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The rapid development of digital technology in the past decade has transformed Christian Religious Education (PAK) through synchronous–asynchronous models, Learning Management Systems (LMS), and blended learning, thereby expanding access and enriching both cognitive and spiritual learning experiences. However, this digital shift also introduces new risks related to child protection in online environments. National regulations mandate schools and higher education institutions, including PAK, to embed safeguarding principles into digital learning practices. Recent literature identifies three main research streams: the effectiveness of technology-enhanced learning, Christian ethics and digital spirituality, and faith-based digital literacy. Nonetheless, three research gaps remain: (1) limited integration of legal norms into technology-driven pedagogy, (2) absence of a safeguarding-by-design framework tailored for PAK, and (3) insufficient evaluation instruments to measure child protection outcomes in digital learning environments. This study aims to: (a) analyze the juridical implications of child protection regulations for the design, implementation, and evaluation of technology-based PAK strategies, (b) develop a “child-safe technology-based PAK framework” that integrates theological-pedagogical formation with regulatory compliance. The scientific contribution of this study lies in offering a PAK strategy that is not only pedagogically effective but also legally compliant, ethically grounded, and pastorally responsive thereby fostering a safe, inclusive, and child- centered learning ecosystem in the digital era.

This quasi-experimental study examines the effectiveness of Artificial Intelligence (AI)-assisted learning in enhancing critical thinking skills among undergraduate history students. The study involved 60 students divided into experimental and control groups. The experimental group received AI-supported instruction integrating adaptive learning modules, scaffolded source-analysis prompts, and guided argumentative discussions facilitated by conversational AI tools, while the control group followed conventional lecture-based instruction. Data were collected using a validated critical thinking test, classroom observation protocols, and semi-structured interviews. Quantitative data were analyzed using paired and independent sample t-tests, while qualitative data were examined through Miles and Huberman’s interactive analysis model. Results indicate statistically significant improvements in critical thinking scores in the experimental group compared to the control group. Thematic findings reveal enhanced sourcing, contextualization, corroboration, and evidence-based argumentation skills. However, minor risks of over-reliance on AI highlight the need for instructional scaffolding and ethical guidance. The findings suggest that AI can function as a cognitive scaffold that strengthens historical thinking and metacognitive awareness when implemented within a structured pedagogical framework.

Madhhab fanaticism in Islamic education, which appears in fiqh teaching practices that tend to absolutize a single madhhab, restrict dialogical space, and insufficiently appreciate the diversity of scholarly opinions. Such conditions may foster exclusive and intolerant religious attitudes among students. To respond to this problem, the study employs a qualitative approach with a library research design by critically examining books, journal articles, and documents related to fiqh madhhabs, Islamic education, religious moderation, and multicultural education. The data are analyzed using content analysis and descriptive–analytical techniques to map the forms of madhhab fanaticism in the learning process, the stages of transformation in madhhab understanding, and the pedagogical strategies that support the emergence of tolerant attitudes. The findings indicate that the transformation toward a more tolerant understanding of madhhabs is supported by curricula that accommodate comparative fiqh (multi-madhhab), inclusive learning materials, dialogical teaching methods, and teachers’ role modeling of moderate attitudes. Inhibiting factors include deeply rooted madhhab fanaticism, the dominance of conservative curricula, ideological bias in textbooks, and a weak culture of critical thinking. It is concluded that strengthening fiqh instructional design that consciously integrates religious moderation and multicultural education is essential for shifting madhhab understanding from patterns of fanaticism to patterns of tolerance within Islamic educational institutions.

The development of the Industrial Revolution 4.0 to the Society 5.0 era presents new challenges for education, including Islamic Religious Education (PAI). PAI is required not only to transfer religious knowledge but also to shape character, morality, and 21st-century competencies. This study aims to examine the philosophical foundations, characteristics, and application of PAI learning models to ensure their relevance in modern education. The research employed a qualitative approach with a library research design, involving the exploration of primary and secondary literature, critical reading, systematic note-taking, and content analysis validated through triangulation of classical and contemporary sources. The findings indicate that PAI learning models are conceptual, theoretical, systematic, and rooted in religious, philosophical, psychological, and sociological foundations. Four main models behavioristic, information processing, social, and humanistic each have strengths and limitations, yet their integration is relevant to forming insan kamil, a holistic human being balanced in cognitive, affective, psychomotor, spiritual, and social aspects. Therefore, developing PAI learning models based on Islamic philosophy and adaptive to technological advancements is a strategic necessity to face global challenges.

