Acquiring implicit knowledge

According to Bereiter and Scardamalia, implicit knowledge is acquired by problem-solving or participating in activities similar to those one wants to gain facility in. “There is no magic to how expert knowledge is acquired, but it is not enough to say that it comes about through study, experience and practice. Those terms explain mediocrity as well as expertise…problem-solving provides the dynamic element in the growth of all kinds of expert knowledge” (Bereiter & Scardamalia, 1993: 74). Schön claims that this process is driven by reflection-in-action. In reflection-in-action the very act of participating in a process and solving problems leads people to notice what is important or less important for the task, what is problematic, possible ways of getting around such problems, etc.

Usually reflection on knowing-in-action goes together with reflection on the stuff at hand. There is some puzzling, or troubling, or interesting phenomenon with which the individual is trying to deal. As he tries to make sense of it, he also reflects on the

understandings which have been implicit in his action, understandings which he surfaces, criticizes, restructures, and embodies in further action (Schön, 1983: 50).

Schön distinguished between reflection-on-action, i.e., looking back and analyzing what has happened, and reflection-in-action, which refers to the monitoring, experimenting, and evaluational processes one goes through while engaging in professional practice.

“Much reflection-in-action hinges on the experience of surprise…But when intuitive performance leads to surprises, pleasing and promising or unwanted, we may respond by reflecting-in-action…reflection tends to focus interactively on the outcomes of action, the action itself, and the intuitive knowing implicit in the action” (Schön, 1983: 56).

Schön saw reflection-in-action as the process that drives professional learning and practice. “It is this entire process of reflection-in-action which is central to the ‘art’ by which practitioners sometimes deal well with situations of uncertainty, instability, uniqueness, and value conflict” (Schön, 1983 : 50). Ironically, while referring to Schön as their central inspiration, the focus in SLTE has instead been on reflection-on-action, for example stressing activities such as teacher diaries, analysis of classroom transcripts, thinking about theoretical concepts in terms of practice, etc. (Farrell, 2006; Richards &

Lockhart, 1994; Wallace, 1991).

Despite the popularity of Schön’s ideas in the field of teacher education, his work has been effectively criticized for arguing “mainly by example and metaphor rather than sustained argument” (Eraut, 1995: 13), for not addressing the complex contextual factors professionals have to deal with, and for failing “to link his analysis to the work of other researchers in this field” (Eraut, 1995: 21). Despite this, there is some evidence of the importance of reflection-in-action for professional learning and action. A series of studies has shown that having learners verbalize what they are doing and why improves their learning and performance on a number of different tasks (Berry & Broadbent, 1990;

Chi, de Leeuw, Chiu, & LaVancher, 1994; Renkl, Stark, Gruber, & Mandel, 1998;

Sengupta & Xiao, 2002). Furthermore, there has been evidence of such on-line cognition in professional practice. Szesztay (2004), for example, used stimulated recall to study the cognition of seven L2 teachers. She found that all the teachers did engage in this kind of in-action monitoring of action, student’s reactions, and instructional plans. The data also indicated that such monitoring is so enmeshed with the action of teaching that it is not explicitly verbalized. “The word ‘reflect’ might be somewhat misleading, as it refers to a process which often does not happen in the medium of words” (Szesztay, 2004: 130);

instead, “reflecting in the midst of action is a movement of the mind that may or may not be accompanied by verbal thought” (Szesztay, 2004: 132). In addition, Chi & Bassok (1989) found that such self-monitoring during performance was important to learning and performance in math problem-solving. Students who engaged in self-regulation of action and learning learned more and performed better presumably because this allowed them to recognize what they did not understand and focus their efforts in these areas.

[T]he good students generated a large number of statements that reflected their failure to comprehend …the poor students not only did not realize that they did not understand, in fact, they thought more often that they did understand. …Basically this suggests that the poor students do not accurately monitor their own comprehension. Not only do they not realize that they have misunderstood, they in fact think that they do understand…The advantage of having an accurate monitoring of one’s understanding is that the realization that one does not understand should elicit attempts to understand. This is exactly what we found...in the majority of the cases (85% of the time for good students and 60% of the time for poor students) realizations of comprehension failures triggered episodes of self-explanations (Chi

& Bassok, 1989: 273-4).

Participation in teaching-similar activities is important because implicit knowledge is acquired for the specific task which people engage in. (Berry & Broadbent, 1984, 1988, 1990; Klayman, 1988; Lewicki, 1985, 1986a, 1986b; Lewicki, Czyzewska, & Hoffman, 1987; Lewicki, Hill, & Bizot, 1988). As mentioned earlier in this chapter, humans are good at implicitly noticing patterns in practice and using them to solve difficult, non-linear problems such as estimating the trajectory of a moving object in a computer program (Klayman, 1988) or deciding which chemical factory was secretly dumping chemicals into the river (Berry & Broadbent, 1990) without explicit knowledge of how they were able to solve these problems (Berry & Broadbent, 1984, 1988; Kuhn &

Dienes, 2005; Lewicki, Czyzeska, & Hoffman, 1987; Reber, 1989; Roßnagel, 2001;

Stadler, 1989). This suggests that, for example, engaging in a discussion about recasts as feedback for L2 learners results in implicit knowledge, but implicit knowledge about engaging in such academic discussions. To gain implicit knowledge about using recasts in actual teaching situations, teachers need to engage in activities, with the same time constraints as teaching, which require them to decide when and how to use recasts.

