Using Crowdsourced Exercises for Vocabulary Training to Expand ConceptNet

Christos Rodosthenous, Verena Lyding, Federico Sangati, Alexander König, Umair Ul Hassan, Lionel Nicolas, Jolita Horbacauskiene, Anisia Katinskaia, Lavinia Aparaschivei

Forskningsoutput: KonferensbidragKonferenspapper


In this work, we report on a crowdsourcing experiment conducted using the V-TREL vocabulary trainer which is accessed via a Telegram chatbot interface to gather knowledge on word relations suitable for expanding ConceptNet. V-TREL is built on top of a generic architecture implementing the implicit crowdsourding paradigm in order to offer vocabulary training exercises generated from the commonsense knowledge-base ConceptNet and -- in the background -- to collect and evaluate the learners' answers to extend ConceptNet with new words. In the experiment about 90 university students learning English at C1 level, based on Common European Framework of Reference for Languages (CEFR), trained their vocabulary with V-TREL over a period of 16 calendar days. The experiment allowed to gather more than 12,000 answers from learners on different question types. In this paper we present in detail the experimental setup and the outcome of the experiment, which indicates the potential of our approach for both crowdsourcing data as well as fostering vocabulary skills.
Antal sidor316
StatusPublicerad - 2020
MoE-publikationstypEj behörig
EvenemangThe 12th Language Resources and Evaluation Conference - Le Palais du Pharo, Marseille, Frankrike
Varaktighet: 11 maj 202016 maj 2020
Konferensnummer: 12


KonferensThe 12th Language Resources and Evaluation Conference
Förkortad titelLREC 2020

Citera det här

Rodosthenous, C., Lyding, V., Sangati, F., König, A., Ul Hassan, U., Nicolas, L., ... Aparaschivei, L. (2020). Using Crowdsourced Exercises for Vocabulary Training to Expand ConceptNet. 307. Artikel presenterad vid The 12th Language Resources and Evaluation Conference, Marseille, Frankrike.