1 Introduction

Across the globe, participation in Higher Education (HE) is expanding for several reasons, not least competition for desired career outcomes, with non-attendance of HE often incurring opportunity costs (Marginson, 2016). Higher Education Institutions (HEIs) are therefore positioned as having responsibility to the wider economy (Hunter, 2013), e.g. via providing “work-ready” graduates (Tomlinson, 2012). In Britain, HEIs are expected to justify their high tuition fees through enhanced graduate employability levels (Tholen, 2014). Employability has variously been described as the ability to gain and maintain desired forms of employment (Rothwell & Arnold, 2007) and as a collection of achievements and understandings that will promote future career success (Knight & Yorke, 2004). More recently, Clarke has proposed an integrative model of employability, in which perceived employability is informed by human capital, e.g. skills, social capital such as networks, individual behaviours such as career management skills, and individual attributes such as adaptability (Clarke, 2018). Significantly, Clarke’s model also acknowledges the role of labour market factors, i.e. supply and demand, on both perceived employability and actual career outcomes.

In modern labour markets, individuals are responsible for managing their own career progress and outcomes (Smith, 2010) and need to be adaptable (Clarke, 2013). There have been calls for HEIs to improve graduate employability, as UK governments (Browne, 2010) and some portions of British industry (CBI, 2015) have claimed that graduates are not prepared for the world of work—although other reports have claimed that employers are generally satisfied with the quality of graduates (UK Commission for Employment and Skills, 2015). Employers report large numbers of “hard-to-fill” vacancies (CIPD, 2018), but there are signs of an “oversupply” of graduates (Humburg, de Grip, & van der Velden, 2017) which is seen as resulting from mass participation in HE that has not been matched by increased demand for highly skilled workers (Verhaest & Van Der Velden, 2013). This has consequences for graduates, in that there is increased competition for a finite supply of desired occupations (Helyer & Lee, 2014). Brown and Hesketh (2004) characterise this as “positional conflict”, whereby graduates are now required to find a means beyond that of their degree to make themselves distinctive to employers. Logically, while it is possible to help individual students become more employable, employability interventions are unlikely to enhance the career outcomes of graduates as a whole (Greenbank, 2017) as the number of graduate positions remains finite. The focus in this chapter therefore is on how career outcomes might be improved for individuals, although structural issues (e.g. inequality) must also be considered. Individuals have largely been given the task of managing their own careers. Inevitably people vary in how well they perform this task, for a variety of reasons.

The role that motivation plays in the pursuit of career goals is key. Some scholars have expressed concern that students do not engage with employability early enough during their time in HE (Tansley, Jome, Haase, & Martens, 2007). Early in their studies, students may be less likely to place a high value on work experience as compared to how they view it in their final year of study (Tymon, 2013). There is evidence too that some students fail to seek advice from careers services, in part perhaps because students prefer to speak to people whom they know and who know them as individuals (Greenbank, 2011). Greenbank (2011) noted that students thus preferred to speak with lecturers or family rather than the careers service, even though this preferred source may lack the career-specific knowledge needed by the enquiring student. For example, the parents of first-generation HE students are less likely to have labour market knowledge relevant to their children’s goals (Tate, Caperton, Kaiser, Pruitt, White, & Hall, 2015). There are also several reasons that students may put off engaging with employability, including a preference for focusing on immediate concerns (e.g. assignments), a tendency to base career decisions on intuition rather than research, and passive reliance on the provision of information (Greenbank, 2017). However, some students clearly engage better than others with the development of employability skills, despite these competing demands. To discuss why this may be, motivation theory will be looked at, given how motivation reflects the direction, intensity and duration of action (Locke & Latham, 2004).

