International Journal of Research and Innovation in Social Science

Submission Deadline-29th November 2024
November 2024 Issue : Publication Fee: 30$ USD Submit Now
Submission Deadline-05th December 2024
Special Issue on Economics, Management, Sociology, Communication, Psychology: Publication Fee: 30$ USD Submit Now
Submission Deadline-20th November 2024
Special Issue on Education, Public Health: Publication Fee: 30$ USD Submit Now

Aesthetic Characteristics Skills of the Students through Visual Understanding and Visual Matching Skills

  • Borneo S. Vijar III
  • Galilei Jade DR. Morale
  • Mhia B. Silverio
  • Joseline M. Santos
  • Reniel Renz C. Gallardo
  • 1785-1798
  • Jul 12, 2024
  • Education

Aesthetic Characteristics Skills of the Students through Visual Understanding and Visual Matching Skills

Borneo S. Vijar III, Galilei Jade DR. Morale, Mhia B. Silverio, Joseline M. Santos, and Reniel Renz C. Gallardo

Bulacan State University, City of Malolos, Bulacan, Philippines

DOI: https://dx.doi.org/10.47772/IJRISS.2024.803128S

Received: 20 May 2024; Revised: 06 June 2024; Accepted: 12 June 2024; Published: 12 July 2024

ABSTRACT

This study aimed to improve students’ aesthetic sensibilities by honing their visual comprehension and matching abilities. Visual Understanding encompasses individuals’ capacity to grasp various aspects of clothing, including gender appropriateness, color coordination, size suitability, occasion relevance, and weather adaptation. Visual Matching, on the other hand, pertains to students’ proficiency in selecting and combining garments to craft diverse clothing ensembles.

Conducted as a quantitative research endeavor, employing a correlational research design, this study utilized stratified sampling to gather data from Grade 10 students at Laboratory High School, Bulacan State University, Malolos Bulacan with the total of 140 samples. The research employed a survey questionnaire divided into three parts. The first part gathered demographic information such as section, gender, and Technical Livelihood Education (TLE) focus. The second part, completed by grade 10 students of various specializations, assessed visual understanding skills using a research-based questionnaire inspired by the Textual Value Chain (2020). The third part, also completed by grade 10 students, measured visual matching skills using an adapted questionnaire based on Ofori (2014), where participants selected options reflecting their feelings or opinions on provided statements or questions. Data collection occurred at Laboratory High School after obtaining permission from the principal. The Grade 10 Head Chairman assisted in selecting students randomly from each section, divided by gender. Researchers secured necessary permissions for students to participate during class time, considering ethical and time constraints.

Finally, collected data were submitted for statistical analysis with simple linear regression. Prior to data collection, researchers obtained informed consent due to the respondents being minors. The findings revealed a significant correlation between visual understanding and students’ visual matching skills, indicating that a nuanced comprehension of fashion facilitates adept clothing selection and style creation.

Keywords: Visual Understanding, Visual Matching, Aesthetic Characteristic, Factors, Enhanced, Selecting, Fashion

INTRODUCTION

Fashion serves as a universal means of communication, enabling individuals to convey their identities, beliefs, and values to the world. According to Malik (2023), an individual’s personal style could narrate a tale of their life experiences and personality traits, serving as a medium for connection with others. Furthermore, fashion provided a platform for self-expression, granting individuals the liberty to explore and exhibit their uniqueness through diverse styles, colors, and patterns. Fashion provides a platform for individuals to showcase their uniqueness, creativity, and personality. It transcends mere trend-following, serving as a medium for making statements and expressing oneself authentically. Confidence often accompanied wearing attire that resonated positively, instilling a sense of empowerment and bolstering self-esteem. It wasn’t solely about appearance; rather, it encompassed how one felt. Donning an outfit that exuded confidence and beauty could noticeably impact posture, attitude, and overall demeanor. Fashion, as an art form, offered women a canvas to unleash their creativity. Hence, understanding the essence of fashion and its adaptability to various occasions, climates, and life moments held significant importance.

In the Philippines, as per Salazar (2021), fashion has assumed significant importance among many individuals, particularly the youth. It serves as a form of concealment for some and a showcase for others, allowing them to express their creativity through carefully curated ensembles that reflect their identity and personal preferences. However, a recent study by Gervis (2021), analyzing the wardrobes of 2,000 men and women, revealed that the average individual experiences ‘wardrobe panic’ approximately 36 times a year due to feeling unprepared or lacking suitable attire. Furthermore, as reported by Bigtas (2019) of GMA Multimedia Production, a significant portion of Filipinos, about 60 percent, disposed of their clothing due to size issues, while 46 percent did so because of damage. Additionally, 34 percent discarded clothes with faults, 21 percent got rid of outfits deemed “outdated,” and 14 percent simply grew tired of wearing them.

While many studies have focused on visual understanding or visual literacy skills, as highlighted by Thompson (2019), In the realm of proficiently discovering, deciphering, assessing, and generating visuals and visual content, along with scrutinizing the cultural, moral, artistic, intellectual, and technical elements of visual materials, there exists a scarcity of studies on the influence of visual comprehension on individuals’ aesthetic traits via visual correlation. Existing research primarily utilizes visual content to understand visual compatibility and perform matching in a latent space. However, despite extensive studies on visual matching and visual understanding, there has been little investigation into how visual understanding influences students’ aesthetic characteristics through visual matching.

