scholarly journals Motives for Obtaining a Doctorate and Perceived Meaningfulness of Doctorates: A Comparison between Medicine and Life Sciences

2020 ◽  
Author(s):  
Nurith Epstein ◽  
Johanna Huber ◽  
Kathrin Redies ◽  
Sonja Heuser ◽  
Daniel Lachmann
Keyword(s):  
Additional Data ◽  
Life Sciences ◽  
Academic Research ◽  
Research Career ◽  
Career Interest ◽  
Doctoral Graduates ◽  
Medical Graduates ◽  
Effective Interventions ◽  
Using Data ◽  
Career Motives

Abstract Background: In Germany, more than half of the students complete a doctorate in the life sciences and medicine. Thus the doctorate, which is supposed to pave the way for a research career, also seems to perform other functions. In medicine, there is a cliché that students earn doctorates for reasons of prestige but in the life sciences, there is an assumption that you will not succeed on the labor market without a doctorate. To date, we know little about the actual motives for earning a doctorate and its perceived meaningfulness after graduation. Methods: Motives for obtaining a doctorate from both subject groups were analyzed using data from the E-Prom study (N = 1518). For medicine, additional data from the Bavarian Graduate Study MediBAS (N = 570) were analyzed. Qualitative interview data from the E-Prom study (N = 28) were used to better understand the motives for obtaining a doctorate in their substance and to compare them with the retrospectively perceived meaningfulness. Results: In medicine, the motives of “customariness” and feared “career disadvantages” predominate. Approximately half of the medical doctoral graduates had little or no interest to do research during or after the doctorate. In the life sciences, customariness and feared career disadvantages are important motives, too. However, research (career) interest also receives high and significantly higher approval than in medicine. Moreover, female medical graduates express significantly lower research and career motives; the latter also applies to the life sciences. The qualitative analyzes indicate a close connection between career paths and justifications of meaningfulness of the doctorate in the life sciences. In medicine, justifications of meaningfulness are closely related to initial motives for obtaining a doctorate. Hence, people who only pursued a doctorate to bear a title accordingly justified their doctorate’s meaningfulness merely with its acquisition. Conclusion: Our results stress the need for greater promotion of (academic) research careers among medical students, as well as the promotion of female careers in and outside of academic research. Further investigations are necessary to understand the exact mechanisms behind our results and to develop effective interventions.

Using Learning Analytics to Improve Engagement, Learning, and Design of Massive Open Online Courses

2019 ◽  
pp. 76-107
Author(s):  
David Santandreu Calonge ◽  
Karina M. Riggs ◽  
Mariam Aman Shah ◽  
Tim A. Cavanagh
Keyword(s):  
Student Performance ◽  
Curriculum Design ◽  
Learning Analytics ◽  
Online Courses ◽  
Academic Research ◽  
Massive Open Online Courses ◽  
Massive Open Online ◽  
Design Decisions ◽  
Effective Interventions ◽  
Using Data

Academic research in the past decade has indicated that using data and analyzing learning in curriculum design decisions can lead to improved student performance and student success. As learning in many instances has evolved into the flexible format online, anywhere at any time, learning analytics could potentially provide impactful insights into student engagement in massive open online courses (MOOCs). These may contribute to early identification of “at risk” participants and provide MOOC facilitators, educators, and learning designers with insights on how to provide effective interventions to ensure participants meet the course learning outcomes and encourage retention and completion of a MOOC. This chapter uses the essential human biology MOOC within the Australian AdelaideX initiative to implement learning analytics to investigate and compare demographics of participants, patterns of navigation including participation and engagement for passers and non-passers in two iterations of the MOOC, one instructor-led, and second self-paced.

scholarly journals Gender Inequity during the Ph.D.: Females in the Life Sciences Benefit Less from Their Integration into the Scientific Community

2018 ◽  
Vol 7 (8) ◽  
pp. 140 ◽  
Author(s):  
Nurith Epstein ◽  
Daniel Lachmann
Keyword(s):  
Scientific Community ◽  
Academic Career ◽  
Life Sciences ◽  
Academic Research ◽  
Lead Author ◽  
Publication Productivity ◽  
Research Career ◽  
Gender Inequity ◽  
Current Article ◽  
Career Survey

