Understanding pedagogical essentials of employability embedded curricula for business school undergraduates: a multi-generational cohort perspective

ABSTRACT The concepts of employability and generational effects are emerging disciplines within the context of business education management research, but their complementary role in curriculum development and enrichment is yet to be explored. The study employs a work-related employability course for a business school undergraduate cohort (N = 267) consisting of various generations to examine the generational effects from the student stakeholder perspective of work-related learning outcomes in employability embedded curricula. This research shows the differences in students’ perceptions based on age generations as shown to be marked by the Generations X, Y and Z, which also produces a different inter-generational learning opportunity with distinct characteristics. We established that undergraduate multi-generational cohorts expect contextualised employability-related teaching to accompany designing and embedding work-related employability curricula. We show that an employability embedded curriculum is likely to improve students’ employability decisions when different inter-generational learning environments are factored into programme development, delivery, and assessment.


Introduction
The recent shift in higher education stakeholder expectations, particularly demands by the business sector, has placed increasing pressure on higher education institutions (HEIs) to produce employable graduates. Thus, policies in higher education globally have shown an increasing preoccupation with employability and with equating success in higher education with graduate employability (Tymon, 2013). Meanwhile, there is an emerging trend in the age diversity of students found in the traditional degree-awarding programmes, which is posing a multifaceted challenge to HEIs (Williams, Matt, & O'Reilly, 2014). The inclusion of diverse age groups in the cohorts, each with their own needs, expectations, and learning abilities, challenges HEIs pedagogically since it raises the need to offer alternative learning possibilities for some participants depending on the learning situation (Franz & Scheunpflug, 2016). For the HEIs, their overarching view of what students attain at the end of their university education depends on the content of the HE provision and students' previous experiences, including their school education and everyday lives (McCowan et al., 2016). Yorke (2006, p. 14) argued that the graduate employability skill set is derived from the ways in which students learn from their experiences, both as individuals and in association with others, in a diverse and changing society. In addition, Del Campo, Navallas, and Camacho-Miñano (2016) posited that students' perceptions affect their learning experiences, as the learning process is an interactive system of different variables, including the learning environment and student characteristics. Williams et al. (2014) argued that the current increase in the higher education student population has brought diversity in age and educational background with their attendant generational learning styles. Honey and Mumford (1992, p. 1) described these learning styles as 'a description of the attitudes and behaviours which determine an individual's preferred way of learning'.
In pursuit of implementing the learning of employability skills, many HEIs have adapted or designed employability embedded courses. Indeed, Pegg, Waldock, Hendy-Isaac, and Lawton (2012) reported that structured work experience and work-based learning approaches are key tools in developing both initial and continuing employment opportunities for graduates. Other studies further called for modifications in pedagogy for students' employability and their associated learning styles (Yawson, Yamoah, Sarpong, & Abban-Ampiah, 2020). More importantly, Barnes, Presziosi, and Gooden (2004) reported that 'learning styles change from generation to generation requiring faster speed, a more visual approach and greater active engagement' (p.21). Prensky (2001aPrensky ( , 2001b) argued that learners today think and process information fundamentally differently from their predecessors (preceding generations) as a result of being surrounded by new technology, which conditions them. Helsper and Eynon (2010) contributed to the debate positing that other factors, such as the breadth of use, experience, gender, and educational levels, are also important predictors of advanced interaction with technology in the current learning environment, which may be more important than the generational cohort.
In the literature of generational studies, there is a canon of knowledge derived from and applied in psychology and marketing by demographers, who categorize and contextualize behaviour. In this contextualization, it is posited that there are differences in values, needs, preferences, characteristics, and behaviours which are conditioned by the age generations (Howe & Strauss, 2003;Howe & Strauss., 1993, 2000Reeves & Oh, 2008;Strauss & Howe, 1991. Therefore, students' learning experiences would be conditioned by their age generation, as their learning styles change from generation to generation (Barnes et al., 2004). This has, however, not been researched in a multiple generational cohort context especially in an African context.
We, therefore, look to study these generational effects in another sparsely researched context of embedding work-related learning in developing employability in a multiple generational cohort of a higher education degree programme. It is important to note that, generally, only a few studies have been conducted on generational differences in higher education targeting traditional degree-awarding institutions and addressing academic and student affairs issues (Dziuban, Moskal, & Hartman, 2005;Giunta, 2017;Howe & Strauss, 2003;Strauss & Howe, 2007) and continuing higher education (Sandeen, 2008). However, Sánchez. and Kaplan (2014) argued that multigenerational classrooms in formal higher education constitute windows of opportunity to rethink the practice of teaching as far as they may become venues for triggering processes of intergenerational learning with its attendant complexities. Indeed, employability and intergenerational concepts have been researched from various perspectives (Franz & Scheunpflug, 2016;Pstross et al., 2017;Sánchez. & Kaplan, 2014); however, their complementary role in educational management has not been explored. This study seeks to contribute research insights to close the research gap. The African experience suggests that considering the enormity of the concerns for employability in these countries, graduate employability skills programmes are not sufficient (British Council, 2015). As a result, many HEIs are being urged to develop employability skills for their students; this is consistent with, but lagging behind global trends (McCowan et al., 2016). Nonetheless, there is sparse research on interventions in HEIs on employability programmes and their effectiveness in African countries. In situations where some research has been conducted, the views of undergraduates, the recipients of the employability development, are not well known (Harry, Chinyamurindi, & Mjoli, 2018;Tymon, 2013). However, increasing the understanding of the educational practitioner about the varied student population entering higher education provides for the establishment of stronger educational practices (Williams et al., 2014). Sánchez. and Kaplan (2014) argued that a generational approach enriches the understanding of teaching and learning practices in higher education beyond chronological age because it takes into consideration the existence of more facets of individual social identities. This study seeks to make a contribution to this area by capturing the perceptions of student stakeholders.
This paper contributes to the literature on employability and intergenerational effects in three ways. Firstly, it contributes by demonstrating that differences in students' perceptions based on age generations are marked by the social categorisations of Generations X, Y and Z that produces a different inter-generational learning environment with distinct characteristics. The second contribution is the suggestion that undergraduate multi-generational cohorts expect contextualised employability-related teaching to accompany designing and embedding work-related employability curricula. The third contribution is a proposition that an employability embedded curriculum is likely to improve student career motivations in employability decisions when different inter-generational learning environments with distinct characteristics are factored into programme development, delivery, and assessment.
The rest of the paper is organized as follows. The review of the existing literature and the salient research questions are presented. Then, the methodology, in particular the sample, the design, the method, the procedure, and the instrument used to gather evidence are elaborated upon. Finally, the empirical results are presented and discussed, and the paper concludes by highlighting its theoretical and practical implications, the limitations of the research, and possible future research directions.

