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Mehrsprachigkeit in Europa: Plurilinguismo in Europa ... - EURAC

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Quantity OR quality – an <strong>in</strong>evitable dilemma <strong>in</strong><br />

<strong>in</strong>novative CALL systems?<br />

Judith Knapp, Europäische Akademie Bozen, jknapp@eurac.edu<br />

Angelika Höber, Universität Klagenfurt, angelika.hoeber@uni-klu.ac.at<br />

Abstract<br />

Interactive contact with the learn<strong>in</strong>g material as well as the provision of immediate feedback is the ma<strong>in</strong><br />

advantage of e-learn<strong>in</strong>g <strong>in</strong> comparison to classical learn<strong>in</strong>g environments. However, former developments<br />

gave the impression that researchers, educators and developers had to choose either quality OR quantity<br />

<strong>in</strong> exercise development. As a solution to this dilemma we propose the automatic generation of exercises<br />

by reus<strong>in</strong>g exist<strong>in</strong>g language data and provid<strong>in</strong>g high-quality feedback by us<strong>in</strong>g NLP-tools and structured<br />

language resources. In ELDIT, a web based language learn<strong>in</strong>g system for the German and Italian languages<br />

(www.eurac.edu/eldit), the ma<strong>in</strong> content of the system is described and stored accord<strong>in</strong>g to a very<br />

detailed data model, additionally different tools are <strong>in</strong>cluded that provide externally collected language<br />

<strong>in</strong>formation. Reus<strong>in</strong>g part of these highly structured data (semantic fi elds, <strong>in</strong>fl ection, collocations…) we<br />

developed a prototype which succeeded <strong>in</strong> provid<strong>in</strong>g quantity and quality <strong>in</strong> automatic exercise generation<br />

and correction.<br />

1. Introduction<br />

It is widely accepted that learn<strong>in</strong>g can be supported effi ciently by so-called new technologies.<br />

They offer excit<strong>in</strong>g and powerful new features to present complex <strong>in</strong>formation. Recent<br />

<strong>in</strong>vestigations have shown that learn<strong>in</strong>g with technology support might be motivat<strong>in</strong>g and<br />

effi cient (Eklund and Brusilovsky 1998, Laufer 2000). Language learn<strong>in</strong>g is a specifi c sector<br />

which defi nitely profi ts from new technologies. Nowadays more and more systems arise which<br />

comb<strong>in</strong>e the advantages of the Web with Artifi cial Intelligence technologies (Gamper and Knapp<br />

2002b).<br />

At the European Academy of Bolzano/Bozen we are currently develop<strong>in</strong>g a Web-based<br />

language learn<strong>in</strong>g system called ELDIT. ELDIT <strong>in</strong>cludes an <strong>in</strong>novative learner’s dictionary<br />

and a learner text corpus. Currently, the system is implemented for the German and Italian<br />

languages.<br />

The dictionary is the most advanced module of the system. It conta<strong>in</strong>s approximately 4,000<br />

word entries per language. Each word entry represents semantic <strong>in</strong>formation which helps the<br />

learner to comprehend the right mean<strong>in</strong>g of a word and syntactic <strong>in</strong>formation which helps to<br />

use the word correctly. A dictionary entry is presented to the user <strong>in</strong> two frames (see Figure 1).<br />

The left-hand frame shows the lemma of the word and a list of different word mean<strong>in</strong>gs, each of<br />

which is described by a defi nition, an example sentence, and an optional translation equivalent<br />

<strong>in</strong> the other language. The right-hand frame is organized <strong>in</strong> several tabs and shows additional,<br />

semantic and syntactic <strong>in</strong>formation such as word comb<strong>in</strong>ations, idiomatic expressions, semantic<br />

fi elds, <strong>in</strong>formation on <strong>in</strong>fl ection, l<strong>in</strong>guistic diffi culties, images, etc.<br />

The second module we developed was a text corpus consist<strong>in</strong>g of 400 texts for each<br />

language. The texts are short articles selected from various magaz<strong>in</strong>es and books and conta<strong>in</strong><br />

Multil<strong>in</strong>gualism.<strong>in</strong>db 129 4-12-2006 12:26:21<br />

129

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