The Impact of Setting,Time of Day,and Giftedness on Divergent Thinking Test Scores

Abstract

Students may not express their creativity uniformly, across all settings and under all conditions. Creativity is sensitive to expected evaluations, for example, and likely to vary when the individual is alone, in a small group, or in a large group. Quite a bit of research has demonstrated that certain conditions can be created to support creative thinking by students. The present study focused on two key factors that may impact divergent thinking (DT) performance: classroom setting and time of the day. DT is the capacity to generate ideas along diverse cognitive pathways. It can be contrasted with convergent thinking, where cognitive processes lead to one correct or conventional solution. Divergent thinking, in contrast, often leads to original and unconventional ideas. The sample consisted of 160 female students from Saudi Arabia (80 gifted and 80 nongifted) in grades 10 to 12. Two DT tests were administered: the Alternative Uses Test (AUT) and the Figural Divergent Thinking Test. A repeated measures ANOVA indicated that verbal and figural fluency performance was higher in the art room than in the regular classroom. Moreover, the difference in verbal flexibility performance between the two settings was larger for nongifted students than gifted students. The differences between the settings in figural and verbal originality were not statistically significant, although gifted and nongifted students both performed better in the art room. Another repeated measure ANOVA was performed to test whether or not there was a difference in DT performance related to the time of the school day (first vs. second half). The results showed no differences between DT performance due to the time of the day except for verbal originality in the regular classroom during the second half of the school day. Limitations and future research of the current study are discussed.

Keywords

divergent thinking school environment time of the day gifted students constructionist education

Students may not express their creativity uniformly, across all settings such as home, school, the natural environment (Abdulla Alabbasi, Runco, et al., 2024; Runco et al., 2023) and under all conditions (Abraham, 2022; Amabile, 1996). Creativity is sensitive to expected evaluations, for example, and likely to vary when the individual is alone, in a small group, or in a large group (Amabile, 1990; Rubenson & Runco, 1995). Quite a bit of research has demonstrated that certain conditions can be created to support creative thinking by students (Acar et al., 2020; Runco, 1986; Said-Metwaly et al., 2020; Wallach & Kogan, 1965). Even the physical characteristics of the setting can have an impact on divergent thinking (DT) and creativity test performances (Deng et al., 2016; Lee & Lee, 2023; McCoy & Evans, 2002). The present study focused on two key factors that may impact DT performance: classroom setting and time of the day. The rationale for focusing on these two factors instead of numerous other possible conditions (e.g., lighting, colors, window view, presence of plants, daylight; see Lee & Lee, 2023 for a review on the relationship between physical environment and creativity) was that the effects of such factors were investigated before (Küller et al., 2006; Lee & Lee, 2023; Lucius & Damberg, 2024). The impact of classroom setting and time of the day was empirically examined in the current study, which also considered the influence of giftedness.

Classroom Setting

Extant research showed that immediate setting may have an influence on creativity and DT performance. Batey et al. (2021) showed that the presence of a large nature poster where testing was conducted resulted in a greater DT performance, evaluated by raters who were blind to the study design than in a setting without such a poster even when openness personality trait and mood were controlled. In another study by Ichimura (2023), the perceived environment was manipulated by the use of virtual reality (VR) to examine the differences in performance on the Alternative Uses Test (AUT). In Experiment 1, participants viewing a 360° video with immersive head-mounted displays scored higher on the AUT than those viewing the same video on a computer screen or viewing a real-world laboratory. In Experiment 2, participants viewing a 360° video of a visually open coast (i.e., Okinawan coast) scored higher on the AUT than those viewing a visually closed laboratory. The findings suggest that visually open VR environments viewed through head-mounted displays promote DT. More broadly, these studies show that changes in the immediate environment can influence DT performance. However, they did not focus on classroom settings. There is also research that compared the influence of different settings on children’s DT performance. In one such study, Guegan et al. (2020) exposed 96 children (grades 1 through 5) to one of three virtual settings (a replica of the headmistress’s office, a replica of their schoolyard, and a dreamlike environment) while completing the DT tests. They found that children generated more original ideas in the dreamlike and playful environments compared to the headmistress’s office. This finding of the benefit of a playful environment is consistent with earlier research showing that DT was more likely in “game-like” rather than “test-like” assessment conditions (Paek et al., 2021; Wallach & Kogan, 1965).

There is also research that considered real classroom or educational settings. Dudek et al. (1993) examined the impact of “classroom atmosphere” on students’ performances on the Torrance Test of Creative Thinking (TTCT). The classroom atmosphere had a significant impact. A related line of research shows the impact of classroom atmosphere on students’ creativity is the difference between students’ performance on DT in traditional (formal schools) vs non-traditional (open schools) (Day, 1974; Lewis, 1980; Thomas & Berk, 1981). Lewis (1980) reported that kindergarten children from open classrooms scored higher in Wallach and Kogan’s (1965) verbal and figural DT tests than their peers in non-open classrooms. The same conclusion was reached by Thomas and Berk (1981), where second-grade children scored higher in an intermediate formal-informal continuum on the figural form of the TTCT.

More recent studies identified specific elements of the school learning environment associated with students’ creativity. These include the physical environment, sense of place, learner engagement, perceived naturalness, and the classroom’s learning climate (Blomberg & Kallio, 2022; Piya-Amornphan et al., 2020; Richardson & Mishra, 2018; Yeh et al., 2022; Zhang et al., 2023). In their scoping review on the association between the physical environment and creativity, which included 33 articles, Lee and Lee (2023) listed 15 physical attributes (e.g., light, furniture, indoor plants, and sounds) and seven spatial types (e.g., open spaces, mixed-use spaces, and production labs) that can support creativity. Related to the current study, Shah and Gustafsson (2021) compared the performances of 7 to 11-year-old students when they had received a verbal DT test (i.e., AUT) and a figural test, namely the Test for Creative Thinking–Drawing Production (TCT-DP) in either an art room or a formal classroom. They reported that verbal originality and total TCT-DP scores were higher in the art room than in the classroom. Based on the abovementioned findings, we hypothesized that DT performance would differ based on classroom setting (i.e., art room vs. regular classroom).