2 Social Cognitive Career Theory

Social cognitive career theory (SCCT) was formulated to account for the processes by which people form career interests, make academic and career choices, and pursue career goals (Lent, Brown, & Hackett, 1994). A key concept in SCCT is self-efficacy, a construct representing an individual’s perception of their capability (Bandura & Cervone, 1983). In SCCT it is expected that career interests are influenced by self-efficacy, i.e. one’s perceived ability in a career field, perceived outcomes (e.g. rewards) and perceived barriers (Brown & Lent, 1996). For example, a graduate may intend to have a career in management. They believe themselves capable of managing others, find the work interesting, and the pay appealing—yet the question of whether they do apply for a job in management may be influenced by their self-perceptions e.g. that they are able to get the job. Influences on self-efficacy might include previous performance, direct and indirect learning, and others’ persuasion of the individual (Brown, Lent, Telander, & Tramayne, 2011; Lent & Brown, 1996). The hypothetical graduate seeking management work may well have a sense of their own ability that is informed by their experience of a work placement, feedback from supervisors and tutors, and advice from their HEI’s careers service. More recently, Lent et al. proposed an SCCT model of career self-management (CSM) to explain developmental processes in careers (Ireland & Lent, 2018; Lent & Brown, 2013; Lent, Ezeofor, Morrison, Penn, & Ireland, 2016). The CSM is intended to extend SCCT, which focuses more on career interests and choices—career content—by examining career processes, such as career planning, career exploration and decision-making (Lent & Brown, 2013). CSM draws also upon Savickas’ concept of career adaptability, which relates to individuals’ ability to adapt to changing circumstances (Savickas, 1997). CSM distinguishes between developmental tasks, such as career decision-making and seeking employment, and the coping skills that enable an individual to manage key transitions such as school-to-work or job loss (Lent & Brown, 2013). The model draws upon the earlier work of Super (1975) in distinguishing between a series of life stages, each of which are associated with particular adaptive tasks (Lent & Brown, 2013):

  • Growth, an early stage in which the emphasis is upon skill development

  • Exploration, in which skills are further developed, but additional tasks include career exploration and career decision-making

  • Establishment, which includes the tasks of obtaining work and adjustment to work environments

  • Maintenance, which includes the task of career self-renewal, but may also lead to recycling of earlier stages (e.g. due to voluntary or involuntary departure from a job)

  • Disengagement/reengagement, which can include adjustment to changing responsibilities, or adjustment from work to leisure (i.e. retirement).

This chapter looks at the stages of exploration and establishment. In line with CSM, it is important to recognise that these stages may apply not only to young HE students, but also to mature students who have decided to attend HE as part of a strategy for making career changes, i.e. recycling exploration and establishment as part of the maintenance stage. As in SCCT, CSM proposed that learning experiences influenced self-efficacy and outcome expectations, which in turn inform career goals. Contextual factors (such as the presence of support and barriers) are expected to influence goals, the actions implemented to pursue goals, and goal outcomes e.g. by contributing to self-efficacy. As predicted, self-efficacy and outcome expectations have been found to influence career exploration goals (Lent, Ezeofor, Morrison, Penn, & Ireland, 2016). Learning experiences associated with success, operationalised as mastery experiences, have also been associated with self-efficacy (Bandura, 1977; Ireland & Lent, 2018; Warner et al., 2018). A meta-analytic review demonstrated further that cognitive ability and conscientiousness—a personality trait reflecting discipline and persistence—also influence self-efficacy (Brown et al., 2011). While SCCT and CSM identify a key role for self-efficacy, these models do not address the characteristics of career goals. As such, Goal-Setting Theory requires discussion here.

3 Goal-Setting Theory

Goal-Setting Theory (GST) proposes that goal characteristics influence the level of effort and persistence individuals devote to their goals, and thus shapes the likelihood of success (Latham & Locke, 2007; Locke & Latham, 2004, 2013). Specifically, GST states that people perform better when they have “high goals,” i.e. goals that are specific, achievable, and challenging (Locke & Latham, 1990). A challenging target requires new behaviours, encouraging the formation of strategy, while the specific nature of the high goal enables an individual to monitor goal progress (Locke & Latham, 2013). As in SCCT and CSM, self-efficacy is an important feature of the goal-setting process. Individuals with higher self-efficacy set themselves more challenging goals (Bandura & Locke, 2003; Donovan, 2009) and persist longer when striving for these goals (Locke & Latham, 2002). Feedback is an important part of the goal-striving process, as it enables individuals to see how much progress has been made, and how much is perhaps still needed (Bandura & Cervone, 1983). Individuals with higher levels of self-efficacy combined with goal commitment are more likely to recover from failures during goal attainment, while those individuals with higher self-efficacy levels may respond by setting new, more challenging goals (Bandura & Locke, 2003).

