CHATGPT USE AND STUDY HABITS OF FILIPINO LEARNERS

Published: 18 May 2026| Version 1 | DOI: 10.17632/n3z2p2hknv.1
Contributor:
Enrique B Picardal Jr

Description

This study used a qualitative research design with secondary data analysis using documentary analysis and thematic analysis to examine the influence of ChatGPT on learning habits and academic behavior among Filipino students. A qualitative approach is appropriate because the research is focused on understanding patterns in AI-assisted learning, digital academic engagement, and new educational practices that can be found in public documents and scholarly sources. Secondary data was obtained from academic journals, education reports, online publications, policy documents, and authentic digital sources related to artificial intelligence in education from 2023 to 2026. Documentary analysis was used to systematically review and interpret relevant written materials, while thematic analysis was used to identify recurring themes and patterns regarding learning strategies, learning skills, critical thinking, academic confidence, and digital learning experiences. This research design allows for a focus on generating comprehensive insights about the educational implications of using ChatGPT among Filipino students without direct interaction with human participants.

Files

Steps to reproduce

The study followed a systematic qualitative secondary data analysis procedure to ensure transparency and replicability. First, the researcher defined the scope of the study focusing on social media anxiety among Filipino youth from 2023 to 2026. A structured search strategy was then conducted across academic databases, peer-reviewed journals, government reports, mental health publications, and credible online sources using keywords such as “social media anxiety,” “Filipino youth mental health,” “fear of missing out (FOMO),” “social comparison,” and “digital stress.” A purposive inclusion and exclusion protocol was applied, selecting only publicly available, credible, and relevant materials while excluding non-academic, duplicate, and outdated sources. All collected data were organized using spreadsheet and document-based software for systematic coding and reference tracking. The analysis process involved thematic coding, where recurring ideas were identified and grouped into key themes such as social comparison, peer validation, emotional stress, self-esteem, and fear of missing out, followed by interpretative synthesis to examine relationships among themes. No surveys, interviews, or laboratory instruments were used, as the study relied entirely on documentary evidence, and all procedures were documented to ensure consistency and reproducibility.

Institutions

Categories

Artificial Intelligence, Assistive Technology, Digital Communication, ChatGPT

Licence