Exploring the scientific conceptual understanding of intermediate-grade learners on Earth and Space FAUSTINO, SHARMAINE P., CABRADILLA, JOSEPHINE O., ESTOQUE, GERALDINE S., FLORES, JULIE ANNE C., GENESE, DIONISIA N., et al. Review of Science Mathematics and ICT Education, 2025 This research study aimed to determine the scientific conceptual understanding of Earth and Space Science among intermediate-grade learners at La Union, Philippines. A descriptive research design was utilized for 299 participants (146 males and 153 females; aged 9-12 years old) using a two-tiered multiple-choice type to measure the scientific conceptual understanding of the participants. The two-tiered test was subjected to the Rasch measurement model, which can resolve guessing problems and detect outliers who answer via guessing for reliability and validity. The data results indicated that more students “do not understand the concept” and have “misconceptions”. The study found that the conceptual understanding of the pupils had significant differences in terms of grade level through Kruskal-Wallis H Test. However, a significant difference in conceptual understanding between gender in every grade level was not found using Mann-Whitney U Test. These findings highlight the importance of focusing on building a strong conceptual understanding of science in intermediate grades (4–6) by addressing foundational gaps to master science concepts and succeed
Examining the Potential Benefits and Ethical Risks of GenAI in Lesson Planning: A TAM Approach Vyoana Estocapio, Ruffa Mae Bilog, Jessica Cacananta, Jea Marie Corpuz, Bonny Ibasan Jr., Sheikka Paneda, Raphael Job Asuncion Journal of Teaching and Learning, 2025 Generative Artificial Intelligence (GenAI) is a transformative technology in education, especially in lesson planning (LP). This research examines pre-service teachers' (PSTs) perceptions of GenAI benefits and ethical risks in LP, with consideration for the Technology Acceptance Model (TAM). The findings show that PSTs are generally cognizant of the benefits and ethical ramifications of GenAI use. PSTs demonstrated a positive attitude toward integrating GenAI in lesson planning and recognized the relevance and varying levels of incorporation into their current practice. The data also highlighted that the relationship of key TAM variables influenced how PSTs view and adopt GenAI. The findings provided support for the collect construct of perceived usefulness (PU) and perceived ease of use (PEU) mediating the relationship between attitude (ATT) and use (AU). These findings contributed relevant information to inform teacher education, illustrating the need for training that balances the practical benefits and ethical dimensions of GenAI. This research can serve as a starting point for future research, curricular design, and policy making regarding the responsible and informed use of GenAI in teacher preparation.
Preservice Teachers’ Readiness Towards Integrating AI-Based Tools in Education: A TPACK Approach Angelina Bautista, Christine Estrada, Andrei Melvin Jaravata, Laina Mae Mangaser, Ferdinand Narag, Rachell Soquila, Raphael Job Asuncion Educational Process International Journal, 2024 Background/Purpose – Technological pedagogical content knowledge (TPACK) emphasizes the effective integration of artificial intelligence (AI)-based tools in education, where specific knowledge is measured individually. This research determines the readiness of preservice teachers (PSTs) to integrate AI-based tools in education through the TPACK approach. Materials/Methods – This descriptive study involves 429 PSTs from Don Mariano Marcos Memorial State University in the Philippines through a face-to-face survey. Exploratory factor analysis was employed using a minimum residual extraction method with oblimin rotation. Partial least squares structural equation modeling was performed, and goodness of fit indices (GFI, AGFI, PGFI, RMSEA, and TLI) were tested. Results – The PSTs’ readiness to integrate AI-based tools in education revealed their readiness based on their technical knowledge (TK), technical pedagogical knowledge (TPK), technical content knowledge (TCK), and TPACK, as well as their ethical readiness. The study found that the PSTs’ TK, TPK, TCK, and TPACK were positively related to their ethical readiness. Conclusion – When PSTs enhance their technological competencies, their ethical considerations in the use of AI tools also improve. Relationships between TK, TPK, TCK, TPACK, and ethical readiness emphasize the need for teacher training approaches that nurture not just technical abilities, but also students’ ethical consciousness. This highlights the interconnectedness of these knowledge frameworks in fostering effective and responsible technology integration in education.
