Impact of AI-Generated Emotionally-Charged Images on Vocabulary Learning among Teenage EFL Learners
محورهای موضوعی : Teaching
Reza Bakhsheshi-Atigh
1
,
Javad Gholami
2
,
Salva Kazemipour-Khabbazi
3
1 - Department of English Language and Literature, Urmia University, Urmia, Iran
2 - Department of English Language and Literature, Urmia University, Urmia, Iran
3 - Department of English Language and Persian Literature, Hamadan University of Medical Sciences, Hamadan, Iran
کلید واژه: AI-generated images, emotionally-charged stimuli, teenage EFL Learners, vocabulary retention,
چکیده مقاله :
This study examines whether emotionally-charged images created by Artificial Intelligence (AI) can improve vocabulary learning for teenage English as a Foreign Language (EFL) learners. Drawing on the Dual-Coding Theory and Multisensory Learning frameworks, the research explores how emotional stimuli influence vocabulary retention. A within-subjects experimental design was employed, involving 348 male students aged 12-16. Participants were exposed to vocabulary items paired with AI-generated images categorized by emotional valence (positive, negative, non-emotional) and tested on their retention through pretests and posttests. Results from a Repeated-Measures ANOVA revealed that both positive and negative emotional images significantly enhanced vocabulary retention compared to non-emotional images, with no significant difference between positive and negative stimuli. These findings suggest that emotional engagement, regardless of valence, plays a crucial role in enhancing memory and learning outcomes. The study underscores the potential of AI-generated emotionally charged visuals as a transformative tool in EFL education, offering educators innovative strategies to improve vocabulary retention. However, the study also highlights the need for further research to explore the interplay between emotional valence, cognitive load, and contextual learning environments. The findings advocate for the integration of emotionally resonant materials in language instruction to foster greater student engagement and optimize learning outcomes.
This study examines whether emotionally-charged images created by Artificial Intelligence (AI) can improve vocabulary learning for teenage English as a Foreign Language (EFL) learners. Drawing on the Dual-Coding Theory and Multisensory Learning frameworks, the research explores how emotional stimuli influence vocabulary retention. A within-subjects experimental design was employed, involving 348 male students aged 12-16. Participants were exposed to vocabulary items paired with AI-generated images categorized by emotional valence (positive, negative, non-emotional) and tested on their retention through pretests and posttests. Results from a Repeated-Measures ANOVA revealed that both positive and negative emotional images significantly enhanced vocabulary retention compared to non-emotional images, with no significant difference between positive and negative stimuli. These findings suggest that emotional engagement, regardless of valence, plays a crucial role in enhancing memory and learning outcomes. The study underscores the potential of AI-generated emotionally charged visuals as a transformative tool in EFL education, offering educators innovative strategies to improve vocabulary retention. However, the study also highlights the need for further research to explore the interplay between emotional valence, cognitive load, and contextual learning environments. The findings advocate for the integration of emotionally resonant materials in language instruction to foster greater student engagement and optimize learning outcomes.
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