When Stories Get a Visual Voice: AI-Generated Images, a Visual Pedagogy for Enhancing Student Engagement and Critical Analysis in World Literature
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| Title: | When Stories Get a Visual Voice: AI-Generated Images, a Visual Pedagogy for Enhancing Student Engagement and Critical Analysis in World Literature |
|---|---|
| Language: | English |
| Authors: | Nusaibah Dakamsih (ORCID |
| Source: | Educational Process: International Journal. Article e2025416 2025 18. |
| Availability: | UNIVERSITEPARK Limited. iTOWER Plaza (No61, 9th floor) Merkez Mh Akar Cd No3, Sisli, Istanbul, Turkey 34382. e-mail: editor@edupij.com; Web site: http://www.edupij.com/ |
| Peer Reviewed: | Y |
| Page Count: | 22 |
| Publication Date: | 2025 |
| Document Type: | Journal Articles Reports - Research |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Undergraduate Students, Russian Literature, English Literature, Literary Genres, Artificial Intelligence, Computer Assisted Design, Illustrations, Learner Engagement, Reader Text Relationship, Reader Response, Emotional Response, Aesthetics, Algorithms, Social Bias, Gender Differences, Technology Uses in Education, Student Attitudes |
| ISSN: | 2147-0901 2564-8020 |
| Abstract: | Background/Purpose: This study investigates the pedagogical potential of AI-generated images to enhance student engagement and critical analysis in world literature curricula. Grounded in Reader-Response Theory, it explores how algorithmic visuals impact student interpretation, addressing a gap in understanding technology's role in fostering aesthetic literacy. Materials/Methods: A mixed-method approach was employed in an undergraduate literature course using surveys (N=30) and educator interviews. Students engaged in short stories (e.g., Kafka, Hemingway) accompanied by AI-generated images (Midjourney v5.2). Questionnaires measured emotional/intellectual engagement, and open-ended responses captured interpretive reasoning. Data were analyzed via ANOVA and thematic coding (NVivo14). Results: AI images significantly boosted student emotional engagement (+22%, *p*<0.01), effectively hooking reluctant readers. However, interpretive diversity decreased (3 vs. 9 thematic variants in control groups), potentially narrowing critical thinking. Disparities emerged: women engaged more with symbolic visuals (77.4% emotional connection), while men preferred literal depictions (69.8% analytical focus). AI's cultural biases were identified as a teachable moment for digital literacy by 28% of participants. Conclusion: AI visuals deepen student-text interactions but risk homogenizing interpretation. The study highlights AI's value as a scaffolded pedagogical tool for differentiating instruction, advocating for ethical prompt-crafting exercises to teach algorithmic bias and preserve hermeneutic openness. Findings urge interdisciplinary collaboration to harness AI's capacity for enriching literary learning. |
| Abstractor: | As Provided |
| Entry Date: | 2025 |
| Accession Number: | EJ1485474 |
| Database: | ERIC |
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