Session Information
02 SES 05 A, Successful Students
Paper Session
Contribution
Vocational skills competitions, such as international WorldSkills and EuroSkill Competitions and national skills competitions, have established their place as part of vocational education and training (VET). At the international level, vocational skills competitions provide a platform for feedback, benchmarks, and dissemination of VET systems and practices (WorldSkills International [WSI], 2019, p. 11). Overall, vocational skills competitions present a complementary, even an opposing image of VET, which has at times and in some contexts suffered from its reputation and image as an unattractive choice (Chankseliani et al., 2016; Rintala & Nokelainen, 2020; Ryan & Lőrinc, 2018). Thus, it has been suggested that skills competitions may positively contribute to the image and attractiveness of VET, for instance, through inspiring people by showcasing outstanding performance, demonstrating that VET can offer economic benefits (including awards), and creating a positive image of young people choosing a VET pathway (Chankseliani et al., 2016; see also Virolainen & Stenström, 2014).
This study investigates Finnish vocational students competing in global WordSkills Competitions (WSC). WSC is organised once every two years by a host member of WorldSkills International (WSI). WSCs include a variety of skill areas (e.g., painting and decorating,construction metal work, and hairdressing) and participants in WSCs are usually selected through national or regional competitions; age is the only eligibility criterion and, depending on the occupational level, the age limit is either 22 or 25 years. After four days of competition, the best competitors in each skill area are awarded gold, silver, and bronze medals. Competitors who perform above the average point score in their skill are awarded a Medallion for Excellence (more than 500 points in competitions prior to 2019). The present study aims to investigate whether highly successful medal winners and medallion recipients (group A) differ from other WSC competitors scoring fewer than 500 points (group B). The present study focuses on investigating the role of Finnish competitors’ goal orientations and metacognitive and resource management strategies in WSC success.
The study employs the achievement goal framework (e.g., Ames, 1992; Dweck, 1986; Maehr & Midgley, 1991; Nicholls, 1984; Nicholls et al., 1989) to understand how vocational students interpret and experience achievement context skills. Two major types of achievement goal orientations are mastery and performance. In mastery goal orientation, the focus is on the task (desire to develop competence and mastery of a new skill area), while in performance-goal orientation the focus is on the self (desire to demonstrate to others an ability in a new skill area) (Ross et al., 2002).
Next to motives and desire to learn, the importance of metacognitive strategies, such as self-regulation and effort, have also been emphasised in the VET context (e.g., Jossberger et al., 2020; Kallio et al., 2018). Individuals may have strong vocation-specific knowledge but still have extensive shortcomings in their metacognitive and resource management strategies. For instance, Jossberger et al. (2020) recently found that well-performing vocational students planned their time and resources, but they monitored work processes and evaluated outcomes rather than their learning behaviours. Previous studies have also suggested that students with mastery goals and high task orientation may also self-report higher levels of self-regulatory strategies (Bouffard et al., 1995; Riveiro et al., 2001).
Based on the issues above, the present study analyses success in WSC and answers the following research questions:
- RQ 1: How are vocational students’ self-reported mastery and performance-goal orientations associated with objective performance measurement in international skills competitions?
- RQ 2: How are vocational students’ self-reported metacognitive and resource management strategies associated with objective performance measurement in international skills competitions?
Method
Numerical empirical data (N = 137) were collected from the Finnish WSC competitors in 2008–2017. Competitors, mostly secondary level vocational school students, represented Finland in WSCs in 2009 (n = 41, Calgary, Canada), 2011 (n = 35, London, UK), 2013 (n = 42, Leipzig, Germany), and 2017 (n = 19, Abu Dhabi, United Arab Emirates). The sample comprised 64 male (46.7%) and 71 female (51.8%) respondents (two missing values, 1.5%). The average age for the males was 20.0 years (SD = 1.431) and for females was 20.1 years (SD = 1.198). The average age of the respondents was 20.1 years (SD = 1.310). Data were collected with a pen-and-paper questionnaire during the Finnish WSC team training camps 2008–2017. The questionnaire contained 17 five-point Likert scale items (1 = totally disagree through 5 = totally agree) related to goal orientations (nine items) and metacognitive and resource management strategies (eight items). Participants were instructed to focus on their WSC training when answering the questions. In addition to these questions, participants reported their age, gender, and middle school grade-point average. Goal orientations were measured with nine items adapted from the personal achievement goal orientation section of PALS (Patterns of Adaptive Learning Scales, Midgley et al., 2000; Ross et al., 2002). Metacognitive strategies (metacognitive self-regulation, elaboration, and critical thinking) were measured in two dimensions (six items) that were adapted from the learning strategies scales of the MSLQ (Motivated Strategies for Learning Questionnaire, see Pintrich et al., 1991). Resource management strategies (time management and effort regulation) were measured in one dimension (two items adapted from MSLQ). T and Chi-square tests were applied to identify gender, age, or middle school GPA-related differences between the A and B groups. Results revealed no differences. Pearson product moment bivariate correlations were calculated to examine associations within and between three goal orientation dimensions and three metacognitive and resource management strategies dimensions. A four-way between-group multivariate analysis of variance (MANOVA) was conducted to investigate whether vocational students’ WorldSkills competition success is related to their goal orientations (RQ 1) and metacognitive and resource management strategies (RQ 2).
