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Peran Dosen Sebagai Korektor dalam Model Human-in-the-Loop (HITL) untuk Meningkatkan Akurasi Evaluasi Pembelajaran Berbasis Artificial Intelligence Abdul Rahman; Brezto Asagi Dewantara
Advances In Education Journal Vol. 2 No. 1 (2025): Advances In Education Journal (Agustus)
Publisher : Yayasan Al-Afif

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Artificial Intelligence (AI)-based learning evaluation is efficient but lacks nuance and risks bias, and the integration of lecturer assessments into the system remains unclear. This study aims to systematically review Human-in-the-Loop (HITL) models to map lecturer roles and measure the impact of their interventions. The study used a literature review of Google Scholar, IEEE, ACM Digital Library, Scopus, dan ERIC databases (2016–2025) with empirical inclusion criteria; 15 studies were analyzed. The results show that while AI improves evaluation efficiency, three lecturer roles initiator, supervisor, and facilitator generally do not directly improve model accuracy. Conversely, the corrector role, which utilizes lecturer feedback for retraining, has the greatest potential for accuracy improvement, but empirical evidence remains limited. Therefore, a shift from simply “Human-in-the-Loop” to a structured feedback mechanism based on Intelligence Augmentation that enables lecturers to contribute to the continuous improvement of Artificial Intelligence models is needed.
Enhancing Teachers' Digital competency through Participatory LMS Training for Junior High School Teachers Abdul Rahman; Brezto Asagi Dewantara; Lazaro Kumala Dewi
Teknodika Vol 24, No 1 (2026): Teknodika
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/teknodika.v24i1.113957

Abstract

The digital competency gap among teachers is a crucial barrier to integrating technology into learning and represents a real challenge for junior high school teachers, as technology proficiency remains uneven. This study aimed to examine the effectiveness of a participatory Learning Management System (LMS) training program designed to improve the digital competency of 28 teachers at State Junior High School (SMPN 24) in Banjarmasin City. This study used a one-group pre-test–post-test design. The Shapiro–Wilk normality test confirmed that the data were normally distributed (p > 0.05); therefore, a paired samples t-test was used to measure the impact of the intervention. The results showed a highly significant increase in teacher competency scores from before the training (mean = 75.00, SD = 13.264) to after the training (mean = 89.82, SD = 7.134), with a p-value (p < 0.001), indicating a statistically significant improvement in teachers’ digital competency after participating in the LMS training program. These findings demonstrate that a participatory training approach effectively improves teachers’ digital competency and can serve as a strategic model for professional development in the digital era.
Digital Teaching Reinvented: The Effectiveness of AI-Based and IFP-Based Interactive Media in Improving Teacher Competence Brezto Asagi Dewantara; Eka Cahya Sari Putra; Fitri Nurmahmudah
Pedagogik Journal of Islamic Elementary School Vol. 8 No. 3 (2025): Pedagogik Journal of Islamic Elementary School
Publisher : Institut Agama Islam Negeri Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24256/pijies.v8i3.8675

Abstract

Digital transformation in education requires teachers to have competencies that are not only technically strong, but also adaptive and creative in utilizing smart technologies. This study aims to analyze the effectiveness of "Digital Teaching Reinvented" training that integrates the use of Artificial Intelligence (AI) and Interactive Flat Panel (IFP)-based media in improving teachers' digital competence. The research design used a one-group pre-post test involving 32 teachers who participated in intensive training based on direct practice and media co-creation. Data was collected through competency evaluation instruments covering three main domains: AI-based media competence, IFP media competency and attitudes, and overall digital competence. Data analysis was carried out using a paired sample t-test, Wilcoxon test, and effect size calculation. The results of the study showed a significant increase in all competency domains. AI-based media competence increased from an average of 43.81 to 63.56 (p < 0.001; d = 1.50), IFP media competence and attitudes increased from 110.00 to 173.44 (p < 0.001; d = 2.16), while total digital competence increased from 76.91 to 118.50 (p < 0.001; d = 2.03). This improvement confirms that training that combines AI media design and IFP operation is able to strengthen technical skills, pedagogical readiness, and teachers' attitudes towards learning technology. These findings also show that integrative training models can accelerate teachers' ability to design innovative, interactive, and student-centered learning. This research provides theoretical and practical contributions through empirical evidence that AI–IFP integration-based training can be an effective strategy to improve teachers' digital competencies in the era of smart learning. This training model is recommended as an approach that can be replicated in various educational contexts to strengthen teachers' readiness to face the challenges of sustainable digital transformation.