at a British University who were randomly allocated to one of the three
conditions. The control group were placed in a classroom with no plants present and blinds drawn to
block view to natural settings, the ﬁrst experimental group were placed in a classroom with no plants
present, blinds drawn to block views to nature but completed the creativity tasks on green paper. The
second experimental group were placed in the same room as the other groups, but were surrounded
by live plants and had views to nature through the large classroom windows. All participants
completed two creativity tasks; a visual creativity task and a verbal creativity task. Visual creativity
was assessed using a modiﬁed version of Amabile’s Consensual Assessment Technique (Amabile,
1982). Verbal creative was assessed using a modiﬁed scoring method of Guilford’s alternative uses
task developed by Silvia et al. (2008). Findings indicate that access to natural views, plants and the
colour green increase visual creativity, but have no impact on verbal creativity in classroom settings.
The results suggest that creativity is domain speciﬁc and any practical measures taken to enhance
creativity need to be aligned with the target domain.
Keywords: Creativity Learning Nature
The research area of enhancing creativity in educational settings is an area of growing interest (i.e.
Fasko, 2000; Feldhusen & Goh, 1995; Sternberg & Lubart, 1991; Hennessey & Amabile, 1987;
Guilford, 1967; Pithers & Soden, 2000). Creativity research has identiﬁed a number of environmental,
situational and personal factors which affect an individual’s ability to be creative (i.e. Mumford, 2003;
Runco, 2004; Simonton, 2003). This paper reports upon a study which examines the effects of plants
and the colour green upon visual and verbal creativity. Previous research has identiﬁed that creative
thinking can be enhanced by situating individuals in natural settings (Atchley, Strayer, & Atchley,
2012; Atchley et al., 2012; Shibata & Suzuki, 2002) and that exposure to the colour green can also
enhance creative performance (Lichtenfeld, Elliot, Maier, & Pekrun, 2012). However, research into
these areas has been sparse and to date has not been linked to the possible beneﬁcial effects to be
garnered in the classroom. Others (e.g. Friedman & Forster, 2010) have looked at the impact of colour
in expanding or constricting cognitive functions. We build on this research and expand it by studying
the impact of exposure to nature and the colour green on creativity and, more speciﬁcally, the
outcomes of creative functions.
Creativity is widely deﬁned as a behaviour or product that is both novel and useful (Sternberg &
Lubart, 1991). Studies in the area of creativity research have acknowledged that creativity is a ﬁeld of
research which is divided into four parts; the person, the product, press or the creative process
(Rhodes, 1961; Boden, 2004; Csikzentmihalyi, 1996). This widely accepted framework denotes that
creativity can be viewed from one or more of these four perspectives (Runco, 2011; Simonton, 2003).
In this paper we report upon a study with a core focus on ‘creative products’. In this context, creative
products are understood as responses to an open-ended problem. Our focus is upon investigating
conditions which are conducive or prohibitive for creative thinking in the classroom with regard to
views to nature, plants and the colour green.
2. Background motivation
2.1. Towards an understanding of creativity
Although no universal deﬁnition of creativity exists due to its inherently subjective nature, a widely
accepted deﬁnition is that creativity involves: “the ability to produce work that is both novel and
appropriate” (Sternberg, 1998). Traditionally, creativity was viewed as a phenomena attributed to
gifted individuals. A more contemporary and widely accepted perspec-tive is that creativity is
possessed by all (Weisberg, 1993). It is also understood that creativity does not exist in isolation, but
rather is inﬂuenced by individual differences and environmental factors (Amabile, 1996).
The ability to be creative is often perceived as involving divergent thinking as opposed to convergent
thinking, the lat-ter concerning itself with predictable, logical cognitive operations (De Bono, 1967). It
is owing to this reason that divergent thinking and the ability to view situations in a new and novel
way are strongly associated with creativity. Divergent thinking is associated with producing several
solutions to an open ended problem (Guildford, 1967). As well as classiﬁcations of dif-ferent ways of
thinking involved in creativity, differing categories of creativity have also been identiﬁed as verbal
creativity and visual creativity (i.e. Dau-Gaspar, 2013; Zhu, Zhang & Qiu, 2013; Zadeh, Sook-Lei, &
Dandekar, 2012). The term ‘Visual Creativity’ is often deﬁned as the production of novel and useful
visual forms such as; drawing, painting and photography (Dake, 1991). The term ‘Visual Creativity’ is
often used synonymously with the term ‘Figural Creativity’ (Hetrick, Lilly, & Merriﬁeld, 1968;
Dziedziewicz et al., 2013). ‘Verbal Creativity’ is deﬁned as the production of novel and useful
responses in verbal forms such as written and spoken words (Torrance, 1962). A number of studies
have been conducted to investi-gate the similarities and differences between visual and verbal
classiﬁcations of creativity (i.e. Ulger, 2015; Petsche, 1996; Kozhevnikov et al., 2013). Whilst some
scholars have reported a signiﬁcant correlation between visual and verbal creativ-ity (Ulger, 2015;
Hota, 2003), others have reported that no correlation was found (Saw DeMers, 1986; Roskos-
Ewoldsen, Intons-Peterson, & Anderson; Palmiero, Nakatani, Raver, Belardinelli, & vanLeeuwen,
2.2. Creativity and education
The research area of enhancing creativity in educational settings is an area of growing interest (i.e.
