Next Article in Journal
Teaching Methodologies of Gross Anatomy Education for Undergraduate Physiotherapy Students: An Updated Scoping Review
Next Article in Special Issue
Learning/Earning: Characteristics of Student Work and Its Impact on Academic Careers at a Regional Hungarian University
Previous Article in Journal
Application of Student-Centered Learning in Improving Teaching English as a Foreign Language Students’ 21st-Century Skills Performance
Previous Article in Special Issue
Mature Working Student Parents Navigating Multiple Roles: A Qualitative Analysis
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Can Social Identities Improve Working Students’ Academic and Social Outcomes? Lessons from Three Studies

by
Vladislav H. Grozev
1,* and
Matthew J. Easterbrook
2
1
Sheffield University Management School, University of Sheffield, Sheffield S10 1FL, UK
2
School of Psychology, University of Sussex, Brighton BN1 9QH, UK
*
Author to whom correspondence should be addressed.
Educ. Sci. 2024, 14(9), 939; https://doi.org/10.3390/educsci14090939
Submission received: 28 June 2024 / Revised: 20 August 2024 / Accepted: 21 August 2024 / Published: 27 August 2024
(This article belongs to the Special Issue Working Students in Higher Education)

Abstract

:
Previous research has linked working for pay while attending university with negative academic and health outcomes; yet, working students are often resilient when experiencing such adverse circumstances. This makes it crucial to explore potential psychological mechanisms that transform adverse experiences into sources of motivation and persistence for working students. We explore one mechanism—social identification—and its different foci—identifying as a student, employee, working student, or a student of one’s discipline of study—as potential predictors of important academic (academic self-efficacy, approaches to learning, and academic achievement) and social (status in society) outcomes in three cross-sectional studies. In Study 1, part-time working hours (but not identification processes) were associated with academic self-efficacy. In Study 2, discipline identification and part-time working hours were associated with using deep approaches to learning. In Study 3, student identification was associated with increased status in society. Overall, discipline identification may be solely linked to academic outcomes, but student identification should be explored further as a potential enhancer of social and graduate outcomes. We discuss additional mechanisms that can help to transform working students’ experiences through their social identities and suggest boundary conditions that can affect the link between these identities and important outcomes.

1. Introduction

The number of working students in paid employment (henceforth, working students) in higher education is increasing worldwide [1,2]. Working undergraduate students may encompass 40% or more of all undergraduate students in the UK [1], with similar or increased representation in Australia [3] and the USA [4]. This increase in the number of working students [5] has coincided with an increased interest in how they experience higher education [6], and scholars have placed particular focus on the relationships between working status and physical and mental health outcomes [7] as well as between working status and academic attainment [8]. Indeed, working students can experience increased tiredness [9] and disrupted sleep patterns [10], as well as increased levels of stress and anxiety [11] and depression [7]. These negative health consequences can also have knock-on effects for reducing working students’ levels of academic attainment [12], as working students exhibit higher levels of tardiness [13], miss more classes [14], and avoid attending campus altogether [15]. Being from a lower socioeconomic background can further compound these pressures on working students if they must work longer hours [16]. Overall, understanding the negative experiences associated with being a working student is important for universities and policymakers as these experiences can cause working students to prolong their studies [17] or to quit their education pursuits altogether [18].
However, negative consequences are only one side of the working student experience. A new wave of research demonstrates how they can transform their experiences to build resilience and maintain motivation for their studies [19,20,21]. Universities have also shown increased interest in providing structural support for working students to normalise their experience of higher education and to increase graduation rates [4,22], with one example being establishing work-integrated learning in Australia, which aims to enhance students’ employability while they are working a part-time job [23,24]. Together, these research streams highlight the importance of understanding working students holistically and identifying mechanisms for universities to help them transform their experiences with the aim of improving their academic, social, and graduate outcomes.
One way of helping working students to see themselves in a positive light and to unlock their resilience is by emphasising the different groups in which they feel that they participate meaningfully. Here, the concept of social identity—defined as ‘the part of the self-concept, which is derived from meaningful participation in a group, together with the emotional significance attached to that membership’ ([25], p. 3)—is helpful as it offers a mechanism through which experiences and connections with others can become integrated as valuable parts of the self-concept and consequently influence psychological processes. Specifically, if a working student participates in a group that provides them with a positive self-image and a sense of self-esteem, then they will identify with that group, adopt the group’s attitudes, behaviours, and norms [26] and be more likely to receive social support from fellow group members and to find that the group membership is psychologically satisfying [27]. The different groups that working students can identify with (being a student in general, being an employee, being a student of their own discipline, or being a working student) in different contexts could, therefore, provide a wide range of varied resources that could boost their resilience.
Working students in higher education balance their roles as students and employees [28]. Their transitory immersion into either position inherently makes their identification processes more complex; while non-working students or workers may only identify with those respective social categories, working students can choose to identify as a student, as an employee, or indeed, as a working student in different contexts and situations. All these groups can become sources of strength and resilience as identifying with either identity can be beneficial for working students in particular circumstances. For example, previous research has suggested that identifying as a working student (as opposed to identifying as simply a student) by drawing on their distinct experiences of working life can increase academic motivation [29] and elicit social support from other working students [30].
Below, we present three cross-sectional studies that explore whether the different foci of identification are associated with important positive academic and social outcomes in the present research. Because learning processes are intertwined with the social and personal dimensions of student life [31], the four different foci of identification can be associated with important academic and social outcomes (academic self-efficacy, student approaches to learning, academic achievement, and status in society), all of which have been previously linked with either commencing term-time employment or social identification processes.
We next present research that discusses why identifying with the four different foci can lead to positive distinctiveness for working students and then outline the potential links between those identities and academic and social outcomes in more detail. We then present our three cross-sectional studies and discuss their results. Finally, we contend that future research can embed working students into specific interventions that can transform students’ experiences through social identification and explore boundary conditions that can further impact their academic, social, and graduate employability outcomes.

1.1. Motivations for Identifying as a Student, Employee, Discipline of Study, and Working Student

To blend in with non-working students, working students can opt to identify as students [32] and minimise any differences between working students and the overarching student group. Identifying as a student has also been associated with increases in well-being for all students [33]. Because previous research has suggested that student identity may be a chronically salient identity for all students [34], in the current research, we explore whether this identity is associated with important academic (academic self-efficacy and academic achievement) and social (status in society) outcomes for working students.
Furthermore, working students may see commencing employment as a welcome sign of entering adulthood [29,35], which can make starting to work for pay a precursor to positive identity change [36]. Therefore, working students may also choose to adopt an employee identity—a form of social identification in which the individual feels a sense of belonging with the workplace, their colleagues, or the larger organisation [37]—as part of their self-concept. Working students may also choose to identify with other workers specifically so that they can receive on-the-job guidance or mentorship [38] or complain about management [39]. These motivations can make identifying as an employee important for working students, and we wanted to explore whether there are relationships between employee identification and important academic (academic self-efficacy, approaches to learning, and academic achievement) and social (status in society) outcomes.
When considering learning processes, an important (and very salient) social identity for students is identification with their specific discipline of study [40]. Extensive research has linked discipline identification to increases in using adaptive deep approaches to learning, which can positively influence academic performance [40,41,42,43,44,45], making discipline identification an important social identity for students in higher education. However, to the best of our knowledge, to date, there has been no study that has explored the link between term-time employment, discipline identification, and important academic outcomes. We contend that this identity can be an important source of strength and resilience for working students because students in higher education can study their preferred discipline that represents their future profession [43]. While students who work in a job that is related to their studies [46] can enhance this identity, this may not be a viable option for working students who often work due to sheer necessity [16]. For these reasons, we wanted to explore whether this identity is associated with using deeper approaches to learning and academic achievement specifically for working students.
Finally, our previous research has found that considering important aspects of being a working student (thinking of oneself as being motivated, disciplined, and acquiring skills, as well as being hardworking and organised) can foster identification as a working student [19]. Additionally, when working students have frictional relations with colleagues or experience negative comparisons to non-working students, they can adopt the working student identity to maintain their positive self-view [30]. This research suggests that identifying as a working student can be an important mechanism in transforming the experiences of working students to foster resilience, which is why we wanted to explore whether this identity is associated with academic achievement and status in society in the current research.
These different motivations suggest that working students could hold the identity of an employee, a student, a student in their own discipline of study, and a working student. To explore whether these identities are associated with important academic and social outcomes, we next outline these outcomes in more detail and simultaneously present previous evidence that links them to commencing employment or the identities of students in general.

