Statistical literacy is crucial for educators as it enables them to analyze data, make informed decisions, and create evidence-based learning environments. However, many teacher-education students struggle to apply advanced statistical reasoning. This study assessed graduate students’ statistical, research, and AI literacy profiles and identified predictors of statistical literacy. It measured statistical literacy through descriptive and inferential skills, research literacy via awareness, attitude, skills, and application, and AI literacy across affective, behavioral, cognitive, and ethical domains. Using a descriptive-predictive design, the study analyzed data from 42 graduate students enrolled in the MAT, MAED, and MST programs at Saint Mary’s University during the 2024–2025 academic year. Results showed that students were proficient in descriptive statistics but faced challenges with inferential reasoning. Research literacy was at an average level, with weaknesses in conducting and disseminating research, while AI literacy reflected positive attitudes but limited ethical understanding and advanced engagement. Regression analysis revealed no significant impact of research or AI literacy on statistical literacy. The study concludes that improving statistical understanding requires active learning strategies, integration of statistical software, and real-world applications. It recommends embedding AI and research literacy training into teacher education curricula to boost future educators’ ability to make data-driven decisions.

Authors:
Melanie Serquiña, Saint Mary’s University, Philippines
Melanie Gurat, Saint Mary’s University, Philippines

About the Presenter(s)
Ms Melanie Serquiña is a research coordinator, college instructor and testing coordinator at Aldersgate College Inc. in Solano Nueva Vizcaya Philippines

See this presentation on the full schedule – Friday Schedule

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