Background: The development of modern manufacturing systems requires production scheduling strategies that not only improve productivity but also optimize energy utilization. Multi-machine production systems with job-shop configurations exhibit high complexity due to dynamic interactions between machines, job queues, and varying processing times, making conventional scheduling methods less effective in handling changing operational conditions. Objective: This study aims to develop and evaluate a reinforcement learning based production scheduling approach to improve production efficiency while reducing energy consumption in multi-machine manufacturing systems. Methods: This research employs a job-shop based multi-machine production simulation model as the experimental environment. The scheduling problem is formulated as a Markov Decision Process, enabling the implementation of reinforcement learning algorithms, namely Q-learning and Deep Q-Network, to learn optimal scheduling policies through interaction with the simulation environment. Energy consumption parameters are incorporated into the reward function so that the learning agent can consider energy efficiency in the scheduling decision-making process. System performance is evaluated using three main metrics, namely energy consumption, throughput, and makespan. Results: The experimental results show that the reinforcement learning based scheduling approach achieves better performance compared to conventional scheduling methods, resulting in lower energy consumption, higher job completion rates, and shorter production completion times within the multi-machine manufacturing system.

Outcome-Based Education (OBE) has emerged as a strategic approach to improving graduate quality in higher education, including pastoral colleges. The pastoral education context in Indonesia, particularly in island regions such as Nias, requires the integration of academic, spiritual, and pastoral dimensions in the learning process. This study aims to analyze the strategies for implementing OBE at the Pastoral College Dian Mandala Gunungsitoli and to identify its supporting factors and challenges. A qualitative research design with a literature review approach was applied, drawing on 25 scientific articles published between 2021 and 2025. The analysis involved identifying main themes, categorizing supporting and challenging factors, and synthesizing strategies for implementation. The findings indicate that OBE implementation includes developing curriculum documents aligned with the Indonesian National Qualification Framework (KKNI) and National Standards of Higher Education (SN-Dikti), strengthening faculty capacity through training, integrating innovative learning models, and applying authentic assessment that evaluates both academic and spiritual competencies. Supporting factors consist of institutional leadership commitment, the availability of curriculum information systems, and collaboration with external stakeholders. Major challenges involve limited faculty understanding of OBE, inadequate technological infrastructure, and resistance to changes in academic culture. This study concludes that OBE can enhance graduates’ competencies and strengthen pastoral identity, provided that faculty training, internal quality assurance systems, and the integration of local wisdom into the curriculum are consistently developed.

Flower disease detection is a common challenge in modern agriculture. Various factors, such as changes in leaf color, shape, petal structure, and environmental conditions, make it difficult to achieve high accuracy with conventional models. Transfer learning is an effective solution to improve model performance in image detection, especially when available data is limited. This study used several pre-trained models, namely VGG16, ResNet50, and EfficientNet-B0, to detect three types of flower diseases: black spot on roses, white powdery mildew, and leaf rust. The process included data processing, increasing the data volume, model training, and result verification. The results showed that the EfficientNet-B0 model provided the highest accuracy of 97.2%, significantly better than the CNN model created from scratch with an accuracy of 85.1%. This study proves that the transfer learning method is very effective in improving the accuracy of flower disease detection. These results confirm that transfer learning is effective for detecting plant diseases with higher accuracy, especially when the dataset is limited.  

The paradigm of Islamic education requires the integration of Western learning theories with an Islamic perspective to create a holistic approach to education. With the rapid development of psychological theories in education, such as behaviorism, cognition, humanism, and constructivism, it is essential to examine their relevance within the context of Islamic education. This article aims to analyze the integration of these theories in Islamic learning, with a focus on their connection to key Islamic concepts such as reward-punishment (pahala-dosa), reflection (tafakkur), self-actualization, mutual assistance (ta'awun), and consultation (syura). This study uses a literature review method with a qualitative approach. Articles were gathered through Google Scholar and Publish or Perish with keywords "Behaviorism in Islamic Education" AND "Cognitive Learning in Islam" AND "Humanistic Approach in Islamic Education" AND "Constructivism in Islamic Education." Of the initial 40 articles obtained, a screening process resulted in 5 articles that met the publication criteria (2020–2025), relevance to the topic, and open access. The review results show that integrating these theories into Islamic education can enrich the learning process by linking moral, social, and spiritual elements that are essential in Islamic teachings. This literature synthesis reveals the importance of integrating psychological theories with the principles of Islamic education to create a more comprehensive and holistic educational system. Further research should develop empirical methodologies and more detailed and practical application models in Islamic education practice.