4 Career Goal Pursuit

The creation of discrepancy is a crucial feature of Goal-Setting Theory (Bandura & Locke, 2003). In other words, people are motivated to achieve, and this therefore leads them to setting challenging goals. After all, if one merely wished to experience no discrepancy between current and desired states, it would be simpler not to set goals at all. On the other hand, discrepancies between what we want to achieve and what we have actually achieved can also create distress (Creed, Wamelink, & Hu, 2015). This may be weakened by engagement in career exploration and planning however, as Creed et al. (2015) noted (albeit in relation to young people in general rather than those specifically enrolled in HE). Creed, Hood, and Hu (2017) surveyed 564 young people in their first year of HE. They reported that students with proactive orientations experienced less career goal-performance discrepancy, and therefore had less career-related distress and more employability confidence: those with higher interpersonal rejection sensitivity experienced greater career-goal discrepancy and thus saw higher distress and lowered confidence. Through moderated mediation models, Creed et al. (2017) also demonstrated that goal commitment (which they treated as a measure of goal importance) buffered the impact of rejection sensitivity and strengthened the impact of proactive orientations. In other words, when students were more committed to their career goals, those who were proactive experienced even less discrepancy, and those who were worried about disappointing others experienced less discrepancy than they otherwise would.

In another study examining aspects of self-regulation in the career goal pursuit, Hu, Hood, and Creed (2017) explored the impact of negative career feedback in a sample of 184 HE students. As might be expected, negative career feedback was associated with a greater inclination amongst students to abandon their career goals. However, this effect was weakened for those who had a higher career-related growth mind-set (i.e. who see struggle as a normal part of career pursuit) and strengthened for those with a higher career-related destiny mind-set (i.e. who see adversity as a sign that the career path is not ‘meant to be’). In a study exploring engagement with employability amongst a sample of 432 UK undergraduates, mastery approach—a tendency towards seeking challenges in order to personally develop—was associated with greater engagement in three out of four proactive career behaviours: career consultation, network building, and skill development—but not career planning (Clements & Kamau, 2018). They reported that career goal commitment was positively associated with all four proactive career behaviours. Goal commitment is a key concept in Goal-Setting Theory (Hollenbeck, Williams, & Klein, 1989). A meta-analytic review has demonstrated that goal commitment moderates the relationship between goal difficulty and performance, with goal commitment becoming more important at higher levels of difficulty (Klein, Wesson, Hollenbeck, & Alge, 1999). Clements and Kamau (2018) predicted that goal commitment would moderate the relationship between mastery approach (used as a proxy for the setting of challenging goals) and proactive career behaviours. Instead, they found that goal commitment acted as a full mediator between mastery approach and career planning, and as a partial mediator between mastery approach and the other three proactive career behaviours (career consultation, network building, and skill development). Taken together, key attributes for students to engage with employability would appear to include self-efficacy, commitment to career goals, proactive approaches and a tendency towards seeking challenge. However, drawing on the CSM, it is possible to further explore the specific stages of career goal pursuit for students.

5 Career Exploration

Career exploration is an important activity within the exploration stage of the CSM (Lent & Brown, 2013). Career exploration can include both self-exploration (to identify relevant personal qualities) and environmental exploration (to identify career opportunities and barriers) (Guan et al., 2017), and may take place across the life-span as a developmental process (Cheung & Arnold, 2010). This developmental task is expected to have benefits in terms of enhancing the ability to make career decisions, including reduced indecision or decision-related anxiety (Lent et al., 2016). In other words, career exploration should result in more confidence for students as they come to realise what their own preferences are, and what options are available that align with those preferences. To the extent that career exploration identifies potential career barriers, we might also expect career exploration to inform adaptation of career strategies.

Betz and Voyten (1997) conducted a study of career decision-making self-efficacy, career indecision, and career exploration in a sample of 350 students. As might be expected, career decision-making self-efficacy was negatively related to career indecision. Interestingly, they reported that career indecision was in turn related to intentions to engage in career exploration for women, but not for men. More recently a three-wave longitudinal test of the CSM in 420 students found that exploratory intentions were positively predicted by outcome expectancies and career decision-making self-efficacy, and these intentions (alongside self-efficacy) then predicted exploratory behaviours (Lent et al., 2019). In contrast to the study by Betz and Voyten (1997), Lent et al. (2018) did not find that career indecision predicted exploration intentions. Instead, decisional anxiety was consistently negatively predicted by self-efficacy, while career decidedness was positively predicted at T2 by exploratory actions at T1, and at T3 by self-efficacy and social support measured at T2. Given the longitudinal design of the study by Lent et al. (2019), we may have greater confidence in their findings, which enabled the testing of reverse and reciprocal relationships. For example, the study was able to show that T2 self-efficacy was influenced by T1 decidedness—positively—and by T1 decisional anxiety—negatively. Lent and colleagues interpreted this as support for the existence of a feedback loop, with prior experiences informing self-efficacy, and thus shaping future behaviour.

