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All Journal Journal of Artificial Intelligence in Education & Learning Innovation (JAIELI)
Kim Silva
College of Education, Mindanao State University-General Santos
Computer Science & IT Education Languange, Linguistic, Communication & Media Mathematics

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Assessing academic integrity patterns among pre-service teachers using AI-based plagiarism detection Irish Arroyo; Sittie Nor Aisha Rusiana; Daniere Maryje Tabada; Kim Silva; Carla Marie Rubio; Esmeraldo Sarad; Cathy Mae Toquero
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 very high level of academic integrity in their book reviews, scoring 97% or interpreted as students committing 3% 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.
Themes and values in pre-service teachers’ digital storybooks: A content analysis for elementary English education Najma Macatanto; Desiery Maghinay; John Dale Pendon; Carla Marie Rubio; Esmeraldo Sarad; Kim Silva
Journal of Artificial Intelligence in Education & Learning Innovation Vol. 2 No. 1 (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.v2i1.701

Abstract

Background: Digital storytelling has emerged as an innovative pedagogical approach that promotes meaningful learning experiences and enhances student engagement. Objectives: This study examined the themes and values embedded in digital storybooks created by pre-service teachers and explored their implications for teaching English in elementary education. Methods: Using a qualitative content analysis design, ten digital storybooks were purposively selected based on predetermined inclusion criteria. Data were analyzed through directed content analysis using an adapted thematic analysis framework. Results: Findings revealed nine major themes. The most prominent were exploration-related themes (3 out of 10 storybooks, 30%) and family-sharing themes (3 out of 10 storybooks, 30%), followed by community-oriented themes (2 out of 10 storybooks, 20%). Other themes included parent-child communication and financial responsibility. The digital storybooks also embodied core values such as respect, compassion, humility, responsibility, tolerance, forgiveness, and commitment to the common good. Conclusions: These findings suggest that digital storybooks can serve as effective resources for integrating language development, values education, and socio-emotional learning in elementary English classrooms. The study is limited by its small sample size and context-specific dataset. Further research should include a larger dataset and cross-cultural analysis to strengthen the generalizability of findings.
Co-Authors Carla Marie Rubio Cathy Mae Toquero Daniere Maryje Tabada Desiery Maghinay Esmeraldo Sarad Irish Arroyo John Dale Pendon Najma Macatanto Sittie Nor Aisha Rusiana