Artificial Intelligence for English Learning Enhancing Vocabulary Acquisition
BY AUNG KHANT KYAW
Authors
Rodríguez Altamiranda, M. C., Villamizar Parada, N. J., Martinez Bula, L. R., Restrepo Ruiz, M., Herazo Chamorro, M., & Gómez Díaz, C. (2024) (IJISAE)
Published In
International Journal of Intelligent Systems and Applications in Engineering (IJISAE), Vol. 12, No. 21s (2024), United States. (IJISAE)
1. Brief Research Background
Vocabulary acquisition is a foundational part of English language learning, particularly because vocabulary knowledge supports all language skills—reading, listening, writing, and speaking. Traditional methods such as rote memorization and repetitive drills often fail to engage students and do not effectively support long-term retention.
With advancements in Artificial Intelligence (AI) technology, there are opportunities to transform vocabulary learning through personalized and adaptive systems. These AI systems analyze learners’ performance and tailor practice materials to meet individual needs, potentially increasing engagement and learning gains.
This study explores how AI can enhance English vocabulary acquisition by offering adaptive learning experiences that respond to learners’ strengths and weaknesses. (IJISAE)
2. Literature Review (Brief)
Previous research indicates that traditional vocabulary learning approaches often lack personalization and fail to sustain learner engagement. Scholars in educational technology have emphasized that adaptive learning systems, driven by AI and machine learning, can offer customized content that aligns with learners’ individual profiles, promoting more effective learning experiences.
Studies also show that personalized feedback and tailored exercises can increase motivation and improve retention of new words. However, research on AI’s specific impact on English vocabulary acquisition is still emerging, prompting the need to investigate the potential benefits and challenges of AI-enhanced vocabulary learning. (IJISAE)
3. Research Keywords
Vocabulary acquisition
English language learning
Artificial intelligence (AI)
Personalized learning
Adaptive algorithms
Machine learning
Engagement (IJISAE)
4. Research Scope
This research explores the application of AI technologies in enhancing English vocabulary learning. The study focuses on how AI systems can:
Provide customized vocabulary practice
Analyze learners’ strengths and weaknesses
Deliver adaptive content based on individual learner needs
The analysis emphasizes the potential of AI to increase engagement and improve learning outcomes in English vocabulary acquisition. The study does not involve new experimental research but evaluates existing AI tools and educational strategies described in the literature. (IJISAE)
5. Related Literature Topics
Adaptive learning and personalized instruction
The role of AI in language education
Machine learning applications in vocabulary teaching
Student engagement through digital learning tools
Impact of personalized feedback on learning outcomes
Technology-enhanced language learning strategies (IJISAE)
6. Overall Research Framework
The research framework centers on the premise that vocabulary acquisition is more effective when learning experiences are tailored to students’ individual needs. In this model:
AI systems analyze learner data (e.g., past performance, error patterns)
Adaptive algorithms generate personalized exercises
Learners engage with content suited to their proficiency level
Immediate feedback and adaptive pacing improve retention and understanding
This structured, AI-supported learning cycle aims to increase learner engagement, motivation, and ultimately vocabulary acquisition effectiveness compared to traditional one-size-fits-all methods. (IJISAE)
7. Key Findings
The study concludes that AI has significant potential to enhance English vocabulary learning. Key insights include:
Personalization: AI systems can tailor content to learners’ individual needs, making learning more effective.
Engagement: Adaptive exercises increase student interest and participation.
Retention: Customized practice and feedback help improve retention of new words.
Flexibility: Learners benefit from self-paced, responsive learning environments.
Overall, the research suggests that when integrated thoughtfully, AI tools can transform vocabulary acquisition by making it more adaptive, engaging, and efficient. (IJISAE)
Reference
Rodríguez Altamiranda, M. C., Villamizar Parada, N. J., Martinez Bula, L. R., Restrepo Ruiz, M., Herazo Chamorro, M., & Gómez Díaz, C. (2024). Artificial intelligence for English learning: Enhancing vocabulary acquisition. International Journal of Intelligent Systems and Applications in Engineering, 12(21s), 1575–1580. https://ijisae.org/index.php/IJISAE/article/view/5630 (IJISAE)
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