About: Prediction of Group Learning Results from an Aggregation of Individual Understanding with Kit-Build Concept Map

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

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Prediction of Group Learning Results from an Aggregation of Individual Understanding with Kit-Build Concept Map
Creator	Hayashi, Yusuke Hirashima, Tsukasa Nomura, Toshihiro
Source	PMC
abstract	With the development of information and communication technology, we can collect and analyze a variety of data for optimization. It is expected that the prediction of learning with the data enables a deep reflection for enhancing the learning experience. This paper describes a method to predict the group learning results from aggregation of an individual’s understanding with the Kit-build concept map (KBmap). KBmap is a reconstruction-type concept map with automated diagnosis of the content. To test this method, we examined the prediction results from the data collected from a classroom lesson. The results show that most of the actual results are in good agreement with the prediction, and the comparison between the actual results and the predictions could be useful for the teacher.
has issue date	2020-06-10(xsd:dateTime)
bibo:doi	10.1007/978-3-030-52240-7_20
has license	no-cc
sha1sum (hex)	d3b0a9eccde340117eb759ec8cc1e36016f77064
schema:url	https://doi.org/10.1007/978-3-030-52240-7_20
resource representing a document's title	Prediction of Group Learning Results from an Aggregation of Individual Understanding with Kit-Build Concept Map
has PubMed Central identifier	PMC7334709
schema:publication	Artificial Intelligence in Education
resource representing a document's body	covid:d3b0a9eccde340117eb759ec8cc1e36016f77064#body_text
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