Fasko, 2000; Feldhusen & Goh, 1995; Sternberg & Lubart, 1991; Hennessey & Amabile, 1987;
Guilford, 1967; Pithers & Soden, 2000; Runco, 2008; Shaheen, 2010). Research in this area has
explored a number of facets from teaching creative thinking techniques in the classroom (i.e.
Torrance, 1962), developing cognitive tools for creative thinking (i.e. Wissink, 2001; Candy &
Edmonds, 2000), designing learning environments conducive to creativity (Piirto, 2005; Hennessey,
2004; Waugh, 2003) to the assessment of creative thinking (i.e. Runco, 1989; Torrance, 1971).
Although approaches towards creative education differ in focus, they all acknowledge that a student’s
creativity can be stimulated by providing assignments which involve both convergent and divergent
thinking (Karnes et al., 1961; Davis & Rimm, 1985). In addition, research also suggests that providing
students with insight problems within which they are required to brainstorm uses of everyday objects
in unusual ways can assist with facilitating problem restructuring which in turn facilitates the creative
process (Jacobs & Dominowski, 1981; Martinsen, 1995).
Creativity research has identiﬁed a number of environmental, situational and personal factors which
affect an individual’s ability to be creative (i.e. Mumford, 2003; Runco, 2004; Simonton, 2003).
Runco & Johnson, 2002 state that in terms of education, the creative development of students is
largely dependent upon the environment in which they exist. Extending upon this point we seek to
investigate the effect of plants and the colour green upon creative thinking. Prior research into these
areas is discussed below.
2.3. Psychological and physiological effects of plants and natural settings
There is a growing body of research exploring the effects of views to nature and the inclusion of plants
and greenery on people (i.e. Shibata & Suzuki, 2004). Research in the area reports that access to the
natural environment has both physical and psychological beneﬁts (Grinde & Patil, 2009) such as;
promoting health and recovery (Bell, Greene, Fisher, & Baum, 2001; Kaplan, 2001), promoting well-
being in the work place (Heerwagen & Orians 1986; Shibata & Suzuki, 2001), reduction of tension and
stress (Ulrich et al., 1991), and increased attention and focus (Taylor, Kuo, & Sullivan, 2001). Atchley
et al. (2012) report that creative thinking can be improved through situating individuals in natural
settings. Atchley et al. attribute this to exposure to natural stimuli such as greenery which is low-
arousing and emotionally positive.
Shibata & Suzuki, 2002 report similar ﬁndings from a study within which participants performed
better on creative tasks when situated in rooms decorated with foliage such as plants than those
without. Shibata & Suzuki conclude that nature provides a source of inspiration and stimulation for
creativity. Similar ﬁndings are also reported by Hesselink et al.(2004) whose study identiﬁed an
enhancement of creative task performance by participants situated in rooms with foliage compared to
those situated in rooms without.
These positive effects of plants on task performance may be attributed to by the relaxing connotations
of views to nature and plants (Williams & Cary, 2002; Ulrich, Lunden, & Etinge, 1993). In regard to
creativity literature, a number of scholars emphasise that creative thinking is impaired under stressful
conditions (Talbot, Cooper, & Barrow, 1992; Farr & Ford, 1990; Amabile, 1983), and that creative
ideas arise when an individual is in a state of relaxation (Claxton, 1998; Lehrer, 2012; Kaplan, 2012).
This may also explain the positive effects of plants upon creativity. However, these ﬁndings have yet to
be linked to education in terms of beneﬁts for classroom learning.
2.4. The colour green and creativity
Scholars have reported there exists little research conducted into the psychological effects of colour
(Fehrman & Fehrman, 2004; Whitfeild & Wiltshire, 1990), except for that relating to colour
preferences (i.e. Franklin et al., 2010; Hurlbert & Ling, 2007). There are however researchers who
have demonstrated that the colour red can be perceived as a cue for danger (Elliot & Maier, 2007). In
contrast, the colour blue is associated with peace and tranquillity and has been shown to increase
creativity (Mehta and Zhu (2009). For example, when participants were asked to design new
children’s toys after being shown pictures of different toy parts, the participants were more creative
when the parts had been coloured blue rather than red (ibid.). Friedman & Forster, 2010 argued that
this is because colours can tune the scope of attention by signalling the nature of the situation as a
threatening or a calm situation.
