Abstract
The concept of belonging within society is important to all human beings but this is enhanced in school settings, particularly amongst adolescents, who are negotiating their place in the community. School connectedness is linked to improved outcomes for young people. This research updates a measure of school connectedness with a participatory methodology involving adolescent co-production. Given our desire to develop a questionnaire that is easy to administer in schools and which reliably measures the level of school connectedness of students, it was important to include the voice of young people. The team tested a questionnaire, discussed the results, evaluated the question wording and structure, and developed a revised version of a belonging survey that is meaningful to young people. The resulting questionnaire was administered in two schools and the data shared with those schools. This paper discusses the validity of the questionnaire and uses statistical analysis to prove that the new version can be used to measure the level of school connectedness in individual schools and across schools. This will be a useful instrument for schools to use on a regular basis to measure the level of belonging within their schools, at whole school, year group, or class level.
Plain language summary
A student-centred survey to measure feelings of belonging to school.
Feeling connected to a school community is essential to underpin learning and support positive health. This is especially important for adolescents who sometimes find school difficult. The Covid-19 pandemic has made re-establishing school connections a challenge for some young people. It is important that schools and teachers understand how to cultivate feelings of belonging to school and that they have a simple survey they can use to test the connectedness of their students. We decided to test and revise a well-established survey by working with school students to ensure that we understood what was important to them and that the questions in the survey made sense to them.
We worked with ten students to look at the results of the survey from their school. We discussed the findings and what might have affected students’ answers, such as the way the question was worded. Over several workshops we revised the survey and then tested it in two secondary schools.
The results show that the new version of the survey can measure the level of school connectedness for an individual school as well as being useful for measuring connectedness across a larger group of students. The resulting survey only has ten questions, which can be quickly and easily filled in by students online or on paper. Teachers could use this as a tool to measure school connectedness of their students and to identify areas where improvements could be made. They can then use the survey to check whether the changes have made any difference to how students feel about school.
It is important that the school connectedness survey is put into the hands of teachers (rather than researchers) who can regularly review how students feel about school and make adjustments to improve their feelings of belonging.
Introduction
In an era marked by exceptional difficulties in the field of education, including the Covid 19 pandemic, the development of a feeling of connection within schools has acquired increased importance. School connectedness plays a pivotal role in shaping students’ overall well-being and academic success. Several studies have highlighted its significance as a protective factor against various negative outcomes, making it an essential aspect of a positive and supportive school environment. Some young people have struggled to re-connect with school since the pandemic, the details of which schools need to understand then work to improve.
According to Shochet et al. (2016), the term “school connectedness” encompasses a wide range of ideas, such as school involvement, school bonding, school attachment and school belonging. School connectedness is essentially the psychological and emotional bond children have with their learning environment. It is crucial for building a supportive learning environment, raising academic standards, and nurturing students’ overall well-being.
The current study attempts to provide a more comprehensive and inclusive metric for assessing ‘School Connectedness’ by fostering collaboration among students and educators in the United Kingdom. The Psychological Sense of School Membership (PSSM) survey devised by Carol Goodenow in 1993, which has been extensively used as a helpful instrument for analysing the complexities of the concept of school connectedness, serves as the foundation of our research. We considered that it would be valuable to review this instrument thirty years after its publication to evaluate its efficacy in a UK context.
The active participation of students in the creation and evaluation of our revised tool for measuring school connectedness, is a crucial feature of our research. In a positive display of active participation, a group of ten Year 9 (14-15 years old) students volunteered to contribute their time as co-researchers. Their evaluation of the outcomes of the survey completed by students in their school resulted in exceptional contributions that provided critical semantic insights. The student engagement displayed in this study demonstrates the possibilities for participatory research in education. Furthermore, it contributes significantly to the trustworthiness and relevance of our survey instrument.
This collaborative project stresses the need for inclusive and student-centred research, which is especially important in today's educational settings, where teachers and students face unprecedented challenges.
Theoretical Framework
Understanding School Belonging
The theoretical underpinnings of school belonging are varied. Theories such as Maslow's hierarchy of needs (Maslow, 1943), Social Identity Theory (Tajfel & Turner, 1979), Self-Determination Theory (Ryan & Deci, 2000), and Bronfenbrenner's Ecological Systems Theory (Bronfenbrenner, 1994) have been mentioned in the literature (Waters et al., 2010; Kiefer et al., 2015; Slaten et al., 2016; Hautala et al., 2022). These theories facilitate comprehension of the notion of belonging and its development.
The notion of belonging is a fundamental human need rather than merely a particular desire. Belonging was mentioned in Maslow's theory of the hierarchy of needs, which states that satisfaction of five fundamental needs is a prerequisite for motivation and satisfaction of other higher needs (Maslow, 1943). Maslow discusses how all humans have a fundamental need for affection and belonging. He hypothesised that the need for belonging would emerge only once the physiological and safety criteria were met. Maslow defines belonging as being tied to family, friends, community, and social groups, as well as the connections made via the establishment of meaningful relationships (Slaten et al., 2016). As a result, in the context of schools, if a person's social requirements are not met, they are unable to advance to higher demands, such as learning.