The Problem-Based Learning (PBL) model is a teaching strategy that focuses on students being the main participants in their education by engaging in the resolution of actual problems. This article looks into how PBL is applied in the classroom, its effects on enhancing students' critical thinking abilities, and the primary attributes of this model that aid in developing problem-solving skills. PBL consists of five key phases: identifying a challenge, organizing research efforts, performing both individual and group inquiries, gathering and sharing findings, and reflecting on the process. These phases create a learning experience that promotes teamwork, self-directed research, and thorough analysis of information. Findings from this research reveal that PBL significantly enhances students' critical thinking skills, particularly in areas like analysis, assessment of evidence, solution formulation, and articulating arguments logically. Furthermore, features of PBL, which include prioritizing students, addressing real-world issues, fostering self-directed learning, encouraging group collaboration, and positioning the teacher as a guide, play a crucial role in enhancing problem-solving capabilities. By tackling issues that relate to their daily lives, PBL motivates students to independently build knowledge, foster innovation, and reinforce their autonomy in the learning journey.

This research aims to improve the mathematics learning outcomes of Grade VII B students at SMP Darul Ulum 5 Rebalas through the implementation of Madurese language-based ethnomathematics. The study is motivated by the students' difficulties in understanding mathematical concepts delivered in formal Indonesian, as their daily communication relies on the specific Madurese dialect of Rebalas Village. This study employs the Classroom Action Research (CAR) method using the Kemmis and McTaggart model, conducted in two cycles. Each cycle consists of planning, action, observation, and reflection stages. The subjects of this research were 28 students from class VII B. The research instruments included test instruments in the form of group Student Worksheets (LKPD) and observation sheets for both teacher and student activities. The material focused on the topic of Lines and Angles. The results indicated an improvement in student learning outcomes from Cycle I to Cycle II. In Cycle I, the average group score was 80.2, which increased to 88 in Cycle II. Observations of student activities also showed a shift from passive participation in Cycle I to active and enthusiastic engagement in Cycle II. Furthermore, teacher observations showed significant improvement; initial issues regarding time management and excessive workloads were resolved, resulting in more enthusiastic and punctual teaching delivery. These findings demonstrate that the use of Madurese-based ethnomathematics helps students grasp mathematical terms more easily, increases discussion participation, and creates a more comfortable and interactive classroom atmosphere, thereby leading to improved learning outcomes.

This study was motivated by the need for modern education to develop students' creative thinking skills, which are still hampered by the dominance of conventional teacher-centred learning methods. The Group Investigation (GI) cooperative learning model is seen as a strategy that can encourage active participation, collaboration, and independent investigation among students. This study aims to describe the GI concept, its elements and principles, implementation steps, as well as its strengths and weaknesses in the context of learning. The research method used is a literature study through theoretical analysis and GI implementation experiences as described in the paper. The results of the study show that GI increases learning activities, critical and creative thinking skills, and students' social skills through heterogeneous group work and a structured investigation process. However, this model requires more time and teacher readiness in managing the class. The implications of this study confirm that GI is relevant to the Merdeka Curriculum and can be an effective alternative for collaboration- and project-based learning.

This study investigates the influence of financial literacy, entrepreneurship training, and financial inclusion on the performance of micro, small, and medium enterprises (MSMEs) through business sustainability. Using a systematic literature review (SLR) examines the impact of financial literacy, entrepreneurship training, and financial inclusion on MSME performance through business sustainability mediation by synthesizing empirical data from 12 research (2020–2025) across Scopus and Web of Science. Positive direct effects on sustainability (financial literacy via budgeting/risk management; training via adaptive resilience; inclusiveness via digital access) and performance metrics like profitability/growth are confirmed by results using the PRISMA 2020 flow.  Amid obstacles like financial access restrictions and COVID-19 disruptions, business sustainability appears as a crucial mediator, linking these factors to improved MSME results in developing contexts (Africa, Indonesia). Practical implications compel policymakers to give integrated literacy programs, contextual training, and inclusive finance top priority. Theoretical contributions combine financial literacy, entrepreneurial learning, and sustainability ideas into a holistic mediation model. The results highlight the importance of integrating financial education, entrepreneurial skill development, and inclusive financial systems to strengthen MSME resilience and competitiveness. This study provides practical implications for policymakers, financial institutions, and support organisations in designing effective interventions that foster sustainable business growth. The research also contributes theoretically by confirming the mediating role of business sustainability in the relationship between financial literacy, entrepreneurship training, financial inclusion, and MSME performance. Future studies may expand these insights by examining additional contextual factors such as digital technology adoption and business networking that further support sustainable MSME development.