Contemporary research has suggested that similarly to the colour blue, the colour green has a positive
inﬂuence on creativity. An example arises from a study conducted by Lichtenfeld et al., 2012 who
report that a brief glimpse of the colour green prior to completing a task enhances creative
performance. Research has identiﬁed that physiological responses to the colour green include a feeling
of calmness, peace and positive emotions (Clarke & Costall, 2008) and this is attributed to the colour’s
strong associations with nature (Hutchings, 2004; Wierzbicka, 1990). Aside from the study by
Lichenfeld et al., there exists little research into the relationship between the colour green and
enhanced creative thinking, but based on the earlier research on the positive impact of colour blue on
creativity because of its association with tranquillity, it can be predicted that the colour green also
The research reported in this paper seeks to extend upon previous studies relating the effects of
exposure to live plants and the colour green on creative thinking. To date, research into these areas
has been sparse and has not been applied to educational settings. This study will investigate the effects
of exposure to live plants and the colour green on visual and verbal classiﬁcations of creativity in
3. Research aims and objectives
The purpose of this research is to investigate whether exposure to live plants and the colour green has
a positive impact upon visual and verbal creative thinking in classroom settings. The hypotheses to be
investigated through this study are as follows:
(H1) Students who are exposed to live plants and views to nature in the classroom will demonstrate a
higher level of creativity on given tasks than those who are not.
(H2) Students who complete given tasks on green paper will demonstrate a higher level of creativity
than those completing tasks on generic white paper.
4.1. Participants and procedure
108 business students from a British University participated in the study. Each participant was
randomly assigned to one of the control or experimental groups. Participants within the control group
were seated in a classroom with no plants present and blinds drawn to block views to natural settings.
Participants allocated to experimental group one were placed in a classroom surrounded by live plants
and blinds were opened providing a view to a green area. Participants allocated to experimental group
two were placed in a classroom with no plants present and blinds drawn to block views to nature, but
were provided with the creativity tasks on green paper. These groupings and participant numbers are
summarised in Table 1.
The participants were used to blinds being closed and opened regularly for adjusting room
temperatures and preventing sun from creating reﬂections on computer screens; only few of the
rooms in the old Victorian building have air-conditioning.
A visual and a verbal creativity task was completed uniformly by participants across conditions. The
tasks used are explained below.
4.2. Data collection protocols
4.2.1. Verbal creativity test
Verbal creativity was measured using the Alternative Uses Task (GAUT) proposed by Guildford as a
method of measuring various criteria of creativity, such as ﬂuency, ﬂexibility, and originality
(Guildford, 1967). GUAT is a standard test which is used to measure divergent thinking in verbal
creativity. The test requires participants to list uncommon uses for everyday objects and is widely used
in the area of creativity research (i.e. Chermahini, Hickendorff, & Hommel, 2012; Lewis & Lovatt,
2013; Pretz & Link, 2008). GUAT measures the ﬂuency of participants in idea generation, across both
speed and number of ideas. In other words, participants who could generate a greater number of ideas
in a given period of time would have an advantage in creative efforts.
Participants were instructed to “Name all of the uses you can think of for a brick”. It is noteworthy to
state that this task is not a measure of performance as such, but of speciﬁc problem-solving ability.
Simonton (1998) believed that the greater the rate of idea generation, the larger the pool of items to
work with and the greater production of originality. There is, however, a positive relationship between
the amount of time individuals spend on idea generation and originality (Christensen, Guilford, &
Wilson, 1957; Getzels & Csikszentmihalyi, 1976). Participants were given two minutes to complete this
4.2.2. Visual creativity test
After completing the verbal task, visual creativity was measured by asking the participants to complete
the ‘30 Circles Test’ devised by McKim (1980). Participants were provided with a sheet of paper
containing 30 circles and instructed to incorporate the circles into a drawing and to use as many of the
circles as possible in three minutes. Participants in the control and experimental groups followed this
5. Results analysis
5.1. Verbal creativity results
Results from the verbal creativity task were evaluated using a modiﬁed scoring method of Guilford’s
standard criteria developed by Silvia et al. (2008). Three criteria were used to assess verbal creativity;
uncommon, remote and clever. The scoring of participant’s responses was conducted by three
independent evaluators. The scoring was performed on a scale of 1 to 5, where the value of 5
represented the highest level of creativity. An intra-class correlation analysis was used to assess the
consistency of creativity scorings across the three evaluators. The co-efﬁcient of 0.089 (single
measures) and .226 (average measures) (p = .02) signalled from slight to fair agreement across the
evaluators, which is acceptable for evaluating subjective topics such as creativity outputs (Landis &
Koch, 1977). The consistency of evaluations based on the three criteria (uncommon, remote, clever)
was also acceptable with Cronbach’s alpha of 0.81. Further analysis based on a between-items ANOVA
test showed that there was a signiﬁcant effect when the three criteria were used to analyse the
creativity outputs (F = 109.74, p < 0.00).