From the self-determination theory perspective, this centres on intrinsic drive and human behaviour. The theory suggests that individuals possess three fundamental psychological needs: autonomy (the perception of control), competence (the sense of being capable), and relatedness (the ability to connect with others). Psychological well-being is contingent upon the fundamental requirement of relatedness, which encompasses a profound sense of belonging and connection (Deci & Ryan, 2008). Because of this, schools that encourage meaningful interactions and cultivate relationships between students and teachers can fulfil the necessity for a feeling of connection.
Social Identity Theory from Tajfel and Turner (1979) is based on intergroup interactions between personal and social identity. The theory states that one source of self-esteem is based on membership. In that sense individuals want to boost their self-esteem by aligning themselves with specific social groupings, emphasising the significance of group or community membership in shaping an individual's identity and self-perception (Hogg & Vaughan, 2018). For example, within an educational setting, students may establish a connection with extracurricular groups receiving a feeling of belonging and improving self-esteem from these associations.
Allen et al. (2016) reviewed the school belonging concept using the bioecological model of human development framework from Bronfenbrenner (1994). As a result, they stated that school belonging is influenced not only by peers, families, and teachers but also by the school's social and organizational culture, and interactions with parents, broader policies, norms, cultural values and temporal aspects.
According to the findings of Allen et al., a sense of belonging at school is influenced by a variety of factors that are present at different levels. Individual elements such as academic drive, emotional stability, and personal attributes such as conscientiousness, optimism and self-esteem, all have a substantial impact on school belonging. Emotional stability appeared as an important predictor, highlighting its importance in promoting school belonging (Allen et al., 2016).
On a different level, support networks are crucial for the development of adolescents. Parental support plays a crucial role in a child's upbringing, encompassing academic and social guidance, effective communication, and nurturing behaviour. This relationship provides the necessary elements of safety and acceptance that are essential for a child's sense of security. During adolescence, peers assume importance in terms of acceptance and social bonding. Peers who provide support offer both social and academic motivation, promote a sense of care, and acceptance. On the other hand, peers who do not offer support can cause stress and social anxiety. Teachers who promote reciprocal respect, motivation, equity, and independence, contribute to a cherishing atmosphere. Their accessibility, approval, and tailored academic support fosters bonds that enhance student learning and success (Dweck et al., 2014; Allen et al., 2016).
Finally, at the school level, this has a huge impact on pupils’ sense of belonging. The number of group memberships and engagement in extracurricular activities, for example, both contribute to a student's sense of belonging. Participation in a variety of extracurricular activities is associated with improved school belonging. While less studied, larger environmental factors within schools, such as overall climate and structural regulations, have significant roles in promoting belonging. Feeling cared for, supported, and emotionally linked are all elements that contribute to a sense of school community (Allen et al., 2016). Kuttner (2023) suggests that much of the literature focussed on school belonging takes a psychological perspective, which does not satisfactorily consider all of the other factors impacting on the experience of young people. His definition of belonging includes a focus on belonging being ‘agentic, intersectional, systemic, place-based, political, and a right’ (p.8). after consideration of all of these aspects, Kuttner offers a definition, which encompasses more of the reality of school life. 'School belonging is a dynamic social process in which students engage interpersonal relationships, intersecting and fluid identities, their locations within systems of power, and the politics of inclusion and exclusion as they establish a place for themselves and realize their right to be—and feel that they are—valued and active participants, on their own terms, in formal educational spaces’ (2023, p.8).
School Belonging or School Connectedness?
The terms “school connectedness” and “school belonging” have been utilized interchangeably in scholarly literature. In their study, Alink et al. (2023) investigated the construct of “school belonging”. The researchers were tasked with assessing the various synonyms associated with this notion, as well as evaluating and categorising the factors that contribute to a sense of school belonging. The researchers reach the initial determination that “school connectedness” is the most suitable term to be used interchangeably with the concept of school belonging. Furthermore, measures pertaining to inclusion, acceptance, connection, and respect were accorded considerable marks. The results demonstrate a consensus among experts about these indicators. The idea of school belonging, as proposed by Goodenow (1993), is widely recognised and frequently cited in academic literature. Her operationalization of this concept is highly regarded and occupies a prominent place within the field.
For the purposes of our research, we consider two aligned definitions: ‘School connectedness’, refers to the extent to which adolescents feel personally accepted, respected, included, and supported by others, especially teachers and other adults in the school social environment (Ciani et al., 2010; Goodenow & Grady, 1993; Osterman, 2000; Shochet et al., 2016). It signifies a student's sense of affiliation and connection to their school (Allen & Boyle, 2018). Second, The Centres for Disease, Control and Prevention from the United States (CDC) defines ‘School connectedness’ as the belief by students that adults and peers in the school care about their learning as well as about them as individuals (CDC, 2009).
