Entrepreneurship Assessment in Higher Education: A Research Review for Engineering Education Researchers

BackgroundDespite the wide adoption of entrepreneurship by United States engineering programs, there have been few advances in how to measure the influences of entrepreneurial education on engineering students. We believe the inadequate growth in engineering entrepreneurship assessment research is due to the limited use of research emerging from the broader entrepreneurship education assessment community.PurposeThis paper explores entrepreneurship education assessment by documenting the current state of the research and identifying the theories, variables, and research designs most commonly used by the broader community. We then examine if and how these theories and constructs are used in engineering entrepreneurship education.Scope/MethodTwo literature databases, Scopus® and Proquest, were searched systematically for entrepreneurship education assessment research literature. This search yielded 2,841 unique papers. Once inclusion and exclusion criteria were applied, 359 empirical research papers were coded for study design, theory, variables measured, instruments, and validity and reliability.ConclusionsWhile there has been growth in entrepreneurship education assessment research, little exchange of ideas across the disciplines of business, engineering, and education is occurring. Nonempirical descriptions of programs outweigh empirical research, and these empirical studies focus on affective, rather than cognitive or behavioral, outcomes. This pattern within the larger entrepreneurship community is mirrored in engineering where the use of theoryâ based, validated entrepreneurship education assessment instruments generally focuses on the context of intent to start a new company. Given the engineering community’s goals to support engineering entrepreneurship beyond business creation, the engineering education community should consider developing assessment instruments based in theory and focused on engineeringâ specific entrepreneurship outcomes.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/145556/1/jee20197.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/145556/2/jee20197_am.pd

Learning by hiring: the effects of scientists’ inbound mobility on research performance in academia

This study investigates the effects of scientists’ inbound mobility on the research performance of incumbent scientists in an academic setting. The theoretical framework integrates insights from learning theory and social comparison theory to suggest two main mechanisms behind these effects, localized learning and social comparison. The authors propose several hypotheses about the conditions that might intensify or weaken such effects. Specifically, the arrival of new scientific personnel is likely to exert stronger positive effects on the performance of incumbent scientists with shorter (cf. longer) organizational tenure; in addition, academic departments with less diversified expertise and with higher levels of internal collaborations likely reap greater benefits from learning by hiring. The empirical findings, based on a longitudinal analysis of a sample of 94 U.S. academic chemical engineering departments, provide empirical support for these contentions

Design for occupational safety and health of workers in construction in developing countries: A study of architects in Nigeria

Purpose. Design for safety (DfS) of workers is amongst the prominent ways of tackling poor occupational safety and health performance in construction. However, in developing countries there is extremely limited research on DfS. This study thus makes an important contribution to the subject of DfS in developing countries by specifically examining the awareness and practice of DfS amongst architects within the construction sector of Nigeria. Materials and methods. A survey of architects, yielding 161 valid responses, was conducted. Results. While there is high awareness of the concept of DfS, the actual practice is low. Additionally, although there is high interest in DfS training, the engagement in DfS training is low. Significantly, awareness of DfS, training and education related to DfS, and membership of a design professional body have very limited bearing on the practice of DfS by architects. Conclusions. The findings are thus symptomatic of the prevalence of influential DfS implementation barriers within the construction sector. Industry stakeholders should seek to raise the profile of DfS practice within the sector. Furthermore, similar empirical studies in the construction sector of other developing countries would be useful in shedding light on the status of DfS in these countries

Uncertainties in the Anti-neutrino Production at Nuclear Reactors

Anti-neutrino emission rates from nuclear reactors are determined from thermal power measurements and fission rate calculations. The uncertainties in these quantities for commercial power plants and their impact on the calculated interaction rates in electron anti-neutrino detectors is examined. We discuss reactor-to-reactor correlations between the leading uncertainties and their relevance to reactor anti-neutrino experiments.Comment: Submitted to Phys Rev

Perspectives in visual imaging for marine biology and ecology: from acquisition to understanding

Durden J, Schoening T, Althaus F, et al. Perspectives in Visual Imaging for Marine Biology and Ecology: From Acquisition to Understanding. In: Hughes RN, Hughes DJ, Smith IP, Dale AC, eds. Oceanography and Marine Biology: An Annual Review. 54. Boca Raton: CRC Press; 2016: 1-72