This study aims to develop an interactive digital learning media based on Wordwall, named TANGKAS (Tantangan Asyik Ngulik Pecahan Kelas Empat Seru), as a practice tool for addition and subtraction of fractions in fourth-grade elementary students. The development process employed the ADDIE model, which includes the Analyze, Design, Develop, Implement, and Evaluate stages. The research subjects consisted of 29 fourth-grade students at SDN Ngemplak I Baureno. The needs analysis revealed that learning activities were still dominated by conventional methods with limited use of digital media, resulting in low student engagement. To address this issue, TANGKAS was developed using a maze chase game design to enhance motivation and support engaging fraction practice. The validation results indicated a material validity score of 94% (highly valid) and a media validity score of 80% (valid). The practicality aspect obtained 81.8% from students, both categorized as highly practical. The effectiveness test showed an improvement in learning outcomes with N-Gain scores of 0.6 for fraction addition and 0.54 for fraction subtraction, both classified as moderate. Therefore, TANGKAS is proven to be feasible, practical, and effective as an interactive game-based learning media to support students’ understanding of mathematics in elementary school.

The integration of Artificial Intelligence (AI) in higher education has led to the increasing use of AI-powered adaptive learning models that support personalized and data-driven learning. However, studies examining preservice teachers’ perceptions of these models remain limited, despite their important role in future classroom implementation. This study aims to explore preservice teachers’ perceptions of AI-powered adaptive learning in higher education, focusing on perceived usefulness, learning adaptivity, learning experience, and perceived concerns. A descriptive qualitative research design was employed involving 53 preservice teachers from various universities. Data were collected using a Likert-scale questionnaire and open-ended questions. Quantitative data were analyzed descriptively using percentage distributions, while qualitative data were examined through simple thematic analysis. The findings reveal that preservice teachers generally demonstrate positive perceptions of AIpowered adaptive learning, particularly in terms of learning effectiveness, adaptability, and engagement. Nevertheless, concerns related to over-reliance on AI, ethical issues, and data privacy were also identified. These results indicate that preservice teachers show readiness to engage with AI-supported learning, while highlighting the need for teacher education programs to promote responsible and pedagogically informed AI integration.

This study discusses the relevance and role of hybrid learning strategies as a conceptual solution to the crisis of effectiveness in traditional fiqh learning in Islamic boarding schools in the digital age. The background of this study stems from the problem of declining efficiency and interactivity of classical learning methods such as sorogan and bandongan amid technological developments that demand pedagogical innovation. This study aims to analyze theoretically how the integration of traditional pesantren values and modern learning approaches can be applied without eliminating spiritual identity and scientific sanad. The method used is library research with a descriptive-analytical approach through a review of the latest scientific literature on Islamic education and hybrid learning. The results show that a hybrid learning model based on synchronous and asynchronous approaches can increase flexibility, effectiveness, and student participation in the learning process, while maintaining personal relationships with teachers. The theoretical implications enrich the concept of integrating Islamic education and technology, while the practical implications offer an adaptive curriculum model for Islamic boarding schools to respond to the challenges of the digital age without abandoning Islamic values.

Islamic character education faces dual challenges: declining moral values among students and conventional teaching methods inadequate for developing higher-order thinking skills. This study examines the implementation of a smart learning environment (SLE) model to enhance metacognitive understanding in Aqidah Akhlak (Islamic Creed and Ethics) instruction among eighth-grade students at MTs Salafiyah Merakurak. Employing a mixed-methods action research design, involved 16 eighth-grade students divided into two groups. Data collection utilized classroom observations, semi-structured interviews, and learning documentation. The SLE model integrated Google Classroom, interactive video content, WhatsApp Group discussions, and Google Forms assessments to create a technology-enhanced learning ecosystem. Findings revealed substantial improvements in students' metacognitive capacities: planning skills increased from 25% to 75%, monitoring abilities rose from 31% to 81%, and evaluation competencies grew from 19% to 69%. Students demonstrated enhanced learning autonomy, active participation in collaborative discussions, and improved self-reflection on content comprehension. The SLE approach successfully fostered engaging learning experiences while facilitating deeper internalization of Islamic ethical values. However, implementation encountered constraints including limited technological infrastructure and varied digital literacy levels among students. This research underscores the critical need for developing teachers' digital competencies and strengthening madrasah technological infrastructure to optimize technology-integrated Islamic education.

