Sisyphus in the Digital Workplace
Today’s IT professionals must keep up with both continuous demands for new skills and new ways of learning.
By Aditya Johri
For engineering professionals, workplace learning is in a turbulent state. As the work of engineers and technologists continues to change, so does the knowledge required to perform that work. Accompanying the requirement for continuous learning is the need to adjust to new ways of learning. Most critically, the fusion of changing knowledge and ways in which that knowledge can be acquired is giving rise to new practices of learning that are novel because they are both reified and malleable; they become entrenched but are also continuously changing. More than any other aspect of workplace learning, these shifting practices make technology work challenging. Their dynamism and unpredictability mean that advance preparation is often inadequate and preparing for the future is akin to guesswork. So, how are technology professionals coping with these changes?
With one of my doctoral advisees, I just finished a field study of information security professionals working in the Washington, D.C., area. In this project, partly funded by the National Science Foundation, we wanted to understand how engineering professionals learn on the job when they work in fields where information needed to successfully complete tasks changes continuously. In information security, workers must keep abreast of all the latest changes in tools and techniques—both hardware and software related—to stay ahead of those who are trying to take advantage of vulnerabilities in systems.
Most of the professionals we interviewed or surveyed had between five and 15 years of work experience. Notably, even those who had started just five years ago reported that they had received little or no training in their degree programs on the primary technologies and techniques that made up the bulk of their work. The biggest shifts they had encountered were a move toward cloud computing and the use of data analytics across various functions within their firms.
Study participants told us that in the work context, learning was motivated largely by the need to solve a problem that they faced on the job or by their aspiration to be prepared for technologies that were being introduced or were likely to become common. For problem-solving, professionals reported that they often relied first on coworkers or people in their network, depending on the sensitivity of the information, but they also used online resources such as websites of vendors who made a specific technology and online communities such as StackExchange or Reddit. YouTube was also a popular resource, especially for problems that had a linear, step-by-step solution.
When it came to learning for the future, things were a little complicated. The rapid pace of work made it hard to keep up, and their jobs afforded little time for exploration. Our respondents reported that they used online resources, especially social media such as LinkedIn and Twitter, blogs by experts in the field, and also online communities such as StackExchange to be “in the know.” Workers developed these approaches ad hoc, and often they were not shared within the organization or team beyond their close networks. Overall, we found that the ability both to exploit existing knowledge and networks and to explore new knowledge was necessary for professionals to succeed in a fast-changing work environment.
These findings have two major implications for the preparation of the future technology workforce in higher education. Since most courses and curricula are focused on training students to be good at exploiting knowledge, there is little encouragement for students to explore new information. Even in the case of projects and assignments that are more open-ended and research-driven, there is little explicit guidance on how to approach information seeking and skills that should be developed to maintain these practices over time. The findings also alert us to our own need, as educators, to make better use of technology and new techniques in the area of data mining and machine learning to be able to explore relevant information online and incorporate it in our teaching. There is also a need to develop better interfaces and platforms for learning that are focused on both exploitation and exploration to support student success.
Aditya Johri is a professor of information sciences and technology at George Mason University.