1.2. Academic and Social Outcomes

Bandura [47] describes general self-efficacy as ‘the belief in one’s capabilities to organise and execute courses of action required to produce given attainments’. Therefore, academic self-efficacy refers to the self-serving belief in one’s potential to attain a certain level of academic achievement and is a belief that ‘operates within sociocultural influences’ [48]. Academic self-efficacy has also been associated with positive increases in academic achievement [49,50].
Huie et al. [51] have reported a small negative correlation between the weekly hours spent in paid employment and academic self-efficacy (r = −.12), and Pennington et al. [52] have shown a positive association between student identification and academic self-efficacy for students in general. Because no studies have examined the link between academic self-efficacy and identification processes for working students specifically, we explored whether student identification and employee identification exhibit significant associations with academic self-efficacy in Study 1.
Because academic self-efficacy beliefs may represent stable beliefs in one’s ability to deal with academic tasks [53], we wanted to explore whether identification processes may also influence how working students approach the way they learn more dynamically. Therefore, we explored whether discipline identification or employee identification is associated with choosing approaches to learning [54] and academic achievement in Study 2. The two approaches to learning (deep and surface) consider how the learner uses the information they obtain in response to a given academic task [55]. The deep approach to learning signals an intrinsic desire in the learner to consume information to improve their own understanding of the material [56]. Students who use deep approaches to learning carefully consider the given information, question its validity, and discuss it with interested others to make tenuous links with preexisting knowledge [57]. Students who use surface approaches to learning often pursue more extrinsic rewards (e.g., a better grade or a better job position), use rote memorisation, exhibit a lack of interest in alternative explanations, and defend the validity of their preferred solution [58]. Students may use either approach to learning in different situations [54,59].
Discipline identification has been linked to increases in using deep approaches to learning, and using deep approaches to learning has been subsequently associated with increased objective academic achievement [40,41,42,43,44,45]; therefore, fostering discipline identification in working students can lead them to use deep approaches to learning, which might be especially important for those who are struggling with their academic performance [8,12], or to use surface approaches to learning [17]. However, to date, no studies have examined the relationship between term-time employment, discipline identification, and using either approach to learning. Additionally, working students who identify strongly as employees may see studying as beneficial only to upskill or to find a different job, which can prompt them to use surface approaches to learning. For these reasons, we wanted to explore whether there are significant relationships between working students’ discipline and employee identification and their use of different approaches to learning in Study 2.
There has been mixed evidence for the effect of commencing employment on students’ academic achievement as some research has indicated a negative effect (e.g., [8,12,60,61]), while other evidence suggests that working part-time can be beneficial [62,63,64]. Thus, illuminating important socio-psychological factors that can help working students maintain or increase their academic achievement is important, and Wilkins et al. [65] have shown that student identification is positively associated with the academic achievement of students in general. This led us to explore whether the different foci of identification are associated with the academic achievement of working students in Studies 2 and 3.
In terms of social outcomes, working students in Blake and Worsdale [66] indicated that the main reason for them to commence employment was to increase their status in society by accumulating more financial and cultural capital. Creed et al. [67] added credence to this argument by suggesting that job precariousness is associated with working students having lower social status. Grozev and Easterbrook [19] suggested that identifying as a working student via certain positive aspects of their experience (e.g., seeing themselves as hardworking, disciplined, and organised) can make working students more resilient to intergroup comparisons and help them gain support from other working students. For these reasons, we tested whether adopting the working student identity (and the student or employee identities) would be associated with increases in their social status (i.e., seeing themselves more positively) in Study 3.

1.3. The Present Study

We present three cross-sectional studies that link the different foci of identification with important academic and social outcomes for working students. More specifically, in Study 1 we explore whether student identification and employee identification are associated with working students’ levels of academic self-efficacy. However, because self-efficacy beliefs might be more stable [53], we wanted to explore whether identification processes are associated with working students choosing a particular approach to studying, which represents a more dynamic choice. Therefore, in Study 2, we examine whether discipline identification and employee identification are associated with using deep or surface approaches to learning [58] and subjective academic achievement. However, if the main reason behind working students attending university (and undertaking employment while doing so) is to improve their career choices and increase their status in society [68], then it is important to explore whether their different identities are associated with their perception of their general status in society. Therefore, in Study 3, we explore whether identifying as a student, employee, or working student is associated with subjective academic achievement and status in society.

2. Materials and Methods

2.1. Participants

We received ethical approval for all studies by the second author’s institution, which is where we collected all the data. For each study, one online questionnaire was used for data collection. We collected the data for Study 1 in 2016–2017, the data for Study 2 in 2017–2018, and the data for Study 3 in 2020–2021. The gap in data collection between Studies 2 and 3 helped us to consider the role of the working student identity, as illustrated by [30]. We recruited participants for each study by creating an online link, which we included on an online study participation system (SONA) and on social media. We also distributed the link in the form of a QR code in classrooms and the library on campus. We further boosted recruitment by asking lecturers to give the online link to their students in seminars and lectures. All participants could enter prize draws for four prizes of £25 (Studies 1 and 2) or four prizes of £50 (Study 3). Ninety-seven working students took part in Study 1, of which 40 were male and 57 were female. Seventy working students took part in Study 2, of which 15 were male and 55 were female. Two hundred and twenty-one working students took part in Study 3, of which 30 were male, 184 were female, and seven identified as another gender. We present other demographic details for the three samples in Table 1.

2.2. Materials

We present descriptive statistics and zero-order correlations for all variables in the three studies in Table 1. We note that the three questionnaires measured only cross-sectional data using self-report measures, which could reduce the veracity of findings. However, in line with Pike et al. [69], we expect that respondents can easily recall key objective data, such as weekly working hours or academic performance. We measured the strength of identification using Likert-type scales ranging from [1] Strongly Disagree to [7] Strongly Agree, with 7 indicating maximum strength of identification.

