Near and far transfer

Not all transfer seems to be difficult; Detterman (1993) distinguishes between near and far transfer. Near transfer refers to situations where how something is learned and how it is used are “identical except for a few important differences” (Detterman, 1993: 4). The summer Math programs for elementary teachers (e.g., Carpenter, Fennema, Peterson, Chiang, & Loef, 1989; Schifter & Fosnot, 1993) would be an example of near transfer because the courses focused primarily on how to use knowledge of math for teaching in their particular contexts. Far transfer refers to situations where the learning task and the transfer task are significantly different. An example of far transfer would be reading an academic research study on some aspect of SLA and then trying to use this for teaching, since reading an article and teaching are two very different activities. Detterman argues that while near transfer is relatively common, far transfer is rare: “there is no compelling evidence that far transfer occurs spontaneously” (Detterman, 1993: 18). For example, Reed, Dempster and Ettinger (1985) looked at 48 students solving algebra word problems. The students practiced with the same problem and then were given either an equivalent problem (i.e., a problem where they can use the same basic formula to solve) or a problem that was only similar (i.e., a problem which requires them to reorganize the formula to solve the problem). For example, for the problem “Sam can type a manuscript in 10 hr, and Mark can type it in 5 hr. How long will it take them together?” an equivalent problem would be “Ann can mow a lawn in 20 min, while Mary can mow the same lawn in 30 min. How long will it take them to mow the lawn if they both work together?” and an equivalent problem would be “A carpenter can build a fence in 3 hr.

but his apprentice needs 6 hr. to do the same job. When they work together to build the fence, the apprentice works 2 hr. more than the carpenter. How long does each work?” It was found that students were generally able to solve the equivalent word problems (near transfer), but if the practice problems were similar but not the same, practice did not significantly help solving the word problem (far transfer).

Studies of doctors also show the ease of spontaneous near transfer. For example, Brooks and his colleagues used 3 experiments to investigate doctors’ diagnosis of skin problems.

They found that “diagnosis of skin disorders by medical residents and general

practitioners was facilitated by similar cases previously seen in the same context”

(Brooks, Norman & Allen, 1991: 278). A study by Patel, Groen and Norman (1993) provides more evidence of near transfer. All seven cardiologists in their study were at least partially successful in diagnosing a cardiology case (four completely correct, three partially), the six surgeons in the study were not as successful (one completely correct, six partially correct), but none of the psychiatrists (who had received full medical training) were able to come up with even a partially correct diagnosis. In a further experiment, the problem-solving methods of practicing doctors and researchers in the same area of medicine were examined. When solving a medical diagnosis task, each used the problem-solving methods used in their practice (much like Bassok’s algebra students). The practitioners found a diagnosis by ruling out alternatives while the researchers tried to build an extensive picture of all the factors involved in the case (Patel

& Groen & Norman, 1993).

Holyoak and Koh (1987) argue that both the surface and the structural similarity between practice and target activities are important. Surface similarity refers to the extent to which activates appear to be similar during a quick first impression. Activities would have structural similarity if the same fundamental processes are used to participate in the activates. Holyoak and Koh used the Duncker radiation problem mentioned above and fashioned four analogous stories about repairing a special kind of light bulb. In the story, either parts of the filament have become fused and need to be broken apart (structurally similar) or the filament needs to be fused (structurally different). In one story, ultrasound is used to break up or fuse (surface similarity) and, in another, lasers are used (surface difference). They found that participants who had the puzzle stories with high surface and structural similarity had little problem-solving the problem (69%). Those whose stories either structural similarity/surface dissimilarity (38%) or surface similarities/structural dissimilarity (33%) were still much better than those whose stories had both structural and surface dissimilarity (13%). Other research using such puzzle stories have produced similar findings (Lockhart, Lamon & Gick, 1988; Ross, 1989;

Krauss & Wang, 2003).