This study aims to explain the application of various differentiated learning techniques based on Problem-Based Learning (PBL) to improve analytical and writing skills related to procedural texts among junior high school students. This research is based on students' lack of ability to understand and compose procedural texts methodically and in accordance with language conventions, which is caused by the prevalence of conventional teacher-centered learning. This study used a descriptive qualitative methodology involving seventh-grade students from a junior high school that has adopted the PBL model in Indonesian language subjects. Data were collected through observation, interviews, and documentation, then analyzed qualitatively. The results showed that the application of PBL along with differentiated learning and TPACK increased student engagement, accommodated diverse learning styles, and fostered critical thinking, analytical abilities, and collaborative skills. Learning became more meaningful and relevant, enabling students to compose procedural texts more effectively. This study recommends the application of the PBL model with differentiation as an innovative strategy to improve the quality of Indonesian language education in junior high schools.

This study evaluates the AIESEC Incoming Global Volunteer (IGV) Program at the Veteran National Development University in Yogyakarta using the CIPP (Context, Input, Process, Product) evaluation model. Employing a descriptive qualitative approach, data were collected through interviews, non-participatory observation, and documentation studies, with validity ensured through triangulation. The findings reveal that the IGV Program is highly relevant to the university’s internationalization agenda and contributes significantly to strengthening cross-cultural competencies among students. The availability of resources and the overall implementation of the program have been effective, though improvements are needed in ensuring consistent mentoring for international participants. The evaluation highlights that the program has generated positive outcomes, particularly in enhancing intercultural competencies and fostering collaboration with local partners. These results underscore the importance of sustaining and refining the IGV Program as a strategic initiative to support global engagement and student development.

This article develops a conceptual model that explains how social capital and digital literacy interact in shaping Islamic financial literacy in the digital era. Through a comprehensive literature review, this study synthesizes theories, empirical findings, and thematic patterns derived from reputable academic journals, scholarly books, and institutional publications. The analysis shows that social capital functions as a value foundation encompassing trust, collective norms, and behavioral orientations that influence individuals’ initial acceptance of sharia-based financial practices. Information obtained through family, religious communities, and social networks becomes a crucial entry point that shapes early perceptions and preferences toward Islamic financial products. Meanwhile, digital literacy strengthens individuals’ ability to access, evaluate, and verify Islamic financial information independently through various digital content such as online articles, infographics, educational videos, and Islamic fintech platforms. The interaction between these two dimensions creates a layered learning process in which social capital provides contextual value and trust, while digital literacy deepens technical understanding in a more objective manner. This article contributes theoretically by proposing the Social Capital–Digital Literacy Integrative Model and offers practical implications for Islamic financial institutions, regulators, and fintech providers in designing more effective strategies to enhance Islamic financial literacy in society.

Sudden Infant Death Syndrome (SIDS) is a sudden and unexpected death in infants that is often associated with the prone sleeping position. This study aims to develop an automated monitoring system capable of detecting SIDS risk factors using the YOLOv8 algorithm and to analyze the effect of data augmentation on model performance. The dataset consists of two classes, baby-lying-on-back (supine) and baby-lying-on-stomach (prone), which were processed through model training and evaluation using precision, recall, F1-score, and mAP metrics. The model was trained under two scenarios, without data augmentation and with data augmentation. The results show that the model without augmentation achieved a precision of 90%, recall of 85%, F1-score of 86%, and mAP50 of 93.7%. After applying augmentation, performance improved to a precision of 90%, recall of 87%, F1-score of 88%, and mAP50 of 95.1%. These findings indicate that augmentation increases detection accuracy and enhances model generalization, including robustness against variations in lighting and camera angles. Furthermore, testing with image and video inputs revealed that the non-augmented model exhibited a tendency toward overfitting, particularly in favor of the baby-lying-on-stomach, whereas the augmented model successfully classified both classes accurately. The developed system is also equipped with an alarm feature and early-warning notifications via Telegram to smartphone when a prone position is detected for a certain duration. Overall, the results demonstrate that YOLOv8 with data augmentation is effective for an automated, non-invasive monitoring system for infants, making it suitable for detecting and preventing potential SIDS risk factors.