Social support is a further, contextual factor expected to influence career exploration via enhanced self-efficacy (Lent et al., 2016). While some correlational studies have found a relationship between social support and students’ career exploration (e.g. Lent et al., 2016; Zhang & Huang, 2018), other longitudinal studies have failed to support this (Cheung & Arnold, 2010; Lent et al., 2019). Combined with the findings of Lent et al. (2019), we may perhaps expect support to influence confidence in making the right choices, rather than encouraging students to simply explore what choices are available. However, an important consideration may be the use that students make of support. Help-seeking behaviours often receive more attention in the context of career decisions.

6 Career Decision Making

It has been previously suggested that many students struggle to make career decisions (Tokar, Withrow, Hall, & Moradi, 2003) and thus universities are seen as playing a key role in providing students opportunities to improve in this career task (Esters & Retallick, 2013). One of the challenges is that people do vary in their tendency towards decisiveness; Jaensch, Hirschi, and Freund (2015) reported two three-wave longitudinal surveys that demonstrated a strong stable component of career indecision, which was associated with lower core self-evaluations (i.e. a generally negative view of self) and perceived career barriers. However, it should be noted that Jaensch et al. did not use a full-panel design, with only career indecision measured across all three time points. Individual differences in self-awareness may also play an important role in decision-making; in a study of 189 Chinese students, both goal commitment and occupational commitment were reported to mediate the relationship between emotional intelligence and career decision-making self-efficacy (Jiang, 2016). This was thought to reflect the role of self-awareness in helping students to form goals in which they are interested, leading to greater commitment.

Work-based or work-integrated learning is expected to have benefits for students’ skill development (Jackson, 2015). Esters and Retallick (2013) reported that students doing placements increased in both career decision self-efficacy and vocational identity. A similar effect was reported by Jackson and Wilton (2016) who compared career management competencies in those participating in placement with those who did not – although this effect was only found once the impact of current employment was controlled. Support has also been examined as a potential influence on career decision-making. Garcia, Restubog, Bordia, Bordia, and Roxas (2015) reported that parental and teacher support was positively associated with career decision-making self-efficacy, and that the latter was positively associated with career optimism. While this was a longitudinal study, only career optimism and demographic variables were measured at T2, which limits the rigour of the analysis. De Lange, Taris, Kompier, Houtman, and Bongers (2003) recommend the use of complete panel designs, in which the full range of measures are used at each point of data collection, to permit the identification of reverse or reciprocal causations.

As well as the provision of support, support-seeking has attracted attention in career research. In a study of 1176 Israeli students, perceptions of difficulty in making career decisions was associated with greater procrastination, slower speed and more effort in making decisions, and less interest in finding an ideal occupation (Vertsberger & Gati, 2015). Similarly, those who were more inclined to seek help from others tended to procrastinate, made slower decisions, and with greater effort. As has been reported elsewhere (e.g. Greenbank, 2011), Vertsberger and Gati found that their participants were most likely to approach friends and family for advice, despite identifying expertise as the most important consideration when seeking assistance. In another longitudinal study, differences in career indecision coping styles were associated with career decision difficulties and decision status (Lipshits-Braziler, Gati, & Tatar, 2015). Specifically, non-productive coping (e.g. helplessness and isolation) was associated with greater decision difficulties; those scoring more highly in this coping were more likely to remain undecided in their career choices. Support-seeking was also higher in those who remained undecided, whilst productive coping (e.g. problem-solving and information-seeking) was unrelated to career difficulty or to the final career decision status (i.e. decided vs. undecided).

