Seno Lamsir
Departemen Ilmu Kulit, Kelamin dan Estetika

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Curriculum 5.0: Reimagining Education Management with Augmented Reality and Learner-Centric Design Loso Judijanto; Arkam Lahiya; Seno Lamsir
Journal of Paddisengeng Technology Vol. 1 No. 2 (2025)
Publisher : PT. Sinergi Bersahaja Sejahtera

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65224/jopate.v1i2.188

Abstract

Background. The transition toward Curriculum 5.0 reflects a paradigm shift in education management, where emerging technologies such as Augmented Reality (AR) and learner-centric pedagogies are integrated to foster personalized, immersive, and competency-driven learning experiences. In this context, AR is not merely a technological tool but a transformative medium that enhances engagement, contextual understanding, and collaboration, while learner-centric design ensures that educational processes are tailored to individual needs, preferences, and learning pathways. Purpose. This quantitative study aimed to investigate the influence of Augmented Reality-based instructional environments and learner-centric design strategies on the perceived effectiveness of education management within the Curriculum 5.0 framework. Specifically, it examined whether these perceptions differ according to educators’ digital competence, teaching experience, field of expertise, and openness to technology adoption. Method. The study involved 312 educators from diverse educational institutions who had experience integrating AR into curriculum delivery. Data were collected through a structured questionnaire measuring perceptions of AR’s pedagogical value, the quality of learner-centric design, and overall education management effectiveness. The responses were analyzed using statistical methods, including descriptive analysis, ANOVA, and multiple regression, to identify relationships and differences across demographic and professional variables. Results. The findings indicate that both AR integration and learner-centric design strategies have a significant positive impact on the perceived effectiveness of education management. Educators with higher digital competence and openness to innovation reported stronger alignment between AR-enhanced instruction and the goals of Curriculum 5.0. Conclusion. This study provides empirical support for the integration of AR and learner-centric design in realizing the vision of Curriculum 5.0. By combining immersive technology with personalized learning approaches, educational institutions can create adaptable, engaging, and future-ready learning ecosystems.
AI-Driven Career Pathways: Predictive Counseling Systems for Aligning Student Potential with Future Job Markets Loso Judijanto; Herryansyah Herryansyah; Seno Lamsir
Journal of Paddisengeng Technology Vol. 1 No. 1 (2025)
Publisher : PT. Sinergi Bersahaja Sejahtera

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65224/jopate.v1i1.189

Abstract

Background. Rapid technological advancements and evolving labor markets have created significant challenges in aligning students’ academic pathways with future career opportunities. Traditional counseling approaches often lack predictive capacity, leaving students underprepared for emerging job sectors. Artificial Intelligence (AI)-driven predictive counseling systems offer new possibilities by integrating student potential, skills, and aspirations with real-time labor market trends. Purpose. This study aims to examine the effectiveness of AI-driven career counseling systems in predicting and aligning student potential with future job markets. Specifically, it explores the extent to which AI-based predictive models can enhance the accuracy of career guidance and reduce mismatches between educational outcomes and employment demands. Method. Using a quantitative design, the research collected data from 312 university students across three institutions in Indonesia. Students engaged with an AI-powered career counseling platform that generated personalized career recommendations based on academic performance, psychological profiling, and labor market analytics. Data were obtained through system usage logs, surveys, and follow-up evaluations. Statistical analyses, including regression and ANOVA, were employed to assess the impact of AI counseling on student decision-making and career clarity. Results. Findings reveal that AI-driven counseling significantly improves students’ career awareness and alignment with future labor demands. Students using the predictive system demonstrated higher confidence in their career choices and reduced anxiety about employability. Additionally, the AI system identified potential career trajectories in emerging sectors, such as digital finance, green technologies, and AI ethics, which were often overlooked in traditional counseling. Conclusion. The study underscores the transformative role of AI in educational counseling, emphasizing its potential to bridge gaps between academic preparation and job market realities. Implementing predictive AI models in career services can empower students to make informed choices, while enabling institutions to adapt curricula to future workforce needs.