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Flipped Design Thinking with Generative AI for Digital Literacy in ODL

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Title: Flipped Design Thinking with Generative AI for Digital Literacy in ODL
Language: English
Authors: Gede Suwardika (ORCID 0000-0002-4799-9048), Agus Tatang Sopandi, I. Putu Oktap Indrawan, Kadek Masakazu
Source: Asian Association of Open Universities Journal. 2026 21(1):48-64.
Availability: Emerald Publishing Limited. Howard House, Wagon Lane, Bingley, West Yorkshire, BD16 1WA, UK. Tel: +44-1274-777700; Fax: +44-1274-785201; e-mail: emerald@emeraldinsight.com; Web site: http://www.emerald.com/insight
Peer Reviewed: Y
Page Count: 17
Publication Date: 2026
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Flipped Classroom, Design, Thinking Skills, Artificial Intelligence, Digital Literacy, Open Education, Distance Education, Foreign Countries, Undergraduate Students, Academic Language, Writing Instruction, Electronic Learning, Student Attitudes
Geographic Terms: Indonesia
DOI: 10.1108/AAOUJ-11-2025-0206
ISSN: 2414-6994
Abstract: Purpose: This study examines how three instructional conditions -- Conventional Tutorial, Flipped Classroom Design Thinking (FCDT), and an AI-supported FCDT-AI model using ChatGPT -- shape undergraduate students' Digital Literacy within an open and distance learning (ODL) environment at Universitas Terbuka, Indonesia. It responds to the growing need for scalable pedagogical models that integrate flipped learning, design thinking, and generative AI across Asian open universities. Design/methodology/approach: A within-subjects repeated-measures design was employed with 26 undergraduate students enrolled in an Academic Writing Techniques course. All participants experienced the three conditions in counterbalanced order via TUWEB, the institutional learning management system. Digital Literacy was measured after each condition using a multidimensional performance-based questionnaire. Quantitative analysis used Huynh--Feldt-adjusted repeated-measures ANOVA with Holm-adjusted post-hoc tests, while qualitative reflection logs were examined using reflexive thematic analysis to elucidate mechanisms underlying observed differences. Findings: A significant and substantial main effect of instructional condition was identified, demonstrating a clear performance gradient: Conventional < FCDT < FCDT-AI. The AI-supported condition yielded the highest Digital Literacy scores and the broadest distribution of advanced practices. Qualitative themes further revealed progressive development from basic access and retrieval (Conventional), to structured evaluation and emerging digital production (FCDT), and to multimodal, reflective, and AI-mediated digital engagement (FCDT-AI). Research limitations/implications: This study has several limitations. The small sample from a single programme at one ODL institution restricts generalisability, suggesting the need for replication across disciplines, universities, and learner profiles. The reliance on self-reported reflections may introduce subjectivity; integrating learning analytics or artefact analysis would strengthen triangulation. The AI scaffolding was intentionally limited for ethical reasons, meaning future studies could examine varying intensities or types of AI support. Despite these constraints, the findings offer empirically grounded implications for designing scalable, AI-supported flipped learning models in ODL environments. Practical implications: The findings provide actionable guidance for ODL institutions seeking to strengthen Digital Literacy at scale. Tutors should integrate structured flipped-learning cycles supported by design thinking to guide learners from basic access toward evaluative and creative digital practices. Incorporating generative AI as guided scaffolding -- rather than as an autonomous problem-solver -- can expand students' idea generation, support multimodal production, and reduce cognitive load. Curriculum designers can embed FCDT-AI workflows into tutorial manuals, LKMs, and online learning activities to promote consistent digital engagement. Institutions may also develop training programmes to enhance tutors' digital pedagogy and ethical AI facilitation. Social implications: Enhancing Digital Literacy through structured flipped and AI-supported models can help narrow digital inequities among geographically dispersed ODL learners. The FCDT-AI framework supports more inclusive participation by providing scaffolding that benefits students with lower digital readiness, thereby promoting equitable access to 21st-century competencies. As generative AI becomes more widespread in education and work, developing students' evaluative, ethical, and creative digital practices contributes to a more informed and responsible digital citizenry. The model also supports lifelong learning, empowering working adults to engage confidently in digitally mediated environments and strengthening broader community digital resilience. Originality/value: The study offers one of the first empirically tested pedagogical models that systematically integrates flipped learning, design thinking, and generative AI to strengthen Digital Literacy in ODL environments. It provides a theoretically grounded and scalable framework (FCDT-AI) that can support Asian open universities in implementing ethical and effective AI-enhanced digital learning.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1508319
