open window

open window

Educational content enriched with links enables learners to look beyond the current text and start learning self-contained in the World Wide Web. Just like looking out of an open window.


open window is concerned to give the opportunity for learners to look into interlinked educational content in the World Wide Web. As part of the Open Window project, technologies for automatic linking educational content with different collaboratively created media are developed. These collaborative created media include encyclopedias, such as Wikipedia, and social media services, such as Twitter.

Automatic linking of educational content is done via the identification of so-called learning elements: learning elements are themes that describe the main concepts of a document. Learning elements are the most important learning concepts present in a document. For example, a document about the American Civil War can have “USA”, “Civil War” and “Lincoln” as learning elements. Learning elements are similar to tags, with the restriction that they rely on learning topics. These learning elements can be used to group texts which have the same learning elements and link them together.


The Open Window project is focused on the development of NLP components for processing educational content and its annotations. Educational content can be any kind of document with an educational reference, such as textbooks, lecture notes, forums on education topics and so on.

Challenges to tackle:

  • Identification of individual learning elements (topics);
  • Improvement of annotations, images and opinions descriptions. Some of them might have a poor explanation in a specific context;
  • Link discovery between educational content.

For this purpose, components which must treat faulty texts, as is the case with Twitter or Flickr, have to be developed. Likewise, components for identification of learning elements in educational content and linking these contents have to be developed as well.


We preprocess our data using reusable NLP components from Darmstadt Knowledge Processing Software Repository. Decompounding algorithms, preprocessing components from DKPro Core and keyphrase extractiong methods from DKPro Keyphrases are examples of software components reused by the open window project.


IMC is the industry partner for this Software Campus project. IMC is working in national and international research projects to develop innovations and new products for learning and knowledge management. Thereby the focus lies on the development of new tools and innovative prototypes in the fields of learning management systems, content management, performance support, authoring tools, Web 2.0 applications as well as web-based and mobile platforms.


  • Prof. Dr. Iryna Gurevych, Principal Investigator
  • Nicolai Erbs, Doctoral Researcher
  • Pedro Santos, Research Assistant