Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal Aktual : Jurnal Pengabdian Kepada Masyarakat Journal of Educational Technology and Learning Creativity
M. Esad Kuloğlu
Abdullah Gül University
Computer Science & IT Education Engineering Environmental Science Public Health

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Human-AI Collaboration in Scientific Writing Training: A Quantitative Evaluation of Learning Effectiveness and Academic Integrity Eko Risdianto; Nanik Setyowati; Mohammad Qaiz Rezvani; M. Abdul Jamal; Mageswaran Sanmugam; M. Esad Kuloğlu
Aktual: Jurnal Pengabdian Kepada Masyarakat Vol. 4 No. 2 (2026): Aktual: Jurnal Pengabdian Kepada Masyarakat
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/aktual.v4i2.728

Abstract

Background: The rapid advancement of Artificial Intelligence (AI) has significantly transformed academic writing practices, offering both opportunities and ethical challenges, particularly related to plagiarism and over-reliance on automated tools.Objectives: This study aims to evaluate the effectiveness of AI-assisted scientific writing training in enhancing participants’ writing skills, academic integrity awareness, and writing efficiency through a Human-AI Collaboration approach.Methods: A quantitative descriptive method was employed using a structured questionnaire consisting of 20 Likert-scale items administered to 85 participants. The instrument measured five dimensions: relevance and conceptual understanding, instructional quality, writing skill improvement, academic integrity awareness, and perceived impact. Data were analyzed using descriptive statistics, including mean scores and percentage distributions.Results: The findings reveal that the training achieved a very high level of effectiveness, with an overall mean score of 3.59. All variables were categorized as very high, with academic integrity awareness obtaining the highest mean score (3.70), indicating strong improvement in ethical understanding. Writing skill improvement showed relatively lower scores, suggesting the need for continuous practice.Conclusion: AI-assisted scientific writing training based on the Human-AI Collaboration framework is highly effective in improving scientific writing competence and promoting ethical awareness. This approach provides a balanced model integrating technical skills and academic integrity in AI-supported writing practices.
Integrated Virtual Reality Learning Framework with Digital Ecosystem for Enhancing Physics Conceptual Understanding Eko Risdianto; Joselin Santos; Noel Lomerio; Deshinta Arrova Dewi; M. Esad Kuloglu; Sultan Hammad Alshammari; Ressti Nurfitriani
Journal of Educational Technology and Learning Creativity Vol. 4 No. 1 (2026): June
Publisher : Cahaya Ilmu Cendekia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37251/jetlc.v4i1.2955

Abstract

Purpose of the study: This study develops and evaluates an integrated virtual reality learning framework to improve high school students’ physics conceptual understanding. The framework combines immersive 360° virtual reality videos via Kuula with Google Classroom, ClassPoint, digital flipbooks, and PhET simulations within a problem-based learning environment. Methodology: This study employed a research and development approach using the ADDIE model, combined with a pre-experimental one-group pretest–posttest design. The participants consisted of three cohorts of high school students (n = 115) across different physics topics: Kinematics (n = 36), fluids (n = 39), and particle dynamics (n = 40). The framework was validated by three experts using structured instruments assessing content, media, language, and presentation aspects. Data were collected through validation sheets, student response questionnaires, and conceptual understanding tests. Data analysis included percentage-based measures, N-Gain, Shapiro Wilk tests, paired t-tests, Wilcoxon signed rank tests, and effect size calculations. Main Findings: The results indicate high validity (88.89%–97%) and practicality (86%–98%). The implementation was associated with significant improvements in conceptual understanding, reflected in high N-Gain scores (0.81–0.87) and large effect sizes (p < 0.05). These findings suggest that the integrated virtual reality based learning ecosystem can effectively support conceptual understanding within the studied context. Novelty/Originality of this study: The novelty lies in the systematic integration of the Kuula platform within a multi-component digital learning ecosystem under a problem based learning framework, as well as its application across multiple physics topics to demonstrate consistent learning outcomes.
Co-Authors Deshinta Arrova Dewi Eko Risdianto Joselin Santos M. Abdul Jamal Mageswaran Sanmugam Mohammad Qaiz Rezvani Nanik Setyowati Noel Lomerio Ressti Nurfitriani Sultan Hammad Alshammari