7 Job Search

The job search process marks a key stage in the transition from HE to work, following career decisions, but also incorporating further decisions (e.g. identification of targets and strategies). Graduates may begin with high expectations, but these are often lowered as a result of repeated rejections (McKeown & Lindorff, 2011). Job search self-efficacy, i.e. confidence in one’s ability to effectively seek work, is an important predictor of job search behaviour in students and graduates (Lim, Lent, & Penn, 2016; Liu & Wang, 2014), likely via the mediator of job search intentions (Lim et al., 2016). Job search self-efficacy has been predicted by conscientiousness and social support (Lim et al., 2016), career adaptability (Guan et al., 2013), and perceived job search progress (Liu & Wang, 2014). Guan et al. (2013) reported that job search self-efficacy is associated with subsequent employment status; we may expect that this is because job search self-efficacy predicts job search behaviour, which is also associated with the number of job offers received (Liu & Wang, 2014). However, evidence from a longitudinal study suggests that higher job search self-efficacy is associated with increased job search effort in those students motivated to avoid failure but lower effort in those motivated by success (Sun, Song, & Lim, 2013). Thus, job search self-efficacy may not be a universal panacea for motivational interventions. Given that there is far more evidence in favour of the beneficial impact of self-efficacy, it may be helpful for replication studies to take place.

Da Motta Veiga and Gabriel (2016) reported a study of the dynamics of job searching in business students over the course of five weeks. They found that autonomous (i.e. intrinsic) motivation for job search declined during the search period before plateauing at the mid-point, whilst controlled motivation (i.e. a sense of necessity) remained stable. While autonomous motivation was positively associated with strategizing about job search (and thereby influenced job search effort), controlled motivation was initially negatively associated with strategizing and effort but became positively associated with strategizing later in the job search process. Although there has been research exploring student and graduate engagement with the job search process, there seems to be a lack of research on the broad strategies that they use. Previous research in the broader job search literature has distinguished between focused, exploratory, and haphazard job search strategies (Bonaccio, Gauvin, & Reeve, 2014; Crossley & Highhouse, 2005).

A focused job search sees the individual only seeking work in which they are interested and for which they are qualified (Crossley & Highhouse, 2005) and choices are planned and driven by criterion rather than emotions (Bonaccio et al., 2014). This search strategy is associated positively with job offers (Koen, Klehe, Vianen, Zikic, & Nauta, 2010), re-employment amongst the unemployed (De Battisti, Gilardi, Guglielmetti, & Siletti, 2016) and job satisfaction in obtained employment (Crossley & Highhouse, 2005). Those higher in perceived employability are more likely to report using a focused job search strategy (De Battisti et al., 2016), which suggests that outcome expectancies may prompt beneficial strategies. By contrast, haphazard job search is characterised by passive information gathering (e.g. relying on others to supply information), the setting of ill-defined goals, a tendency to react to external events and changing tactics without rationale (Crossley & Highhouse, 2005). In this approach, decisions are much more likely to be grounded in emotions (Bonaccio et al., 2014). Those adopting this approach are less likely to experience job satisfaction, because they may not realise what jobs would suit them, and because they might accept the first job offer made to them (Crossley & Highhouse, 2005). The exploratory job search strategy is one in which individuals are open to a number of job options, and is characterised by information search across a number of sources, including friends and colleagues (Crossley & Highhouse, 2005). This search strategy is positively associated with the receipt of job offers, although one longitudinal study suggested that an exploratory approach was negatively associated with subsequent reemployment quality (Koen et al., 2010).

8 Implications and Future Directions

Considerable attention has been directed toward student engagement with employability. There are some limitations to the literature, attention to which might help enhance our understanding of the motivational processes underpinning employability. Much of the published research is based upon correlational survey designs. This limits the kind of causal claims that can be supported (de Lange et al., 2003). There have been some longitudinal studies, but more are needed. It would also be useful for researchers to publish evaluations of interventions, for example using randomised controlled trials to provide greater confidence in causal claims. There is a rich tradition of experimental research in the goal-setting literature (Locke & Latham, 2013) which could be applied to the challenge of promoting student employability.

