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p-Index From 2021 - 2026
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All Journal Journal of Artificial Intelligence in Education & Learning Innovation (JAIELI)
Sarad, Esmeraldo
Unknown Affiliation
Computer Science & IT Education Languange, Linguistic, Communication & Media Mathematics

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Using children’s digital picture books to teach disease preventive behaviors: A visual analysis of the Duma Says series Sarad, Esmeraldo; Cabatuan, Charmen; Tionson, Cleo; Subong, April Grace
Journal of Artificial Intelligence in Education & Learning Innovation Vol. 1 No. 2 (2026): Journal of Artificial Intelligence in Education & Learning Innovation
Publisher : CV Rezki Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56003/jaieli.v1i2.572

Abstract

Background: During health emergencies such as the COVID-19 pandemic, children require accessible and developmentally appropriate resources to understand disease prevention and health-related behaviors. Children’s digital picture books have emerged as a promising medium for conveying public health messages through visual storytelling and age-appropriate narratives. Objectives: This study aimed to examine how children’s digital picture books represent disease preventive behaviors and moral values, using the Duma Says series as a case study. Methods: A qualitative visual and textual analysis was conducted on four digital picture books from the Duma Says Collector’s Edition. The study employed qualitative visual analysis and a critical discourse approach to examine representations of hygiene practices, social responsibility, and community engagement embedded in both images and narratives. Results: The findings indicate that the Duma Says series effectively integrates key COVID-19 preventive behaviors—such as handwashing, mask-wearing, social distancing, and sanitation—within child-friendly language and culturally contextualized visuals. In addition to promoting health practices, the books emphasize values of hope, responsibility, cooperation, and service, portraying children as active contributors to community well-being during a crisis. Conclusions: Children’s digital picture books, such as the Duma Says series, function as effective educational tools for promoting disease prevention awareness and values-based learning. Incorporating culturally grounded digital picture books into early childhood and health education may strengthen children’s health literacy, emotional resilience, and sense of social responsibility during public health emergencies.
Assessing academic integrity patterns among pre-service teachers using AI-based plagiarism detection Arroyo, Irish; Rusiana, Sittie Nor Aisha; Tabada, Daniere Maryje; Silva, Kim; Rubio, Carla Marie; Sarad, Esmeraldo; Toquero, Cathy Mae
Journal of Artificial Intelligence in Education & Learning Innovation Vol. 1 No. 2 (2026): Journal of Artificial Intelligence in Education & Learning Innovation
Publisher : CV Rezki Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56003/jaieli.v1i2.685

Abstract

Background: The advent of artificial intelligence has intensified concerns about academic dishonesty among students, particularly in written outputs. Plagiarism, a common form of misconduct, involves using others’ ideas without proper attribution. Objectives: This study aimed to determine the degree and patterns of academic integrity in the pre-service teachers’ book reviews. Methods: Employing a descriptive research design through document analysis, the study used purposive sampling to collect 40 book reviews, applying set inclusion and exclusion criteria. An AI-based plagiarism detection tool, Grammarly, was used to identify instances of plagiarism and assess the level of academic integrity reflected in the outputs. Descriptive statistical methods were applied to examine plagiarism levels across different sections of the book reviews. Results: Results showed that the majority of pre-service teachers demonstrated a moderate level of academic integrity in their book reviews, scoring 82% or interpreted as students committing 15% plagiarism. Furthermore, sectional analysis showed that the introduction and conclusion exhibited higher integrity, while the body contained the most instances of plagiarism. This suggests that students struggled more with sections requiring critical thinking, original insights, and proper citation. Most plagiarism cases were linked to failure to cite sources and unintentional misuse of references. Conclusions: Teacher Education Institutions integrate AI-supported evaluation tools and plagiarism detection systems into instruction and assessment. Embedding academic integrity modules and discussions on AI ethics is also encouraged. Future research should involve larger and more diverse samples and utilize multiple AI detection tools to enhance the reliability and validity of findings through cross-verification.
Co-Authors Arroyo, Irish Cabatuan, Charmen Rubio, Carla Marie Rusiana, Sittie Nor Aisha Silva, Kim Subong, April Grace Tabada, Daniere Maryje Tionson, Cleo Toquero, Cathy Mae