The significance of the emotional support, acceptance, and sense of belonging that children feel within their school community is highlighted by these concepts. Students are more likely to be actively involved in their study, create good connections with peers and teachers, and gain a stronger sense of identity within the educational environment when they experience a feeling of belonging to their school.
Why School Connectedness is Important?
The literature reveals a multitude of benefits associated with school connectedness. Some of these are:
Improved Academic Success and Healthy Behaviours: When students feel connected to their school, they are more likely to be actively engaged in their education. The Centers for Disease Control and Prevention (CDC, 2009) have found that students who experience a sense of connectedness are more inclined to participate in healthy behaviours and are more likely to succeed academically. Such students tend to be more motivated, focused, and committed to their learning, resulting in improved educational outcomes. Protection Against Risky Behaviours: Research conducted by Resnick et al. (1997) has revealed that school connectedness serves as the strongest protective factor for both boys and girls against engaging in risky behaviours. Adolescents who feel connected to their school are less likely to indulge in substance use, experience school absenteeism, engage in early sexual initiation, resort to violence, or face a higher risk of unintentional injury. By fostering a sense of belonging and support, schools can significantly reduce the likelihood of students engaging in harmful behaviours. Emotional Well-being and Mental Health: In the study by Resnick et al. (1997), school connectedness emerged as the second most critical protective factor against emotional distress, disordered eating, and suicidal ideation and attempts. When students feel a strong sense of connection to their school community, they experience lower levels of emotional turmoil and are less susceptible to mental health challenges. A supportive school environment can provide a buffer against feelings of isolation and promote emotional resilience.
School connectedness is a dynamic process that can be influenced and strengthened by various factors within the school community. By understanding and nurturing these factors, educators and administrators can create a supportive and inclusive environment that fosters strong connections between students and their school (CDC, 2009).
Co-Production of Knowledge with School Students
What is Co-Production of Knowledge?
Co-production of knowledge is a collaborative research process where academic researchers and community members, specifically students in this case, work together as equal partners to develop new insights. In educational settings, this strategy entails engaging students not just as participants but also as active contributors in the research process. A transition is necessary from conventional research paradigms, in which researchers often generate knowledge and then disseminate it. Co-production prioritises the integration of the community viewpoints and experiences to provide research findings that are more relevant and effective (Shea, 2024).
Shea (2024) provides a clear definition “I define the co-production of knowledge as a process of mutually articulating, refining, and amplifying valued knowledge and practices with community partners to strengthen learning environments locally and influence theory, teaching, and policy more broadly. Interrogating the ways in which we know, how knowledge is constructed, and by whom has implications for how we make choices about the future” (Shea, 2024, p. 1).
In our project, we collaborated with students from Year 7 to Year 10 in an independent school in Nottingham. This method allowed the students to actively participate in various stages of the research process. Students actively participated in shaping the research instrument, starting from answering the initial questionnaire and continuing with co-designing later iterations of it. This interaction not only enhanced the research process but also empowered students with ownership of the project, resulting in a final product that was more relatable and important to them.
Why is it Relevant for Education Research?
Strengthening Student Engagement through Co-Creation: Co-production enhances student engagement by actively including them in the development of tools and resources that will be utilised in their educational setting. This cooperative method fosters a sense of responsibility among students, empowering them to actively participate in the research process and observe the impact of their contributions. Active participation in research not only increases the significance of the study results but also has a beneficial influence on students’ perception of their roles within the school community. Through active engagement in the co-creation process, students have a crucial role in moulding their educational experience, which can significantly impact their level of involvement and participation in future school activities (Fletcher-Watson et al., 2021).
Iterative Learning and Collaboration: The iterative aspect of the project, in which students were engaged in the process of developing the questionnaire through multiple stages, highlights the efficacy of co-production in educational research. This approach is consistent with Pellicano et al.'s (2014) focus on participatory approaches, which promote ongoing engagement with participants to improve both the research process and the results. The iterative procedure enhanced the research instrument's quality by making it more pertinent to the students’ experiences, so enriching their learning. According to Fletcher-Watson et al. (2021), students were able to enhance their critical thinking skills by participating in workshops, reviewing video content, and collaborating in pairs to improve specific items. The authors emphasise the importance of inclusive research practices that empower participants by actively involving them in the process. The collaborative method facilitated significant contacts between students and the research team, demonstrating the co-production process as a potent instrument for generating more efficient and contextually appropriate research.
Challenges in Co-Production with School Students
Co-production with students, while valuable, comes with its own set of challenges. One of the primary obstacles was managing the logistics within a busy school environment. Teachers often have limited time to accommodate external research activities, which can make scheduling difficult. Furthermore, maintaining student engagement throughout the iterative process required careful consideration of how to make the activities relevant and accessible to them.
