The role of informal learning spaces in promoting social integration and wellbeing in higher education

The global mental health crisis, intensified by the post-pandemic context, calls for holistic approaches to wellbeing in higher education. While prior research highlights the relevance of physical learning environments for health, limited attention has been paid to how these spaces foster social and psychological outcomes. This study examines how informal learning spaces (ILS) contribute to student wellbeing through the mediating role of social integration, with a focus on students facing personal challenges (FPC). Drawing on Tinto’s social integration model and the person–environment fit theory, this study explores two key questions: (1) Does social integration mediate the relationship between ILS availability/accessibility and student wellbeing? (2) Does FPC moderate the relationship between ILS and social integration? A cross-sectional survey was conducted with 932 university students from Austria, Germany, Italy, and Türkiye. Results showed that social integration mediates the relationship between ILS and wellbeing (β = 0.09). Moderation analysis indicated that the relationship between ILS and social integration was stronger for students FPC (β = 0.12), who reported significantly lower social integration when ILS were less accessible. Our findings present novel empirical evidence linking the physical learning environment to social integration and wellbeing, particularly for students facing personal challenges. These findings call for ILS to be intentionally designed as inclusive, welcoming, and supportive spaces that promote equity and wellbeing in higher education.

1 Introduction

In recent years, student wellbeing in higher education has become a focus of concern due to the increasing prevalence of mental health problems among university students (Brown, 2018; Khatri et al., 2024; Ribeiro et al., 2024). Students face a range of stressors, including academic, social, financial, cultural and environmental challenges, which can be overwhelming and detrimental to their wellbeing making them a ‘high risk population’ for psychological distress and mental disorders (Baik et al., 2019; Brett et al., 2023; Brown, 2018; Liu et al., 2022). The EUROSTUDENT 8 Survey conducted in 22 countries includes a special section focusing on mental health and wellbeing. Results indicate that student wellbeing is widespread concern: between 37 and 58% of students report poor wellbeing, with this being the majority experience in eight of the 22 nations examined. Younger students and those facing financial hardship report significantly lower wellbeing compared to their older and financially stable peers. Among students reporting mental health issues, depression and anxiety are the most common diagnoses. In Austria 44% of the students report low sense of wellbeing (Cuppen et al., 2024). In a representative German survey, 15.9% of students reported experiencing impairments that hinder their studies, with mental illnesses accounting for the majority (65%) of these cases. In other words, around one in 10 students suffers from a mental illness that negatively impacts his or her academic success (Kroher et al., 2021). A cross-national study by Ochnik et al. (2021) found high prevalence rates of mental health problems among university students in the Czech Republic, Türkiye, Israel, Slovenia, Germany, Poland, Ukraine, Russia, and Colombia during the COVID-19 pandemic. Turkish students reported the second highest levels of stress (70%), and the highest levels of anxiety (51.3%) and depression (62.3%) of all countries surveyed.

In addressing these mental health challenges, universities recently are focusing on structural interventions for health-promoting learning environments, but interventions on physical environments are underexplored compared to pedagogical interventions (Konstantinidis, 2024; Olsson et al., 2024). Recent research has increasingly recognized that the physical learning environment, particularly informal learning spaces (ILS), can serve as a protective factor supporting student wellbeing (Agg and Khimji, 2021; Makaremi et al., 2024; Neves and Hillman, 2017; Pepper, 2024; Scannell et al., 2016; Stanton et al., 2016). Informal learning spaces refer to areas where students use without direct teacher oversight, usually beyond the structure of formal class time. These spaces include hallways, university libraries, communal lounges, cafés, outdoor settings, and digital space (Cerasoli et al., 2018; Ninnemann and Jahnke, 2018). According to Berman (2020) ILS not only support academic engagement but also foster social interaction and overall wellbeing. In response, universities have begun reimagining campus spaces to balance social and academic needs and meet the growing demands for personalized learning (Berman, 2020). A holistic approach to campus design—integrating physical, social, and pedagogical dimensions—has been emphasized by Beckers et al. (2016) and Papaioannou et al. (2023), reinforcing the need to consider both the physical and social environments in higher education as well as the role of built-in environments of student wellbeing.

There exists some research that has examined various dimensions of physical learning space and their impact on learner wellbeing. Some studies examined the role of natural elements and biophilic design in stress reduction, to promote restorative experiences and to improve wellbeing (Agg and Khimji, 2021; Liu et al., 2022; Peters and D’Penna, 2020; Ribeiro et al., 2024). Research on acoustic thermal comfort, furniture, availability of food and drink facilities and lighting has shown that these physical elements impact students stress level and wellbeing (Amasuomo and Amasuomo, 2016; Muhammad et al., 2014; Ricciardi and Buratti, 2018; Scannell et al., 2016).

Despite these insights, the specific role of ILS in supporting student wellbeing remains insufficiently explored, particularly in relation to availability, accessibility, and characteristics contribute to students’ overall wellbeing and campus experience. While availability, accessibility and flexibility of ILS have primarily been investigated in relation to learning experiences and student engagement (Beckers et al., 2016; Costa and Steffgen, 2020; Guney and Al, 2012; Wang and Han, 2021; Wu et al., 2021), connection to wellbeing outcomes remains underexplored. This study addresses this gap by investigating the role of ILS in supporting student wellbeing, with the aim of promoting the development of more inclusive and wellbeing-oriented learning environments.

1.1 Informal learning spaces

The influence of physical learning environments on various dimensions of learning, both in compulsory and post-compulsory education, is widely acknowledged across educational science, design, and architecture (Higgins et al., 2005; Melhuish et al., 2008; Sivunen et al., 2014). However, research specifically addressing spatial use in higher education remains limited and highly fragmented (Ellis and Goodyear, 2016). Wilson’s (2009) Places for Learning Spectrum presents campuses as interconnected networks of diverse learning environments, emphasizing that learning occurs across a mix of spaces, activities, and technologies. His student-centered model spans a continuum from informal, self-directed settings to formal, teacher-led ones. It highlights three key components from the learner’s perspective: physical spaces, learning communities (e. g., staff, peers), and learning modalities that support various outcomes. In this model, informal learning spaces (ILS) constitute the majority of spaces in higher education institutions. ILS are areas where students gather without teacher supervision, typically outside scheduled classes. These spaces often take the form of redesigned university libraries, student lounges, cafes, outdoor areas, and even virtual spaces. Research highlights that the effective design of these spaces should reflect learning principles and support the different modalities of learning (e. g. active learning, focused learning, and collaborative learning) by structuring ways students interact with resources, technology, staff, and peers (Clark et al., 2007; Dovey and Fisher, 2014; Skerlak et al., 2014).

The role of ILS can also be understood by applying the Person–Environment (P–E) Fit Theory (Gilbreath et al., 2011). P-E Fit Theory suggest that individuals experience greater wellbeing, satisfaction, and performance when there is a good fit between their personal characteristics, (needs, values, abilities) and the environment they are in (social context, physical space). ILS in this account can address students’ social and academic needs (Pepper, 2024) that encourage peer interaction, reduce isolation, and foster informal social support and learning.

ILS are also central to the concept of the “sticky campus,” which encourages students to spend more time on campus (Ellis and Goodyear, 2016). A “sticky campus” environment blends spaces for living, learning, and leisure (Berman et al., 2024). This concept integrates study, relaxation, eating, and socializing areas, prioritizing flexibility, and variety to support both academic and recreational needs (Acker and Miller, 2005; Berman et al., 2024; Groves, 2017). In this concept, ILS provide opportunities for students to connect, collaborate, and engage in self-directed learning beyond the formal curriculum (Chattaraj and Vijayaraghavan, 2021; Matthews et al., 2011). These spaces contribute significantly to the development of a sense of community and belonging, which are essential for students’ social and emotional wellbeing (LeGrow et al., 2023).

Thus, ILS play a crucial, yet often underestimated, role in fostering social integration and enhancing the overall health and wellbeing of students within higher education institutions, moving beyond the traditional focus on formal classroom settings (Halupka and Li, 2023; Konstantinidis, 2024). The growing importance of learning spaces and technologies has attracted attraction from researchers focused on the design and utilization of these spaces to optimize teaching, learning, and research outcomes (Papaioannou et al., 2023). To achieve this, understanding the design and effective use of ILS requires a holistic perspective that accounts for the interplay of physical, social, and psychological factors influencing student behavior and learning outcomes.

1.2 Availability and accessibility of ILS

In environmental psychology and architecture, rooms are predominantly assessed based on physical criteria, such as light, climate, acoustics, temperature, furniture, and size (Keser Aschenberger et al., 2022; Ninnemann, 2018). Overarching criteria relevant to the appropriation and use of learning spaces include availability and accessibility of the space as well as the quality of the facilities (Ninnemann, 2018). Although, no comprehensive model currently focuses solely on availability and accessibility of learning spaces, related conceptual frameworks exist. For example, Tomaševski’s (2001) 4-A Model outlines key educational criteria—availability, accessibility, acceptability, and adaptability—primarily focused on human rights obligations in education. While originally designed to address access to schools and teachers, these criteria can be meaningfully applied to learning spaces. Availability is defined as the opportunity to use ILS in terms of sufficient existence of spaces and knowledge about ILS. Accessibility covers the possibility for actual usage of ILS, which might be hindered by barriers, such as restricted access, physical barriers, or lacking information about ILS.

Spatial Justice Theory by Soja (2010) emphasizes that space is socially produced and inherently related to power and inequality. He identifies that ‘space is filled with politics and privileges, ideologies and cultural collisions, utopian ideals and dystopian oppression, oppressive power and the possibility for emancipation’ (p. 103). He shows how the organization of space (physical, social, political) produces and reproduces inequalities, and how the design and distribution of learning spaces can either reinforce or reduce exclusion and marginalization. Applied to ILS, the theory urges institutions to consider how spatial arrangements affect access, inclusion, and wellbeing of diverse student groups. Sen’s (1980, 1993, 1999) Capability Approach compliments this by shifting from resources to what individuals are actually able to do and be. Capability approach is a normative framework for evaluating individual wellbeing. It emphasizes what individuals are actually able to do and be (their capabilities) rather than merely the resources they possess or their subjective satisfaction (Walker and Unterhalter, 2007). Key concepts include capabilities (real opportunities to achieve valuable states of being and doing), functionings (the actual achievements, e. g., being literate, being healthy), and agency (the ability to pursue goals and values). Educational spaces, physical, social, and institutional, can either enhance or restrict students’ capabilities. For example, access to space can enhance students’ real freedoms to learn, participate, and thrive. Together, these perspectives position ILS not just as material settings, but as critical enablers (or barriers) of students’ wellbeing, agency, and educational outcomes—especially for those facing personal challenges (FPC).

