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Recent Advances in Multimodal Educational Data Mining in K-12 Education

Liu, Z; Yang, S; Tang, J; Heffernan, N; Luckin, R; (2020) Recent Advances in Multimodal Educational Data Mining in K-12 Education. In: KDD '20: Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. (pp. pp. 3549-3550). ACM Green open access

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Abstract

Recently we have seen a rapid rise in the amount of education data available through the digitization of education. This huge amount of education data usually exhibits in a mixture form of images, videos, speech, texts, etc. It is crucial to consider data from different modalities to build successful applications in AI in education (AIED). This tutorial targets AI researchers and practitioners who are interested in applying state-of-the-art multimodal machine learning techniques to tackle some of the hard-core AIED tasks. These include tasks such as automatic short answer grading, student assessment, class quality assurance, knowledge tracing, etc. In this tutorial, we will comprehensively review recent developments of applying multimodal learning approaches in AIED, with a focus on those classroom multimodal data. Beyond introducing the recent advances of computer vision, speech, natural language processing in education respectively, we will discuss how to combine data from different modalities and build AI driven educational applications on top of these data. More specifically, we will talk about (1) representation learning; (2) algorithmic assessment & evaluation; and (3) personalized feedback. Participants will learn about recent trends and emerging challenges in this topic, representative tools and learning resources to obtain ready-to-use models, and how related models and techniques benefit real-world AIED applications.

Type: Proceedings paper
Title: Recent Advances in Multimodal Educational Data Mining in K-12 Education
Event: 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining
ISBN-13: 9781450379984
Open access status: An open access version is available from UCL Discovery
DOI: 10.1145/3394486.3406471
Publisher version: https://doi.org/10.1145/3394486.3406471
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Education
UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education
UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education > IOE - Culture, Communication and Media
URI: https://discovery.ucl.ac.uk/id/eprint/10131577
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