Furthermore, learners need to be actively involved in the task, rather than passively observing. Studies have consistently found that active learning activities lead to more learning that passive activities (Klayman, 1988; Moreno, Mayer, Spires, & Lester, 2001;

Natter & Berry, 2005; Stern, Aprea, & Ebner, 2003; Wagenaar, Scherpbier, Boshuizen,

& van der Vleuten, 2003) For example, Borg (2005) found that teachers who actively sought out knowledge about grammar knew more than those who did not. Moreover, Yates and Wigglesworth (2005) found that teachers who actively prepared materials for learning about pragmatics were much more likely to use their knowledge of pragmatics in instruction that teachers who had simply had these materials explained to them in workshops.

There are several reasons why active learning (in most situations) is more effective than passive learning. To begin with, active participation generally has more structural similarity with the target activity (i.e., teachers usually teach rather than observe others teaching). Ellis, Whitehall, and Irick (1996), for example, found that when learners were assembling a motorized crane, action-oriented explanations explaining what to do (similar to the task of assembling the crane) were much more effective than static explanations which explained the purpose of a part or what the crane should look like or do (which is not similar to the action the learners were engaged in). In addition, active learning may focus participants’ attention on crucial aspects of an activity; while in passive learning situations observers may not be able to differentiate between crucial and peripheral aspects of the activity. Learning from such passive experiences would then result in more cognitive load because learners would have to focus on a wider range of information than those actively working on the problem. For instance, Berry (1991) had some learners work on a simulated problem of managing a sugar factory. Learners who only followed the managerial changes by the other learners only exhibited any learning on the task if it was very clear why the changes were made, while those who actively participated learned regardless of the situation. Finally, it is also possible that in passive situations learners do not pay as much attention to information because they do not need to use it in the near future. For instance, Mathan and Koedinger (2005) studied students learning to use a spreadsheet program. They found that students whose mistakes were simply pointed out and corrected learned less than students who were prompted to figure out the problems with their work and to improve it.

Although it is possible for explicit knowledge to be helpful in the acquisition of implicit knowledge, explicit knowledge is not central to the process of acquiring implicit knowledge. Research shows that it is very difficult to develop implicit knowledge from explicit knowledge and explicit knowledge is often derived from implicit knowledge rather than the other way around. Some psychologists have noted that in many areas (typing, computer programming, etc.) people can use explicit knowledge to develop implicit knowledge, for example by engaging in typing practice (Anderson, 1993;

Singley & Anderson, 1989). In SLTE it has been implied that novice L2 teachers can use explicit knowledge from academic fields to develop implicit, practice-oriented knowledge (e.g. Hedgcock, 2002; Wallace, 1991). The problem with this argument is that, according to the research presented in the previous chapter, L2 teachers do not use the explicit knowledge they learned in SLTE programs to develop practice-specific implicit knowledge. Furthermore, in many cases implicit knowledge precedes explicit knowledge; in other words, people can learn something first (implicit) and only later learn to explain what they know (explicit). Thus, explicit knowledge may be a product of implicit knowledge, not the other way around (Dulany, Carlson, & Dewey, 1984; Graff, Squire & Mandler, 1984; Howard & Ballas, 1980, 1982; Millward, 1981; Reber, 1967).

In fact, it has been shown that explicit knowledge can hinder the implicit rule learning process and often does not even lead to explicit rule learning (Berry & Broadbent, 1988, 1990; Roßnagel, 2001). While explicit instruction has not been shown to help develop knowledge useful in actually solving problems, it does increase inert knowledge in that the quality of the participants’ explicit comments and answers improves but not their ability to solve the problems (Berry & Broadbent, 1988, 1990).

Finally, some claim that the implicit knowledge we gain by participating in activities is cognitively more useful than explicit, declarative knowledge. “A considerable amount of evidence indicates that as compared with consciously controlled cognition, the nonconscious information-acquisition processes are incomparably faster and structurally more sophisticated” (Lewicki, Hill, & Czyzeska, 1992: 796). This may explain why people often reject new information or concepts when this is presented explicitly. If it comes to choosing between fast and flexible implicit knowledge and difficult-to-process explicit knowledge, people will generally rely on their implicit knowledge to guide practice regardless what the explicit empirical evidence shows.

Implicit knowledge is acquired by actively participating in activities relevant and central to the practice being learned. It seems that the processes of participating in activities force learners to pay attention to relevant cues, correlations, causes, and constraints, and that this attention aids the acquisition of implicit knowledge about that practice. This body of research has lead many scholars to conclude that most of our knowledge is acquired through implicit learning (Berry & Dienes, 1993; Jacoby, Lindsay, & Toth, 1992; Lewicki, Hill, & Czyzeska, 1992; Moors & de Houwer, 2006; Underwood &

Bright, 1996). “[A] person typically learns about the structure of a fairly complex stimulus environment, without necessarily intending to do so, and in such a way that the resulting knowledge is difficult to express” (Berry & Dienes, 1993: 2). Contextualized activities similar to tasks and processes that teachers regularly engage in would be in a much better position to take advantage of human beings’ natural tendency for implicit learning than “read and discuss” seminars focusing on explicit knowledge. (Novice teachers would also gain implicit knowledge in such activities, but this would tend to be implicit knowledge about reading and discussing academic literature, not teaching.)

Explicit knowledge may be useful in this process, but the possession of explicit knowledge itself does not necessarily lead to the growth of implicit knowledge. It is likely that explicit knowledge most helps the acquisition of implicit knowledge if it is used to engage in tasks similar to teaching activities.