Academic engagement: A review of the literature 2011-2019     

Markus Perkmann  Rossella Salandra  Valentina Tartari  Maureen McKelvey  Alan Hughes 《Research Policy》2021,50(1):104114

We provide a systematic review of the literature on academic engagement from 2011 onwards, which was the cut-off year of a previous review article published in Research Policy. Academic engagement refers to knowledge-related interactions of academic scientists with external organisations. It includes activities such as collaborative research with industry, contract research, consulting and informal ties. We consolidate what is known about the individual, organisational and institutional antecedents of academic engagement, and its consequences for research, commercialisation, and society at large. Our results suggest that individual characteristics associated with academic engagement include being scientifically productive, senior, male, locally trained, and commercially experienced. Academic engagement is also socially conditioned by peer effects and disciplinary characteristics. In terms of consequences, academic engagement is positively associated with academics’ subsequent scientific productivity. We propose new areas of investigation where evidence remains inconclusive, including individual life cycle effects, the role of organisational contexts and incentives, cross-national comparisons, and the impact of academic engagement on the quality of subsequent research as well as the educational, commercial and society-wide impact.  相似文献   

How the existence of special schools affects the placement of students with special needs in inclusive primary schools     

Nikola Ebenbeck  Jakob Rieser  Jana Jungjohann  Markus Gebhardt 《Journal of Research in Special Educational Needs》2022,22(3):274-287

Although inclusion is the declared goal, the transition from a system based on special schools to an inclusive school system has only been progressing very slowly in individual countries. In an evolving school system, the existing special schools keep struggling to justify their existence. This study investigates the regional distribution effects based on official school data and shows the influence of a pull effect on special schools as a distance effect of special schools affecting the placement of students. For this purpose, official school statistics including all students at special and regular schools in the years 2010, 2015 and 2020 (N = 11 280 040) are evaluated in a spatiotemporal comparison using Educational Data Mining. In a hierarchical regression model on school placement in inclusive schools, the distance between primary and special schools has the highest influence (β = 0.48) on the inclusion rate (i.e., the proportion of students with special needs who are educated in regular schools in relation to all students with disabilities), along with the size (β = −0.14) and the density of special schools in a district (β = −0.12). The effects differ according to the population density of the region and are stronger in large cities. When the proportion of students with and without SEN in regular schools is considered (support rate), the density of special schools has the greatest impact on school placement (ß = 43.44). Self-preservation of schools, traditional funding systems and regional differences between urban and rural areas are discussed as possible reasons.  相似文献   

Early Maternal Employment and Children's Vocabulary and Inductive Reasoning Ability: A Dynamic Approach          下载免费PDF全文

Michael Kühhirt  Markus Klein 《Child development》2018,89(2):e91-e106

This study investigates the relationship between early maternal employment history and children's vocabulary and inductive reasoning ability at age 5, drawing on longitudinal information on 2,200 children from the Growing Up in Scotland data. Prior research rarely addresses dynamics in maternal employment and the methodological ramifications of time‐variant confounding. The present study proposes various measures to capture duration, timing, and stability of early maternal employment and uses inverse probability of treatment weighting to control for time‐variant confounders that may partially mediate the effect of maternal employment on cognitive scores. The findings suggest only modest differences in the above ability measures between children who have been exposed to very different patterns of eary maternal employment, but with similar observed covariate history.  相似文献   

Parameter study using a finite element simulation of a carving Alpine ski to investigate the turn radius and its dependence on edging angle,load, and snow properties     

Peter Federolf  Anton Lüthi  Markus Roos  Jürg Dual 《Sports Engineering》2010,12(3):135-141