2.2.1. Strength of Identification Measures

We measured student social identification in Study 1 using four modified items from the scale developed by Doosje et al. [70] (e.g., ‘I feel strong ties with other University of Sussex students’). The scale had a good internal consistency in this sample, as measured by Cronbach’s alpha (a = 0.82). We then computed an average score of student social identity for each participant.
We measured employee identification in Studies 1 and 2 using the same scale with modifications to disentangle this identity from the student identity (e.g., ‘I identify with other employees of the organisation I am currently employed in’). The scale had a good internal consistency in both studies, as measured by Cronbach’s alpha (Study 1: a = 0.78 and Study 2: a = 0.80). We computed an average score of employee identity for each participant in both studies.
We measured discipline identification in Study 2 with a 5-item measure of discipline identification adopted from Smyth et al. [43]. One example question ‘I would rather NOT tell other people that I am a student in my field of study’ was reverse-scored. The scale had adequate internal reliability (a = 0.82).
In Study 3, we opted to assess student, employee, and working student identification using a single item for each construct, adapted from Postmes et al. [71]. An example item was ‘I identify with working students’. We chose this method of assessing the strength of identification in this study because the items formed part of a larger project and we wanted to reduce any cognitive load experienced by working students who completed the survey.

2.2.2. Academic and Social Outcomes

We measured academic self-efficacy in Study 1 using four items from Marsh et al.’s [72] scale (e.g., ‘I’m certain I can understand the most difficult material presented in texts’). The factor had a good internal consistency in this study, as measured by Cronbach’s alpha (a = 0.81), and we computed an average score for each participant. Possible answers ranged from [1] Almost Never to [4] Always, with 4 indicating maximum academic self-efficacy.
We examined deep and surface approaches to learning in Study 2 using the 20-item Revised Two-Factor Study Process Questionnaire (R-SPQ-2F; 58). This is a shortened version of the SPQ and is particularly useful for quick administration. Ten items each were used to measure both approaches to learning, and illustrative items include ‘I find that at times studying gives me a feeling of deep personal satisfaction’ and ‘My aim is to pass the course while doing as little work as possible’ for deep and surface approaches, respectively. We summed up the scores on both pairs of ten items to create composite scores of a deep approach (a = 0.81) and a surface approach (a = 0.79) to learning. Possible answers ranged from [1] Strongly Disagree to [5] Strongly Agree, with 5 indicating a maximum deep or surface approach to learning.
We asked students about their subjective academic performance in Studies 2 and 3 using one item: ‘What was your average module result in the autumn term?’ Participants answered this question by dragging a slider that ranged from [0] to [100], with 100 indicating a perfect average module result in the autumn term. We preferred to measure the termly result using the method by Pike et al. [69], who maintained that this result should be easily recalled by the respondents, and because students may have taken holidays to work on particular essays or examinations, which suggests that the effect of work may not influence a more particular assignment.
We asked working students about their general status in society in Study 3 using an adapted pictorial ladder measure from Adler et al. [73], which scholars often use to identify participants’ subjective socioeconomic status (e.g., [74]). In the ladder measure, students who select a higher rung of the ladder indicate that they have a higher status in society, and participants could select from [1] (zero status in society) to [10] (utmost status in society).

2.3. Analysis

To assess the exploratory associations between constructs in the different studies, we created path analyses using RStudio and the lavaan package (lavaan v. 0.6-7 [75]). We included age, gender, and the number of working hours per week as control variables in all models. Because we had small sample sizes for path analyses, we used bootstrapping with 10,000 bootstrap iterations [76] to estimate the parameters and their associated standard errors in the models. We used the strength of identification measures as predictors of academic and social outcomes experienced by working students in higher education; however, our cross-sectional data did not rule out the possibility that any increases in the academic and social correlates could lead to increases in the strength of identification or that these effects are bidirectional.

3. Results

3.1. Study 1

In Study 1, we assessed whether the student identity and the employee identity are associated with working students’ levels of academic self-efficacy. We found that working hours were marginally significantly associated with academic self-efficacy (b = 0.18, p = 0.08). However, social identities were not significantly associated with academic self-efficacy. These results suggest that any increases in academic self-efficacy for working students may occur via different socio-psychological processes rather than identifying as a student or as an employee. The model explained 8% of the variance in academic self-efficacy scores.

3.2. Study 2

We conducted Study 2 to understand whether discipline identification and employee identification were associated with approaches to learning and academic achievement. We constructed a model wherein deep and surface approaches to learning predicted academic achievement as an outcome variable. Discipline identification and employee identification predicted these two approaches to learning in this model.
Deep approaches to learning were significantly associated with academic achievement (b = 0.35, p = 0.002). Discipline identification was significantly associated with using a deep approach to learning (b = 0.41, p = 0.001). These effects suggest that thinking about oneself in terms of one’s discipline can lead to using a deep approach to learning more, which can in turn aid working students’ academic achievement.
Weekly working hours were also significantly associated with using a deep approach to learning (b = 0.32, p = 0.01). Indeed, although working more hours takes away opportunities to study, working more hours may also make students feel grateful for their education and enhance their intrinsic motivation to improve their own understanding of the material. The model explained 29.1% of the variance in academic achievement scores, 11.8% of the variance in surface approaches to learning scores, and 33.2% of the variance in deep approaches to learning scores.

3.3. Study 3

In Study 3, we aimed to explore whether identifying as a student, an employee, and a working student was associated with increases in academic achievement and status in society. Our results suggest that none of the focal constructs were significantly associated with academic achievement, which is in line with the results of Study 2. This suggests that identification processes may exert a positive influence on the ways in which working students approach their studies but not directly on their results.
Student identification (b = 0.16, p = 0.05) was significantly associated with status-in-society scores. This suggests that identifying strictly with other students (rather than specifically with working students) could increase working students’ own societal perceptions and indicates that identifying as a working student could help them see themselves in a more positive light. The model explained 4.8% of the variance in academic achievement scores and 12.5% of the variance in status-in-society scores.

