Is Data-Driven Learning with AI-Generated Example Sentences Effective for Elementary-Level Learners? A Case Study of the Synonyms &#x0201c;collect&#x0201d; and &#x0201c;gather&#x0201d;

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Asian Journal of English Language Teaching ›› 2025, Vol. 34 ›› Issue (1) : 5-22.

Is Data-Driven Learning with AI-Generated Example Sentences Effective for Elementary-Level Learners? A Case Study of the Synonyms “collect” and “gather”

Ryosuke NAKAHARA

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Despite its potential, data-driven learning (DDL) remains underutilized in pre-tertiary education, partly due to the lack of tools that provide ample and level-appropriate example sentences. This classroom-based case study investigates whether generative artificial intelligence (GenAI) can generate suitable example sentences to help elementary-level learners distinguish between the synonyms “gather” and “collect”, and whether the learners can discern their differences through hands-off DDL with the AI-generated example sentences using a pre- and post-test design. Analyses based on the English Vocabulary Profile (EVP) and Coh-Metrix revealed that GenAI can generate sentences that align with the CEFR levels specified in the prompt (i.e., A1-A2). Furthermore, a Bayesian Wilcoxon signed-rank test yielded a Bayes factor (BF₁₀) of 31.564 and an effect size (δ) of -0.68, indicating that the hypothesis that post-test scores are higher than pre-test scores is approximately 32 times more plausible, representing a medium effect size. Although this is a small-scale, classroom-based case study, the findings suggest that GenAI can function as a user-friendly concordancer, offering accessible tools for younger learners and potentially addressing some of the key barriers to implementing DDL in schools.

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Ryosuke NAKAHARA. (2025). Is Data-Driven Learning with AI-Generated Example Sentences Effective for Elementary-Level Learners? A Case Study of the Synonyms “collect” and “gather”.Asian Journal of English Language Teaching , 34(1): 5-22

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