Career Changers in Teaching Jobs: A Case Study Based on the Swiss Vocational Education System

This study investigates the determinants and motives of professionals who change career to vocational teaching. The framework for this study is the Swiss vocational education system, which requires that teachers of vocational subjects must have a prior career in that specific field. Thus, to work in teaching, every vocational teacher has to change his or her initial career. This paper focuses on the relevance of monetary motives for changing a career to teaching. Using a unique data set of trainee teachers, we show that professionals who change their careers to teaching earned on average more in their first career than comparable workers in the same occupation. Our findings additionally demonstrate that the average career changer still expects to earn significantly more as a teacher than in the former career. However, the study shows substantial heterogeneity and a zero wage elasticity of the teacher supply, suggesting that non-monetary motives are more relevant for career change than monetary factors.career change, occupational change, rate of return to education, wage differentials, teacher wages, vocational education and training

Educational strategies in data journalism: A comparative study of six European countries

The article explores training programs in higher education with regard to data journalism from a multi-national perspective. By carrying out a comparative analysis in six European countries (Germany, Switzerland, the Netherlands, Italy, Poland, and the United Kingdom), it covers different models of media systems and journalistic cultures envisaged by Hallin and Mancini. Based on a desk review and in-depth interviews with instructors of data journalism in each country, the article identifies different approaches to the way data journalism is taught. In Europe, such programs are offered by four types of organizations: academic, vocational, professional, and civic. The role played by those organizations can be explained as a result of the peculiarities of national media systems. But there are also commonalities, for example, non-academic institutions (such as the European Journalism Center or the Center for Investigative Journalism) and major international news outlets (such as The Guardian and The New York Times) seem to take over a leading role in all of the analyzed countries. Generally speaking, data journalism education appears to be a very young discipline that frequently neglects fundamental journalistic topics such as ethical issues, transparency, accountability, and responsiveness although they are crucial in a journalistic field as sophisticated tools to reveal hidden aspects of reality

Opening Schools to Students' Informal Digital Knowledge to Enable the Emancipatory Employment of Digital Media

While classes become more heterogeneous and children grow up as digital natives, instruction is still characterized by an emphasis on middle-class children and analogue media. Moreover, national and international comparative studies have repeatedly shown that Germany in OECD comparisons often ranks last in terms of the level of digital learning opportunities in schools. A gap exists between children's lifeworld experiences and informal learning processes in a digital world on the one hand and digital learning opportunities at school on the other. Thus, schools do not offer content and digital infrastructure that links to students' informal digital knowledge. Therefore, there is a need to discuss how schools can integrate the emancipatory power of digitalization

Prediction Markets: A Systematic Review and Meta-Analysis

Prediction markets (PM) have drawn considerable attention in recent years as a tool for forecasting events. Studies surveying and examining relevant the trends of PM using traditional approaches have been reported in the literature. However, research using meta-analysis to review Prediction markets systems is very limited in Management Information System (MIS). This paper aimed to fill this gap by using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method to study Prediction markets trends over the past decades. Our results are as follows. First, we find that shows that more than 64% of academic studies on Prediction markets are published in top journals such as Journal of the Association for Information Systems, Journal of Consumer Research and Information Systems Research. Second, we showed that Prediction markets applications can be can be divided into two groups: internal use PMS and general public usage. Finally, our significant meta-analysis result show that on average prediction markets is 79% more accurate than alternative forecast methods based

The Effects of the Quantification of Faculty Productivity: Perspectives from the Design Science Research Community

In recent years, efforts to assess faculty research productivity have focused more on the measurable quantification of academic outcomes. For benchmarking academic performance, researchers have developed different ranking and rating lists that define so-called high-quality research. While many scholars in IS consider lists such as the Senior Scholar’s basket (SSB) to provide good guidance, others who belong to less-mainstream groups in the IS discipline could perceive these lists as constraining. Thus, we analyzed the perceived impact of the SSB on information systems (IS) academics working in design science research (DSR) and, in particular, how it has affected their research behavior. We found the DSR community felt a strong normative influence from the SSB. We conducted a content analysis of the SSB and found evidence that some of its journals have come to accept DSR more. We note the emergence of papers in the SSB that outline the role of theory in DSR and describe DSR methodologies, which indicates that the DSR community has rallied to describe what to expect from a DSR manuscript to the broader IS community and to guide the DSR community on how to organize papers for publication in the SSB

Innovation and skill dynamics: a life - cycle approach

This paper focuses on the complementary institutional and organizational adjustments that facilitate the routinization of technological opportunities. To address this issue we propose a life-cycle approach that accounts for the emergence, development and transformation of the conduits for the transmission of new knowledge and skills. While it is widely held that knowledge tends to get more organized as by-product of innovation, the purposeful absorption of practical know-how into formal education is another crucial, and arguably less analysed, intermediate step to bridge the beginning of the life-cycle, when new skills are closely tied to some novel technology, to later phases when the emergence of new disciplines and the diffusion of those skills elicit complementary developments in the technology. The paper connects themes that are central to the tangled policy discourse on skills impact innovation, namely: the institutional adjustments required to favour the re-absorption of skill mismatches; the systematization of knowledge underpinning the creation of new academic disciplines; and implications for dynamics of productivity and of the wage structure.

