Effect of Cognitive Style and Working Memory on Floral Design Ability

Abstract

Students were sampled from two universities in southern Taiwan from 1 September 2022 to 31 October 2022. This study examined the factors affecting the floral design ability of 125 university students by analyzing the relationship between demographic variables, cognitive styles, working memory, and floral design ability. The results revealed that the cognitive style, working memory, and floral design ability scores of the participants were 2.82 (standard deviation [SD]: 0.35), 5.06 (SD: 1.11), and 77.27 (SD: 5.43), respectively. Most participants were visual processors and demonstrated favorable scores for working memory and floral design ability. Floral design ability had a moderately positive correlation with cognitive style (r = 0.474, p < 0.000) and working memory (r = 0.521, p < 0.000). Both working memory and cognitive style were influential factors for floral design ability. Specifically, working memory exhibited a higher predictive power and explained 27.2% of the variance, whereas cognitive style only explained 10.3% of the variance. Therefore, teaching aids that improve working memory, such as computer games and picture cards, can be used as supplementary teaching aids in floral design education. Visual processors can be taught using more picture-based or photo-based teaching methods, whereas a list of operational procedures is more suitable for verbal processors.

1. Introduction

The ongoing COVID-19 pandemic has posed unprecedented challenges to the floral market in Taiwan. To avoid the pandemic risks associated with crowd gatherings, the number of weddings, funerals, and events has decreased considerably, and ceremonies have become less decorative. Additionally, the number of visits to inpatients in hospitals, who often receive flowers from visitors, and community courses for horticulture have decreased drastically. Because decorative flowers are not considered daily necessities, the annual mean expenditure of Taiwanese people on such products is only TWD 926 [1], which is substantially lower than in Europe, the United States, and Japan. According to surveys conducted by Taiwan’s Council of Agriculture, the total revenue of cut flowers generated by wholesale flower markets in Taiwan was TWD 281.48 million in February 2020, which was 10% to 20% lower than during the same period in previous years [2]. In 2009, Taiwan had 3345 registered flower stores, but this figure decreased to 1270 in 2020 [3]. The worldwide consumption of floral products has also decreased, leading exported products to circulate back into the domestic market and causing a further slump in the market. Advertisement campaigns promoting the use of flowers among the Taiwanese population are an effective approach to alleviating the current downturn in the domestic floral market [4].

Floral designers create artistic arrangements and designs by using flowers. By using various techniques, floral designers improve the attractiveness and value of floral products. Therefore, floral designers play a vital role in stimulating the floral market. In Taiwan, courses for training floral designers are mostly offered by vocational high schools or the horticulture and home economics departments of universities; such courses are usually called “Flower Application” or “Floral Design.” The public can also attend floral design courses arranged by private organizations (e.g., the China Floral Art Foundation and the Chinese Flower Design Association) and pass multiple stages of exams to receive a floral designer certificate [5]. Although such courses align with programs at renowned international floral design institutions, no standardized teaching method exists in Taiwan, and scholars have rarely discussed the standardization of teaching methods. Nonetheless, the development of adequate teaching materials and methods is imperative for the growth of the floral industry.

Cognitive style is the method through which individuals collect and organize data [6] and is expressed by individuals through their cognition, thinking, problem solving, and memory. In contrast to cognitive ability, which can be measured through experiments or intelligence tests, cognitive style is associated with individuals’ habits and traits when thinking or processing information. Cognitive style is constant and stable, does not vary over time, is unaffected by the environment, and is observed in an individual’s learning process [7]. Cognitive style pertains to the information processing method preferred by individuals and is considered neither good nor bad [8]. Cognitive style can be classified into visual and verbal processors [9,10], high conceptual level and low conceptual level trainees [11], and field independent and field dependent individuals. When learning, visual processors prefer using tangible images or imagery, such as pictures, photographs, figures, tables, and graphs, to support their thinking process. Their thinking mode is subjective and self-oriented. By contrast, verbal processors prefer using abstract symbols to learn, such as written text or verbal narratives, and their thinking mode is objective and task-oriented. Rather than being abstract and packed with theory, floral design courses focus on spatial arrangement, angle interpretation, and aesthetic design. Therefore, whether the learning outcomes of students enrolled in floral design courses are associated with their cognitive style merits further exploration.

