Artificial intelligence-assisted vocabulary teaching: a meta-analysis study.

Area of Science:

• Educational Technology
• Artificial Intelligence in Education
• Applied Linguistics

Background:

• Research indicates artificial intelligence (AI) shows promise for improving vocabulary learning.
• Existing studies present varied findings, necessitating a synthesis of evidence.
• Gaps in current research highlight the need for deeper insights into AI-supported vocabulary instruction.

Purpose of the Study:

• To conduct a meta-analysis on the effectiveness of AI-supported interventions for vocabulary learning.
• To synthesize existing evidence on AI's impact on vocabulary acquisition.
• To provide generalizable conclusions on AI in vocabulary teaching.

Main Methods:

• Meta-analytic design utilizing 18 studies published between 2015 and 2025.
• Data sourced from Web of Science Core Collection, Scopus, and ERIC databases.
• Inclusion criteria yielded 23 effect sizes from 1,823 participants.

Main Results:

• AI-supported interventions demonstrated a large, positive overall effect on vocabulary learning performance (g = 1.309).
• Significant moderating effects were observed for language type, learner educational level, control treatment, and intervention setting.
• Teacher involvement and intervention duration did not significantly moderate the effects.

Conclusions:

• AI-supported vocabulary instruction is highly effective in enhancing learning outcomes.
• AI applications offer personalized, context-sensitive learning opportunities across diverse educational settings.
• This study underscores the significant instructional potential of AI in vocabulary education.