Expected Outcomes
Regarding RQ1, vocational students' self-reported mastery and performance-goal orientations, both mastery and performance-approach goal orientations of group A competitors (medal winners and medallion recipients) were higher than those in group B (other WSC competitors scoring fewer than 500 points). No difference was found between the two groups’ performance-avoidance goal orientations. Regarding RQ2, metacognitive and resource management strategies, metacognitive strategies in studies were higher in highly-successful group A than in group B. Although metacognitive strategies in training were higher in group A than in group B, there was no statistically significant difference. Furthermore, resource management strategies were higher in group A than in group B. Our results correspond with findings of an earlier study (Nokelainen et al., 2012) that medal winners and medallion recipients had higher mastery and performance-approach goal orientations than other WSC participants. This may indicate that adaptive patterns of learning (related to both mastery and performance-goal orientations) during training are related to the effective and versatile development of competencies needed for success in skills competitions. However, the application of maladaptive patterns has also been demonstrated to correlate with high achievement in the context of international skills competitions, as shown in the findings from the UK squad (Nokelainen & Stasz, 2016). Considering the results, inconsistencies between goal orientations in various samples suggest that there may be a need to consider cultural and educational policy factors. For example, Finnish team for the international skills competitions is primarily selected to represent the level of the vocational education training system (instead of ‘bringing home’ as many medals as possible). This may lead to a relatively low pressure compared to some other countries and show in competitors’ responses to questions that ask their opinion about ‘losing their face in front of others’.
References
Chankseliani, M., James Relly, S., & Laczik, A. (2016). Overcoming vocational prejudice: How can skills competitions improve the attractiveness of vocational education and training in the UK? British Educational Research Journal, 42(4), 582–599. Dweck, C. (1986). Motivational processes affecting learning. American Psychologist, 41(10), 1040–1048. Jossberger, H., Brand-Gruwel, S., van de Wiel, M. W. J., & Boshuizen, H. P. A. (2020). Exploring students’ self-regulated learning in vocational education and training. Vocations and Learning, 13(1), 131–158. Maehr, M. L., & Midgley, C. (1991). Enhancing student motivation: A school-wide approach. Educational Psychologist, 26, 399–427. Midgley, C., Maehr, M. L., Hruda, L. Z., Anderman, E., Anderman, L. H., Freeman, K. E., Gheen, M., Kaplan, A., Kumar, R., Middleton, M. J., Nelson, J., Roeser, R., & Urdan, T. (2000). Manual for the Patterns of Adaptive Learning Scales (PALS). University of Michigan. Nicholls, J. G., Cheung, P. C., Lauer, J., & Patashnick, M. (1989). Individual differences in academic motivation: Perceived ability, goals, beliefs, and values. Learning and Individual Differences, 1(1), 63–84. Nokelainen, P., Smith, H., Rahimi, M. A., Stasz, C., & James, S. (2012). What contributes to vocational excellence? Characteristics and experiences of competitors and experts in WorldSkills London 2011. https://api.worldskills.org/resources/download/6666/6753/7647?l=en. Nokelainen, P., & Stasz, C. (2016). What contributes to vocational excellence? A study of the characteristics of WorldSkills UK participants for WorldSkills Sao Paulo 2015. Skope. http://vocationalexcellence.education.ox.ac.uk/wordpress/wp-content/uploads/2016/05/Project-1-Final-What-contributes-to-Vocational-Excellence.pdf Pintrich, P. R., Smith, D., Garcia, T., & McKeachie, W. J. (1991). A manual for the use of the motivated strategies for learning questionnaire. Technical Report 91-B-004. University of Michigan, National Center for Research to Improve Postsecondary Teaching and Learning. Riveiro, J. M. S., Cabanach, R .G., & Arias, A. V. (2001). Multiple-goal pursuit and its relation to cognitive, self-regulatory, and motivational strategies. British Journal of Educational Psychology, 71, 561–572. Ross, M. E., Shannon, D. M., Salisbury-Glennon, J. D., & Guarino, A. (2002). The patterns of adaptive learning survey: A comparison across grade levels. Educational and Psychological Measurement, 62(3), 483–497. Ryan, L., & Lőrinc, M. (2018). Perceptions, prejudices, and possibilities: Young people narrating apprenticeship experiences. British Journal of Sociology Education, 39(6), 762–777. Virolainen, M., & Stenström, M.-L. (2014). Finnish vocational education and training in comparison: Strengths and weaknesses. International Journal for Research in Vocational Education and Training, 1(2), 81–106.
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