Female researchers remain underrepresented in higher academic ranks, even within female-dominated fields, such as the life sciences. The phenomenon is often attributed to women’s lower publication productivity. The current article explores gender differences with respect to integration into the scientific community, pursued tasks during the Ph.D. (e.g., teaching and research), and publication productivity in the life sciences. Moreover, it explores how these variables relate to the intention of pursuing an academic research career. Survey data with recent Ph.D. graduates from the life sciences in Germany (N = 736) were analyzed through descriptive and multivariate analysis. Females had fewer publications as lead author (1.4 vs. 1.9, p = 0.05). There were no differences in pursued tasks, perceived integration into the scientific community, and co-authorship. However, Ph.D. characteristics affected females and males differently. Only male Ph.D. graduates benefited from being integrated into their scientific community by an increase in lead author publications. In contrast to male Ph.D. graduates, women’s academic career intentions were significantly affected by their integration into the scientific community and co-authorship. Results suggest that women may benefit less from their integration into the scientific community and may ascribe more importance to networks for their career progress.

Cooperation and Competition

2017 ◽  
Author(s):  
Ken Peach
Keyword(s):  
Graduate Students ◽  
Particle Physics ◽  
Life Sciences ◽  
Academic Research ◽  
Research Groups ◽  
Experimental Science ◽  
Multidisciplinary Research ◽  
Common Goal ◽  
Physical Sciences ◽  
Research Sector

This chapter discusses the need for cooperation (or collaboration) to be balanced with competition, including between research groups, within a university or laboratory and between the academic research sector and industry. Healthy competition is a great motivator but unhealthy competition can be disastrous. While it is still possible for an individual scientist working alone or with a couple of graduate students or postdocs to make ground-breaking discoveries, today much experimental science requires large teams working collaboratively on a common goal or set of goals. While this trend is most evident in particle physics and astronomy, it is also present in the other physical sciences and the life sciences. Collaboration brings together more resources–physical, financial and intellectual–to address major challenges that would otherwise be beyond the scope of any individual or group. Multidisciplinary research and interdisciplinary research are examples of cooperation between different disciplines.

Research during psychiatric training as a predictor of future academic research career: the Maudsley experience

1991 ◽  
Vol 6 (3) ◽  
pp. 115-118 ◽  
Author(s):  
DJ Castle ◽  
S Refault ◽  
RM Murray
Keyword(s):  
Academic Psychiatry ◽  
Career Paths ◽  
Academic Research ◽  
Psychiatric Training ◽  
Junior Doctors ◽  
Research Career ◽  
Future Career

SummaryJunior doctors who trained in psychiatry at the Maudsley Hospital between 1965 to 1975 were followed up at a mean of 17 years to ascertain whether pre-psychiatric experience or performance during training could predict future career paths. The most consistent predictor of a career in academic psychiatry was involvement in research during training.

scholarly journals Closing the research-implementation gap using data science tools: a case study with pollinators of British Columbia

2020 ◽  
Author(s):  
Laura Melissa Guzman ◽  
Tyler Kelly ◽  
Lora Morandin ◽  
Leithen M’Gonigle ◽  
Elizabeth Elle
Keyword(s):  
British Columbia ◽  
Data Science ◽  
Academic Research ◽  
Science Methods ◽  
Research Implementation ◽  
Conservation Practice ◽  
Implementation Gap ◽  
Web App ◽  
Using Data

AbstractA challenge in conservation is the gap between knowledge generated by researchers and the information being used to inform conservation practice. This gap, widely known as the research-implementation gap, can limit the effectiveness of conservation practice. One way to address this is to design conservation tools that are easy for practitioners to use. Here, we implement data science methods to develop a tool to aid in conservation of pollinators in British Columbia. Specifically, in collaboration with Pollinator Partnership Canada, we jointly develop an interactive web app, the goal of which is two-fold: (i) to allow end users to easily find and interact with the data collected by researchers on pollinators in British Columbia (prior to development of this app, data were buried in supplements from individual research publications) and (ii) employ up to date statistical tools in order to analyse phenological coverage of a set of plants. Previously, these tools required high programming competency in order to access. Our app provides an example of one way that we can make the products of academic research more accessible to conservation practitioners. We also provide the source code to allow other developers to develop similar apps suitable for their data.