As can be seen in Table 2, the results of a one-way ANOVA analysis suggest that there was a signiﬁcant
effect when the control group was compared to the green paper condition. The overall value for
creativity was lower in the green paper condition (1.59) than in the control group (1.73) (F = 4.387, p =
.04). Creativity was therefore judged to be lower in the green paper group than in the control group.
There was no signiﬁcant effect when the control group was compared to the plant group. The results
of the ANOVA analysis were consistent across the three criteria used to measure verbal creativity,
except for ‘cleverness’ which varied little across the different conditions. The results suggest, in
contrast to our hypothesis, that exposure to plants and the colour green do not increase creativity for
verbal tasks. In fact, verbal creativity can be higher in normal conditions.
5.2. Visual creativity results
Results from the visual creativity task were assessed using a modiﬁed version of the consensual
assessment technique established by Amabile (1982). This involved the three evaluators
independently rating the drawings according to eight dimensions. This technique was selected, due to
its focus on evaluating creative products. In using the technique we followed the four procedural
requirements outlined by Hennessey et al. (2011). These requirements are as follows; evaluators
should be experienced in using the technique. Secondly, evaluators must make their evaluations
independently. They must not be trained to agree with each another; and are not to be given criteria
for judging creativity; and must not confer in their assessments. Thirdly, evaluators should be
instructed to rate products relative to one another. Finally, each judge should view the products in a
different random order. The evaluators who participated in the evaluations had previously used the
consensual assessment technique (where all evaluations were made independently), following
instructions to rate the drawings as relative to one another, whilst given the drawings in a different
random order. An important aspect of this technique is that evaluators should make their assessment
independently using their own subjective deﬁnition of creativity (Amabile, 1982; Baer & McKool,
2009; Kaufman, Lee, Baer & Lee; Hickey, 2001).
In this technique, interjudge reliability is regarded as an equivalent to construct validity, i.e. if
evaluators independently agree that a product is creative, it is accepted as such. The technique is
reported to offer a more authentic method towards assessing creative products than factoral
approaches and is a widely accepted method for assessing creativity (Sternberg & Lubart, 1991;
Hennessey, 1994). In our study, the rating between the three evaluators was consistent with an intra-
class correlation co-efﬁcient of 0.425 (single measures) and 0.689 (average measures) (Landis &
As expected, levels of creativity differed between the control and experimental groups. Evaluations
were made on a scale of 1 to 5 where the value of 5 represented the highest level of creativity.
Creativity scores were higher in the plants condition than in the control group. In the plants condition,
creativity was evaluated on average at the level of 2.13 points against 1.78 points in the control group
where plants were not present (p = 0.01). As expected, exposure to the colour green increased
creativity and was evaluated at 2.05 points (p = 0.05). There was no statistically relevant difference
between the plants and green paper conditions (p = 0.57). The scores for visual creativity are
summarized in Table 3. The results are presented for each judge separately as well as across judges.
Previous research has suggested that environmental factors have an impact on creativity (Runco &
Johnson, 2002). Schol-ars have attributed these positive effects to the relaxing connotations of views
to nature and plants. However, research into these areas has been sparce and has not been previously
applied to educational settings. A number of studies have demon-strated that views to nature and
exposure to the colour green have a positive effect on the ability to think creatively (Atchley et al.,
2012; Lichtenfeld et al., 2012; Shibata & Suzuki, 2002). The results of our research support the
previous ﬁndings in that they demonstrate a positive connection between nature and visual creativity.
However, our study ﬁndings do not support earlier ﬁndings on the positive impact of nature on other
forms of creativity. Shibata & Suzuki, 2002 reported in their study that indoor plants enhanced
creativity measured through a word association task which resembled the alternative uses task used in
the present study to measure verbal creativity. Even though Shibata & Suzuki’s study applied only to
women, it is contradictory to our results and suggests that environmental manipulation needs to be
precise in order to produce the targeted effect. The quality of access to nature, the creativity task, the
measurement of creativity and other factors can have an effect on the overall impact.