Research showed that ILS can accommodate diverse types of learning activities. Beckers et al. (2016) identified four main learning configurations: autonomous learning, instructional learning, interactive/small group learning and network learning. These configurations yield to nine learning activities such as independent study, collaborative learning, attending classes, or social learning activities. Scott-Webber (2015) presents another model bringing together types of learning needs and activities and form of ILS, a two-by-two matrix with four quadrants—Private/Alone, Public/Alone, Private/Together, and Public/Together—each representing different learner behaviors and spatial needs. Private/alone spaces support individual focused work, public/alone spaces offer individual work alone in the presence of others, private/together spaces support group learning with analogue and digital co-creation capabilities and public/together offers open group learning with peers, faculty, or supporting public venues. Based on these frameworks, in this study we centered on focused (individual) learning activities and collaborative (group) learning activities. Focused learning activities are conducted individually and usually undisturbed. Examples are reading, writing and repetition or studying for exams alone. Collaborative learning activities are conducted in groups. These can be the following learning activities: group work, preparing a group presentation and repetition or studying for exams in groups (Beckers et al., 2016).

Empirical studies show that students’ preferences for ILSs are closely linked to their learning activities, with convenience, proximity, and comfort being critical factors (Chin et al., 2021; Cui and Ahn, 2024; Harrop and Turpin, 2013; Ramsden, 2011). Quiet, secluded spaces are preferred for focused study, while open, flexible environments support collaboration, highlighting the importance for adaptable designs that accommodate diverse learning strategies and allow students to manage their own space effectively (Beckers et al., 2016; Guney and Al, 2012; Scoulas and De Groote, 2019; Shouder et al., 2014; Wang and Han, 2021). Building on this framework we hypothesize that availability and accessibility of ILS are significant predictors of student wellbeing.

1.3 Wellbeing

Wellbeing is a multidimensional construct encompassing biological, psychological, and social aspects. Diverse disciplines and contexts offer unique perspectives and insights that enrich our understanding of mental health and wellbeing (Hernández-Torrano et al., 2020). In the literature, two dominant conceptualizations of wellbeing have emerged, rooted in hedonic and eudaimonic traditions: subjective wellbeing and psychological wellbeing. Subjective wellbeing, rooted in the hedonic tradition, was described by Diener (1984) as consisting of three elements: frequent experiences of positive emotions, rare occurrences of negative emotions, and cognitive assessments of overall life satisfaction. On the other hand, psychological wellbeing is grounded in the eudaimonic tradition and includes six aspects of wellbeing: self-acceptance, autonomy, life purpose, positive relationships, personal growth, and mastery of one’s environment (Ryan and Deci, 2001; Ryff, 1989). Furthermore, Keyes (1998) introduced the concept of social wellbeing, referring to individuals’ perceptions of the quality of their relationships with others. In addition to these definitions, the World Health Organization (WHO) offers a holistic definition of mental health and wellbeing as ‘a state of complete physical, mental and social wellbeing, and not merely the absence of disease or infirmity’ (World Health Organization (WHO), 2020, p. 1). In higher education, student wellbeing typically includes emotional wellbeing, which involves experiencing positive feelings and being satisfied with life; psychological wellbeing, which encompasses having a sense of purpose, personal growth, and self-fulfillment; and social wellbeing, which relates to the quality of relationships and a sense of belonging (Li, 2025). This study adopts the WHO’s salutogenetic definition, focusing on the mental, emotional, and social aspects of wellbeing, and emphasizing enjoyment, happiness, and life satisfaction.

Student wellbeing and mental health have gained increased attention due to rising reports of mental health concerns, particularly depression and burnout (Brown, 2018; Khatri et al., 2024; Ribeiro et al., 2024). Numerous studies have employed the WHO-5 Item index to assess the wellbeing of students. For instance, Kuehner et al. (2020) reported an index of 57 in 2018 and of 56 in 2020 for German students. In 2021, Holm-Hadulla et al. (2021) reported a WHO-5 Item index of 37 for German students. Therefore, it is necessary to understand which factors drive wellbeing of students.

The body of research is growing, investigating the factors influencing student wellbeing. Broad models identify a variety of factors, grouping them into demographics, pre-university experiences, supportive college climate, social and academic interactions, and confidence and sense of belonging (Fink, 2014). Recently, studies have turned to structural approaches which are carried out by universities to find answers for policy advisors and instructors how to improve student wellbeing. Olsson et al. (2024) focused on structural interventions for health-promoting learning environments in higher education. They identified four categories of institutional intervention: (1) inclusion and diversity approaches, (2) adaptations to the physical environment, (3) teaching health-related skills and behaviors and (4) adaptations to pedagogical practices and teaching approaches. Only two studies looked at the physical environment (category 2), whereas nearly two-thirds of the interventions identified belonged to pedagogical practices and teaching approaches (category 4). Similarly, in an integrative review Konstantinidis (2024) identified four overarching factors: the instructor, course design, class climate, and available resources. In this review majority of the interventions belonged to the instructor, the course design or class climate with only a few studies addressing resource-related factors. There is a notable gap in understanding how structural approaches in the learning environment affect student wellbeing (Cooper et al., 2009). Furthermore, students mostly were favorable to the interventions to which they were exposed (Olsson et al., 2024), but evidence on the effectiveness of the interventions remains mixed (Konstantinidis, 2024; Olsson et al., 2024). Mostly, interventions improving competence/confidence and sense of belonging as well as supportive college climate are successful (Brooker and Vu, 2020; Fink, 2014), but there are no studies looking at the interplay between the physical environment as a resource and their effects on wellbeing, sense of belonging, connectedness, and supportive college climate. This study addresses this gap by exploring how ILS can improve social integration and wellbeing. In the next section the Social Integration Model by Tinto (1975) will be explained.

1.4 Social integration

Social integration, encompassing students’ interactions with peers, faculty, and the broader university community, is a key determinant of student wellbeing and success in higher education. It fosters interpersonal connections, shared attitudes and values, and personal development of students (Berger and Milem, 1999). Tinto’s (1975, 1993) Social Integration Model is foundational in this field, positing that students with higher levels of social and academic engagement reduce the risk of student dropout (Tinto, 1975). Tinto’s (1993) model shifted attention from individual student characteristics to institutional factors, emphasizing the interactive relationship between students and their educational environments (Tinto, 1986, 1993).

While the model has evolved with later revisions (Tinto, 1993) and competing theories (Allen, 1999), academic and social integration remain central components. Empirical evidence consistently shows that the lack of academic and social integration leads to higher dropout rates of students (Bers and Smith, 1991; Klein, 2019; Tinto, 1975). Social integration not only mitigates dropout risks, but also enhances other positive outcomes such as student satisfaction and wellbeing. For example, Merola et al. (2019) demonstrated that students who feel socially integrated report greater overall satisfaction. Other research indicates that close social ties foster mental wellbeing. Zheng et al. (2004) revealed that international students reported higher subjective wellbeing when they felt socially integrated at their new university. Imaginário et al. (2013) likewise found out that all aspects of social integration in higher education, such as interpersonal relationships, emotional balance, and personal wellbeing, appear to have significant impact on students’ subjective wellbeing.

In addition to physical characteristics, spaces that facilitate social connection and collaboration are essential elements of students’ preferences for ILS (Berman, 2020; Webb et al., 2008). According to Neves and Hillman (2017), students expect effective learning spaces for social engagement and need more and better-quality ILS’s that are accessible to all students. Research has shown that learning in collaborative settings, social connectedness and integration are crucial for student wellbeing (Chaudhry et al., 2024; Crawford et al., 2024; Pepper, 2024). ILS function as facilitators of social integration by providing areas where students can interact informally and build relationships, which promotes student wellbeing. For instance, McFarland et al. (2008) discovered that students who frequently use campus green spaces were more likely to experience social interactions with their peers and reported a high quality of life. The results of a qualitative study by Stanton et al. (2016) noted that spaces which encourage social engagement can reduce feelings of isolation and improve student wellbeing. A study by Pepper (2024) showed that students highlighted the importance of ‘socially engaging environment’ as the most crucial factor influencing their wellbeing, pointing out the crucial role of social interaction in maintaining mental health. As the research shows, the availability, accessibility, and quality of ILS that foster a sense of social connectedness and integration play a crucial role in student wellbeing in higher education. To summarize, social integration is proven to reduce dropout rates of students. Furthermore, social integration leads to other positive outcomes, especially fostering health, and wellbeing.

1.5 Facing personal challenges

Research indicates that disadvantaged students continue to face substantial challenges in accessing and succeeding in higher education, despite overall increase in enrolment rates (OECD, 2023; Palmisano et al., 2022). The European commission adopts a broader conceptualization of participants with fewer opportunities, describing them as individuals who, due to economic, social, cultural, geographical or health reasons—as well as those with migrant backgrounds, disabilities or other educational difficulties—face obstacles that prevent their full access to and participation in education (European Commission (EC), 2025). Students from lower socioeconomic backgrounds face structural, financial, and technological barriers which limit their access to and engagement in university life. Additional groups that experience difficulties in higher education include individuals with disabilities, students balancing work and study commitments, those with caregiving responsibilities, and individuals from migrant or transient backgrounds. These groups frequently experience reduced social integration, limited engagement in extracurricular activities, and increased time devoted to academic pursuits (Fernández-Batanero et al., 2022; Sachs and Schreuer, 2011). Such barriers not only limit educational participation but also exacerbate feelings of isolation, creating a compounding effect on wellbeing and academic success. To address these disparities higher education institutions must implement inclusive policies and strategies that promote equitable access and success for all students.

In line with the European Commission’s broad definition, our study adopts an inclusive view of “students facing personal challenges” (FPC) identifying them as those facing at least one of the challenges. This framing allows us to better understand and address the multifaceted barriers these students encounter, particularly in relation to their access to ILS and the implications for their social integration and wellbeing.

