gender. Significant interactions using univariate ANOVAs, with a Bonferroni correction (α=.013), are summarised in Table 3. Tukey post-hoc analysis indicated an effect for degree specialisation on transition learning with HRM students reporting significantly higher levels than those in Marketing (p=.006), Finance/Accounting (p=.003), Management (p=.032) and those in the Other grouping (p=.005). Univariate analysis suggested that those working typically achieved higher ratings than both those not working (p=.035) and those working on a full-time basis (p=.050). We found no evidence of a significant effect for stage of degree, despite the significant MANOVA. Table 3 Analysis of variance in career management competencies by individual characteristics and participation in WIL Characteristic Dimension df MS F p-value η2 Degree Transition learning 6 1.378 3.549 .002 .043 specialisation Employment Opportunity awareness 2 2.482 3.924 .009 .024 status Work placement Self-awareness 1 4.180 16.377 .000 .033 Decision-making learning 1 5.706 14.759 .000 .030 Transition learning 1 2.922 7.389 .007 .015 Influence of WIL A significant MANOVA (α=.05) interaction was detected in competency ratings by participating in a work placement, 475)=7.710, partial F(4, p=.000, λ=.939, η2=.061. Significant ANOVAs (α = .013) for self-awareness, decision-making learning and transition learning are presented in Table 3. Comparative mean analysis indicated that, contrary to expectations, those not completing placements achieved significantly higher (p=.000) mean ratings for self-awareness (4.06) than those who did (3.84). Similarly, non-placement students achieved higher ratings for decision-making learning (p=.000) 3.86 in comparison to 3.60 – – and transition learning (p=.007) 3.81 in contrast to 3.63. –
gender. Significant interactions using univariate ANOVAs, with a Bonferroni correction (α=.013), are summarised in Table 3. Tukey post-hoc analysis indicated an effect for degree specialisation on transition learning with HRM students reporting significantly higher levels than those in Marketing (p=.006), Finance/Accounting (p=.003), Management (p=.032) and those in the Other grouping (p=.005). Univariate analysis suggested that those working typically achieved higher ratings than both those not working (p=.035) and those working on a full-time basis (p=.050). We found no evidence of a significant effect for stage of degree, despite the significant MANOVA. Table 3 Analysis of variance in career management competencies by individual characteristics and participation in WIL Characteristic Dimension df MS F p-value η2 Degree specialisation Transition learning 6 1.378 3.549 .002 .043 Employment status Opportunity awareness 2 2.482 3.924 .009 .024 Work placement Self-awareness 1 4.180 16.377 .000 .033 Decision-making learning 1 5.706 14.759 .000 .030 Transition learning 1 2.922 7.389 .007 .015 Influence of WIL A significant MANOVA (α=.05) interaction was detected in competency ratings by participating in a work placement, λ=.939, F(4, 475)=7.710, p=.000, partial η2=.061. Significant ANOVAs (α = .013) for self-awareness, decision-making learning and transition learning are presented in Table 3. Comparative mean analysis indicated that, contrary to expectations, those not completing placements achieved significantly higher (p=.000) mean ratings for self-awareness (4.06) than those who did (3.84). Similarly, non-placement students achieved higher ratings for decision-making learning (p=.000) – 3.86 in comparison to 3.60 – and transition learning (p=.007) – 3.81 in contrast to 3.63.
The%20development%20of%20career%20management%20competencies%20and%20role%20of%20Work-Integrated%20Learning%20-%20Jackson%20%26%20Wilton.docx