A study on folklore for glocalized children's literature at PTKI: Artificial Intelligence (AI) innovations in visual storytelling
Abstract
The intersection of folklore and Artificial Intelligence (AI) has become a prominent trend in contemporary research, driven by the widespread availability of applications such as Leonardo.ai, Storybook, and Canva that support folklore creation. Given folklore's significant role in shaping the personalities of younger generations, integrating glocalization with AI becomes increasingly relevant. This study aims to explore the projection of AI through storytelling in folklore and examine the glocalization of children's literature within PTKI (Indonesian Islamic Higher Education Institutions) using the theory of Glocalization by Khondker (five main elements of glocalization) and Leonardo.ai. This research employed a descriptive qualitative method by Creswell to describe the phenomenon and its characteristics. The data were collected qualitatively by documenting, examining, and thoroughly classifying using three steps: reading the folktales, taking notes, and interpreting or analyzing. Employing a qualitative approach, the research involved 125 student participants from PTKI and utilized the Likert Scale theory by Rensis Likert for data analysis. The findings reveal two key outcomes: first, Leonardo.ai effectively generates detailed visual storytelling by creating and refining prompts without losing the narratives based on the elements of the story. Second, AI-generated products can achieve global dissemination while promoting local cultural elements, as evidenced by over 70% of participants expressing agreement or strong agreement on the Likert scale. These findings highlight AI's potential in preserving and promoting local folklore in a global context. Future research can enhance design comprehensiveness with engaging, interactive visuals through platforms like Storynest.ai, fostering deeper emotional connections with readers through richer character portrayals.
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DOI: http://dx.doi.org/10.30659/e.10.1.120-139
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