Learning Control: Sense-Making, CNC Machines, and ... - Springer Link

Vocations and Learning (2009) 2:177–194 DOI 10.1007/s12186-009-9023-8 O R I G I N A L PA P E R

Learning Control: Sense-Making, CNC Machines, and Changes in Vocational Training for Industrial Work Boel Berner

Received: 22 October 2008 / Accepted: 30 April 2009 / Published online: 15 May 2009 # Springer Science + Business Media B.V. 2009

Abstract The paper explores how novices in school-based vocational training make sense of computerized numerical control (CNC) machines. Based on two ethnographic studies in Swedish schools, one from the early 1980s and one from 2006, it analyses change and continuity in the cognitive, social, and emotional processes of learning how to become a machine tool operator. What and how students learn will become part of their self-understanding, future vocational identity, and sense of what they know. The paper discusses in detail the various tasks involved in learning CNC and how students and teachers understand and handle their everyday encounters with the machines. The study combines a situated learning perspective with one from science and technology studies, which focuses on how a technology’s script is made workable, or “localized”, as part of ongoing activities and interactions in the school. Keywords Vocational training . Sense making . Novice learning . CNC machines . Localization . Ethnographic revisit

Learning Control Computerized numerical control (CNC) is one of a class of new electronic technologies that, in recent decades, has fundamentally affected the traditional organization and definition of many industrial jobs. Modern machine tools operate under computer control, according to either programs written by machinists or longer, more complicated programs written by programmers. In this way, complex components can be shaped more accurately, much faster than through manual machining, and in a more flexible way than in earlier forms of automation. Operators’ work may now include tasks such as machine tool set-up, programming,

B. Berner (*) Department of Technology and Social Change, Linköping University, Linköping S-581 83, Sweden e-mail: [email protected]

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troubleshooting, and repair, depending on the organization of production, but not the direct machining of parts. These changes raise questions about the kinds of skills operators now need in order to use the new machines competently, and how these skills should be learnt. This paper discusses how 16–18-year-old beginners in vocational education learn CNC machining, more or less “from scratch”, their only knowledge of machine work being that acquired at school. The paper addresses the following questions. How do these students and their teachers make sense of what should be learnt and how? What learning activities are involved, and what are the problems with which the students struggle in interacting with the machines? These questions will be addressed here with the help of an ethnographic study conducted in a Swedish vocational high school in 2006. To gain perspective on the skills to be learnt and on student interactions with the machines, the results of this study will be compared with those of an earlier one conducted in 1983 in the same school. This comparison leads to an auxiliary research question: What are the most important changes, and continuities, from before the advent of CNC machines to the present in learning how to control and make sense of machine tasks?

Theoretical Perspectives There is a vast engineering literature on CNC technology, a less extensive one on its implications for operators’ work and skills (for overviews, see Kelley 1986; Pagell & Barber 2000), yet the literature includes very few studies of learning processes with CNC machines. The few such studies that exist mainly focus on what experienced operators have to relearn as they switch from traditional ways of working to the new technology. The research most relevant to the present study is that of Martin, Scribner, and Beach (reported in Martin 1995; Martin & Scribner 1991; Martin & Beach 1992). Using an activity-based approach to cognition, these researchers investigated the intellectual demands posed by the new technology. This ambitious research conducted in several settings encountered a number of difficulties when trying to identify the cognitive changes involved in switching from conventional to CNC machines (Martin 1995). The present study shares that previous work’s commitment to understanding the tasks involved in handling CNC machines in the performance context. This focus involves looking at the specific practices in which CNC is introduced, at the individuals involved, and at the conditions under which they use the technology (cf. Martin & Scribner 1991). The current study differs from the previous research in three respects: first, as already mentioned, the current study focuses on vocational education students rather than experienced workers; second, it problematizes the introduction of technology into the learning environment; and third, it considers aspects other than cognition in exploring the manner in which teachers and students make sense of the machines. Turning first to research into vocational education, there is an interesting lacuna. Few studies deal with education for industrial trades, and those that do, mainly discuss the advantages and disadvantages of workplace or apprenticeship training (e.g., Billett 1995), while seldom analyzing the nature of training in a school setting. This limitation means that sociocultural theories of learning, which focus on the

