Quantifying NSHS Students’ Engagement: Assessing the Efficacy of Language Model Generative AI in Educational Research

The study, “Quantifying NSHS Engagement: Assessing the Efficacy of Language Model Generative AI in Educational Research,” seeks to determine the link between students’ Behavioral, Emotional, Cognitive, and Social engagement and exposure to ChatGPT. Bard, and Grammarly. Moreover, it aims to provide information about the efficacy of AI technology. A correlational research design measures students' engagement level toward Language Model Generative AI (LMGAI). It identifies the relationship between students’ engagement and exposure to Language Model Generative AI (LMGAI) in educational research without causation. This study covers one hundred (100) Noveleta Senior High School students. Researchers used a heuristic method for correlational study to select the number of participants. Samples are drawn from populations that utilized Language Model Generative AI in their research regardless of age, grade level, and gender. The researchers employed a non-random purposive sampling technique. Based on the study's findings, the student’s behavioral, emotional, cognitive, and social engagement is at mid-level with an average mean of (x?=3.04). Moreover, their exposure to ChatGPT, Bard, and Grammarly is at mid-level with an average mean of (x?=2.87). Finally, using the Spearman Correlation Correlation Coefficient, the researchers found a “very strong positive relationship” between students’ behavioral, emotional, cognitive, and social engagement and ChatGPT, Bard, and Grammarly.