Time of the Day

Time of day was examined in the present research because it may have an impact on creative thinking. This follows from Breslin’s (2019) report that the time of the day influenced group creativity exercises. Across two studies with 36 and 18 groups, respectively, where performance was compared between morning and afternoon, Breslin (2019) found midday to be the optimal time for fluency. In contrast, originality was not influenced by the time of the day. Aiello (2022) found similar results: DT performance was higher around lunchtime and afternoon than morning for both originality and effectiveness. Explanations for the effect of time of day typically focus on cognitive or mental fatigue (Boksem et al., 2005; Goldstein et al., 2007; Mullette-Gillman et al., 2015), and sometimes attention as it may suffer after students have worked for several hours, doing their academic work (Lufi et al., 2011; Sievertsen et al., 2016). There are practical implications, if time of day is indeed associated with performance on tests of creative potential. If performances are in fact better during the first half of the school day, for example, and if there is an interest in determining students’ maximal performances, examiners could schedule accordingly.

The Current Study

The present research was modeled after Shah and Gustafsson’s (2021) study. In addition to examining the setting (art room vs. regular classroom), this investigation compared (a) gifted and nongifted students and (b) early in the school day vs. late in the school day in terms of the impact of setting.

Shah and Gustafsson found that verbal originality and total TCT-DP scores were higher in the art room than in the classroom. These are interesting findings, but there are several limitations because they collected data in a British Catholic Primary School, for example, and their sample size was only moderate. There were 111 students placed in one of two groups (art classroom or regular classroom). Although Shah and Gustafsson used both Urban’s TCT-DP and Guilford’s AUT tests, the latter only contained one item (a ping pong ball). Second, Shah and Gustafsson (2021) study did not use equal sample sizes as this is one of the univariate analysis of variance (ANOVA) assumptions. Related limitations include (a) the use of a univariate ANOVA when the observations are not independent (the same measures were administered once in the art room and then in the classroom) and (b) using univariate ANOVA when there is more than one independent variable. This investigation considered an equal sample size in each condition: (a) art room vs. regular classroom, and (b) first vs. second half of the school day (see Table 1 for the study design). The main four advantages of the current study are: (a) use of repeated measure ANOVA rather than separate univariate ANOVAs, (b) controlling for fluency confound, (c) use of two tasks from each test (i.e., the verbal and the figural DT tests), and (d) scoring DT for figural fluency, flexibility, and originality rather than relying on a composite figural test score (i.e., TCT-DP). Aside from these improvements, replication studies are very informative, especially when conducted in different cultures (Makel & Plucker, 2014).

Table 1.

A Description of the Study Design.

Groups	Day	DT test	1st vs. 2nd half	Place
Group 1 (N = 40)	Wednesday	1 verbal and 1 figural	First half	Regular classroom
Gifted	Thursday	1 verbal and 1 figural	First half	Art room
Group 3 (N = 40)	Wednesday	1 verbal and 1 figural	Second half	Regular classroom
Gifted	Thursday	1 verbal and 1 figural	Second half	Art room
Group 2 (N = 40)	Monday	1 verbal and 1 figural	First half	Regular classroom
Nongifted	Tuesday	1 verbal and 1 figural	First half	Art room
Group 4 (N = 40)	Monday	1 verbal and 1 figural	Second half	Regular classroom
Nongifted	Tuesday	1 verbal and 1 figural	Second half	Art room

Research Hypotheses

H1: Gifted students would perform better than the nongifted students on measures of creative potential.

H2: Gifted students would not be influenced as much as their nongifted peers by the time of day.

The logic for (b) is much like that used by Abdulla Alabbasi, Runco, et al. (2024) in their research comparing creativity at home and school. They found that nongifted students performed better when they were at home than when they were at school. Gifted students, on the other hand, performed more equivalently at home and at school. In a different study, Rayneri et al. (2006) investigated the relationship between classroom environment, learning styles, and academic achievement. They found that the classroom environment did not influence gifted students’ academic performance even when it was compatible with their learning styles.

Method

Participants

The current sample consisted of 160 female students (80 gifted and 80 nongifted) in grades 10 to 12. It was not possible to collect data from male students since education is segregated in Saudi Arabia, and the author who collected the data is a female. The mean age for the total sample was 15.84 (SD = 0.91), the mean age for the gifted sample was 15.90 (SD = 0.99), and the mean age for the nongifted sample was 15.79 (SD = 0.84). The mean Grade Average Point (GPA) for the gifted sample was 96.84 out of 100 (SD = 1.92; range: 92 to 100) and the GPA for the nongifted sample was 81.36 out of 100 (SD = 6.72; range = 60–98). The conventional definition of a gifted student in Saudi Arabia is as follows:

A student who has extraordinary aptitudes and abilities or outstanding performance from the rest of their peers in one or more of the areas valued by society, especially in the areas of mental excellence, educational achievement, creativity and innovation, and special skills and abilities, who are selected according to the specific scientific bases and standards used for this purpose (Alfaiz et al., 2022, p. 3).

The participants (i.e., gifted and nongifted) were randomly selected from one of the high schools in the Eastern region of Saudi Arabia. According to the National Center for Assessment in Saudi Arabia, the first step in the identification process for selecting gifted students is a self or a teacher nomination. The following assessments, which were developed and normed for Saudi students, are administered in the final selection of gifted learners: (a) a mental flexibility test, (b) a scientific and mechanical reasoning test, (c) a mathematical and spatial reasoning test, and (d) a linguistic reasoning and reading comprehension test. Those who score at or above the 95th percentile in at least two tests (and above the 90th percentile in the third) are being selected for the gifted program (for more details on the identification process in Saudi Arabia, see Abdulla Alabbasi, Acar, et al., 2024; Alfaiz et al., 2022). Both gifted and nongifted students in the present research were from the same school. Gifted students participated in a pull-out program that focuses on three areas: (a) scientific research, (b) an enrichment program, and (c) a counseling program.