Storylines: an alternative approach to representing uncertainty in physical aspects of climate change

As climate change research becomes increasingly applied, the need for actionable information is growing rapidly. A key aspect of this requirement is the representation of uncertainties. The conventional approach to representing uncertainty in physical aspects of climate change is probabilistic, based on ensembles of climate model simulations. In the face of deep uncertainties, the known limitations of this approach are becoming increasingly apparent. An alternative is thus emerging which may be called a ‘storyline’ approach. We define a storyline as a physically self-consistent unfolding of past events, or of plausible future events or pathways. No a priori probability of the storyline is assessed; emphasis is placed instead on understanding the driving factors involved, and the plausibility of those factors. We introduce a typology of four reasons for using storylines to represent uncertainty in physical aspects of climate change: (i) improving risk awareness by framing risk in an event-oriented rather than a probabilistic manner, which corresponds more directly to how people perceive and respond to risk; (ii) strengthening decision-making by allowing one to work backward from a particular vulnerability or decision point, combining climate change information with other relevant factors to address compound risk and develop appropriate stress tests; (iii) providing a physical basis for partitioning uncertainty, thereby allowing the use of more credible regional models in a conditioned manner and (iv) exploring the boundaries of plausibility, thereby guarding against false precision and surprise. Storylines also offer a powerful way of linking physical with human aspects of climate change

Measurement of ϒ production in pp collisions at √s = 2.76 TeV

The production of ϒ(1S), ϒ(2S) and ϒ(3S) mesons decaying into the dimuon final state is studied with the LHCb detector using a data sample corresponding to an integrated luminosity of 3.3 pb−1 collected in proton–proton collisions at a centre-of-mass energy of √s = 2.76 TeV. The differential production cross-sections times dimuon branching fractions are measured as functions of the ϒ transverse momentum and rapidity, over the ranges pT < 15 GeV/c and 2.0 < y < 4.5. The total cross-sections in this kinematic region, assuming unpolarised production, are measured to be σ (pp → ϒ(1S)X) × B ϒ(1S)→μ+μ− = 1.111 ± 0.043 ± 0.044 nb, σ (pp → ϒ(2S)X) × B ϒ(2S)→μ+μ− = 0.264 ± 0.023 ± 0.011 nb, σ (pp → ϒ(3S)X) × B ϒ(3S)→μ+μ− = 0.159 ± 0.020 ± 0.007 nb, where the first uncertainty is statistical and the second systematic

A framework for evolutionary systems biology

<p>Abstract</p> <p>Background</p> <p>Many difficult problems in evolutionary genomics are related to mutations that have weak effects on fitness, as the consequences of mutations with large effects are often simple to predict. Current systems biology has accumulated much data on mutations with large effects and can predict the properties of knockout mutants in some systems. However experimental methods are too insensitive to observe small effects.</p> <p>Results</p> <p>Here I propose a novel framework that brings together evolutionary theory and current systems biology approaches in order to quantify small effects of mutations and their epistatic interactions <it>in silico</it>. Central to this approach is the definition of fitness correlates that can be computed in some current systems biology models employing the rigorous algorithms that are at the core of much work in computational systems biology. The framework exploits synergies between the realism of such models and the need to understand real systems in evolutionary theory. This framework can address many longstanding topics in evolutionary biology by defining various 'levels' of the adaptive landscape. Addressed topics include the distribution of mutational effects on fitness, as well as the nature of advantageous mutations, epistasis and robustness. Combining corresponding parameter estimates with population genetics models raises the possibility of testing evolutionary hypotheses at a new level of realism.</p> <p>Conclusion</p> <p>EvoSysBio is expected to lead to a more detailed understanding of the fundamental principles of life by combining knowledge about well-known biological systems from several disciplines. This will benefit both evolutionary theory and current systems biology. Understanding robustness by analysing distributions of mutational effects and epistasis is pivotal for drug design, cancer research, responsible genetic engineering in synthetic biology and many other practical applications.</p