Another challenge in co-production is ensuring that students’ contributions are genuinely valued. Within the project, this was addressed by actively involving students in the redesign of the questionnaire and ensuring their feedback was incorporated into the final version. However, maintaining this balance requires ongoing dialogue and flexibility to adapt to the needs and insights of the students.
Co-production of knowledge with school students, offers a powerful approach to educational research. It enhances the abilities of students and generates research results that are both pertinent and influential. Through involving students in the collaborative creation of research instruments, we successfully crafted a questionnaire that is both more relatable and efficient. This approach also fostered a stronger sense of ownership and connection among the students towards their school community. Although co-production has problems related to managing school logistics and guaranteeing authentic engagement, the advantages of this approach outweigh the disadvantages, making it a desirable method for both educational scholars and practitioners.
Methodology
The main objective of the present study is to enhance the assessment of school connectedness. The research was segmented into six distinct sections. Initially, it entails the application of a recognised instrument referred to as the Psychological Sense of School Membership (PSSM) scale (Goodenow, 1993). Second, it involves gathering students’ perspectives on the instrument, particularly from a semantic perspective. Third, we used the results of the reliability assessments and factorial analysis from the survey with the data supplied by the students to develop an innovative measurement instrument. Fourth, we organised a workshop in partnership with the students to assess the newly designed instrument using a respondent-centred method. Fifth, a new and redesigned instrument was developed; sixth, and ultimately, the instrument was tested in two secondary schools.
First Stage: Psychological Sense of School Membership (PSSM) Scale
In 1993, Carol Goodenow developed the Psychological Sense of School Membership (PSSM) scale. The goal was to investigate how students’ perceived belonging or psychological membership in the school environment. She considered that a student's success not only depends on individual skills, but also on contextual factors, such as the quality of social relationships (Goodenow, 1993).
Positives outcomes of the PSSM scale as a measure of students’ sense of belonging has been associated with improved academic performance, higher motivation, and enhanced overall well-being. One of the advantages of this instrument is that it has been developed specifically for adolescent students. The significance of belonging, social support, and acceptance becomes particularly notable in adolescence, especially in early adolescence when individuals start to contemplate their identity, desired affiliations, and future aspirations (Goodenow, 1993).
The survey comprises a total of eighteen items, which are assessed using a five-point Likert scale (not at all true, partly true, not sure, almost completely true, and completely true).
Various tests were conducted on the scale, and the reliability indicator Cronbach's alpha was reported to range from 0.817 to 0.875 -for the English version-, which is considered acceptable. The validation procedures employed to compare groups revealed that, as hypothesised, girls had a greater sense of membership or belonging in comparison to boys (Goodenow, 1993).
In the thirty years since its publication the PSSM has been used by researchers in a variety of projects. Many have used it in its original form with adolescents, whilst others have applied it in a primary (Castro-Kemp et al., 2020) and cross cultural context (Wagle et al., 2018), or with university students. In addition, Hagborg (1998) developed a ‘brief’ version of the survey by removing two of the positively worded items and all five of the negatively worded items based on their earlier analysis of the factors underlying the scale, which they concluded had made the results difficult to interpret (1994). In the published research to date, the PSSM has been conducted and analysed by researchers, possibly given the need to score the negative as well as positive responses to establish a final score.
For the research reported here it was decided to trial the measure in one small all age school, in order to have the opportunity of surveying all students in the secondary age range using a participatory research approach. Ethical approval was received from the School of Education Ethics Committee of the University of Nottingham Research Ethics Committee. The parents of all students were sent an information sheet and consent form via the school to introduce the research and to ask for permission to include their child in the project. All students were also given an information sheet, which we discussed with them, before they were asked to sign a consent form. Only one pupil decided they did not want to participate in the research.
In a pilot, a set of 15 items was administered to Year 9 students, whereas the entire set of 18 items was administered to students in Years 7, 8, and 10. The surveys were administered with the assistance of teachers, and the questionnaire was completed manually. All the students present in the classroom were collaborative and responded to the survey. The total number of students that responded to the survey was 92.
Second Stage: Students’ Perspectives
The succeeding phase of the research focuses on the perspectives of the student co-researchers. Year 9 students who completed the survey were asked if anyone would like to volunteer to be a co-researcher to help develop a new questionnaire to measure school connectedness. Ten students volunteered and after data analysis, were asked to attend a session where initial findings from their year group were presented. The primary objective was to get their interpretations of the questions in relation to their own context and circumstances.
Within this setting, some items were perceived as having ambiguous interpretations and some items received positive feedback. Table 1 shows a synthesis of students’ views on each item.
Students’ Semantic Assessment.
Internal Reliability.
Cronbach Alpha.
(*) This table includes data from Year 7, 8 and 10.