This study aims to determine whether students can visually understand fashion and match clothes visually to reflect their aesthetic characteristics. Understanding visual compatibility could help individuals easily identify matching clothing, provided they have a clear grasp of fashion. The lack of aesthetic characteristics among respondents is a key concern addressed in this research. By identifying visual understanding, individuals can more easily match clothing to their aesthetic characteristics or style.

Researchers asserted that there were no rigid rules in the realm of fashion. As highlighted by Slone (2021), the fashion industry gradually embraced concepts such as inclusivity and diversity, acknowledging that not all individuals shared the same physical appearance, nor did they necessarily aspire to dress alike. Varied tastes and perspectives in clothing and self-presentation were recognized among people. The selection of clothing, as outlined by Textile Value Chain (2020), was influenced by several factors including age, season, income, occasion, and prevailing fashion trends. Additionally, considerations such as personality, climate, occupation, and body type were deemed significant in the decision-making process related to attire.In this study, researchers examined the relationship between visual matching and visual understanding among Grade 10 students in the context of fashion. Previous research predominantly relied on recommendation loss as the sole guiding factor for visual understanding and matching. While these methods effectively captured basic characteristics such as color, texture, and shape of input items, they did not directly address the visual signals of the output items to be recommended.

Presently, fashion experts have the ability to disseminate their fashion advice through platforms like fashion-oriented online communities. These experts typically showcase their outfit compositions, each comprising multiple complementary fashion items such as a top, bottom, and pair of shoes. These compositions are accompanied by both images and textual metadata, including categories and titles. The wealth of fashion data available offers opportunities for clothing matching, particularly in matching complementary fashion items by Liu (2019).

This study aimed to assist students in understanding how their visual understanding influenced their clothing choices across various factors. Visual understanding was assessed based on gender, size, color, weather conditions, and occasion. The visual matching skills of the respondents were evaluated in terms of their influence and various factors including physical, aesthetic, economic, and psycho-emotional factors. Following the analysis, researchers identified the relationship between visual understanding and the matching skills of the students using a quantitative method. Quantitative methods involve collecting and analyzing numerical data, enabling researchers to Recognize trends, means, examine cause-and-effect connections, forecast outcomes, and extrapolate findings to broader demographics.

Statement of the problem

The general problem of this study is: How may the aesthetic characteristics of the respondents be enhanced through determining the visual understanding and visual matching?

Research Questions

Specifically, it seeks to answer the following questions:

  1. How can we analyze the visual understanding of respondents in terms of the following variables: gender, size (body type), color preferences, response to weather conditions, and occasions (formal, casual, etc.)?
  2. How can we interpret the visual matching ability of respondents in terms of the influence of fashion trends, physical attributes (such as body shape), aesthetic preferences, economic considerations (budget), and psycho-social factors (peer influence, cultural background)?
  3. Is there a statistically significant relationship between the visual understanding and visual matching skills of the respondents?
  4. What specific fashion websites can be recommended to improve the aesthetic characteristics of respondents?

Hypotheses

The researchers hypothesize that the following statements will be rejected in subjecting the data into statistical test:

H01. There is no significant relationship between the visual understanding in the aesthetic characteristics skills of the respondents.

METHOD

The study utilized quantitative methods, employing a correlational research design to examine the relationship between visual understanding skills and visual matching skills of Grade 10 students at Laboratory High School of Bulacan State University. The researchers employed adapted-modified questionnaires to assess these skills and proposed a fashion website to assist individuals with visual challenges in understanding and matching clothing.

The research was conducted at the Laboratory High School of Bulacan State University, focusing on Grade 10 students due to their accessibility and critical developmental stage. Stratified sampling was used to ensure representation across different sections and specializations, with a target sample size of 140 students. Results showed a higher participation rate among male students, indicating a greater interest in aesthetic characteristics among males. The Science, Technology, and Engineering (STE) section had the highest number of respondents due to its unique class structure.

The research instrument consisted of a survey questionnaire with three parts: demographic traits, visual understanding skills assessment, and visual matching skills assessment. Data collection was conducted with proper authorization and ethical considerations, ensuring voluntary informed consent, privacy protection, and respect for participants’ rights and dignity. Statistical analysis included summary statistics and Pearson’s Correlation Coefficient to examine the correlation between visual comprehension and matching abilities. The study also outlined verbal interpretations for the scales used in analyzing the questionnaire responses. Throughout the research process, ethical considerations were paramount, with measures taken to minimize risks to participants and ensure research integrity, including transparency in methods and findi

RESULT

Part 1: Analysing Visual understanding skills of the respondents through gender, size, color, weather and Occasions.

Table 6: Visual Understanding skills in terms of Gender.

Indicators Ave Rating SD Description Interpretation
Gender
1.    I understand clothes that are appropriate for men. 3.75 0.60 Always Highly Understand
0.    I understand clothes that are appropriate for women. 3.75 0.59 Always Highly Understand
0.    I understand clothes that are appropriate to your gender. 3.72 0.66 Always Highly Understand
0.    I understand any fashion suited for men. 3.68 0.64 Always Highly Understand
0.    I understand any fashion suited for women. 3.70 0.64 Always Highly Understand
OVERALL 3.72 0.63 Always Highly Understand

SD-Standard Deviation

Respondents demonstrate a commendable grasp of clothing suitable for different genders, as evidenced by an overall rating of 3.72, indicating a high level of comprehension. While the standard deviation (SD) of 0.63 reveals some variability among respondents’ ratings, there remains a notable consistency in understanding gender-appropriate clothing. The researchers suggest that mutual understanding of fashion between males and females arises from gendered clothing, as demonstrated by Akdemir (2021), which shows how individuals express their gender identity through clothing choices. This emphasizes clothing’s role in reflecting gender identity and potentially challenging societal norms.

