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The future of teaching: Analyzing the interplay between AI literacy and TPACK among BEED pre-service teachers
Karl Alvin Aglibot1, Chelsea Lorraine Rito2, Larence Villalon3, Nelvin Gampal 41. Mindanao State University - General Santos , PH2. Mindanao State University – General Santos , PH3. Mindanao State University – General Santos , PH4. Mindanao State University – General Santos , PH2025-10-08|page 50-65AbstractBackground: As artificial intelligence (AI) continues transforming the educational landscape, pre-service teachers must develop theoretical understanding and practical skills in AI integration.
Objectives: This study explored the relationship between AI literacy and TPACK among 139 BEED pre-service teachers.
Methods: Using descriptive statistics, Spearman's correlation, and multiple linear regression analysis, the study investigated how components of AI literacy relate to TPACK.
Results: Results revealed that the pre-service teachers demonstrated high levels of AI literacy, particularly in ethical awareness and intrinsic motivation. Pre-service teachers expressed strong interest in AI's educational potential and a commitment to its responsible use. While their foundational AI knowledge was high, many reported moderate self-efficacy and lacked confidence in executing AI-related tasks. Gaps were also noted in applying AI concepts to real-world teaching scenarios and designing AI-driven solutions. Furthermore, the results showed high TPACK proficiency, with strength in pedagogical and technological knowledge, though weaknesses were observed in content areas like mathematics and technical troubleshooting. A moderate positive correlation (Spearman's ρ = 0.48, p < 0.05) between AI literacy and TPACK indicates a meaningful association. Regression analysis revealed that AI literacy components explained 25.5% of the variance in TPACK. Cognitive learning emerged as the only significant predictor.
Conclusions: The findings underscore the need for teacher education programs to provide hands-on, cognitive-focused AI training. Hence, enhancing pre-service teachers' cognitive and practical skills is essential to thoroughly preparing them for AI-enhanced teaching environments' demands.
APA Citation StyleAglibot, K. A. , Rito, C. L. , Villalon, L. , & Gampal , N. (2025). The future of teaching: Analyzing the interplay between AI literacy and TPACK among BEED pre-service teachers. Journal of Artificial Intelligence in Education & Learning Innovation, 50-65. https://doi.org/10.56003/jaieli.v1i1.570 -
Academic goals and learning strategies of pre-service teachers during emergency online learning in the Philippines
Swen Joshryll Acebes1, Jaizel Malitante2, Nikki Tuble3, Rowena Bongolto41. Mindanao State University - General Santos , PH2. Mindanao State University - General Santos , PH3. Mindanao State University - General Santos , PH4. Mindanao State University - General Santos , PH2025-10-08|page 32-49AbstractBackground: The COVID-19 pandemic has lasted an extended period, during which many students have reported being adversely affected by the escalating global crisis.
Objectives: This study examined the academic goals, learning barriers, facilitative strategies, and ways forward of pre-service teachers during emergency online learning.
Methods: This qualitative case study employed content analysis to examine data gathered through focus group discussions. To explore the implications of survey findings and gain deeper insights into students' perspectives on remote learning, the researchers conducted Focus Group Discussions (FGDs) with twelve purposively selected pre-service teachers via Google Meet. The discussion transcripts were analyzed to construct a compelling narrative, supported by literature and prior research, to explain emerging themes.
Results: Among the twelve participants, ten reported experiencing psychosocial stress, eight cited recurring technical issues, and seven mentioned financial constraints as significant learning barriers. Despite these challenges, the participants remained motivated to complete their coursework, viewing academic achievement as a stepping stone toward improving their socio-economic conditions. They employed various strategies, including scheduling, note-taking, goal-setting, optimistic thinking, parental scaffolding, and systematic planning, to adapt to online learning. To ensure credibility, the researchers used member checking, peer debriefing, and FGD and survey data triangulation.
Conclusions: These findings highlight the resilience and adaptability of pre-service teachers in navigating the challenges of emergency online learning, underscoring the need for supportive institutional policies and resources. Future research may consider comparing student experiences in public and private institutions or examining the long-term impact of emergency remote learning on teaching efficacy. Pedagogical and academic implications are further discussed.