Employability
The literature on employability and employment states clearly that they are different concepts (AdvanceHE, 2015;Artess, Hooley, & Mellors-Bourne, 2017;Knight & Yorke, 2004;Owens. & Tibby., 2012;Yorke, 2010). Artess et al. (2017) noted that the debates on the meaning and definition of employability are not simply questions of academic interest but are of interest to a wide variety of stakeholders including governments, graduate employers, higher education providers (HEPs), and, of course, students and graduates.
The main definitions of employability have remained those of Bowden, Hart, King, Trigwell, and Watts (2000) and Knight and Yorke (2003). Bowden et al. (2000) defined employability as a set of graduate attributes, that is, the qualities, skills, and understandings that a university community agrees its students would desirably develop during their time at the institution and, consequently, that shape the contribution they are able to make to their profession and as a citizen. The Knight and Yorke definition, however, is widely quoted (Cole & Tibby, 2013); it considers employability as a set of achievementsskills, understandings, and personal attributes -that makes graduates more likely to gain employment and be successful in their chosen occupations, which benefits themselves, the workforce, the community, and the economy (Yorke, 2006, p. 8). Dacre Pool and Sewell (2007) redefined employability as having a set of skills, knowledge, understanding, and personal attributes that make a person more likely to choose, secure, and retain occupations in which they can be satisfied and successful. These definitions suggest that there is a close relationship between employability and good learning. Cole and Tibby (2013) stated that employability is embedded as providing the opportunities for students to develop the knowledge, skills, experiences, behaviours, attributes, achievements and attitudes to enable them as graduates to make successful transitions and contributions, thus benefitting them, the economy, and their communities. Since most of these definitions require the possession of skills and personal attributes, it is therefore said that a student exhibits employability in respect of a job if he or she can demonstrate a set of achievements relevant to that job (Yorke, 2006). However, Yorke (2006, p. 8) asserted that the definitions are probabilistic, as there is no certainty that the possession of a range of desirable characteristics will convert employability into employment. Further, higher education awards describe the graduate's past performance, but some achievements vital for workplace success might not be covered. In addition, the choice of occupation is, for many graduates, likely to be constrained. They may have to accept that their first choice of a post is not realistic in the prevailing circumstances, and it may not be possible to maximise the benefits to all interested parties.
The extant literature acknowledges that both the complexity of employability and the variety that exists in curricula in higher education means that no single ideal prescription for the embedding of employability can be provided (Eden, 2014;Knight & Yorke, 2003. This view is clearly demonstrated, as it is widespread in the literature (Cole & Tibby, 2013;Hooley, 2017;Pegg et al., 2012;Yorke, 2006). However, while a curriculum may facilitate the development of the prerequisites, it may not guarantee it (Yorke, 2010). Therefore, Yorke (2006) cautioned that it is inappropriate to assume that students are highly employable on the basis of curricular provision alone even though employers expect graduates to have employability skills (Artess et al., 2017;Cole & Tibby, 2013;Harry et al., 2018). In addition, the condition of local, national, and international labour markets is a powerful determinant of graduates' employment success (Brown, Hesketh, & Williams, 2002).
To embed employability in higher education, Knight and Yorke (2003) proposed the USEM model of employability, one of the best known and most respected in the area of employability. However, Dacre Pool and Sewell (2007) recounted that the USEM model has the weakness of not being easily accessible to non-experts in the field for explaining the concept of employability. They, therefore, proposed the CareerEDGE model of graduate employability. This model is acknowledged to be valuable in explaining the concept of employability to those new to the subject, including students and stakeholders, and in being appealing to academics (Cole & Tibby, 2013). Pegg et al. (2012) recognised that there are many forms of work-based/work-related learning; a list of them includes integrated practice, company projects, residential activities, 'live' projects and mentoring and apprenticeship schemes. They stated that these offer opportunities for different disciplines to build accreditation of 'learning from work' into their programmes in an appropriate context. They also noted that courses embedded with work-related employability learning give adequate consideration to curricula and pedagogy. The multiple dimensional nature of employability has enabled innovations in extensions by including the curriculum of enterprise and entrepreneurial skills and embedding work-based/work-related learning into the curriculum to include the award of academic credit for employability skills development. Pegg et al. (2012) posits that Even when employability skills development has been successfully built into the curriculum, and suitable learning, teaching and assessment vehicles identified, success by any measure is still dependent on the effectiveness of the teaching practice. Teaching 'employability' well requires some distinctive skills and attributes, including an understanding of how people learn to develop such skills and the ability to contextualise employability-related teaching. (p.42)

