Ambient Learning Spaces: Discover, Explore and Understand Semantic Correlations

Allgemeines

Art der Publikation: Conference Paper

Veröffentlicht auf / in: Proceedings of ICERI2020 Conference 9th-10th November 2020

Jahr: 2020

Seiten: 7990-7999

Verlag (Publisher): IATED

ISBN: 978-84-09-24232-0

Autoren

Michael Herczeg

Toni Schumacher

Alexander Ohlei

Abstract

There is a worldwide discussion about digitization in school education. This discussion is mostly
technology-centered, leaving a lack of solutions for daily schooling or focuses on isolated educational
applications. With the Ambient Learning Spaces (ALS) platform, we developed a didactic infrastructure
as an integrated environment that supports self-directed learning inside and outside school. The
platform interlinks mobile and stationary learning applications. The artificial division between the
classroom and the world outside vanishes through the pervasive cloud-based backend system NEMO
(Network Environment for Multimedia Objects) connecting students’ mobile applications with central
semantic media storage. This paper emphasizes on the two learning applications for general semantic
correlations (SemCor) and chronological correlations (TimeLine). SemCor is a learning application
within ALS that supports interactive exploration of semantic relationships between knowledge entities
and graphically visualizes a semantic web. With SemCor students may use any knowledge entity as a
starting point to search for related entities. SemCor can use any semantically annotated ALS media
object, any notion, or Wikipedia entity as a seed leading to related entities through attributes, tags
(e.g. Wikipedia weblinks) or abstractions (e.g. DBpedia categories). Other knowledge spaces can be
defined and available ones can be connected to SemCor leading to learning by discovery in more
predefined topical domains. SemCor implements the principle of serendipity through a dynamic
graphical representation of structure and content of knowledge. The learning application TimeLine is
specialized in showing chronological correlations of events in the world. It allows setting up
multidimensional timelines to display knowledge entities represented by annotated media like text,
image, audio, or video in the ALS storage NEMO, visualizing distances between events and their
entities. It enables students to set up their own timelines and attach media related to selected events
and entities. TimeLine entities can be used as seeds for SemCor leading to further semantical
explorations of the time structures already found.

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