ASSESS — automatic self-assessment using linked data
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The Semantic Web – ISWC 2015 - 14th International Semantic Web Conference, Proceedings. ed. / Marcelo Arenas; Oscar Corcho; Elena Simperl; Markus Strohmaier; Mathieu d’Aquin; Kavitha Srinivas; Paul Groth; Michel Dumontier; Jeff Heflin; Krishnaprasad Thirunarayan; Steffen Staab. Springer-Verlag Wien, 2015. p. 76-89 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9367).
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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TY - CHAP
T1 - ASSESS — automatic self-assessment using linked data
AU - Bühmann, Lorenz
AU - Usbeck, Ricardo
AU - Ngonga Ngomo, Axel Cyrille
N1 - Publisher Copyright: © Springer International Publishing Switzerland 2015.
PY - 2015
Y1 - 2015
N2 - The Linked Open Data Cloud is a goldmine for creating open and low-cost educational applications: First, it contains open knowledge of encyclopedic nature on a large number of real-world entities. Moreover, the data being structured ensures that the data is both human and machine-readable. Finally, the openness of the data and the use of RDF as standard format facilitate the development of applications that can be ported across different domains with ease. However, RDF is still unknown to most members of the target audience of educational applications. Thus, Linked Data has commonly been used for the description or annotation of educational data. Yet, Linked Data has (to the best of our knowledge) never been used as direct source of educational material. With ASSESS, we demonstrate that Linked Data can be used as a source for the automatic generation of educational material. By using innovative RDF verbalization and entity summarization technology, we bridge between natural language and RDF. We then use RDF data directly to generate quizzes which encompass questions of different types on user defined domains of interest. By these means, we enable learners to generate self-assessment tests on domains of interest. Our evaluation shows that ASSESS generates high-quality English questions. Moreover, our usability evaluation suggests that our interface can be used intuitively. Finally, our test on DBpedia shows that our approach can be deployed on very large knowledge bases.
AB - The Linked Open Data Cloud is a goldmine for creating open and low-cost educational applications: First, it contains open knowledge of encyclopedic nature on a large number of real-world entities. Moreover, the data being structured ensures that the data is both human and machine-readable. Finally, the openness of the data and the use of RDF as standard format facilitate the development of applications that can be ported across different domains with ease. However, RDF is still unknown to most members of the target audience of educational applications. Thus, Linked Data has commonly been used for the description or annotation of educational data. Yet, Linked Data has (to the best of our knowledge) never been used as direct source of educational material. With ASSESS, we demonstrate that Linked Data can be used as a source for the automatic generation of educational material. By using innovative RDF verbalization and entity summarization technology, we bridge between natural language and RDF. We then use RDF data directly to generate quizzes which encompass questions of different types on user defined domains of interest. By these means, we enable learners to generate self-assessment tests on domains of interest. Our evaluation shows that ASSESS generates high-quality English questions. Moreover, our usability evaluation suggests that our interface can be used intuitively. Finally, our test on DBpedia shows that our approach can be deployed on very large knowledge bases.
KW - Informatics
KW - inferior vena cava
KW - educational material
KW - link data
KW - automatic generation
KW - data layer
KW - Business informatics
UR - http://www.scopus.com/inward/record.url?scp=84952646935&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/60436f24-e810-3fde-add7-8eeaebdfb5a1/
U2 - 10.1007/978-3-319-25010-6_5
DO - 10.1007/978-3-319-25010-6_5
M3 - Article in conference proceedings
AN - SCOPUS:84952646935
SN - 978-3-319-25009-0
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 76
EP - 89
BT - The Semantic Web – ISWC 2015 - 14th International Semantic Web Conference, Proceedings
A2 - Arenas, Marcelo
A2 - Corcho, Oscar
A2 - Simperl, Elena
A2 - Strohmaier, Markus
A2 - d’Aquin, Mathieu
A2 - Srinivas, Kavitha
A2 - Groth, Paul
A2 - Dumontier, Michel
A2 - Heflin, Jeff
A2 - Thirunarayan, Krishnaprasad
A2 - Staab, Steffen
PB - Springer-Verlag Wien
T2 - 14th International Semantic Web Conference, ISWC 2015
Y2 - 11 October 2015 through 15 October 2015
ER -