The absence of specificity in the items is a significant contributor to the presence of ambiguity. For instance, the statements “Most teachers at the school are interested in me” and “Teachers here are not interested in people like me” fail to specify the aspect or aspect(s) in which teachers may display interest towards the student. The statements can be approached from different perspectives; academic, mental health, physical health, and family dynamics, among others. The students felt it was important to be clear about what teachers might be interested in about them.
Statements such as “Other students in this school take my opinion seriously.”, and “I am treated with as much respect as other students.”, can produce different interpretations for different students, hence specificity in the statement is required for an unambiguous interpretation. The student co-researchers found it difficult to project what other students might be thinking or how they might behave in order to compare themselves.
Regarding “Sometimes I feel as if I don’t belong here.” This remark demonstrates a lack of consideration for the overall context, and students’ responses to the survey may vary based on their subjective feelings on the day they are providing their answers. The student co-researchers discussed this point at length and concluded that the answer would be influenced by both context and time, particularly in the life of an adolescent and their often volatile friendships.
Concerning “I am included in lots of activities at the school.” The statement exhibits ambiguity due to the presence of multiple activities inside a school setting, some of which may lack appeal for certain pupils, such as sports activities. The students felt this question implied they were passive and that they did not have choice in the activities they participated in, rather than their experience of choosing additional activities.
Finally, regarding “I feel very different from most other students here” was not deemed a “good question” because its meaning might be taken in a variety of ways depending on who is reading it. Adolescents found it difficult to know how other students might be feeling. Again, the ways in which students might feel different are many and varied and will be influenced by their context and relationships.
Third Stage: Integrating Students’ Perspectives and Validity and Reliability Measures
Consideration of reliability emerges as a crucial factor in the research of psychological structures. For this reason, precise methods of measuring must be employed. Internal consistency reliability, which is a one-time assessment, was used for this research in the form of Cronbach's alpha, which considers the number of items in the measure as well as the average of the correlations among them (Cozby, 2011).
The table presented below (Table 2) displays the results of internal consistency reliability as determined by Cronbach's alpha. It is computed since the quantity of items applied varied every time.
A Cronbach's alpha coefficient of 0.601 suggests that the internal consistency of the measure is relatively weak. Cronbach's alpha is a statistical measure that falls within the range of 0 to 1, good reliability will be represented with alpha values from 0.75 up to 1 (Coolican, 2019).
Our analysis focuses on analysing the instrument rather than drawing generalizable inferences about the population. We considered this technique to evaluate problematic items. Items 3, 6, 9, and 16 could be removed to enhance the instrument's reliability (Table 3). However, further analysis will be done on the different items.
Given our primary objective of enhancing the measurement of school connectedness, additional analyses like the factorial analysis was performed. Cronbach's alpha is a statistical metric used to assess the internal consistency of a scale or questionnaire. However, it does not offer insights into the underlying structure or dimensions of the scale. Factor analysis is a statistical technique that aids in the identification of item groupings and the determination of whether they load onto separate factors. The generated information retains significant importance in understanding the construct validity of the scale.
Exploratory Factor Analysis
Factor analysis is a statistical technique which helps in the construction and revision of psychometric scales. It is important to understand the structure of the scale, since it provides factor loadings that indicate the magnitude as well as the direction of the association between each item and the latent factor. This information can provide guidance for making judgements regarding the retention or removal of items to enhance the reliability of the scale. For example, numerous factors might lead to rethink the scale's conceptualization or removing items that are inconsistent with the intended construct (Coolican, 2019).
Conducting an exploratory factor analysis might be difficult when the sample size is limited. According to a well-established guideline, there should be a minimum of 10 cases for every 1 item (Lloret et al., 2017). In our specific situation, this means that we would require a total of 180 cases, given that we have 18 items. However, Exploratory Factor Analysis (EFA) is inherently exploratory. In situations when these methods may not be viable due to constraints on sample size, EFA can be utilised as an exploratory instrument to detect probable factor structures (Tabachnick & Fidell, 2013).
Before proceeding with a factorial analysis, Kaiser-Meyer-Olkin (KMO) is calculated. This is an index used to assess the adequacy of the data for conducting factor analysis. It evaluates the degree of common variance among variables and indicates whether factor analysis is an appropriate technique for the dataset. The KMO value ranges from 0 to 1, and higher values generally suggest that the data is more suitable for factor analysis. The KMO value for our dataset is 0.757 considered to be satisfactory to proceed with factor analysis (Lloret et al., 2017; Coolican, 2019) (Table 4).
The subsequent phase will involve the extraction of factors, aiming to elucidate a significant portion of the variance. The guideline is to preserve all the elements that possess eigenvalues exceeding 1 (see Table 5). To complement the analysis, the scree plot is employed to graphically determine the number of components to maintain depending on their significance. This implies choosing all the components that are positioned above the ‘elbow’ in the plot. These factors will account for significant amounts of the overall variance or interrelationships among them (see Fig. 1) (Coolican, 2019).
Scree plot.
KMO and Barlett's Test.