Table 5: Visual Understanding skills in terms of Size.

Indicators Ave Rating SD Description Interpretation
Size
1.   I understand the different body types. 3.79 0.53 Always Highly Understand
0.   I understand the different sizes of clothes. 3.85 0.40 Always Highly Understand
0.   I understand any fashion suited for different body types. 3.61 0.70 Always Highly Understand
0.   I consider size when buying clothes. 3.86 0.37 Always Highly Understand
0.   I follow the appropriate size based on your body. 3.69 0.55 Always Highly Understand
OVERALL 3.76 0.51 Always Highly Understand

The overall rating for understanding different body types and sizes among respondents is 3.76, indicating a consistently high level of comprehension in this area. The standard deviation (SD) of 0.51 suggests some variability in the ratings among respondents, but overall, there is a strong level of understanding across different body types and sizes.  The findings indicate that respondents have a strong grasp of different body types, clothing sizes, and the importance of size in clothing selection. Hidayati’s (2020) highlights fashion designers’ and stylists’ meticulous examination of the relationship between body shapes and modern fashion trends, emphasizing the importance of tailoring style recommendations to individual body attributes. The study underscores the significance of dressing according to one’s body shape, whether hourglass, rectangle, round, or inverted triangle, to enhance positive features.

Table 6: Visual Understanding skills in terms of Color.

Indicators Ave Rating SD Description Interpretation
Color
1. I understand different kinds of colors. 3.76 0.60 Always Highly Understand
0. I understand what color of your clothes suited your skin type. 3.19 0.86 Sometimes Often Understand
0. I understand how to choose color for my clothes. 3.32 0.81 Sometimes Often Understand
0. I wear contrast colors every time you wear clothes. 3.03 0.79 Sometimes Often Understand
0. I understand what color of clothes are suited for different bodies. 3.08 0.92 Sometimes Often Understand
OVERALL 3.28 0.79 Sometimes Often Understand

SD- Standard Deviation

Respondents exhibit a moderate level of comprehension across various aspects of color in clothing, as indicated by an overall rating of 3.28. The standard deviation (SD) of 0.79 highlights variability in ratings among respondents, suggesting differing levels of understanding across different facets of color in clothing.  While respondents consistently demonstrate understanding of different kinds of colors, with an average rating of 3.76, there is less uniformity in other aspects. For example, comprehension of what colors of clothes suit one’s skin type received a lower rating of 3.19, indicating that respondents only sometimes or often understand this aspect. Similarly, respondents sometimes or often understand how to choose colors for their clothes, as reflected in a rating of 3.32. Additionally, ratings for wearing contrast colors every time one wears clothes (3.03) and understanding what colors of clothes are suited for different body types (3.08) are relatively low.  Xiong (2023) highlights the importance of matching colors to convey emotion in design. However, there’s insufficient data-driven support for understanding color perception in color matching patterns. The study suggests an innovative technique integrating aesthetics. Respondents show moderate understanding of color in clothing, but improvements are needed, especially in selecting colors that complement skin and body types.

Table 7: Visual Understanding skills in terms of Weather.

Indicators Ave Rating SD Description Interpretation
Weather 
1.    I wear clothes that are appropriate in hot weather. 3.63 0.54 Always Highly Understand
0.    I wear clothes that are appropriate in cold weather. 3.66 0.57 Always Highly Understand
0.    I wear clothes that are appropriate on a rainy day. 3.55 0.68 Always Highly Understand
0.    I wear clothes that are appropriate in snowwing. 3.09 1.15 Sometimes Often Understand
0.    I wear clothes that are appropriate in windy weather. 3.49 0.71 Sometimes Often Understand
OVERALL 3.48 0.73 Sometimes Often Understand

SD- Standard Deviation

Respondents demonstrate a moderate level of comprehension regarding appropriate clothing choices for various weather conditions, with an overall rating of 3.48. The standard deviation (SD) of 0.73 suggests variability in ratings among respondents, indicating differing levels of understanding across different weather scenarios. Respondents consistently demonstrate a high level of understanding in selecting clothes suitable for hot weather (3.63), cold weather (3.66), and rainy days (3.55), as indicated by their average ratings. However, there is less consistency in understanding appropriate clothing for snowing weather, with a lower rating of 3.09, suggesting that respondents sometimes or often understand this aspect. Similarly, understanding of appropriate clothing for windy weather received a moderate rating of 3.49, indicating that respondents sometimes or often understand this aspect as well. This underscores the necessity for further education or guidance. Liu (2017) found that the system can provide weather-specific clothing recommendations. It can suggest suitable attire based on the user’s wardrobe or propose combinations with specified reference clothing. The lower rating for appropriate clothes in snowing conditions may be due to the tropical climate of the Philippines, where snow attire is less familiar.

