DIGITAL LIBRARY
AMBIENT LEARNING SPACES: DISCOVER, EXPLORE AND UNDERSTAND SEMANTIC CORRELATIONS
University of L├╝beck (GERMANY)
About this paper:
Appears in: ICERI2020 Proceedings
Publication year: 2020
Pages: 7990-7999
ISBN: 978-84-09-24232-0
ISSN: 2340-1095
doi: 10.21125/iceri.2020.1771
Conference name: 13th annual International Conference of Education, Research and Innovation
Dates: 9-10 November, 2020
Location: Online Conference
Abstract:
There is a worldwide discussion about digitization in school education. This discussion is often technology-centered leaving a lack of solutions for daily schooling or focuses on isolated educational applications. Neither WiFi at school nor desktop-PCs, tablets, or smartphones will be the answer. However, they can be elements for a solution, if there is a didactic infrastructure that connects and integrates these devices into methods of student-centered forms of solving and discovering teaching content.

With the Ambient Learning Spaces (ALS) platform, we developed such a didactic infrastructure as an integrated environment for 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 different interactive learning applications with central semantic media storage. This paper emphasizes on the two learning applications for semantic (SemCor) and chronological correlations (TimeLine).

Semantic relationships are a key in building up knowledge about the world. SemCor is a learning application within ALS that supports interactive exploration of semantic correlations between knowledge entities and graphically visualizes a semantic web. With SemCor students may use any knowledge entity as a start (seed) to search for related entities. SemCor can use any semantically annotated media object of ALS, notion, or Wikipedia entity as a seed leading to related entities through attributes and tags (e.g. Wikipedia weblinks) or abstractions (e.g. DBpedia categories). Other knowledge spaces can be defined and connected to SemCor leading to learning by discovery in predefined topical domains. SemCor implements the principle of serendipity through a dynamic graphical representation of the structure and content of knowledge. Other than just following links in the WWW, SemCor keeps and visualizes the current context of learning with its complexity.

Another learning application of ALS, TimeLine, is specialized in showing chronological correlations of 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. Several dimensions can be displayed as parallel timelines visualizing chronological correlations of events. TimeLine has been used for natural sciences (e.g. paleontological excavations) and history (e.g. political, economic, and technological development in certain contexts and periods). It enables students to set up their own timelines and attach media connected 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 and represented.

Teachers and learners are enabled to use the different modular teaching applications of the ALS system as a modeling environment as well as learning applications. An overview of the whole system can be found in Proceedings of iCERi 2019 (Herczeg, Ohlei, Winkler, 2019). ALS installations are currently in use in several schools and museums.
Keywords:
Ambient Learning Spaces, Semantic Modeling, Semantic Web, Timelines, Multimedia Learning.