4. Discussion

Our findings suggest that student identification is associated with increased status in society for working students and that their discipline identification is associated with using deep approaches to learning. We also found that students who spend more weekly hours in part-time work exhibit higher levels of academic self-efficacy and use more deep approaches to learning.
Our results support previous research on the positive relationship between discipline identification and using deep approaches to learning [40,41,42,43,44,45] and extend those to working students. This result reveals the importance of fostering discipline identification in higher education, especially so for working students who might miss lectures [14] or do not attend campus altogether [15]. Researchers can increase the discipline identification of working students by reminding them of the reasons why they study (i.e., through value affirmation [29]) and thus position part-time employment as a vehicle for working students to use deep approaches to learning and indirectly increase their academic achievement.
Although we expected that identifying as a working student by seeing that identity in positive terms would be associated with having improved status in society, we found that student identification (rather than working student identification) was significantly associated with increased status in society. However, because society might place a higher status on being a student over being an employee [29], making working students see themselves as similar to other non-working students can have important positive effects on other important social outcomes, such as belonging and receiving social support from all students. Following Fernandez et al.’s typology of belonging in higher education [77], we hypothesise that working students who feel a lack of authenticity can benefit from events that aim to minimise the differences between them and non-working students to receive social support (akin to Levine et al. [78]). Similarly, feeling similar to others is another form of belonging, which working students may lack because their experiences are different to the experiences of non-working students [30,35,79]. Therefore, finding ways to raise the student identification of working students might be an important first step for them to belong at university and to receive social support from all students.
We also found that the hours students spend per week working in paid employment were positively associated with their academic self-efficacy (in Study 1) and with using a deep approach to learning (in Study 2). These findings suggest that working may limit opportunities to study, but it can foster intrinsic motivation (exemplified by using deep approaches to learning) and higher beliefs in one’s own ability to study [21]. However, because of our cross-sectional data, we cannot rule out the possibility that students who feel that they already have a good academic standing are more likely to allow themselves to work longer hours. As both suggestions are plausible, future research using longitudinal methods can further disentangle the relationship between working hours and positive academic outcomes. Such research can also better control for changes in students’ jobs, such as reducing hours of work, changing the nature of the job, or quitting employment altogether (c.f. [51]).
Although there were no significant links between working student identification and employee identification to the outcomes we measured, future research can seek to transform the experiences of working students to boost identification with these identities as they can be linked to different academic, social, and graduate employability outcomes. For example, identifying as a working student might be important to positively differentiate the student from non-working students, which can help to equip oneself with the appropriate defences against negative intergroup comparisons and to receive social support from other working students [30]. Leaning on the positive aspects of being a working student, such as being motivated and disciplined or being hardworking and organised [19], can foster identification with this identity. However, if the working student identity consists of the narrative of working students having adverse consequences, then it is unlikely that working students would espouse this identity and that this identity has a beneficial effect on academic, social, and graduate outcomes.
Conversely, higher employee identification could lead to an increase in the perceived meaningfulness of their course [29] or a reduction in degree consumerism (defined as expecting high grades in courses because they pay university fees [80]) in working students. Indeed, working students in previous studies have maintained that work is more fun than university [81] and that work allows them to gain more satisfaction from university [82]. High employee identification may also be associated with receiving on-the-job mentorship and support [38] and can thus lead to increases in important graduate employability outcomes.
Examining graduate employability outcomes in general can be an important extension of our current research as Geel and Backes-Gellner [83] suggest that working students embark on more financially successful career trajectories after graduation in comparison to non-working students. Working part-time can help to build skills and competencies that employers and educators seek in students [84], such as time-management skills [85], increased social networks [14], and confidence [86]. Working students are also more likely to be prepared to work harder [31] and to have better interpersonal skills than non-working students [87]. For these reasons, future research that seeks to transform the experiences of working students into forms of resilience can also explore the relationships between the identification processes of working students and their graduate employability outcomes.

4.1. Considerations for Future Research

The studies in the current research present initial evidence for how social identification processes can influence academic and social outcomes for working students. To augment this research, we now use our findings as an important point of departure and discuss recommendations, as follows: 1. Increase working students’ levels of identification with the different foci; 2. Explore boundary conditions that can influence the relationships between identification processes and academic, social, and graduate outcomes. Following these recommendations can help practitioners support working students in navigating higher education effectively by linking their experiences to their identification processes and to additional important academic, social, and graduate outcomes.

4.1.1. Ways to Increase Identification for Working Students

The experiences of working students could be useful in transforming the narrative surrounding working students from one of adverse consequences to one of perseverance and resilience [19]. Transforming the narrative could create a positive image of what it means to be a working student, and future research can both facilitate this transformation and examine the positive academic, social, and graduate outcomes emanating from it. We next present three specific ways of achieving these aims.
Positive psychology principles [20,86,88] can help to foster identification with the different social identities that working students hold. Nicklin et al. [20] have found that practising mindfulness and expressing self-compassion, resilience, and recovery are associated with lower levels of stress in working graduate students. Ng and Kong [88] have also found that mindfulness is associated with working students having increased levels of positive affect and resilience. Kocherhina and Stelmashchuk [86] show that working students exhibit higher levels of self-regulation and self-acceptance in comparison to non-working students. We posit that creating interventions that enable working students to identify with the different groups based on these positive psychology principles can lead to increases in important academic, social, and graduate employability outcomes.
Acceptance and commitment training [89] can also foster mindfulness for working students. This type of training aims to make the individual see themselves as being detached from daily stressors (e.g., stressful work experiences or negative comparisons to non-working students) and to act in line with their own values and motivations [90]. Working students who have undergone acceptance and commitment training report increases in life satisfaction, mindfulness, and well-being [91] and reductions in stress and symptoms of depression [92]. University students in general also report improved time and effort management [93] and academic performance [94] after undergoing acceptance and commitment training. This accumulated evidence suggests that developing acceptance and commitment interventions can help to improve the academic, social, and graduate employability outcomes for working students by increasing their identification with relevant groups.
Identity-reframing interventions [95,96,97] also aim to foster resilience by focusing on the positive experiences of being a member of a particular group. Identity-reframing interventions have led to increased study engagement and course completion for refugees [96], reducing academic anxiety in first-generation students [97], and reducing depression in the general population [95]. Thus, embedding working students into an identity-reframing intervention based on the positive aspects of being a working student [19] can assess whether the intervention leads to increased identification and improved academic, social, and graduate outcomes.

4.1.2. Exploring Boundary Conditions of Identification

The effects of identification processes on academic and social outcomes for working students may also be dependent on other socio-psychological processes. Because some of the identities can have contrasting norms and behaviours, working students may experience a sense of identity incompatibility [98]. As an example, commencing employment can be associated with entering adulthood and taking on additional responsibilities, whereas being a student may be associated with having free time and fun [29]. Because experiencing identity incompatibility can be associated with decreasing identification with one of the incompatible identities [99] and lower academic achievement [100], future research can examine whether students perceive the different identities that we examined as incompatible and whether this affects the academic, social, and graduate employability outcomes for working students.
The relationships between identification processes and important outcomes may also be dependent on intergroup differentiation or the perceived degree of difference between working and non-working students. Indeed, working students who perceive differences between these groups can feel a sense of isolation and lack of adaptation at university [35,100,101]. Thus, contexts that minimise the differences between working and non-working students can foster a higher sense of identification and can lead to increases in important outcomes (e.g., belonging and social support) for working students.
Finally, superordinate group prototypicality (the extent to which individuals believe that their group, and not a relevant outgroup, is the best representative of an overarching category that combines both groups [102]) may also impact the link between identification processes and important outcomes. As an example, if working students believe that they represent what it means to be a student better than non-working students, then identification as a working student (where exaggerated differences between groups exist) may become more important for fostering positive outcomes. Conversely, if working students perceive that non-working students better represent what it means to be a student, then identifying as a student (where the differences between groups should be minimised) may become more important to foster positive outcomes. These considerations point to the importance of understanding the relationships between the different identities and the context in which they are situated to foster positive academic, social, and graduate employability outcomes for working students.

4.2. Limitations of the Current Research

Although our studies link identification processes to academic and social outcomes for working students, the findings are subject to the cross-sectional nature of our data. We now present two additional considerations that future research can implement to disentangle the causal associations between the social identities of working students and their academic, social, and graduate outcomes.
First, we measured the strength of identification with the different groups at a particular point in time. Because of this, we were not able to track how working students develop their identification over time and whether such changes in the strength of identification were associated with academic and social outcomes. Future research can explore how working students’ identities change throughout their university years by using longitudinal (e.g., through narrative analysis [21]) or experimental (e.g., acceptance and commitment training [89]) approaches. This will extend the current research by exploring when the different identities become important for working students and whether they have links with important academic and social outcomes at those points in time.
Second, understanding how and why working students identify with the different groups throughout their time at university is also important because working students can be at a particular risk of dropping out of university [18]. Effective strategies to mitigate that risk can include adapting university policies to help working students (such as collapsing teaching sessions into two weekdays) and creating events designed to foster identification and belonging for working students [4]. However, these types of support may have limited impact if students’ identities do not align with this support—for example, working students may identify strongly with the student identity at the beginning stages of their course but place more importance on their employee identity towards the end of their degree. Extending the current research to understand when (and due to what motivation) working students identify with the different groups can serve to inform institutional support offerings and to present working students as persevering and resilient students in higher education.

