22 SES 09 C, Paper Session
One of the most important concerns of higher education institutions is to ensure students’ smooth and quick transition into the job market after graduation. Nevertheless, universities are often criticized for not preparing enough students with the skills and personal resources needed for professional practice and success (Knight & Yorke, 2003). Hence, higher education institutions are more and more concerned about increasing students’ employability, defined as “a set of achievements – skills, understandings and personal attributes - that make 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). Employability has been investigated both from an organizational perspective (e.g., what employers want) and from an individual perspective (e.g., the characteristics that make individuals more employable); furthermore, employability can be measured based on outcomes, such as employment rate within a specified timeframe, or as the propensity of students to get an employment (Harvey, 2001). In the current study we embrace the conceptualization of employability as a combination of personal dispositions skills, and knowledge, and we measured it with a self-report questionnaire. Self-perceived employability is associated with both higher job satisfaction, higher job engagement (Ngo, Liu, & Cheung, 2017) and overall better well-being and health (Berntson & Marklund, 2007); for this reason, it represents a valuable indicator of the effectiveness of students’ transitions into the job market.
The aim of the present study was to identify different typologies of Bachelor and Master students at the end of their studies at Swiss institutions and relate them to their level of employability. More specifically we investigated cognitive abilities, personality dispositions, emotional skills, and personal resources related to career behavior, with the goal of identifying which typologies were more employable and which would need support to approach the job market. Ultimately, we were interested to have an overview regarding the percentage of students who were lacking the necessary characteristics to succeed in the transition to finding a job after graduation to inform policy and understand the need for introducing courses meant to improve students’ employability.
From a larger sample of 400 students from three Swiss higher education institutions, we retained 115 students at the end of their Master and Bachelor degree. To identify different typologies of students we employed cluster analysis, and the K-means procedure with a preset number of 4 clusters. The goal of cluster analysis is to identify groups of individuals that share common characteristics so as to maximize the similarity of individuals within the group and maximize the dissimilarity of individuals among the groups. The variables that were used to aggregate students were: cognitive ability, measured with the Raven's Standard Progressive Matrices (RPM; Raven 1938); Trait Emotional Intelligence, which measures individuals’ self-efficacy perceptions regarding using and managing emotions (TEIQue-SF; Cooper & Petrides, 2010), the personality traits more strongly related to career success, namely Extraversion, Conscientiousness, and Emotionality (HEXACO; De Vries, 2013); Career Adaptability, or the personal resources that help students in career transitions, in particular the dimensions of concern, control, curiosity, and confidence (Savickas & Porfeli, 2012). The clusters emerging from these personal characteristics were then related to students’ level of employability, which was measured with the Self-Perceived Employability Scale for university students (Rothwell, Jewell, & Hardie, 2009). We were able to identify 4 different clusters of students: Cluster n. 1—which we call Successful students-- represented 41.7% of the sample and included students with good reasoning skills, curiosity and optimist about their future career, emotionally stable and confident. Cluster n. 2—which we label students Mobilizing resources—represented 11.3% of the sample and described students who did not have very strong reasoning skills, but were hardworking, rather adaptable and rather self-confident in managing their emotions. Cluster n. 3—which we label Supersmart, but uninterested —represented 14.8% of the sample and described those students that had very high reasoning skills, but who were not concerned about their career choices and appeared more introverted and emotionally cold. Cluster n. 4—which we label Good potential, but confused—represented 32.2% of the sample and described those students who had good reasoning skills, but were very emotional, not able to manage their emotions, nor proactive in looking at their career options.
We employed the four clusters as predictors of employability in a one-way Anova. Results showed that Cluster n. 1 had the highest level of employability (M = 5.43 SD = 0.77) and cluster n. 3 the lowest (M = 4.48 SD = 0.90). Cluster n. 2 and n.4 did not significantly differ from each other with respect to their employability (M = 4.59 SD = 1.03 vs. M = 4.76 SD = 0.77), nor with respect to the employability of cluster n. 3. Overall, our results show that only cluster n.1 showed a significantly higher employability than the other three clusters. In addition, findings highlight that 58.3% of the sample comprising clusters 2, 3, and 4 had employability lower than the benchmark of our larger N= 400 sample (M = 4.91 SD = 0.81). Our results suggest that about 60% of the students ending their studies could benefit from attending courses meant to improve their employability. Furthermore, they highlight areas, such as reasoning skills, career adaptability, emotional skills, which warrant consideration for curricula design and policymaking.
Berntson, E., & Marklund S. (2007) The relationship between perceived employability and subsequent health, Work & Stress, 21:3, 279-292, DOI: 10.1080/02678370701659215 Cooper, A., & Petrides, K. V. (2010). A psychometric analysis of the Trait Emotional Intelligence Questionnaire–Short Form (TEIQue–SF) using item response theory. Journal of Personality Assessment, 93, 449–457. http://dx.doi.org/10.1080/ 00223891.2010.497426. De Vries, R. E. (2013). The 24-item brief HEXACO inventory (BHI). Journal of Research in Personality, 47, 871–880. http://dx.doi.org/10.1016/j.jrp.2013.09.003. Knight, P.; Yorke, M. Learning, Curriculum and Employability in Higher Education; Psychology Press: Hove, UK, 2003; ISBN 020346527X. Raven, J. C. (1938). Progressive matrices: A perceptual test of intelligence. London, UK: H. K. Lewis. Rothwell, A., & Arnold, J. (2007). Self-perceived employability: Development and vali- dation of a scale. Personnel Review, 36, 23–41. http://dx.doi.org/10.1108/ 00483480710716704. Savickas, M. L., & Porfeli, E. J. (2012). Career adapt-abilities scale: Construction, reliability, and measurement equivalence across 13 countries. Journal of Vocational Behavior, 80, 661–673. http://dx.doi.org/10.1016/j.jvb.2012.01.011. Yorke, M. Employability in Higher Education: What It Is, What It Is Not; Learning & Employability Series; Higher Education Academy (HEA): Heslington, UK, 2006.
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