The Relationship Between University Dormitory Environmental Factors and Students’ Informal Learning Experiences: A Case Study of Three Universities in Guangdong Province

Abstract

In recent decades, university dormitories have gradually evolved from traditional residential spaces into educationally meaningful venues that support informal learning. However, limited research has explored how supportive environmental factors within dormitories influence students’ informal learning experiences. This study aims to evaluate key environmental factors that affect students’ satisfaction with informal learning in dormitory settings. Based on a comprehensive literature review, two types of informal learning behaviors—individual and collaborative—were defined, and a multi-dimensional evaluation framework comprising five categories and 26 environmental indicators was established. Field observations and structured questionnaires were employed to assess students’ satisfaction with each environmental factor and their overall informal learning experiences. Quantitative analyses were conducted to examine the relationships between environmental conditions and learning satisfaction. Results show that all five-factor categories—spatial designs, natural environments, physical settings, social aspects, and resources—positively influence informal learning, with resources being the most impactful. While environmental influences on individual and collaborative learning exhibit minor differences, the overall patterns are consistent. Compared to other informal learning spaces on campus, dormitory users place greater emphasis on spatial controllability. This study further demonstrates the cognitive and emotional value of dormitory environments and proposes targeted directions for optimizing them as informal learning spaces.

1. Introduction

In higher education, campus spaces have traditionally been constructed around two educational paradigms—lecture-based and student-centered—commonly aligned with formal and informal learning, respectively [1]. With the advancement of constructivist learning theory in pedagogy and the growing emphasis by universities on cultivating innovative talents, the importance of informal learning has become increasingly prominent. American adult educator Victoria J. Marsick conceptualizes informal learning as a loosely organized form of active learning, inherently linked to the physical environment and social context in which it occurs. Compared to formal and non-formal learning modes, informal learning is voluntary in nature and develops independently of frameworks imposed by external factors such as instructors or institutions [2].

Scholars widely acknowledge informal learning as a powerful complement to formal education [3,4], enabling the development of students’ social adaptability and emotional resilience [5]. Moreover, this form of learning aids in conveying key societal norms and expectations [6,7] and enhances social abilities through interactive and cooperative experiences [8,9]. Therefore, higher education institutions need to deliberately reimagine and optimize campus spaces to support diverse informal learning practices and ensure student success in a sustainable educational context [10,11].

College students spend a significant portion of their time in dormitories. Especially in China, almost all universities adopt a full-time boarding system for undergraduates, making dormitories one of the most frequently used spaces throughout students’ college years. Traditionally, dormitories have been treated merely as a simple living place, often lacking shared spaces for learning and social interaction. However, as the boundaries between living and learning increasingly blur in modern higher education, there is growing recognition that dormitories hold untapped potential as informal learning environments. Over the past decade, educators and designers have begun to shift perceptions, viewing dormitories as integral components of the educational ecosystem—spaces not only for living, but also for fostering social interaction, personal growth, and self-directed learning [12,13,14]. Compared with academic buildings that serve formal teaching functions, dormitories are particularly conducive to informal and non-institutionalized learning activities [15]. Nonetheless, many dormitory environments still reflect industrialized and institutionalized design logic, characterized by monotonous layouts and rigid functional configurations. Such designs often neglect the psychological needs of users and overlook the role of spatial environments in shaping students lived experiences. Existing research has shown that the physical attributes of a learning environment can significantly influence learners’ emotions, leading to important cognitive and behavioral outcomes. Spaces that offer emotional support and cognitive stimulation can effectively enhance students’ perceived experience and behavioral performance [16]. Therefore, this study advocates for a renewed understanding of the role and function of dormitories and proposes exploring targeted design strategies from the user’s perspective to unlock their unique spatial potential in supporting informal learning.