For ski manufacturers, it is important to know how a given ski-binding system performs under different loading conditions. Important performance parameters are the ski deformation and the resulting turn radius. This study focuses on carving turns. The aims of this study were: (1) to investigate the dependence of the turn radius on edging angle, load on the binding, and snow hardness using a finite element (FE) simulation, and (2) to compare the results with predictions of a frequently used model introduced by Howe. The FE simulation used a quasi-static approach (similar to Howe’s model), but the ski–snow interaction model incorporated the groove that forms in the snow during a carved turn. Up to edging angles of 40°, the results of the FE simulation agreed well with Howe’s model. However, for large edging angles (>50°) the calculated turn radius leveled out, whereas Howe’s model tends to zero. This effect was more pronounced for soft snow than for hard snow conditions. Increasing forces on the binding caused a decrease in the calculated turn radii. In summary, the FE simulation showed that particularly at large edging angles the groove in the snow needs to be considered in models of the ski–snow interaction or in computations of the turn radius.  相似文献   

Core executive functions are selectively related to different facets of motor competence in preadolescent children     

Sebastian Ludyga  Uwe Pühse  Markus Gerber  Christian Herrmann 《European Journal of Sport Science》2019,19(3):375-383

Background: Although accumulating evidence suggests that motor and cognitive development is interrelated, only a few studies have investigated links between executive function and motor control. Therefore, the present cross-sectional study examined the relationship between motor competences and core components of executive functioning, including inhibitory control, working memory and cognitive flexibility. Methods: In 89 preadolescent children, motor competences were assessed using the MOBAK-5 test battery. Additionally, all participants completed computer-based versions of the Flanker task, which included standard and switch blocks, and the 2-Back task. Results: Partial correlations (correcting for age, gender and body mass index) revealed that locomotor skills were associated with the adjusted hit-rate on the 2-Back task (r?=?0.34) whereas object control was linked with conflict score on the Flanker task (r?=??0.39). In contrast, there was no correlation between switch costs and motor competences. Conclusion: In preadolescent children, high competences in locomotor skills and object control skills are associated with high performance on specific executive function tasks. This finding supports the current view that motor competences and cognitive control share some common underlying processes.  相似文献   

Sports activity patterns and cardio-metabolic health over time among adults in Germany: Results of a nationwide 12-year follow-up study     

Lars Gabrys  Jens Baumert  Christin Heidemann  Markus Busch  Jonas David Finger 《运动与健康科学(英文)》2021,10(4):439-446

BackgroundPhysical activity is favorable for health, and vigorous sports activity is particularly beneficial. This study investigates the association between changes in sports participation patterns over time and cardio-metabolic and self-perceived health outcomes.MethodsData from 3752 adults (18–79 years of age) who participated in 2 national health interview and examination surveys in 1997–1999 and 2008–2011 were included, with a mean follow-up time of about 12 years. A change in self-reported sports activity was analyzed with respect to the incidence of type 2 diabetes, coronary heart disease (CHD), hypertension, obesity, dyslipidemia, metabolic syndrome, and poor self-perceived health. Participants with pre-existing disease or risk factor of interest at baseline were excluded from the analysis. Being sufficiently active in sports was specified as doing sports for at least 1–2 h per week, and 4 activity categories were defined: 1) inactive at both time points (inactive–inactive), 2) inactive at baseline and active at follow-up (inactive–active), 3) active at baseline and inactive at follow-up (active–inactive), and 4) active at both time points (active–active). Associations between sports activity engagement and health outcomes were estimated by logistic regression models with different stages of adjustments.ResultsNot engaging in any regular sports activity at both time points (inactive–inactive) was associated with higher rates of type 2 diabetes (odds ratio (OR) = 1.82, 95% confidence interval (95%CI): 1.08–3.08), CHD (OR = 1.82, 95%CI: 1.16–2.84), hypertension (OR = 1.36, 95%CI: 1.03–1.81), metabolic syndrome (OR = 1.58, 95%CI: 1.08–2.32), and poor self-perceived health (OR = 2.54, 95%CI: 1.83–3.53) compared to doing regular sports for a minimum of 1–2 h per week over time (active–active). In case of change from inactivity to any regular sports activity (inactive–active), the rate of risk factor occurrence was not statistically different from the active–active reference group except for poor self-perceived health, but it was higher for type 2 diabetes (OR = 2.15, 95%CI: 1.12–4.14) and CHD (OR = 1.77, 95%CI: 1.03–3.03). Being active at baseline but inactive at follow-up (active–inactive) was not associated with higher disease incidence of type 2 diabetes (OR = 0.70, 95%CI: 0.25–1.97) or CHD (OR = 1.20, 95%CI: 0.49–2.99), but was associated with higher rates of hypertension (OR = 1.61, 95%CI: 1.11–2.34), obesity (OR = 2.34, 95%CI: 1.53–3.57), metabolic syndrome (OR = 1.70, 95%CI: 1.11–2.63), and poor self-perceived health (OR = 2.16, 95%CI: 1.53–3.07) at follow-up.ConclusionEven a low weekly quantity (1–2 h) of regular sports activity is partly associated with health benefits. Being formerly but not currently active was not associated with an increased disease incidence, but was associated with a higher risk-factor development compared to the reference group (active–active). Becoming active was preventive for risk-factor development but was not preventive for disease incidence, which probably means that the health benefits from sports activity are not sustainable and disease incidence is only shifted to a later period in life. For this reason, the promotion of and commitment to regular sports activity should be addressed as early as possible over the lifespan to achieve the best health benefits.  相似文献   

