Journal of Educational Studies in Science, Technology, Engineering, Arts and Humanities
STEM Education: Curriculum and pedagogical innovations in science, technology, engineering, and mathematics across formal and informal settings. STEAM Integration: Approaches that incorporate arts and humanities to enrich STEM learning and enhance creativity, communication, and critical reflection. Educational Technology & Design Thinking: Engineering design, maker culture, and technology-enhanced learning in classrooms, workshops, and community environments. Equity, Inclusion, and Access: Research addressing inclusive practices in STEM, arts, and humanities, including learners with special needs and under-represented groups. Methodological Advances: Quantitative, qualitative, mixed-methods, design-based research, and action research in multidisciplinary educational studies. Humanities & Cultural Dimensions: Ethics in engineering education, socio-cultural factors in technology learning, and history/philosophy of science education. Project-Based & Experiential Learning: Maker spaces, innovation labs, and capstone projects, including implementation and evaluation in schools, higher education, and lifelong learning. Policy, Leadership, and Institutional Change: Governance and strategic initiatives that connect STEM, arts, and humanities to address societal challenges (e.g., sustainability, digital transformation, globalization).
Articles
12 Documents
<![CDATA[Achievement of National Education Standards as an Indicator of School Quality ]]>
<![CDATA[Artia Sihombing]]>;
<![CDATA[Gressya Pebriani Agatha Tamba]]>;
<![CDATA[Kristi Debora Siagian]]>
<![CDATA[ Journal of Educational Studies in Science, Technology, Engineering, Arts and Humanities Vol.1 No.2 (2026): March 2026 ]]>
Publisher : <![CDATA[PT. Global Research Collaboration ]]>
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<![CDATA[One important indicator for evaluating the quality of education in Indonesia is the Achievement of the National Education Standards (SNP). Each educational unit must meet various aspects of the SNP, including the curriculum, the learning process, and evaluation results. This research aims to analyze the relationship between the achievement of the National Education Standards (SNP) and school quality, as well as its impact on student learning outcomes. Using quantitative methods, data were collected from several schools in various regions, including national exam results, graduation rates, and other relevant indicators. The research results indicate that there is a significant positive correlation between SNP achievement and the quality of education perceived by students and parents. Learning outcomes and community satisfaction levels are higher in schools that successfully meet the standards. These findings indicate that SNP can be an effective tool for improving the quality of education in Indonesia if implemented regularly. It is hoped that this research will provide recommendations for policymakers and education practitioners to improve school quality by adhering to the established educational standards.]]>
<![CDATA[Implementation of a Gel Electrophoresis Image Analysis System ]]>
<![CDATA[Kittiphat Kaewchimplee]]>;
<![CDATA[Chaturawit Bunkaeokrut]]>;
<![CDATA[Sitthichot Somthong]]>;
<![CDATA[Supphawet Tipphayut]]>;
<![CDATA[Boonchat Mekkaeo]]>
<![CDATA[ Journal of Educational Studies in Science, Technology, Engineering, Arts and Humanities Vol.1 No.2 (2026): March 2026 ]]>
Publisher : <![CDATA[PT. Global Research Collaboration ]]>
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DOI: 10.66314/jesteah.v1i2.941
<![CDATA[This study developed a gel electrophoresis image analysis system using digital image processing and the Structural Similarity Index (SSIM) to improve interpretative accuracy and reduce analysis time. Traditional laboratory methods often rely on subjective human observation, which can lead to significant diagnostic errors. The system, implemented in Python, streamlines the research workflow from image import and enhancement to band-intensity pattern analysis and automated lane comparison. Performance was evaluated using 10 standardized gel images, with results compared against a group of 15 students and domain experts (gold standard). The system achieved an average lane-detection accuracy of 80.00%, closely matching expert performance and significantly outperforming the student group (36.01%). Furthermore, the average analysis time was 14.96 seconds per image, approximately 3–4 times faster than manual interpretation. However, certain limitations were observed during testing, particularly a reduction in performance when analyzing images with excessive noise or poor band clarity, which occasionally affected lane detection and similarity assessment accuracy. Beyond laboratory efficiency, the system serves as an effective educational tool for high school students in biology and introductory bioinformatics education, reducing the barrier to entry for image analysis and computational biology concepts through an intuitive, low-cost interface. These findings demonstrate that the system enhances accuracy, speed, and consistency, offering a robust, scalable, and practical solution for both professional biological laboratories and modern science education.]]>
