ASSESS: Automatic Self Assessment

The Linked Open Data Cloud is a goldmine for educational applications: First, it contains knowledge of encyclopedic nature on a large number of real-world entities. Moreover, the data being structured ensures that the meaning of the data can be understood by both humans and machines. 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 we can use Linked Data as 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. Teachers are supported through the automatic generation and evaluation of tests. Our evaluation shows that ASSESS scales on very large knowledge bases such as DBpedia.

Download Demo

The Linked Open Data Cloud is a goldmine for educational applications: First, it contains knowledge of encyclopedic nature on a large number of real-world entities. Moreover, the data being structured ensures that the meaning of the data can be understood by both humans and machines. 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 we can use Linked Data as 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. Teachers are supported through the automatic generation and evaluation of tests. Our evaluation shows that ASSESS scales on very large knowledge bases such as DBpedia.

Project Team

Publications

by (Editors: ) [BibTex of ]

News

DBpedia @ Google Summer of Code – GSoC 2017 ( 2017-03-13T11:12:50+01:00 Christopher Schulz)

2017-03-13T11:12:50+01:00 Christopher Schulz

DBpedia, one of InfAI’s community projects, will be part of the 5th Google Summer of Code program. The GsoC has the goal to bring students from all over the globe into open source software development. Read more about "DBpedia @ Google Summer of Code – GSoC 2017"

New GERBIL release v1.2.5 – Benchmarking entity annotation systems ( 2017-03-10T11:49:51+01:00 by Ricardo Usbeck)

2017-03-10T11:49:51+01:00 by Ricardo Usbeck

Dear all, the Smart Data Management competence center at AKSW is happy to announce GERBIL 1.2.5. Read more about "New GERBIL release v1.2.5 – Benchmarking entity annotation systems"

DBpedia Open Text Extraction Challenge – TextExt ( 2017-03-09T12:15:57+01:00 Christopher Schulz)

2017-03-09T12:15:57+01:00 Christopher Schulz

DBpedia, a community project affiliated with the Institute for Applied Informatics (InfAI) e.V., extract structured information from Wikipedia & Wikidata. Now DBpedia started the DBpedia Open Text Extraction Challenge – TextExt. Read more about "DBpedia Open Text Extraction Challenge – TextExt"

The USPTO Linked Patent Dataset release ( 2017-02-24T17:18:51+01:00 by Mofeed Hassan)

2017-02-24T17:18:51+01:00 by Mofeed Hassan

Dear all, We are happy to announce USPTO Linked Patent Dataset release. Patents are widely used to protect intellectual property and a measure of innovation output. Read more about "The USPTO Linked Patent Dataset release"

Two accepted papers in ESWC 2017 ( 2017-02-22T17:43:38+01:00 by Dr. Mohamed Ahmed Sherif)

2017-02-22T17:43:38+01:00 by Dr. Mohamed Ahmed Sherif

Hello Community! We are very pleased to announce the acceptance of two papers in ESWC 2017 research track. The ESWC 2017 is to be held in Portoroz, Slovenia from 28th of May to the 1st of June. Read more about "Two accepted papers in ESWC 2017"