Using natural language processing to support peer-feedback in the age of artificial intelligence: A cross-disciplinary framework and a research agenda     

Elisabeth Bauer  Martin Greisel  Ilia Kuznetsov  Markus Berndt  Ingo Kollar  Markus Dresel  Martin R. Fischer  Frank Fischer 《British journal of educational technology : journal of the Council for Educational Technology》2023,54(5):1222-1245

Advancements in artificial intelligence are rapidly increasing. The new-generation large language models, such as ChatGPT and GPT-4, bear the potential to transform educational approaches, such as peer-feedback. To investigate peer-feedback at the intersection of natural language processing (NLP) and educational research, this paper suggests a cross-disciplinary framework that aims to facilitate the development of NLP-based adaptive measures for supporting peer-feedback processes in digital learning environments. To conceptualize this process, we introduce a peer-feedback process model, which describes learners' activities and textual products. Further, we introduce a terminological and procedural scheme that facilitates systematically deriving measures to foster the peer-feedback process and how NLP may enhance the adaptivity of such learning support. Building on prior research on education and NLP, we apply this scheme to all learner activities of the peer-feedback process model to exemplify a range of NLP-based adaptive support measures. We also discuss the current challenges and suggest directions for future cross-disciplinary research on the effectiveness and other dimensions of NLP-based adaptive support for peer-feedback. Building on our suggested framework, future research and collaborations at the intersection of education and NLP can innovate peer-feedback in digital learning environments.

Practitioner notes

What is already known about this topic

• There is considerable research in educational science on peer-feedback processes.
• Natural language processing facilitates the analysis of students' textual data.
• There is a lack of systematic orientation regarding which NLP techniques can be applied to which data to effectively support the peer-feedback process.

What this paper adds

• A comprehensive overview model that describes the relevant activities and products in the peer-feedback process.
• A terminological and procedural scheme for designing NLP-based adaptive support measures.
• An application of this scheme to the peer-feedback process results in exemplifying the use cases of how NLP may be employed to support each learner activity during peer-feedback.

Implications for practice and/or policy

• To boost the effectiveness of their peer-feedback scenarios, instructors and instructional designers should identify relevant leverage points, corresponding support measures, adaptation targets and automation goals based on theory and empirical findings.
• Management and IT departments of higher education institutions should strive to provide digital tools based on modern NLP models and integrate them into the respective learning management systems; those tools should help in translating the automation goals requested by their instructors into prediction targets, take relevant data as input and allow for evaluating the predictions.

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