5. Conclusions

We present three cross-sectional studies in which we explored whether the social identities of working students (identifying as a student, an employee, a student in their own discipline of study, and a working student) were associated with important academic (academic self-efficacy, approaches to learning, and academic achievement) and social (status in society) outcomes. While student identification was positively associated with working students’ status in society, discipline identification was positively associated with using deep approaches to learning. We suggest two distinct ways to augment our research and to assess whether the social identities of working students can function as important mechanisms to increase the resilience and perseverance of working students in higher education. Conducting important interventions (based on either positive psychology principles, acceptance and commitment coaching, or previous identity-reframing interventions) can help to transform working students’ experiences into sources of resilience and motivation. Exploring boundary conditions (such as levels of intergroup differentiation, superordinate group prototypicality, and identity incompatibility) can also enhance our understanding of the effect of identification processes on important academic, social, and graduate outcomes. We hope that the present research sparks additional interest from researchers and practitioners who aim to enhance students’ academic outcomes, foster their social adaptation at university, and strengthen their graduate employability.

Author Contributions

Conceptualisation, V.H.G. & M.J.E.; methodology, V.H.G. & M.J.E.; formal analysis, V.H.G. & M.J.E.; data curation, V.H.G.; writing—original draft preparation, V.H.G.; writing—review and editing, V.H.G. & M.J.E.; and supervision, M.J.E. All authors have read and agreed to the published version of the manuscript.

Funding

University of Sheffield Institutional Open Access Fund.

Institutional Review Board Statement

This study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of the University of Sussex (protocol codes ER/VG68/02, ER/VG68/03, and ER/VG68/12; Approval Date: 12 February 2021).

Informed Consent Statement

Informed consent was obtained from all subjects involved in this study.