Design and Procedure

After (a) obtaining the approval for conducting the current study from the Ministry of Education in Saudi Arabia and (b) receiving the consent forms from the students and their parents, participants were randomly divided into four equal groups: (a) Group 1, consisting of 40 gifted students, took two DT tasks in the classroom in the first half of the school day and two more DT tasks in the art room in the first half of the school day (on another day), (b) Group 2, consisting of 40 nongifted students, took two DT tasks in the classroom in the first half of the school day and two more DT tasks in the art room in the first half of the school day (on another day), (c) group 3, consisting of 40 gifted students two took two DT tasks in the classroom in the second half of the school day and two more DT tasks in the art room in the second half of the school day (on another day), and (d) Group 4, consisting of 40 nongifted students two took two DT tasks in the classroom in the second half of the school day and two more DT tasks in the art room in the second half of the school day (on another day; see Table 1).

All DT tasks were administered under a game-like condition with explicit instructions on being fluent and creative. The first half of the school day was sampled by collected data in the second class (8:15 a.m.–9:00 a.m.). Similarly, the second half of the school day was represented by collecting data during the fifth class (11:35 a.m.–12:20 p.m.). This structured approach ensured a consistent testing environment for all participants.

The third author collected the data with the assistance of two classroom teachers. She visited the school twice to familiarize herself with the study participants. After the two introductory visits, she administered the DT tasks. Each group administered the DT tasks in two different rooms (i.e., the regular classroom and the art room; see Figures 1 and 2) to ensure that there was enough space between study participants. The capacity of each class is around 35 seats and tables. This procedure (i.e., dividing each group) ensured that students did not copy or share their responses. In all sessions, two teachers assisted the third author. Before starting the session, the third author asked all students if they had any questions about the tasks. Moreover, she asked them to read the instructions for each task carefully. The administration time was calculated using a stopwatch. The mean time for completing each session ranged between 18 and 36 min. Students were asked to raise their hands after completing the two tasks.

Figure 1.

Regular classroom.

Figure 2.

Regular art room.

Instruments

Alternative Uses Test (AUT)

The AUT was administered to assess participants’ verbal fluency, flexibility, and originality. Two items of the AUT were administered: (a) the alternative uses for a spoon and (b) the alternative uses for a toothbrush. Previous research that used the AUT in Saudi Arabia, Bahrain, Kuwait, and the United Arab Emirates (i.e., Gulf Cooperative Council; GCC) showed a good reliability coefficient (Cronbach’s Alpha) ranging from .61 to .93 for fluency, .84 to .85 for flexibility, and .61 to .89 for originality (Abdulla Alabbasi, Reiter-Palmon et al., 2021; Abdulla Alabbasi, Runco, et al., 2021; Acar et al., 2019; AlSaleh et al., 2021). In the current study, an interclass correlation between two raters indicated good reliability for fluency (.91), flexibility (.80), and originality (.87). For fluency, a score of 1 was given for each response related to the stimuli that was not repeated. Regarding flexibility, a score of 1 was given for each shift/move from one response category to another. Two authors created a list of categories for the two verbal and the two figural tasks. For the spoon task, there were 11 different categories for flexibility in addition to the “others” category, and for the toothbrush task, there were nine categories for flexibility in addition to “others.” Finally, originality was scored based on statistical infrequency with a 1% cutoff. Each participant was awarded 1 point if the response was not above the 1% cutoff. The participants generated 164 ideas for the spoon task and 96 different ideas for the toothbrush task. The verbatim instructions were as follows:

Now, in this game, I am going to name an object—any kind of object, like a light bulb or the floor—and it will be your job to tell me many, different, and unique ways that the object could be used. Any object can be used in a lot of different ways. For example, think about string. What are some of the ways you can think of that you might use string? Let’s begin now. And remember, think of all the different and original ways you could use the object that you will see on the next page (Wallach & Kogan, 1965, p. 31).

Figural Divergent Thinking Test

The authors used two figural DT tasks from the Runco Creativity Assessment Battery (r-CAB; http://creativitytestingservice.com) that have been used extensively in previous research: (a) the Lines task and (b) the Squires task. Those figural tasks resemble Wallach and Kogan’s (1965) Line Meaning Test. Again, previous research that used the figural DT in Saudi Arabia and other GCC countries showed a good reliability coefficient ranging between .86 to .93 for fluency, .81 to .85 for flexibility, and .78 to .89 for originality (Abdulla Alabbasi, Reiter-Palmon et al., 2021; Abdulla Alabbasi, Runco, et al., 2021; Acar et al., 2019; AlSaleh et al., 2021). In the current study, an interclass correlation between two raters indicated good reliability for fluency (.93), flexibility (.79), and originality (.88). These tasks do not require participants to draw; they ask them to see the stimuli and tell everything it might be. Like the AUT test, the figural DT was scored for fluency, flexibility, and originality using the same scoring method. For the first figural task (Lines), there were 15 categories for flexibility in addition to “others,” and the same number of categories were for the second figural task (Squires). Participants generated 299 different ideas for the Lines task and 330 different ideas for the Squires tasks. The verbatim instructions for the figural DT were as follows:

Look at the figure below. What do you see? List as many things as possible that this figure might be or represent. This is NOT a test. Think of this as a game and have fun with it! The more ideas you list, the better.

Results

Table 2 presents descriptive statistics for the DT performance by giftedness and setting, while Table 3 shows descriptive statistics as a function of giftedness status and time of the day in the classroom and art room settings.

Table 2.

Divergent Thinking Performance by Giftedness and Setting.