1.6 Current study

Students’ wellbeing is recognized as a critical outcome in higher education, influenced by a range of academic, social, and environmental factors. While the relation between wellbeing and social integration is well-established, the role of ILS in student wellbeing is underdeveloped. Building on the literature reviewed and gaps in the literature, we have theorized a model to explore how physical learning environments, particularly informal learning spaces (ILS), contribute to student wellbeing through social integration processes.

We adopt Tinto’s (1975, 1993) Social Integration Model as a foundational framework. This model is well-established in higher education research and emphasizes that students who are more socially integrated into the academic community are less likely to dropout and more likely to succeed (Tinto, 1993). However, a key limitation of Tinto’s framework is that it does not specify the mechanisms or environmental factors that can actively enhance social integration. In this context, we theorize that the availability and accessibility of ILS function as environmental factors facilitating social interaction and thus increasing social integration. This aligns with broader research indicating that supportive environments contribute to positive students’ outcomes, including wellbeing and commitment (Beckers et al., 2016; Costa and Steffgen, 2020; Wang and Han, 2021).

By combining these theoretical streams, we hypothesize a mediated relationship, where social integration mediates the link between availability and accessibility of ILS and student wellbeing. This conceptual model is illustrated in Figure 1.

Figure 1

Figure 1. Conceptual model of mediation hypothesis.

In addition, we extend the model by considering students facing personal challenges (FPC). This status was identified as facing challenges due to socio-economic, health related, or cultural barriers (European Commission (EC), 2025). We hypothesize that for students FPC, ILS can play an even more critical role in fostering social integration, as these spaces can provide essential opportunities for interaction and inclusion that might otherwise be limited. Therefore, we propose a moderation hypothesis, predicting that the relationship between availability and accessibility of ILS and social integration is influenced by students FPC status. This hypothesis is depicted in Figure 2.

Figure 2

Figure 2. Conceptual model of moderation hypothesis.

Based on these models, following research questions and hypotheses guide the study:

1.6.1 Research question 1: mediation

Does social integration mediate the relationship between the availability and accessibility of ILS and students’ wellbeing?

Hypothesis:

H1a (Direct Effect): The availability and accessibility of ILS are positively associated with students’ social integration.

H1b (Direct Effect): Social integration is positively associated with students’ wellbeing.

H1c (Indirect Effect): Social integration mediates the relationship between the availability and accessibility of ILS and students’ wellbeing.

1.6.2 Research question 2: moderation

Does the relationship between the availability and accessibility of ILS and social integration differ according to FPC status?

H2a (Main Effect): The availability and accessibility of ILS are positively associated with students’ social integration.

H2b (Moderation Effect): The positive relationship between the availability and accessibility of ILS and social integration is stronger for students FPC compared to students without such personal challenges.

2 Method

This study employed a quantitative, cross-sectional survey design to investigate the relationships between the availability and accessibility of informal learning spaces (ILS), social integration, facing personal challenges (FPC) and students’ wellbeing. The study aimed to test both mediation and moderation effects and was conducted within the framework of a European project with four partners from Austria, Germany, Italy, and Türkiye. A cross-sectional survey was selected as data collection method, as it is appropriate for understanding and assessing associations among variables at a single point in time and for testing hypothesized pathways (Creswell and Creswell, 2017).

2.1 Data collection and procedure

Data was collected through an online survey administered between May and July 2022. The survey was originally developed in English and translated in the language of the participating countries. Translation was done by the project team and then checked by the experts in the area for the accuracy. Data from four universities was included in the analyses. Participants were recruited through a combination of digital (e. g. circular e-mails, university newsletters, QR codes) and printed (e. g. poster, flyers, handouts) outreach strategies. In some cases, instructors involved in the project, distributed the survey during classes and encouraged students to share the link with peers.

Ethical approval for this study was obtained from Akdeniz University (Approval No: 174, date: 20.04.2022). The survey questions did not include any personally identifiable information. Prior to participation to survey, participants were presented a consent form on the first page of the survey which outlined the voluntary nature of their participation, and the right to withdraw any time without consequences, and the confidentiality of their responses. Given the sensitive nature of questions particular care was taken to ensure anonymity. No IP addresses were collected through the online forms. The data was stored on the researchers’ password-protected computers.

2.2 Sample

According to Fritz and MacKinnon (2007) a minimum sample size of n = 558 is required to detect mediation effects when assuming small-to-moderate effects. For moderation effects, which generally require larger sample sized due to range restrictions, Judd et al. (2014) emphasize the importance of including reliable variables to increase statistical power. Our sample meets these requirements.

A total of N = 932 students from four partner universities took part in the online survey: University for Continuing Education Krems in Austria (UWK), HTW Berlin University of Applied Sciences in Germany (HTW), Sapienza University of Rome in Italy (SAP), and Akdeniz University in Türkiye (AKD). Bigger universities (AKD and HTW) contributed a slightly larger sample size than the other universities (SAP and UWK). Sample characteristics are depicted in Table 1.

Table 1

Table 1. Descriptive sample characteristics (N = 932).

The majority of respondents identified as female (56.3%), followed by male (40.2%), with a small proportion identifying as diverse (0.4%) or choosing not to disclose their gender (3%). Most participants were between 21 and 25 years old (52.8%), with 18.6% under 20 and 28.6% older than 25. Regarding degree, 58% were enrolled in bachelor’s programs, 32.6% in master’s programs, 6.9% in associate’s degree programs, and 1.5% were pursuing doctoral studies.

2.3 Measures

To examine the hypothesized relationship in our model, we used self-developed instruments to assess the availability and accessibility of ILS, and validated instruments to assess social integration and student wellbeing. We also included a variable to capture FPC status All subscales and items are listed in Supplementary Material.

2.3.1 Availability and accessibility of ILS

The term availability refers to the extent to which informal learning spaces (ILS) are present, diverse, and known to students as usable options. This includes the quantity and variety of available spaces—such as quiet zones, collaborative areas, and social settings—along with adequate furnishings like seating and workstations. Availability also depends on transparent communication tools, such as signage, booking systems, and real-time occupancy updates. High availability empowers students to choose environments that best align with their specific learning needs (Ellis and Goodyear, 2016; Morieson et al., 2018; Wu et al., 2021).

Accessibility refers to how easily students can physically and psychologically reach and use ILS without facing barriers. It encompasses physical aspects like ramps and adaptable furniture, as well as organizational features such as opening hours, access regulations, and the provision of specialized equipment or technologies. These features aim to ensure that students can find comfortable, functional spaces to study or collaborate (Devlin et al., 2012; Halupka and Li, 2023; Vidalakis et al., 2013). Equally critical is the perceived inclusivity of these spaces—whether they are experienced as safe, welcoming, and socially supportive by a diverse student population (Kassab et al., 2024; Morieson et al., 2018; THRIVE Project, 2025).

Since no standard instrument exists measuring ILS availability and accessibility, self-developed items were used. Separate scales were developed for focused (individual) and collaborative learning activities for Availability and Accessibility of ILS. Sample items are:

• Availability (Focused): “If I want to study on my own, I know where I can go in my university.”

• Availability (Collaborative): “If I want to study together with my fellow students, I know where I can go in my university.”

• Accessibility (Focused): “Places for focused learning activities are open to all students at my university.”

• Accessibility (Collaborative): “Places for studying in groups are open to all students at my university.”

Items were rated on a 5-point Likert scale (ranging from 1 = totally disagree, 2 = disagree, 3 = neither agree nor disagree, 4 = agree, 5 = totally agree). Full item list is presented in Supplementary Material.

Reliability analyses indicated that all four scales demonstrated good internal consistency, with all Cronbach’s Alpha coefficients ≥0.81. Descriptive statistics showed that students perceive similar levels of availability and accessibility for focused vs. collaborative learning activities with scale means ranging from M_CLAvail = 3.33 an M_FLAccess = 3.46. The assumption of normality was supported by visual inspection and sample size. High Pearson correlation coefficients were observed among the four scales (ranging from r = 0.59 to r = 0.80), indicating that students did not as strongly differentiate between types of ILS for different learning activities as we assumed. Further analyses on the impact of ILS for focused and collaborative learning activities show only small effects (see Geister et al., 2024). These suggest that students may visit the campus for a blend of focused and collaborative learning activities rather than a specific type of activity, which is in line with the concept of “sticky campus” (Berman et al., 2024) and flexible design and use of ILS supporting diverse learning needs (Guney and Al, 2012; Wang and Han, 2021).

Since we conceptualize availability and accessibility as overarching variable and to prevent multicollinearity, we merged all four scales. The resulting scale “Availability and Accessibility of ILS” consisted of 14 items with high reliability (α = 0.94). An exploratory factor analysis supports a one-factor solution. All factor loadings on factor 1 are at least 0.68. Therefore, we proceeded with the summarized scale. The mean of this scale is M_AvAcc = 3.37, standard deviation is SD_AvAcc = 0.84.

2.3.2 Social integration

To measure social integration, we used the subscale peer-group interaction of the Institutional Integration Scale (IIS; Pascarella and Terenzini, 1980). The IIS, based on Tinto’s (1975) theoretical framework, was developed to assess student self-reported levels of social and academic integration. French and Oakes (2004) showed evidence for high reliability for the peer-group interaction scale (α = 0.84) and proved construct validity for differentiating between student and faculty integration as separate factors. Klein (2019) showed satisfying reliability (α = 0.72), construct validity by factor analyses for subscales of social integration with peers and faculty and predictive validity for student dropout by the subscales. Paine (2008) used the IIS, again showing high reliability for the subscale peer-group interaction (α = 0.81). In this study social integration with peers was measured using six items adapted from Paine’s (2008) subscale peer group interaction (e.g., “My interpersonal relationships with students have positively influenced my intellectual growth.,” “I have developed close personal relationships with other students”).

All items were rated on a 5-point Likert scale (1 = totally disagree, 2 = disagree, 3 = neither agree nor disagree, 4 = agree, 5 = totally agree). In our study the six items show a satisfying reliability (α = 0.89). The mean of social integration is M_SI = 3.57, standard deviation is SD_SI = 0.87. Items for the Social Integration Scale, specifically for Peer Group Interactions, are listed in Supplementary Material.

2.3.3 Wellbeing

The WHO 5-item index was used to assess students’ subjective wellbeing. Participants rated how frequently they had experienced five wellbeing indicators over the past 2 weeks. Responses ranged from 0 (At no time) to 5 (All of the time) with a total score ranging from 0 (no wellbeing) to 100 (highest level of wellbeing) after multiplying the raw score by 4. It encompasses five items, which are related to the two facets of wellbeing (e.g., “I have felt active and vigorous.,” “My daily life has been filled with things that interest me”).