A possible explanation for the differences in results between visual and verbal creativity tasks can be
found in the domain of cognitive science. Research in this area suggests that there are signiﬁcant
differences in the cognitive processing of visual and verbal information (Mayer & Masser, 2003), and
that individuals may have a preference for visual or verbal processing (Childers, Houston, & Heckler,
1985). Furthermore, research suggests that visual and verbal information is processed in two distinct
channels in the brain (Paivio, 1971). Verbal information is processed in the left hemisphere which
specialises in rational, analytical and convergent thinking, whereas, the right hemisphere is often
associated with creativity and divergent thinking (Runco, 2014; Vartanian & Goel, 2005).
Additionally, studies in the area of neuroscience report that the right hemisphere of the brain is
concerned with the processing of visual information and the left with verbal (Kramer, Rosenberg, &
Thompason-Schill, 2009), and that creative thinking often involves bilateral processing (Aziz-Zadeh,
Liew, Dandekar, 2012). This suggests that the verbal task may not have been best matched with
creative thinking, although it is noteworthy to state that Guilford’s Alternative Uses Task is a widely
used measure of creative thinking. Our outcome is congruent with previous studies which have
reported dissociation between visual and verbal creativity (i.e. Shaw & DeMers, 1986; Roskos-
Ewoldsen et al., 1993).
Another explanation may arise in differences in the evaluator’s subjective deﬁnitions of creativity in
assessing the verbal creativity task. Amabile (1996) acknowledges that in some instances it can be
problematic for experts in their ﬁelds, to agree on the level of creativity expressed in creative products.
Furthermore, this outcome might also be explained by the domain speciﬁcity of creativity. Previous
research suggests that creativity consists of both domain speciﬁc and general skills and talents (i.e.
Amabile, 1983; Baer, 2010). For example, an individual might be artistically creative, but not in
everyday chores. Our results indicate that access to nature has a positive impact on the domain of
visual creativity, but not on verbal creativity as operationalised in the alternative uses task. Our
ﬁndings are similar to Baer (1996) research which reported that when creativity training is targeted at
a speciﬁc domain, creativity improves only in this domain, not others. This is substantiated by a
number of scholars who also report that creativity is dependent on domain-speciﬁc skills (Palmiero et
al., 2010; Silvia et al., 2009). More empirical research is needed to establish the domain categories.
The tests used in our research come close to two of the seven general thematic areas identiﬁed by
Kraufman, Cole & Baer, 2009, which are; artistic/visual area and problem solving area, and provide
support to the overall argument that creativity is domain speciﬁc.
In this study, we have extended upon previous research by demonstrating that the inﬂuence of
environmental factors is not uniform for different forms of creativity. The results have clear practical
implications in demonstrating that classroom features can enhance creativity among students. The
visual creativity of students can be increased by incorporating plants in classrooms or ensuring that
classrooms are designed with views to nature. When access to nature is difﬁcult to arrange, using
green coloured paper in classroom tasks can have a similar effect on creativity. It is also possible that
these environmental features have a positive impact on other domains of creativity, but this impact
needs to be investigated in further studies.
We extend acknowledgement to Filia Garivaldis, Isidora Kourti (Regent’s University London) and
Chia-Yu Kou (University College London) for their assistance with the creativity evaluations.
Amabile, T. (1996). Creativity in Context: Update to The Social Psychology of Creativity. Westview
Amabile, T. (1983). The Social Psychology of Creativity. Springer-Verlag; New York.
Amabile, T. (1982). Social psychology of creativity: A consensual assessment technique. Journal of
Personality and Social Psychology, 43, 997–1013. Atchley, R., Strayer, D., & Atchley, P. (2012).
Creativity in the wild: Improving creative reasoning through immersion in natural settings. PLOS
One, 7 (Issue 2).
Aziz-Zadeh, L., Liew, S., & Dandekar, F. (2012). Exploring the neural correlates of visual creativity.
Social Cognitive and Affective Neuroscience, 8, 475–480.
Baer, J. (2010). Is creativity domain speciﬁc? In J. Kaufman, & R. Sternberg (Eds.), In the cambridge
handbook of creativity. New York: Cambridge University Press.
Baer, J., & McKool, S. (2009). Assessing creativity using the consensual assessment. In C. Schreiner
(Ed.), Handbook of assessment technologies, methods, and applications in higher education. Hershey,
Pennsylvania: IGI Global.
Baer, J. (1996). The effects of task-speciﬁc divergent thinking training. Journal of Creative Behaviour,
Bell, P. A., Greene, T. C., Fisher, J. D., & Baum, A. (2001). Environmental psychology (5th ed.). Fort
Worth: Harcourt College Publishers.
Boden, M. (2004). The creative mind: myths and mechanisms (2nd edn.). London: Routledge.
Candy, L., & Edmonds, E. A. (2000). Creativity enhancement with emerging technologies.