Pedagogy for employability
The literature on employability cautions that the context is so important in the pedagogical approach to delivery that generic guidance on successful methods is rare.

The generations
The concept of a generation has been conceptualised in three different ways, that is, from genealogical, pedagogical, and historical-sociological perspectives (Franz & Scheunpflug, 2016). This study takes the historical-sociological perspective, referring to different groups in a society. We, therefore, define a generation as a cohort of people born within a particular period of time. It is an interval of approximately 20 years in length (Sandeen, 2008). Strauss and Howe (1991) stated that it is a social categorization, which offers a safer basis for personality generalization than other social categories. Researchers recognize distinct differences among generations, which they call 'peer personality'. Howe and Strauss. (2000) termed this as generational persona and defined it as 'a distinctly human and variable creation embodying attitudes about family life, gender roles, institutions, politics, religion, culture, lifestyle, and the future' (pp.40-41). Sandeen (2008) posited that if we knew more about this peer personality, we might perform better at developing and delivering effective educational programs. Also, Williams et al. (2014), in summarizing research in this area, recounted that, first, 'students construct knowledge by organizing and making meaning of their experiences,' and second 'that this construction takes place in the context of their evolving assumptions about knowledge itself and the students' role in creating it' (Baxter Magolda, 1999, p. 6). It is through these 'self-authoring' (Kolb & Kolb, 2005, p. 209) experiences that each of these generational groups differs from other generational groups (p.36).
The generations, their characteristics and effects have been a major point of research for business professionals, especially marketers (Giunta, 2017), but not much work has been done by academics to research issues in business education. Specifically, this topic of the perceptions of students from different generations in business education has not received much scholarly attention (Giunta, 2017;Sandeen, 2008). Educators have been known to segment students by age, gender, and interest, among other factors, to help drive decisions about program content, marketing messages, and channels (Coomes & DeBard, 2004;Sandeen, 2008). However, this study seeks to examine the perceptions of multi-generational student stakeholders about work-related employability embedded courses, which have been known to be affected by differences in how people learn, as well as the individual's age, values, needs, preferences, and behaviours.
This generation were the first to grow up with computers. They generally want to build more portable and more resilient careers than their parents. Members in this group are not loyal to a single employer but see job changing as necessary and advantageous. They are family-oriented, and therefore, value and protect their leisure time. In education, they appreciate feedback and generally want information about their progress. Generation X appreciate the opportunity for professional development, and some employers may use learning opportunities as a retention device for Generation X employees. • Generation Y (1980-1995) (Millennials) -These are students born between 1980 and 1995. They are also called the Millennials. This generation grew up with computers; they also experienced the rapid adoption of the internet, cell phones, and other mobile devices (Monaco & Martin, 2007;Sandeen, 2008). They are highly networked, connected generation and tend to be completely immersed in technology (Frand, 2000). The concern for quality education increased in this generation, and many millennials began their preparation for higher education earlier than had the preceding generation.
They are very skilful at multi-tasking and tend to be very career-oriented and to expect rapid advancement. They tend not to concentrate on one job or profession, which leads to a form of flexibility and continuous changing of jobs. Millennials also appreciate feedback, having been graded, evaluated, and ranked throughout their lives. Also, due to the intense focus on learning and achieving throughout their lives, millennials are likely to appreciate continuous learning opportunities (Sandeen, 2008;Strauss & Howe, 2007). Howe and Strauss. (2000) identified seven general characteristics of this generation which they considered to be significant: sheltered, team-oriented, confident and highly optimistic, pressured, keen to achieve, and conventional.
• Generation Z (1996 − 2003) (The iGeneration) -This refers to students born between 1996 and 2003. They have many labels including iGeneration, Internet Generation, Computer Generation, and Net Natives among others (Giunta, 2017). This multiple labelling is due to their compatibility and dependency on computer technology (Koutropoulos, 2011;Slavin, 2014). They have no memory of pre-Internet history, and so they believe computer technology is commonplace. They are very active in electronic communities, building communities by wanting to be heard, and actively participating in what is around them and leading. Giunta (2017) noted that they have short attention spans, and they tend to be frequent bloggers and to enjoy digital publishing. Compared to their older counterparts, they plan to get educated and to start working earlier, and they prefer the integration of practical experiences within their programme of study. This generation is also described as outspoken, idealistic, action-oriented, and optimistic, and they are the first to use emerging technologies.
It is important to note that, though these values often drive an individual's behaviours, while not all members of a generation will share these same values and behaviours, it is expected that each generation will show similar consumer behaviours among themselves. However, in the education literature, the current emergence of the four generations in undergraduate programmes produces a unique context in the learning process, as the generations learn from each other, with each other, and about each other through observation, imitation, and modelling in a multigenerational setting of intergenerational learning (Corrigan, Mcnamara, & O'Hara, 2013;Franz & Scheunpflug, 2016). Intergenerational learning is a concept defined as 'the reciprocal exchange of knowledge between people of all ages so they can learn together, and learn from each other and those in a variety of sectors' (Dantzer, Keogh, Sloan, & Zekely, 2012, p. 14). Students engaging in intergenerational learning have been found to have gained knowledge, competences, and skills which contributed to both their personal and professional development. It is considered an excellent methodology for enabling transformative education (Corrigan et al., 2013) and an emerging pedagogy that facilitates knowledge transfer and understanding between generations (Corrigan, 2012).