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gradual introduction of novices into a community of practice (e.g., Wenger 1998), are less useful for the present analysis: schools lack such a community in which students can participate. Instead, the analysis must consider the institutionally specific characteristics of schools, such as an orientation towards individual learning and evaluation, the organization of students into classes and time into lessons, a set curriculum, and, in the case of vocational training, an indirect and even problematic connection to the ‘demands’ of working life (cf. Berner 1989; Bernstein 1977; Grignon 1971; Hodkinson 2005; Hodkinson et al. 2008; Resnick 1987). Second, I turn to the role of technology. Most studies of vocational training, even for industrial work, do not problematize the techniques and technologies to be learnt. Machines are often treated as the ‘context’ of learning, not as problematic objects to be handled or understood, or with which to interact. One reason for this omission may be the predominant interest of many studies in how vocational identities are formed, rather than in how particular vocational skills are learnt. However, work identities are hard to understand without considering the practical skills that members of a particular work environment are expected to have learnt and know, or not managed to learn (cf. Brockman & Dirkz 2006; Suchman 2000). Some other approaches to studying learning pay greater attention to technology. Activity theory, for example, is concerned with how material objects are drawn into ongoing activities (e.g., Engeström 2001). Tools (and symbols), however, are mainly treated as mediators for how tasks are accomplished, not as objects that people have to learn and understand. Other approaches focus on learning as innovation, that is, as the creation of new knowledge, technical or otherwise (Paavola et al. 2004), or on the ‘cognitive demands’ new technologies place on workplace learning (Torraco 2002). Neither approach, however, is entirely relevant to an analysis of how an existing technology is learnt in a school setting. Insights from science and technology studies (STS) are useful in understanding how the material world intervenes in learning activities. These insights focus on the intertwining of the ‘material’ and the ‘social’ in constructing technologies and on how tools and machines (re)configure practices and identities at work (Grint & Woolgar 1997; Berner 2008). Such a focus involves looking at how students and teachers, on the one hand, must accept the ‘script’ inscribed by designers in the machine. The script defines the relevant context of use, who is a competent user of the machine, and what is expected from the user (Akrich 1992). On the other hand, STS scholars argue that necessary skills cannot be derived directly from the properties of the technology in question; instead, skills are interpreted and reconfigured by the actors involved. To integrate a technology into everyday practices and make it work involves what researchers have variously called ‘description (Akrich 1992), ‘localization’ (Berg 1997), ‘reconstitution’ (Johnson 2004), and ‘articulation work’ (Star & Strauss 1999), all of which are procedures of interpretation and trial and error. Timmerman and Berg’s concept of ‘localization’ is helpful to understand how CNC machines are used in the school setting. The concept refers to how a technology’s script is articulated in relation to various relevant actors’ trajectories (cf. Timmermans & Berg 1997). Each actor in the school follows a trajectory, which refers to a past, present, and possible future. The human actors examined in this study were students and teachers. The students were adolescent boys with an often

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poor school record and a far from settled future work situation. They were relative beginners in understanding how to use the CNC technology, having had only a short introductory CNC course in their first year; in the second-year class that is the focus of the current study, they encountered more complex tasks, and in the third year — if they succeeded in the first steps — they would be introduced to more advanced programming. The teachers were former manufacturing workers who, via teachers’ training college, had moved to a ‘higher’ social position, albeit in a low-status programme in the school system. Other elements in the school situation follow trajectories, too. The machines used in the school were 10–15 years old and no longer advanced. Two of them were similar to those used in industry, while the five others were special training machines for school use (cf. Lewis 1998). Other material elements were handbooks, pieces of metal to be worked on or already finished, drawings and process sheets at various stages of completion, tables, and measuring instruments. There was also a curriculum to be followed, there were rules and procedures for grading the work, as well as school routines (e.g., bells), other teachers, and other school subjects to which to relate. This assemblage of heterogeneous elements with their varying trajectories constitutes the specific learning environment of the vocational school; the collection of elements defines the learning environment and distinguishes school training from workplace training in the same technology. Third, there is sense-making, here understood as cognition but also as social and emotional understanding of the machines. The analysis of cognition is inspired by H. L. and S. E. Dreyfus’s (1986) five-stage model of skill acquisition, especially their discussion of ‘novices’ and ‘advanced beginners’. According to this account, a novice has just recently encountered the particular object to be learnt. The advanced beginner has had some experience in actually coping with real situations and has begun to develop an understanding of the relevant context. The Dreyfus model has been criticized for not easily fitting the real world and may, as one study concludes, instead reflect “the structure or the way skills are taught, rather than the way they are learnt” (Farrar & Trorey 2008, p. 47). Here, the model is used tentatively for just that purpose, to analyse how teachers and students, individually and together, interpret the tasks to be learnt. Thus, interaction and interpretation, rather than “acquisition” (cf. Sfard 1998; Mason 2007), are the focus here. Novice learners, H. L. Dreyfus argues, are confronted with instructors “decomposing the task environment into context-free features that the beginner can recognize without the desired skill. The beginners are then given rules for determining actions on the basis of these features, just like a computer following a program” (Dreyfus 2004, p. 177). Not only facts or rules are presented, however. Novices must also gain an understanding of the context in which the information makes sense; later on, they must learn to recognize the context, and the advanced beginners are expected to be able to see new situational aspects and not only the nonsituational clues taught to novices. This cognitive perspective takes us some way towards understanding what occurs in the CNC training class. However, sense-making is social and emotional as well as cognitive. In line with sociocultural theory, the machine is a tool for thinking and acting in the world, and the technology is regarded as embodying preexisting concepts and cultural assumptions (cf. Säljö 1999). In an important historical analysis of the origins of the forerunner to CNC, that is, numerically controlled (NC)