Working memory can be defined as the ability to process and maintain information for a short period of time [12]. This ability pertains to the outcomes achieved through phonologic loops, visuospatial sketchpads, episodic buffers, and central executive systems. Studies have reported that learners with favorable working memory are more successful [13,14,15], particularly when studying complex ideas and skills. For example, working memory significantly predicts fluency and originality during the creation process [16,17], and artistic ability and working memory are significantly correlated [18]. Floral design is the manifestation of creativity; however, whether floral design ability is related to working memory requires further research.

Teaching methods affect learning outcomes. Understanding students’ learning characteristics and the factors affecting their learning process can greatly affect their learning outcomes [19,20]. Employing teaching materials or methods that consider learners’ cognitive style enables students to achieve favorable learning outcomes [21]. Art education can incorporate different teaching methods based on learners’ characteristics [22]. Because floral design is a type of spatial art, adequate teaching methods that align with students’ cognitive style can be used to improve their cognitive ability and are a vital aspect of course design and student performance. Thus, this study used cognitive style and working memory as variables to explore their relationship with floral design ability. Moreover, we examined factors affecting student learning and identified teaching methods for businesses and floral design educators.

2. Materials and Methods

2.1. Sampling

This study recruited students from the Department of Living Services Industry and the Department of Fashion Design at Tainan University of Technology and students from the Department of Cosmetic Science at National Tainan Nursing Junior College from 1 September 2022 to 31 October 2022. Purposive sampling was performed to recruit students enrolled in the School of Living Technology and the School of Design at two universities in southern Taiwan in 2022. The three departments were selected because they offer various courses associated with aesthetic literacy, including floral design and accessory design courses. Becoming a floral designer is also a career option for students graduating from the departments. The students were selected to develop adequate teaching methods and determine whether they demonstrated the potential to become floral designers. Students who did not receive floral design training prior to the study were invited to complete a questionnaire. This study met the criteria for an ethical review exemption as specified by the National Chengchi University Research Ethics Committee [23]. However, the author still provided an Informed Consent Form to inform the participants of the research purpose and procedure. The author emphasized that participants could freely withdraw from the study at any time if they felt uncomfortable, and an appropriate incentive was provided to participants after the study. The tests began after all the participants understood the research procedure. A total of 131 questionnaire copies were distributed, and all 131 responses were collected, yielding a return rate of 100%. After incomplete responses were excluded, 125 responses were used for subsequent analysis, yielding a valid return rate of 95.4%.

2.2. Measures

2.2.1. Demographic Information

Information on the class, name, age, and gender of students was collected.

2.2.2. Cognitive Style Scale

(1) Scale design: The cognitive style scale used in this study was the Style of Processing Scale (SOP) developed by Childers et al. [24]. The SOP contains 22 items and adopts a 4-point Likert scale with endpoints at 1 and 4 (1 = always false, 2 = usually false, 3 = usually true, and 4 = always true). Eleven items pertain to visual processors, and the remaining items pertain to verbal processors. The verbal processors are evaluated using reverse scoring; in other words, visual processors receive higher scores and verbal processors receive lower scores. For example, when answering the item “I generally prefer to use a diagram rather than a written set of instructions,” the respondent receives 4 points if they answer always true but only 1 point if they answer always false. For the item “I do a lot of reading,” the respondent receives only 1 point if they answer always true but 4 points if they answer always false. A high score indicates that the respondent prefers using visual images to process their thoughts, whereas a low score indicates that the respondent prefers textual information. In the present study, the median score was used as the point of division; participants who scored less than or equal to the median score were categorized as verbal processors, and participants who scored higher than the median score were categorized as visual processors [25].

Table 1. Participant scores for the cognitive style test.