Communications of the ACM Special Issue on Personalization Systems, 43(8), 63–65.
Chermahini, S., Hickendorff, M., & Hommel, B. (2012). Development and validity of a Dutch version
of the remote associates task: An item-response theory approach. Thinking Skills and Creativity, 7,
Childers, T., Houston, M., & Heckler, S. (1985). Measurement of individual differences in visual versus
verbal information processing. Journal of Consumer Research, 12(2), 125–134.
Christensen, P., Guilford, J., & Wilson, R. (1957). Relations of creative responses to working time and
instructions. Journal of Experimental Psychology, 3, 82–88.
Clarke, T., & Costall, A. (2008). The emotional connotations of colour: A qualitative investigation.
Colour Research and Application, 33, 406–410.
Claxton (1998) Hare Brain Tortoise Mind: Why Intelligence Increases When you Think Less. London.
Fourth Estate Limited.
Csikzentmihalyi, M. (1996). Creativity: ﬂow and the psychology of discovery and invention. New York:
Dake. (1991). The visual deﬁnition of visual creativity. Journal of Visual Literacy, 1, 99–118.
Dau-Gaspar, O. (2013). Verbal and ﬁgural creativity in contemporary high-school students. Procedia
Social and Behavioural Sciences, 78, 662–666.
Davis, G., & Rimm, S. (1985). Education of the gifted and talented. NJ: Prentice Hall.
Dziedziewicz, D., Oledzka, D., & Karwowski, M. (2013). (295.013) Developing 4 to 6 year old
children’s ﬁgural creativity using a doodle-book program. Thinking Skills and Creativity, 9, 85–95.
De Bono, E. (1967). New think: the use of lateral thinking in the generation of new ideas. New York:
Elliot, A. J., & Maier, M. A. (2007). Color and psychological functioning. Current Directions in
Psychological Science, 16, 250–254.
Farr, J., & Ford, C. (1990). Human hypothalamus-pituatary-adrenal axis responses to acute
psychological stress in laboratory settings. Neuroscience and Biobehavioural Reviews, 36, 91–96.
Fasko, D. (2000). Education and creativity. Creativity Research Journal, 13(3), 317–327.
Feldhusen, J., & Goh, B. (1995). Assessing and accessing creativity: An integrative review of theory,
research and development. Creativity Research Journal, 8, 231–247.
Fehrman, K., & Fehrman, C. (2004). Colour: the secret inﬂuence. NJ: Prentice Hall.
Franklin, A., Bevis, L., Ying, Y., & Hulbert, A. (2010). Biological componenets of colour preference in
infancy. Developmental Science, 13, 346–354. Friedman, R. S., & Forster, J. (2010). Implicit affective
cues and attentional tuning: An integrative review. Psychological Bulletin, 136(5), 875–893.
Getzels, J., & Csikzentmihalyi, M. (1976). The creative vision: A longitudinal study of problem ﬁnding
in art. New York: John Wiley.
Grinde, B., & Patil, G. G. (2009). Biophilia: Does visual contact with nature impact on health and well-
being? International Journal of Environmental Research and Public Health, 6, 2332–2343.
Guilford, J. (1967). Creativity: Yesterday, today and tomorrow. Journal of Creative Behaviour, 1, 3–14.
Heerwagen, J. H., & Orians, G. H. (1986). Adaptations to windowlessness: A study of the use of visual
decor in windowed and windowless ofﬁces. Environment and Behavior, 18, 623–639.
Hennessey, B. A. (2004). Creativity, classrooms, culture, and communication. In John Houtz (Ed.),
Review of the educational psychology of creativity (49) (pp. 761–763). Contemporary Psychology: APA
Review of Books.
Hennessey, B. A. (1994). The consensual assessment technique: An examination of the relationship
between ratings of product and process creativity. Creativity Research Journal, 7(2), 193–208.
Hennessey, B., & Amabile, T. (1987). Creativity and Learning. Washington DC: NEA Professional
Hennessey, B. A., Amabile, T. M., & Mueller, J. S. (2011). Consensual Assessment. In M. A. Runco, &
S. R. Pritzker (Eds.), Encyclopedia of Creativity (vol. 1) (Second Edition, vol. 1, pp. 253–260). San
Diego: Academic Press.
Hesselink, J, Duijn, B, Bergen, S, Hooff, M & Cornelissen, E. (2004) Plants enhance productivity in
the case of creative work. [online]. Available from:
Hetrick, S., Lilly, R., & Merriﬁeld, P. (1968). Figural creativity, intelligence, and personality in
children. Multivariate Behvioural Research, Vol 3(2)
Hickey, M. (2001). An application of amabile’s consensual assessment technique for rating the
creativity of children’s musical compositions. Journal of Research in Music Education, 49(3), 234–
Hota, A. (2003). Creativity-Cultural Perspective. Discovery Publishing House.