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machine tools, Noble (1984) concluded that such machines were designed to dispossess all-round machinists of their skills; a capitalist political script was thus inscribed or embodied in the technology. Noble’s interpretation has since been questioned, as researchers have documented the very different ways that such machines have been used or, in my terminology, ‘localized’, in specific social settings (e.g., Kelley 1986; Pagell & Barber 2000; Whittaker 1993). In the school setting analysed here, these contradictory social interpretations are present in the everyday sense-making concerning the machines. CNC technology is depicted as both enabling and restraining, and mastering it is seen as promising both an interesting future working life and the opposite. Finally, learning processes are emotional processes, linked to experiences of failure or mastery of school tasks (cf. Zembylas 2007). Students, individually and collectively, make sense of their encounters with the machine as stressful, joyful, or tedious, or all three simultaneously. Learning control will thus be analysed here as an intertwined cognitive, social, and emotional endeavour, taking place in situated encounters between machines, teachers, students, past individual experiences, and a projected trajectory into a future vocational identity.

Methodology In Sweden, unlike in many other industrial countries, vocational training is part of upper secondary school. In 1983, I conducted a year-long study consisting of participant observations in two Swedish vocational schools and interviews with a number of teachers and students; the focus was on the teaching and learning of machine tool skills (Berner 1989). Over 20 years later, in autumn 2006, one of the schools studied in the early 1980s was revisited (the other school no longer offered the studied programme). Interviews and observations were made in the second year of what is now a three-year programme including more academic subjects than before. Workshop and classroom activities in school are today combined with at least 15 weeks of workplace practice (not discussed here). Twenty-five years ago, the corresponding programme lasted only two years, had fewer academic subjects, and included little or no workplace-based training. The 2006 study was conducted by a research assistant. It included 2 months of observations in the school workshops, audio recordings of interactions between students and teachers, and interviews with teachers and students. The autumn term studied here had two CNC training periods per week. Students spent a varying number of hours at each machine, depending on the time needed to finish different training tasks. Semi-structured and audio recorded interviews were conducted with the five students present in the class and with five teachers who were involved in varying capacities with these students. The interviews lasted between 30 min and 2 hours and focused on the skills and problems involved in CNC machining and on the future work prospects of the students. The audio recordings and interviews were transcribed in full and analysed, with a focus on themes emerging from the material (Berner 2005; Coffey & Atkinson 1996). There were difficulties involved in interpreting interactions with CNC machines, as also noted by other researchers (Perret et al. 1995). Exchanges between

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students and teachers, or between the students, are difficult to understand without knowing the specific objective of the activity involved. In addition, vital information is often lost due to noise in the workshops. The interpretations given here of the audio recorded interactions therefore do not try to capture individual details of tasks or cognition but rather more general aspects of the training processes involving CNC; these interpretations are complemented with information from field notes and interviews, manuals, and secondary material. Emerging themes were systematically related to material from the 1980s study to shed light on issues of continuity and change in how teachers and students make sense of the technology to be learnt (cf. Burawoy 2003). In what follows, students are anonymized using names beginning with an “S”, teachers with a “T”. Teachers in the 1980s study are referred to as they were in that study, using a letter (e.g., B or X). Quotations are slightly edited for readability. The discussion begins by considering what students have to learn about CNC by relating it to how a worker is expected to handle so-called ‘conventional’ machines. The following description comes from a Swedish CNC manual (Lindén 2007, p. 34): In manual machining with a conventional lathe, the operator gets all his information from the parts drawing and the work preparation sheet. In the operator’s brain, this information is treated and transformed into “orders” to his hands that handle the machine. While machining, the operator checks that the cutting tool is moving in the right trajectory in relation to the work piece. The operator’s brain will then compare the result with the drawing and the preparation sheet. The manual describes that these activities change with the use of CNC machines, the main difference being that the machinist no longer controls the metal-cutting actions of the machine by adjusting hand levers. Instead, a computer program directs the machine. A worker thus has to learn, first, how to plan the work of the various tools and parts involved, then how to program the computer so that the tools and parts will do what he or she plans for them to do, and, finally, how to run the program on the machine and successfully trouble-shoot if problems arise. Next, are discussed how these three sets of activities were taught in the class studied in 2006 and how they differ from, or resemble, comparable activities involved in learning to use conventional machines.

Setup: Getting Everything in Place Set-up is the first step, when the appropriate tools and materials have to be assembled to machine a particular part. CNC machines have turrets with different tools that are programmed to machine the metal part in various ways and in a predetermined order. According to Martin and Scribner (1991), before the introduction of CNC, machinists often made mental notes of the steps to be taken and tools to be used, and plans were adjusted as needed. This process made use of machinists’ experiential knowledge, and machinists often kept private ‘recipe books’ to keep track of how they did things. This way of knowing changed with the advent of CNC. Now there


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had to be fixed written plans with each tool having an identification number, a procedure that, according to Martin and Scribner (1991), demands a new need for explicitness. What was previously private knowledge now became a matter of public record (Martin & Scribner 1991). In a school setting, such explicitness was already the rule. First, for a social practice, such as machining, to become a school task, it must be made explicit, verbalized, and organized into parcels of knowledge that can be taught and assessed. Second, students, even with conventional machines, must learn how to plan their work in an explicit and systematic way. The necessity of such prior conceptualization was emphasized repeatedly by the teachers in my 1980s study: Interviewer: What are the most common mistakes that the students make in machining? Teacher (O): A lot are careless mistakes. I guess it has to do with age … They don’t think enough before starting work. They are always in a hurry … ‘Before you start the job’, you tell them, ‘you should sit down in peace and quiet and look at the drawing. Think about it step by step. Now I’ll do this, and then I’ll do that and then I’ll do that …’ Then I come back and ask, and they have already started. ‘But, now when you have done this — how will you do that?’ They haven’t thought about that. They are in too much of a hurry. They think too little. (Berner 1989, p. 129) Thus, in the 1980s and with conventional machines, students were urged to verbalize their working order and specify materials, tools, and steps in a preparation sheet, before starting work at the lathe or milling machine. With CNC machines, this task becomes even more imperative: without such preparation, the machine cannot be programmed or run. The students must ask themselves what kind of machine is to be used, what tools, what material with what characteristics, what type of machining, and what cutting speed and feed rate are to be used. Given the elaborate and standardized nomenclature used for CNC machines at each step and with each tool used, students must learn how to follow handbooks and manuals to understand the symbols for different materials, thread types, drawing details, and machining methods. In both the 1980s and 2006, the students were taught the various rules to follow, nomenclatures to use, and tables to consult to get the right results. In addition, rulebased instructions have always been accompanied by encouragement to contextualize the information in an industrial setting. Good workers, the teachers insist, must consider the temperature at which the machine will be used, the load on the part, economic circumstances, et cetera (cf. Lindberg 2003). They must make allowances for different kinds of machines, with different steering systems and commands. Thus, although learning and following rules is strongly emphasized, teachers constantly refer to conditions of use in industry, which may alter the strict application of the rules.

Programming: Visualizing Machine Movements in a Geometric Space The next step in 2006 was to produce a detailed programme for the CNC machine. This was done through detailing line by line, step by step on a process sheet the

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various operations (called blocks) to be executed by the machine. The information was then entered into the machine’s computer programme, whereupon the computer would simulate in three dimensions what the product would look like; the student would then compare this image with the drawing. Programming demands that the students learn to visualize machine movements in geometric space and express the steps to be taken when machining a certain part in that space according to standardized rules and commands.1 Thinking in three dimensions is central to machining, and not just with CNC machines. Both in the 1980s and 2006, students had to understand drawings, symbols, and nomenclatures. “If you cannot interpret those, you can’t machine a part, even if you are the world’s best machinist. If you cannot read drawings, you can’t do anything yourself”, one teacher argued in the 1980s (Berner 1989, p. 125). In 2006, the need to understand the particular language of drawings was underlined even stronger; teacher Terry explained: You could say that if you have a drawing, you should be able to visualise the part that is drawn. You should almost see it in front of you, as a product, in a way … This is not just a drawing, it is a finished detail. And the detail could actually look like this! Then the point is that you should be able to see what it looks like when it’s placed like that. And then you should be able to see it from above — yes, then it becomes that big. But if I turn it in that direction and you look at it from above, then it would become very thin here and high there … This all is about three dimensions, being able to see it in three dimensions and from different perspectives. (Interview 2006) The three-dimensional interpretation of drawings comes more easily to some students than others: “Yes, I see what I think are figures … like in my head, how it looks in reality. But not everybody thinks like that” (Steve). “For some students it is too abstract [one teacher said]. They cannot use a drawing, they do not see … They may understand the symbols and so on, but they do not get the design … [But] this is not just a line, it’s a product.” (Terry). Students must also know how to calculate the cutting speed correctly, and this task presupposes a previous understanding of formulas, decimal fractions, and negative numbers (Bredberg 2005). To select the coordinates used in programming, students need to understand the Pythagorean theorem, and now even some elementary trigonometry: “If you do not master that, you will never be able to program a CNC machine”, one teacher argued. “You can press the “On” and “Off” buttons, that’s the only thing you can do. Because you cannot alter the programme yourself.” (Thomas) Programming was seen as difficult by the students interviewed in 2006. The general problem was how to relate the various numbers to concrete operations. How A programme contains a large number of signs (i.e. numbers, letters, + or –, or special signs), and groups of signs denoting an address. An address indicates how large the movement of the tool should be, and in what direction, for example, z-40. A starting point (zero) must always be specified, and all movements from that point described in the coordinate system, which is either in two dimensions, i.e. x and y (for turning), or in three, i.e. x, y, and z (for milling). Everything is expressed in an ISO-standardized way with codes, such as G00 to G98, indicating commands (e.g. G81 for feed and rapid traverse back), M00 to M99 for miscellaneous functions such as coolant or constant spindle speed, and T for various tool functions (Lindén 2007; Eriksson and Karlsson 2000).

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is one to visualize movements in three-dimensional space in relation to feed rate, cutting speed, the metal part, the tools, and what the drawing says? Students found it difficult to switch between turning and milling with their quite different uses of the coordinate system. They became bewildered about the order in which to do things, very often forgot a step, or were confused as to whether it should be + or −, or x, y, or z in the program. Remembering the correct nomenclature was also difficult. Students tended not to be consistent in the symbols used, or used the wrong symbols, sometimes getting completely lost. One reason for confusion was the fact that the concepts used in the simulator were expressed in English: “Damn it, I don’t understand what it says here [one student said and pointed to the simulator screen]. There are 55 different tools all in all, so it is not easy to choose one when you’re not sure of your English.” Most interactions seen between teachers, students, and the machines involved what Dreyfus (2004) calls ‘context-free features’. A novice student has to follow rules for how to combine the various elements in a step-by-step sequence of operations for the machine, “just like a computer following a program” (Dreyfus 2004, p. 177). Once the students get beyond the novice stage, however, the teachers expect them to have internalized the rules and the vocabulary. Thinking in terms of the terminology, one teacher said, is something that students should be able to do almost automatically, once they become accustomed to it. Here the teacher Terry is telling the student Steve how to start programming with the help of standard procedures: Terry: Then G40 must be there and it tells us to move from our radius compensation here … It is the same in every program and if you don’t remember it you will never succeed! Steve: No. Terry: There is the starting block and the finishing block. This is like a mantra. There are no surprises, there are no surprises. It is just the same, it’s the same thinking all the time [tapping the drawing to emphasize what he says]. Then the coordinates may differ a little depending on the zero. Then we change it here, it’s the contact point. Steve: Yes. Terry: But this must be there, we must specify the origin, we must specify the tools … Now at least you can start the program. The teacher anticipated the students would reach a stage in which they would not have to follow all the detailed rules for writing a programme. The teacher Thomas told one of the students: Not all information needs to be programmed into the machine. Everything is over there. But since we are a little uncertain, I will enter it here so that you’ll remember it. But when you get a bit better later, you will ignore this, because you’ll already know it. But now, when you do this part — to get a complete structure with too much information, really … we will write it all, with commas and the lot. We do not remove anything. The students were expected to learn from experience, and remember and use stratagems similar to those used in previous tasks: “Do it the way you did it last

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week,” Thomas often said. “Look at how you did the last piece, and do it like that again.” There is a pattern, a ‘mantra’ that the students should internalize. Likewise, the students quite often presented ‘maxims’ about how things should be done, based on their own experience and on the teachers’ rules of thumb. As noted above, it was important also in the 1980s, and with conventional machines, to be explicit and learn how to plan one’s work. Students had to think through the sequence of operations line by line, use some mathematics, and study tables and handbooks before starting work; there was often a logical order to follow when machining a piece. Thus, one could argue that there is continuity in the skills needed between the 1980s and today. However, three things have changed. First, the worker’s body is no longer needed for the actual running of the machine, as machining is now done automatically, behind closed doors and glass windows. Second, the new task of computer programming has appeared, placing strong demands for three-dimensional reasoning. Third, the need for rule-based explicitness and detail has vastly increased. Improvisation and trial-and-error procedures are much less possible; instead, every step must be thought through and specified in a detailed and standardized way, before the machine is started. Students in the class studied in 2006 experienced this contrast, because they were taught to use both CNC and conventional machines. To these students, the manually operated lathes or milling machines allowed for greater personal control, improvisation, and flexibility. As one student, Silas, said: “I have done this myself, with my own hands; it’s not the computer. You turn the knobs yourself with your hands; it’s not the computer that turns them for you. This sentiment was echoed by another: Spike: But manual cutting is also fun, because then you’re the driver. You twist all the knobs and things, and it goes around and carries on … Interviewer: You steer, you are more in control in manual cutting, or … ? Spike: Yes, then you do it all by yourself. You turn the knobs, it feels more like your own hand doing it … and while you are working, you can think more than with a CNC machine. Because when you’re using a manual machine, it’s like, ‘If I have done it like this, aha, I can start doing it like that instead’. And go, like, step by step. .. and then it’s nice when you like draw and turn. It is you who governs it in a way. It is not [like] the [CNC] machine where you have just clicked a button, and then it goes around. In the schools studied in the 1980s, such manual improvisation and experimentation were ubiquitous. Students were encouraged to try out new ways of machining and use trial-and-error in solving upcoming practical problems (Berner 1989). In 2006, students still were taught how to use conventional machines and get a feel for their functions and capacities. However, such manual tasks were seen as less important than the intellectual ones required with the CNC machines. The students, being inexperienced beginners, could not yet improvise or try out alternative ways of programming or set up; they had to stick to the rules. That the students experienced these tasks as constraining and less creative than those involved with the manual machines is not surprising.


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Running the Job: New Kinds of Feedback In the 1980s, when NC machines were new, we interviewed teachers about how they felt about this new technology. Several tended to dismiss the threat that these would take over the job of the skilled machinist. One teacher put it like this: [The NC machine] must have me — my knowledge, my experience — to function. You can’t just push a button and then the machine will take care of itself. I must listen to hear if the machine is working right, if the sound is right when the machine is cutting. All this is still with me, and that is the most important thing. These qualities will not disappear, rather the opposite: they will be reinforced. Because if such a machine breaks down, it is me, the operator, who must push the button. The machine does not push the button. It may feel a greater load and then it may be too late. You can insert a brake, but this may not be necessary if you have good hearing and really know your stuff. (X) (Berner 1989, p. 119) This teacher hinted at two related things: A skilled machinist would still be needed to do troubleshooting, and sensory cues would still be important in understanding what has gone wrong. In my 1980s study, I found that the importance of personal, sensory cues was constantly emphasized; one teacher said: “You hear with your ears, you see from the shards when cutting if there is flow. Then it sounds like a beautiful song. If it sounds disturbing, it is not working as it should” (B). Another showed the students how they could judge surface roughness with their nails; a third recommended that the student touch the machine when it was turning, “So you can feel if it is vibrating or not, at the right speed. The manuals give too high a speed. That is totally wrong” (Ö) (Berner 1989, p. 117). How relevant is this sensory feedback today, with the automated CNC machines? The students in 2006 encountered feedback in two kinds of situations, one with the simulator and one with the trial run on a piece of metal. The simulator is a device that depicts the part to be machined in three dimensions according to the programmed parameters. The students were expected to compare this simulated image with the original drawing. However, the simulator picture is incomplete; it does not show, for example, whether one has put in the right tools or if the speed is correctly calculated. The students were often bewildered about why the simulation differed from what they had intended and why the simulator’s alarm was triggered. Interestingly, the teacher was sometimes also just as confused by what the students had done; then he would often ask them to run the machine in any case: “Run it and we’ll see if it works, otherwise you will have to reprogram it. Test it … do a test piece! If you’re not certain, test it!” Here the teacher Terry and the student Steve do a trial run: Terry: We test, we test — it can’t be worse than wrong. It could be right. Steve: Yes, it could be right, but it could also be wrong. Terry: Well, now it’s starting to look like something. Hello there, can you move this inwards a little, to avoid having the radius out there? [Steve then pushes the button that makes the machine run. The tension is high.] Steve: Yes, look, good God, how nice! Holy shit!

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The trial run is a moment of truth and an occasion for expressing emotions. It is something you really look forward to, one student says, to see the results after all the tedious programming. Other students were more anxious and tense. Those not running a machine often gathered around the person who was going to do a trial run, to advise, encourage, or challenge. When things did not work, there was a lot of collective guesswork as to the reasons why. In many situations studied, the students could quite quickly see or feel that something was wrong: The piece was too short and nothing happened, or it was too long and started wobbling and vibrating. Most telling, however, was the feedback to the ear; a teacher said: “Often you notice when you start that there will be a terrible noise — that is a common sign that you are running it too fast. The machine will squeak and grumble.” If the programming is wrong or the speed too high, the tool might bang into the piece with a terrible clamour, and if the operator does not reach the emergency stop button quickly, something disastrous could happen: Thomas: Yes, it might get too hot. It might go too fast. Yes, it might even go too slow! Interviewer: What happens then? Thomas: Too slow! Often bad surfaces. Wears the tools down terribly. Important for the tolerances. Vibrations, and … I: If it goes too fast, then? Thomas: Then the tools will burn themselves out. Then things happen fast! That the students sometimes hesitated to start the machine is not surprising. They were afraid of destroying the machine, the tool, or the work piece, all things that were expensive. To be on the safe side, several preferred to run the machine manually at first, either very slowly or one step, or block, at a time. In that way, they could sense whether they were in control and immediately stop the process if necessary. How did the students interpret the various sensory and other cues? According to one teacher interviewed, the students tended to blame the machine if something went wrong: “Yes, the machine did it all wrong. — But, couldn’t you have …? No, the machine was wrong!” (Thomas). It is as though responsibility for the activity was left to the machine, which was given the task of testing the worth of the decisions made (cf. Golay Schilter et al. 1999, p. 19). However, the teachers argued, the students must learn that the machine itself cannot make mistakes: “The machine does not invent any surprises of its own for us, if we have not programmed the surprises ourselves,” said one teacher, Thomas. The students reluctantly agreed: Well, most often the problem comes when you run the machine. And when it goes wrong … you stand there and swear for a while and say, bloody machine, damn it, and all that, the whole rigmarole. And in your heart of hearts you know that it is you, who has done something wrong. (Spike) There are many ways to do things wrong: measuring poorly, using the wrong tool, or, most often, programming incorrectly: “Perhaps you have chosen too fast a speed, and then it just goes on cutting and the part breaks and everything,” one student (Silas) said. “Probably you have written something wrong in the program, like you


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have forgotten something. Or have set the wrong zero, or …,” said another (Simon). The students have to reason logically about the problem, and this reasoning was not easy for them: “You do everything to move forward, but sometimes it just does not work. Because you have no [clue] … you do not understand at all what you are doing, or seeing” (Simon). Being novice learners, the students had not yet acquired a mental model of the situation that would help them see the tool, the piece, and the programme in relation to one another, and that, according to Dreyfus (2004), characterizes the competent user. Nor did they, as yet, have a mental repertoire of previous problems and solutions that would help them grasp what has gone wrong.

Mastering the Machine There is a strong element of constraint in how novice students can use the machine. They have to obey the script embedded in the machine’s design and, thus, the possible meanings and uses of the technology are circumscribed. They cannot yet improvise the way they (think they) can with conventional machines. CNC programming — with its disciplined steps and exacting demands — was therefore not immediately appealing to the students. Just pressing a lot of buttons was seen as boring and even mysterious work, divorced as it was from hands-on machining, of which one is in control. The individuals recruited to this programme are students who distrust their own capacity. They have often failed in traditional school subjects and are not strongly motivated. In the 1980s, they could take pride in mastering manual tasks with conventional machines. However, as one teacher interviewed said in 2006: CNC is no longer practical. There are a lot of codes, deeper thinking, numerical control … Not everybody can handle all this. They cannot fix it ... Some of them need an instructor of their own, but we do not have the means for that. They must master maths, mental calculation, keep track of figures and codes. You get stuck, you cannot solve it. They try, maybe, but that doesn’t make them into CNC operators … It is not surprising that they lose the spark. (Timothy) Students tackled the difficulties differently: Some improvised, others tried again and again, still others kept asking the teacher for advice, or gave up. In the school studied, several students never got further than the first year introductory course, and much encouragement and support were needed to keep others on track. Again and again, the teachers underlined that the students had to use their own judgement, and not be overwhelmed by the power of the machine: they should be the ones in command. “You must set up the tools, it is you who decides!” the teachers said. “It is you who decides how much that first cut will take. It is wholly and only you who decides.” The machine may ‘want’ to do various things, but it was the student who should tell ‘him’ (as the machine was often referred to) what to do. Asserting one’s agency against that of the machine should result in both scholastic and vocational success. The machine might appear mysterious and somewhat frightening, but it could not do the work alone; a competent machinist was needed to help it along. Although programming and set-up steps were seen as tedious by the

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students, the actual running of the machine was often described as “fun”. Then there was excitement, and the hoped-for concrete proof that the student was in control: Silas: Then he [i.e., the machine] goes straight out there, to that point there. Thomas: He does exactly what you have told him. Silas: He skips, he skips that block! Thomas: Yes! He skips the block, he runs this as an x 0 z, two more there, and then he goes and gets it. He can’t do it himself. Making sense of the machine was an emotionally charged endeavour, involving boredom, excitement, disappointment, and even joy. Sense-making was social, in that it was often undertaken collectively with other students or with the teacher. It was social also in the sense that the tasks to be learnt were continuously defined and redefined in a hierarchy of more or less desirable work. One student had originally seen CNC machining as not quite manly: Spike: Well, at the beginning [of the first year] when we had to chose, I thought, ‘No, I will do welding. Because CNC is a little nerdy, it’s for old women. I won’t sit and peck away like that’. Interviewer: How did you think about it then? Spike: Well, it seemed like a lot of detailed picking and pecking. And welding was rougher. There you could, like, bang things together and if it was a bit crooked it was still OK. And here you have such exact measurements to deal with. And at the beginning, I was not so good at that. Yes, that was the worst problem for me, when they kept insisting on exact measurements. In the 1980s, the professional pride of the competent machinist was strongly linked to this demand for exactitude. Being careful and precise was a sign of proficiency in industry: being able to “target the thousandths”, as one teacher put it, not the hundredths, as in sheet-metal work. One must know that when the drawing calls for a tolerance of 4/100, one should and can execute that and not 5/100 or 3/100 (Berner 1989). Twenty-five years later, CNC machines can obtain this precision with greater accuracy and speed than any human operator. The professional competence that the teachers were now trying to convey was therefore different, broader, and more theoretical. The students had to think in three dimensions, understand drawings and programming, and employ complex rules and nomenclatures; they must be able to troubleshoot from various sensory and nonsensory machine cues, and still do some hands-on machining themselves. This was a combined manual and intellectual competence and a new kind of vocational identity that the teachers hoped would secure jobs for their students. This hope was echoed by the students: Today, smaller companies want a CNC operator who can do everything … Earlier it was often that … here comes one of those office nerds with their drawings, and tells you ‘Do this, do that!’ Now you will be in it from the very start to the end. And you are supposed to do everything, most of the time. (Spike)


