Systematic Review of AI in EFL Vocabulary Learning, 2015–2025

25 empirical studies from 2015 to 2025 are synthesized in this systematic review following PRISMA 2020 guidelines. The review maps publication trends, methodological characteristics, and forms of AI integration in higher education English as a Foreign Language contexts. It was authored by Xi Chen and uploaded to figshare in May 2026.

Use Cases

• Analyzing publication trends in AI-supported vocabulary learning research based on the 2015–2025 time frame
• Comparing methodological approaches and AI integration forms across studies based on the reviewed empirical evidence
• Identifying gaps in vocabulary learning outcomes, such as depth and delayed retention, based on the reported dimensions
• Evaluating pedagogical design features associated with stronger learning outcomes based on the synthesis of implementation characteristics

Strengths

• Follows PRISMA 2020 systematic review guidelines, a recognized methodological standard.
• Synthesizes findings from 25 empirical studies, providing a defined evidence base.
• Covers a decade of research from 2015 to 2025, capturing recent trends.

Limitations

• The dataset is a 320 KB document, indicating a limited scope of raw data.
• Row count and column-level documentation are absent; field semantics must be inferred after download.
• Data may reflect publication bias inherent to the systematic review's source selection.

Provenance

Source

figshare

Collection Method

Systematic literature review following PRISMA 2020 guidelines.

Time Range

2015–2025

Freshness

Last updated 2026-05-08 11:04:36