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Current STEAM and Education Research
Published by PT Mitra Jurnal Indonesia
ISSN : -     EISSN : 30258529     DOI : https://doi.org/10.58797/cser
Core Subject : Science, Education, Art,
Arts Chemistry Computer Science & IT Education Physics
This journal serves as an interdisciplinary publication with the aim of promoting cutting-edge research in the fields of science, technology, engineering, art, mathematics, and education. With a focus on various disciplines, this journal provides a significant platform for researchers, scientists, and educators to share their latest findings in an effort to advance our understanding of various aspects of life. The journal, titled "Current STEAM and Education Research," presents articles that cover a wide range of topics, including innovations in science and technology, recent developments in engineering, creative explorations in the arts, mathematical problem-solving, as well as research and development in the field of education. The articles in this journal also support an educational approach centered on students and emphasize the application of STEAM (Science, Technology, Engineering, Art, and Mathematics) concepts in the learning process. This journal serves as a valuable resource for practitioners, policymakers, and academics who are interested in gaining insights across various fields of knowledge and understanding ways to improve education and society through research and development. With its interdisciplinary focus, this journal facilitates dialogue among different fields of study and encourages collaborations that can have a positive impact on global problem-solving.
Arjuna Subject : Ilmu Sosial - Pendidikan
Articles 64 Documents
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Augmented Reality-Assisted Multiliteracy Learning and Reading Comprehension among Students Monica Syafitri; Nurita Bayu Kusmayusi; Edi Puryanto
Current STEAM and Education Research Vol. 4 No. 2 (2026): Current STEAM and Education Research, Volume 4 Issue 2, August 2026
Publisher : MJI Publisher by PT Mitra Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58797/cser.040203

Abstract

Reading lessons now include more than printed words. Students often need to connect text with visual and digital information. We examined reading comprehension in a Grade 7th class that used a multiliteracy model supported by augmented reality (AR). We used a quasi-experimental nonequivalent control group pretest-posttest design. Sixty students from one of public school in Jakarta took part. Thirty students learned with the AR-assisted multiliteracy model, and 30 students received regular text-based instruction. We used a reading comprehension test and analyzed the scores with descriptive statistics, paired-samples t-tests, direct group comparisons, and Hedges’ g. Both groups improved from pretest to posttest (p < .001). The control group gained 11.97 points, while the experimental group gained 17.20 points. The experimental group also had a higher posttest mean, t(58) = 4.10, p < .001. The standardized posttest difference was large (Hedges’ g = 1.04). The results show that AR can support reading when teachers use it as part of a clear multiliteracy lesson. AR supported meaning making by presenting visual and contextual information alongside the text. It complemented reading activities without replacing them.
Digitalizing Scholarly Communication: Development and Functional Validation of a Web-Based Scientific Conference Management System Pandu Wicaksono; Nur Aziezah; Walidatush Sholihah
Current STEAM and Education Research Vol. 4 No. 2 (2026): Current STEAM and Education Research, Volume 4 Issue 2, August 2026
Publisher : MJI Publisher by PT Mitra Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58797/cser.040202

Abstract

This study developed a standalone web-based system for managing scientific conferences, with a focus on manuscript submission and peer review. The work used the Waterfall model. Development moved through requirements analysis, system design, implementation, and functional validation. The requirements analysis identified four user roles: admin, reviewer, author, and guest. It also defined the main functions needed for manuscript submission, verification, reviewer assignment, review and feedback, status monitoring, and Letter of Acceptance (LoA) issuance. The system used separate frontend and backend components. Vue.js was used for the frontend, Laravel for the backend, and MySQL for the database. The components communicated through a JSON-based RESTful API. Functional validation was carried out with scenario-based black-box testing to check whether each function met its stated requirement without examining the source code. In total, 59 test scenarios were run. Every scenario produced the expected output, giving a 100% functional conformity rate. The results show that the system can perform the defined conference management functions within one digital platform for manuscript submission and peer review. It therefore provides a technical basis for a more structured process of research dissemination and scholarly communication. Further work is still needed to evaluate usability, performance, accessibility, security, and user satisfaction before its broader effectiveness can be assessed.
A Subject-Independent Comparison of EEGNet and CSP+LDA on EEGMMIDB: Implications for Assistive Educational Technology Nur Aziezah; Fajar Nur Hamzah; Walidatush Sholihah
Current STEAM and Education Research Vol. 4 No. 1 (2026): Current STEAM and Education Research, Volume 4 Issue 1, April 2026
Publisher : MJI Publisher by PT Mitra Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58797/cser.040104