Currently, more and more studies are beginning to focus on the supportive environment design of university dormitories. Worsley et al. explored the impact of the physical and social structure of dormitories on the mental health of British college students and found that providing interactive spaces designed with diverse interactions in mind is beneficial to students’ physical and mental health [17]. Easterbrook and Vignoles found that setting up shared common areas in dormitories can promote interpersonal relationships among students, thereby improving their happiness [18]. Research by Brown et al. shows that the design of dormitory buildings affects students’ participation and their academic performance [19]. Nurul et al. found in their study that diverse space types and service facilities can improve students’ accommodation satisfaction, thus helping them achieve better academic results [20]. Huang et al. found that dormitory environment indirectly affects college students’ mental health through the mediating role of learning engagement, offering empirical support for the broader educational value of residential settings [21]. Ning and Chen constructed a framework for the POE of university dormitories in China to identify and analyze the factors that affect student accommodation satisfaction. They found that the ease of using the amenities in dormitory rooms, dormitory services, and diversified and personalized design are important factors affecting satisfaction [22]. In addition, some studies have also used POE to investigate residents’ satisfaction with student housing facilities [23,24]. While these studies affirm the influence of dormitory environments on health, behavior, and satisfaction, few have explicitly investigated their role in facilitating informal learning. Addressing this gap, this study believes that it is necessary to have a clearer understanding of dormitory environment design factors that can support informal learning behaviors from the students’ perspective, contributing to the creation of more effective and development-oriented residential learning environments.

In summary, this study highlights the prevalence and importance of informal learning in universities, explores the trend of contemporary university dormitories evolving from simple living spaces into living–learning communities, and emphasizes the need to reconceptualize student dormitories as environments that support informal learning. Based on existing literature and identified research gaps, this study aims to answer the following questions:

• Are informal learning experiences affected by the dormitory environment? Are different types of behaviors affected differently?
• Which dormitory environmental factors have the greatest impact on informal learning experiences?
• Are there differences between dormitory environmental factors that influence informal learning experiences and those in other university spaces? If so, in what aspects are these differences reflected?

2. Materials and Methods

This study employed a three-step methodology. First, a comprehensive literature review and field investigation were conducted to inform the development and selection of questionnaire indicators. Second, on-site surveys were distributed to students from three schools to collect data on their satisfaction with informal learning experiences and various environmental factors. Finally, the collected data were analyzed using IBM SPSS Statistics 24.0 software for descriptive statistics, correlation analysis, and priority analysis.

2.1. Case Selection

This study selected five undergraduate dormitories from three universities in Guangdong: Guangzhou International Campus of South China University of Technology (SCUT-GZIC), Beijing Normal University at Zhuhai (BNU Zhuhai), and Shantou University (STU). The case selection was based on four criteria: (1) research convenience—data could be collected without interference; (2) similar geographical location—all sites are in the same climate zone, minimizing unnecessary external climate factors; (3) availability of diverse public activity spaces—each dormitory includes numerous closed and open areas suitable for informal learning; (4) all three universities operate full-time undergraduate boarding systems, ensuring high dormitory usage and familiarity among students.

This study aims to holistically explore how dormitory environmental factors affect students’ informal learning experiences. To this end, it is necessary to obtain extensive data, including various public spaces. The survey covered all furnished public spaces in the selected dormitories, such as semi-outdoor lounge areas, study rooms, and self-service kitchens (Figure 1). For example, at SCUT-GZIC, the two dormitory buildings are connected by a second-floor corridor, with most public activity spaces located on the first and second floors. The study conducted on-site observations and administered questionnaires within these shared areas (Figure 2).

2.2. Questionnaire Development

Firstly, this study identified types of informal learning behaviors. Beckers et al. divided informal learning into two basic categories: individual learning necessitating concentrated attention and autonomous regulation, alongside group social collaborative learning dependent on peer interaction dynamics [25]; Guo et al. divided informal learning behaviors into personal public learning, personal private learning, teamwork learning and free and open learning according to the four-quadrant classification method [26]; Cox conceptualizes informal learning as comprising multifaceted engagements, incorporating reading, intense revision, quiet consultations with others, collaborative projects, and peer networking [27]. Chen et al. believe that informal learning behaviors include dialogue, seminars, communication, contemplation, and even rest [28]. Based on these studies, this study combines the characteristics of university student dormitories and divides informal learning behaviors into individual learning and collaborative learning. The specific contents are shown in

Table 1. The type and contents of informal learning behaviors.

N	Type	Content
1	Individual Learning	Reading, observing, using electronic devices, private study, contemplation, rest, etc.
2	Collaborative Learning	Dialogue, seminars, communication, group work, socializing, event organization, etc.