Table 8: Visual Understanding skills in terms of Occasion

Indicators Ave Rating SD Description Interpretation
Occasion 
1.    I understand the appropriate clothes for a casual gathering. 3.79 0.51 Always Highly Understand
0.    I understand the appropriate clthes for a spiritual celebration. 3.74 0.54 Always Highly Understand
0.    I understand the appropriate clothes for a formal event . 3.81 0.49 Always Highly Understand
0.    I understand the appropriate clothes during beach time. 3.71 0.61 Always Highly Understand
0.    I understand the appropriate clothes while playing your favorite sports. 3.73 0.57 Always Highly Understand
OVERALL 3.75 0.54 Always Highly Understand

SD- Standard Deviation

Respondents demonstrate a commendable high level of comprehension regarding appropriate clothing choices for different occasions, as evidenced by an overall rating of 3.75. The minimal standard deviation (SD) of 0.54 suggests little variability in ratings among respondents, underscoring a high degree of consistency in understanding clothing selections for diverse events. Respondents consistently demonstrate a high level of understanding in selecting appropriate clothing for different occasions, as indicated by their average ratings. Whether it’s for a casual gathering (3.79), a spiritual celebration (3.74), a formal event (3.81), beach time (3.71), or playing favorite sports (3.73), respondents consistently exhibit a strong comprehension of appropriate clothing choices across various scenarios. Vanissa Closet’s blog (2023) highlights that dressing differently for various occasions is a symbolic strategy for navigating social, professional, and cultural settings. It allows individuals to meet expectations, express themselves, and adjust to specific needs. The study indicates that respondents have a strong grasp of suitable clothing choices for different occasions, showcasing familiarity with appropriate attire for each setting. This underscores their capability to adapt clothing choices based on event requirements.

Part 2:  Interpreting Visual Matching skills of the respondent through influence, physical factors, aesthetic factors, economic factors and psycho-social factors.

Table 9: This section refers to the factors that affect your fashion clothing selection.

Indicators Ave Rating SD Description Interpretation
Influence
1.   I made my choice in clothing. 3.61 0.60 Always Extremely Match
0.   My parents made choices in my clothing. 2.39 0.87 Rarely Rarely Match
0.   My friends made choices in my clothing. 1.85 0.90 Rarely Rarely Match
0.   My partner made choices in my clothing. 1.42 0.80 Never Never Match
0.   My classmate made choices in my clothing. 1.50 0.82 Rarely Rarely Match
OVERALL 2.15 0.80 Rarely Rarely Match

SD- Standard Deviation

The overall assessment of the influence of various individuals on respondents’ clothing choices yields a score of 2.15, reflecting a generally low level of external influence. The standard deviation (SD) of 0.80 indicates some variability in influence ratings among respondents, suggesting differing degrees of susceptibility to external influences. Respondents consistently assert their autonomy in clothing choices, reflected in a notable average rating of 3.61. This underscores a strong tendency to independently determine their attire. However, the impact of external figures such as parents (mean: 2.39), friends (mean: 1.85), partners (mean: 1.42), and classmates (mean: 1.50) is considerably lower. This indicates infrequent influence from these sources on respondents’ clothing decisions. This aligns with findings from the Indian Institute of Fashion Technology (2023), which underscores fashion’s historical role in self-expression, identity, and values. Throughout cultures and history, fashion has served as a means for individuals to convey their position and identity, highlighting its profound significance in personal expression.

Table 10: This section refers to the factors that affect your fashion clothing selection.

Indicators Ave Rating SD Description Interpretation
Physical Factor
1.    The type of fabric and texture influence my clothing selection. 3.56 0.55 Always Extremely Match
0.    The size, length and fit influence my clothing selection. 3.80 0.40 Always Extremely Match
0.    The style of clothing items influence my clothing selection. 3.76 0.43 Always Extremely Match
0.    The weather and environment influence my clothing selection. 3.60 0.61 Always Extremely Match
0.    The comfort and protection influence my clothing selection. 3.76 0.45 Always Extremely Match
0.    The label, brand or designer name influences my clothing selection. 2.79 1.04 Sometimes Moderately Match
0.    The uniqueness of the style influences my clothing selection. 3.34 0.79 Sometimes Moderately Match
0.    The care and maintenance influence my clothing selection. 3.53 0.70 Always Extremely Match
OVERALL 3.52 0.62 Always Extremely Match

 SD- Standard Deviation

The overall rating for the influence of various physical factors on respondents’ clothing selection is 3.52, indicating a consistently high level of impact in this area. The standard deviation (SD) of 0.62 suggests minimal variability in influence ratings among respondents, highlighting a strong level of consistency in the influence of physical factors on clothing choices. Respondents consistently report that factors such as the type of fabric and texture (mean: 3.56), size, length, and fit (mean: 3.80), style of clothing items (mean: 3.76), weather and environment (mean: 3.60), and comfort and protection (mean 3.76) always or extremely influence their clothing selection. This underscores the significant role that physical attributes play in guiding respondents’ fashion choices. Furthermore, factors such as the label, brand, or designer name (mean: 2.79), uniqueness of the style (mean: 3.34), and care and maintenance (mean: 3.53) sometimes or moderately influence clothing selection. While these factors still exert some influence, they are not as consistently impactful as the physical attributes mentioned earlier. The findings suggest that physical factors strongly guide respondents’ clothing selection processes. Insights from Fable Street (2023) support these findings, emphasizing the importance of a good fit in clothing. Understanding one’s unique body shape and measurements is crucial to finding outfits that accentuate best features while ensuring comfort and freedom of movement. While factors like color and occasion still matter, the study suggests that physical attributes strongly influence respondents’ clothing selection processes.

Table 11: This section refers to the factors that affect your fashion clothing selection.