Data Availability Statement

The original data presented in this study are openly available in Open Science Framework at https://osf.io/cg3mx/?view_only=0d654426ef8c40918ea41651f1b0bf35. Accessed on 27 June 2024.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Quintini, G. Working and Learning: A Diversity of Patterns; OECD: Paris, France, 2015. [Google Scholar] [CrossRef]
  2. OECD Employment Outlook. Organization for Economic Cooperation and Development, 2012. Available online: https://www.oecd-ilibrary.org/employment/oecd-employment-outlook-2012_empl_outlook-2012-en (accessed on 27 June 2024).
  3. Eastgate, L.; Bialocerkowski, A.; Hood, M.; Creed, P.A. Applying boundary management theory to university students: A scoping review. Int. J. Educ. Res. 2021, 108, 101793. [Google Scholar] [CrossRef]
  4. Remenick, L.; Bergman, M. Support for working students: Considerations for higher education institutions. J. Contin. High. Educ. 2021, 69, 34–45. [Google Scholar] [CrossRef]
  5. Metcalf, H. Paying for university: The impact of increasing costs on student employment, debt and satisfaction. Natl. Inst. Econ. Rev. 2005, 191, 106–117. [Google Scholar] [CrossRef]
  6. Owen, M.S.; Kavanagh, P.S.; Dollard, M.F. An integrated model of work–study conflict and work–study facilitation. J. Career Dev. 2018, 45, 504–517. [Google Scholar] [CrossRef]
  7. Roberts, R.; Golding, J.; Towell, T.; Reid, S.; Woodford, S.; Vetere, A.; Weinreb, I. Mental and physical health in students: The role of economic circumstances. Br. J. Health Psychol. 2000, 5, 289–297. [Google Scholar] [CrossRef]
  8. Curtis, S.; Shani, N. The effect of taking paid employment during term-time on students’ academic studies. J. Furth. High. Educ. 2002, 26, 129–138. [Google Scholar] [CrossRef]
  9. Savoca, M. Campus Employment as a High Impact Practice: Relationship to Academic Success and Persistence of First-Generation College Students. Ph.D. Dissertation, Colorado State University, Fort Collins, CO, USA, 2016. Available online: https://www.proquest.com/dissertations-theses/campus-employment-as-high-impact-practice/docview/1805293024/se-2?accountid=14182 (accessed on 27 June 2024).
  10. Teixeira, L.; Lowden, A.; da Luz, A.A.; Turte, S.L.; Valente, D.; Matsumura, R.J.; de Paula, L.P.; Takara, M.Y.; Nagai-Manelli, R.; Fischer, F.M. Sleep patterns and sleepiness of working college students. Work 2012, 41 (Suppl. S1), 5550–5552. [Google Scholar] [CrossRef]
  11. Mounsey, R.; Vandehey, M.; Diekhoff, G. Working and non-working university students: Anxiety, depression, and grade point average. Coll. Stud. J. 2013, 47, 379–389. Available online: https://link.gale.com/apps/doc/A337070506/AONE?u=anon~56ba4b07&sid=googleScholar&xid=2acbea38 (accessed on 27 June 2024).
  12. Callender, C. The impact of term-time employment on higher education students’ academic attainment and achievement. J. Educ. Policy 2008, 23, 359–377. [Google Scholar] [CrossRef]
  13. Robotham, D. Combining study and employment: A step too far? Educ. Train. 2009, 51, 322–332. [Google Scholar] [CrossRef]
  14. Curtis, S. Students’ perceptions of the effects of term-time paid employment. Educ. Train. 2007, 49, 380–390. [Google Scholar] [CrossRef]
  15. Rubin, M.; Wright, C.L. Age differences explain social class differences in students’ friendship at university: Implications for transition and retention. High. Educ. 2015, 70, 427–439. [Google Scholar] [CrossRef]
  16. Moreau, M.-P.; Leathwood, C. Balancing paid work and studies: Working (-class) students in higher education. Stud. High. Educ. 2006, 31, 23–42. [Google Scholar] [CrossRef]
  17. Tuononen, T.; Parpala, A.; Mattsson, M.; Lindblom-Ylänne, S. Work experience in relation to study pace and thesis grade: Investigating the mediating role of student learning. High. Educ. 2016, 72, 41–58. [Google Scholar] [CrossRef]
  18. Moulin, S.; Doray, P.; Laplante, B.; Street, M.C. Work intensity and non-completion of university: Longitudinal approach and causal inference. J. Educ. Work. 2013, 26, 333–356. [Google Scholar] [CrossRef]
  19. Grozev, V.H.; Easterbrook, M.J. The identities of employed students: Striving to reduce distinctiveness from the typical student. Anal. Soc. Issues Public Policy 2024, 1, 1–22. [Google Scholar] [CrossRef]
  20. Nicklin, J.M.; Meachon, E.J.; McNall, L.A. Balancing work, school, and personal life among graduate students: A positive psychology approach. Appl. Res. Qual. Life 2019, 14, 1265–1286. [Google Scholar] [CrossRef]
  21. Taylor, A. ‘Being there’: Rhythmic diversity and working students. J. Educ. Work 2022, 35, 572–584. [Google Scholar] [CrossRef]
  22. Ceneciro, C.C. Integrating narratives of working students into higher education curriculum: Equalizer for the socio-economically challenged. Environ. Soc. Psychol. 2023, 8, 1736. [Google Scholar] [CrossRef]
  23. Fleming, J.; Rowe, A.D.; Jackson, D. Employers as educators: The role of work placement supervisors in facilitating the transfer of skills and knowledge. J. Educ. Work 2021, 34, 705–721. [Google Scholar] [CrossRef]
  24. Jackson, D.; Dean, B.A. The contribution of different types of work-integrated learning to graduate employability. High. Educ. Res. Dev. 2023, 42, 93–110. [Google Scholar] [CrossRef]
  25. Turner, J.C. Social Influence; Thomson Brooks/Cole Publishing Co., Ltd.: Pacific Grove, CA, USA, 1991. [Google Scholar]
  26. Tajfel, H. (Ed.) Differentiation between Social Groups: Studies in the Social Psychology of Intergroup Relation; Academic Press: Cambridge, MA, USA, 1978. [Google Scholar]
  27. Kyprianides, A.; Easterbrook, M.J.; Brown, R. Group identities benefit well-being by satisfying needs. J. Exp. Soc. Psychol. 2019, 84, 103836. [Google Scholar] [CrossRef]
  28. Broadbridge, A.; Swanson, V. Managing two roles: A theoretical study of students’ employment whilst at university. Community Work. Fam. 2006, 9, 159–179. [Google Scholar] [CrossRef]
  29. Grozev, V.H.; Easterbrook, M.J. Accessing the phenomenon of incompatibility in working students’ experience of university life. Tert. Educ. Manag. 2022, 28, 241–264. [Google Scholar] [CrossRef]
  30. Grozev, V.H.; Easterbrook, M.J. The relationships of employed students to non-employed students and non-student work colleagues: Identity implications. Anal. Soc. Issues Public Policy 2022, 22, 712–734. [Google Scholar] [CrossRef]
  31. Cameron, J.E. Social identity and the pursuit of possible selves: Implications for the psychological well-being of university students. Group Dyn. Theory Res. Pract. 1999, 3, 179. [Google Scholar] [CrossRef]
  32. Daniel, J.D. When Environments Collide: The Role of Social Identity and Drinking among Working Students; University of California, San Diego and San Diego State University: Los Angeles, CA, USA, 2011; Available online: https://www.proquest.com/docview/868726975?pq-origsite=gscholar&fromopenview=true (accessed on 27 June 2024).
  33. Greenaway, K.; Amiot, C.E.; Louis, W.R.; Bentley, S.V.; Mavor, K.I.; Platow, M.J.; Bizumic, B. The role of psychological need satisfaction in promoting student identification. In Self and Social Identity in Educational Context; Routledge: New York, NY, USA, 2017. [Google Scholar]
  34. Obst, P.L.; White, K.M. Choosing to belong: The influence of choice on social identification and psychological sense of community. J. Community Psychol. 2007, 35, 77–90. [Google Scholar] [CrossRef]
  35. Outerbridge, H.J. The Impact of Part-Time Work on the Student Experience. 2016. Available online: http://summit.sfu.ca/item/16466 (accessed on 27 June 2024).
  36. Haslam, S.A.; O’Brien, A.; Jetten, J.; Vormedal, K.; Penna, S. Taking the strain: Social identity, social support, and the experience of stress. Br. J. Soc. Psychol. 2005, 44, 355–370. [Google Scholar] [CrossRef]
  37. Ashforth, B.E.; Mael, F. Social identity theory and the organization. Acad. Manag. Rev. 1989, 14, 20–39. [Google Scholar] [CrossRef]
  38. Choo, C.E.K.; Kan, Z.X.; Cho, E. A review of the literature on the school-work-life interface. J. Career Dev. 2021, 48, 290–305. [Google Scholar] [CrossRef]
  39. Lammont, N.; Lucas, R. “Getting by” and “getting on” in service work: Lessons for the future of accounting? Crit. Perspect. Account. 1999, 10, 809–830. [Google Scholar] [CrossRef]