.

Based on previous research, the environmental factors that affect informal learning behavior are divided into five basic categories: spatial design, natural environment, physical settings, social aspect, and resources [29]. Drawing on relevant studies, 24 environmental factors were identified within these five categories [4,30,31,32,33,34,35,36,37,38,39,40]. Additionally, based on field research and expert consultation, two new indicators were added: space theme and community interaction. After screening and integration, a total of 26 environmental indicators were identified (

Table 2. Environmental evaluation indicators for informal learning in dormitories.

N	Factor Categories	Environmental Factors
1	Spatial design	D1 Lighting quality
		D2 Interior decoration
		D3 Use of color
		D4 Spatial scale
		D5 Acoustic environment
		D6 Spatial flexibility
		D7 Furniture configuration
		D8 Spatial complexity
		D9 Space theme
2	Natural environment	N1 Natural Lighting
		N2 Thermal comfort
		N3 Access to greenery
		N4 Air quality
3	Physical settings	P1 Advance reservation
		P2 Opening hours
		P3 Facility management
		P4 Proximity and accessibility
		P5 Private usability
		P6 Safety and security
4	Social aspect	S1 External interaction
		S2 Community interaction
5	Resources	R1 Food and beverage access
		R2 Power sockets
		R3 Wireless network
		R4 Availability of reading materials
		R5 Availability of shared learning equipment

).

Therefore, this study developed a questionnaire to assess students’ satisfaction with their informal learning experiences in dormitory environments. It includes three parts: (1) personal background (gender, grade, and major type); (2) types of informal learning behaviors; (3) satisfaction with the dormitory spatial environment. Satisfaction was measured using a 5-point Likert scale: 1 = strongly dissatisfied; 2 = dissatisfied; 3 = neutral; 4 = satisfied; 5 = strongly satisfied. The items were developed based on the five categories and 26 environmental factors (see Appendix A: “Questionnaire Survey”).

2.3. Data Collection

Data collection was conducted over 18 days in total (in April 2025), with 6 days allocated to each participating university for field observation and questionnaire distribution. Data were collected daily from 9:00 a.m. to 9:00 p.m. Investigators patrolled the public areas of the dormitories every hour to identify student activities and invite those engaged in informal learning to complete questionnaires, thereby ensuring data authenticity and accuracy. With students’ consent, investigators also asked brief follow-up questions regarding their preferences to obtain more comprehensive insights. Participants received a small token of appreciation for completing the questionnaire. A total of 8 graduate students were recruited to assist in data collection. In total, 1502 questionnaires were distributed, and after excluding those with incomplete responses or excessive repeated answers, 1489 valid samples were retained. According to local regulations, this investigation did not require ethical approval.

2.4. Data Analysis

The evaluation was conducted using SPSS Statistics 24.0 based on 27 questionnaire items. The analysis demonstrated excellent internal consistency (Cronbach’s α = 0.940 > 0.90) and superior sampling adequacy (KMO = 0.948 > 0.85). Bartlett’s test of sphericity confirmed strong inter-variable correlations (χ² = 5823.7, p < 0.001). Principal component analysis with varimax rotation extracted factors meeting Kaiser’s criterion (eigenvalue > 1), with a cumulative explained variance of 73.2%, indicating robust construct validity.

The methodological sequence began with descriptive statistics to profile respondents’ demographic characteristics. Subsequently, bivariate correlation analysis and multivariate linear regression were used to examine inter-variable relationships. Finally, a composite weighting method was used to determine the weights of the 26 indicators. This method integrates multiple influencing factors to enhance the accuracy and objectivity of the weight calculation [41,42]. Specifically, a multi-level indicator weighting approach was adopted, combining the entropy weight method and standardized regression analysis. It assigns weights from two complementary perspectives: the internal information disparity of individual indicators and the explanatory power of each major category with respect to overall satisfaction. All indicator weights were calculated using Formula (1), which produces the final results in a proportionally normalized form.

W′_j = (ω_ij × β_i)/[∑_j₌₁ⁿ (ω_ij × β_i)] × 100%

(1)

W′_j: Normalized composite weight (percentage) of indicator j.

