Abstract

This research aims at promoting the usage of an online children's dictionary within a context of reading comprehension and vocabulary acquisition. Inspired by document retrieval approaches developed in the area of information retrieval (IR) research, we adapt a particular IR strategy, based on fuzzy logic, to a search in the electronic dictionary. From an unknown word, searched for by a learner, our proposed fuzzy inference process makes it possible to retrieve relevant lexical information from any entry of the dictionary. Furthermore, it organises this information in the form of semantic maps of an adaptable size surrounding the query word. Manual construction of such semantic maps are seen as being effective for helping learners in vocabulary acquisition and reading comprehension tasks. Our research leads to a capability for building them automatically. Using concrete examples, we provide details of the calculation for the construction of semantic maps as well as for the retrieval of information. We introduce a software component which could be integrated in a computer assisted language learning (CALL) environment to promote vocabulary acquisition in L1.

Citation

St-Jacques, C. & Barriere, C. (2005). Search by Fuzzy Inference in a Children's Dictionary. Computer Assisted Language Learning, 18(3), 193-215. Retrieved January 27, 2023 from https://www.learntechlib.org/p/165883/.

This record was imported from ERIC on December 3, 2015. [Original Record]

ERIC is sponsored by the Institute of Education Sciences (IES) of the U.S. Department of Education.

Copyright for this record is held by the content creator. For more details see ERIC's copyright policy.

Keywords

• Dictionaries
• Inferences
• information retrieval
• Logic
• reading comprehension
• Semantics
• Vocabulary Development