The WHO-5-item index is very well developed and shows excellent quality criteria. Interpretation objectivity is high: scores can be interpreted as follows: scores >50 no depression, scores between 30 and 50 slight depression and scores <30 medium depression (Blom et al., 2012). In a study with a German sample (n = 2.456) Brähler et al. (2007) showed high internal consistency (α = 0.92), high split-half-reliability (r_tt = 0.87), and convergent validity by correlating the WHO-5 with EUROHIS-QOL (r = 0.60). Several studies support the validity of the WHO-5-item index as a sensitive and specific screening instrument for depression and a valid predictor for burnout (Blom et al., 2012; Krieger et al., 2014; Topp et al., 2015). Items for the Wellbeing scale are listed in Supplementary Material. In our study the five items show a satisfying reliability (α = 0.89). The mean of wellbeing is M_WB = 50.75, standard deviation is SD_WB = 22.77.

2.3.4 Facing personal challenges (FPC)

To measure different challenges students might have to deal with, participants were asked “Are there any personal challenges you are facing as a student?” Eleven categories were created based on European Commission (EC) (2025) framework of participants with fewer opportunities due to economic, social, cultural, geographical or health reasons. Our items included physical impairment, chronic illness, mental illness, learning difficulties, cultural and financial barriers, family responsibilities and an “other” option including a free text box was given. Multiple selections were allowed. Respondents were coded as FPC if they selected at least one of the 11 categories.

3 Results

This section presents the results of our study in three parts. First, we report the descriptive analyses of the key constructs, including students’ perceptions of the availability and accessibility of informal learning spaces (ILS), perceived social integration and wellbeing and their self-reported personal challenges. Second, we address the first research question which examines whether social integration mediates the relationship the availability and accessibility of ILS and student wellbeing. Third, we explore the second research question, testing whether the strength of the relationship between ILS and social integration is moderated by facing personal challenges (FPC). The findings are based on mediation and moderation models using the PROCESS procedure (Preacher and Hayes, 2004). Together, these results provide insights into the role of informal learning environments in promoting student wellbeing and integration, with particular attention to students facing personal challenges.

3.1 Descriptive analyses

3.1.1 Facing personal challenges (FPC)

Figure 3 shows the distribution of self-reported challenges (n = 932). The most frequently cited challenges were the “need to work for living while studying” (34%) and “financial obstacles” (28%). Notably, 20% reported suffering from “mental diseases.” Every other challenge is experienced between 3 and 11% of the participants. In the “other” option 25 students (3%) mentioned specific problems (e. g. anxiety, mobbing, or pressure to find a flat). Students reporting at least one of the 11 challenges were classified as FPC. This resulted in 70% of the sample being students FPC (n = 656) and 30% being students who are not FPC (n = 276).

Figure 3

Figure 3. Personal challenges of students. Personal challenges to define students facing personal challenges (n = 932). Item: “Are there any personal challenges you are facing as a student?” Different answers were listed and could be tagged, multiple selection of challenges was possible.

3.1.2 Availability and accessibility of ILS, social integration and wellbeing

Means and standard deviations of key variables are shown in Table 2. The assumption of normality was supported by visual inspection and sample size. Pearson correlations revealed significant associations among the variables with small and medium effect sizes (see Table 2).

Table 2

Table 2. Descriptive analyses and correlations between key constructs.

Table 3 presents the means and standard deviations of key variables grouped by FPC status. Descriptive analyses revealed differences across all key variables between student FPC and those who do not FPC. Students who do not FPC report slightly higher mean scores for availability and accessibility of ILS (M = 3.47, SD = 0.87) compared to the FPC group (M = 3.32, SD = 0.82). Similarly, students FPC report lower levels of social integration (M = 3.49, SD = 0.89) in comparison to students who do not FPC (M = 3.78, SD = 0.79). A notable difference was also observed in wellbeing scores. Students FPC reported lower levels of wellbeing (M = 48.71, SD = 22.91), while students who do not reported higher levels of wellbeing (M = 55.66, SD = 21.69).

Table 3

Table 3. Means and standard deviations of key variables grouped by FPC status.

3.2 Hypotheses testing

3.2.1 Research question 1: mediation

The first research question aimed to investigate the influence of availability and accessibility of ILS on social integration and wellbeing. It was hypothesized that social integration mediates the relationship between availability and accessibility of ILS and wellbeing (see Figure 1). To test for the mediating effect of social integration we used the Process Procedure proposed by Preacher and Hayes (2004). By bootstrapping, weaknesses of the mediation analysis described by Baron and Kenny (1986) are overcome. The results of the mediation model are presented in Table 4. The indirect effects of social integration (MV) calculated by bootstrapping are shown in Table 5.

Table 4

Table 4. Mediation analysis: direct effects in the model.

Table 5

Table 5. Mediation analysis: indirect effect of social integration (MV) analyzed with bootstrapping.

The findings indicate that all direct effects in the model are significant (see Table 4). Hypothesis 1a is supported: the availability and accessibility of ILS (IV) is significantly associated with social integration (MV) (β = 0.24; p < 0.001, R²_corr. = 0.06). Hypothesis 1b is also confirmed: Social integration (MV) is significantly related to student wellbeing (DV) with (β = 0.35; p < 0.001; R²_corr. = 0.18). Furthermore, the direct effect of availability and accessibility of ILS (IV) on wellbeing (DV) is also significant (β = 0.25; p < 0.001, R²_corr. = 0.06). Next, the indirect effects of the social integration as MV are analyzed. By this we test hypothesis 1c, which assumed that social integration mediates the relationship between the availability and accessibility of ILS and students’ wellbeing. The bootstrapping procedure as proposed by Hayes (2022) was used (see Table 5).

There is a significant indirect effect of availability and accessibility (IV) on wellbeing (DV) mediated by social integration (MV) (b = 2.31, percentile bootstrap 95% CI [1.54, 3.17]). The completely standardized indirect effect of social integration (MV) was β = 0.09, Percentile Bootstrap CI [0.06, 0.12]. The CI does not include zero. Therefore, the data support the hypothesized mediation process (Hypothesis 1c).

3.2.2 Research question 2: moderation

The second research question investigated whether the availability and accessibility of ILS is more critical for students FPC compared to those who do not face personal challenges (no FPC). It was hypothesized that students experiencing personal challenges may rely more heavily on ILS to achieve social integration with their peers. To test this assumption, we established a conceptual model as seen in Figure 2 and a moderation hypothesis testing whether FPC status moderates the relationship between ILS availability/accessibility and social integration. To test the moderation hypothesis the Process Procedure for SPSS by Hayes (2022) was used with mean centered variables for all variables that define products. Results of this analysis are depicted in Table 6.

Table 6

Table 6. Moderation analysis: direct effect of availability and accessibility of ILS (IV) on social integration (DV).

The results indicate an ordinal interaction, allowing for interpretation of both main effects and the interaction effect within the model. The first main effect shows higher availability and accessibility of ILS is significantly associated with increased social integration, whereas lower availability and accessibility corresponds with reduced social integration. The second main effect pertains to FPC status: students not facing personal challenges report higher levels of social integration compared to those who do.

Additionally, there is a small interaction effect between the availability and accessibility of ILS and FPC status: students who both face personal challenges and report low availability/accessibility of ILS exhibit the lowest levels of social integration. In other words, these two risk factors appear to have a compounding negative impact. Notably, when ILS availability and accessibility is high, the difference in social integration between FPC and non-FPC students is minimal. However, under conditions of low ILS availability/accessibility, the gap between the two groups becomes substantially wider (see Figure 4).

Figure 4

Figure 4. Simple slopes analysis to visualize the interaction effect. Simple slopes analysis to visualize the interaction effect. Values for Availability and Accessibility of ILS are mean-centered and categorized in three groups (low = –0.80, medium = 0.09, high = 0.76), Social Integration can range between 1 to 5, FPC as the moderator variable is discrete. β (FPC) = 0.28***, β (no FPC) = 0.16**.

These findings suggest that the availability and accessibility of ILS is particularly vital for students facing personal challenges, to promote social integration. In contrast, students without such challenges appear to be less affected by variations in ILS accessibility.

4 Discussion

This study contributes to the growing body of research on how informal learning spaces (ILS) influence student wellbeing in higher education. It offers an understanding of how the availability and accessibility of ILS are associated with social integration and wellbeing, especially for students facing personal challenges (FPC). Drawing on Tinto’s (1975) model of social integration, our findings extend its theoretical scope by empirically demonstrating the mediating role of social integration between physical learning spaces and psychosocial outcomes.

4.1 Informal learning spaces and student wellbeing

Our findings are consistent with the hypothesized mediation mechanism: the positive effect of availability and accessibility of ILS on student wellbeing is mediated by social integration. ILS provide opportunities for peer interaction, exchange, and a sense of belonging which are crucial factors for fostering social integration. This in turn positively influences students’ wellbeing.

The results corroborate with and extend the Social Integration Model proposed by Tinto (1975, 1993), which focuses on academic and social integration in relation to dropout. By including physical and spatial elements such as availability and accessibility of ILS, we contribute to a novel perspective. Our findings suggest that physical and spatial elements, can play a crucial role in mediating social integration, especially for students FPC.

Our results also contribute to the Person–Environment (P–E) Fit Theory (Gilbreath et al., 2011), which posits that wellbeing improves when individuals interact with environments that meet their needs. ILS support students’ social needs by offering flexible, socially engaging environments (Pepper, 2024) that encourage peer interaction, reduce isolation, and foster informal social support. This psychosocial support helps to buffer stress and enhance mental health reinforcing the findings of earlier studies emphasizing the importance of social integration for student wellbeing (Imaginário et al., 2013; Zheng et al., 2004). Thus, our findings highlight recent calls for more inclusive, student-centered campus environments (Stanton et al., 2016). In face of increasing numbers of students facing mental health problems (Brown, 2018; Khatri et al., 2024; Ribeiro et al., 2024), it is especially important to know how to improve wellbeing and which measures are effective in supporting mental health.