ω_ij: Normalized entropy weight of indicator j within category i.

β_i: Standardized regression coefficient of category i, obtained through regression analysis.

∑_j₌₁ⁿ (ω_ij × β_i): Sum of the intermediate weights across all indicators.

3. Results

3.1. Respondent Characteristics

Table 3. Demographic and behavioral characteristics of respondents.

Title	Frequency	Percentage (%)
Gender:
Male	733	49.2
Female	756	50.8
Grade:
Y1	345	23.2
Y2	377	25.3
Y3	453	30.4
Y4	314	21.1
Major:
Science and Engineering Disciplines	847	56.9
Humanities and Social Sciences	559	37.5
Arts and Design Disciplines	83	5.6
Informal learning type:
Individual Self-Directed Learning	677	45.5
Collaborative Group Learning	812	54.5
Total number of respondents	1489

presents the demographic profile of respondents. The gender distribution showed a balanced representation with males (n = 733, 49.2%) and females (n = 756, 50.8%), yielding a gender ratio of 0.97:1. Academic standing analysis revealed junior students constituting the largest cohort (30.4%), followed by sophomores (28.1%), freshmen (25.7%), and seniors (15.8%). Disciplinary distribution indicated predominance of science and engineering disciplines (56.9% of total respondents). Regarding learning behavioral patterns, collaborative learning emerged as the predominant mode (54.5% participation rate), surpassing individual learning engagement (45.5%).

3.2. Correlation Analysis and Linear Regression Analysis Results

A preliminary Pearson correlation analysis was conducted using SPSS to examine the bivariate relationships between students’ satisfaction with informal learning experience and the five-factor categories. As shown in

Table 4. Pearson correlation between satisfaction and dormitory environmental factor categories.

	Overall Satisfaction	Spatial Designs	Natural Environments	Spatial Designs	Social Aspects	Resources
Overall satisfaction	1
Spatial designs	0.483 **	1
Natural environments	0.572 **	0.477 **	1
Physical Settings	0.577 **	0.521 **	0.556 **	1
Social aspects	0.291 **	0.269 **	0.284 **	0.353 **	1
Resources	0.603 **	0.432 **	0.507 **	0.551 **	0.261 **	1

** Significant correlation at the 0.01 level (two-tailed).

, each factor category exhibited a statistically significant positive correlation with satisfaction (r = 0.291 to 0.603, p < 0.05).

A multivariate linear regression analysis was conducted using SPSS to quantify the influence of environmental factors on students’ satisfaction with informal learning experiences. The model showed substantial explanatory power (R² = 0.507), accounting for 50.7% of the variance in satisfaction levels. Model significance was confirmed by an F-test (F = 305.036, p < 0.001), indicating strong statistical validity. As detailed in

Table 5. Regression results of the factor categories.

Model	Unstandardized Coefficients		Standardization Coefficient	t	Significance	Collinearity Statistics
	B	Standard Error	Beta 1			Tolerance	VIF
(Constant)	−0.079	0.108		−0.733	0.463
Spatial design	0.140	0.025	0.124	5.508	0.000	0.661	1.513
Natural environment	0.290	0.029	0.235	9.967	0.000	0.600	1.668
Physical settings	0.218	0.028	0.197	7.832	0.000	0.527	1.897
Social aspect	0.047	0.023	0.041	2.061	0.040	0.857	1.167
Resources	0.306	0.023	0.311	13.493	0.000	0.625	1.601

¹ Beta: a “unit-free” measure of effect size, one that can be used to compare the magnitude of effects of predictors measured in different units.

, all five-factor categories had significant predictive effects: spatial designs (beta = 0.124, p < 0.05), natural environments (beta = 0.235, p < 0.05), physical settings (beta = 0.197, p < 0.05), social aspects (beta = 0.041, p < 0.05), and resources (beta = 0.311, p < 0.05). Among them, the standardized beta coefficients indicated that resources were the most influential predictor, followed by natural environments and physical settings, in order to decrease the effect size.

To investigate the differential environmental impacts on distinct learning types, this study employed multivariate linear regression to examine associations between two learning behaviors (individual and collaborative learning) and the five-factor categories. As shown in

Table 6. Standardized regression coefficients for informal learning behaviors and environmental factor categories.