DT performance	Giftedness	M	SD	N
Figural fluency classroom	Gifted	6.45	3.22	80
	Nongifted	6.01	3.04	80
	Total	6.23	3.13	160
Figural fluency art room	Gifted	7.78	4.39	80
	Nongifted	6.89	3.14	80
	Total	7.33	3.83	160
Figural flexibility classroom	Gifted	4.66	1.97	80
	Nongifted	4.23	1.83	80
	Total	4.44	1.91	160
Figural flexibility art room	Gifted	5.49	2.26	80
	Nongifted	5.18	2.09	80
	Total	5.33	2.17	160
Figural originality classroom	Gifted	2.40	1.91	80
	Nongifted	2.25	1.95	80
	Total	2.33	1.92	160
Figural originality art room	Gifted	2.68	2.39	80
	Nongifted	1.86	1.44	80
	Total	2.27	2.01	160
Verbal fluency classroom	Gifted	4.78	2.33	80
	Nongifted	4.14	1.67	80
	Total	4.46	2.05	160
Verbal fluency art room	Gifted	6.18	3.27	80
	Nongifted	5.91	3.13	80
	Total	6.04	3.19	160
Verbal flexibility classroom	Gifted	3.16	1.22	80
	Nongifted	2.69	0.85	80
	Total	2.93	1.07	160
Verbal flexibility art room	Gifted	4.23	2.03	80
	Nongifted	4.46	2.09	80
	Total	4.34	2.06	160
Verbal originality classroom	Gifted	0.75	1.16	80
	Nongifted	0.35	0.75	80
	Total	0.55	1.00	160
Verbal originality art room	Gifted	1.58	1.47	80
	Nongifted	1.16	1.38	80
	Total	1.37	1.44	160

Table 3.

Descriptive Statistics by Giftedness and Time of the Day in Classroom and Art Room Settings.

Divergent Thinking Indices	Classroom					Art room
Divergent Thinking Indices	Giftedness		M	SD	N	Giftedness		M	SD	N
Figural fluency	Gifted	First half	5.98	2.96	40	Gifted	First half	8.63	5.03	40
	Gifted	Second half	6.93	3.44	40	Gifted	Second half	6.93	3.50	40
	Nongifted	First half	6.05	3.23	40	Nongifted	First half	7.00	3.46	40
	Nongifted	Second half	5.98	2.88	40	Nongifted	Second half	6.78	2.81	40
	Total	First half	6.01	3.07	80	Total	First half	7.81	4.37	80
	Total	Second half	6.45	3.19	80	Total	Second half	6.85	3.15	80
Figural flexibility	Gifted	First half	4.58	1.77	40	Gifted	First half	5.88	2.41	40
		Second half	4.75	2.18	40		Second half	5.10	2.05	40
	Nongifted	First half	4.13	2.00	40	Nongifted	First half	5.20	2.26	40
		Second half	4.33	1.65	40		Second half	5.15	1.93	40
	Total	First half	4.35	1.89	80	Total	First half	5.54	2.34	80
		Second half	4.54	1.94	80		Second half	5.13	1.98	80
Figural originality	Gifted	First half	1.95	1.69	40	Gifted	First half	2.98	2.68	40
	Gifted	Second half	2.85	2.02	40	Gifted	Second half	2.38	2.03	40
	Nongifted	First half	2.33	2.19	40	Nongifted	First half	1.93	1.23	40
	Nongifted	Second half	2.18	1.71	40	Nongifted	Second half	1.80	1.64	40
	Total	First half	2.14	1.95	80	Total	First half	2.45	2.14	80
	Total	Second half	2.51	1.89	80	Total	Second half	2.09	1.86	80
Verbal fluency	Gifted	First half	5.00	1.89	40	Gifted	First half	6.58	3.47	40
		Second half	4.55	2.70	40	Gifted	Second half	5.78	3.05	40
	Nongifted	First half	4.10	1.72	40	Nongifted	First half	6.18	3.27	40
		Second half	4.18	1.65	40	Nongifted	Second half	5.73	3.64	40
	Total	First half	4.55	1.85	80	Total	First half	6.10	2.55	80
		Second half	4.36	2.23	80	Total	Second half	5.91	3.13	80
Verbal flexibility	Gifted	First half	3.18	1.06	40	Gifted	First half	4.35	2.12	40
		Second half	3.15	1.37	40	Gifted	Second half	4.10	1.95	40
	Nongifted	First half	2.70	0.99	40	Nongifted	First half	4.48	2.55	40
		Second half	2.68	0.69	40	Nongifted	Second half	4.45	1.54	40
	Total	First half	2.94	1.05	80	Total	First half	4.41	2.33	80
		Second half	2.91	1.10	80	Total	Second half	4.28	1.75	80
Verbal originality	Gifted	First half	0.58	0.84	40	Gifted	First half	1.65	1.46	40
	Gifted	Second half	0.93	1.40	40	Gifted	Second half	1.50	1.50	40
	Nongifted	First half	0.15	0.53	40	Nongifted	First half	1.25	1.24	40
	Nongifted	Second half	0.55	0.88	40	Nongifted	Second half	1.08	1.53	40
	Total	First half	0.36	0.73	80	Total	First half	1.45	1.36	80
	Total	Second half	0.74	1.18	80	Total	Second half	1.29	1.52	80

Analyses focused on two main research questions. The first research question focused on the DT performance as it varied as a function of setting (art room vs regular classroom). The second examined the association of test performance as a function of time of the school day.

DT Performance in Art Rooms Versus Classroom

DT scores collected while students were in the art room were compared to those collected when students were in formal classrooms. Giftedness status was included in the model as an independent variable. A repeated measures ANOVA with two independent variables (setting and giftedness status) showed students performed higher in figural fluency in an art room than in the classroom, F(1, 158) = 14.37, p < .001, $η_{p}^{2}$ = .083, regardless of giftedness status, F(1, 158) = 0.60, p = .439, $η_{p}^{2}$ = .004 (see Figure 3). Analyses with figural flexibility and originality included figural fluency in the model to control for a possible fluency confound. Figural flexibility did not differ significantly, F(1, 156) = 3.20, p = .075, $η_{p}^{2}$ = .020, nor did figural originality, F(1, 156) = 0.36, p = .850, $η_{p}^{2}$ = .000, between the two settings and there was not a significant difference by giftedness in the models with flexibility, F(1, 156) = 2.13, p = .147, $η_{p}^{2}$ = .013, and originality, F(1, 156) = 3.85, p = .052, $η_{p}^{2}$ = .024. Table 2 presents the means and standard deviations by setting and gifted status.