Knowledge Co production and Behavioural Change, Collaborative approaches for promoting low carbon mobility

2016 ◽  
Author(s):  
Stewart Barr ◽  
Gareth Shaw
Keyword(s):  
Climate Change ◽  
Behavioural Change ◽  
Academic Research ◽  
Low Carbon ◽  
Policy Makers ◽  
Productive Process ◽  
Emergent Literature ◽  
Using Data ◽  
The Uk ◽  
Personal Travel

Behavioural change has become regarded as a key tool for policy makers to promote behavioural change that can reduce carbon emissions from personal travel. Yet academic research has suggested that promoting low carbon travel behaviours, in particular those associated with leisure and tourism practices, is particularly challenging because of the highly valued and conspicuous nature of the consumption involved. Accordingly, traditional top-down approaches to developing behavioural change campaigns have largely been ineffectual in this field and this chapter explores innovative ways to understand and develop behavioural change campaigns that are driven from the bottom upwards. In doing so, we draw on emergent literature from management studies and social marketing to explore how ideas of service dominant logic can be used to engage consumers in developing each stage of a behavioural change campaign. Using data and insights from research conducted in the south-east of the UK, we outline and evaluate the process for co-producing knowledge about low carbon travel and climate change. We illustrate how behavioural change campaign creation can be an engaging, lively and productive process of knowledge and experience sharing. The chapter ends by considering the role that co-production and co-creation can have in developing strategies for low carbon mobility and, more broadly, the ways in which publics understand and react to anthropogenic climate change.

Examining the Implications of Process and Choice for Strategic Decision Making Effectiveness

2013 ◽  
pp. 344-359
Author(s):  
Paul L. Drnevich ◽  
Thomas H. Brush ◽  
Alok Chaturvedi
Keyword(s):  
Decision Making ◽  
Academic Research ◽  
Decision Processes ◽  
Strategic Decision ◽  
Strategic Decision Making ◽  
Political Decision ◽  
Agent Based ◽  
Response Choice ◽  
Decision Making Processes ◽  
Using Data

Most strategic decision-making (SDM) approaches advocate the importance of decision-making processes and response choices for obtaining effective outcomes. Modern decision-making support system (DMSS) technology is often also needed for complex SDM, with recent research calling for more integrative DMSS approaches. However, scholars tend to take disintegrated approaches and disagree on whether rational or political decision-making processes result in more effective decision outcomes. In this study, the authors examine these issues by first exploring some of the competing theoretical arguments for the process-choice-effectiveness relationship, and then test these relationships empirically using data from a crisis response training exercise using an intelligent agent-based DMSS. In contrast to prior research, findings indicate that rational decision processes are not effective in crisis contexts, and that political decision processes may negatively influence both response choice and decision effectiveness. These results offer empirical evidence to confirm prior unsupported arguments that response choice is an important mediating factor between the decision-making process and its effectiveness. The authors conclude with a discussion of the implications of these findings and the application of agent-based simulation DMSS technologies for academic research and practice.

Efficiency Assessment of University-Industry Collaboration

2021 ◽  
pp. 155-175
Author(s):  
Ebru Yüksel Haliloğlu
Keyword(s):  
Industrial Development ◽  
Academic Research ◽  
Data Envelopment ◽  
Academic Knowledge ◽  
Technological Advances ◽  
Industry Collaboration ◽  
Close Cooperation ◽  
Using Data ◽  
New Applications ◽  
University Industry

Today, in addition to teaching and research roles, universities are one of major drivers of economic development and technological progress in society. To propagate technological innovation and industrial development, to implement output of academic research in practice universities should be in close cooperation with industry. University-industry collaborations have various benefits both for universities and industry. Universities gain additional funds for academic research, apply academic knowledge to industry; industry benefits from skilled human resources, new applications, and technological advances. Since university-industry collaborations have great mutual benefits for all partners, it is important to administer these operations effectively. Therefore, it is central to develop some efficiency indicators and efficiency measurement methods so that productive projects can be selected and funded more. This study aims to outline a framework on determinants of university-industry collaboration efficiency and construct a benchmark model to evaluate it using data envelopment analysis.

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