Independent	Variable						R2
	Overall Satisfaction	Spatial Designs	Natural Environments	Spatial Designs	Social Aspects	Resources
Individual Learning	0.163	0.190	0.171	0.063	0.298	0.468	0.163
Collaborative Learning	0.104	0.264	0.246	0.043	0.318	0.589	0.104

, both learning types exhibited comparable regression patterns across the five-factor categories. Specifically, resources emerged as the predominant predictor for both individual learning (beta = 0.298) and collaborative learning (beta = 0.318), while social aspects demonstrated minimal predictive power across both modalities (individual: beta = 0.063; collaborative: beta = 0.043). The regression models revealed that collaborative learning exhibited greater environmental sensitivity (R² = 0.589) than individual learning (R² = 0.468). In comparison, spatial designs and physical settings exhibited greater effect sizes in the individual learning model, whereas natural environments showed stronger influence in the collaborative learning model.

3.3. Weight Calculation Results

Table 7. Composite weights of the 26 environmental factors.

Sort	Environmental Factors	Weights
1	R2 Power sockets	8.41%
2	R3 Wireless network	6.70%
3	R1 Food and beverage access	6.28%
4	R5 Availability of shared learning equipment	5.69%
5	R4 Availability of reading materials	5.11%
6	D5 Acoustic environment	4.63%
7	D7 Furniture configuration	4.61%
8	P2 Opening hours	4.28%
9	D6 Spatial flexibility	4.15%
10	P3 Facility management	3.90%
11	D4 Spatial scale	3.78%
12	N2 Thermal comfort	3.75%
13	P1 Advance reservation	3.69%
14	D2 Interior decoration	3.67%
15	N1 Natural Lighting	3.61%
16	D8 Spatial complexity	3.36%
17	P4 Proximity and accessibility	3.34%
18	N3 Access to greenery	3.28%
19	D1 Lighting quality	3.19%
20	P5 Private usability	2.84%
21	N4 Air quality	2.69%
22	P6 Safety and security	2.66%
23	D9 Space theme	2.64%
24	D3 Use of color	2.64%
25	S2 community interaction	0.58%
26	S1 External interaction	0.53%
Total	--	100%

delineates the weight distribution of 26 environmental indicators across the five-factor categories. The results demonstrate that indicators under the resources category received the highest weights, including power sockets (8.41%), wireless network (6.70%), food and beverage access (6.28%), availability of shared learning equipment (5.69%), and availability of reading materials (5.11%). Notable indicators from the spatial designs category included acoustic environment (4.63%) and furniture configuration (4.61%), followed by opening hours (4.28%) from the physical settings category. In contrast, community interaction (0.58%) and external interaction (0.53%) had the lowest weights in the assessment framework.

4. Discussion

4.1. Discussion on the Relationship Between Environment and Behavior

4.1.1. Discussion on Spatial Designs

The results indicate that the spatial design is a key environmental factor affecting students’ informal learning experiences, especially for individual learning, which typically involves focused, self-directed cognitive processes requiring a quiet, comfortable, and personalized setting [43].

Among the nine indicators of spatial design, the acoustic environment held the highest weight. This aligns with findings from numerous university-based studies, which have demonstrated that noise levels significantly affect learning outcomes. Un-pleasant sensory stimuli, such as sudden or intrusive noise, tend to disrupt concentration and reduce learning motivation [44,45,46]. Furniture configuration also received a relatively high weight. Observations indicated that students preferred sofas or chairs with backrests, which improve physical comfort and support prolonged study sessions. Previous studies have similarly noted that providing comfortable and personalized furniture can offer emotional value, reduce stress, and improve students’ productivity and cognitive performance [47,48]. Additionally, spatial flexibility was highly rated. Consistent with earlier research, students favored environments where layouts or furniture could be adjusted according to personal needs. Such adaptable spaces enhance one’s sense of control over the environment, encouraging both cognitive engagement and emotional responsiveness, thereby supporting attention and creativity [49].

Based on these findings, it is recommended that future dormitory design strategies pay greater attention to providing diverse, movable furniture and multifunctional partitions (e.g., bookshelves and green walls) within public learning spaces. This would allow students to rearrange their learning areas, control levels of noise and privacy, and select furniture types that best support their preferred learning style—ultimately enabling them to create a personalized and effective informal learning environment.