  40. Platow, M.J.; Mavor, K.I.; Grace, D.M. On the role of discipline-related self-concept in deep and surface approaches to learning among university students. Instr. Sci. 2013, 41, 271–285. [Google Scholar] [CrossRef]
  41. Bliuc, A.-M.; Ellis, R.A.; Goodyear, P.; Hendres, D.M. Understanding student learning in context: Relationships between university students’ social identity, approaches to learning, and academic performance. Eur. J. Psychol. Educ. 2011, 26, 417–433. [Google Scholar] [CrossRef]
  42. Smyth, L.; Mavor, K.I.; Platow, M.J.; Grace, D.M.; Reynolds, K.J. Discipline social identification, study norms and learning approach in university students. Educ. Psychol. 2015, 35, 53–72. [Google Scholar] [CrossRef]
  43. Smyth, L.; Mavor, K.I.; Platow, M.J. Learning behaviour and learning outcomes: The roles for social influence and field of study. Soc. Psychol. Educ. 2017, 20, 69–95. [Google Scholar] [CrossRef]
  44. Smyth, L.; Chandra, V.; Mavor, K.I. Social identification and normative conflict: When student and educator learning norms collide. J. Appl. Soc. Psychol. 2018, 48, 293–303. [Google Scholar] [CrossRef]
  45. Smyth, L.; Mavor, K.I.; Platow, M.J. Social identification and academic performance: Integrating two existing models of tertiary student learning. Educ. Psychol. 2019, 39, 409–425. [Google Scholar] [CrossRef]
  46. Gbadamosi, G.; Evans, C.; Richardson, M.; Ridolfo, M. Employability and students’ part-time work in the UK: Does self-efficacy and career aspiration matter? Br. Educ. Res. J. 2015, 41, 1086–1107. [Google Scholar] [CrossRef]
  47. Bandura, A. Self-Efficacy: The Exercise of Control; HW H Freeman/Times Books/Henry Holt & Co., Ltd.: New York, NY, USA, 1997; Volume 333, p. 48461. [Google Scholar]
  48. Pajares, F. Self-efficacy beliefs in academic settings. Rev. Educ. Res. 1996, 66, 543–578. [Google Scholar] [CrossRef]
  49. Multon, K.D.; Brown, S.D.; Lent, R.W. Relation of self-efficacy beliefs to academic outcomes: A meta-analytic investigation. J. Couns. Psychol. 1991, 38, 30. [Google Scholar] [CrossRef]
  50. Richardson, M.; Abraham, C.; Bond, R. Psychological correlates of university students’ academic performance: A systematic review and meta-analysis. Psychol. Bull. 2012, 138, 353. [Google Scholar] [CrossRef] [PubMed]
  51. Huie, F.C.; Winsler, A.; Kitsantas, A. Employment and first-year college achievement: The role of self-regulation and motivation. J. Educ. Work 2014, 27, 110–135. [Google Scholar] [CrossRef]
  52. Pennington, C.R.; Bates, E.A.; Kaye, L.K.; Bolam, L.T. Transitioning in higher education: An exploration of psychological and contextual factors affecting student satisfaction. J. Furth. High. Educ. 2018, 42, 596–607. [Google Scholar] [CrossRef]
  53. Scherrer, V.; Preckel, F. Development of motivational variables and self-esteem during the school career: A meta-analysis of longitudinal studies. Rev. Educ. Res. 2019, 89, 211–258. [Google Scholar] [CrossRef]
  54. Biggs, J.B. Approaches to the enhancement of tertiary teaching. High. Educ. Res. Dev. 1989, 8, 7–25. [Google Scholar] [CrossRef]
  55. Marton, F.; Säljö, R. On qualitative differences in learning: I—Outcome and process. Br. J. Educ. Psychol. 1976, 46, 4–11. [Google Scholar] [CrossRef]
  56. Ramsden, P. Student learning and perceptions of the academic environment. High. Educ. 1979, 8, 411–427. [Google Scholar] [CrossRef]
  57. Pask, G. Styles and strategies of learning. Br. J. Educ. Psychol. 1976, 46, 128–148. [Google Scholar] [CrossRef]
  58. Biggs, J.; Kember, D.; Leung, D.Y.P. The revised two-factor study process questionnaire: R-SPQ-2F. Br. J. Educ. Psychol. 2001, 71, 133–149. [Google Scholar] [CrossRef] [PubMed]
  59. Hailikari, T.K.; Parpala, A. What impedes or enhances my studying? The interrelation between approaches to learning, factors influencing study progress and earned credits. Teach. High. Educ. 2014, 19, 812–824. [Google Scholar] [CrossRef]
  60. Bradley, G. Work participation and academic performance: A test of alternative propositions. J. Educ. Work 2006, 19, 481–501. [Google Scholar] [CrossRef]
  61. Hawkins, C.A.; Smith, M.L.; Hawkins, R.C.; Grant, D. The relationships among hours employed, perceived work interference, and grades as reported by undergraduate social work students. J. Soc. Work. Educ. 2005, 41, 13–27. [Google Scholar] [CrossRef]
  62. Canabal, M.E. College student degree of participation in the labor force: Determinants and relationship to school performance. Coll. Stud. J. 1998, 32, 597–605. [Google Scholar]
  63. Hammes, J.F.; Haller, E.J. Making ends meet: Some of the consequences of part-time work for college students. J. Coll. Stud. Pers. 1983, 24, 529–535. Available online: https://eric.ed.gov/?id=EJ296529 (accessed on 27 June 2024).
  64. Kuh, G.D.; Kinzie, J.; Cruce, T.; Shoup, R.; Gonyea, R.M. Connecting the Dots: Multi-Faceted Analyses of the Relationships between Student Engagement Results from the NSSE, and the Institutional Practices and Conditions That Foster Student Success. Indiana University Center for Postsecondary Research, 2007. Available online: http://cms.uhd.edu/qep/QEP_web_page_files/Connecting_the_Dots_Report.pdf (accessed on 27 June 2024).
  65. Wilkins, S.; Butt, M.M.; Kratochvil, D.; Balakrishnan, M.S. The effects of social identification and organizational identification on student commitment, achievement and satisfaction in higher education. Stud. High. Educ. 2016, 41, 2232–2252. [Google Scholar] [CrossRef]
  66. Blake, J.; Worsdale, G.J. Incorporating the learning derived from part-time employment into undergraduate programmes: Experiences from a business school. J. Furth. High. Educ. 2009, 33, 191–204. [Google Scholar] [CrossRef]
  67. Creed, P.A.; Hood, M.; Selenko, E.; Bagley, L. The development and initial validation of a self-report job precariousness scale suitable for use with young adults who study and work. J. Career Assess. 2020, 28, 636–654. [Google Scholar] [CrossRef]
  68. Savić, M.; Kresoja, M. Modelling factors of students’ work in Western Balkan countries. Stud. High. Educ. 2018, 43, 660–670. [Google Scholar] [CrossRef]
  69. Pike, G.R.; Kuh, G.D.; Massa-McKinley, R.C. First-year students’ employment, engagement, and academic achievement: Untangling the relationship between work and grades. NASPA J. 2008, 45, 560–582. [Google Scholar] [CrossRef]
  70. Doosje, B.; Ellemers, N.; Spears, R. Perceived intragroup variability as a function of group status and identification. J. Exp. Soc. Psychol. 1995, 31, 410–436. [Google Scholar] [CrossRef]
  71. Postmes, T.S.; Haslam, A.; Jans, L. A single-item measure of social identification: Reliability, validity, and utility. Br. J. Soc. Psychol. 2013, 52, 597–617. [Google Scholar] [CrossRef] [PubMed]
  72. Marsh, H.W.; Seaton, M.; Trautwein, U.; Lüdtke, O.; Hau, K.-T.; O’Mara, A.J.; Craven, R.G. The big-fish–little-pond-effect stands up to critical scrutiny: Implications for theory, methodology, and future research. Educ. Psychol. Rev. 2008, 20, 319–350. [Google Scholar] [CrossRef]
  73. Adler, N.E.; Epel, E.S.; Castellazzo, G.; Ickovics, J.R. Relationship of subjective and objective social status with psychological and physiological functioning: Preliminary data in healthy, White women. Health Psychol. 2000, 19, 586. [Google Scholar] [CrossRef]
  74. Tan, J.J.X.; Kraus, M.W.; Carpenter, N.C.; Adler, N.E. The association between objective and subjective socioeconomic status and subjective well-being: A meta-analytic review. Psychol. Bull. 2020, 146, 970–1020. [Google Scholar] [CrossRef] [PubMed]
  75. Rosseel, Y. Lavaan: An R package for structural equation modeling. J. Stat. Softw. 2012, 48, 1–36. [Google Scholar] [CrossRef]
  76. Efron, B.; Tibshirani, R.J. Estimates of bias. In An Introduction to the Bootstrap; Springer: Berlin/Heidelberg, Germany, 1993; pp. 124–140. [Google Scholar]
  77. Fernández, D.P.; Ryan, M.K.; Begeny, C.T. Recognizing the diversity in how students define belonging: Evidence of differing conceptualizations, including as a function of students’ gender and socioeconomic background. Soc. Psychol. Educ. 2023, 26, 673–708. [Google Scholar] [CrossRef]
