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Learning analytics for learners - Ways of seeing learning


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Learning analytics for learners - Ways of seeing learning

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Learning analytics for learners - Ways of seeing learning

  1. 1. Learning Analytics for Learners - Ways of seeing Learning Mary Loftus NUI Galway
  2. 2. Central to education’s purpose is “the coming into presence of unique individual beings” Education “spaces might open up for uniqueness to come into the world” – Gert Biesta – ‘Good Education in an Age of Measurement: Ethics, Politics, Democracy’
  3. 3. If we can make learning more visible, we can... • Reduce the need for formal testing and examinations • More Problem-based Learning Assessment • More Formative Feedback for Students • Model Student’s Conceptual Understanding • Support Metacognition
  4. 4. What do you mean - ways of seeing learning? • Piech (2015) - Deep Knowledge Tracing - looked at how students learn to program, modelled their learning path, identified where they got stuck, how they got unstuck (Piech 2015) • Blikstein, Baker & Berland (2014) used Educational Data Mining (EDM) in informal learning spaces such as ‘maker spaces’ and programming clubs to measure and log the process of creative problem solving • PELARS Project (2015) developed a framework for Learning Analytics for Maker Spaces and creative problem solving (Cukurova, Spikol et al 2015) • Kitto et al (2015) developed a Natural Language Processing tool which automatically classified student discussion posts according to the Community of Inquiry model (Kitto, Gasevic et al 2015) • Lin (2013) used data mining to provide a personalized learning path in a creativity programme • Buckingham Shum & Deakin Crick (2016) looked at measuring features like Mindful Agency, Sensemaking, Creativity, Curiosity, Belonging, Collaboration, Hope and Optimism, and Orientation to Learning
  5. 5. Ways of Seeing Learning – the research proposal • 1st Yr Cohort of BSc in Computing students • Students using a system to capture, and learn from, their own learning data as part of their course work • Data Literacy capability building • Use of Machine Learning to classify and model aspects of learning as it happens
  6. 6. “For apart from inquiry, apart from the praxis, individuals cannot be truly human. Knowledge emerges only through invention and re-invention, through the restless, impatient, continuing, hopeful inquiry human beings pursue in the world, with the world, and with each other.” Paulo Freire “Action can never manifest through a predictable, deterministic series of consequences, since the subject, by acting, is placed within a complicated web of relationships which cannot be predicted before hand. In the same sense, Action is irreversible.” Hannah Arendt