4.1.2. Discussion on Natural Environments

The results show that the natural environments significantly influence students’ informal learning, with a stronger effect on collaborative learning. Collaborative learning involves communication, coordination, and negotiation, all of which benefit from a comfortable natural environment and access to greenery that helps reduce social tension and promote positive social behavior [50].

Among the evaluated indicators, thermal comfort held the highest weight, followed by natural lighting and access to greenery. These factors influence not only physiological well-being but also sustained cognitive functioning. For example, appropriate indoor temperatures help reduce stress responses and support prolonged focus [51], while natural daylight enhances alertness, emotional stability, and circadian balance [52]. Although greenery emerged as a significant factor, many current dormitory settings still lack meaningful biophilic features—limiting their potential to foster psychological restoration and mental ease. Studies have demonstrated that biophilic environments—rich in natural elements and patterns—can improve attention, reduce stress, and create a sense of safety and coherence within the space [53,54,55,56]. Introducing such features could further enhance the dormitory’s capacity to support restorative and engaging learning experiences.

To achieve this, future design strategies should combine passive and active approaches—such as insulation optimization, operable windows, dynamic shading systems, and biophilic interventions like indoor vegetation and natural textures—to foster comfort, cognitive clarity, and a balanced sensory atmosphere.

4.1.3. Discussion on Physical Settings

The findings confirm that physical settings significantly influence students’ informal learning experiences, with a notably stronger effect on individual learning. This may be attributed to the nature of individual learning, which often involves prolonged periods of sustained attention, self-regulation, and low-stimulus environments [57]. In contrast, collaborative learning tends to be more episodic, task-oriented, and socially dynamic, allowing students to adapt more flexibly to fluctuations in the physical environment [58].

Among the physical settings indicators, opening hours, facility management, and advance reservation received the highest weights—consistent with prior research [59]. When learners are able to anticipate access and control their study schedules, it reduces the cognitive load associated with uncertainty and increases intrinsic motivation. Cleanliness and effective maintenance of shared facilities further shape a sense of environmental trust and safety, which are essential psychological conditions for sustained engagement. Students who feel confident about the functionality and order of their surroundings are more likely to use the space consistently and deeply engage in their learning tasks.

Based on these insights, dormitory design should extend access hours—ideally to 24/7—and implement reservation systems for high-demand spaces to reduce conflicts. Maintaining a clean and orderly environment through regular cleaning and timely facility upkeep is essential. Efficient repair and feedback mechanisms can further enhance usability and satisfaction, contributing to a more supportive and reliable informal learning environment.

4.1.4. Discussion on Social Aspects

The analysis indicates that social aspects exert a relatively limited influence on students’ informal learning experiences within dormitories. Observations and interviews suggest that many students choose dormitory-based learning precisely because these spaces offer familiarity, privacy, and minimal distractions. As a result, community interaction is often not a primary consideration, with students focusing more on the spatial and environmental qualities of the space. Additionally, the indicator opportunities for external interaction, which reflects the openness and permeability of dormitory spaces to surrounding environments, was generally perceived as insignificant. Students reported that when seeking to expand their social networks, they prefer more public or neutral venues—such as libraries or student centers—over semi-private dormitory settings.

These findings suggest that while students are generally satisfied with the social atmosphere in their dormitories, social aspects are not a major determinant of informal learning engagement. This may reflect a spatial–functional separation between learning and socializing in student behavior: learners tend to associate dormitories with personal or academic activities, and seek social interaction elsewhere.

4.1.5. Discussion on Resources

The study results show that resources are the most influential environmental category affecting students’ informal learning experiences, with power sockets and wireless network identified as the most important indicators. In modern learning contexts, laptops, tablets, and smartphones are essential tools for both formal and informal learning [60,61]. Sustained informal learning often relies on the availability of power and stable internet access. Many students reported that accessible power outlets and reliable connectivity were primary factors in selecting a learning space. Access to food and drinks was also a significant factor. Observations revealed that many students preferred eating in the dormitory common areas rather than the cafeteria. Prior studies have shown that food and beverage availability increase dwell time and support social engagement [39,62]. In addition, such provisions are crucial for maintaining energy levels and reducing cognitive fatigue during extended learning sessions. Furthermore, the presence of shared learning equipment (e.g., printers and projectors) and reading materials (e.g., books and newspapers) also contributes to a more effective informal learning environment by supporting a variety of learning activities and improving efficiency.