One possible intervention is to provide training (Kamau & Spong, 2015), which could involve the setting of high goals (Clements & Kamau, 2018). The impact of self-efficacy on various stages of career planning (exploration, decision-making, and job search) is one of the most consistently supported findings within the literature. There is some evidence that career management training can help enhance such self-efficacy (Jackson & Wilton, 2016) and reduce negative thoughts about career choice (Belser, Prescod, Daire, Dagley, & Young, 2018). As noted above, feedback is an important contributor to self-efficacy (Bandura, 1977; Ireland & Lent, 2018), as well as leading to the setting of more challenging goals (Donovan, 2009). However, we might also consider what kind of goals should be set. So far, the employability literature does not seem to have addressed this question. The broader goal-setting literature suggests that when tasks are new and complex, a specific, challenging performance goal may be detrimental to achievement as compared to a learning goal (Locke & Latham, 2004). In other words, when acquiring a new skill, concern over end results is less helpful than learning more about how to perform that skill. Given that many HE students will be new to career self-management, we should direct their attention initially to learning how to evaluate self, search for career options, and so on. Providing feedback on specific skill attainment should enhance confidence and promote career exploration and career decision-making. Encouraging students to see struggle as normal and to see failure as a learning opportunity should aid them in remaining engaged during a process that can be discouraging (Hu, Hood, & Creed, 2017).

As students gain greater competence in career self-management, they can be encouraged to set more concrete goals, e.g. for meeting a specified number of recruiters to discuss employment opportunities. Meta-analysis suggests that job search interventions that address both job skills (e.g. search, self-presentation) and motivation (e.g. goal-setting) are more effective than those interventions that address only one of these factors (Liu, Huang, & Wang, 2014). Other interventions might include mentoring. Career mentoring has been associated with increased career planning and job search intentions, and reductions in negative job search behaviours such as procrastination, failing to network, and impulsively accepting the first job offer that is received (Renn, Steinbauer, Taylor, & Detwiler, 2014). Further, the provision of mentoring may help supply students and graduates with relevant feedback for skill acquisition. Although research has shown links between some stages of the career planning process, e.g. career exploration’s association with decision-making self-efficacy, it would be useful to examine the career planning process from career exploration to job search.

There has been a lack of research exploring job search strategies in student and graduate samples. It seems reasonable to expect that students who have appropriately engaged in career exploration, because of increased career decision-making self-efficacy, would be more likely to engage in a focused job-search strategy. Given the criterion-based nature of a focused job search strategy, we might also expect those adopting this strategy to be more inclined to set high goals, i.e. challenging, specific, and achievable (Locke & Latham, 1990), which should result in greater motivation and thus job search intensity, which has been shown to influence the number of job offers received. By contrast, inadequate engagement in career exploration, e.g. in terms of the time spent on this process or low effort, might be associated with later adoption of a haphazard job search strategy.

As well as further exploring motivational processes in employability for students and graduates as a larger group, it will also be helpful to examine variations in the journey from exploration to job attainment. For example, SCCT points to the role of perceived barriers in shaping career choices (Brown & Lent, 1996). Research has demonstrated the existence of barriers for marginalised groups such as women and people of ethnic minority background in part due to consciousness of negative stereotypes (Owuamalam & Zagefka, 2014). Further, the lack of transparency in job selection processes may contribute to perceptions that discrimination plays a role in hiring decisions (Clements, 2018). More attention is needed to address these barriers, including identifying the most appropriate interventions. As noted early in this chapter, motivation-based interventions may address behaviour in individuals, but these are not able to address environmental challenges. There is therefore also a need for examining structural inequality in the environment, which may contribute to self-efficacy via feedback processes. In examining motivation in disadvantaged students and graduates, I therefore suggest it is important to also examine the behaviour of employers who make hiring decisions—an important source of feedback.

9 Conclusion

While it is not the aim of this chapter to claim that motivating students is a “magic bullet” that will address the employability agenda in full, it can be argued that motivation theory and research offers useful insights into ways to make progress. The strongest findings in the literature identify the role of self-efficacy, which should direct our attention towards interventions that best enable students to experience mastery of challenging tasks. We need to consider too the role of failure, given that this is a potential outcome of challenging activities, and in the case of job search, likely to be frequent. Some research on learning goals and growth mind-set suggest that these are qualities we should encourage, for example by identifying failure as a normal part of career pursuit. To encourage engagement with employability, we therefore should consider how students may be given opportunities for mastering career management skills and gaining feedback, e.g. via training or mentorship. We should also consider the psychological role that perceived barriers play in helping to perpetuate disadvantage for particular groups of students. Motivation theory and research often direct our attention to internal processes, but we should consider motivation as an interaction between the individual and their environment. Further attention is therefore needed to identify productive ways of helping students overcome barriers and challenging those with the influence to address such structural inequality.