Total Variance Explained.
Components and Factor Loading.
Items Decision.
Survey Assessed in Stage Four.
New Instrument.
KMO and Barlett's Test Combined Sample.
Total Variance Explained Combined Sample.
Components and Factor Loading Combined Sample.
Both approaches have been complemented, leading us to choose four factors. These factors account for the 60.67% or variance of the data. Additional analysis, such as parallel analysis, will be conducted after piloting the new instrument with a suitable sample size.
Keeping in mind that our scope is to analyse the instrument, the next step is to investigate the factor loadings. Factor loading will be considered accordingly with the sample size. Our sample has 91 cases. Stevens (2002) suggests that for a sample size of 50, a loading of 0.722 is significant, and for a sample size of 100, the loading should be more than 0.512. We shall maintain all items with a factor loading of 0.6, whether positive or negative.
Two oblique rotation methods, Promax and Oblimin, were considered to allow for potential factor correlations. Promax was selected as the primary rotation method due to its computational efficiency and suitability for handling complex structures. Promax successfully converged, yielding a theoretically interpretable four-factor solution, while Oblimin did not converge within the default iteration limit and suggested a less stable structure. Given these considerations, Promax was deemed the most appropriate choice for this analysis.
Out of the 18 questions, six have factor loadings over 0.6 and are spread across four components (Table 6). This finding indicates that the survey's structure is inadequate and requires revision. After considering the students’ feedback in the second stage of the research, conducting Cronbach's alpha analysis, exploratory factor analysis, and reviewing the concept of school connectedness, decisions were reached for each item as shown in Table 7.
The next step was to present our conclusion to our co-researchers.
Fourth Stage: Assessing a new Instrument
The fourth stage involves evaluating the newly developed instrument with the input of the student co-researchers who have been engaged in the project since it started. There were two approaches to accomplish this task: a ‘user-centred design’ and ‘cognitive interviewing’.
User Centred Design
This strategy involves comprehending and fulfilling the requirements of participants throughout their survey experience. Wilson (2023), from the Office for National Statistics in the UK, believes “involving respondents in design is the secret to a successful survey” (SRA Newsletter, 2023, p. 4). Accordingly with the guidance from the UK government, key considerations include understanding respondents; gathering insights from their context; understand how respondents conceptualize the survey topics; ensure readability and use language familiar to respondents; and questions should be self-explanatory, minimising the complexity of answering each question.
Cognitive Interview
The cognitive interview, as implemented in the survey methodologies area, aims to assess, and enhance self-report survey questions, measuring tools, research consent forms, and other textual materials. The method essentially embodies a type of qualitative investigation. The main goal of the cognitive interview is to comprehend the internal mechanisms that underlie the process of responding to surveys. Equally significant is the contribution towards the establishment of effective procedures for formulating survey inquiries that are easily comprehensible and provide few response inaccuracies (Willis, 2015). Engaging adolescents in the questionnaire's response process can pose issues if the survey is not relevant to them or not properly understood.
Using the principles of cognitive interviewing we aimed to assess the students’ comprehension of the questionnaire. To do this, we put together an activity that involved gathering the students at the University, showing them videos about school connectedness, engaging in a discussion about their perspectives on school connectedness, and then splitting the group of ten students into five pairs to individually assess specific questions from the questionnaire. Each couple assessed a minimum of two questions, with a maximum limit of three questions per couple. The students were accompanied by their Deputy Head Teacher who encouraged them to consider their reactions to the questions and to clarify their thinking about required changes. Each pair presented their initial thoughts about the questions they were reviewing and then led a group discussion about suitability of the wording and any suggested changes.
Each item was accompanied with two questions, prompting students to respond with either ‘Yes’ or ‘No’, with a follow-up question asking what potential improvements can be made to the item. Table 8 below summarises the specific outcomes.
Initiating a dialogue with the children regarding the concept of school connectedness and its personal significance proved beneficial in gaining a comprehensive understanding of their perspectives. The students’ suggestions for redefining the last three questions are both critical and constructively appreciated.
Students proposed redirecting the focus of item number 9. Shifting the focus from “people here know I can do good work” to emphasize “effort and doing your best.” New proposed statements include: “people here know I will do the best I can” or “I am recognised for my efforts”.
Item number 10 initiated a discussion on the concept of “being proud” of belonging to the school, but the students were more concerned with “enjoying being at school” or feeling “happy to be” there. Therefore, it was recommended to update the item.
Lastly, question number 11, was qualified as “hard to understand” and “needs more specificity": is the question about what I do; the way I do it; how I act; my looks; or about my personality. As such this item required revision.
The suggested rephrasing of questions was deliberated in the group and various possible changes were written down and practised to work out whether they captured the intended meaning within the survey. At this stage we were aiming to improve clarity of questions as interpreted with this group of co-researchers, which would be trialled in subsequent phases of the research.