Based on these findings, dormitory spaces should be equipped with abundant power outlets and robust network infrastructure. Designers should consider permitting or providing food and beverage services in designated areas, offering amenities such as microwaves, and increasing the availability of learning-related resources to better support diverse informal learning needs.

4.2. Discussion on the Differences Between Dormitories and Campus Places

As demonstrated in the previous analysis, environmental factors in dormitory public areas significantly influence students’ informal learning experiences. To better understand these factors and assess their relative importance, it is useful to compare dormitories with other typical informal learning spaces on campus. While prior studies have mainly focused on learning centers, libraries, and coffee shops, this section combines previous findings with results from the current study to identify key similarities and differences in how these spaces support informal learning.

Table 8. Environmental factors affecting informal learning experiences in different campus places.

	D1	D5	D6	D7	D8	N1	N2	N3	N4	P2	P4	S1	R1	R2	R3	R4	R5	Sources
T1	✔		✔		✔	✔	✔	✔			✔	✔		✔	✔	✔	✔	[63]
T2		✔	✔	✔			✔	✔				✔	✔	✔			✔	[64,65]
T3	✔	✔		✔			✔		✔	✔				✔	✔		✔	[26]
T4		✔	✔	✔						✔			✔	✔	✔	✔	✔	-

T1: learning center; T2: library; T3: coffee shop; T4: dormitory.

summarizes the primary environmental factors shaping informal learning across four campus space types. Some elements—such as access to power sockets, wireless network, and shared learning equipment—consistently enhance learning convenience and efficiency. Similarly, aspects of spatial design, including acoustic environment, furniture configuration, and spatial flexibility, are widely recognized as essential for fostering supportive informal learning environments.

However, noticeable differences also exist. Students in learning centers, libraries, and coffee shops generally place high value on natural environmental qualities—such as thermal comfort, air quality, and natural lighting—which are known to enhance focus, comfort, and cognitive engagement. In contrast, spatial openness is particularly emphasized in learning centers and libraries, where open layouts help facilitate visibility, circulation, and interaction, thereby enhancing motivation.

In contrast, coffee shops and dormitories, which serve both living and social functions, tend to offer greater familiarity and belonging. Students in these spaces prioritize autonomy over openness and focus on the ability to use the space freely and comfortably. Consequently, opening hours become a critical factor, reflecting the need for flexible, self-paced learning in familiar environments.

These findings suggest that although university dormitories share several environmental priorities with other informal learning spaces, they emphasize controllability to a greater degree. This includes ready access to essential resources, adaptable spatial configurations, low-noise conditions, and unrestricted use over time. These findings can be further interpreted through the lens of environmental psychology. Existing studies have shown that environmental controllability enhances individuals’ perceived agency and psychological safety, thereby fostering positive emotional states, stronger self-efficacy, and improved cognitive performance [66,67]. Compared with other informal learning spaces on campus, dormitories exhibit a hybrid nature—being both private and communal—and are used with high frequency. This dual functionality and prolonged occupancy heighten students’ sensitivity to both the supportive and restrictive features of their environment. When dormitory spaces enable behavioral self-regulation and spatial autonomy, they not only enhance students’ learning engagement but also reinforce place attachment and mental well-being. Therefore, future dormitory design should move beyond standardized, institutionalized models and instead create environments that are both controllable and emotion-ally resonant—such as ensuring an ample supply of power sockets and high-speed wireless networks, introducing reconfigurable furniture and movable partitions to accommodate diverse learning needs, applying acoustic zoning and intelligent noise reduction systems to maintain quietness, and offering extended or 24 h access to shared learning spaces to support flexible and self-paced use.