In more contextualized tasks, surface and structural similarity of the practice task to the target task have also shown to be helpful. Chi, Slotta and de Leeuw, (1994) show how conceptual change in biology and physics happens more easily if new knowledge conceptualizes the object of study in a similar fashion to how the person already conceives of it. Thus, it is much more difficult to understand information about acceleration as a process if it is conceived as a thing rather than a process. Wineburg (1998) studied two history professors, only one of which was an expert on US Civil War history. They were asked to analyze and interpret a series of documents related to the Civil War. The professor with expertise in that era had framework for analyzing the documents before he began the process. The other professor had no such framework, but was able to construct one, perhaps because he used the same process in doing work in his own area (i.e., the process was near transfer). Using math problems, Novick (1988) looked at the effects of expertise (high or low math scores on SAT) and surface and structural similarity together. Students practiced a short set of math problems and then had to solve other math problems that either contained some combination of surface and structural similarity or none. Novick found that math novices benefited most from surface similarity while experts benefited most from structural similarity between the practice and test problems.

3.4.4 Experiential vs. theoretical knowledge or near vs. far transfer?

The issue of near vs. far transfer is important because this distinction is often confused with other issues, which makes addressing the problem of transfer more difficult. For example, conceptual knowledge is often contrasted with “experiential” knowledge (Hawkins & Irujo, 2004), although the terms vary. For example, Ellis (1997) contrasts technical with practical knowledge, Wallace (1991) compares received with experiential knowledge, and Freeman and Johnson (1998) contrast academic with experiential knowledge. Studies have shown that teachers primarily use experiential knowledge in teaching (Caspari, 2003; Schocker-von Ditfurth, 2001), and, therefore, are primarily interested in this type of knowledge. “SLA, as an academic discipline, is concerned with the production of technical knowledge, whereas language pedagogy, as a profession, is primarily directed at practical knowledge” (Ellis, 1997: 237). The tension between these types of knowledge is considered one of the principal problems in teacher education:

“the distinction between technical knowledge and practical knowledge lies at the heart of the problem of the relationship between SLA and language pedagogy” (Ellis, 1997: 7).

However, there is a fundamental problem underlying this purported distinction. Listening to a lecture, engaging in research or thinking about academic ideas, each of which is a processes thought to engender technical or academic knowledge rather than experiential knowledge, are experiences just as observing a class or student teaching. Consider the following description of what teachers and academics do:

while teachers must constantly struggle throughout their work day to find ways to meet student needs, motivate students to learn, and develop a curriculum that fits grade level requirements, academics, at best, do this sort of work for only part of the day. The rest of their work is likely to involve developing an understanding of educational issues, reviewing literature on a particular subject, writing up reports and research papers, and conversing with other academics about methodological issues and design questions (Gitlin

& Burbank, 2000: 5-6).

Reviewing literature, writing papers and talking with other academics are experiences that will give rise to knowledge, as are reviewing new teaching materials, preparing lesson plans and talking with other teachers. In fact, it is relatively easy to apply Kolb’s (1984) model of experiential learning, which includes the stages of (a) concrete experience, (b) observation and reflection, (c) forming abstract concepts, and (d) testing these in new situations , to such experiences. Take, for instance, the experience of an MA TESOL student reading a textbook chapter on phrase structure rules. The concrete experience of actually reading the words in the chapter is not enough to form solid knowledge in the subject. (I speak from experience when I report that it is perfectly possible to read all the words of a chapter and still have no idea what it is about.) After step (a), reading the chapter (or, realistically, parts of it), the teacher student can look back at what was read and reflect on what the main points are, what they think the teacher wanted them to learn, and what the teacher will expect them to be able to do to show they read the chapter, step (b). This will probably take a bit of rereading and looking at the examples, but it will hopefully give rise to some abstract concepts answering those questions, step (c). The teacher student then tests these concepts in the next class by observing whether the teacher focuses on the issues that they had predicted, if they can do the tasks the teacher sets (regardless of whether they actually raise their hand and offer to do this, as this can be done silently). They then bring the knowledge of

this whole cycle to bear on the next concrete experience, step (a) again, when reading the next assigned chapter.

Some may counter this argument by defining experiential knowledge as knowledge gained directly from the five senses without any higher cognition involved (e.g.

