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This paper details the results of a study that aims to reimagine the professional development offered to Irish secondary school mathematics teachers. This reimagined design will be based on four perspectives, one of which is that of current mathematics teachers in the Irish context. It is this perspective that is the subject of this paper. Through a series of semi-structured interviews and a follow-up national survey, teachers expressed their opinions on what professional development should and shouldn’t entail. These opinions can be grouped into the following themes: the role of the internet in professional development; the provision and sharing of teaching and learning resources; having opportunities to discuss teaching approaches and pedagogy styles with colleagues; engagement with and access to professional development; professional development activities; the facilitator; and the role of professional conversations in teachers’ continued professional development.

This study examines how technology implementation within workplaces impacts job ending among employees. We advance the literature on the labor market consequences of new technologies by focusing on their impact within workplaces where they are implemented, rather than inferring from aggregate labor structural changes. We also address how the impact of technology differs depending on workers education, organizational tenure and age. Using large-scale Dutch matched employer-employee panel data directly measuring technology implementation, we find that technology implementation is associated with an overall decrease in the probability of job ending. In line with the skill biased technological change hypothesis, higher educational attainment is associated with lower probabilities of job ending. Furthermore, we find older workers (around 50+) and workers with longer organizational tenure (around 12+ years) to have a higher probability of job ending when technology is implemented. Finally, we do not find the effects of technology implementation to differ depending on the union density of the industry in which an enterprise operates.

Studying firm-level adjustments is important for understanding the economic effects of workplace automation. So far, emerging firm-level evidence is focused on robotics and the manufacturing sector. In this paper, we document that the adoption of automation technologies extends beyond manufacturing firms. We identify firm-level automation events and show that automating firms experience faster employment and revenue growth than do nonautomating firms. However, around automation events themselves, employment growth slows markedly. Notably, we find that these effects are similar for manufacturing and nonmanufacturing firms, suggesting that an increasing diffusion of automation technology has important consequences for firms and their workers.

This paper uses historical labour market data for Belgium for the period 1846–2011 to illustrate how the employment impacts of the ongoing Digital Revolution after 1980 compare to those of the Second Industrial Revolution before 1980. Our analyses show that the period 1846–1947 was characterized by economy-wide skill-upgrading due to an increase in the demand for skilled relative to unskilled workers because of skill-biased technological change (SBTC). The period 1947–81 is characterized by particularly high labour market turbulence, in part due to a gradual switch from economy-wide skill-upgrading to job polarization. Consequently, the impact of the ongoing Digital Revolution on labour markets after 1980 is not uniquely characterized by exceptionally high labour market turbulence but by the nature of changes in the composition of jobs, namely a process of job polarization. To explain job polarization, the paper discusses the hypothesis of Routine-Biased Technological Change (RBTC) that has recently emerged in the academic literature.

We show that tightness in markets for jobs for which an unemployed job seeker fully qualifies in terms of her task competencies is predictive of her unemployment duration. This suggests that the labour market is organized along jobs and their task content. We also find that unemployed job seekers do not compete in markets where they possess only part of the required task competencies, suggesting that task overlap across jobs is unimportant for worker mobility between job markets. This implies that adverse task-biased shocks are likely to have pronounced distributional consequences across workers with different task competencies. To illustrate this, we quantify the impact of technological progress that automates routine tasks, showing that this imposes substantial adjustment costs that are highly unevenly distributed across unemployed job seekers with routine versus non-routine task competencies.