교수자 없는 교육: 한계는 무엇인가? (IJSDL, 2009)

교수자 없는 교육: 한계는 무엇인가? (IJSDL, 2009)

PEDAGOGY WITHOUT A TEACHER: WHAT ARE THE LIMITS? 

Paul Bouchard

Long은 몇 년 전 학습이 학습자 통제를 따를 수 있게 하는 두 가지 토대을 제시했다. 그는 '심리적', '교육적'이라는 두 가지 용어를 사용했는데, 다음과 같다. '심리적'토대는 자기주도학습을 선호하는 성향, '교육적'토대는 스스로 학습활동을 계획하고 수행하는 것.

A few years ago, Long (1992) gave us two fundamental ways in which learning could be learner-controlled. He coined the terms psychological and pedagogical to describe the two dimensions of learner-control along which self-directedness could vary in its expression. 

• In this model, learners could be psychologically driven to learn, which makes them predisposed to self-directed learning. 
• The other dimension refers to the planning and carrying out of the learning activities themselves. The pedagogical dimension of learner-control is concerned with what it is that self-directed learners do.

이 모델에 근거한 몇 가지 관찰결과. 

심리적 통제 수준이 높은 학습자는 다음과 같다. 무엇을 배울지에 대해 선택할 기회가 없어도 학습에 대한 동기가 높고, 자발적으로 다른 사람에게 학습계획 설정권을 양도할 수도 있다.

Here are a few observations based on this model. Learners with a high-level of psychological control, for instance, can be highly motivated to learn without necessarily being given the opportunity to chose in what ways they learn. They could also voluntarily devolve the planning of any learning activities to another person.

대학생이 이러한 케이슨데, 대학의 공식 교육과정에서 공부하면서 대학에서 요구하는 학점이나 학위에 무관하게 공부할 수 있다. 

For example, this would be the case of learners who register for a formal course in a university, where doing so for personal reasons has little to do with institutional imperatives such as credits or program degrees. In both cases, the learner conserves a high level of psychological control over the act of learning.

교육적 통제 수준이 높은 학습자는 다음과 같다. 교육적 영역은 교수-주도적 학습에서 요구되는 거의 모든 활동의 총체이며, 목표 설정, 활동 계획, 자원 선택, 시한 설정 등이 있다. 물론, 자기주도적 학습자는 이 모든 것을 스스로 한다.

On the other hand, the pedagogical dimension is the sum of all activities that are normally the responsibility of an instructor in teacher-directed learning, such as formulating goals, planning activities, selecting resources, and setting deadlines. Of course, a self-directed learner must do all of these things, hence the pedagogical control that self-direction allows.

위의 대학생 사례에서, 학생은 심리적 통제 수준이 높으면서 교육적 통제 수준이 낮다. 반대되는 사례는 왜, 무엇을 공부해야 하는지 전혀 책임감은 없으면서도 모든 학습활동을 스스로 해야하는 학생이 있다. 

In the example above of registering for a formal course, the learner displayed a high degree of psychological control and a low level of pedagogical control (albeit voluntarily). An alternative example would be learners who hold no responsibility for why and what to learn, but nevertheless are left to their own devices regarding how to learn it. Such situations occur with increasing frequency in the workplace, as some recent research revealed (Bouchard & Hrimech, 2007).

그러나 Long 의 도입한 용어는 문제가 있다. '정신적'이라는 말을 쓸 때 거의 모든 것이 '정신적' 혹은 '정신적 함의'가 있다고 할 수 있다. 어떤 사람이 학습과정을 시작하게끔 하는 내적 역동에 대해 한정해서 쓴다면 학습의 능동적(conative) 영역에 대해서 말하는 것인데, 여기에는 drive, impulse, initiative 등이 모두 들어간다. 

The terminology employed by Long is problematic, however. To talk about something being psychological is misleading since the term itself can designate any process that originates from or affects the human mind. Therefore, almost everything can be said to be psychological or to have psychological implications. If we are referring specifically to the inner dynamics that will ultimately entice someone to initiate a learning process, we are really talking about the conative dimension of learning, which includes all the possible reasons a person can have for learning, such as their drive, impulses, initiative, and drive.