Research questions
This paper examines the generational effects of students' perceptions of work-related learning experiences in employability embedded courses for undergraduates. Research indicates that teaching work-related employability embedded courses require some distinctive skills and attributes, including an understanding of how people learn to develop such skills and the ability to contextualise employability-related teaching.
In a cohort of multiple generations, how people learn is related to their career motivations, which in turn, are shaped by the learner's learning experiences and prior knowledge, and their expectations of and attitudes to the forthcoming learning event (Stuart & Holmes, 1982). Also, key factors of the learning process include the amount of knowledge the learner already has in the subject area, the level of interest in and the need to acquire the learning, the degree to which the learner is ready to accept the responsibility for their learning, and the learner's degree of skill in learning. Therefore, students' learning experiences would be conditioned by their age generation, as their learning styles change from generation to generation (Barnes et al., 2004;Yawson & Yamoah, 2021). Little (2005) posited that these factors are also related to students' subject of study and their gender. Coomes and DeBard (2004) reported relationships between gender, race, sexual orientation, and identity in career motivations. Sandeen (2008) established that in an undergraduate cohort of students, most part-time students are student workers with a variety of work experience. However, McDowell (1993) stated that in undergraduate employability courses, some part-time students see the explicit emphasis on skills development as a waste of time and resent having to demonstrate abilities they use in their everyday work. Also, part-time students, according to Little (2005), may well be looking to gain career advancement within (or outside of) their current employment situation as a result of their higher education experiences or to move into a different occupation altogether. Such considerations may well affect how they engage with the taught curriculum in terms of developing both subject-specific expertise and more general personal attributes.
Therefore, we envisage measuring satisfaction characteristics, such as the perceived utility, opinion, difficulty, and satisfaction of the course content and overall satisfaction (Artess et al., 2017;Idaka & Uzoechi, 2016;Paadi, 2014). Also, we seek to examine the generational characteristics affecting these factors, such as gender, work experience, student status (full-time students and student workers), course of study, student expectations, course content, course delivery and accessibility, and the utility of the course (Artess et al., 2017;Idaka & Uzoechi, 2016;Paadi, 2014;Yawson & Yamoah, 2021). Thus, we expect to evaluate student stakeholder perceptions of work-related employability embedded courses. Little (2005) stated that students' reasons for studying varied depending on the subject of study and the individual's age amongst others. This difference is marked by variations, with the majority of younger students (those aged under 30) citing mainly career-based reasons and the majority of older students (aged over 49) citing personal interest. Therefore, this sensitivity to generational differences is particularly relevant for this research to consider the perceptions of students born in the three main generations, namely, Generation X, Generation Y (Millennials) and Generation Z (iGeneration) (Coomes & DeBard, 2004). Also, students have been known to have different perceptions of employability (Harry et al., 2018). However, they have not been investigated across the generations and in a developing country setting. Based on the above premise, the research questions for the study are as follows: RQ1 -Do generational differences affect student stakeholder perceptions of work-related employability embedded courses in the undergraduate curriculum?
RQ2 -What are the student stakeholder perceptions of work-related employability embedded courses in the undergraduate curriculum of generational cohorts? RQ3 -What are the conditions that influence students' generational perceptions of workrelated employability embedded courses in the undergraduate curriculum?
The answers to these research questions could contribute to the understanding of this issues and could extend knowledge in the area of employability and generational effects, with programme design and pedagogical implications for higher education stakeholders (lecturers, curriculum designers, career development and student affairs staff) involved in teaching and learning.