Brookfield, 1983). Thus, experiential knowledge would be the result of “education that occurs as a direct participation in the events of life” (Houle, 1980: 221). This conception envisions a clear separation between the input from our senses and knowledge arising from using a theoretical idea when observing student actions, from seeking or reading empirical data or from thinking about something, even though these are all things that can be experienced (Jarvis, 1995; Weimer, 2001). Experiential knowledge, it has been postulated, comes from “direct encounters with the phenomena being studied rather than merely thinking about the encounter, or only considering the possibility of doing something about it” (Borzak 1981: 9).

The problem with this argument is that it is an inaccurate picture of how humans take in and process information. We do not record the reports of our senses like a videotape, analyze them in a subsequent operation, and then review them at leisure (LeDoux, 1996).

For instance, even experiential knowledge, such as memories, is just as much a product of our conceptions and cognitions as is data directly from our senses. “Explicit memories, regardless of their emotional implications, are not carbon copies of the experiences that created them. They are reconstructions at the time of recall, and the state of the brain at the time of recall can influence the way in which the withdrawn memory is remembered” (Christianson, 1992a: 210). People’s recollections of pivotal events change through time as they use different conceptions and cognitions when reconstructing their memories (Christianson, 1992b; Loftus, 1993; Loftus & Hoffman, 1989; Neisser & Harsch, 1992).

Instead, the information from our senses activates similar knowledge which is then used to construct interpretations of what the senses report (Berliner, 1994; Ericsson, 1996;

Glaser, 1986). Our conceptions also effect how we perceive objects and situations (LeDoux, 1996). For example, in one study participants were given several identical stockings although they were told that each pair was different. Their task was to choose the one they liked the best and explain why. All the participants not only were able to choose one pair of stockings, but also offered reasons for their choice even though the stockings were identical. In other words, their conceptions of the situation affected the information they received from their senses (Nisbett & Wilson, 1977). Thus, there is no real separation between our senses, our conceptions, and our cognition, and, therefore, all knowledge can be considered “experiential”.

I would suggest that instead of experiential vs. conceptual knowledge the real issue here is near vs. far transfer. It appears that what is called “experiential knowledge” arises from experiencing something very similar to what you will do later (like student teaching) while “conceptual/technical/received/academic knowledge” refers to the product of experiencing something different from what you would do later (like diagramming sentences unlikely to occur in a language classroom). For a language teacher, the first situation would require only near transfer to be used (since the two situations are very similar) while the second would require far transfer (since reading academic works is very different from language teaching). However, for someone who is interested in becoming a researcher in theoretical linguistics it would be the opposite. For

them diagramming sentences not normally used in classrooms would result in

“experiential” knowledge (because it is similar to what they want to do later on), while student teaching would not. Since near transfer is generally much more successful than far transfer, the basic conflict here is exposing novice teachers to educational experiences that require far transfer vs. those that require only near transfer. In other words, when people call for more “experiential knowledge” they are calling for teacher education experiences which would only require near transfer to the practice of teaching.

Furthermore, the distinction between experiential knowledge and conceptual knowledge does not hold up to scrutiny. To begin, perception (e.g., what should lead to

“experiential” knowledge) and processing (e.g., what should lead to “conceptual”

knowledge) of information are not two separate process, rather humans construct their perceptions by combining input from the senses with previous knowledge all in one process. Furthermore, engaging in the learning of academic or theoretical knowledge is an experience itself and, therefore, would result in “experiential knowledge”. The main question is what sort of learning experiences novice teachers are exposed to in teacher education programs, rather than whether learning is “experiential” or not. Learning experiences in SLTE programs (whether this is classroom experiences, doing homework, meeting with professors, etc.) which are similar to classroom teaching (and hence are usually labeled “experiential” learning) such as creating lesson plans, engaging in micro- or student teaching, evaluating tests for specific cases, and so on, are likely to result in near transfer. SLTE experiences which are dissimilar to classroom teaching (which are usually labeled “academic” or “theoretical” learning), for example writing papers or discussing academic theories, would require far transfer and, thus, would be less likely to produce actual transfer to language teaching.