Hurlbert, A., & Ling, Y. (2007). Biological components of sex differences in colour preference. Current
Biology, 17, 623–625.
Hutchings, J. (2004). Colour in folklore and tradition. Colour Research and Application, 29, 57–66.
Jacobs, M., & Dominowski, R. (1981). Learning to solve insight problems. Bulletin of the Psychonomic
Society, 17, 171–174.
Kaplan, M. (2012) Why great ideas emerge when you aren’t trying. Nature: Interational Wekly Journal
of Science. [online]. Available from: http://www.nature.com/news/why-great-ideas-come-when-you-
Kaplan, R. (2001). The nature of the view from home: Psychological beneﬁts. Environment and
Behavior, 33, 507–542.
Karnes, M., McCoy, G., Zehrback, R., Wollersheim, J., Clarizio, H., Costin, L., & Stanley, L. (1961).
Factors associated with under achievement and overachievement of intellectually gifted children.
Community Unit Schools: Champaign IL.
Kaufman, J., Lee, J., Baer, J., & Lee, S. (2007). Captions, consistency, creativity, and the consensual
assessment technique: New evidence of reliability. Thinking Skills and Creativity, 2, 96–106.
Kramer, D., Rosenberg, L., & Thompason-Schill, S. (2009). The neural correlates of visual and verbal
cognitive styles. The Journal of Neuroscience, 29(12), 3792–3798.
Kraufman, J., Cole, J., & Baer, J. (2009). The construct of creativity: Structural model for self-
reported creativity ratings. Journal of Creative Behaviour, 43, 119–132.
Kozhevnikov, M., Kozhevnikov, M., Yu, C., & Blazhenkova, O. (2013). Creativity, visualisation abilities
and cognitive style. British Journal of Educational Psychology, 83, 196–209.
Lehrer, J. (2012). Imagine: how creativity works. New York: Houghton Mifﬂin Harcourt Publishing.
Lewis, C., & Lovatt, P. (2013). Breaking away from set patterns of thinking: Improvisation and
divergent thinking. Thinking Skills and Creativity, 9(9), 46–58. Lichtenfeld, S., Elliot, A., Maier, M., &
Pekrun, R. (2012). Fertile green: green facilitates creative performance. Personality and Social
Psychology Bulletin, 38(6), 784–797.
Martinsen, O. (1995). Cognitive styles and experience in solving insight problems: Replication and
extension. Creativity Research Journal, 8, 291–298. Mayer, R., & Masser, L. (2003). The Facets of
visual and verbal learners: Cognitive ability, cognitive style and learning preference. Journal of
Educational Psychology, 95(4), 833–846.
McKim, R. (1980) Experiences in Visual Thinking. Monterey; Brooks/Cole.
Mehta, R., & Zhu, R. (2009). Blue or red? Exploring the effect of color on cognitive task performances.
Science, 323, 1226–1229.
Mumford, M. (2003). Where have we been, where are we going? Taking stock of creativity research.
Creativity Research Journal, 15, 107–120.
Paivio, A. (1971). Imagery and verbal processes. New York: Holt, Rinehart, and Winston.
Palmiero, M., Nakatani, C., Raver, D., Belardinelli, M., & vanLeeuwen, C. (2010). Abilities within and
across visual and verbal domains: How speciﬁc is their inﬂuence on creativity? Creativity research
Journal, 2(4), 369–377.
Petsche, H. (1996). Approaches to verbal, visual and musical creativity by EEG coherence analysis.
International Journal of Psychophysiology, 145–159. Piirto, J. (2005). The creative process in poets.
In J. Kaufman, & J. Baer (Eds.), Creativity in domains: faces of the muse. (pp 1–20). Parsippany, NJ:
Pithers, R., & Soden, R. (2000). Creative thinking in education. Educational Research, 43(3), 237–
Pretz, J., & Link, J. (2008). The creative task generator: A tool for generation of customized web-
based creativity tasks. Behaviour Research Methods, 40(4), 1129–1133.
Rhodes, M. (1961). An analysis of creativity. The Phi Delta Kappan, 42(7), 305–310.
Roskos-Ewoldsen, B., Intons-Peterson, M., & Anderson, R. (1993). Imagery, creativity and discovery:
a cognitive perspective. Elsevier,
Runco, M. (2014). Creativity: theories and themes: research, development and practice. Elsiver.
Runco, M. (2008). Creativity and Education. New Horizons in Education, Vol 56(No 1).
Runco, M. (2004). Creativity. Annual Review of Psychology, 55, 657–687.
