ChatGPT in STEM Classrooms: Students’ Perceptions of Interest, Academic Proficiency, and Learning Independence

Purpose of the study: To provide K-12 evidence from a low- and middle-income context, this study examines how basic education STEM students use ChatGPT and how it relates to their interest, academic proficiency, and learning independence. Methodology: Design: descriptive cross-sectional survey in one large public school. Participants: 186 Grade 11–12 STEM students. Instrument: 17-item researcher-developed questionnaire, administered online during class. Tool: ChatGPT (OpenAI). Analysis: item-level frequencies and percentages; reliability and validity checks treated as supportive for a heterogeneous instrument. Main Findings: ChatGPT use was episodic and concentrated in Research and English. Students reported greater engagement, clearer understanding, and shorter assignment time. Independence gains were modest; textbook reliance declined while tutoring reliance was largely stable. Governance practices were common, including verification and paraphrase-synthesis or inspirational use. Older students emphasized efficiency and integration; younger students reported larger conceptual gains. Novelty/Originality of this study: This study contributes classroom-proximate, item-level evidence from Philippine basic education, an underrepresented K-12 setting. It characterizes selective, front-end deployment and widespread verification, offering rubric-ready handles for responsible use. It identifies grade-linked orchestration differences and connectivity-aware implications that can guide targeted scaffolds to translate efficiency into competence and independent learning.

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Publication Details

Journal
Journal of Basic Education Research
Published
2025-09-28
DOI
https://doi.org/10.37251/jber.v6i3.2096
Citations
1
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
1.69
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article

ChatGPT in STEM Classrooms: Students’ Perceptions of Interest, Academic Proficiency, and Learning Independence

Aaron A. Funa, Renz Alvin E. Gabay, Dave Diaz
1 citations
Journal of Basic Education Research
Online Learning and Analytics
1.69
article

ChatGPT in STEM Classrooms: Students’ Perceptions of Interest, Academic Proficiency, and Learning Independence

Aaron A. Funa, Renz Alvin E. Gabay, Dave Diaz
article en
1 citations

Abstract

Purpose of the study: To provide K-12 evidence from a low- and middle-income context, this study examines how basic education STEM students use ChatGPT and how it relates to their interest, academic proficiency, and learning independence. Methodology: Design: descriptive cross-sectional survey in one large public school. Participants: 186 Grade 11–12 STEM students. Instrument: 17-item researcher-developed questionnaire, administered online during class. Tool: ChatGPT (OpenAI). Analysis: item-level frequencies and percentages; reliability and validity checks treated as supportive for a heterogeneous instrument. Main Findings: ChatGPT use was episodic and concentrated in Research and English. Students reported greater engagement, clearer understanding, and shorter assignment time. Independence gains were modest; textbook reliance declined while tutoring reliance was largely stable. Governance practices were common, including verification and paraphrase-synthesis or inspirational use. Older students emphasized efficiency and integration; younger students reported larger conceptual gains. Novelty/Originality of this study: This study contributes classroom-proximate, item-level evidence from Philippine basic education, an underrepresented K-12 setting. It characterizes selective, front-end deployment and widespread verification, offering rubric-ready handles for responsible use. It identifies grade-linked orchestration differences and connectivity-aware implications that can guide targeted scaffolds to translate efficiency into competence and independent learning.

Journal of Basic Education ResearchVol. 6(3)
Sorsogon State University (PH)
Openalex Percentile: Top 10%
Online Learning and Analytics
1.69
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