About: EdNet: A Large-Scale Hierarchical Dataset in Education

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	EdNet: A Large-Scale Hierarchical Dataset in Education
Creator	Bae, Chan Baek, Jineon Cho, Junghyun Choi, Youngduck Heo, Jaewe Kim, Byungsoo Lee, Seewoo Lee, Youngnam Park, Seoyon Shin, Dongmin
topic	covid:ffc0b608f917bb85d07b8edbe54a26f29bb37604#this
source	PMC
abstract	Advances in Artificial Intelligence in Education (AIEd) and the ever-growing scale of Interactive Educational Systems (IESs) have led to the rise of data-driven approaches for knowledge tracing and learning path recommendation. Unfortunately, collecting student interaction data is challenging and costly. As a result, there is no public large-scale benchmark dataset reflecting the wide variety of student behaviors observed in modern IESs. Although several datasets, such as ASSISTments, Junyi Academy, Synthetic and STATICS are publicly available and widely used, they are not large enough to leverage the full potential of state-of-the-art data-driven models. Furthermore, the recorded behavior is limited to question-solving activities. To this end, we introduce EdNet, a large-scale hierarchical dataset of diverse student activities collected by Santa, a multi-platform self-study solution equipped with an artificial intelligence tutoring system. EdNet contains 131,417,236 interactions from 784,309 students collected over more than 2 years, making it the largest public IES dataset released to date. Unlike existing datasets, EdNet records a wide variety of student actions ranging from question-solving to lecture consumption to item purchasing. Also, EdNet has a hierarchical structure which divides the student actions into 4 different levels of abstractions. The features of EdNet are domain-agnostic, allowing EdNet to be easily extended to different domains. The dataset is publicly released for research purposes. We plan to host challenges in multiple AIEd tasks with EdNet to provide a common ground for the fair comparison between different state-of-the-art models and to encourage the development of practical and effective methods.
has issue date	2020-06-10(xsd:dateTime)
bibo:doi	10.1007/978-3-030-52240-7_13
has license	no-cc
sha1sum (hex)	ffc0b608f917bb85d07b8edbe54a26f29bb37604
schema:url	https://doi.org/10.1007/978-3-030-52240-7_13
resource representing a document's title	EdNet: A Large-Scale Hierarchical Dataset in Education
has PubMed Central identifier	PMC7334672
schema:publication	Artificial Intelligence in Education
resource representing a document's body	covid:ffc0b608f917bb85d07b8edbe54a26f29bb37604#body_text
is http://vocab.deri.ie/void#inDataset of	proxy:http/ns.inria.fr/covid19/ffc0b608f917bb85d07b8edbe54a26f29bb37604
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