Figure 3.

Differences in DT figural fluency performance between classroom and art room.

Analyses with verbal fluency and originality showed a similar pattern to those of figural fluency and originality. Verbal fluency performance was significantly higher in the art room than in the classroom, F(1, 158) = 39.69, p < .001, $η_{p}^{2}$ = .201, whereas giftedness status was not significant, F(1, 158) = 0.55, p = .458, $η_{p}^{2}$ = .003. Verbal flexibility scores did not show a main effect for setting, F(1, 156) = 2.79, p = .097, $η_{p}^{2}$ = .018, but there was a significant interaction of giftedness by setting, F(1, 156) = 10.95, p = .001, $η_{p}^{2}$ = .066. As seen in Figure 4, the difference between classroom and art room performance was significantly larger for nongifted students than for gifted students. For verbal originality, there was not a significant difference by setting, F(1, 156) = 0.41, p = .840, $η_{p}^{2}$ = .000, and no interaction of giftedness and setting, F(1, 156) = 0.39, p = .533, $η_{p}^{2}$ = .002.

Figure 4.

Differences in DT figural flexibility performance between classroom and art room.

Finally, the mean scores in Table 2 showed a pattern: students, in general, scored higher in the art room than in the classroom, and when fluency was not controlled, the magnitude of the effect sizes for the various DT indices were medium to large (.31 < d < .86), the sole exception being figural originality (d = .03; see Table 4).

Table 4.

Effect Sizes (Cohen’s d) for the Difference Between DT Indices by Setting (Art Room vs. Classroom) When Fluency Is Not Controlled.

DT performance	M	SD	N	d
Figural fluency classroom	6.23	3.13	160	.314
Figural fluency art room	7.33	3.83	160	.314
Figural flexibility classroom	4.44	1.91	160	.435
Figural flexibility art room	5.33	2.17	160	.435
Figural originality classroom	2.33	1.92	160	−.0305
Figural originality art room	2.27	2.01	160	−.0305
Verbal fluency classroom	4.46	2.05	160	.600
Verbal fluency art room	6.04	3.19	160	.600
Verbal flexibility classroom	2.93	1.07	160	.859
Verbal flexibility art room	4.34	2.06	160	.859
Verbal originality classroom	0.55	1.00	160	.6614
Verbal originality art room	1.37	1.44	160	.6614

DT Performance by Time of the School Day

DT performance was then examined as it varied by time of day. As seen in Table 5, time of the day was a significant factor only in analyses that used DT verbal originality. Performance was higher in the second half (M = 0.74, SD = 1.18) than in the first half of the school day (M = 0.36, SD = 0.73) (see Figure 5) when students took DT tasks in the classroom. Table 3 presents descriptive statistics.

Table 5.

Descriptive Statistics of Divergent Thinking Performance.

Setting	Dependent variableSource	Figural fluency			Figural flexibility			Figural originality
Setting	Dependent variableSource	F	p	$η_{p}^{2}$	F	p	$η_{p}^{2}$	F	p	$η_{p}^{2}$
Classroom	Corrected model	0.88	.454	.017	113.84	<.001	.746	60.5	<.001	.610
	Intercept	633.2	<.001	.802	45.37	<.001	.226	8.15	.005	.050
	Fluency				445.83	<.001	.742	230.15	<.001	.598
	Giftedness	0.78	.378	.005	1.80	.181	.012	0.09	.77	.001
	Time	0.78	.378	.005	0.08	.783	.000	0.76	.385	.005
	Giftedness × Time	1.07	.302	.007	3.33	.070	.021	2.14	.145	.014
Art room	Corrected model	2.1	.103	.039	153.88	<.001	.799	147.80	<.001	.792
	Intercept	598.6	<.001	.793	86.29	<.001	.358	14.60	<.001	.086
	Fluency				599.1	<.001	.794	567.31	<.001	.785
	Giftedness	2.19	.141	.014	0.80	.374	.005	0.78	.379	.005
	Time	2.58	.11	.016	0.25	.619	.002	0.41	.523	.003
	Giftedness × Time	1.51	.22	.010	0.01	.931	.000	0.08	.778	.001
Setting	Dependent variableSource	Verbal fluency			Verbal flexibility			Verbal originality
Setting	Dependent variableSource	F	p	$η_{p}^{2}$	F	p	$η_{p}^{2}$	F	p	$η_{p}^{2}$
Classroom	Corrected model	1.65	.181	.031	45.81	<.001	.542	25.76	<.001	.399
	Intercept	768.14	<.001	.831	79.14	<.001	.338	21.75	<.001	.123
	Fluency				166.51	<.001	.518	83.31	<.001	.350
	Giftedness	3.93	.049	.025	4.04	.046	.025	3.12	.079	.020
	Time	0.34	.561	.002	0.15	.699	.001	11.95	<.001	.072
	Giftedness × Time	0.67	.416	.004	0.71	.401	.005	0.16	.695	.001
Art room	Corrected model	0.60	.618	.011	145.73	<.001	.790	44.84	<.001	.536
	Intercept	568.99	<.001	.785	29.03	<.001	.158	12.28	<.001	.073
	Fluency				579.05	<.001	.789	171.39	<.001	.525
	Giftedness	0.27	.605	.002	6.60	.011	.041	4.35	.039	.027
	Time	0.18	.676	.001	0.01	.918	.000	0.36	.552	.002
	Giftedness × Time	1.34	.248	.009	2.20	.140	.014	1.66	.199	.011

Figure 5.

DT performance in verbal originality by time of the school day.