Indicators Ave Rating SD Description Interpretation
Aesthetic Factor
1. The color influences my clothing selection. 3.63 0.59 Always Extremely Match
0. The attractiveness/neatness influence my clothing selection. 3.77 0.44 Always Extremely Match
0. The design influenced my clothing selection. 3.76 0.47 Always Extremely Match
0. The simplicity/formality influence my clothing selection. 3.74 0.54 Always Extremely Match
0. The way accessories influence my clothing selection. 3.48 0.73 Sometimes Moderately Match
OVERALL 3.68 0.56 Always Extremely Match

SD- Standard Deviation

The overall rating for the influence of various aesthetic factors on respondents’ clothing selection is 3.68, indicating a consistently high level of impact in this area. The standard deviation (SD) of 0.56 suggests minimal variability in influence ratings among respondents, highlighting a strong level of consistency in the influence of aesthetic factors on clothing choices.  Respondents consistently report that factors such as color (mean: 3.63), attractiveness/neatness (mean: 3.77), design (mean: 3.76), and simplicity/formality (mean: 3.74) always or extremely influence their clothing selection. This underscores the significant role that aesthetic considerations play in guiding respondents’ fashion choices. However, the influence of accessories (mean: 3.48) is rated slightly lower, indicating that respondents sometimes or moderately consider accessories in their clothing selection.  Matte’s study (2018) indicates that the aesthetic dimension significantly impacts clothing comfort. It suggests that understanding psychological comfort in clothing can benefit from recognizing aesthetics’ role in the wearer-clothing interaction. This includes not only appearance but also pleasure perceived through the five senses. The findings highlight the strong influence of aesthetic factors on respondents’ clothing choices, emphasizing the importance of color, attractiveness, design, and simplicity/formality in shaping fashion decisions.

Table 12: This section refers to the factors that affect your fashion clothing selection.

Indicators Ave Rating SD Description Interpretation
Economic Factors
1.The quality influences my clothing selection. 3.75 0.52 Always Extremely Match
0.The durability influences my clothing selection. 3.81 0.41 Always Extremely Match
0.The price influences my clothing selection. 3.59 0.68 Always Extremely Match
0.The availability influences my clothing selection. 3.69 0.55 Always Extremely Match
0.The time influences my clothing selection. 3.34 0.73 Sometimes Moderately Match
OVERALL 3.64 0.58 Always Extremely Match

 SD- Standard Deviation

The overall rating for the influence of various economic factors on respondents’ clothing selection stands at 3.64, suggesting a consistently high impact in this domain. With a standard deviation (SD) of 0.58, there appears to be minimal variability in influence ratings among respondents, indicating a strong consistency in the impact of economic factors on clothing choices. Respondents consistently emphasize the significance of factors such as quality (mean: 3.75), durability (mean: 3.81), price (mean: 3.59), and availability (mean: 3.69), which always or extremely influence their clothing selection. This underscores the pivotal role that economic considerations play in guiding respondents’ fashion decisions. However, the influence of time (mean: 3.34) receives a slightly lower rating, suggesting that respondents sometimes or moderately consider time constraints in their clothing selection. These findings underscore the importance of economic factors in clothing selection, showing how individuals prioritize quality, durability, price, and availability when making fashion decisions. Anth Clothing’s research (2023) supports this, indicating that consumer spending on fashion items can fluctuate based on economic conditions, influencing businesses in the sector. These findings highlight the complex interplay of psycho-social influences on clothing choices, showing how various factors shape individuals’ fashion preferences and behaviors.

Table 13: This section refers to the factors that affect your fashion clothing selection.

Indicators Ave Rating SD Description Interpretation
Psycho-Social Factors
1.    The suitability for occasion influences my clothing selection. 3.77 0.50 Always Extremely Match
0.    Fashion influences my clothing selection. 3.54 0.72 Always Extremely Match
0.    The decency influences my clothing selection. 3.69 0.59 Always Extremely Match
0.    The opinion of others influences my clothing selection. 2.81 1.03 Sometimes Moderately Match
0.    My religious expectation influences my clothing selection. 2.59 1.04 Sometimes Moderately Match
0.    My parents’ approval influences my clothing selection. 2.88 0.91 Sometimes Moderately Match
0.    My mood influences my clothing selection. 3.41 0.95 Sometimes Moderately Match
OVERALL 3.24 0.82 Sometimes Moderately Match

SD- Standard Deviation

The overall assessment of the influence of psycho-social factors on respondents’ clothing choices yields a rating of 3.24, suggesting a moderate impact in this regard. With a standard deviation (SD) of 0.82, there is some variability among respondents, indicating that while certain factors strongly affect clothing decisions for some, they may have less impact on others. Respondents consistently prioritize factors such as occasion suitability (mean: 3.77), fashion (mean: 3.54), and decency (mean: 3.69), indicating a preference for appropriateness, current trends, and personal values when selecting attire.  Conversely, the influence of factors like others’ opinions (mean: 2.81), religious expectations (mean: 2.59), parents’ approval (mean: 2.88), and mood (mean: 3.41) receive lower ratings. This suggests that while these factors sometimes or moderately influence clothing choices, they are not as consistently impactful as occasion suitability, fashion, and decency.  As discussed in the Fashion Innovation blog (2022), clothing serves as a form of communication, conveying messages about personalities, beliefs, and social identities. While these factors sometimes moderately influence clothing choices, occasion suitability, fashion, and decency are consistently impactful.