It is important to note that questions 10 and 11 were not reviewed by Year 9 students in the second phase, as they were included in the second version of the survey.
Finally, note that to improve the internal validity of the initial measure, several items were deliberately created to elicit responses from both positive and negative viewpoints. This approach sought to ensure consistency in students’ answers, thereby serving as a safeguard against response biases, including acceptance and social desirability. The measure was designed to validate the reliability of students’ self-reported attitudes or experiences by framing similar questions with opposing attitudes. As we refined the measure, certain items were eliminated to enhance the instrument's efficiency and concentrate on the core constructs pertinent to our research objectives. This revision has enhanced the questionnaire's clarity, but it may have diminished certain inherent mechanisms for validating response consistency. We recognise this change and understand the necessity of interpreting results considering this adjustment.
Fifth Stage: new Instrument
During the last stage, a renewed scale was created which required further testing. To conduct a factorial analysis, it is necessary to have an adequate sample size, typically consisting of 10 participants per item as stated in the technical advice (Black, 1999). The newly suggested instrument is presented in Table 9.
Sixth Stage: Testing the new Instrument
Sample
Once we had agreed the new instrument with the student co-researchers the next step was to conduct a thorough validation of the scale. To achieve this objective, we worked with two institutions in Nottingham. We received 46 responses from school 1 (the original participants) from years 8, 9, 10, and 11 and 86 responses from school 2, including years 9, 10, and 11.
Reliability
To assess the internal consistency of the school connectedness scale, Cronbach's alpha was calculated separately for each school as well as for the combined sample. Cronbach's alpha is a measure of internal consistency, indicating how well the items within a scale are correlated and thus how reliably they measure a cohesive construct.
When the data from both schools were combined, Cronbach's alpha for the overall sample was 0.885. This high alpha indicates that the scale consistently measures a cohesive construct of belonging across both school environments, further supporting its generalizability.
Exploratory Factor Analysis
An Exploratory Factor Analysis (EFA) was conducted to examine the underlying structure of the belonging scale across two schools as well as for the combined sample. Principal Component Analysis (PCA) was employed with an Oblimin rotation to account for potential correlations among factors. Missing values were handled using mean substitution. To identify the underlying factors the Exploratory Factor Analysis (EFA) was conducted using Principal Axis Factoring. After careful consideration, Oblimin rotation was chosen as the rotation method for this analysis.
Oblimin rotation is an oblique rotation, meaning it allows the factors to be correlated with each other. This choice was guided by the theoretical expectation that different aspects of belonging, such as recognition, respect, and social engagement, may naturally overlap and influence each other. By allowing for correlations among factors, Oblimin rotation provides a more realistic view of these interrelated constructs (Fabrigar et al., 1999; Costello & Osborne, 2005). Researchers often select oblique rotations, like Oblimin, in psychological and social science research because constructs in these fields are rarely entirely independent (Field, 2018).
To ensure the appropriateness of factor analysis, the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy and Bartlett's test of sphericity were evaluated for the Combined Sample. The KMO measure was 0.870, and Bartlett's test was significant, χ2(45) = 572.828, p < .001, further confirming the suitability of the data for factor analysis across the combined dataset. See Table 10 and Table 11.
Ultimately, for the complete sample, as only a single component was extracted, no rotation was implemented. All components exhibited substantial loadings on this singular factor, with values ranging from 0.498 to 0.805. This outcome suggests that, broadly, the notion of belonging can be perceived as a unified, singular concept across schools (Table 12).
Expanded Interpretation of the Four-Factor vs. One-Factor Structure
When examining each school separately, the EFA suggested a multi-factor structure (four factors), whereas the combined dataset produced a single-factor solution. This divergence is theoretically meaningful and has practical implications for how the belonging construct operates in different school contexts.
Theoretically, the four-factor pattern in individual schools indicates that belonging may manifest as a multidimensional experience, with distinct but related domains—for example:
Recognition/validation (e.g., being noticed for strengths), Respectful treatment, Peer relationships/friendliness, Engagement/participation.
In these schools, students may differentiate between these facets in their psychological experience. This aligns with research suggesting that belonging is shaped locally by school culture, peer norms, and teacher–student interactions, which can emphasise some dimensions more strongly than others. In other words, the structure of belonging is context-sensitive, and different school environments can amplify or suppress certain aspects of the construct.
In contrast, the single-factor structure in the combined sample suggests that when all students and both settings are analysed together, the items cohere around a general, overarching sense of school belonging. This implies that, despite contextual nuances, there is a core latent dimension shared across schools that captures the fundamental psychological experience of “feeling part of the school community.” The strong and relatively homogeneous loadings (0.498–0.805) support this interpretation.