A repeated measures ANOVA analysis with time also included gifted status. There was no significant interaction of giftedness and time in DT verbal or figural tasks. There was no significant difference by giftedness in figural DT tasks, either. In verbal tasks, gifted students had a higher score on verbal fluency (M = 4.78, SD = 2.33) than non-gifted students (M = 4.14, SD = 1.67) as well as on verbal flexibility (Gifted; M = 3.16, SD = 1.22; Non-gifted; M = 2.69, SD = 0.85) when they completed the divergent tasks in the classroom. When they took the DT tasks in the art room, nongifted students had a higher verbal flexibility score (M = 4.46, SD = 2.09) than gifted students (M = 4.23, SD = 2.03), but gifted students’ verbal originality scores were still higher (M = 1.58, SD = 1.47) than nongifted students (M = 1.16, SD = 1.38) (see Table 3 for descriptive Statistics of divergent thinking performance)

Discussion

There is evidence that different environmental dimensions can, in fact, affect students’ creativity (Dul, 2019; Plucker et al., 2017; Runco et al., 2023; Taylor, 1975). In the present research, several repeated measures ANOVAs, using both verbal and figural DT scores, indicated that performance was higher in the art room than in the classroom. Further, the difference in verbal flexibility performance between the two settings was larger for nongifted students than gifted students. The differences between the settings in figural and verbal originality were not statistically significant.

The findings contribute to the body of knowledge describing how constructivist education can enhance learning for all students. Moreover, the repeated measures ANOVA uncovered significant differences in verbal and figural fluency, where the students’ performance was higher in the art room, regardless of giftedness status. Shah and Gustafsson (2021) reported nonsignificant differences in verbal fluency, flexibility, and elaboration between the two settings, and they reported a significant difference in verbal originality in the art room. This is quite important because fluency can sometimes confound originality scores (Acar et al., 2023; Hocevar, 1980; Runco & Albert, 1985).

Certainly, the specific environmental features of regular classrooms and art rooms in Saudi Arabia might be different from those in England, where Shah and Gustafsson (2021) collected their data. Further, the participants in the current research were in high school, while those who participated in Shah and Gustafsson’s investigation were in elementary school. The figural test used by Shah and Gustafsson (i.e., TCT-DP) is different from the figural test used in the current study. Nonetheless, various repeated measures analyses of variance, which examined each of the DT indices and compared gifted and nongifted students, were consistent with previous findings where DT performances were higher in open classrooms than in traditional ones (Hyman, 1978; Lewis, 1980; Thomas & Berk, 1981).

The second objective of the current study was to test whether or not there was a difference in DT performance related to the time of the school day (first vs. second half). Previous studies using various cognitive tests have uncovered such differences, and it was possible that DT would also differ (Boksem et al., 2005; Goldstein et al., 2007; Mullette-Gillman et al., 2015; Sievertsen et al., 2016). Interestingly, Sievertsen et al. (2016, p. 2621) reported that “for every hour later in the day, test performance decreases by 9% when administering standardized tests.” This was not the case for the DT tests, at least in the current study, except for verbal originality in the regular classroom during the second half of the school day. Differences in verbal fluency, verbal flexibility, figural fluency, figural flexibility, and figural originality were small and not statistically significant. Finally, the current study’s findings were in line with Breslin’s (2019) reporting that creative thinking performance was higher in the afternoon compared with morning, but only the fluency index. In contrast, the originality index was not influenced by the time of the day.

There are limitations to the current investigation. First, the current sample did not include male students, although a recent meta-analysis study showed a very slight difference in DT between males and females in favor of females (Abdulla Alabbasi et al., 2022). As explained in the Method, this occurred because, in Saudi Arabia, boys and girls are segregated in schools. Second, the elaboration index of DT was not assessed in the current study, as it was in Shah and Gustafsson’s (2021) study. Third, the time of the day was compared within a restricted range, corresponding to early in the morning (8:15 a.m.–9:00 a.m.) and around midday (11:35 a.m.–12:20 p.m.) because the school day was set up as such. The impact of fatigue could be better observed if the second or another assessment was conducted late in the afternoon of a longer school day.

Further research should be conducted on the time of day in different cultures, school systems, and school types (i.e., private vs. government schools). Unlike place (regular classroom vs. art room), the mean scores for the time of the day (see Table 3) were inconsistent: some DT indices were higher in the first half of the school day, whereas others were higher in the second half of the school day. Comparisons of gifted and nongifted students indicated that the former had higher verbal DT scores, except for flexibility. Further research on classroom settings is recommended, but for now, we can conclude that (a) future research might compare different school places such as regular classrooms vs. resource rooms and natural environments (in the school garden, for example); (b) it is advisable to avoid regular classroom when administering DT test, at least for generating more ideas (i.e., fluency); (c) there is no difference in administering DT in different times of the school day; (d) researchers can compare morning vs. evening time for administering DT tests; and (e) it is recommended to compare government vs. private schools in terms of place and time of administering DT tests. More research such as that reported here is needed to improve education such that it leads direction to better student learning, higher test scores, and efficient communication skills.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Ahmed M. Abdulla Alabbasi

Selcuk Acar

Mark A. Runco

Zainab M. Sultan

Data Availability Statement

Data will be made available on request.