Furthermore, our study addresses a notable research gap identified in recent reviews by Olsson et al. (2024) and Konstantinidis (2024): the lack of interventions targeting physical learning environments. While most structural wellbeing interventions target curriculum, pedagogy or support services, our findings demonstrate that well-designed and accessible ILS serve as crucial resources for fostering social integration and wellbeing. By showing how ILS (as physical resources) support social connectedness our study provides a tangible link between previously disconnected categories of structural interventions, positioning ILS as structural levers for promoting wellbeing and inclusion.

4.2 Vulnerable groups and role of inclusive ILS

The moderation analysis further reveals that the relationship between ILS and social integration is stronger for students facing personal challenges. These students, who experience structural, health-related, or social disadvantages, report significantly lower levels of social integration when ILS are not available or accessible highlighting the disproportionate importance of such spaces for vulnerable groups.

The findings emphasize that environmental constraints can exacerbate personal challenges reinforming social and psychological exclusion. This aligns well with theories of spatial justice (Soja, 2010) which highlight that campus environments can either reproduce or disrupt inequalities. Soja (2010) argues that the physical layout, accessibility, and inclusivity of spaces carry social meaning and affect students’ opportunities for participation and belonging. Our findings confirm this theoretical perspective by showing that students with personal challenges are more sensitive to environmental barriers, thus benefit more from ILS. From the perspective of Sen’s Capability Approach (Sen, 1993), ILS function as enabling resources that expand students’ real opportunities to participate, connect, and flourish within the university environment. Our findings extend the concept of capabilities and suggest that accessible ILS enhance students’ capabilities for social integration and wellbeing, particularly for students FPC, by creating equitable conditions for engagement and belonging.

Our results also support the P-E Fit Theory (Gilbreath et al., 2011) and the Social Fit Model (Walton and Cohen, 2007) suggesting that student wellbeing and belonging are contingent on how well environments accommodate individual needs and social identity. Students who perceive themselves as misaligned with dominant institutional norms or lacking the resources to access shared spaces may experience exclusion, which can negatively impact their academic and emotional wellbeing. Our study also corroborates with the results of Harrop and Turpin (2013) which emphasized the importance of creating learning environments that facilitate both academic participation and communication, recognizing the critical role of space in fostering a sense of belonging. Similarly, Beckers et al. (2016) demonstrated that students’ preferences for learning spaces are influenced by the potential for social integration, which subsequently affects their social integration.

Furthermore, our study highlighted that students with different challenges may use or have to use the facilities of the campus or university more. Evidence from Habashi et al. (2023) during COVID-19 pandemic illustrates how students from lower socioeconomic backgrounds, minorities, and first-generation college students depended more on campus facilities due to their inadequate home learning environments. This underscores the role of accessible ILS, especially for students with fewer technological and physical resources.

Additional studies highlight the structural barriers that underrepresented and disadvantaged students face in higher education. Trowler and Trowler (2010) emphasize that while engagement benefits all students, non-traditional and disadvantaged groups, such as those who are academically underprepared, from low-income backgrounds, racial and ethnic minorities, first-generation college students, LGBTQ+ individuals, students with disabilities, and international students, encounter significant barriers to meaningful engagement, often resulting in negative experiences as alienation, cultural dissonance, and isolation. However, when engagement is effectively nurtured, it can compensate, for these disadvantages and improve academic and personal outcomes.

Wong’s (2024) framework of spatial belonging stresses the importance of inclusive educational environments that are accessible and welcoming, promoting a sense of belonging and connectedness among students, particularly for students from underrepresented groups. Fernandez et al. (2025) show that perceived social status, shaped by visible markers as clothing, accent, and activity participation, strongly influences students’ sense of belonging. For those from lower-status backgrounds, ILS may either support or hinder this belonging depending on their inclusivity. This underscores the need for ILS to promote inclusive signals that affirm diverse student identities and alleviate feelings of uncertainty about belonging (Walton and Cohen, 2007). Meeuwisse et al. (2010) further reveal that while formal relationships foster belonging for ethnic minority students, informal peer connections more strongly enhance both belonging and academic performance for majority students.

Our study confirms and expands these findings by demonstrating that ILS play a significant role in fostering integration for students FPC. When access to ILS is limited, these students experience significantly lower levels of integration. On the other hand, when ILS are accessible, the integration gap between vulnerable and non-vulnerable students narrows. This interaction supports wellbeing as well as theories of spatial justice (Soja, 2010) and P-E Fit (Gilbreath et al., 2011) by showing that inclusive spatial design can mitigate structural disadvantages.

By linking physical environment, social integration and wellbeing, our study contributes new empirical evidence to the literature, underscoring the need for ILS to be intentionally designed as inclusive spaces that foster wellbeing, belonging and promote equity in higher education. It highlights how ILS act as equity mechanisms—buffering the disadvantages of limited home resources, digital inequality, or social exclusion.

4.3 Limitations

Despite the valuable insights offered by this study, several limitations should be acknowledged. First the cross-sectional design limits the ability to draw causal inferences. While the sample size is substantial and includes participants from four universities across four different countries, the findings may not be generalizable to other institutions or national contexts. Moreover, the study employed a voluntary participation, which precludes the use of random sampling and may include self-selection bias. In addition, the measurement of availability and accessibility of ILS was based on a self-developed instrument. Although the scale was carefully constructed and demonstrated strong internal consistency, it lacks prior validation in other research contexts. Future studies should seek to refine and validate this scale to enhance its robustness and comparability of findings. While mediation and moderation analysis were appropriate for exploring complex relationships among variables, the use of cross-sectional data limits the ability to confirm temporal or directional causality. Longitudinal or experimental designs are recommended to establish causal pathways and examine change over time. Finally, the study relied on self-reported data, which represents subjective perceptions of participating students and may be influenced by social desirability or recall bias. Future research could benefit from incorporating objective data (e.g., square meters of ILS per student) or observational data to measure availability and accessibility of ILS to triangulate findings.

4.4 Implications for practice and future research

The findings of this study highlight the importance of ILS as a structural resource for enhancing student wellbeing through social integration. Learning spaces can be seen as the “third teacher,” environments that shape behavior, interaction, and learning outcomes. While ambience and comfort are important, our results emphasize the significance of organizational aspects such as availability, accessibility, and ease of use. ILS should be clearly marked, barrier-free, and accompanied by transparent guidelines for use to ensure all students can engage with them meaningfully. When students can easily locate and utilize these spaces, ILS are more likely to foster informal interactions, strengthen peer networks, and contribute positively to social integration and wellbeing. For universities, this underscores the need to intentionally design and manage ILS to serve not only academic functions but also social and emotional needs (Ninnemann et al., 2024). Three key areas of institutional focus, enhancing awareness, taking action, and strengthening communication, can contribute to this aim.

First, increasing awareness is essential to ensure students and staff understand the purpose and benefits of ILS. Institutions can integrate ILS into student orientation programs, promote them through visual and digital communication, and share success stories to illustrate their impact. Tools like the NIILS mapping platform can help make ILS more visible and accessible. Second, universities must take concrete action by forming task forces to guide ILS development, allocating funding for inclusive design, and supporting innovation through research and pilot projects. Engaging cross-functional teams, including students, staff, and designers, can help ensure ILS reflect diverse needs. Recognizing individuals and teams that contribute to ILS initiatives can further embed these efforts institutionally. Finally, strengthening communication and networking is key to sustaining progress. Institutions should foster dialogue through online platforms, feedback channels, and regular events that bring together students, faculty, and external partners. Collaborating with alumni and industry stakeholders can expand support for ILS initiatives and ensure their long-term relevance. By aligning these strategies with broader goals of inclusion and wellbeing, universities can transform ILS into accessible, socially engaging environments that support academic and personal success for all students.

Future research could build on our findings by employing longitudinal, participatory and mixed-method designs to explore how students’ sustained engagement with ILS influences their learning behavior and wellbeing over time. Comparative studies across different institutional and cultural contexts may further clarify how spatial and social factors interact with students’ diverse needs. In addition, examining the role of digital and hybrid ILS would deepen our understanding how learning spaces can support inclusive and equitable learning outcomes especially for students who face challenges. Future research can also disaggregate the category of students FPC to identify how diverse groups (e.g., students with disabilities, first-generation students, migrants, older students) experience and utilize ILS.

5 Conclusion

Student wellbeing is declining globally, forcing higher education institutions to seek structural solutions that support mental health and academic success. Among these, informal learning spaces (ILS) represent a promising yet underexplored area. While recent reviews categorize structural interventions (see Konstantinidis, 2024; Olsson et al., 2024), the mechanisms by which physical environments influence wellbeing remain insufficiently understood.

This study integrates multiple streams of research (education, architecture, psychology, and business administration) to explain the link between physical spaces and health of students. It is demonstrated that availability and accessibility of ILS significantly enhance students’ social integration, which in turn positively impacts their wellbeing. Our findings support Tinto’s (1993) model of social integration and the person-environment fit theory (Gilbreath et al., 2011) as well as spatial justice (Soja, 2010), confirming that well-designed inclusive environments foster behaviors and relationships that fulfill students psychological and social needs and also creating a more just environment.

Crucially, our study shows that students facing personal challenges (FPC) benefit most from accessible ILS. These students, who often experience higher risks of exclusion, report markedly lower social integration when access to ILS is limited. When access improves, the integration gap between them and their peer narrows significantly. This highlights ILS as an effective equity-oriented strategy and aligns with calls for inclusion-focused campus interventions.

To translate these insights into practice, universities should invest not only in creating new ILS but also in upgrading existing ones. Equally important is ensuring transparency and awareness as students need to know where ILS are located and how they can be used. When ILS are both accessible and socially engaging, they serve as structural levers that promote integration, reduce dropout risks, and foster academic and emotional resilience.

Data availability statement

The datasets generated and/or analysed during the current study are available from the corresponding author upon request.

Ethics statement

The studies involving humans were approved by Akdeniz University Research and Publication Ethics Committee Date: 20/04/2022 Number:174. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

Author contributions

SG: Conceptualization, Investigation, Writing – review & editing, Formal analysis, Writing – original draft, Data curation, Methodology. FK: Methodology, Conceptualization, Writing – review & editing, Project administration, Investigation, Writing – original draft, Funding acquisition, Data curation. EÇ-Y: Writing – original draft, Formal analysis, Methodology, Writing – review & editing, Data curation, Investigation. SA: Writing – review & editing, Investigation, Data curation, Writing – original draft, Methodology.