Item	Mean (SD)	Ranking of Grades
* 1. I enjoy doing work that requires the use of words (W).	2.62(0.75)	16
3. I can never seem to find the right word when I need it (W).	2.28(0.62)	20
* 4. I do a lot of reading (W).	2.65(0.80)	12
6. I think I often use words in the wrong way (W).	2.65(085)	12
* 7. I enjoy learning new words (W).	2.26(0.82)	21
* 9. I often make written notes to myself (W).	2.23(0.70)	22
* 15. I like to think of synonyms for words (W).	2.63(0.76)	15
* 17. I like learning new words (W).	2.57(0.82)	19
* 18. I prefer to read instructions about how to do something rather than have someone show me (W).	2.84(0.85)	10
19. I prefer activities that don’t require a lot of reading (W).	2.65(0.81)	12
21. I spend very little time attempting to increase my vocabulary (W).	2.60(0.85)	18
2. There are some special times in my life that I like to relive by mentally “pic -turing” just how everything looked (P).	3.22(0.61)	5
5. When I’m trying to learn something new. I’d rather watch a demonstration than read how to do it (P).	3.27(0.77)	3
8. I like to picture how I could fix up my apartment or a room if I could buy anything I wanted (P).	3.42(0.69)	2
10. I like to daydream (P).	2.86(0.98)	9
11. I generally prefer to use a diagram rather than a written set of instructions (P).	3.22(0.74)	5
12. I like to “doodle” (P).	2.94(0.83)	8
13. I find it helps to think in terms of mental pictures when doing many things (P).	3.37(0.70)	1
14. After I meet someone for the first time, I can usually remember what they look like, but not much about them (P).	2.62(0.75)	16
16. When I have forgotten something I frequently try to form a mental “pic- ture” to remember it (P).	3.27(0.70)	3
20. I seldom daydream (P).	2.68(1.00)	11
22. My thinking often consists of mental “pictures” or images (P).	3.19(0.79)	7

* reverse scoring items; W: verbal processor items; P: visual processor items.

displays the participant scores.

(2) Validity: The validity of the SOP was verified using discriminant validity and criterion validity. For discriminant validity, the scores of the visual processor and verbal processor constructs were weakly correlated (r = −0.10). For criterion validity, the SOP was significantly related to both aided recall and recognition of previously presented advertisements. The negative correlation indicated that retention was strongest among verbally oriented processers. Therefore, the scale demonstrated favorable validity [24,26].

(3) Reliability: Cronbach’s α values were 0.81 and 0.86 for the verbal processor and visual processor constructs, respectively. The total reliability of the scale reached 0.88, which verified that the scale demonstrated favorable reliability [24].

2.2.3. Working Memory Test

A test was performed using the Java-based color corsi task of Stone and Towse [27] to assess participants’ visual-spatial working memory capacity. In this task, participants are asked to memorize the locations of black squares that appear individually in sequence in a 5 × 5 grid. After all the squares appear, the participants recall the location of each square sequentially. The difficulty level is based on the working memory length, which spans from 2 (i.e., memorizing the locations of two squares in a row) to 9 (i.e., memorizing the locations of nine squares in a row). Each length is repeated thrice, and participants are required to recall all locations sequentially to provide the correct answer. In the present study, participants confirmed the test procedure and underwent two practice sessions before taking the formal test. The test-retest reliability was examined using Cronbach’s α, which was 0.825; thus, the test was reliable. Figure 1 presents the test procedure.

2.2.4. Semispherical Table Potted Flower Test

(1) Test design: This test was created on the basis of the floral design specialist exam registered with Taiwan’s Ministry of the Interior [28]. A previous investigation identified the semispherical table potted flower design as an item that always appears in the elementary exam. Therefore, the present research team referenced the procedure of the specialist exam by using similar flower materials and tools to record a 20 min demonstration video.

Table 2. Instructions and materials used in the potted flower test.

Instructions	Materials
Please view the 30 min demonstration video for creating a semispherical table potted flower and then recreate the potted flower by following the assembly steps presented in the video. The time limit is 40 min.	(1) 17 cut roses (2) 12 branches with jasmine leaves (3) 3 branches with baby’s breath (4) 3 branches with squirrel’s foot fern (5) 1 sponge (6) 1 vase

presents the instructions shown in the video and the materials used for the test. After viewing the video, participants were asked to create a potted flower identical to that shown in the video. The total test time was 40 min. The potted flowers created by the participants were filmed using a digital camera (Canon IXUS285 HS/Tokyo/Japan) at a distance of 70 cm (eye-level shot) and 75 cm (overhead shot) from the potted flowers; specifically, three photos were taken from the front, back, and bird’s-eye view perspectives, respectively, for each potted flower. Three experts with at least 10 years of floral design teaching experience were invited to rate each potted flower according to its shape and structure. Scores ranged from 0 to 100, and ranges of 0–20, 21–40, 41–60, 61–80, and 81–100 denoted very incomplete, incomplete, moderately complete, complete, and very complete structures, respectively. A high score indicated that the potted flower was highly similar to that in the demonstration video and that the participant demonstrated favorable floral design ability;