References

Abdulla Alabbasi

A. M.

Acar

Al-Shehri

Aljasim

. (2024). Testing the effects of time-on-task and instructions to “be creative” on gifted students. Gifted Education International, 40(1), 67–91. https://doi.org/10.1177/02614294231173783

Abdulla Alabbasi

A. M.

Reiter-Palmon

Sultan

Ayoub

. (2021). Which divergent thinking index is more associated with problem ﬁnding ability? The role of ﬂexibility and task nature. Frontiers in Psychology, 12, 1–11. https://doi.org/10.3389/fpsyg.2021.671146

Abdulla Alabbasi

A. M.

Runco

M. A.

Almutairi

M. S.

Ayoub

A. E. A

. (2024). Is creativity expressed at home related to creativity expressed at school? A re-examination of the creativity gap with gifted and nongifted students. Journal of Creative Behavior. Advance online publication. https://doi.org/10.1002/jocb.656

Abdulla Alabbasi

A. M.

Runco

M. A.

Sayed Mohammad

AlSaleh

. (2021). Problem ﬁnding, divergent thinking and evaluative thinking in gifted and nongifted students. Journal for the Education of the Gifted, 44(4), 398–413. https://doi.org/10.1177%2F01623532211044539

Abdulla Alabbasi

A. M.

Thompson

T. L.

Runco

M. A.

Alansari

L. A.

Ayoub

A. E. A

. (2022). Gender differences in creative potential: A meta-analysis of mean differences and variability. Psychology of Aesthetics, Creativity, and the Arts, 19(1), 87–100. https://doi.org/10.1037/aca0000506

Abraham

(2022). Creativity or creativities? Why context matters. Design Studies, 78, 1–16. https://doi.org/10.1016/j.destud.2021.101060

Acar

Abdulla Alabbasi

A. M.

Runco

M. A.

Beketayev

(2019). Latency as a predictor of originality in divergent thinking. Thinking Skills and Creativity, 33, 1–10. https://psycnet.apa.org/doi/10.1016/j.tsc.2019.100574

Acar

Ogurlu

Zorychta

(2023). Exploration of discriminant validity in divergent thinking tasks: A meta-analysis. Psychology of Aesthetics, Creativity, and the Arts, 17(6), 705–724. https://doi.org/10.1037/aca0000469

Acar

Runco

M. A.

Park

(2020). What should people be told when they take a divergent thinking test? A meta-analytic review of explicit instructions for divergent thinking. Psychology of Aesthetics, Creativity, and the Arts, 14(1), 39–49. https://doi.org/10.1037/aca0000256

10.

Aiello

(2022). Time of day and background: How they affect designers’ neurophysiological and behavioral performance in divergent thinking [Doctoral dissertation, Politecnico di Torino].

11.

Alfaiz

F. S.

Alfaid

A. A.

Aljughaiman

A. M.

(2022). Current status of gifted education in Saudi Arabia. Cogent Education, 9(1). https://doi.org/10.1080/2331186X.2022.2064585

12.

AlSaleh

Abdulla Alabbasi

A. M.

Ayoub

Hafsyan

A. S. M.

(2021). The effects of birth order and family size on academic achievement, divergent thinking, and problem ﬁnding among gifted students. Journal for the Education of Gifted Young Scientists, 9(1), 67–75. http://dx.doi.org/10.17478/jegys.864399

13.

Amabile

T. M.

(1990). Within you, without you: The social psychology of creativity, and beyond. In Runco

M. A.

Albert

R. S.

(Eds.), Theories of creativity (pp. 61–91). Sage.

14.

Amabile

T. M.

(1996). Creativity in context: Update to “the social psychology of creativity.”Westview Press.

15.

Batey

Hughes

D. J.

Crick

Toader

(2021). Designing creative spaces: An experimental examination of the effect of a nature poster on divergent thinking. Ergonomics, 64(1), 139–146. https://doi.org/10.1080/00140139.2020.1811398

16.

Blomberg

A. J.

Kallio

T. J.

(2022). A review of the physical context of creativity: A three-dimensional framework for investigating the physical context of creativity. International Journal of Management Reviews, 24, 433–451. https://doi.org/10.1111/ijmr.12286

17.

Boksem

M. A.

Meijman

T. F.

Lorist

M. M.

(2005). Effects of mental fatigue on attention: An ERP study. Cognitive Brain Research, 25(1), 107–116. https://doi.org/10.1016/j.cogbrainres.2005.04.011

18.

Breslin

(2019). Group creativity and the time of the day. Studies in Higher Education, 44(7), 1103–1118. https://doi.org/10.1080/03075079.2017.1413082

19.

Day

H. I.

(1974). Curiosity, creativity, and attitude to schooling in open-plan and traditional schools (Grades 2 to 4). Final Report. Studies of Open Education, No. 12.

20.

Deng

Wang

Zhao

(2016). How creativity was affected by environmental factors and individual characteristics: A cross-cultural comparison perspective. Creativity Research Journal, 28(3), 357–366. https://doi.org/10.1080/10400419.2016.1195615

21.

Dudek

S. Z.

Strobel

M. G.

Runco

M. A.

(1993). Cumulative and proximal influences on the social environment and children’s creative potential. The Journal of Genetic Psychology: Research and Theory on Human Development, 154(4), 487–499. https://doi.org/10.1080/00221325.1993.9914747

22.

Dul

(2019). The physical environment and creativity: A theoretical framework. In Kaufman

J. C.

Sternberg

R. J.

(Eds.), The Cambridge handbook of creativity (pp. 481–510). Cambridge University Press.

23.

Goldstein

Hahn

C. S.

Hasher

Wiprzycka

U. J.

Zelazo

P. D.

(2007). Time of day, intellectual performance, and behavioral problems in morning versus evening type adolescents: Is there a synchrony effect? Personality and Individual Differences, 42(3), 431–440. https://doi.org/10.1016/j.paid.2006.07.008

24.

Guegan

Brechet

Nelson

(2020). Dreamlike and playful virtual environments to inspire children’s divergent thinking. Journal of Media Psychology, 33(1), 28–38. https://doi.org/10.1027/1864-1105/a000279

25.

Hocevar

(1980). Intelligence, divergent thinking, and creativity. Intelligence, 4(1), 25–40. https://doi.org/10.1016/0160-2896(80)90004-5

26.

Hyman

R. B.

(1978). Creativity in open and traditional classrooms. The Elementary School Journal, 78(4), 266–274. https://doi.org/10.1086/461111

27.

Ichimura

(2023). Effects of virtual reality’s viewing medium and the environment’s spatial openness on divergent thinking. PLoS One, 18(3), e0283632. https://doi.org/10.1371/journal.pone.0283632

28.

