Catapulting Vocabulary through Corpora and Corpus Tools
Year: 2026
Type: article
Abstract: The rapid advancement of Information and Communication Technology has led to the large-scale proliferation of data across educational domains. This accelerated development of ICT has paved the way for innovative language learning approaches such as Data-Driven Learning (DDL). Corpus-based tools allow learners and teachers to investigate recurring patterns in language, including frequency and collocation. This study analysed the effectiveness of corpus-based intervention in enhancing the vocabulary proficiency of beginner-level English learners, with particular focus on words from the Academic Word List (AWL). A pilot study was conducted to assess the existing vocabulary knowledge of 30 basic-stream English learners. The pilot study revealed a clear lexical gap and informed the design of corpus-based resources. The conventional prescribed instructional materials were then uploaded into VocabProfile, a corpus linguistic tool, to categorise vocabulary according to frequency bands and to identify AWL items. Targeted instructional materials were developed using these profiles featuring authentic language input and frequency-informed vocabulary activities. A pre-test–post-test design was used with the same cohort, with a two-week intervention between the tests. The paired t-test revealed a statistically significant improvement from pre-test to post-test, t(29) = 10.00, p < .001, with a large effect size (Cohen’s d = 1.84), and the test instrument showed high reliability (KR-20 = 0.90). The results showed a statistically significant improvement in post-test scores, indicating that the corpus-informed materials enhanced learners’ vocabulary acquisition, including AWL words. The study highlights the potential of corpus-based pedagogical materials to strengthen lexical competence among ESL learners.
Authors: F S Roselin Jenifer, S J Kala
Language: English
Subfield: Developmental and Educational Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W7225748800