Part 3: Identifying the significant relationship between the visual understanding and visual matching skills of the respondents.

Table 14: Correlation Analysis Between the Visual Understanding and Visual Matching Skills of the Students

Variables Correlated r Description Sig-value Decision Interpretation
Visual Understanding and Visual Matching 0.5598 A strong positive uphill (positive) linear relationship 0.00001 Reject the Null Hypothesis There is a significant relationship

Table 1 shows the significant relationship of visual understanding and visual matching skills of the students. Having the value of r=0.5598 shows a strong positive uphill (positive) linear relationship. The data indicated from Table 1 shows the relationship of visual understanding and visual matching in aesthetic characteristics of the students. In addition, the p-value score is 0.00001 which is less than 0.5 so that the null hypothesis is rejected. The data interpretation reveals a significant correlation between students’ visual understanding and matching skills regarding aesthetic attributes. Improving students’ visual understanding can enhance their visual matching skills, as indicated by the researcher’s findings. Similarly, the Fashion Recommendation Machine (FARM) model by Lin et al. (2019) suggests that enhancing the encoding of aesthetic information improves visual matching through a refined layer-to-layer matching technique.

CONCLUSIONS

The researchers found that students’ aesthetic characteristics are related by their visual understanding and matching skills. Visual understanding involves grasping fashion concepts like gender, size, color, weather, and occasion, enabling individuals to make informed clothing choices. Visual matching encompasses factors such as influence, physical attributes, aesthetics, economics, and social considerations. The data revealed a significant correlation between visual understanding and matching skills.

This study addressed a gap in research by exploring the connection between visual understanding, matching skills, and aesthetic characteristics. A broad understanding of fashion allows people to effortlessly identify and select clothing, shaping their personal style. The researchers observed that students independently chose their attire, influenced by various factors like peers, economic conditions, and current trends.

Understanding fashion empowers students to make informed clothing choices, enhancing their aesthetic appeal. Knowledge of what’s appropriate and stylish helps individuals navigate wardrobe decisions confidently, minimizing struggles in selecting suitable attire for different occasions. Moreover, this understanding aids in prudent shopping decisions, allowing individuals to select clothes wisely and save money.

In summary, this research not only benefits individuals in fashion and clothing selection but also promotes financial savvy by making informed purchasing decisions.

ACKNOWLEDGMENT

The researchers extend their warmest gratitude to the individuals whose support and guidance were instrumental in bringing this research to fruition. Firstly, heartfelt appreciation is extended to our Research Adviser Dr. Joseline Santos, whose unwavering presence and meticulous feedback have been invaluable. Her insightful guidance and feedback have greatly contributed to refining and shaping our research. Special thanks are also owed to our Research Validators: Dr. Romulo B. Mercado Jr., Mrs. Maria Lea B. Tamboong Lpt., and Mr. Erwin D. Tarroquin, whose expertise in grammar, professional connections, and research formatting ensured the quality and credibility of our work. We are deeply grateful to our Panelists, whose invaluable insights and constructive feedback have enriched our research journey, offering invaluable suggestions for improvement.

Additionally, sincere thanks are extended to our friends and classmates for their continuous support and assistance, clarifying unclear concepts and providing valuable information.

Our panelists during the final defense, who provided valuable recommendations for enhancing our paper, were Ms. Daisylene G. Ocsan, Mr. Reniel Renz C. Gallardo, and Dr. Sheila Bernaldez.” Finally, our heartfelt gratitude goes to Dr. Teody C. San Andres, President of Bulacan State University, and Dr. Rafel DJ. Dayao, Dean of the College of Education, for their unwavering support. Special recognition is also extended to our beloved adviser, Mr. Noel P. Lomerio Jr., whose guidance and counsel have been invaluable, particularly in time management and decision-making.

