Session Information
02 SES 07 C, Learning III: Resources and Skills
Paper Session
Contribution
The future studies in the field of VET will need to illuminate the range and weight of different aspects of both cognitive and social factors in expertise development. While expertness can be characterized by automaticity and an ability to solve problems in new situations through the strategic application of existing knowledge, it is seen to develop through a range of learning activities, including practice, demonstration, and mentoring by expert others (Smith, 2003), and through participation in social practice (Billett, 2001). Consequently, the new competence-based orientation of vocational education promotes both self-directed and authentic learning within and beyond the workplace that has led to fundamental changes in the work of vocational educators (i.e., teachers and trainers): The shared problem is the novice who knows a lot but is not yet able to utilize this knowledge fully in the workplace (Brujin & Leeman, 2010).
Recent interest in the flexible delivery of training in the workplace is challenged by those characteristics of learners that do not facilitate self-directed learning or receptiveness to verbal presentation (e.g., through texts or lectures) of training material (Smith, 2003). Workplaces, on the other hand, often are not able to provide learners with the structured support and guidance required to develop knowledge through the effective deployment of a wide range of learning strategies within a community of practice (Smith, 2003). For instance, the lack of time, resources and pedagogical approaches have been found to challenge workplace learning by hindering individual guidance and reciprocal workplace learning between apprentices and experienced workers (Pylväs, Nokelainen, & Rintala, 2017). This study focuses on examining VET students’ approaches to learning and experiences of workplaces as learning environments from the perspective of self-regulation. Whereas self-directed learning can be situated at the macro level, which means that it concerns a learning trajectory as a whole (a self-directed learner is able to decide what needs to be learned next and how one’s learning is best accomplished), self-regulated learning in educational psyvhology provides a valuable contribution to our understanding of the underlying learning processes (Jossberger et al., 2018).
The concept of self-regulation refers to “the process in which self-generated thoughts, feelings and actions are planned and systematically adapted to further one’s learning and motivation” (Schunk & Ertmer, 2000, p. 631; Zimmerman, 2000, p. 14). Self-regulated learning is not limited to academic contexts, but can occur wherever learning—whether formal or informal—takes place (Kaplan, 2008). The study applies the cyclical model of self-regulation that includes three general phases: forethought, performance and self-reflection (Zimmerman & Moylan, 2009). According to Zimmerman (1989, 1990), all learners use regulatory processes to some degree; however, by the systematic use of metacognitive, motivational, and/or behavioral strategies, self-regulated learners proactively seek out information when it is needed and take the necessary steps to master it, even when encountering obstacles. Furthermore, self-regulatory skills allow learners to modify their performance based on personal characteristics and environmental conditions (Zimmerman, 2000). The research questions are as follows: 1) How VET students regulate their learning?; 2) What individual and environmental factors influence on VET students approaches to learning?
Method
The semi-structured interview data (N=33) was collected in 2017 in Finland. The data included both apprentices (n=15) and students in a school-based VET (n=18) in the fields of social services, health and sports, business and administration, and technology. The semi-structured interview was formed based on the significance of self-regulation and cognitive and social features in vocational talent development (Greenspan et al., 2004; Nokelainen, 2008; Zimmerman, 1998). The method offered some leeway to follow up on angles deemed important by the interviewee, while it also enabled the interviewer to focus the conversation on issues considered important to the research (Brinkmann, 2014). The qualitative data analysis took the form of a (thematical) content analysis of the textual empirical data. Content analysis of data is highly systematic (Schreier, 2014). It can be defined as a research method for the subjective interpretation of the content of text data through the systematic classification process of coding and identifying themes or patterns (Hsieh & Shannon, 2005).
Expected Outcomes
The initial results have shown that most of the VET students have a strong internal motivation, a ‘professional drive’, to develop their vocational expertise. In addition, most of the students highly emphasized the importance of authentic environments and hands-on experience for their learning. However, when developing their competences, only some of the students mentioned of investing their time in independent study sessions. Those students mentioned a variation of learning strategies that they had used for proactive planning of a learning or working task (e.g., information retrieval or mental practice of an upcoming work/study task). Some more students from institution-based VET emphasised of being active in preparing for an upcoming task and the pleasure of independent studying. Instead, self-directedness of learning at work contexts (e.g., asking questions, finding help or seeking good learning situations) was more emphasised among the apprentices. This research pursues the goals strengthening the role of VET research in the field of educational psychology. While self-regulation is one of the most researched topics in the field of education, it has not yet been widely addressed in VET research. Moreover, the practical aim of this research is to improve the ability of educators and working life stakeholders to strengthen VET students’ learning skills both in school and in the workplace. By enhancing individuals’ abilities to engage in lifelong learning, practitioners play an important role in supporting students’ employability, integration into society and life satisfaction, while also reducing drops-outs and exclusions.
References
Billett, S. (2001b). Learning in the workplace: Strategies for effective practice. Sydney: Allen and Unwin. de Bruijn, E. & Leeman, Y. (2011). Authentic and self-directed learning in vocational education: challenges to vocational educators. Teaching and Teacher Education, 27(4), 694-702. Greenspan, D. A., Solomon, B., & Gardner, H. (2004). The development of talent in different domains. In L. V. Shavinina, & M. Ferrari (Eds.), Beyond knowledge (pp. 119–135). Mahwah, NJ: Lawrence Erlbaum Associates. Hsieh, H.-F., & Shannon, S. E. (2005). Three approaches to qualitative content analysis. Qualitative Health Research, 15(9), 1277–1288. Jossberger, H., Brand-Gruwel, S., Boshuizen, H., & van de Wiel, M. (2010). The challenge of self-directed and self-regulated learning in vocational education: a theoretical analysis and synthesis of requirements. Journal of Vocational Education and Training, 62(4), 415-440. Kaplan, A. (2008). Clarifying metacognition, self-regulation, and self-regulated learning: What’s the purpose? Educational Psychology Review, 20, 477-484. Nokelainen, P. (2008). Modeling of professional growth and learning: Bayesian approach. Tampere: Tampere University Press. Schunk, D. H., & Ertmer, P. A. (2000). Self-regulation and academic learning: Self-efficacy enhancing interventions. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 631–649). San Diego: Academic Press. Smith, P. J. (2003b). Learning Strategies Used by Apprentices in Flexible Delivery. Journal of Vocational Education and Training, 55(3), 369-383. Pylväs, L., Nokelainen, P., & Rintala, H. (2017). Finnish apprenticeship training stakeholders’ perceptions of vocational expertise and experiences of workplace learning and guidance. Vocations and Learning. Advance online publication. doi: https://doi.org/10.1007/s12186-017-9189-4 Zimmerman, B. J. (1989). A social cognitive view of self-regulated academic learning. Journal of Educational Psychology, 81(3), 329-339. Zimmerman, B. J. (1990). Self-regulated learning and academic achievement: An overview. Educational Psychologist, 25(1), 3–17. Zimmerman, B. J. (1998). Academic studying and the development of personal skill: A self- regulatory perspective. Educational Psychologist, 33(3), 73–86. Zimmerman, B. J. (2000). Attaining self-regulation. A social cognitive perspective. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 13-39). San Diego, CA: Academic Press. Zimmerman, B. J., & Moylan, A. R. (2009). Self-regulation: Where metacognition and motivation intersect. In D. J. Hacker, J. Dunlosky, & A. C. Graesser (Eds.), Handbook of Metacognition in Education (pp. 299–315). New York: Routledge.
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