1,493 research outputs found

    Crowdsourcing the Perception of Machine Teaching

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    Teachable interfaces can empower end-users to attune machine learning systems to their idiosyncratic characteristics and environment by explicitly providing pertinent training examples. While facilitating control, their effectiveness can be hindered by the lack of expertise or misconceptions. We investigate how users may conceptualize, experience, and reflect on their engagement in machine teaching by deploying a mobile teachable testbed in Amazon Mechanical Turk. Using a performance-based payment scheme, Mechanical Turkers (N = 100) are called to train, test, and re-train a robust recognition model in real-time with a few snapshots taken in their environment. We find that participants incorporate diversity in their examples drawing from parallels to how humans recognize objects independent of size, viewpoint, location, and illumination. Many of their misconceptions relate to consistency and model capabilities for reasoning. With limited variation and edge cases in testing, the majority of them do not change strategies on a second training attempt.Comment: 10 pages, 8 figures, 5 tables, CHI2020 conferenc

    The Future of Information Sciences : INFuture2013 : Information Governance

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    21st Century Englishes Conference 2018 Program

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    Program from the 6th Annual 21st Century Englishes Conference

    Disrupting the Digital Humanities

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    All too often, defining a discipline becomes more an exercise of exclusion than inclusion. Disrupting the Digital Humanities seeks to rethink how we map disciplinary terrain by directly confronting the gatekeeping impulse of many other so-called field-defining collections. What is most beautiful about the work of the Digital Humanities is exactly the fact that it can’t be tidily anthologized. In fact, the desire to neatly define the Digital Humanities (to filter the DH-y from the DH) is a way of excluding the radically diverse work that actually constitutes the field. This collection, then, works to push and prod at the edges of the Digital Humanities — to open the Digital Humanities rather than close it down. Ultimately, it’s exactly the fringes, the outliers, that make the Digital Humanities both heterogeneous and rigorous. This collection does not constitute yet another reservoir for the new Digital Humanities canon. Rather, its aim is less about assembling content as it is about creating new conversations. Building a truly communal space for the digital humanities requires that we all approach that space with a commitment to: 1) creating open and non-hierarchical dialogues; 2) championing non-traditional work that might not otherwise be recognized through conventional scholarly channels; 3) amplifying marginalized voices; 4) advocating for students and learners; and 5) sharing generously and openly to support the work of our peers

    Using digital technology to engage people with varying degrees of sight loss with archives and filmmaking during COVID-19

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    When the Covid-19 pandemic reached Europe in March 2020, the official archive for Northern Ireland, PRONI (Public Record Office of Northern Ireland) was forced to close its doors and move all work online, including its outreach programmes. One of the people to benefit from the programme was a group with different degrees of sight loss from the Royal National Institute for the Blind (RNIB). Ten people aged 20-60s took part in Everyday is a School Day, an eight-week filmmaking project which used Zoom and smartphone filmmaking to connect them with PRONI’s archives and help them make short films about their experiences of education in 2021. A year later we brought the group back to PRONI for a second project, Music Tales, which helped them continue to develop filmmaking skills and to delve deeper into the archives and explore the role of music in their lives. In this article, we take the two projects as case studies and use a reflective methodology to analyse how Zoom technology and a participatory approach to filmmaking were used to enable the group to engage with archives and learn how to tell their stories through film

    Could AI Democratise Education? Socio-Technical Imaginaries of an EdTech Revolution

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    Artificial Intelligence (AI) in Education has been said to have the potential for building more personalised curricula, as well as democratising education worldwide and creating a Renaissance of new ways of teaching and learning. Millions of students are already starting to benefit from the use of these technologies, but millions more around the world are not. If this trend continues, the first delivery of AI in Education could be greater educational inequality, along with a global misallocation of educational resources motivated by the current technological determinism narrative. In this paper, we focus on speculating and posing questions around the future of AI in Education, with the aim of starting the pressing conversation that would set the right foundations for the new generation of education that is permeated by technology. This paper starts by synthesising how AI might change how we learn and teach, focusing specifically on the case of personalised learning companions, and then move to discuss some socio-technical features that will be crucial for avoiding the perils of these AI systems worldwide (and perhaps ensuring their success). This paper also discusses the potential of using AI together with free, participatory and democratic resources, such as Wikipedia, Open Educational Resources and open-source tools. We also emphasise the need for collectively designing human-centered, transparent, interactive and collaborative AI-based algorithms that empower and give complete agency to stakeholders, as well as support new emerging pedagogies. Finally, we ask what would it take for this educational revolution to provide egalitarian and empowering access to education, beyond any political, cultural, language, geographical and learning ability barriers
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