(2) Validity: after the test content was created, three floral design experts were invited to verify the validity of the test and revise the materials, tools, and scoring method;

(3) Reliability: Scorer reliability was used to verify the stability of the test. The three experts were asked to rate 30 pilot samples created for the test. The Pearson’s correlation coefficients of the scores given by the experts were 0.893, 0.83, and 0.824. Thus, the test demonstrated high stability. After the validity and reliability of the test content were verified, the formal test was administered using the instructions and materials listed in Table 2. Figure 2 presents the main content of the demonstration video.

2.3. Statistical Analyses

Data were analyzed with SPSS Version 23 (IBM Corp., Armonk, NY, USA). This study found the means, standard deviation (SD), frequency (in percent), t-test scores, one-way analysis of variance results, Pearson’s correlation results, and stepwise multivariate regression results to analyze the collected data.

3. Results

3.1. Cognitive Style Analysis

The total score of each item in the cognitive style test was 4. The mean score obtained by the participants was 2.82 (SD: 0.35), which accounted for 71% of the total score. Therefore, most participants were visual processors. Regarding the scores of individual items, Item 13 “I find it helps to think in terms of mental pictures when doing many things” had the highest score (3.37 ± 0.70), whereas Item 9 “I often make written notes to myself” had the lowest score (2.23 ± 0.70). Thus, most participants preferred using images over textual information when learning and memorizing content. Table 1 presents the scores of the analysis.

3.2. Analysis of Working Memory and Potted Flower Test Results

The total score of the working memory test was 9. The median value is 4.5 points and the mean score of the participants was 5.06 (SD: 1.11), which accounted for 56.2% of the total score. Therefore, the participants demonstrated a moderate working memory capacity. However, the score data showed a positive skewness with a value of 0.05 (SD: 0.22), indicating that most participants had low scores. The kurtosis measure was less than 3, indicating that the scores were sparsely distributed.

Table 3. Trends of working memory and potted flower test scores.

Statistics	Working Memory	Floral Design Score
Effective samples	125	125
Mean (SD)	5.06(1.11)	77.27(1.11)
Skewness (SD)	0.05(0.22)	−0.22(0.22)
Kurtosis (SD)	−0.60(0.44)	0.63(0.43)

presents the results of the analysis.

The total score of the potted flower test was 100. The mean score of the participants was 77.27 (SD: 1.11), which accounted for 77.3% of the total score. Therefore, the participants demonstrated moderate-to-high design skills. However, the score data demonstrated a negative skewness with a value of −0.22 (SD: 0.22), indicating that most participants had high scores. The kurtosis measure was less than 3, indicating that the scores were sparsely distributed. Table 3 presents the results of the analysis.

3.3. Differences in Floral Designs Scores with Respect to Cognitive Style and Working Memory

To understand the differences in the floral design scores of participants with different cognitive styles and working memory capacities, this study used the median score of the cognitive style test (2.82) as the point of division to categorize the participants into verbal and visual processors. Additionally, the mean score of the working memory test (5.06) was used as the point of division to categorize the participants into the high and low working memory groups. Further analysis of the differences in floral design scores revealed that visual processors performed more favorably than verbal processors (F = 18.66, p < 0.000), and the high working memory group performed more favorably than the low working memory group (F = 12.39, p = 0.001).

Table 4. Distribution of participants based on cognitive style and working memory.

Variable	Gender	Visual Processor	Verbal Processor	High Working Memory	Low Working Memory	Total
Sex	Men	3	7	3	7	10
	Women	52	63	38	77	115
Age	18	19	37	13	43	56
	19	22	24	17	29	46
	20	14	9	11	12	23

presents the number of participants in each group, and

Table 5. Differences in the floral design scores of participants based on cognitive style and working memory.

Variable		N	Floral Design Score Mean (SD)	Difference Test F Value (p Value)
Gender	Men	10	75.23(10.41)	0.44(0.522)
	Women	115	77.44(4.81)
Age	18 years old	56	76.56(5.17)	2.67(0.074)
	19 years old	46	76.98(4.88)
	20 years old	23	79.57(6.63)
Cognitive style	Visual Processors	55	79.48(5.02)	18.66(0.000) ***
	Verbal Processors	70	75.52(5.13)
Working memory	High working memory	41	79.61(4.71)	12.39(0.001) ***
	Low working memory	84	76.12(5.42)

*** p < 0.001.

presents the test scores of each group.