Essays on the Economics of Education

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Economics, 2016.Cataloged from PDF version of thesis.Includes bibliographical references (pages 109-115).This dissertation combines three essays on the economics of education. The essays share a common focus on comparing experimental and non-experimental econometric methods. I present findings from randomized evaluations of two prominent education interventions for low-income students. In the spirit of LaLonde's (1986) pioneering re-analysis of experimental evidence on federal job training programs, I leverage the experimental data to assess nonexperimental methods for evaluating program impacts. The first chapter - written jointly with Joshua Angrist, David Autor, and Amanda Pallais - reports early results from a randomized evaluation of the Susan Thompson Buffett Foundation (STBF) scholarship, a large, privately-funded financial aid program for applicants to Nebraska's public colleges. Randomly-assigned scholarship offers boosted average grants received by $6,300 per year and dramatically improved enrollment and retention, especially for groups with historically-low persistence rates. Four years after award receipt, nonwhite students and first-generation college goers were nearly 20 percentage points more likely to be enrolled in college. Awards generated similarly large gains for students with the weakest high school GPAs in the eligible applicant pool. Over time, scholarships shifted many students from two- to four-year colleges, reducing associate's degree completion in the process. The economic returns to scholarship support will therefore likely hinge on whether award winners convert their extended enrollment into bachelor's degrees. The oldest study cohort will record its four-year graduation rate in the summer of 2016, but many students will likely take five or more years to finish. A complete picture of award impacts on degree receipt may therefore still be several years away. In the second chapter, I assess how selection bias distorts non-experimental estimates of STBF scholarship impacts. I show that observed gaps in retention rates between scholarship winners and rejected applicants overstate the causal effect of scholarships on dropout by nearly double. Controlling for high school GPA and Expected Family Contribution (EFC) - two widely-used criteria for awarding merit aid - explains roughly half the gap between the experimental benchmarks and observed enrollment rates. Conditional on GPA and EFC, however, additional demographic traits like race, gender, and parental education have little explanatory power. Thus, scholarship winners are positively selected on potential enrollment in the absence of treatment, and a variety of observational estimation strategies overstate the causal impacts of scholarships on enrollment and retention. Among the replication strategies, Kline's (2011) Oaxaca-Blinder procedure outperforms both discrete covariate matching and propensity score weighting on bias and precision. Because STBF award effects are larger for students who are less likely to win scholarships, linear regression estimates are even bigger than the biased estimates of treatment on treated (TOT) effects. In the final chapter, I use experimental estimates of Teach for America's (TFA) impacts on student achievement to validate a non-experimental strategy for measuring the long-run effects of hiring TFA teachers. Randomized evaluations show that TFA teachers outperform colleagues in boosting achievement at hard-to-staff schools. Despite this cross-sectional evidence, TFA's long-run effects remain unknown, a key concern for policymakers. High turnover among TFA recruits - who commit to serve for just two years - may undercut the long-run returns to hiring non-TFA teachers, who improve steeply with experience. To assess this potential tradeoff, I measure the short- and long-run effects of TFA hiring in North Carolina, where schools have employed TFA teachers since the program's founding in 1990. I identify TFA hiring effects by exploiting quasi-random variation in teacher hiring shocks across grades within schools. In the short run, TFA rookies increase math scores markedly relative to the non-TFA teachers schools might otherwise hire; TFA's initial advantage in reading is modest. When schools replace exiting TFA teachers with new TFA recruits, these gains more than offset the costs of lost experience, increasing long-run achievement. On the other hand, when TFA supply fluctuates, schools may have to replace exiting TFA teachers with inexperienced and lower-performing non-TFA hires. On net, short run achievement gains from one-shot TFA hiring still exceed the costs. JEL Classification: C93, I22, J63.by Sally Lindquist Hudson.joint work with Joshua Angrist, David Autor, and Amanda Pallais -- Early results from a randomized evaluation of post-secondary aid / Selection bias in observational estimates of financial aid impacts -- The dynamic effects of teach for America in hard-to-staff schools.Ph. D

Editorial: Technology teachers and their professional competence - peculiarities and starting points for subject-specific didactical research

It goes without saying that teacher competence is an influential factor in pupil education and learning. The importance of professional competence in teachers has increased and become more generally recognised in recent years (cf. for example Baumert et al. 2010; Kunter et al. 2013). Professional knowledge, i.e. subject-specific, didactic, pedagogic and psychological knowledge, is a core area of every teacher’s professional competence. Several studies have shown that the professional knowledge of teachers plays a critical role in the quality of their instruction and the learning success of their pupils (Lipowsky et al. 2009; Voss, Kunter & Baumert 2011; Voss et al. 2014; Wagner et al. 2016). Despite existing research deficits, the current standing of international research leaves no doubt as to the importance of the teacher's professional competence for the learner's development (e.g. Zlatkin-Troitschanskaia et al. 2009; Terhart, Bennewitz & Rothland 2014; KMK 2014). This competence is therefore also significant in economic terms.While a substantial body of knowledge exists as to the professional competence of teachers of various school subjects such as mathematics and physics (cf. for example Tatto et al. 2012; Riese et al. 2015), research findings on teachers of technology and interdisciplinary subjects such as natural sciences and technology (NST) are still comparatively few and far between. After outlining the theoretical background, this editorial article will discuss selected peculiarities and possible approaches to research into the professional competence of technology and NST teachers at comprehensive schools, focusing primarily on upper secondary level