REFERENCES

  1. Akdemir, N. (2021). Deconstruction of gender stereotypes through fashion. European Journal of Social Science Education and Research, 8(2), 10-17.
  2. Admin, I. (2023, February 21). Self-Expression through Fashion – IIFT blog. IIFT Blog. https://www.iiftbangalore.com/blog/the-art-of-self-expression-how-fashion-can-speak-volumes-about-you/
  3. Bhandari, B., Ray, S., & Goswami, S. (2021). Comparative study of positive predictive value of diagnostic single versus dual median branch block for radiofrequency neurotomy in lumbar facet joint syndrome. Indian Journal of Pain, 35(2), 146-149.
  4. Cannon, C. (2022). Non-binary gender identity and algorithmic-psychometric marketing legibility. Feminist Media Studies, 22(6), 1529-1545.
  5. Chattaraman, V., & Rudd, N. A. (2020). Preferences for aesthetic attributes in clothing as a function of body image, body cathexis and body size. Clothing and Textiles Research Journal, 24(1), 46-61.
  6. Chen, X., Chen, H., Xu, H., Zhang, Y., Cao, Y., Qin, Z., & Zha, H. (2019, July). Personalized fashion recommendation with visual explanations based on multimodal attention network: Towards visually explainable recommendation. In Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 765-774).
  7. Chen, Y., Gong, S., & Bazzani, L. (2020). Image search with text feedback by visiolinguistic attention learning. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 3001-3011).
  8. em retratos de Estado, P. I. (2022). The clothes and reigns during Brazilian Independency. Acervo, 35(3), 1-27.
  9. Entwistle, J. (2023). The fashioned body: Fashion, dress and modern social theory. John Wiley & Sons.
  10. Fereidouni, H., Omidi, A., & Tamannaeifar, S. (2019). The effectiveness of choice theory education on happiness and self-esteem in university students. Practice in Clinical Psychology, 7(3), 207-214.
  11. Gao, G., Liu, L., Wang, L., & Zhang, Y. (2019). Fashion clothes matching scheme based on Siamese Network and AutoEncoder. Multimedia Systems, 25, 593-602.
  12. Gervis, D. (2021). Addition of a second atomic source for a dual beam atom sensor (Doctoral dissertation). Naval Postgraduate School, Monterey, CA.
  13. Gibson, J. J. (1966). The senses considered as perceptual systems.
  14. Gierlach, M. T. (2020). Multi-task deep learning models in visual fashion understanding.
  15. GMA News Online. (n.d.). The perils of fast fashion. GMA Network. https://www.gmanetwork.com/news/specials/content/61/the-perils-of-fast-fashion/
  16. Gong, W., & Khalid, L. (2021). Aesthetics, personalization and recommendation: A survey on deep learning in fashion. arXiv preprint arXiv:2101.08301.
  17. Hidayati, S. C., Goh, T. W., Chan, J. S. G., Hsu, C. C., See, J., Wong, L. K., … & Cheng, W. H. (2020). Dress with style: Learning style from joint deep embedding of clothing styles and body shapes. IEEE Transactions on Multimedia, 23, 365-377.
  18. Hourigan, S. R., & Bougoure, U. S. (2020). Towards a better understanding of fashion clothing involvement. Australasian Marketing Journal, 20(2), 127-135.
  19. Hsiao, W. L., & Grauman, K. (2020). ViBE: Dressing for diverse body shapes. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 11059-11069).
  20. Hur, Y. J., Etcoff, N. L., & Silva, E. S. (2023). Can Fashion Aesthetics be Studied Empirically? The Preference Structure of Everyday Clothing Choices. Empirical Studies of the Arts, 41(2), 525-5.
  21. Jardim, M. (2021). The plastic of clothing and the construction of visual communication and interaction: A semiotic examination of the eighteenth-century French dress. Semiotica, 2021(242), 17-37.
  22. Jiang, S., Li, J., & Fu, Y. (2021). Deep learning for fashion style generation. IEEE Transactions on Neural Networks and Learning Systems, 33(9), 4538-4550.
  23. Khaund, A., Thapar, D., & Nigam, A. (2020). PoshakNet: Framework for matching dresses from real-life photos using GAN and Siamese Network. In Computer Vision, Pattern Recognition, Image Processing, and Graphics: 7th National Conference, NCVPRIPG 2019, Hubballi, India, December 22–24, 2019, Revised Selected Papers 7 (pp. 122-132). Springer Singapore.
  24. Kim, D., Saito, K., Mishra, S., Sclaroff, S., Saenko, K., & Plummer, B. A. (2021). Self-supervised visual attribute learning for fashion compatibility. In Proceedings of the IEEE/CVF International Conference on Computer Vision (pp. 1057-1066).
  25. Kodžoman, D. (2019). The psychology of clothing: Meaning of colors, body image and gender expression in fashion. Textile & Leather Review, 2(2), 90-103.
  26. Koopman, J., Matta, F. K., Scott, B. A., & Conlon, D. E. (2015). Ingratiation and popularity as antecedents of justice: A social exchange and social capital perspective. Organizational Behavior and Human Decision Processes, 131, 132-148.
  27. Kuzmichev, V. E., Tislenko, I. V., & Adolphe, D. C. (2019). Virtual design of knitted compression garments based on bodyscanning technology and the three-dimensional-to-two-dimensional approach. Textile Research Journal, 89(12), 2456-2475.
  28. Lazazzera, M. (2023). Finding inspiration in the archives. The New York Times, NA-NA.
  29. Lin, Y., Ren, P., Chen, Z., Ren, Z., Ma, J., & De Rijke, M. (2019). Explainable outfit recommendation with joint outfit matching and comment generation.
  30. Lin, Y., Ren, P., Chen, Z., Ren, Z., Ma, J., & De Rijke, M. (2019, May). Improving outfit recommendation with co-supervision of fashion generation. In The World Wide Web Conference (pp. 1095-1105).
  31. Liu, J., Song, X., Chen, Z., & Ma, J. (2019). Neural fashion experts: I know how to make the complementary clothing matching.
  32. Liu, J., Song, X., Chen, Z., & Ma, J. (2020). MGCM: Multi-modal generative compatibility modeling for clothing matching. Neurocomputing, 414, 215-224.