5. Conclusions

5.1. Main Conclusions

This study investigates the relationship between environmental factors in university dormitories and students’ informal learning experiences. Based on a questionnaire survey conducted across three universities and analyzed through rigorous quantitative methods, the following key findings are identified:

Firstly, all five categories of environmental factors—spatial designs, natural environments, physical settings, social aspects, and resources—exert statistically significant impacts on students’ informal learning satisfaction, though with differing levels of influence.

Secondly, among all indicators, resource-related factors—including power sockets, wireless network, and shared learning equipment—are found to be the most influential. Other high-weight indicators include acoustic environment, furniture configuration, opening hours, and spatial flexibility.

Thirdly, while individual and collaborative learning behaviors exhibit slight differences in environmental preferences, the overall influence patterns are largely consistent, suggesting that a well-designed dormitory environment can accommodate diverse informal learning needs.

Lastly, compared with other informal learning spaces on campus such as learning centers, libraries, and coffee shops, dormitories place greater emphasis on environmental controllability—such as privacy, accessibility, and flexibility—making them particularly suitable for personalized, sustained, and self-directed learning.

5.2. Implications for Dormitory Design and Planning

Based on our analysis of the results, we find that these effects are primarily driven by how spatial features support users’ psychological needs, such as autonomy, comfort, and cognitive stimulation. Environments that allow personal control, offer emotional and physical comfort, and provide appropriate levels of sensory engagement are more likely to enhance students’ satisfaction with informal learning. Accordingly, this study identifies three key directions for optimizing dormitory environments:

1.

Controllability-Oriented Design

Dormitory spaces should offer students meaningful control over their environment. This includes spatial personalization, sensory regulation, and temporal flexibility. Rather than simply extending opening hours or adding adjustable furniture, design strategies could incorporate dynamic partitioning systems, light-modulation panels, or user-controlled microclimate zones. These affordances empower students to align space with cognitive tasks and emotional readiness, encouraging deeper learning engagement.

2.

Comfort-Centered Design

Comfort in dormitory settings is not only physical but also psychological. Environments that offer emotional warmth, perceptual clarity, and low sensory stress are more conducive to focused learning. Designers might consider the use of psychologically appealing materials (e.g., textured surfaces and biophilic accents), spatial proportions that reduce crowding, and multisensory cues that enhance familiarity and security—thus reducing cognitive load and promoting task immersion. Additionally, introducing fractal patterns, organic forms, and naturalistic color palettes can enrich visual coherence and stimulate parasympathetic response, reinforcing the restorative and mood-regulating qualities of the space.

3.

Stimulation-Rich Design

Beyond minimal functionality, spaces should stimulate curiosity and support diverse learning rhythms. Dormitory public spaces may incorporate layered visual perspectives, ambient learning displays, modular walls that double as writable surfaces, or shared zones designed for active experimentation. These elements encourage exploration, interdisciplinary dialogue, and social learning outside the classroom.

By shifting design thinking from a component-based improvement model toward an experience-centered framework, future dormitories can evolve into emotionally resonant, cognitively supportive ecosystems that cultivate informal learning as an everyday practice.

6. Limitations and Further Research

This study advances understanding of how dormitory environments influence students’ informal learning experiences. However, due to its broad scope, it was difficult to collect detailed data on the intensity and frequency of specific learning behaviors, limiting fine-grained analysis. Future research can build upon this foundation in the following three directions:

Firstly, narrowing the research focus to a single space type—such as semi-open communal floors or study lounges—would allow for more precise measurement of environmental impacts. Combining this with automated data collection tools, including video tracking or heat maps, could generate quantifiable evidence on behavior patterns. Additionally, future studies may incorporate physiological or neurological indicators to better capture students’ emotional and cognitive responses.

Secondly, while this study centered on student perspectives, future work should also consider other key stakeholders in dormitory environments, such as faculty and administrative staff. Their experiences, expectations, and interactions with dormitory spaces could be explored through interviews, focus groups, or structured surveys to develop a more inclusive understanding.

Thirdly, comparative studies across institutions in different climatic, cultural, or socioeconomic contexts would help test the generalizability of the findings and identify location-specific strategies for enhancing dormitory learning environments.

Continued research along these lines can deepen the theoretical and practical understanding of dormitory design, supporting the creation of more adaptable, inclusive, and pedagogically supportive living–learning spaces in higher education.