Funding

The author(s) declare that financial support was received for the research and/or publication of this article. This study was conducted within an Erasmus+ Project “NIILS-New Approaches for Inclusive Informal Learning Spaces” (Project Number: 2021-1-AT01-KA220-HED-000032122) with the co-financing from European Commission. Project website: https://www.donauuni.ac.at/en/university/faculties/education-arts-architecture/departments/building-environment/research/niils/about-niils.html.

Acknowledgments

We would like to acknowledge the contribution of project team in all four countries in data collection and data analysis.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The authors declare that no Gen AI was used in the creation of this manuscript.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/feduc.2025.1637874/full#supplementary-material

Abbreviations

ILS, Informal learning space; FPC, Facing personal challenges; IIS, Institutional Integration Scale; P-E fit, Person-environment fit.

References

Acker, S. R., and Miller, M. D. (2005). Campus learning spaces: investing in how students learn. EDUCAUSE Center Appl. Res. Bull. 8, 1–11.

Google Scholar

Agg, C., and Khimji, S. (2021). Perception of wellbeing in educational spaces. Build. Serv. Eng. Res. Technol. 42, 677–689. doi: 10.1177/014362442110098

Crossref Full Text | Google Scholar

Allen, D. (1999). Desire to finish college: an empirical link between motivation and persistence. Res. High. Educ. 40, 461–485. doi: 10.1023/A:1018740226006

Crossref Full Text | Google Scholar

Amasuomo, T. T., and Amasuomo, J. O. (2016). Perceived thermal discomfort and stress behaviors affecting students’ learning in lecture theatres in the humid tropics. Buildings 6, 18–17. doi: 10.3390/buildings6020018

Crossref Full Text | Google Scholar

Baik, C., Larcombe, W., and Brooker, A. (2019). How universities can enhance student mental wellbeing: the student perspective. High. Educ. Res. Dev. 38, 674–687. doi: 10.1080/07294360.2019.1576596

Crossref Full Text | Google Scholar

Baron, R. M., and Kenny, D. A. (1986). Moderator mediator variables distinction in social psychological research: conceptual, strategic, and statistical considerations. J. Pers. Soc. Psychol. 51, 1173–1182. doi: 10.1037/0022-3514.51.6.1173

Crossref Full Text | Google Scholar

Beckers, R., Van der Voordt, T., and Dewulf, G. (2016). Learning space preferences of higher education students. Build. Environ. 104, 243–252. doi: 10.1016/j.buildenv.2016.05.013

Crossref Full Text | Google Scholar

Berger, J. B., and Milem, J. F. (1999). The role of student involvement and perceptions of integration in a causal model of student persistence. Res. High. Educ. 40, 641–664. doi: 10.1023/A:1018708813711

Crossref Full Text | Google Scholar

Berman, N. (2020). A critical examination of informal learning spaces. High. Educ. Res. Dev. 39, 127–140. doi: 10.1080/07294360.2019.1670147

Crossref Full Text | Google Scholar

Berman, N., Mehta, D., and Matsuo, A. (2024). The sticky campus in Japan: re-evaluating campus spaces. Glob. Soc. Educ. 22, 763–772. doi: 10.1080/14767724.2022.2121689

Crossref Full Text | Google Scholar

Bers, T. H., and Smith, K. E. (1991). Persistence of community college students: the influence of student intent and academic and social integration. Res. High. Educ. 32, 539–556. doi: 10.1007/BF00992627

Crossref Full Text | Google Scholar

Blom, E. H., Bech, P., Högberg, G., Larsson, J. O., and Serlachius, E. (2012). Screening for depressed mood in an adolescent psychiatric context by brief self-assessment scales – testing psychometric validity of WHO-5 and BDI-6 indices by latent trait analyses. Health Qual. Life Outcomes 10:149, 1–6. doi: 10.1186/1477-7525-10-149

Crossref Full Text | Google Scholar

Brähler, E., Mühlan, H., Albani, C., and Schmidt, S. (2007). Teststatistische prüfung und normierung der deutschen versionen des EUROHIS-QOL lebensqualität-index und des WHO-5 wohlbefindens-index. Diagnostica 53, 83–96. doi: 10.1026/0012-1924.53.2.83

Crossref Full Text | Google Scholar

Brett, C. E., Mathieson, M. L., and Rowley, A. M. (2023). Determinants of wellbeing in university students: the role of residential status, stress, loneliness, resilience, and sense of coherence. Curr. Psychol. 42, 19699–19708. doi: 10.1007/s12144-022-03125-8

Crossref Full Text | Google Scholar

Brooker, A., and Vu, C. (2020). How do university experiences contribute to students’ psychological wellbeing? Stud. Success 11, 99–108. doi: 10.5204/ssj.1676

Crossref Full Text | Google Scholar

Brown, J. S. (2018). Student mental health: some answers and more questions. J. Ment. Health 27, 193–196. doi: 10.1080/09638237.2018.1470319

Crossref Full Text | Google Scholar

Cerasoli, C. P., Alliger, G. M., Donsbach, J. S., Mathieu, J. E., Tannenbaum, S. I., and Orvis, K. A. (2018). Antecedents and outcomes of informal learning behaviors: a meta-analysis. J. Bus. Psychol. 33, 203–230. doi: 10.1007/s10869-017-9492-y

Crossref Full Text | Google Scholar

Chattaraj, D., and Vijayaraghavan, A. P. (2021). The mobility paradigm in higher education: a phenomenological study on the shift in learning space. Smart Learn. Environ. 8:15. doi: 10.1186/s40561-021-00162-x

PubMed Abstract | Crossref Full Text | Google Scholar

Chaudhry, S., Tandon, A., Shinde, S., and Bhattacharya, A. (2024). Student psychological well-being in higher education: the role of internal team environment, institutional, friends and family support and academic engagement. PLoS One 19:e0297508. doi: 10.1371/journal.pone.0297508

PubMed Abstract | Crossref Full Text | Google Scholar

Chin, D. C., Hsu, C. H., and Yau, K. T. (2021). Developing a taxonomy of informal learning space. Int. J. Educ. 13, 86–105. doi: 10.5296/ije.v13i4.19016

Crossref Full Text | Google Scholar

Clark, C., Myron, R., Stansfeld, S., and Candy, B. (2007). A systematic review of the evidence on the effect of the built and physical environment on mental health. J. Public Ment. Health 6, 14–27. doi: 10.1108/17465729200700011

Crossref Full Text | Google Scholar

Cooper, R., Boyko, C., and Codinhoto, R. (2009). “The effect of the physical environment on mental wellbeing” in Mental capital and wellbeing. eds. C. L. Cooper, J. Field, U. Goswami, R. Jenkins, and B. J. Sahakian (Oxford, UK: Wiley & Blackwell), 967–1006.

Google Scholar

Costa, A. P., and Steffgen, G. (2020). After the move to a new campus—effects on students’ satisfaction with the physical and learning environment. Educ. Sci. 10:370. doi: 10.3390/educsci10120370

Crossref Full Text | Google Scholar

Crawford, J., Allen, K. A., Sanders, T., Baumeister, R., Parker, P., Saunders, C., et al. (2024). Sense of belonging in higher education students: an Australian longitudinal study from 2013 to 2019. Stud. High. Educ. 49, 395–409. doi: 10.1080/03075079.2023.2238006

Crossref Full Text | Google Scholar

Creswell, J. W., and Creswell, J. D. (2017). Research design: qualitative, quantitative, and mixed methods approaches. New York, NY: Sage.

Google Scholar

Cui, X., and Ahn, C. (2024). The mediating role of space satisfaction in enhancing learning outcomes: a study of university library learning spaces and informal learning needs. Int. J. Sustain. Build. Technol. Urban Dev. 15, 545–562. doi: 10.22712/susb.20240038

Crossref Full Text | Google Scholar

Cuppen, J., Muja, A., and Geurts, R. (2024). Well-being and mental health among students in European higher education. EUROSTUDENT 8 topical module report. Hannover: DZHW.

Google Scholar

Devlin, M., Kift, S., Nelson, K., Smith, L., and Mckay, J. (2012). Effective teaching and support of students from low socioeconomic status backgrounds: resources for Australian higher education. Sydney, Commonwealth of Australia: Australian Government Office for Learning and Teaching.

Google Scholar

Diener, E. (1984). Subjective well-being. Psychol. Bull. 95, 542–575. doi: 10.1037/0033-2909.95.3.542

PubMed Abstract | Crossref Full Text | Google Scholar

Dovey, K., and Fisher, K. (2014). Designing for adaptation: the school as socio-spatial assemblage. J. Archit. 19, 43–63. doi: 10.1080/13602365.2014.882376

Crossref Full Text | Google Scholar

Ellis, R. A., and Goodyear, P. (2016). Models of learning space: integrating research on space, place and learning in higher education. Rev. Educ. 4, 149–191. doi: 10.1002/rev3.3056

Crossref Full Text | Google Scholar

European Commission (EC) (2025). Participant with fewer opportunities - Erasmus+ & European Solidarity Corps guides, EC public wiki. Available online at: https://wikis.ec.europa.eu/spaces/NAITDOC/pages/78708758/Participant+with+fewer+opportunities (Accessed March 11, 2025).

