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Social and cultural level mechanisms of adult learning

The individual level learning processes described above never happen in a vacuum but are always situated in physical, social, and cultural contexts. Social support is particularly relevant for the construction of conceptual knowledge and complex skills. Historically, the role of social support by a knowledgeable tutor or teacher has been described in Vygotsky’s model of the zone of proximal development (Vygotsky, 1930/1978). Later empirical studies have highlighted the role of knowledgeable support in constructing scientific concepts (Kirschner, Sweller, & Clark, 2006) as well as in the development of expertise (Gruber, Lehtinen, Palonen, & Degner, 2008). Teachers, coaches, and tutors can present learning content, organise learning activities, and scaffold learning so that it supports the above-described individual level learning processes. For example, expert support is often necessary for constructing schemas to reduce the cognitive load caused by increasingly complex tasks, or coaches can guide trainings which lead to the gradual formation of correct physical actions (Ericsson & Pool, 2016). Studies on teaching dialogues and other instructional methods show the variety of ways by which teachers and other knowledgeable people can support the learning of individuals (Schneider & Preckel, 2017).

However, it is not only this expert - novice or teacher — student relation which is important for learning but also the collaboration of peers can fundamentally support learning (Dillenbourg, 1999; Lehtinen, 2003). Recently, studies on socially shared metacognitive regulation have highlighted processes related to individual regulation and executive functions but go beyond the individual learning and regulation (lis-kala, Vauras, Lehtinen, & Salonen, 2011; liskala, Volet, Lehtinen, & Vauras, 2015; Malmberg, Jarvela, & Jarvenoja, 2017). Research findings on the neural correlates of social interaction have indicated that during evolution the brain has been equipped with functions which support the mutual relationship between humans more deeply than has been assumed before. “These studies have revealed that networks of brain areas support perception of self and others, interpretation of non-verbal and verbal social cues, mutual understanding, and social bonding” (Hari, Sams, & Nummen-maa, 2016, p. 1). Current research approaches for social collaboration and collaborative learning show that these processes are partly unique to the level of social interaction but also connected to the basic mechanisms of the human mind.

The context of learning processes involves not only the immediate social interaction but also the cultural environment in general, which produces and supports activities fundamental for learning (Gutierrez & Rogoff, 2003; Valsiner, 2012). There is a wide variety of ways to analyse the cultural aspects of learning but for the purposes of this article two approaches can be mentioned: firstly, anthropological studies show that a large part of the cultural skills and knowledge people use in work and societal activities have never been intentionally studied as isolated learning contents. Instead, gradually deepening participation in culturally formatted activities has been identified as a basis for the development of such skills, as described in the seminal book by Lave and Wenger (1991). Within the framework of adaptive complex systems the participation in such cultural activities and communities of practice can be seen as a unique level of learning. However, cultural participation is not independent of the other levels. The individuals approaching as legitimate peripheral participants (the term used by Lave and Wenger), the activities and communities of practice do bring their individual-level cognitive architectures to the situations. Gradual formation of neural networks would be the best candidate for explaining much of the individual-level learning taking place during the deepening participation processes.

Secondly, the cultural aspects of learning mean that culture provides individuals with tools for cognitive functioning. Of course, natural language is the most powerful cultural tool, which has fundamentally shaped human cognition and is involved in practically all learning in adulthood. The alphabet, Arabic numerals, and numerous sign systems have changed learning tasks and processes. Technical tools, such as calculators, can dramatically diminish the intrinsic cognitive load of traditionally demanding tasks (Sâljô, 2010). This process opens opportunities to deal with gradually more complex learning tasks because a part of the cognitive load can be outsourced to the tools.

Collaborative learning has been strongly highlighted in the contemporary models of learning for all ages and environments. The research has focused on the basic processes of social interaction (see above) and models which could be applied in formal education and working life contexts. Instead of reviewing different approaches of collaborative learning, we present here a model developed by Hak-karainen and his colleagues (Lehtinen et al., 2014). It focuses on professional learning in an advanced knowledge society and characterises various approaches where the ideas of the adaptive complex system approach are applied to the way learning is conceptualised. Starting from the description of the knowledge acquisition and participation metaphors by Sfard (1998), Hakkarainen and hrs colleagues constructed a model based on a proposed third metaphor of learning which they call “knowledge-creating metaphor” (Paavola et al., 2004). In this model, learning is connected to a creative knowledge work, which deals with incomplete epistemic objects that are open-ended and generate constantly novel questions (Knorr Cetina, 1999; Lehtinen et al., 2014). The approach builds on three basic ideas: 1) learning is focused on building, extending and sharing knowledge artefacts (ideas, theories, products, etc.), 2) learning takes place in tenus of creating collectively shared knowledge practices which aim at creating innovations and novel social practices, and 3) transactive development of expertise, which means the interaction of personal and collaborative knowledge-creating efforts.

The term “knowledge artefacts” has been proposed by Bereiter (2002) to describe the objects knowledge workers have to create, extend, build, and share when working on complex problems. Working on such knowledge artefacts (Bereiter, 2002) or epistemic objects (Knorr Cetina, 1999) is important in knowledge creation because they are incomplete and can be re-interpreted, modified, and connected with other knowledge objects (Bereiter, 2002; Paavola et al., 2004). From the point of view of collaborative professional learning, working with epistemic artefacts is important because they can also work as boundary objects (Akker-man & Bakker, 2011), which facilitate interaction between different epistemic cultures (Knorr Cetina, 1999) leading to knowledge. Wynn, Mosholder, and Larsen (2014) have studied the relationship between collaborative learning and adult cognitive development. Their results indicate that subjects taught with a problem-based learning approach with a learning community reached more often the highest levels of advanced adult thinking, in comparison to the group without such teaching approaches.

Professional creativity and ability for non-monotonic learning do not reside in the human mind only but are embedded in socially shared knowledge practices supported by such knowledge communities (Lehtinen et al., 2014). The process of knowledge creation described in this model is a collective rather than an individual process but it also depends on the individual experts who have a critical role in the pursuit of novelty' and innovation. In most working-life contexts, individual and social learning are intertwined. Collaborative processes make use of the expertise of participating experts, and their participation in the collaborative knowledge building process results in individual learning as well (Lehtinen et al., 2014).

 
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