A new survey of university faculty finds that the idea of altmetrics – using something aside from journal citations as the measure of scholarly impact – has made less headway among faculty than might be expected given the hoopla surrounding altmetrics. These new measures are the most familiar in the social science community (barely) and least familiar in the arts and humanities (dramatically so).
Academics are required to not only find effective ways to communicate their research, but also to increasingly measure and quantify its quality, impact and reach. In Scholarly Communication: What Everyone Needs to Know, Rick Anderson puts us in the picture. And in Measuring Research: What Everyone Needs to Know, Cassidy Sugimoto and Vincent Lariviere critically assess over 20 tools currently available for evaluating the quality of research.
To end his trilogy of articles on the research metric system (and Google Scholar in particular), Louis Coiffait explores what improvements could be made.
The active use of metrics in everyday research activities suggests academics have accepted them as standards of evaluation. Yet when asked, many academics profess concern about the limitations of evaluative metrics and the extent of their use. Why is there such a discrepancy between principle and practices?
In Metric Power, David Beer examines the intensifying role that metrics play in our everyday lives, from healthcare provision to our interactions with friends and family, within the context of the so-termed data revolution. This is a book that illustrates our growing implication in, and arguable acquiescence to, an increasingly quantified world, but, Thomas Christie Williams asks, where do we locate resistance?
A culture of bad science can evolve as a result of institutional incentives that prioritize simple quantitative metrics as measures of success, argues Paul Smaldino. But, he adds, not all is lost as new initiatives such as open data and replication are making a positive difference.
As governments seek practical metrics for determining if their research funding is money wisely spent, the quest for ‘impact’ takes on great importance. Drawing from the Australian experience, Stephen Taylor addresses several key measurement principles.
Sociologist Eric Giannella argues the uncertainty of science makes intuition and judgement essential, and yet the effect of metrics is to reduce the role of judgment.
Drawing on discussions with academics who have oriented their work around public engagement and social impact, Daniel Pearson suggests these academics present an opportunity to rethink the existing structures of reward and recognition in higher education. “We are, as a species, addicted to story,” says English professor Jonathan Gottschall in his book, The Storytelling Animal. “Even when the […] Tom Burns, whose combination of play — and plays – with teaching in higher education added a light, collaborative and engaging model […] A 2024 report by the National Academies explores the latest advances in artificial intelligence (AI) technology and their potential effects on economic productivity, job stability, and income inequality. It also highlights key research opportunities and data needs to help workers and policymakers adapt to the evolving AI landscape. In this post, co-authors Frank T. Piller, Tucker J. Marion, and Mahdi Srour reflect on the inspiration behind their research article, “Generative […] During the final stages of editing the proofs for Artificial Intelligence and Work: Transforming Work, Organizations, and Society in an Age of Insecurity, […]
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Impact
Young Scholars Can’t Take the Field in Game of Academic Metrics
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Canada’s Storytellers Challenge Seeks Compelling Narratives About Student Research
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Tom Burns, 1959-2024: A Pioneer in Learning Development
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Innovation
NAS Report Examines Nexus of AI and Workplace
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When Do You Need to Trust a GenAI’s Input to Your Innovation Process?
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The Authors of ‘Artificial Intelligence and Work’ on Future Risk
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