3.4. Correlations of Floral Design Scores with Cognitive Style and Working Memory

Table 6. Pearson product-moment correlation analysis of floral design, cognitive style, and working memory.

Pretest Correlation Coefficient (r Value) of the Floral Design, Cognitive Style, and Working Memory
Variable	Floral Design	Cognitive Style	Working Memory
1. Floral design	1
2. Cognitive style	0.474 ***	1
3. Working memory	0.521 ***	0.329 ***	1

*** p < 0.001

presents the results of the correlation analysis on cognitive styles, working memory, and floral design scores. The participants’ floral design scores demonstrated moderately positive correlations with their cognitive style (r = 0.474, p < 0.000) and working memory (r = 0.521, p < 0.000). Therefore, visual processors and those with high working memory capacity performed better at floral design. Additionally, a weak positive correlation existed between cognitive style and working memory (r = 0.329, p < 0.000). Thus, visual processors exhibited a higher working memory capacity. Table 6 presents the analysis results.

3.5. Demographic Variables, Cognitive Styles, and Working Memory as Predictors of Floral Design Ability

Table 7. Regression analysis on the prediction of floral design ability through cognitive style and working memory.

Sequence in Which the Variable Was Selected	Multivariate Correlation Coefficient (R)	R2	Increase in the Total Explained Variance	F Value	Net F Value	Standardized Regression Coefficient
Working memory	0.521	0.272	0.272	45.916 ***	45.916	0.410
Cognitive style	0.612	0.375	0.103	36.530 ***	20.038	0.339

*** p < 0.001.

presents the results of the stepwise correlation analysis on the effect of demographic variables, cognitive styles, and working memory on predicting floral design ability. Four variables were initially investigated for predicting floral design ability; however, only two variables, namely, cognitive style and working memory, had significant correlation coefficients (0.612) and jointly explained 37.5% of the total variance. Working memory was most effective in predicting floral design ability and explained 27.2% of the total variance, followed by cognitive styles, which explained 10.3% of the total variance. Visual processors and those with a high working memory capacity performed better at floral design. Therefore, we proposed the following regression equation to predict floral design ability:

Floral design ability = working memory × 0.410 + cognitive style × 0.339

4. Discussion

Floral designers create additional value for floral products and are essential workers in the floral industry. Training floral designers relies on adequate teaching methods and discovering talented individuals. This study identified working memory as a crucial factor affecting students’ floral design ability. Working memory is a system that underpins cognitive activities ranging from attention allocation to specific stimuli (i.e., selective attention) to complex decision making [29]. It plays a vital role in complex cognitive activities through functions such as real-time monitoring, processing, and maintaining relevant information [30,31]. Working memory is also positively correlated with the ability to execute instructions [32,33]. Individuals with a high working memory capacity are more able to appreciate complex artwork [34] because they can process the components of artwork into meaningful information. Moreover, patients with schizophrenia can participate in floral design events to improve their visuospatial working memory by memorizing the positions and sequences of flower arrangements [35]. The present study verified that working memory is an effective predictor of floral design ability (R² = 0.272, p < 0.001), and participants with a high working memory capacity demonstrated stronger floral design ability (p < 0.001). Effective working memory training can improve the connections within the brain network [36] and facilitate the development of floral design ability. Additionally, working memory can be a criterion for business owners to recruit suitable floral designers.

Studies have suggested that training is an effective method of improving working memory. Common training methods include performing verbal and visuospatial memory span tasks in computer games [37,38,39], using images and cards [40,41], and playing chess [42]. Therefore, when arranging elementary training courses, floral design educators can use such teaching materials as alternatives to real cut flowers, which are more expensive. For example, computer games can be used to emulate steps for arranging flowers, or a chess board can be used to teach students flower arrangement positions. Such materials can enable students to become familiar with flower arrangement procedures before working with real flowers, which can reduce training costs and maximize the economic benefits of floral materials.