Database: ERIC
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  Data: Emerald Publishing Limited. Howard House, Wagon Lane, Bingley, West Yorkshire, BD16 1WA, UK. Tel: +44-1274-777700; Fax: +44-1274-785201; e-mail: emerald@emeraldinsight.com; Web site: http://www.emerald.com/insight
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  Data: Purpose: This study examines how three instructional conditions -- Conventional Tutorial, Flipped Classroom Design Thinking (FCDT), and an AI-supported FCDT-AI model using ChatGPT -- shape undergraduate students&#39; Digital Literacy within an open and distance learning (ODL) environment at Universitas Terbuka, Indonesia. It responds to the growing need for scalable pedagogical models that integrate flipped learning, design thinking, and generative AI across Asian open universities. Design/methodology/approach: A within-subjects repeated-measures design was employed with 26 undergraduate students enrolled in an Academic Writing Techniques course. All participants experienced the three conditions in counterbalanced order via TUWEB, the institutional learning management system. Digital Literacy was measured after each condition using a multidimensional performance-based questionnaire. Quantitative analysis used Huynh--Feldt-adjusted repeated-measures ANOVA with Holm-adjusted post-hoc tests, while qualitative reflection logs were examined using reflexive thematic analysis to elucidate mechanisms underlying observed differences. Findings: A significant and substantial main effect of instructional condition was identified, demonstrating a clear performance gradient: Conventional &lt; FCDT &lt; FCDT-AI. The AI-supported condition yielded the highest Digital Literacy scores and the broadest distribution of advanced practices. Qualitative themes further revealed progressive development from basic access and retrieval (Conventional), to structured evaluation and emerging digital production (FCDT), and to multimodal, reflective, and AI-mediated digital engagement (FCDT-AI). Research limitations/implications: This study has several limitations. The small sample from a single programme at one ODL institution restricts generalisability, suggesting the need for replication across disciplines, universities, and learner profiles. The reliance on self-reported reflections may introduce subjectivity; integrating learning analytics or artefact analysis would strengthen triangulation. The AI scaffolding was intentionally limited for ethical reasons, meaning future studies could examine varying intensities or types of AI support. Despite these constraints, the findings offer empirically grounded implications for designing scalable, AI-supported flipped learning models in ODL environments. Practical implications: The findings provide actionable guidance for ODL institutions seeking to strengthen Digital Literacy at scale. Tutors should integrate structured flipped-learning cycles supported by design thinking to guide learners from basic access toward evaluative and creative digital practices. Incorporating generative AI as guided scaffolding -- rather than as an autonomous problem-solver -- can expand students&#39; idea generation, support multimodal production, and reduce cognitive load. Curriculum designers can embed FCDT-AI workflows into tutorial manuals, LKMs, and online learning activities to promote consistent digital engagement. Institutions may also develop training programmes to enhance tutors&#39; digital pedagogy and ethical AI facilitation. Social implications: Enhancing Digital Literacy through structured flipped and AI-supported models can help narrow digital inequities among geographically dispersed ODL learners. The FCDT-AI framework supports more inclusive participation by providing scaffolding that benefits students with lower digital readiness, thereby promoting equitable access to 21st-century competencies. As generative AI becomes more widespread in education and work, developing students&#39; evaluative, ethical, and creative digital practices contributes to a more informed and responsible digital citizenry. The model also supports lifelong learning, empowering working adults to engage confidently in digitally mediated environments and strengthening broader community digital resilience. Originality/value: The study offers one of the first empirically tested pedagogical models that systematically integrates flipped learning, design thinking, and generative AI to strengthen Digital Literacy in ODL environments. It provides a theoretically grounded and scalable framework (FCDT-AI) that can support Asian open universities in implementing ethical and effective AI-enhanced digital learning.
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        Value: 10.1108/AAOUJ-11-2025-0206
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      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 17
        StartPage: 48
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      – SubjectFull: Thinking Skills
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      – SubjectFull: Student Attitudes
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      – SubjectFull: Indonesia
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      – TitleFull: Flipped Design Thinking with Generative AI for Digital Literacy in ODL
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