The context of the research -the practitioners' forum course
The Practitioners' Forum Course is a work-related employability embedded course in an undergraduate programme designed as an innovation to include enterprise and entrepreneurial skills into the curriculum. The course is embedded using the extended Dacre Pool and Sewell (2007) CareerEDGE model of Graduate Employability in business engagement for learning mode (AdvanceHE, 2017; Cole & Tibby, 2013) and delivered in a blended learning environment (Pegg et al., 2012). The Practitioners' Forum Course offers professional development for students across all levels of the undergraduate programme (Pegg et al., 2012;Yorke, 2010) by providing opportunities for learning from industry experts through all functional areas of business and, in this way, integrating practice into theory and creating an understanding of the workings of organisations. This research is based on two courses that each lasting a semester. The courses were delivered through the learning management system with video recordings from selected industry experts. The students were from two campuses of a tertiary institution. As with the extended CareerEDGE modelled course, the learning in career development, experience, subject-specific knowledge and skills, generic skills, and emotional intelligence is evaluated in a reflective report at the end of the course (Cole & Tibby, 2013;Owens. & Tibby., 2012). Reflection is used as a device to help students manage and assimilate their employability learning (Artess et al., 2017).

Participants
The participants, who were from the first-year undergraduate business school cohort of a tertiary institution based in Accra, Ghana, had completed a newly introduced mandatory employability embedded course in the 2018/2019 academic year. The participants comprised a population of 267 students who registered for the first year of the new bachelors' programme of the Business School from two different campuses, with 24 from the satellite campus and 243 from the main campus. Of these, 42 students registered for the Practitioners' Forum Course I, and 225 registered for the Practitioners' Forum Course II. Of the 267 students, 156 (58.4%) were females and 111 (41.6%) were males. In total, 262 students (42 from the Practitioners' Forum Course I and 220 from the Practitioners' Forum Course II) submitted their surveys, out of which 250 responses were usable. The responses were provided voluntarily, and respondents were informed of the possibility of their data being used for publication. Ethical approval was met as per the Institute's ethical guidelines.

Procedure
Two courses of the Practitioners' Forum Course, as described earlier, were held for firstyear undergraduate students in the Business School of a tertiary institution. Students were then required to watch videos of presentations from industry practitioners and to interact with them on an electronic learning management system. They were later asked to submit personal reflective reports for grading at the end of the semester. The questionnaire was then administered electronically to students as a Satisfaction Survey on another electronic platform, which made it clear that it was not part of the course assignment to minimize students' perception that they were obliged to complete the questionnaire. Students' grades were also not part of this research. All analysis was done using SPSS 23 software.

Instrument
The study instrument was derived from a larger survey for evaluating the learning on the learning management system. 1 The survey instrument comprises various sections covering the demographic information, learning experience, and learning environment. The research was explained to students via email, and the purpose and the voluntary nature of the research, as well as anonymity issues, were made explicit on the first page of the survey instrument. The portion of the study instrument relevant for this study dealt with participant satisfaction under learning experience, which utilized a set of nine items on participants' perceptions adapted from Del Campo et al. (2016). In addition, there were items on gender, programme time, student status, work experience, and age groups categorized into the generations.
The items from Del Campo et al. (2016) ask for information about participants' satisfaction with the Practitioners' Forum Course, their initial expectations, the pros and cons of the course, the utility of the course, the difficulty of the content of the course; participants' description of the course, problems encountered with the course, and overall satisfaction. We decided to measure them using Likert-type items on a 7-point scale to ascertain the level of personal perceptions. Additionally, items on the preferred method of delivery and an open-ended question on topics participants would prefer to study in the course were included.
The instrument included an item on gender since the literature indicated there were gender differences in the generational characteristics (Cambiano, De Vore, & Harvey, 2001). Programme time, which is the time students have their course of study at the institute, that is, day or evening, was added to elicit the differences between the time of the programme and the status of the students, since most of the students termed as parttime/student workers followed an evening programme, but there were other full-time students in the cohort understudy who also had evening programmes (Little, 2005;McDowell, 1993). An item on work experience was also included (McDowell, 1993). The three main generations were operationalized as Generation X (40-54 years), Generation Y (Millennials) (24-39 years), and Generation Z (iGeneration) (16-23 years) (Edelman/ StrategyOne, 2010; Giunta, 2017;Wendover, 2002). The variables were grouped as categorical, categorical response, and quantitative variables.