Google Scholar

Fernandez, D., Wong, C. Y., Bedford, S., Oliveria-Silva, L., Begeny, C., and Ryan, M. (2025). Further disadvantages of socioeconomic status: the role of subjective social status in university students' sense of belonging. J. Community Appl. Soc. Psychol. 35:e70037. doi: 10.1002/casp.70037

Crossref Full Text | Google Scholar

Fernández-Batanero, J. M., Montenegro-Rueda, M., and Fernández-Cerero, J. (2022). Access and participation of students with disabilities: the challenge for higher education. Int. J. Environ. Res. Public Health 19:11918. doi: 10.3390/ijerph191911918

PubMed Abstract | Crossref Full Text | Google Scholar

Fink, J. E. (2014). Flourishing: exploring predictors of mental health within the college environment. J. Am. Coll. Heal. 62, 380–388. doi: 10.1080/07448481.2014.917647

PubMed Abstract | Crossref Full Text | Google Scholar

French, B. F., and Oakes, W. (2004). Reliability and validity evidence for the institutional integration scale. Educ. Psychol. Meas. 64, 88–98. doi: 10.1177/001316440325845

Crossref Full Text | Google Scholar

Fritz, M. S., and MacKinnon, D. P. (2007). Required sample size to detect the mediated effect. Psychol. Sci. 18, 233–239. doi: 10.1111/j.1467-9280.2007.01882

Crossref Full Text | Google Scholar

Geister, S., Ninnemann, K., and Schneidt, J. (2024). Synthesis report. Users’ perspective analysis: usage, perception, and impact of informal learning spaces. ERASMUS new ap-proaches for inclusive informal learning spaces (NIILS). Berlin. Available online at: https://opus4.kobv.de/opus4-htw/frontdoor/index/index/docId/1870

Google Scholar

Gilbreath, B., Kim, T. Y., and Nichols, B. (2011). Person-environment fit and its effects on university students: a response surface methodology study. Res. High. Educ. 52, 47–62. doi: 10.1007/s11162-010-9182-3

Crossref Full Text | Google Scholar

Groves, H. (2017). How student centres can help create ‘sticky campuses’. Available online at: https://www.atkinsglobal.com/en-GB/angles/all-angles/how-student-centres-can-help-create-sticky-campuses

Google Scholar

Guney, A., and Al, S. (2012). Effective learning environments in relation to different learning theories. Procedia. Soc. Behav. Sci. 46, 2334–2338. doi: 10.1016/j.sbspro.2012.05.480

Crossref Full Text | Google Scholar

Habashi, K., Andersen, S., Patel, D., Leon, G. K., Lee, C., and Simanton, E. (2023). Disadvantaged students utilize school campus and its resources more than non-disadvantaged students. Cures 15:e46128. doi: 10.7759/cureus.46128

Crossref Full Text | Google Scholar

Halupka, V., and Li, J.. (2023). Informal learning spaces to enhance engagement, belonging and engineering identity in first-year students. In Proc. of the AAEE 2023 conference, Gold Coast, Australia. Australasian Association for Engineering Education.

Google Scholar

Harrop, D., and Turpin, B. (2013). A study exploring learners’ informal learning space behaviors, attitudes, and preferences. New Rev. Acad. Libr. 19, 58–77. doi: 10.1080/13614533.2013.740961

Crossref Full Text | Google Scholar

Hayes, A. F. (2022). Introduction to mediation, moderation, and conditional process analysis: a regression-based approach. 3rd Edn. New York, NY: Guilford Press.

Google Scholar

Hernández-Torrano, D., Ibrayeva, L., Sparks, J., Lim, N., Clementi, A., Almukhambetova, A., et al. (2020). Mental health and well-being of university students: a bibliometric mapping of the literature. Front. Psychol. 11:1226. doi: 10.3389/fpsyg.2020.01226

PubMed Abstract | Crossref Full Text | Google Scholar

Higgins, S., Hall, E., Wall, K., Woolner, P., and McCaughey, C. (2005). The impact of school environments: A literature review. The Centre for Learning and Teaching, School of Education, Communication and Language Science. University of Newcastle. Available online at: https://www.ncl.ac.uk/media/wwwnclacuk/cflat/files/archived-reports/school-environment-literature-review.pdf

Google Scholar

Holm-Hadulla, R. M., Klimov, M., Juche, T., Möltner, A., and Herpertz, S. C. (2021). Well-being and mental health of students during the COVID-19 pandemic. Psychopathology 54, 291–297. doi: 10.1159/000519366

PubMed Abstract | Crossref Full Text | Google Scholar

Imaginário, S., Vieira, L. S., and de Jesus, S. N. (2013). Subjective well-being and social integration of college students. J. Tour. Sustain. Well-being 1, 215–223.

Google Scholar

Judd, C. M., Yzerbyt, V. Y., and Muller, D. (2014). “Mediation and moderation” in Handbook of research methods in social and personality psychology. eds. H. T. Reiss and C. M. Judd (Cambridge, UK: Cambridge University Press), 653–676.

Google Scholar

Kassab, S. E., Rathan, R., Schmidt, H. G., and Hamdy, H. (2024). Influence of the university campus environment on sociocultural engagement and satisfaction of health professions education students: role of the sense of belonging. BMC Med. Educ. 24:1512. doi: 10.1186/s12909-024-06534-4

PubMed Abstract | Crossref Full Text | Google Scholar

Keser Aschenberger, F., Radinger, G., Brachtl, S., Ipser, C., and Oppl, S. (2022). Physical home learning environments for digitally-supported learning in academic continuing education during COVID-19 pandemic. Learn. Environ. Res. 26, 97–128. doi: 10.1007/s10984-022-09406-0

PubMed Abstract | Crossref Full Text | Google Scholar

Keyes, C. L. M. (1998). Social well-being. Soc. Psychol. Q. 61, 121–140. doi: 10.2307/2787065

Crossref Full Text | Google Scholar

Khatri, P., Duggal, H. K., Lim, W. M., Thomas, A., and Shiva, A. (2024). Student well-being in higher education: scale development and validation with implications for management education. Int. J. Manag. Educ. 22:100933. doi: 10.1016/j.ijme.2024.100933

Crossref Full Text | Google Scholar

Klein, D. (2019). Das Zusammenspiel zwischen akademischer und sozialer Integration bei der Erklärung von Studienabbruchintentionen: Eine empirische Anwendung von Tintos Integrationsmodell im deutschen Kontext. Z. Erziehungswiss. 22, 301–323. doi: 10.1007/s11618-018-0852-9

Crossref Full Text | Google Scholar

Konstantinidis, A. (2024). An integrative review of the literature on factors influencing student well-being in the learning environment. Int. J. Educ. Res. Open 7:100384, 1–12. doi: 10.1016/j.ijedro.2024.100384

Crossref Full Text | Google Scholar

Krieger, T., Zimmermann, J., Huffziger, S., Ubl, B., Diener, C., Kuehner, C., et al. (2014). Measuring depression with a well-being index: further evidence for the validity of the WHO well-being index (WHO-5) as a measure of the severity of depression. J. Affect. Disord. 156, 240–244. doi: 10.1016/j.jad.2013.12.015

Crossref Full Text | Google Scholar

Kroher, M., Beuße, M., Isleib, S., Becker, K., Ehrhardt, M., Gerdes, F., et al. (2021). Die Studierendenbefragung in Deutschland: 22. Sozialerhebung. BMBF. Available online at: https://www.bmbf.de/SharedDocs/Publikationen/de/bmbf/4/31790_22_Sozialerhebung_2021.html

Google Scholar

Kuehner, C., Schultz, K., Gass, P., Meyer-Lindenberg, A., and Dreßing, H. (2020). Psychisches Befinden in der Bevölkerung während der COVID-19-Pandemie. Psychiatr. Prax. 47, 361–369. doi: 10.1055/a-1222-9067

PubMed Abstract | Crossref Full Text | Google Scholar

LeGrow, K., Dubrowski, A., Saunders, C., and Roche, J. (2023). How undergraduate and graduate students experience space and place in a new health sciences building. Can. J. High. Educ. 53, 123–140. doi: 10.1177/08445621231190581

Crossref Full Text | Google Scholar

Li, H. (2025). Students’ wellbeing in positive higher education: conceptual frameworks and influencing factors. Front. Educ. 10:1607364. doi: 10.3389/feduc.2025.1607364

Crossref Full Text | Google Scholar

Liu, W., Sun, N., Guo, J., and Zheng, Z. (2022). Campus green spaces, academic achievement and mental health of college students. Int. J. Environ. Res. Public Health 19:14, 8618. doi: 10.3390/ijerph19148618

PubMed Abstract | Crossref Full Text | Google Scholar

Makaremi, N., Yildirim, S., Morgan, G. T., Touchie, M. F., Jakubiec, A., and Robinson, J. (2024). Impact of classroom environment on student wellbeing in higher education: review and future directions. Build. Environ. 265:111958. doi: 10.1016/j.buildenv.2024.111958

Crossref Full Text | Google Scholar

Matthews, K., Andrews, V., and Adams, P. (2011). Social learning spaces and student engagement. High. Educ. Res. Dev. 30, 105–120. doi: 10.1080/07294360.2010.512629

Crossref Full Text | Google Scholar

McFarland, A. L., Waliczek, T. M., and Zajicek, J. M. (2008). The relationship between student use of campus green spaces and perceptions of quality of life. HortTechnology 18, 232–238. doi: 10.21273/HORTTECH.18.2.232

Crossref Full Text | Google Scholar

Meeuwisse, M., Severiens, S. E., and Born, M. P. (2010). Learning environment, interaction, sense of belonging and study success in ethnically diverse student groups. Res. High. Educ. 51, 528–545. doi: 10.1007/s11162-010-9168-1

Crossref Full Text | Google Scholar

Melhuish, E., Belsky, J., Leyland, A. H., and Barnes, J. (2008). Effects of fully-established sure start local programmes on 3-year-old children and their families living in England: a quasi-experimental observational study. Lancet 372, 1641–1647. doi: 10.1016/S0140-6736(08)61687-6

PubMed Abstract | Crossref Full Text | Google Scholar

Merola, R. H., Coelen, R. J., and Hofman, W. H. A. (2019). The role of integration in understanding differences in satisfaction among Chinese, Indian, and South Korean international students. J. Stud. Int. Educ. 23, 535–553. doi: 10.1177/1028315319861355

Crossref Full Text | Google Scholar

Morieson, L., Murray, G., Wilson, R., Clarke, B., and Lukas, K. (2018). Belonging in space: informal learning spaces and the student experience. J. Learn. Spaces 7, 12–22.

Google Scholar

Muhammad, S., Sapri, M., and Sipan, I. (2014). Academic buildings and their influence on students’ wellbeing in higher education institutions. Soc. Indic. Res. 115, 1159–1178. doi: 10.1007/s11205-013-0262-6

Crossref Full Text | Google Scholar

Neves, J., and Hillman, N. (2017). 2017 student academic experience survey. New York, NY: Higher Education Academy.

Google Scholar

Ninnemann, K. (2018). Innovationsprozesse und Potentiale der Lernraumgestaltung an Hochschulen: Die Bedeutung des dritten Pädagogen bei der Umsetzung des "Shift from Teaching to Learning". Münster: Waxmann.

Google Scholar

Ninnemann, K., Geister, S., and Schneidt, J. (2024). “The relevance of bricks and clicks. Research insights on strategies in context of informal learning spaces at universities” in Transdisciplinary workplace research. eds. A. Smith, A. Reid, M. Jowkar, and S. Jaradat, Proceedings of the 4th Transdisciplinary Workplace Research (TWR) Conference (Edinburgh Napier University), 378–388.