Practically, the four-factor vs. one-factor difference indicates that:
Measurement invariance across contexts may be limited. The belonging scale behaves differently depending on school context, which suggests that sub-dimensions may be more salient in some environments. Using a single factor for reporting is appropriate at the aggregate level, because it captures the general sense of belonging across school students. Within individual schools, however, recognising the multidimensional pattern can help practitioners identify more specific areas for improvement—for instance, whether a particular school should prioritise strengthening recognition practices, peer climate, or opportunities for participation. These findings also reinforce the idea that belonging is a dynamic, culturally mediated construct, and that scale adaptations may perform differently depending on local school characteristics.
Therefore, while the combined sample supports interpreting belonging as a unidimensional construct, the school-level analyses reveal meaningful internal differentiation that is masked when data are pooled. This is consistent with literature showing that social–emotional constructs often appear differentiated within specific contexts and more global across diverse samples.
Discussion
This research focused on adapting the PMMS scale, initially created by Carol Goodenow, for application within UK educational environments. We reviewed previous adaptations of the scale, which have been made to enhance the ease of use and/or the applicability to different age cohorts in countries other than the USA. In all the previous research identified the scale was used by researchers to conduct research on these populations of students and suggested changes were made according to their analyses. We decided to take a different approach in order to develop a set of questions that were relevant to adolescents in 2025 and that could easily be employed by teachers to test school belonging on a regular basis. Therefore, in order to enhance the relevance of this scale in measuring students’ sense of school belonging, knowledge co-production was employed, actively involving students in the refinement process. Involving students in research, especially in creating instruments to assess their own experiences, is essential. Student perspectives offer distinct insights into the complexities of school life that may be neglected by researchers. Incorporating their feedback ensured that the scale reflected students’ lived experiences, effectively capturing aspects of connectedness that hold personal significance for them.
Students facilitated revisions to item wording, phrasing, and cultural references, enhancing the instrument's relatability and contextual appropriateness. This collaborative process signifies a significant transition in educational research, emphasising the role of students as co-constructors of knowledge. The developed instrument, shaped by student perspectives, is likely to provide more precise and genuine insights into school connectedness in various educational settings.
The results from the Exploratory Factor Analysis (EFA) provide an initial assessment of the instrument's validity and its potential sensitivity to context. The combined sample analysis indicated a single-factor structure, suggesting that school connectedness may be perceived as a unified construct across a broader population.
The findings highlight the necessity of enhancing measurement tools in education, especially for constructs such as school connectedness that are integral to students’ daily experiences. Feedback from students, obtained through knowledge co-production, enhances the construct validity of the scale and may improve its overall reliability and relevance in various contexts. Student perspectives provide important insights into the aspects of connectedness that are most significant to them, highlighting the potential for more precise and meaningful evaluations when students participate in the creation of measurement instruments.
This study's findings indicate that the adapted PMMS scale effectively captures school connectedness in a context-sensitive manner, demonstrating sufficient flexibility for application across various schools. The observed single-factor structure in the combined sample validates its application as a general measure.
Limitations
While this co-productive approach has notable strengths, it is important to acknowledge several limitations. The small sample size for individual schools limited our capacity to statistically validate the observed contextual differences. The overall small sample size (N = 132) has to be taken into account when considering the robustness of the EFA findings. Future research involving larger and more diverse samples may employ multi-group CFA to investigate measurement invariance across various school contexts, thereby enhancing understanding of the scale's responsiveness to environmental factors. It would also be valuable to employ a test test-retest methodology with a larger sample of students to enhance the reliability of the new scale.
Conclusion
The adaptation of the PMMS scale through a collaborative, student-centred approach has produced an instrument that is theoretically sound and practically applicable within the UK educational context. We have developed a measure that captures significant aspects of school connectedness as experienced by students by recognising them as contributors to the research process. The single-factor structure is adequate for general application; however, the findings indicate that the scale is responsive to contextual variations, potentially enhancing its utility in various school environments. This study demonstrates the significance of student engagement in educational measurement and establishes a basis for the advancement of tools that accurately represent students’ experiences of belonging and connectedness in their school communities.
Importantly, we have developed a ten-item survey that can be quickly and easily administered by teachers to evaluate the connectedness of their students and the effect of any interventions they might employ to improve their sense of belonging.
Footnotes
Acknowledgments
We had ten co-production partners from one of the schools in Nottingham, they were:
Isabella Ashmore Matilda Shelton-Bates Juno Bentley Lily-Mai Boswell Ewan Christopher James Hendy Max Hill Lily Noon Lawson Taylor
We would like to thank the two schools who supported the research and hope they benefitted from the school specific reports about their levels of school connectedness which we developed for them.
Ethical Approval and Informed Consent Statements
Ethics approval was given by the School of Education Ethics Committee of the University of Nottingham. All participants had written parental consent and were asked for their own written informed consent before taking part in any research.
Author Contribution(s)
Funding
The authors received no financial support for the research, authorship, and/or publication of this article.
Declaration of Conflicting Interests
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Data Availability Statement
The data has been shared with individual participating schools, but due to the small sample size and potential for identification of one of the schools we prefer not to share the data more widely.