Abstract

Motor imagery (MI) electroencephalography (EEG) classification remains difficult in cross-subject settings because signals vary substantially between individuals. This study compares a compact deep learning model (EEGNet) with a classical Common Spatial Pattern and Linear Discriminant Analysis pipeline (CSP+LDA) for hands-versus-feet MI classification. Data came from the EEG Motor Movement/Imagery Dataset (EEGMMIDB) on PhysioNet. A leave-one-subject-out (LOSO) evaluation was conducted across 109 subjects using runs 6, 10, and 14. Preprocessing applied a 7-30 Hz band-pass filter, a 1-2 s post-cue window, and subject-wise z-score normalization. Because normalization used unlabeled statistics from each held-out subject, the setting is LOSO with unsupervised test-time normalization rather than a fully inductive calibration-free protocol. EEGNet reached a mean balanced accuracy of 0.660 ± 0.136 (macro-F1 0.640 ± 0.147; Cohen’s kappa 0.312 ± 0.271), whereas CSP+LDA reached 0.635 ± 0.141 (macro-F1 0.605 ± 0.164; kappa 0.270 ± 0.281). A descriptive paired comparison showed that EEGNet scored higher for 60 of 109 subjects, CSP+LDA scored higher for 47 subjects, and 2 subjects were tied. The aggregated EEGNet confusion matrix showed higher recall for hands than for feet (0.735 vs 0.574), and balanced accuracy varied widely across subjects. These results provide a reproducible subject-independent comparison on EEGMMIDB and show that inter-subject variability remains a major barrier to robust MI decoding. The reproducible pipeline also offers a practical neuroinformatics case for teaching biosignal preprocessing, leakage-aware validation, and model comparison, while the subject-level variability shows what must be addressed before assistive educational deployment.
IoT and Edge AI for Quail Environmental Monitoring and Stress-Related Behaviour Classification Inna Novianty; Ahmad Fauzan; Daffa Ardyana Eka Putra; Muhammad Fadhil Al Faruq; Muhammad Faza Elrahman; Radyanka Irza Pramono; Raqhim Putra Al Rusdi; Zulvian Hardhan; Lathifunnisa Fathonah; Faldiena Marcelita; Gema Parasti Mindara; Shelvie Nidya Neyman
Current STEAM and Education Research Vol. 4 No. 1 (2026): Current STEAM and Education Research, Volume 4 Issue 1, April 2026
Publisher : MJI Publisher by PT Mitra Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58797/cser.040105

Abstract

Temperature and humidity readings can show changes inside a quail cage, but they do not tell us how the birds are responding to those conditions. This study developed a low-cost monitoring system that combines environmental sensing with image-based analysis of quail behaviour. A DHT22 sensor measured cage temperature and humidity, while an ESP32 collected and transmitted the readings. A Raspberry Pi 4 processed images captured by a USB camera and ran a Convolutional Neural Network (CNN) based on MobileNet to classify quail behaviour into three operational categories: Normal, Stress, and Aggressive. Environmental readings and classification results were sent through MQTT, stored in a MySQL database, and displayed together on a web dashboard. The system also generated an alert when an abnormal condition was detected. In five comparisons with reference instruments, the DHT22 showed average errors of 0.36% for temperature and 0.38% for humidity. The MobileNet model reached an aggregate validation accuracy of 91.3% on 1,200 labelled images. The average time from image capture to alert delivery was 4.7 seconds. These results show that environmental data and behavioural classification can be processed together on a Raspberry Pi-based platform under the tested conditions. The system was developed for quail monitoring, but its combination of sensors, real-time data, IoT communication, and image classification could also be used as a practical context for interdisciplinary learning.

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