Reliability and validity
The study adopted the use of single global formative items (Bergkvist & Rossiter, 2007;Ellwart & Konradt, 2011) adapted from the literature (Del Campo et al., 2016). Therefore, as with all single-item measures, no calculations of internal consistency could be computed. The only alternative methods for assessing the reliability of the data of single-item measures would be through the use of test-retest or equivalent-forms approaches (Nagy, 2002). However, both of these approaches would have required students to provide their names on the surveys, and, therefore, would have violated confidentiality and may have damaged the credibility of the responses. As traditional measures of validity are not appropriate for formative constructs (Chin, 1998), the validity of the formative constructs was evaluated as follows. Face validity was achieved by an in-depth literature review, which was conducted to identify the relevant concepts related to factors influencing business management education in a multi-generational context. Content validity in this research was achieved by making sure all the research objectives were reflected in the questionnaire (Babbie & Mouton., 2007). Construct validity and criterion validity were guided by the literature review informing the understanding of the adapted variables, which are included in the instrument and which were used to formulate single global statements from the literature (Del Campo et al., 2016) for each concrete construct (Onwuegbuzie et al., 2007;Rossiter, 2002). The literature (Bergkvist & Rossiter, 2007;Nagy, 2002) also shows that single-item scales can perform just as well as multi-item scales without the added cost of respondent fatigue and response bias. Thus, for reliability, organizational research showed single-item scales to provide reliable and valid measures (e.g., Bergkvist & Rossiter, 2007;Nagy, 2002;Wanous, Reichers, & Hudy, 1997). For this study, reliability was achieved by discussing the instruments with experts and pilot testing the instrument.

Sample characteristics
There were 262 responses from 267 participants, giving a response rate of 98%, which is very high even though the survey was made available on a different platform from the students' learning platform, and students were informed of the voluntary nature of the survey. However, this may be due to lecturers' expectation of students to complete the questionnaire, which could only be minimised in the research design. Out of this, a sample of 250 usable responses was obtained. The sample consisted of 60.8% females and 39.2% males. For the social categorisations of birth generations, the sample consisted of 31.6% Generation Z (IGeneration) (16-23 yrs); 60.8% Generation Y (Millennials) (24-39 yrs); 7.6% Generation X (40-54 yrs). Table 1 in the appendix shows the descriptive statistics of the sample. From a population of 20 Baby Boomers (above 55 years), there was only one usable respondent and thus this was treated as underrepresentation, and the responses were excluded from the analysis. This resulted in the non-representation of the Baby Boomers in the analysis.
Since the data came from two courses in the same academic year, a homogeneity test was conducted on the quantitative variables using the Mann-Whitney U test (Hair, Black, Babin, & Anderson, 2010) at the 0.05 significance level. It was determined that for the set of variables, there were no systematic differences between the Practitioners' Forum I and Practitioners' Forum II survey results. Thus, we were able to analyse our responses as a homogeneous sample. For the purpose of analysis, all the variables were put into three categories as stated earlier. The first is the single nominal categorical variables, which is made up of Campus of Student, Gender, Generation, Programme Time, Student's Status, Course of Study, and Student's Work Experience. The second category is the single nominal categorical response variables, which is made up of Initial Expectations, Perception of the Course, Problems Encountered with Course Content, and Preference of Mode of Delivery (Mode of delivery). The third category is the ordinal quantitative response variables, which includes Satisfaction with Course Content, Personal Opinion about the Course, Usefulness of the Course to Study Programme (Utility), Difficulty of the Course Content (Difficulty), and Rating of Total Satisfaction (Overall Satisfaction).
The descriptive characteristics of the quantitative variables were assessed since these variables were adapted from the literature (Del Campo et al., 2016); they are formative variables measured on a scale of 1 to 7. The variable Satisfaction with Course Content had a mean of 5.63 (1.34) and a median of 6.00; Personal Opinion about the Course had a mean of 6.07 (1.08) and a median of 6.00; Usefulness of the Course to Study (Utility) had a mean of 5.91(1.11) and a median of 6.00; Difficulty of the Course Content (Difficulty) had a mean of 4.24 (1.31) and a median of 4.00; and Rating of Total Satisfaction (Overall Satisfaction) a mean of 5.61(1.21) and a median of 6.00. Also, all correlations were below 0.8 indicating that they are independent, as shown in Table 2. Normality in data is often a conventional assumption in the estimation process (Hair et al., 2010). Data distributions with either a highly skewed nature or with high kurtosis are indicative of non-normality, which has random effects on specification or estimation. Therefore, an attempt was made to assess the normality of the data. The categorical items were assumed not to be normally distributed, as they have skewness values ranging from −2.051 to −0.091 and kurtosis between +0.067 to +5.088 (as shown in Table 2) which fall outside the +2 to −2 range recommended for ordered categorical data (Hair et al., 2010). We, therefore, proceeded with analysis techniques that are robust for non-normal data.

