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This Research FULL PAPER extends recent scholarship on the role of technology in workplace learning in professional engineering and computing settings. Digitization of work practices has made a noticeable impact on how engineers gain expertise and solve problems they encounter at work. In this paper we use a workplace learning ecology lens to examine engineers' situated information seeking to identify practices associated with the use of online resources. Building on a previous qualitative interview study, we developed and administered a survey consisting of 16 items to assess use of online resources across learning experiences. We found high use of online resources but with variations among the use of specific resources by field, problem, and learning goal. LinkedIn, Twitter, YouTube, Wikipedia, Reddit, and technology vendor websites were the primary online platforms used by respondents for both learning and problem-solving. Respondents placed different levels of trust in online resources. Social media, especially Twitter, was trusted least across all sources. The highest trust was placed on websites of technology vendors. Findings from this work can help create better educational content as well as pedagogical interventions that use online resources for training the future workforce. 

Keeping up with new knowledge being produced in computing related domains is a difficult task given the pace of change in the field. Specifically, in domains that are undergoing a lot of innovation, such as Data Science or Artificial Intelligence, updating curricula is not easy. Yet, there is a need to be cognizant of new topics in order to create and update curricula and keep it relevant. In this paper we present an innovative approach to help educators keep a better track of changes in a domain and be able to map their curricula objectives to emerging topics and technologies. We leverage Q&A sites, Reddit and StackExchange, which provide a useful online platform for sharing of information and thereby generate a valuable corpus of knowledge. We use Data Science as a case study for our work and through a longitudinal analysis of these sites we identify popular topics and how they have changed over time. We believe innovations such as these are essential for improving computer science education and for bridging the workplace-school divide in teaching of newer topics. Our unique and innovative approach can be applied to other CS topics as well. 

Increasing digitisation of engineering and social practices has altered the relationship between formal schooling and development of expertise for professional engineering work. What does the development of expertise look like when knowledge is generated and shared at an accelerated pace due to shifts in technology? In this paper, I present case studies of two early career software engineers. Using methodological insights from digital ethnography, I trace their professional journeys over two decades. I empirically demonstrate how the development of engineering expertise is a continuous and perpetual endeavour and engineers learn throughout their lives (lifelong) and across all the different spaces they inhabit at any given time (lifewide). I argue for extending engineering work practices research and research in engineering education more broadly to take larger timescales of learning into account to build a comprehensive understanding of engineering expertise development. 

Workforce development in engineering is a high priority to keep pace with innovation and change within engineering disciplines and also within organizations. Increasingly, workforce development requires more retraining and retooling of employees than ever before as information technology has accelerated both the creation of a new body of knowledge and also the skills required to perform the work. In this paper we present a field study of a highly dynamic workplace – a cybersecurity firm – undertaken to better understand how engineers keep up with the pace of knowledge that is needed for their work. Fifteen professionals, with a wide range of experience and educational background, were interviewed. Data were analyzed iteratively and interpretively. The findings from the study suggest that over time some well-defined ways of learning had developed in the workplace we studied. These learning practices combined in-person and online interactions and resources. We also found that learning was triggered largely by the need to solve a problem or by the interests of the engineers to learn more in order to be prepared for new knowledge in the field. Depending on the problem they faced, the engineers mapped the requirements of what was needed to solve the problem, identified the resources that were available, and then selected the optimal resource. Often, as is common with problem solving, our participants had to try out multiple options. Theoretically, our study contributes by integrating an information seeking perspective with situated cognition to inform future studies of learning in information rich engineering and technology workplaces.