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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 0009-0000-2944-8114), Mo’tasim-Bellah Alshunnag (ORCID 0000-0002-9951-1155), Azel Alkayid
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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  Data: 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&#39;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*&lt;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&#39;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&#39;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&#39;s capacity for enriching literary learning.
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  Data: EJ1485474
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1485474
RecordInfo BibRecord:
  BibEntity:
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 22
    Subjects:
      – SubjectFull: Undergraduate Students
        Type: general
      – SubjectFull: Russian Literature
        Type: general
      – SubjectFull: English Literature
        Type: general
      – SubjectFull: Literary Genres
        Type: general
      – SubjectFull: Artificial Intelligence
        Type: general
      – SubjectFull: Computer Assisted Design
        Type: general
      – SubjectFull: Illustrations
        Type: general
      – SubjectFull: Learner Engagement
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      – SubjectFull: Reader Text Relationship
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      – SubjectFull: Reader Response
        Type: general
      – SubjectFull: Emotional Response
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      – SubjectFull: Aesthetics
        Type: general
      – SubjectFull: Algorithms
        Type: general
      – SubjectFull: Social Bias
        Type: general
      – SubjectFull: Gender Differences
        Type: general
      – SubjectFull: Technology Uses in Education
        Type: general
      – SubjectFull: Student Attitudes
        Type: general
    Titles:
      – TitleFull: 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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            NameFull: Mo’tasim-Bellah Alshunnag
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            NameFull: Azel Alkayid
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              Type: published
              Y: 2025
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            – TitleFull: Educational Process: International Journal
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