Journal of Educational Management and Learning

How the Merdeka Curriculum Implementation and Teacher Motivation Shape High School Performance Outcomes in West Aceh, Indonesia

2025-05-31T23:14:42+07:00

This study examines the effects of the Merdeka Curriculum implementation and teacher motivation on high school teacher performance in Aceh Barat Regency, Indonesia. The Merdeka Curriculum, a recent educational reform emphasizing flexibility and student-centered learning, aims to enhance teaching quality and student engagement. Using a quantitative approach, data were collected from 74 high school teachers through structured questionnaires. Statistical analyses, including t-tests and regression, were conducted to assess the impact of curriculum implementation and motivation on teacher performance. Findings reveal that the Merdeka Curriculum significantly improves teacher performance by promoting adaptive teaching practices. Teacher motivation, encompassing intrinsic and extrinsic factors, also positively influences performance, with high motivation levels associated with more extraordinary dedication and effectiveness. The combined analysis indicates that 80.2% of the variation in teacher performance is explained by these factors, suggesting that both curriculum flexibility and motivational support are essential in enhancing educational outcomes. These results offer practical insights for policymakers and educational stakeholders aiming to support teacher engagement and curriculum adaptability.

Developing Digital Microlearning Content on Reaction Rates Using Wix for Senior High School

2025-05-31T23:14:40+07:00

Reaction rate concepts in high school often lack submicroscopic depth and are not supported by digital media that match Generation Z's preferences for interactive learning. This study developed a Wix-based microlearning platform for 11th-grade students featuring videos, infographics, quizzes, worksheets, games, and modules. Using the ADDIE model, the platform was evaluated by experts and tested in the classroom. Expert validation showed high feasibility (91.94% from content and language experts, 90.40% from media experts). Large-scale trials with students and teachers also yielded high acceptance (93.25% and 93.23%, respectively). These findings support the platform’s feasibility and effectiveness in enhancing chemistry learning, especially for teaching reaction rates.

An Explainable Machine Learning Study of Behavioral and Psychological Determinants of Depression in the Academic Environment

2025-05-31T23:14:38+07:00

Depression is a significant and growing concern within academic environments, affecting both students and staff due to factors such as academic pressure, financial stress, and lifestyle challenges. This study explores the use of machine learning, specifically a Random Forest classifier, to predict depression risk among students using behavioral, psychological, and demographic data. A dataset of 27,788 student records was analyzed after thorough preprocessing and exploratory data analysis. The model achieved strong performance, with an accuracy of 83.52% and an AUC of 0.91, indicating reliable classification of depression status. Local Interpretable Model-agnostic Explanations (LIME) were employed to enhance interpretability, revealing key predictive features such as suicidal ideation, academic pressure, sleep duration, and dietary habits. These interpretable insights align with existing psychological research and provide actionable information for mental health professionals. The findings highlight the value of explainable AI in educational settings, offering a scalable and transparent approach to early depression detection and intervention. Future work should focus on longitudinal data integration, multimodal inputs, and real-world implementation to strengthen the model’s utility and impact.

Empowering Teachers in the Digital Age: Leadership Strategies for Enhancing Pedagogic Competencies in High Schools

2025-05-31T23:14:36+07:00

This study examines the strategies employed by school principals to enhance the digital pedagogic competencies of teachers in three public high schools in Kluet Utara, Aceh, Indonesia. With the growing demand for digital integration in education, effective leadership is critical in preparing teachers to utilize digital tools in classroom settings. Using a qualitative descriptive approach, data were collected over a two-month period through semi-structured interviews, direct observations, and document analysis. The findings revealed three main themes: (1) Professional Development Initiatives, (2) Infrastructure and Resource Allocation, and (3) Collaborative Practices. Professional development programs, such as workshops and training sessions, played a crucial role in developing foundational digital skills. Infrastructure investments in internet connectivity and digital resources facilitated digital integration, though resource limitations in some schools posed challenges. Collaborative practices, including peer mentoring and team-based problem solving, played a crucial role in fostering a supportive environment for digital teaching. However, teachers faced challenges related to varying levels of digital proficiency, time constraints, and limited resources. This study highlights the importance of a comprehensive, leadership-driven approach to developing digital competencies among teachers, suggesting that a combination of continuous professional development, adequate resources, and collaborative support can significantly enhance digital integration in schools. These findings underscore the necessity for educational leaders to adopt a comprehensive, multifaceted approach to building digital competencies among teachers. By strategically integrating continuous professional development, adequate infrastructure, and collaborative frameworks, school leaders can significantly accelerate digital transformation efforts. For policymakers, this research underscores the crucial importance of aligning educational policies with resource allocation and leadership training to facilitate systemic digital integration. In an increasingly digitalized educational landscape, such leadership-driven strategies are indispensable for achieving equitable and effective teaching outcomes on a broader scale.

Techniques and Tools in Learning Analytics and Educational Data Mining: A Review

2025-05-31T23:14:33+07:00

Learning analytics and educational data mining are rapidly evolving fields that leverage data-driven methods to enhance teaching, learning, and institutional decision-making. This review provides a comprehensive overview of the key analytical techniques and tools employed in learning analytics and educational data mining, including classification, clustering, regression, association rule mining, and data visualization. It also highlights the integration of advanced methods such as deep learning and adaptive systems for personalized education. The paper examines various platforms and technologies, including learning management systems, open-source tools, and AI/ML libraries, to evaluate their capabilities, scalability, and practical adoption. Key application areas, such as dropout prediction, engagement analysis, personalized learning, and curriculum design, are examined through selected case studies spanning K–12 and higher education. The review emphasizes the growing importance of ethical considerations, interpretability, and usability in the application of educational analytics. By synthesizing current practices and trends, this work aims to inform educators, researchers, and developers seeking to harness educational data for improved learning outcomes and strategic planning.