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Ludic, Co-design and Tools Supporting Smart Learning Ecosystems and Smart Education pp 211–223Cite as

Exploratory Analysis of a Large Dataset of Educational Videos: Preliminary Results Using People Tracking

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Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 197))

Abstract

The impact of data processing and analytics in education has seen a significant increase in the last decade. The volumes of data produced in education are constantly on the rise, not only in online education, but also in more formal settings. Learning analytics has concentrated mainly on mining patterns in student and teaching interactions by using data logs and texts (e.g., discussion forums, chats, social networks) which are widely available in online learning platforms. However, videos from educational settings have received a smaller interest from the learning analytics community. Educational videos are becoming popular, and there are large volumes shared on different social networks and video platforms. At the same time, deep learning provides powerful techniques for understanding the content in educational videos. In this paper, we propose an exploratory data analysis using educational videos from the YouTube-8 M dataset, one of the largest video datasets and most varied to date. Our preliminary study uses state-of-the-art people tracking neural models to extract features that are then used to cluster educational videos based on the number of people involved. This allows us to identify various educational activities in the YouTube-8 M dataset and to estimate the distribution of these activities from videos uploaded by teachers and learners worldwide.

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Acknowledgements

This research was funded by the MARKSENSE project “Real-time Analysis Platform For Persons Flows Based on Artificial Intelligence Algorithms and Intelligent Information Processing for Business and Government Environment,” contract no. 124/13.10.2017, MySMIS 2014 code 119261.

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Authors and Affiliations

  1. University Politehnica of Bucharest, 313 Splaiul Independentei, Bucharest, Romania

    Eduard Cojocea & Traian Rebedea

  2. Open Gov SRL, 95 Blvd. Alexandru Ioan Cuza, Bucharest, Romania

    Eduard Cojocea & Traian Rebedea

Authors
  1. Eduard Cojocea
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  2. Traian Rebedea
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Corresponding author

Correspondence to Eduard Cojocea .

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Editors and Affiliations

  1. Department of Communication and Art, Digital Media and Interaction Research Center, University of Aveiro, Aveiro, Portugal

    Óscar Mealha

  2. Department of Architecture, Design, and Media Technology, Aalborg University, Aalborg, Denmark

    Matthias Rehm

  3. Department of Computer Science, University Politehnica of Bucharest, Bucharest, Romania

    Traian Rebedea

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Cojocea, E., Rebedea, T. (2021). Exploratory Analysis of a Large Dataset of Educational Videos: Preliminary Results Using People Tracking. In: Mealha, Ó., Rehm, M., Rebedea, T. (eds) Ludic, Co-design and Tools Supporting Smart Learning Ecosystems and Smart Education. Smart Innovation, Systems and Technologies, vol 197. Springer, Singapore. https://doi.org/10.1007/978-981-15-7383-5_18

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