Google Scholar

Ninnemann, K., and Jahnke, I. (2018). “Den dritten Pädagogen neu denken: Wie CrossActionSpaces Perspektiven der Lernraumgestaltung verändern” in Digitalisierung und Hochschulentwicklung: Proceedings zur 26. Tagung der Gesellschaft für Medien in der Wissenschaft e.V. mit elearn.nrw. eds. B. Getto, P. Hintze, and M. Kerres (Münster, NY: Waxmann), 133–145.

Google Scholar

Ochnik, D., Rogowska, A. M., Kuśnierz, C., Jakubiak, M., Schütz, A., Held, M. J., et al. (2021). Mental health prevalence and predictors among university students in nine countries during the COVID-19 pandemic: a cross-national study. Sci. Rep. 11:18644. doi: 10.1038/s41598-021-97697-3

Crossref Full Text | Google Scholar

OECD (2023). Education at a glance 2019: OECD indicators : OECD Publishing.

Google Scholar

Olsson, T. M., Broberg, M., Frisk, S., Wackenhut, A. F., Kjellin, D., Gullstrand, S., et al. (2024). Health-promoting learning environments in higher education: a scoping review of structural interventions to protect student mental health. Eur. J. Educ. 59, 1–18. doi: 10.1111/ejed.12772

Crossref Full Text | Google Scholar

Paine, D. E. (2008). An exploration of three residence hall types and the academic and social integration of first year students. [Doctoral dissertation]. Tampa (FL): University of South Florida.

Google Scholar

Palmisano, F., Biagi, F., and Peragine, V. (2022). Inequality of opportunity in tertiary education: evidence from Europe. Res. High. Educ. 63, 514–565. doi: 10.1007/s11162-021-09658-4

PubMed Abstract | Crossref Full Text | Google Scholar

Papaioannou, G., Volakaki, M. G., Kokolakis, S., and Vouyioukas, D. (2023). Learning spaces in higher education: a state-of-the-art review. Trends High. Educ. 2, 526–545. doi: 10.3390/higheredu2030032

Crossref Full Text | Google Scholar

Pascarella, E. T., and Terenzini, P. T. (1980). Predicting freshman persistence and voluntary dropout decisions from a theoretical model. J. High. Educ. 51, 60–75. doi: 10.1080/00221546.1980.11780030

Crossref Full Text | Google Scholar

Pepper, C. (2024). The student experience of informal learning spaces in UK campus universities. [Doctoral dissertation]. UK: Loughborough University.

Google Scholar

Peters, T., and D’Penna, K. (2020). Biophilic design for restorative university learning environments: a critical review of literature and design recommendations. Sustain. For. 12:7064. doi: 10.3390/su12177064

Crossref Full Text | Google Scholar

Preacher, K. J., and Hayes, A. F. (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behav. Res. Methods 36, 717–731. doi: 10.3758/BF03206553

Crossref Full Text | Google Scholar

Ramsden, B. (2011). Evaluating the impact of learning space. Ref. Serv. Rev. 39, 451–464. doi: 10.1108/00907321111161430

Crossref Full Text | Google Scholar

Ribeiro, H., Santana, K. V. D. S., and Oliver, S. L. (2024). Natural environments in university campuses and students’ well-being. Int. J. Environ. Res. Public Health 21:413. doi: 10.3390/ijerph21040413

PubMed Abstract | Crossref Full Text | Google Scholar

Ricciardi, P., and Buratti, C. (2018). Environmental quality of university classrooms: subjective and objective evaluation of the thermal, acoustic, and lighting comfort conditions. Build. Environ. 127, 23–36. doi: 10.1016/j.buildenv.2017.10.030

Crossref Full Text | Google Scholar

Ryan, R. M., and Deci, E. L. (2001). On happiness and human potentials: a review of research on hedonic and eudaimonic well-being. Annu. Rev. Psychol. 52, 141–166. doi: 10.1146/annurev.psych.52.1.141

PubMed Abstract | Crossref Full Text | Google Scholar

Ryff, C. D. (1989). Happiness is everything, or is it? Explorations on the meaning of psychological well-being. J. Pers. Soc. Psychol. 57, 1069–1081. doi: 10.1037/0022-3514.57.6.1069

Crossref Full Text | Google Scholar

Sachs, D., and Schreuer, N. (2011). Inclusion of students with disabilities in higher education: performance and participation in student’s experiences. Disabil. Stud. Q. 31. doi: 10.18061/dsq.v31i2.1593

Crossref Full Text | Google Scholar

Scannell, L., Hodgson, M., García Moreno Villarreal, J., and Gifford, R. (2016). The role of acoustics in the perceived suitability of, and well-being in, informal learning spaces. Environ. Behav. 48, 769–795. doi: 10.1177/0013916514567127

Crossref Full Text | Google Scholar

Scott-Webber, L. (2015). Informal learning places – oft forgotten yet important places for student learning; time for a design rethink! Des. Commun. Theme Rep. 2, 28–43.

Google Scholar

Scoulas, J., and De Groote, S. (2019). The library’s impact on university students’ academic success and learning. Evid. Based Libr. Inf. Pract. 14, 2–27. doi: 10.18438/eblip29547

Crossref Full Text | Google Scholar

Sen, A. (Ed.) (1980). Equality of what? Cambridge, UK: Cambridge University Press.

Google Scholar

Sen, A. (1993). “Capability and well-being” in The quality of life. eds. M. Nussbaum and A. Sen (Oxford, UK: Clarendon Press), 270–293.

Google Scholar

Sen, A. (1999). Development as freedom. New York, NY: Knopf.

Google Scholar

Shouder, T., Inglis, G., and Rossini, A. (2014). Listening to students: make learning spaces your own. Change 46, 26–27. doi: 10.1080/00091383.2014.867208

Crossref Full Text | Google Scholar

Sivunen, M., Viljanen, J., Nenonen, S., and Kajander, J. K. (2014). Evidence-based design in learning environments: a practical framework for project briefing. Int. J. Facil. Manag. 13, 162–174.

Google Scholar

Skerlak, T., Kaufmann, H., and Bachmann, G. (Eds.) (2014). Lernumgebungen an der Hochschule: Auf dem Weg zum Campus von morgen. Münster: Waxmann.

Google Scholar

Soja, E. W. (2010). Seeking spatial justice. Minnesota, MN: University of Minnesota Press.

Google Scholar

Stanton, A., Zandvliet, D., Dhaliwal, R., and Black, T. (2016). Understanding students' experiences of well-being in learning environments. High. Educ. Stud. 6, 90–99. doi: 10.5539/hes.v6n3p90

Crossref Full Text | Google Scholar

THRIVE Project (2025). Accessible campus facilities: making education more inclusive : THRIVE Publishing. Available at https://thrivabilitymatters.org/accessible-campus-facilities/

Google Scholar

Tinto, V. (1975). Dropout from higher education: a theoretical synthesis of recent research. Rev. Educ. Res. 45, 89–125. doi: 10.3102/00346543045001089

Crossref Full Text | Google Scholar

Tinto, V. (1986). “Theories of student departure revisited” in Higher education: handbook of theory and research. ed. J. Smart (New York, NY: Agathon Press), 359–384.

Google Scholar

Tinto, V. (1993). Leaving college: Rethinking the causes and cures of student attrition. 2nd Edn. Chicago, IL: University of Chicago Press.

Google Scholar

Tomaševski, K. (2001). Human rights obligations: making education available, accessible, acceptable and adaptable. Right to Education Primers No. 3. Available online at: https://bibliotecadigital.mineduc.cl/bitstream/handle/20.500.12365/18061/44_Tomasevski_Primer%203.pdf?sequence=1

Google Scholar

Topp, C. W., Østergaard, S. D., Søndergaard, S., and Bech, P. (2015). The WHO-5 well-being index: a systematic review of the literature. Psychother. Psychosom. 84, 167–176. doi: 10.1159/000376585

Crossref Full Text | Google Scholar

Trowler, V., and Trowler, P. (2010). Student engagement evidence summary. York, UK: Higher Education Academy.

Google Scholar

Vidalakis, C., Ming, M., and Papa, A. (2013). The quality and value of higher education facilities: a comparative study. Facilities 31, 489–504. doi: 10.1108/F-10-2011-0087

Crossref Full Text | Google Scholar

Walker, M., and Unterhalter, E. (2007). “The capability approach: its potential for work in education” in Amartya Sen’s capability approach and social justice in education. eds. M. Walker and E. Unterhalter (New York, NY: Palgrave Macmillan US), 1–18.

Google Scholar

Walton, G. M., and Cohen, G. L. (2007). A question of belonging: race, social fit, and achievement. J. Pers. Soc. Psychol. 92, 82–96. doi: 10.1037/0022-3514.92.1.82

Crossref Full Text | Google Scholar

Wang, Q., and Han, X. (2021). The influence of learning styles on perception and preference of learning spaces in the university campus. Buildings 11:572. doi: 10.3390/buildings11120572

Crossref Full Text | Google Scholar

Webb, K. M., Schaller, M. A., and Hunley, S. A. (2008). Measuring library space use and preferences: charting a path toward increased engagement. Portal Libr. Acad. 8, 407–422. doi: 10.1353/pla.0.0014

Crossref Full Text | Google Scholar

Wilson, H. (2009). “The process of creating learning space” in Designing next generation places of learning: collaboration at the pedagogy-space-technology nexus. eds. D. Radcliffe, H. Wilson, D. Powell, and B. Tibbetts (Brisbane: University of Queensland), 19–24.

Google Scholar

Wong, B. (2024). Exploring the spatial belonging of students in higher education. Stud. High. Educ. 49, 546–558. doi: 10.1080/03075079.2023.2243285

Crossref Full Text | Google Scholar

World Health Organization (WHO) (2020). Basic documents. 49th Edn. Geneva: World Health Organization.

Google Scholar

Wu, X., Oldfield, P., Borsi, K., Heath, T., and Kou, Z. (2021). Informal learning spaces in higher education: student preferences and activities. Buildings 11:252. doi: 10.3390/buildings11060252

Crossref Full Text | Google Scholar

Zheng, X., Sang, D., and Lin, Q. (2004). Personality, cognitive and social orientations and subjective wellbeing among Chinese students. Aust. Psychol. 39, 166–171. doi: 10.1080/00050060410001701889

Crossref Full Text | Google Scholar