Do generational differences affect student stakeholder perceptions of work-related employability embedded courses in the undergraduate curriculum?
There were general differences in the means of the quantitative variables across the three generations with almost the same medians and varied standard deviations as shown in Table 2. Generation Y had the highest mean for satisfaction with the course content, followed by Generation X and Generation Z. Thus, Generation Y students reported the highest satisfaction with the course content followed by Generation X and Generation Z. However, Generation X had the highest mean for the importance of the course in their personal opinion, followed by Generation Z and Generation Y. Therefore, Generation X placed the highest importance on the course, followed by Generation Z and Generation Y.
Also, Generation X recorded the highest mean rating for the usefulness of the employability course to their course of study, followed by Generation Y and Generation Z. Therefore, Generation X found the course most useful to their study programme among the three generations. However, Generation X had the most difficulty with the course content with the highest mean, followed by Generation Y and Generation Z. In contrast, Generation X reported the highest mean rating of total satisfaction with the course, followed by Generation Y and Generation Z. These values will be tested further.

What are the student stakeholder perceptions of work-related employability embedded courses in the undergraduate curriculum of generational cohorts?
As an initial test, a Mann-Whitney U test was run, at a 0.05 significance level, to test for statistically significant differences in all the variables across the generations. The distribution of gender is the same across the generations. There was a statistically significant difference for students' campus across the generations (Kruskal-Wallis test p-value < 0.001), with the greatest difference between Generation Z and Generation Y (Adj Sig.< 0.001). The distribution of the programme time was also different statistically across Generation Z (Kruskal-Wallis test p-value < 0.001) and Generation Y (Adj. Sig. < 0.001). Generation Z were spread across the day and evening programmes and Generation Y in the evening programme. This is also repeated in the relationship between Generation Z and Generation X (Adj. Sig. < 0.001).
The distribution of student status across the generations was statistically different (Kruskal-Wallis test p-value < 0.001) between Generation Z and Generation Y (Adj. Sig < 0.001). Generation Z were spread across full-time and part-time students, and Generation Y were mainly student workers. This is also repeated in the relationship between Generation Z and Generation X (40-54 years) (Adj. Sig < 0.001). Also, the distribution of students' work experience across the generations was statistically different (Kruskal-Wallis test p-value < 0.001) with all three generations being statistically different (Adj. Sig < 0.001). As expected, the students in Generation Z had no work experience with about three having work experience of 1 year to 5 years. The Generation Y students had a median of up to 5 years and the Generation X students had a median of more than 10 years.
A Kruskal-Wallis test was run at the 0.05 significance level to test for statistically significant differences in the generations in the categorical response and quantitative variables. There was a statistically significant difference between the generations regarding the preference of the mode of delivery (Kruskal-Wallis test p-value = 0.042), with the difference between Generation Z and Generation X (adjusted using the Bonferroni correction Adj Sig. = 0.036). Generation X preferred the mode of delivery better than Generation Z. This may be due to their protection of leisure time since the blended learning environment eliminates most of the need to attend lectures. Also, there were no differences in Initial Expectations, Perceptions of the Course, and Problems Encountered with Course Content.
For the quantitative variables, there was a statistically significant difference between the generations in the rating of total satisfaction (overall satisfaction) with the course (Kruskal-Wallis test p-value = 0.003) with the difference between Generation Z and Generation X (Adj Sig. = 0.003). Generation X had a better total satisfaction than Generation Z. Also, there were no differences in Satisfaction with Course Content, Personal Opinions, Usefulness of the Course to the Study Programme, and Difficulty of the Course Content.
In summary, there is evidence of a range of differences in students' opinions of course content, the usefulness of a course to study programme, and overall satisfaction of employability embedded courses across the three generations.