  78. Levine, M.; Prosser, A.; Evans, D.; Reicher, S. Identity and emergency intervention: How social group membership and inclusiveness of group boundaries shape helping behavior. Personal. Soc. Psychol. Bull. 2005, 31, 443–453. [Google Scholar] [CrossRef] [PubMed]
  79. Christie, H.; Munro, M.; Rettig, H. Accommodating students. J. Youth Stud. 2002, 5, 209–235. [Google Scholar] [CrossRef]
  80. Bunce, L.; Baird, A.; Jones, S.E. The student-as-consumer approach in higher education and its effects on academic performance. Stud. High. Educ. 2017, 42, 1958–1978. [Google Scholar] [CrossRef]
  81. Lucas, R.; Ralston, L. Youth, gender and part-time employment: A preliminary appraisal of student employment. Empl. Relat. 1997, 19, 51–66. [Google Scholar] [CrossRef]
  82. Muldoon, R. Recognizing the enhancement of graduate attributes and employability through part-time work while at university. Act. Learn. High. Educ. 2009, 10, 237–252. [Google Scholar] [CrossRef]
  83. Geel, R.; Backes-Gellner, U. Earning while learning: When and how student employment is beneficial. Labour 2012, 26, 313–340. [Google Scholar] [CrossRef]
  84. Bowles, S.; Gintis, H. Schooling in Capitalist America: Educational Reform and the Contradictions of Economic Life; Haymarket Books: Chicago, IL, USA, 2011. [Google Scholar]
  85. Pennington, D.C.; Zvonkovic, A.M.; Wilson, S.L. Changes in college satisfaction across an academic term. J. Coll. Stud. Dev. 1989, 30, 528–535. Available online: https://psycnet.apa.org/record/1990-10967-001 (accessed on 27 June 2024).
  86. Kocherhina, I.; Stelmashchuk, K. Peculiarities of Behaviour Self-Regulation in Students who Combine Study and Work. Психoлoгічні науки Series 12 2022, 19, 34–45. [Google Scholar] [CrossRef]
  87. Robotham, D. Student part-time employment: Characteristics and consequences. Educ. Train. 2012, 54, 65–75. [Google Scholar] [CrossRef]
  88. Ng, B.; Kong, L.C. Graduate resilience in future workplace: Mindfulness-based research on personality traits, trait affect and resilience. In Higher Education and Job Employability; Springer International Publishing: Cham, Switzerland, 2022; pp. 255–285. [Google Scholar] [CrossRef]
  89. Gillard, D.; Flaxman, P.; Hooper, N. Acceptance and commitment therapy: Applications for educational psychologists within schools. Educ. Psychol. Pract. 2018, 34, 272–281. [Google Scholar] [CrossRef]
  90. Hayes, S.C.; Strosahl, K.D.; Wilson, K.G. Acceptance and Commitment Therapy: The Process and Practice of Mindful Change; Guilford Press: New York, NY, USA, 2011. [Google Scholar]
  91. Räsänen, P.; Lappalainen, P.; Muotka, J.; Tolvanen, A.; Lappalainen, R. An online guided ACT intervention for enhancing the psychological wellbeing of university students: A randomized controlled clinical trial. Behav. Res. Ther. 2016, 78, 30–42. [Google Scholar] [CrossRef]
  92. Turner, L.; Galante, J.; Vainre, M.; Stochl, J.; Dufour, G.; Jones, P.B. Immune dysregulation among students exposed to exam stress and its mitigation by mindfulness training: Findings from an exploratory randomised trial. Sci. Rep. 2020, 10, 5812. [Google Scholar] [CrossRef]
  93. Katajavuori, N.; Vehkalahti, K.; Asikainen, H. Promoting university students’ well-being and studying with an acceptance and commitment therapy (ACT)-based intervention. Curr. Psychol. 2023, 42, 4900–4912. [Google Scholar] [CrossRef]
  94. Paliliunas, D.; Belisle, J.; Dixon, M.R. A randomized control trial to evaluate the use of acceptance and commitment therapy (ACT) to increase academic performance and psychological flexibility in graduate students. Behav. Anal. Pract. 2018, 11, 241–253. [Google Scholar] [CrossRef]
  95. Bauer, C.A.; Walton, G. Identity-reframing interventions: How to effectively highlight individuals’ background-specific strengths. Soc. Personal. Psychol. Compass 2024, 18, e12830. [Google Scholar] [CrossRef]
  96. Bauer, C.A.; Boemelburg, R.; Walton, G.M. Resourceful actors, not weak victims: Reframing refugees’ stigmatized identity enhances long-term academic engagement. Psychol. Sci. 2021, 32, 1896–1906. [Google Scholar] [CrossRef]
  97. Bauer, C.A.; Job, V.; Hannover, B. Who gets to see themselves as talented? Biased self-concepts contribute to first-generation students’ disadvantage in talent-focused environments. J. Exp. Soc. Psychol. 2023, 108, 104501. [Google Scholar] [CrossRef]
  98. Iyer, A.; Jetten, J.; Tsivrikos, D.; Postmes, T.; Haslam, S.A. The more (and the more compatible) the merrier: Multiple group memberships and identity compatibility as predictors of adjustment after life transitions. Br. J. Soc. Psychol. 2009, 48, 707–733. [Google Scholar] [CrossRef] [PubMed]
  99. de Vreeze, J.; Matschke, C.; Cress, U. Neither fish nor fowl: A perceived mismatch in norms and values between oneself, other students, and people back home undermines adaptation to university. Br. J. Soc. Psychol. 2018, 57, 684–702. [Google Scholar] [CrossRef] [PubMed]
  100. Veldman, J.; Meeussen, L.; van Laar, C. A social identity perspective on the social-class achievement gap: Academic and social adjustment in the transition to university. Group Process. Intergroup Relat. 2019, 22, 403–418. [Google Scholar] [CrossRef]
  101. Christie, H.; Munro, M.; Rettig, H. Making ends meet: Student incomes and debt. Stud. High. Educ. 2001, 26, 363–383. [Google Scholar] [CrossRef]
  102. Wenzel, M.; Mummendey, A.; Waldzus, S. Superordinate identities and intergroup conflict: The ingroup projection model. Eur. Rev. Soc. Psychol. 2008, 18, 331–372. [Google Scholar] [CrossRef]
Table 1. Descriptive statistics and zero-order correlations for all variables in Studies 1–3.
Table 1. Descriptive statistics and zero-order correlations for all variables in Studies 1–3.
Study 1
MSD12345678
1. Age23.624.58-
2.Gender b1.59.50−.13-
3. Working Hours d11.265.13.01−.01-
4. Student Identification5.591.09−.09−.04.01-
5. Employee Identification5.161.12.06.08.01.01-
6. Academic Self-Efficacy2.76.65.11−.14.18 +.10.03-
Study 2
MSD12345678
1. Age23.343.19-
2. Gender b1.79.41.11-
3. Working Hours d16.5510.55.25 *.15-
4. Discipline Identification5.751.01.16.36 **.20-
5. Employee Identification4.941.45.19.08.36 **.26 *-
6. Deep Approaches to Learning30.638.67.25 *.20 +.38 ***.47 ***.23 *-
7. Surface Approaches to Learning25.405.37.19−.02.27 *.15.22 +.36 ***-
8. Academic Achievement59.808.81.19.31 **.07.39 ***.06.40 ***−.01-
Study 3
MSD12345678
1. Age22.205.97-
2. Gender b,c1.90.40−.17 *-
3. Working Hours d15.4410.10.30 ***−.06-
4. Student Identification5.081.44−.26 ***.01−.26 ***-
5. Employee Identification5.031.42−.04.05−.05.25 ***-
6. Working Student Identification5.711.14.07.05.23 **.24 ***.21 **-
7. Status in Society5.071.79.23 **.01.12.04.05−.17 *-
8. Academic Achievement66.268.51.05.01.01−.07−.09−.01.24 **-
Note. N1 = 95, N2 = 70, and N3 = 215. b Identifying as male was coded as 1, and identifying as female was coded as 2. c Identifying as another gender was coded as 3, but those working students were removed from all analyses to preserve the statistical power. d Measured as the hours in paid employment per week and averaged if the student has a flexible work pattern. + p < 0.10, * p < 0.05, ** p < 0.01, and *** p < 0.001.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Grozev, V.H.; Easterbrook, M.J. Can Social Identities Improve Working Students’ Academic and Social Outcomes? Lessons from Three Studies. Educ. Sci. 2024, 14, 939. https://doi.org/10.3390/educsci14090939

AMA Style

Grozev VH, Easterbrook MJ. Can Social Identities Improve Working Students’ Academic and Social Outcomes? Lessons from Three Studies. Education Sciences. 2024; 14(9):939. https://doi.org/10.3390/educsci14090939

Chicago/Turabian Style

Grozev, Vladislav H., and Matthew J. Easterbrook. 2024. "Can Social Identities Improve Working Students’ Academic and Social Outcomes? Lessons from Three Studies" Education Sciences 14, no. 9: 939. https://doi.org/10.3390/educsci14090939

APA Style

Grozev, V. H., & Easterbrook, M. J. (2024). Can Social Identities Improve Working Students’ Academic and Social Outcomes? Lessons from Three Studies. Education Sciences, 14(9), 939. https://doi.org/10.3390/educsci14090939

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop