One way to help educators understand the skill demands for today’s pre-baccalaureate workforce is to study work in its context from the perspective of people who actually perform various tasks in the course of their day (Stasz, 1994). The aim of this study was to describe workers’ activities in a company that uses high-tech machines. In addition, we wanted to observe such work in a small business setting, since it represents the work situation for great numbers of people employed in this country. The firm selected was a small circuit-board manufacturing plant located on the West Coast. What did workers in this firm need to know in order to operate new technologies, and just how did they perform this kind of work? This report focuses on machine operators’ problem-solving actions at a computerized circuit-board assembly machine.

Background

Beliefs about the effect of technology on people’s work lives have shifted over time. In the post-World War II era, the increasing automation of the workplace was enthusiastically received; it was hoped that workers would be freed from monotonous tasks and that automation would result in a reduction of work hours. This positive outlook came under attack in the late 1960s and 1970s, however, when studies showed that automation of the workplace was leading to a degeneration of work skills (e.g., Braverman, 1974; Noble, 1979; Zimbalist, 1979). In recent years, this second notion has been challenged. Bailey (1989) points out that new technologies have forced industries to give up a de-skilling approach. Firms that attempted to transfer all skills to machines soon realized that a skilled worker cannot easily be replaced by a machine (Levine, 1995). In the current view of work around new technologies, skill demands have shifted from mechanical competence to an abstract understanding of how computerized machines function (Adler & Borys, 1989).

A growing body of research in the ethnomethodological tradition is focusing on the way people interact with one another and with the material artifacts surrounding them in the workplace. An example of a detailed examination of work in a technologically saturated environment is a study by Goodwin (1992), who closely analyzes the interaction of employees in an airlines operations room. Goodwin shows how workers’ talk-in-action is combined with their perceptions of what is on TV monitors in such a way that what they see on the screen is co-constructed. By carrying out research at this level of detail in high-tech work settings, it becomes possible to increase our understanding of what kind of skills employees should have.

Setting and Method

The analysis presented in this report is part of a larger ethnographic study of work in a small circuit-board manufacturing plant which assembles circuit boards “to order.” One important characteristic of this company is that it is in a highly competitive market. To survive, the company must have leading-edge equipment, be able to do a fast turnaround of a job, and provide excellent quality control. A second feature of this company is the ethnolinguistic diversity of its employees. The teams generally organize themselves by ethnolinguistic background, an arrangement that is supported by the management because it perceives that these groups work well among themselves. These arrangements do not have tight boundaries, however, and individuals move across teams, when necessary, to make last minute changes requested by the customer, meet deadlines, or troubleshoot the machines. Because circuit-board technology is changing more rapidly than the machines that assemble them, workers frequently confront problems with the assembly.

Over a three-month period, workers were observed and videotaped as they performed their tasks on the manufacturing floor. These observations were supplemented with more formal and extended interviews, providing information on the company’s history and structure, the participants’ background and education, the kinds of tasks performed, and the functions of the different machines. The larger research project provided overarching contextual information for the present microanalysis.

Our microanalytical method is drawn largely from the work of conversational analysis, which provides a theoretical foundation for understanding how talk-in-interaction is organized (c.f., Goodwin & Heritage, 1990). Through the study of ordinary conversation, analysts demonstrate how human activity is coordinated and how meaning and mutual understanding are achieved. Recently, researchers in this tradition have turned to the analysis of task activities in institutional settings such as courtrooms (Atkinson & Drew, 1984), classrooms (McHoul, 1990), and doctors’ offices (Heath, 1992; see Drew & Heritage, 1992, for an excellent collection). In the present research, a microanalysis of workplace interaction was designed to throw light on the kinds of skills workers actually employ in the midst of collaborative activities. Two machine operators’ troubleshooting activities were observed. The workers’ interactions with machine parts, measuring tools, computerized data, and with one another were subjected to various levels of analysis.

Analysis of the Task Activity

The participants in the interaction were a machine operator and his supervisor, both from Vietnam, who were working under tremendous time pressure with a machine programmed on this particular day to build large prototype boards for a major computer corporation. The first board moved on a conveyor belt through the machine which comes equipped with a robotic arm. The arm was taking components from feeders and placing them at assigned locations on the circuit board. Over a six-and-a-half-minute interval, the workers confronted two problems with the assembly. First, the robotic arm was unable to pick a component from the feeder; and second, the component was larger than the place assigned to it on the board. The workers solved the first problem by adapting machine parts so that the arm would place the component correctly; and the second by recommending a change in the customer’s design plans. For each problem, they followed a procedure which can be summarized as follows: notice the problem, hypothesize the source, test the hypothesis, and look for an optimal solution.

