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Can Population-based Engagement Improve Personalisation? A Novel Dataset and Experiments. (arXiv:2207.01504v1 [cs.CY])
July 5, 2022, 1:12 a.m. | Sahan Bulathwela, Meghana Verma, Maria Perez-Ortiz, Emine Yilmaz, John Shawe-Taylor
stat.ML updates on arXiv.org arxiv.org
This work explores how population-based engagement prediction can address
cold-start at scale in large learning resource collections. The paper
introduces i) VLE, a novel dataset that consists of content and video based
features extracted from publicly available scientific video lectures coupled
with implicit and explicit signals related to learner engagement, ii) two
standard tasks related to predicting and ranking context-agnostic engagement in
video lectures with preliminary baselines and iii) a set of experiments that
validate the usefulness of the proposed …
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