Runco, M. A. (1989). Parent’s and teacher’s ratings of the creativity of children. Journal of Social
Behaviour and Personality, 4, 73–83.
Runco, M., & Johnson, D. (2002). Parent’s and teachers implicit theories of creativity: A cross-cultural
perspective. Creativity Research Journal, 14(3), 427–438.
Shaheen, R. (2010). Creativity and education. Creative Education, Vol 1(No. 3), 166–169.
Shaw, G., & DeMers, S. (1986). The relationship of imagery to originality, ﬂexibility and ﬂuency in
creative thinking. Journal of Mental Imagery, 10(1), 65–74. Shibata, S., & Suzuki, N. (2004). Effects of
an indoor plant on creative task performance and mood. Scandinavian Journal of Psychology, 45,
373–381. Shibata, S., & Suzuki, N. (2002). Effects of foliage plant on task performance and mood.
Journal of Environmental Psychology, 22(3), 265–272.
Shibata, S., & Suzuki, N. (2001). Effects of indoor foliage plants on subject’s recovery from mental
fatigue. North American Journal of Psychology, 3, 385–396. Silvia, P., Kaufman, J., & Pretz, J. (2009).
Is creativity domain speciﬁc? Latent class models of creative accomplishments and creative self-
descriptions. Psychology of Aesthetics, Creativity, and the Arts, 3, 139–148.
Silvia, P., Winterstein, B., Willse, J., Barona, C., Cram, J., Hess, K., & Richard, C. (2008). Assessing
creativity with divergent thinking tasks: Exploring the reliability and validity of new subjective scoring
methods. Psychology of Aesthetics, Creativity and the Arts, 2(2), 68–85.
Simonton, D. (2003). Scientiﬁc creativity as constrained stochastic behavior: The integration of
product, person and process perspectives. Psychological Bulletin, 129, 475–494.
Simonton, D. K. (1998). Donald Campbell’s model of the creative process: Creativity as blind variation
and selective retention. Journal of Creative Behavior, 32, 153–158.
Sternberg, R. (1998). The nature of creativity: contemporary psychological perspectives. New York:
Cambridge University Press.
Sternberg, R., & Lubart, T. (1991). Creating creative minds. Phi Delta Kappan, 72, 608–614.
Talbot, R., Cooper, C., & Barrow, S. (1992). Creativity and stress. Creativity and Innovation
Management, 1(4), 183–193.
Taylor, A., Kuo, F., & Sullivan, C. (2001). Coping With ADD: the surprising connection to green play
settings. Environment and Behavior, 33(Number 1), 54–77.
Torrance, E. P. (1971). Technical manual for the creative motivation scale. Report. Georgia studies of
creative behaviour. In University of Georgia. Torrance, E. (1962). Testing and creative talent.
Educational Leadership, 20, 7–10.
Ulger, K. (2015). The structure of creative thinking: visual and verbal areas. Creativity Research
Journal, 27(1), 102–106.
Ulrich, R. S., Lunden, O., & Etinge, J. L. (1993). Effects of exposure to nature and abstract pictures on
patients recovery from heart surgery. Psychophysiology, 1(7).
Ulrich, R., Simons, B., Losito, E., Fiorito, M., Miles, M., & Zelson, M. (1991). Stress recovery during
exposure to natural and urban environments. Journal of Environmental Psychology, 11, 201–230.
Vartanian, O., & Goel, V. (2005). Task constraints modulate activation in right ventral lareral
prefrontal cortex. NeuroImage, 27, 927–933.
Waugh, A. (2003) Thinking and Creating. [online]. Available from:
Weisberg, R. (1993). Creativity: beyond the myth of genius. New York: Freeman.
Whitfeild, T., & Wiltshire, T. (1990). Colour psychology: a critical review. Genetic, Social and General
Psychology Monographs, 116, 385–411.
Wierzbicka, A. (1990). The meaning of colour terms: Semantics, culture and cognition. Cognitive
Linguistics, 1, 99–150.
Williams, K., & Cary, J. (2002). Landscape preferences, ecological quality, and biodiversity protection.
Environment and Behaviour, 34(2), 257–274. Wissink, G. (2001). Creativity and cognition: a study
within the framework of cognitive science, artiﬁcial intelligence and the dynamical system theory.
Department of Psychology, University of Amsterdam: Doctoral Dissertation.
Zadeh, L., Sook-Lei, L., & Dandekar, F. (2012). Exploring the neural correlates of visual creativity.
Social Cognitive and Affective Neuroscience, http://dx.doi.org/10.1093/scan/nss021
Zhu, F., Zhang, Q., & Qiu, J. (2013). Relating inter-individual differences in verb creative thinking to
cerebal structures: An optimal voxel-based morphometry study. PLoS One,