Working with Perceptions and Representations

Fine-grained analysis of the workers’ actions on the machine showed that they applied perceptual and representational competence during the problem-solving process. This second level of analysis of the workers’ collaborative actions on the machine showed that they drew on well-honed perceptions–auditory, visual, and kinesthetic–to discover the trouble and find its source. For example, a sudden shift in the sound of the robotic arm’s rhythmic movements directed the workers’ visual attention to problems with the way the components were being fed onto the machine. Based on their auditory and visual perceptions, the workers formed a hypothesis as to the source of the problem. They confirmed their hypothesis by measuring components on the feeder. They contested one another’s suggestions for adapting a machine part and came to agree on an optimal solution. Then the measurements were checked against the numbers on the machine’s computer screen. Finally, by means of gestures, one worker displayed to his colleague his assessment of the robotic arm’s placement of components on the board. Tracing his finger across the board’s landscape in large and small loops, he showed errors in the relationships between the components already placed and those yet to be placed. This visual assessment led them to alter a series of numbers in the computer program.

Throughout the troubleshooting, the workers referred to various kinds of inscriptions such as a blueprint of the board, the customer’s bill of materials, and the computer program data; they also made their own inscriptions by measuring objects and modifying numbers in the program. Work with numerical inscriptions pervaded the activity. The workers recognized these numbers as representations of the task to be accomplished by the machine, numbers which require careful assessment by comparing them against other inscriptions, and, in particular, against their own perceptions. Contrary to widely held assumptions that workers place greater emphasis on representational knowledge–numbers given in a computer program–than in their perceptual intuitions, this study shows that their assessments moved in both directions during their conjoint problem solving. Worker perceptions and representations mutually elaborated on one another.

Discussion and Educational Implications

Although modern technology places new skill demands on workers, workers still retain many of the skills that were required in traditional work settings. Machine operators still rely on their hands, eyes, and ears when they are setting up a machine for a specific task or when troubleshooting is required. They interpret and manipulate the data in the computer program that runs the machine. They recognize these numbers as representations of the task to be accomplished by the machine and, consequently, as numbers that require careful assessment, comparing them against other inscriptions they make and, in particular, against their own perceptions. The findings of this study challenge claims that workers who use high-tech equipment act primarily as monitors who have abstract knowledge of the machinery and have little use for their perceptual skills.

Workers, moreover, detect and solve problems as problems arise. Because of the rapid changes in machine technology and products, workers have to constantly readjust to more advanced equipment and adapt the machine to the requirements of a specific job. Since they typically work under a tremendous time pressure, they carry out much of the problem-solving on the fly. Lévi-Strauss (1966) formulated the notion of bricoleur to describe a person who uses tools in creative ways, including ways that go beyond the original purposes for which the tools are designed. This research has shown that workers’ bricolage skills have not been lost with the advent of computerized technologies. They are contemporary bricoleurs, adapting even the digital tools to ever-changing circumstances.

This study also demonstrates how effective teamwork actually proceeds. Workers are able to contest one another’s suggested solutions and assemble, as it were, the knowledge that is distributed between them and across material inscriptions surrounding them, and eventually come upon optimal solutions. This trend of working in teams has broader implications about learning on the job. No single person is expected to hold all the knowledge about assembling circuit boards. Workers combine their knowledge with different coworkers, in different situations, and use different cognitive artifacts. Assembling knowledge resides, not in the machine, nor in an individual, but in the dynamics of the conjoint problem-solving situation.

Assuming that this workplace is typical of what work settings will be like in the 21st century, then work-based learning will be a major aspect of a person’s educational life. If this is the case, what is the role of educational institutions in preparing workers for their future jobs? Based on case studies of production workers and professionals, Stasz, Ramsey, Eden, Melamid, and Kaganoff (1995) identified work-related attitudes and “new” generic skill areas–problem-solving, communication, and teamwork. Schools can give learners practice in these new skills through authentic learning situations such as project-based work. Projects present learners with everyday problem-solving situations, require them to come to decisions collaboratively, and compel them to communicate and share knowledge effectively. The present study supports the practical value of such authentic learning practices. Our findings further suggest that more emphasis be placed on the integration of cognitive abilities with perceptual and manual skills into learning practices.

Finally, though employees’ ethnolinguistic diversity was not the primary focus of this research, we observed this firm’s attitudes toward its ethnolinguistically diverse workers. The management created a climate that encouraged workers to use their indigenous ways of interacting in order to assemble high-quality products. Given the continued demographic shifts in this country, we argue that such attitudes should be fostered through on-the-job training and through high-quality instruction in diversity both at school and in the workplace.

Kleifgen, J. A., & Frenz-Belken, P. (1996, June). Problem-solving at a circuit-board assembly machine: A microanalysis. Berkeley, CA: National Center for Research in Vocational Education.

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