Utilizing Computational Technology in Semantic Field Construction: Alternative in Teaching New Vocabulary
Ermanto- Havid Ardi- Novia Juita

Universitas Negeri Padang

Abstract

During the Covid-19 pandemic, new terms and meanings flooded into the Indonesian vernacular. Some of these new lexemes are borrowed English words and some are translated into Indonesian vocabulary. The purpose of this study was to propose the use of technology (computational) to construct the semantic field of the new vocabulary for Indonesian language learners. Current study used 17 web-published news and web-based health care application as source of text about Covid-19 to generate a word-list related to COVID-19 pandemic to construct semantic field of Covid-19 lexemes in Indonesian context. The analysis was conducted by using AntConc (version 3.5.9) application to analyse the appearances of the new lexemes in the corpus. The analysis found 96 pandemic-related terms in 473 corpus files dated from December 2019 to February 2022. The results demonstrate that there are five semantic subfields classified as entities, causes, cure, and individual and societal anticipation. The entities subfield has the greatest number of related terms found in the corpus. These findings indicate that technology might be used to build students understanding about new vocabulary in L1 language.

Keywords: corpus, covid-19 related term, semantic field, teaching vocabulary, technology for language learning.

Topic: Opportunities and Challenges for Future Teachers