Cognitive style is a habitual method used by learners to perceive, organize, and memorize information [43]. The educational implications of cognitive style research focus on how teachers implement adequate teaching materials and methods based on learners’ cognitive styles, which have been verified as a key factor affecting creativity [44]. Cognitive style is closely associated with spatial ability [45], and students with a local cognitive style exhibit more favorable visual-spatial intelligence than those with a global cognitive style. Floral design is a predominantly spatial art that uses flowers to create arrangements. This study revealed that participants who were visual processors demonstrated stronger floral design ability (p < 0.001). Additionally, cognitive style effectively predicted floral design ability (R² = 0.103, p < 0.001). These findings are consistent with those of other studies that have reported that visual processors demonstrate excellent performance in interpreting figures, tables, and other spatial information [46,47]. Moreover, visual processors perform better in information technology courses than verbal processors; however, their performance in management courses is lower than that of verbal processors [48]. Students with strong visual skills recall more details of figures which they had previously drawn than students with poor visual skills [49] and demonstrate more favorable performance in locating items on maps [50]; visual processors prefer using concrete information, such as tangible objects or imagery, in their thinking process [9]. Thus, visual processors in the present study were more able to observe details in the demonstration video than verbal processors.

Cognitive style reflects learner characteristics in three stages, namely, cognition, organization, and memorization. Because visual and verbal processors tend to acquire information by looking and reading, respectively [51], teachers should focus on diversifying teaching materials related to cognition. For example, images, photographs, figures, and tables can be used to teach students and improve their concentration. Other teaching materials, such as exploded-view drawings of flower structures, flow charts, videos with detailed content, and hands-on demonstrations, are conducive to stimulating the memory of visual processors. By observing the appearance of flowers and the angles and positions of flower arrangements, visual processors can easily gather and organize useful information. They can also view the flower arrangements of famous artists to enhance their memory. In this study, a demonstration video was used to teach floral design. This approach enabled visual processors to acquire useful information more effectively than verbal processors; consequently, visual processors demonstrated more favorable performance. This finding further demonstrated that videos are an effective teaching method for visual processors.

Compared with working memory, cognitive style is fostered from a young age and therefore cannot be changed easily. This study observed that verbal processors performed less favorably compared with visual processors. This result may be because verbal processors do not excel at forming mental images; they require more time to analyze the textual content [52] and rely heavily on textual interpretation [53]. In floral design education, textual and verbal information are usually used to supplement hands-on demonstrations, images, or videos. Consequently, verbal processors may receive and process less information than visual processors. Therefore, converting images and videos to textual descriptions is crucial for floral design educators who teach verbal processors. For example, textual descriptions can be used to explain flower arrangement procedures, annotations can be added to images and videos, and verbal processors can be encouraged to take notes when viewing images. Such measures can enable verbal processors to successfully receive and process information. This study also observed that working memory (r = 0.521, p < 0.000) and cognitive style (r = 0.474, p < 0.000) were significantly correlated with floral design ability and that the visual processor cognitive style may be a predictor of visual creativity [54]. Therefore, cognitive style is a suitable criterion for business owners to recruit floral designers.

Finally, cognitive style and working memory jointly explained 37.5% of the total variance in floral design ability, which indicated that 62.5% of the variance is explained by other unknown factors. The possible reason is that the subject is a freshman with no experience in flower arrangement. Consequently, some participants were required to overcome difficulties before creating actual flower arrangements. Other possible factors for floral design ability include learning attitude and spatial ability. Therefore, researchers can explore such factors to gain a more comprehensive understanding of instructing floral design students and develop suitable teaching methods that improve learning outcomes.

5. Conclusions

We divided the participants into two cognitive style groups and two working memory groups to analyze students’ performance of floral design in a semispherical table potted flower test. The results verified that floral design ability was significantly correlated with cognitive style and working memory. Participants who were visual processors performed more favorably than those who were verbal processors, and the high working memory group performed more favorably than the low working memory group. Both working memory and cognitive style were significant predictors of floral design ability and jointly explained 37.5% of the total variance. Therefore, floral design courses should diversify their teaching materials and methods. For example, computer games, cards, and chess can be used to improve learners’ working memory and indirectly enhance their floral design ability. Furthermore, activities such as watching hands-on demonstrations, online videos, and flower arrangements created by famous artists can facilitate learning for visual processors. When teaching verbal processors, teachers should consider including textual information for flower arrangement procedures. The study results can also serve as a reference for business owners to recruit floral designers.