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Localizing the Learning of Machines in School Settings Learning control involves a number of complex cognitive tasks that have a strong focus on rules and nomenclatures. As Martin and Scribner (1991) argue in their study of how experienced workers learn CNC, workers must acquire a form of rulebased discipline, in contrast to the action-based schemata developed when working the machines in the formerly conventional way. Machining tasks have become mental problems to be solved with the help of rules and heuristics, rather than activities in which solutions unfold. These insights are also relevant to the school setting studied here, where young novices learnt CNC. I have compared today’s situation with how the tasks of drawing analysis, set-up, and manual machining were conducted in the early 1980s. Though there are several similarities, the advent of CNC machines has created new kinds of cognitive tasks. Students were trying to develop a rule-based approach to work, as Martin and Scribner (1991) suggested. However, the rules also presented new problems: Students were not always certain what the rules were, how the rules were to be formulated, and in what order tasks were to be executed. There was a wealth of parameters and symbols to keep track of, complex instructions, and a novel way of thinking in three dimensions, which was not intuitively easy to grasp. Unlike the situation in the early 1980s, sensory and bodily cues were downplayed in favour of intellectual troubleshooting, looking at computer screens, or checking programme sheets for faulty codes, wrong coordinates, or other abstract mistakes. To localize the machine’s script in the school setting, students had to enter into a mental and physical dialogue with it. Teachers urged them to ‘talk’ with the machine via the simulator, and make it ‘understand’ what they meant. However, as observers of work situations have noted, “newcomers do not yet have that dialogical relationship with the work and the machine and therefore must search for the dialogue with someone who does” (Brockman & Dirkz 2006, p. 212). The students did not always understand the cues given by the machine or the program, and therefore relied on others to help them develop this ability. In the school setting, there was no ‘community of practice’ to which to relate; these ‘others’ were, therefore, primarily teachers. The predominant mode of dialogue observed was step-by-step coaching by the teachers, combined with the dispensation of maxims based on the teachers’ experience and efforts to contextualise the task and the machine in a wider social environment. The localization of the machine in the school setting thus involved both a cognitive understanding of the machine’s script, intense social interaction, and an emotionally charged sense-making of the tasks to be performed. Students had to understand, but also be motivated to understand; they had to trust their own ability despite earlier failures and intellectually challenging demands. Everyday interactions with the machine were therefore a mixture of private coaching with the teacher and collective trial and error, and of concentrated effort and disappointed withdrawal. In line with other recent work, this paper has combined a cognitive-oriented and a sociocultural discussion of vocational training (e.g. Billett 1996; Hodkinson et al. 2008; Mason 2007; Sfard 1998). Some of the implications for further study are as follows. First, there is value in focusing on how novices and beginners are taught and understand complex new tasks. Such an analysis may highlight difficulties and

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stratagems and make explicit the taken-for-granted and incorporated knowledge of the expert or advanced learner. Second, the cognitive processes should be understood in the context of everyday performance. They make sense only as part of ongoing activity, and in relation to the social and emotional trajectories of the individuals involved. Also, the particular organizational setting may be important. As Billett has suggested, “cognition is not ‘situated’, rather, it is influenced by circumstances and activities provided by the situation in which the engagement in problem-solving activity occurs” (1998, p. 260). I would argue that more attention should be paid to the specific institutionalized “circumstances and activities” of school-based training, specifically, how they influence the learning of a vocation and how this learning relates to workplace training of similar tasks. Finally, the technical detail of tasks themselves, should be taken seriously. This is important for two related reasons. Advanced technologies making new kinds of knowledge demands are being introduced, not only into industrial occupations, but also, for example, into medical and caregiving work, administration, and teaching (cf. Torraco 2002). What kind of training will workers need in order to gain control over this technology, their work situation, and careers? The various ways in which these technologies are handled and made sense of, and what and how students learn, are important both for their present self-understanding and their future vocational identity. For this reason, too, technologies should be analysed in studies of vocational education, not only as tools for learning but as tools to be learnt. Acknowledgements The study reported here is part of a larger project financed by the Swedish Research Council: “Experience and Learning in Technology — On Knowledge Formation, Ingenuity and Creativity in the ‘Knowledge Society’”. The author wishes to thank Sabrina Thelander who participated in the research reported here, as well as anonymous reviewers and members of the “Technology, Practice, Identity” seminar group for useful comments on earlier versions of this paper.

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