APA Citation StyleAcebes, S. J. , Malitante, J. , Tuble, N. , & Bongolto, R. (2025). Academic goals and learning strategies of pre-service teachers during emergency online learning in the Philippines. Journal of Artificial Intelligence in Education & Learning Innovation, 32-49. https://doi.org/10.56003/jaieli.v1i1.569 -
Themes and values in pre-service teachers’ digital storybooks: A content analysis for elementary English education
Najma Macatanto1, Desiery Maghinay2, John Dale Pendon3, Carla Marie Rubio4, Esmeraldo Sarad5, Kim Silva61. College of Education, Mindanao State University-General Santos , PH2. College of Education, Mindanao State University-General Santos , PH3. College of Education, Mindanao State University-General Santos , PH4. College of Education, Mindanao State University-General Santos , PH5. College of Education, Mindanao State University-General Santos , PH6. College of Education, Mindanao State University-General Santos , PH2026-07-02|page 32-43AbstractBackground: 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.
APA Citation StyleMacatanto, N. , Maghinay, D. , Pendon, J. D. , Rubio, C. M. , Sarad, E. , & Silva, K. (2026). Themes and values in pre-service teachers’ digital storybooks: A content analysis for elementary English education. Journal of Artificial Intelligence in Education & Learning Innovation, 32-43. https://doi.org/10.56003/jaieli.v2i1.701 -
Assessing academic integrity patterns among pre-service teachers using AI-based plagiarism detection
Irish Arroyo1, Sittie Nor Aisha Rusiana2, Daniere Maryje Tabada3, Kim Silva4, Carla Marie Rubio5, Esmeraldo Sarad6, Cathy Mae Toquero71. College of Education, Mindanao State University-General Santos , PH2. College of Education, Mindanao State University-General Santos , PH3. College of Education, Mindanao State University-General Santos , PH4. College of Education, Mindanao State University-General Santos , PH5. College of Education, Mindanao State University-General Santos , PH6. College of Education, Mindanao State University-General Santos , PH7. Faculty of Psychology, Malang State University , ID2026-04-06|page 148-163AbstractBackground: 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.
APA Citation StyleArroyo, I. , Rusiana, S. N. A. , Tabada, D. M. , Silva, K. , Rubio, C. M. , Sarad, E. , & Toquero, C. M. (2026). Assessing academic integrity patterns among pre-service teachers using AI-based plagiarism detection. Journal of Artificial Intelligence in Education & Learning Innovation, 148-163. https://doi.org/10.56003/jaieli.v1i2.685 -
Artificial intelligence-supported motor skill performance in physical education and sport: A systematic review and meta-analysis informed by motor learning theory
Yulingga Nanda Hanief1, Vera Septi Sistiasih2, Ferdinando Cereda3, Spyridon Plakias41. Department of Sport Education, Faculty of Sports Science, Universitas Negeri Semarang , ID2. Department of Sport Education, Faculty of Sports Science, Universitas Negeri Semarang , ID3. Department of Education, The Catholic University of the Sacred Heart in Milan, Italy , IT4. Department of Physical Education and Sport Science, University of Thessaly , GR2026-08-30|page 44-71AbstractBackground: Artificial Intelligence (AI) has increasingly been integrated into physical education (PE) to support motor learning through technologies such as computer vision, motion tracking, intelligent tutoring systems, virtual reality, and generative AI. However, evidence regarding its effectiveness remains fragmented across different intervention types and learning contexts.
Objectives: This study aimed to evaluate the effects of AI-supported interventions on motor skill performance in physical education and sport settings and to synthesize complementary learning-related outcomes.
Methods: A systematic review and meta-analysis were conducted in accordance with PRISMA 2020. Scopus, PubMed, and ProQuest were searched through 22 June 2026. Eligible studies evaluated AI-supported, adaptive, or intelligent interventions in physical education, sport, or motor skill-learning contexts and reported learner-level motor performance; complementary learning-related outcomes were synthesized narratively. Risk of bias was assessed using RoB 2 and ROBINS-I, and standardized mean differences (SMDs) with 95% confidence intervals (CIs) were synthesized using a random-effects model.
Results: Fifteen studies were included in the qualitative synthesis; six contributed to the meta-analysis and nine were synthesized narratively. The pooled estimate favored the designated AI-supported experimental conditions over their comparators (SMD = 3.15, 95% CI 1.86–4.44; p < .001; I² = 98%). Given the small evidence base, very high heterogeneity, and variable risk of bias, the magnitude of this pooled effect is uncertain. Qualitative findings concerned short-term motor skill performance and complementary outcomes such as engagement, motivation, learning interest, and self-directed learning.
Conclusions: AI-supported interventions may improve short-term motor skill performance in some physical education and sport contexts and may support complementary learning-related outcomes. However, the evidence is preliminary and highly heterogeneous, and immediate post-intervention performance should not be interpreted as definitive evidence of durable motor learning, retention, or transfer. AI should be considered a complementary pedagogical tool rather than a replacement for teacher or coach expertise.