  33. Liu, L., Silva, I., Nogueira, P., Magalhães, A., & Martins, E. User Aesthetics Identification for Fashion Recommendations. Recommender Systems in Fashion and Retail, 41.
  34. Liu, Y. J., Gao, Y. B., Bian, L. Y., Wang, W. Y., & Li, Z. M. (2018). How to wear beautifully? Clothing pair recommendation. Journal of Computer Science and Technology, 33, 522-530.
  35. Majuran, S., & Ramanan, A. (2023). A single-stage fashion clothing detection using multilevel visual attention. The Visual Computer, 39(12), 6609-6623.
  36. Malik, M., Aziz, A., Iqbal, Z., & Shahid, A. (2023). Exploring potential factors causing intercultural miscommunication using Chick’s and Xin’s model. Journal of Policy Research, 9(2), 465–473. https://doi.org/10.5281/zenodo.8285452
  37. Matté, L. L., Broega, A. C., & Pinto, M. E. B. (2018). When clothing comfort meets aesthetics. In Textiles, Identity and Innovation: Design the Future (pp. 55-60). CRC Press.
  38. Nie, F., Wang, K. Z., & Yan, D. (2023). Supramolecular glasses with color-tunable circularly polarized afterglow through evaporation-induced self-assembly of chiral metal–organic complexes. Nature Communications, 14(1), 1654.
  39. Nie, X., Xu, Z., Zhang, J., & Tian, Y. (2023). Attention-Based Personalized Compatibility Learning for Fashion Matching. Applied Sciences, 13(17), 9638.
  40. Ofori, A., Gadzo, D., & Bates, I. (2014). Transfusion-transmitted malaria: donor prevalence of parasitaemia and a survey of healthcare workers knowledge and practices in a district hospital in Ghana. Malaria Journal, 15, 1-7.
  41. Parthasarathy, S., Jadhav, G. S., & Joshi, N. S. (2023). A Way to Arrange Clothes by Color for the Visually Impaired. In Exergaming Intervention for Children, Adolescents, and Elderly People (pp. 118-127). IGI Global.
  42. Parekh, V., Shaik, K., Biswas, S., & Chelliah, M. (2021). Fine-grained visual attribute extraction from fashion wear. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 3973-3977).
  43. Payne, D. (2022). When the dressing does not fit: choosing the right dressing for the right patient. British Journal of Community Nursing, 27(Sup9), S8-S12.
  44. Perrett, D. I. (2023). Eye color is more important than skin color for clothing color aesthetics. Psychology of Aesthetics, Creativity, and the Arts.
  45. Revenuer, A., Kumar, S., & Johnson, P. (2022). Data-driven fashion insights: Harnessing analytics for trend prediction. Journal of Fashion Marketing, 19(3), 203-218.
  46. Ryoko, A. (2019). Ethics and Society in Tōhoku in March. Tetsugaku Companion to Japanese Ethics and Technology, 1, 219.
  47. Salazar, K. B. (2021). Takes on trends: How globalization influences Philippine fashion. ResearchGate. https://www.researchgate.net/publication/348487568_Takes_on_Trends_How_Globalization_ Influences_Philippine_Fashion
  48. Sidhu, N., Qualter, C., Higgs, E., & Guo, K. (2021). What colour should I wear? How clothing colour affects women’s judgement of other women’s body attractiveness and body size. Acta Psychologica, 218, 103338.
  49. Silva, I. C. R. M. D. (2023). Showing color to the colorblind: the impact of the ColorADD code adoption on consumers’ purchase intention: an analysis of fashion products (Doctoral dissertation).
  50. Slone Partners. (2021, June 18). Top workplaces 2021 – Washington Post. https://www.slonepartners.com/top-workplaces-2021-washington-post/
  51. Smith, J. D., & Johnson, A. (2019). Learning to match clothing from textual feature-based compatible relationships. Journal of Fashion Technology & Textile Engineering, 6(1), 45-56. https://www.researchgate.net/publication/334023379_Learning_to_Match_Clothing_From_Textual_ Feature-Based_Compatible_Relationships
  52. Song, X., Han, X., Li, Y., Chen, J., Xu, X. S., & Nie, L. (2019, October). GP-BPR: Personalized compatibility modeling for clothing matching. In Proceedings of the 27th ACM International Conference on Multimedia (pp. 320-328).
  53. Textile Value Chain. (n.d.). Factors affecting selection of clothing. https://textilevaluechain.in/featured/factors-affecting-selection-of-clothing
  54. Thompson, D. S. (2019). Teaching students to critically read digital images: a visual literacy approach using the DIG method. Journal of Visual Literacy, 38(1-2), 110-119.
  55. Uno, Y. (2015). Aesthetics of Virtual Models: Fashion in the Metaverse. PhilPapers. https://philpapers.org/rec/UNOAVM
  56. Xiong, J., Yuan, L., Wang, M., & Dai, Q. (2023, February). Intelligent color matching method that integrates visual aesthetics. In Proceedings of the 2023 3rd International Conference on Bioinformatics and Intelligent Computing (pp. 195-201).
  57. Xiong, Z., Fu, S., & Fan, M. (2023, November). OperARtistry: An AR-based Interactive Application to Assist the Learning of Chinese Traditional Opera (Xiqu) Makeup. In Proceedings of the Eleventh International Symposium of Chinese CHI (pp. 158-168).
  58. Yin, R., Li, K., Lu, J., & Zhang, G. (2019, May). Enhancing fashion recommendation with visual compatibility relationship. In The World Wide Web Conference (pp. 3434-3440).
  59. Zou, X., Pang, K., Zhang, W., & Wong, W. (2022). How good is aesthetic ability of a fashion model? In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 21200-21209).

Article Statistics

Track views and downloads to measure the impact and reach of your article.

0

PDF Downloads

5 views

Metrics

PlumX

Altmetrics

Paper Submission Deadline

GET OUR MONTHLY NEWSLETTER

Subscribe to Our Newsletter

Sign up for our newsletter, to get updates regarding the Call for Paper, Papers & Research.

    Subscribe to Our Newsletter

    Sign up for our newsletter, to get updates regarding the Call for Paper, Papers & Research.