마찬가지로 '교육적' 이슈라는 것도 이상한데, 왜냐면 pedagogy라는 것은 교사가 하는 일에 초점을 둔 용어이기 때문이다. 

Similarly, it is awkward to talk about pedagogical issues in the context of SDL, since pedagogy is a term that is primarily used to designate what it is that teachers do. In an environment without a teacher, the term resonates falsely. In an interesting article some years back, Danis and Tremblay (1986) interviewed self-directed learners and discovered, contrary to expectation, that they did not engage much in the so-called teaching tasks. This finding was appropriately named by the authors an “analgorithmia of syntaxes,” (p. 432) because the self-teaching processes (or syntaxes) did not correspond to the form or sequence (the algorithms) advocated in teacher development programs. Therefore, Long’s model can be improved by referring to the second dimension of learner-control as the algorithmic dimension.

AUTONOMOUS LEARNING STRATEGIES

Table 1. Algorithmic Dimensions of Autonomous Learning Strategies

Table 2. Conative Dimensions of Autonomous Learning Strategies

ENVIRONMENTAL DIMENSIONS

The two emerging dimensions of learner-control – the semiotic and the economic – give rise to some very specific questions regarding decisions that learners can make pertaining to their own learning. They are the two new dimensions of learner-control.

Learning is no longer the reserved province of traditional institutions such as schools or colleges. Indeed, it is now acknowledged that universities find themselves in direct competition not only with each other, but with a multitude of offerings from a thriving marketplace (Moore & Kearsley, 1996).

Table 3. Semiotic Dimensions of Autonomous Learning Strategies

Table 4. Economic Dimension of Autonomous Learning Strategies

DISCUSSION

Self-directed learning has been the object of considerable prescriptive literature that assumes that SDL is naturally a good thing and that it should be supported in all areas of learning, particularly in the workplace. If we believe that learners are well prepared to assume the tasks of SDL, then we need not explain further the obvious benefits of that approach. What our model proposes however, is to consider as well the not-so-good potential of various dimensions where learner autonomy can surely be developed and expressed, but also considerably thwarted and suppressed. 

• The algorithmic dimension points to the importance of being able to assume complex teaching tasks such as formulating goals and finding appropriate resources. In a world where autonomous learning is more or less expected of learners and employees, these tasks can quickly become overwhelming for the unprepared. 

• The conative dimension reminds us that it is the learner, ultimately, who is at the origin of the act of learning. Failure to recognize this, for example by expecting from employees that they know without providing appropriate support for acquiring the knowledge, can lead to considerable anxiety and frustration. 

• The semiotic dimension requires careful consideration not only to the information available, but also the form in which it is made available. A recent study shows that individuals vary considerably in their ability to search for and retrieve information, and that appropriate search strategies are often overlooked (British Library, 2008). 

• The economic dimension highlights a whole set of factors that need to be applied when deciding what, where and how to learn. These decisions cannot be based on naïve perceptions of the old need-to-know approach that is still prevalent in today’s workplace.

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PEDAGOGY WITHOUT A TEACHER: WHAT ARE THE LIMITS?

Paul Bouchard

Today’s workplace is characterized by a growing expectation that employees will learn on their own what they need to learn in order to meet productivity goals. However, self-directed learning is not a simple “either-or” equation. Careful analysis must be applied to the various dimensions of self-directed learning in order to determine whether our choices will promote or hinder the emergence of effective learning behavior. This article identifies four such dimensions and offers a brief outline of each. They are the algorithmic, the conative, the semiotic, and the economic dimensions of self-directed learning. Each of these discrete dimensions and their sub-factors offer considerable potential for developing self-directed learning behaviors and environments. They also point to the fact that by ignoring these important dimensions, we run the risk of significantly reducing the probability that self-directed learning projects will occur or be successful.