APA Citation StyleHanief, Y. N. , Sistiasih, V. S. , Cereda, F. , & Plakias, S. (2026). Artificial intelligence-supported motor skill performance in physical education and sport: A systematic review and meta-analysis informed by motor learning theory. Journal of Artificial Intelligence in Education & Learning Innovation, 44-71. https://doi.org/10.56003/jaieli.v2i1.753 -
AI-driven learning in physical education: A bibliometric analysis of trends, knowledge structure, and future research directions
Amelia Larassary11. State Junior High School 1 Bunguran Tengah, Natuna Regency, Riau Islands , ID2026-04-06|page 102-118AbstractBackground: Although research on AI-driven learning in PE has expanded rapidly, existing studies remain fragmented across disciplines, journals, and methodological approaches, limiting a comprehensive understanding of the field's development and intellectual structure.
Objectives: This study aimed to systematically map the evolution, influential contributors, intellectual structure, dominant themes, and future research directions of AI-driven learning research in physical education from a bibliometric perspective.
Methods: A quantitative bibliometric analysis was conducted using data retrieved exclusively from the Scopus database. A total of 284 eligible documents published between 2020 and early 2026 were analyzed. Descriptive statistics were applied to examine publication trends, authorship, sources, institutions, and country contributions. Network and thematic analyses were performed using VOSviewer (version 1.6.20) and the Bibliometrix package in R to identify co-authorship patterns, keyword co-occurrence networks, and thematic clusters.
Results: The results indicate a sharp growth in AI-driven learning research in physical education after 2022, with publication output increasing more than fivefold from 2020 to 2025. China emerged as the leading contributing country, accounting for nearly half of the total publications, while institutional productivity was concentrated in several Russian universities. Keyword co-occurrence analysis revealed five major thematic clusters shaping the intellectual structure of the field, integrating pedagogical frameworks, computational intelligence, institutional contexts, and physical training models. Dominant research themes centered on pedagogical design, student engagement, adaptive learning systems, and the integration of educational technology. Emerging themes included virtual reality, advanced machine learning techniques, and immersive learning environments.
Conclusions: This study provides a structured and quantitative overview of AI-driven learning research in physical education, highlighting its interdisciplinary nature and rapid expansion.APA Citation StyleLarassary, A. (2026). AI-driven learning in physical education: A bibliometric analysis of trends, knowledge structure, and future research directions. Journal of Artificial Intelligence in Education & Learning Innovation, 102-118. https://doi.org/10.56003/jaieli.v1i2.673 -
Navigating the infodemic through social media: A qualitative case study of Filipino university students’ learning experiences during the COVID-19 polycrisis
Janel Talaman1, Mc Denver Necosia2, Larence Villalon3, Edrian Mark Tomines41. Mindanao State University – General Santos , PH2. Mindanao State University – General Santos , PH3. Mindanao State University – General Santos , PH4. Mindanao State University - General Santos , PH2026-04-06|page 119-134AbstractBackground: The COVID-19 pandemic has triggered a complex crisis in higher education that has not only disrupted formal learning but also given rise to an infodemic through the rapid spread of misinformation on digital platforms, making social media both a source of learning and a source of epistemic risk for students.
Objectives: This study aims to explore how Filipino university students navigated learning experiences through social media during the COVID-19 polycrisis, focusing on preferred platforms, perceived educational relevance, and strategies for evaluating information credibility amid an infodemic.
Methods: A qualitative case study design was employed. Six Filipino university students enrolled in a Bachelor of Elementary Education program participated in this study through purposive sampling. Data were collected via online semi-structured interviews, group chat discussions, document analysis of shared social media content, and follow-up interviews. Thematic analysis was conducted following Braun and Clarke's framework to identify recurring patterns across data sources.
Results: Findings reveal that social media—particularly Facebook—served as a supplementary learning space, enabling students to access real-time information, engage with societal issues, and sustain their learning during the suspension of formal instruction. Students demonstrated active information-seeking behaviors, including cross-checking sources and exercising caution in sharing content. However, persistent exposure to misinformation highlighted their vulnerability within infodemic environments, especially in the absence of structured institutional guidance.
Conclusions: Social media can support authentic and socially relevant learning during educational disruption, but its pedagogical value depends on students' critical and digital literacy capacities.APA Citation StyleTalaman, J. , Necosia, M. D. , Villalon, L. , & Tomines, E. M. (2026). Navigating the infodemic through social media: A qualitative case study of Filipino university students’ learning experiences during the COVID-19 polycrisis. Journal of Artificial Intelligence in Education & Learning Innovation, 119-134. https://doi.org/10.56003/jaieli.v1i2.571
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