New Approach to Research Evaluation: Evaluative Inquiry
Academic evaluation regimes set up to quantify the quality of research, individual scholars, and institutions have been widely criticized for the detrimental effects they have on academic environments and on knowledge production itself. Max Fochler and Sarah de Rijcke recently called for a more exploratory, less standardized way of doing research evaluation, with the introduction of the concept of the evaluative inquiry.
The Public May Not Understand Logarithmic Graphs Used to Depict COVID-19
Mass media routinely portray information about COVID-19 deaths on logarithmic graphs. But do their readers understand them?
Science is Shifting Toward Collaboration. So Why Don't We Teach More Collaboration?
The way that science is done is changing. More and more, research is conducted in collaborative teams, pulling together scientists from a variety of areas of experience and geographic locations. This is particularly true in environmental sciences, where the types of complex, multifaceted issues faced by society can only be addressed by bringing together researchers with multiple perspectives. Across a wide range of fields, there is evidence that multi-authored research is more highly cited, suggesting that this shift in the culture of science is producing novel and exciting results...
Passion about Research Process (not output!)
My hand trembled with nervousness and anticipation. It was the start of my student research project. My supervisor had talked me through how “by doing X we will learn more about Y” and I was excited to get started.A decade later when I talk to my own students I sometimes catch myself using another way to frame our work: “if we do X, and it ‘works’, then perhaps we can get into prestigious journal Y”. This is poison for an inquiring mind...
Want to Generate Impact? Get Creative.
... For researchers, this matters more than one thinks because funders are increasingly looking for a real return on their research dollars, euros and pounds. For example, the Ford Foundation, the second largest in the US, expects grantees to “achieve the greatest possible impact”; EU Horizon 2020 Proof of Concept grant applicants must outline the economic and/or societal impact expected from the project; and the UK’s REF, in assessing applications, gives a 25 percent weighting to the ‘reach and significance’ of impact. But what is impact and how can you generate it?
What is The Relationship Between Research and Policy?
Christina Boswell and Katherine Smith set out four different approaches to theorizing the relationship between knowledge and policy and consider what each of these suggests about approaches to incentivising and measuring research impact.
How University Policy Research can Become More Responsive
How might universities develop a research agenda that is responsive to the needs of policymakers? After running a series of workshops on public policy innovation with policy practitioners from various levels of government in Australia, Tamas Wells and Emma Blomkamp identified three ways in which policy research might become more “user-centred”.
The Best Tools for Using Twitter as a Data Source
Although platforms such as Facebook and WhatsApp have more active users, Twitter’s unique infrastructure and the near-total availability of its data have ensured its popularity among researchers remains high. In this post from the LSE Impact of Social Sciences blog, Wasim Ahmed offers his rundown of the tools available to social scientists looking to analyse social media data.
Crowdsourcing Raises Host of Methodological and Ethical Questions
Crowdsourcing offers researchers ready access to large numbers of participants, while enabling the processing of huge, unique datasets. However, the power of crowdsourcing raises several issues, including whether or not what initially emerged as a business practice can be transformed into a sound research method. Isabell Stamm and Lina Eklund argue that the complexities of managing large numbers of people mean crowdsourcing reduces participants to one faceless crowd. Applied to research, this is inherently problematic as it contradicts the basic idea that we control who participates in our studies. This not only challenges scientific rules of representativeness but also leaves methodological designs vulnerable to researchers’ implicit assumptions about the crowd.