Impact Cases

Developing new technologies which benefit mobility assistance dogs and people with disabilities in the UK - Banner

Developing new technologies which benefit mobility assistance dogs and people with disabilities in the UK

Dr Mancini’s and her colleagues’ pioneering research in Animal-Computer Interaction (ACI) has led to the design of novel animal-centred interactive technologies and has had a significant impact by benefitting mobility assistance dogs and the people they assist in the UK and by enhancing public understanding of Animal-Computer Interaction (ACI). Their research has given mobility assistance dog charities new tools with which to efficiently train dogs and has made the premises of public-facing businesses more accessible. Together, this work has enhanced the wellbeing of dogs and people by facilitating daily tasks and strengthening the human-dog bond.
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Empowering people to find solutions to complex challenges through Collective Intelligence - Banner

Empowering people to find solutions to complex challenges through Collective Intelligence

De Liddo’s research on the theories and methods required to harvest the Collective Intelligence (CI) of large numbers of people has developed new technologies which public sector organisations, educators, broadcasters and NGOs have used to engage people to participate in decision-making. Through these tools, De Liddo’s work has:

  • Equipped more than 800 UK Health Visitors with a tool to enhance their professional practice;
  • Enabled more than 1,300 school and university teachers in Brazil to engage in online collaborative learning;
  • Promoted citizen engagement with political election debates in the 2015, 2017 and 2019 UK General Elections;
  • Supported peace building education in Rwanda after the 1994’s genocide.

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Supporting Professional Development and Improving the Quality and Efficiency of Editorial Processes at Springer Nature - Banner

Supporting Professional Development and Improving the Quality and Efficiency of Editorial Processes at Springer Nature

Since 2016, Springer Nature, one of the world’s foremost academic publishing companies, has used a software solution developed through Motta, Osborne and Salatino’s research on scholarly knowledge mining to significantly improve the efficiency and quality of its editorial processes.

Using the researchers’ Smart Topic Miner (STM) software to automate the process of annotating conference proceedings for its Computer Science book series, Springer Nature has reduced its associated editorial costs by 75%. STM has also enabled its editorial assistants’ professional development and improved the quality of its processes, leading directly to an additional 12 million downloads of its approximately 3,200 STM-edited Computer Science books. This corresponds to a 53% positive growth differential with respect to the average growth trend for non-STM-edited Computer Science books.
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Making scientific knowledge more easily and freely discoverable through CORE.ac.uk - Banner

Making scientific knowledge more easily and freely discoverable through CORE.ac.uk

Dr Knoth’s novel research in aggregating research repositories has created the world’s largest Open Access (OA) collection of research literature and pioneered machine access to this content. His not-for-profit CORE.ac.uk is ranked among the top 1,500 websites in the world by website popularity and top 20 websites in Science and Education. It has over 40 million Monthly Active Users (MAU) and is valued at USD94,250,000.

CORE.ac.uk has played a pivotal role in the global open science movement by:

  • Widening access to and discoverability of scientific knowledge and driving change towards open science;
  • Empowering commercial and academic partners to develop novel solutions leveraging scientific literature;
  • Ensuring compliance with research funders’ open access policies.

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Using predictive learning analytics to improve student retention - Banner

Using predictive learning analytics to improve student retention

Professor Zdenek Zdrahal and Dr Martin Hlosta’s pioneering research in Predictive Learning Analytics has developed new tools which successfully improve higher education student retention, by providing an early warning when students are at risk of failing or abandoning their studies. These tools have reduced from 37% to 19% the average drop-out rate for first-year students at the Faculty of Mechanical Engineering of the Czech Technical University in Prague, thus saving 422 students from abandoning their studies and preventing the faculty from losing close to GBP1 million in government funding. Zdrahal and Hlosta’s work has also improved professional practice, student outcomes and retention rates at The Open University.
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