Küller

Ballal

Laike

Mikellides

Tonello

(2006). The impact of light and colour on psychological mood: A cross-cultural study of indoor work environments. Ergonomics, 49(14), 1496–1507. https://doi.org/10.1080/00140130600858142

29.

Lee

J. H.

Lee

(2023). Relationships between physical environments and creativity: A scoping review. Thinking Skills and Creativity, 48, 1–18. https://doi.org/10.1016/j.tsc.2023.101276

30.

Lewis

S. P.

(1980). A study of the varying degrees of creativity manifested by kindergarten children from open or traditional classrooms [Unpublished Master’s thesis, Western Michigan University].

31.

Lucius

Z. K.

Damberg

(2024). Why we need employees back at the office: The effect of workplace design on creativity in organizations. Creativity and Innovation Management. Advance online publication. https://doi.org/10.1111/caim.12611

32.

Lufi

Tzischinsky

Hadar

(2011). Delaying school starting time by one hour: Some effects on attention levels in adolescents. Journal of Clinical Sleep Medicine, 7(2), 137–143.

33.

Makel

M. C.

Plucker

J. A.

(2014). Facts are more important than novelty: Replication in the education sciences. Educational Researcher, 43(6), 304–316. https://doi.org/10.3102/0013189X14545513

34.

McCoy

J. M.

Evans

G. W.

(2002). The potential role of the physical environment in fostering creativity. Creativity Research Journal, 14(3–4), 409–426. https://doi.org/10.1207/S15326934CRJ1434_11

35.

Mullette-Gillman

O. A.

Leong

R. L. F.

Kurnianingsih

Y. A.

(2015). Cognitive fatigue destabilizes economic decision making preferences and strategies. PLoS One, 10(7), e0132022. https://doi.org/10.1371/journal.pone.0132022

36.

Paek

Abdulla Alabbasi

A. M.

Acar

Runco

M. A.

(2021). Is more time better for divergent thinking? A meta-analysis of the time-on-task effect on divergent thinking. Thinking Skills and Creativity, 41, 15–38. https://doi.org/10.1016/j.tsc.2021.100894

37.

Piya-Amornphan

Santiworakul

Cetthakrikul

Srirug

(2020). Physical activity and creativity of children and youths. BMC Pediatrics, 20(1), 118. https://doi.org/10.1186/s12887-020-2017-2

38.

Plucker

J. A.

McWilliams

Guo

(2017). Smart contexts for 21st-century talent development: Sociocultural approaches to gifted education. In Plucker

J. A.

Rinn

A. N.

Makel

M. C.

(Eds.), From giftedness to gifted education: Reflecting theory in practice (pp. 227–248). Prufrock Press.

39.

Rayneri

L. J.

Gerber

B. L.

Wiley

L. P.

(2006). The relationship between classroom environment and the learning style preferences of gifted middle school students and the impact on levels of performance. Gifted Child Quarterly, 50(2), 104–118. https://doi.org/10.1177/001698620605000203

40.

Richardson

Mishra

(2018). Learning environments that support student creativity: Developing the SCALE. Thinking Skills and Creativity, 27, 45–54. https://doi.org/10.1016/j.tsc.2017.11.004

41.

Rubenson

D. L.

Runco

M. A.

(1995). The psychoeconomic view of creative work in groups and organizations. Creativity and Innovation Management, 4, 232–241. https://doi.org/10.1111/j.1467-8691.1995.tb00228.x

42.

Runco

M. A.

(1986). Maximal performance on divergent thinking tests by gifted, talented, and nongifted children. Psychology in the Schools, 23(3), 308–315. https://doi.org/10.1002/1520-6807(198607)23:3<308::AID-PITS2310230313>3.0.CO;2-V

43.

Runco

M. A.

Abdulla Alabbasi

A. M.

Acar

Ayoub

(2023). Creative potential is differentially expressed in school, at home, and the natural environment. Creativity Research Journal, 35(1), 15–22. https://doi.org/10.1080/10400419.2022.2031437

44.

Runco

M. A.

Albert

R. S.

(1985). The reliability and validity of ideational originality in the divergent thinking of academically gifted and nongifted children. Educational and Psychological Measurement, 45(3), 483–501. https://doi.org/10.1177/001316448504500306

45.

Said-Metwaly

Fernández-Castilla

Kyndt

Van den Noortgate

(2020). Testing conditions and creative performance: Meta-analyses of the impact of time limits and instructions. Psychology of Aesthetics, Creativity, and the Arts, 14(1), 15–38. https://doi.org/10.1037/aca0000244

46.

Shah

Gustafsson

(2021). Exploring the effects of age, gender, and school setting on children’s creative thinking skills. Journal of Creative Behavior, 55(2), 546–553. https://doi.org/10.1002/jocb.480

47.

Sievertsen

H. H.

Gino

Piovesan

(2016). Cognitive fatigue influences students’ performance on standardized tests. Proceedings of the National Academy of Sciences of the United States of America, 113(10), 2621–2624. https://doi.org/10.1073/pnas.1516947113

48.

Taylor

(1975). Perspectives in creativity (1st ed.). Routledge. https://doi.org/10.4324/9781315126265

49.

Thomas

N. G.

Berk

L. E.

(1981). Effects of school environments on the development of young children’s creativity. Child Development, 52(4), 1153–1162. https://doi.org/10.2307/1129501

50.

Wallach

M. A.

Kogan

(1965). Modes of thinking in young children: A study of the creativity-intelligence distinction. Holt, Rinehart & Winston.

51.

Yeh

C. W.

Hung

S. H.

Chang

C. Y.

(2022). The influence of natural environments on creativity. Frontiers in Psychiatry, 13, 895213. https://doi.org/10.3389/fpsyt.2022.895213

52.

Zhang

Yang

Liang

(2023). Stimulating creativity in the classroom: Examining the impact of sense of place on students’ creativity and the mediating effect of classmate relationships. BMC Psychology, 11(1), 432. https://doi.org/10.1186/s40359-023-01479-7