What are the conditions that influence students' generational perceptions of workrelated employability embedded courses in the undergraduate curriculum?
This section presents the conditions that influence students' perceptions of work-related employability embedded courses in the three social generational categorisations (Generations X, Y and Z). First, the conditions that influence Generation X are (1) Course of Study, (2) Problems Encountered with Course Content, (3) Difficulty of the Course Content, (4) Preference of Mode of Delivery, (5) Satisfaction with Course Content and (6) Perception of the Course. Second, Generation Y is also conditioned by (1) Initial Expectations, (2) Programme Time, (3) Course of Study and (4) Rating of Total Satisfaction (Overall Satisfaction). Third, Generation Z is also conditioned by (1) Rating of Total Satisfaction (Overall Satisfaction), (2) Course of Study and (3) Initial Expectation. The results further show that the multi-generational cohort as a unit is conditioned by (1) Preference of Mode of Delivery, (2) Usefulness of the Course to Study and (3) Rating of Total Satisfaction (Overall Satisfaction). Overall, the above evidence suggests that the characteristics exhibited by the multi-generational cohort is distinct from the individual generations constituting the degree cohort. Therefore, different generations have different learning experiences. This research evidence provides insights for the design of employability embedded courses in higher education.

Conclusions and implications for stakeholders
This paper studied the generational effects of students' perceptions of work-related learning experiences in employability embedded courses for undergraduates. The aim is to understand the implications for pedagogy in management education to improve student career motivations in employability decisions. The results show that there are differences in students' perceptions based on age generations, thus confirming differences based on social categorisations of Generations X, Y and Z in the current cohort of undergraduates in the traditional degree-awarding programmes (Howe & Strauss., 2000;Strauss & Howe, 1991). The results did not confirm the gender differences as raised by Artess et al. (2017) and Paadi (2014). Also, differences in initial expectations, perception of the course, and problems encountered with course content and the rating of total satisfaction (overall satisfaction) were not confirmed. However, the study confirmed the differences due to age (Idaka & Uzoechi, 2016), student's campus (Del Campo et al., 2016), programme time, student's status (Little, 2005), student's work experience, and preference of the mode of delivery. There was general evidence of a range of differences in student's opinion, of course, the usefulness of course to study programme and overall satisfaction of employability embedded courses between the generations. However, there were no differences in satisfaction with course content, personal opinions, the usefulness of the course to the study programme, and difficulty of the course content (Del Campo et al., 2016). Nonetheless, in the current emerging multi-generational cohorts in traditional undergraduate degree programmes, this evidence will inform programme designers, lecturers, and stakeholders on embedding employability skills and maximising student uptake of and satisfaction with these courses.
Concerning the generations, Generation Y reported the highest satisfaction with the course content followed by Generation X and Generation Z. Also, Generation X had the highest mean for the importance of the course in their personal opinion, followed by Generation Z and Generation Y. Therefore, Generation X placed the highest importance on the course, followed by Generation Z and Generation Y. Among the three generations, Generation X found the course most useful to their study programme, even though Generation X had the most difficulty with the course content with the highest mean, followed by Generation Y and Generation Z. On the contrary, Generation X reported the highest mean rating of total satisfaction with the course, followed by Generation Y and Generation Z. The generational attribute of appreciation of opportunity for professional development, a characteristic discussed in section 3 for Generation X, was evidenced. Also, being relatively less conversant with the use of technology in higher education course delivery, reflected in the difficulty with the course content, as the course was delivered through a blended environment.
It is also important to note, as recognised by Sánchez. and Kaplan (2014), that the intergenerational class environment is not simply a collection of students with different ages, but it produces a different inter-learning experience, which is evidenced by the different factors that condition their perceptions. The collective factors that condition their perceptions differ from those of the multi-generational cohort as a unit. Thus, this study provides evidence of intergenerational learning taking place in a multigenerational learning environment.
The results showed that in designing and embedding work-related employability courses in the emerging multigenerational cohorts of degree-awarding programmes, there is a need to assess the composition of the cohort to recognise how learning takes place in the cohort to inform and contextualise employability-related teaching. Also, there is a need to vary the andragogical and pedagogical orientations of the course on a continuum to accommodate the composition of the cohort. These findings provide important contributions for lecturers, curriculum designers, and the career development and administrative staff of HEIs to input into strategies of graduate employability programmes, which will enhance student learning and experience.

Limitations and further research
Finally, the limitations of the paper include the inability to completely control for lecturers' expectations of how many students would join or what the gender breakdown might be to complete the questionnaire, which could only be minimised in the research design. A major limitation of the study is that the sample was drawn from two campuses of one tertiary institution, which may influence the responses and therefore the generalisability of the findings. The paper also provides an opportunity for future research, which could examine the generality of the results through a bigger sample, and a longitudinal study could also provide evidence on the changing patterns over time.