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This research is motivated by the view that literary works, including children's films, serve not only as entertainment but also as a means of moral learning that plays an essential role in shaping children's character. The film Paddington (2014) was chosen because it features an innocent main character who can represent moral values ​​through simple actions and dialogue. The purpose of this study is to describe how the main character's innocence is depicted in the film and how these moral values can serve as a learning medium for children. This study uses a qualitative descriptive approach with content analysis. Data were obtained through observations of scenes, dialogues, and the main character's actions that demonstrate innocence and the moral values ​​contained therein. The results show that Paddington's innocence manifests in honesty, politeness, trust, and a high level of curiosity, though this often leads to misunderstandings or chaos. This innocence serves as a medium for conveying moral values ​​such as responsibility, empathy, and learning from mistakes. The implications of this study indicate that children's films can be an effective means of character education if studied and accompanied by an understanding of the moral values ​​contained therein.

The integration of Information and Communication Technology (ICT) and tools like Canva has revolutionized English Language Teaching (ELT) in Indonesia, shifting from traditional methods to interactive, student-centered approaches. This study aims to explore the benefits and challenges of incorporating these technologies into ELT practices. Employing a qualitative literature review methodology, the research analyzed over 20 empirical studies from 2020 to 2023 on Canva and ICT in Indonesian ELT, supplemented by global Computer-Assisted Language Learning (CALL) frameworks. Key findings reveal that ICT and Canva enhance student motivation, creativity, and communicative skills through multimodal and constructivist learning, while fostering authentic language exposure and collaboration. However, challenges include inadequate infrastructure, limited teacher training, digital inequities between urban and rural areas, ethical issues such as copyright infringement, and increased teacher workload. The implications underscore the need for systematic professional development, institutional support, curriculum alignment, and policies promoting equitable access to ensure transformative and sustainable technology integration in Indonesian ELT.  

This study examines students’ perceptions of the use of online platforms for English listening practice. The research employs a mixed-methods approach involving 150 undergraduate students through questionnaires and semi-structured interviews. The findings indicate that the majority of students hold positive attitudes toward the use of online platforms, primarily due to time flexibility, diverse content, and the ability to learn independently. Nevertheless, several challenges were identified, including internet connectivity issues that disrupt the learning experience, a lack of personalized feedback, and difficulties in maintaining learning motivation. Features such as adjustable playback speed, the availability of transcripts, and interactive exercises received high levels of satisfaction. Overall, the study concludes that although online platforms have great potential to enhance English listening skills, their effectiveness largely depends on proper implementation, adequate technical infrastructure, and active support from educators. Therefore, this study recommends improvements in technical aspects and the development of more effective learning methods to achieve more optimal outcomes.

Arabic holds an important position in Islamic education as the language of the Qur'an and Hadith. However, the teaching of Arabic in Islamic educational institutions often focuses only on linguistic aspects, thus not fully achieving the goals of comprehensive Islamic education. This study aims to analyze the strengthening of Arabic language education objectives from the perspective of Islamic Tarbiyah. The method used in this study is qualitative, with a literature study and descriptive analysis approach. The analysis was conducted on relevant sources. The findings indicate that Arabic education within the framework of Islamic Tarbiyah not only emphasizes mastery of language skills but also the importance of shaping students' faith, morals, and Islamic character. The integration of tarbawi values into the objectives, materials, methods, and evaluation of learning becomes a key element in creating Arabic language education that is valuable and aligned with the goals of Islamic education. Its implications are expected to serve as a reference for curriculum development, teacher competence improvement, as well as the formulation of contextual, integrative, and sustainable Arabic language learning policies in national Islamic educational institutions.

Arabic holds an important position in Islamic education as the language of the Qur'an and Hadith. However, the teaching of Arabic in Islamic educational institutions often focuses only on linguistic aspects, thus not fully achieving the goals of comprehensive Islamic education. This study aims to analyze the strengthening of Arabic language education objectives from the perspective of Islamic Tarbiyah. The method used in this study is qualitative, with a literature study and descriptive analysis approach. The analysis was conducted on relevant sources. The findings indicate that Arabic education within the framework of Islamic Tarbiyah not only emphasizes mastery of language skills but also the importance of shaping students' faith, morals, and Islamic character. The integration of tarbawi values into the objectives, materials, methods, and evaluation of learning becomes a key element in creating Arabic language education that is valuable and aligned with the goals of Islamic education. Its implications are expected to serve as a reference for curriculum development, teacher competence improvement, as well as the formulation of contextual, integrative, and sustainable Arabic language learning policies in national Islamic educational institutions.

Private vehicles are a frequently used mode of transportation because they are considered more practical. However, using private vehicles carries several risks, such as traffic accidents due to drivers losing focus on the road due to other activities, such as making calls on smartphones, drinking, or operating the radio. Approximately 90% of accidents are caused by human error. Convolutional Neural Network (CNN) is a type of neural network commonly used on image data. CNN is often used for image classification due to its high performance and accuracy. Therefore, this study aims to analyze the performance of CNN for the classification of distracted driving activities. The results show that the CNN model is able to effectively classify images of distracted driving activities, with an accuracy of approximately 99% across all datasets and across all input image size variations. Furthermore, the results of this study also show that differences in right-hand and left-hand drive datasets do not significantly affect model accuracy. Variations in input image size also do not significantly affect model accuracy, but do affect the training duration.

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.

Background: The increasing complexity of industrial production systems requires machine condition monitoring solutions that are capable of operating in real time with high accuracy and responsiveness to support predictive maintenance strategies. Conventional cloud based monitoring systems often experience limitations such as high latency and dependence on stable network connectivity, which can delay decision making processes in critical industrial operations. Objective: This study aims to design and evaluate an Industrial Internet of Things (IIoT) architecture based on edge computing to improve the efficiency of industrial sensor data processing and accelerate anomaly detection in industrial machines. Method: The research adopts an experimental approach by designing a system architecture consisting of a sensor layer, edge computing layer, and cloud layer. Industrial sensors, including vibration, temperature, and current sensors, continuously collect machine operational data, which are then processed locally at the edge node using a machine learning based anomaly detection algorithm. System testing is conducted in a simulated manufacturing environment to evaluate performance based on latency, reliability, and detection accuracy. Results: The results indicate that edge based data processing significantly reduces latency compared with cloud-based processing and enables faster responses to machine condition changes. Additionally, the implemented anomaly detection algorithm achieves high accuracy in identifying abnormal sensor data patterns.

Background: The development of industrial technology in the Industry 4.0 era has encouraged the implementation of intelligent monitoring systems to improve machine reliability and operational efficiency. However, machine fault diagnosis systems based on artificial intelligence often face limitations in terms of interpretability because the models used are complex and difficult to explain. Objective: This study aims to develop a deep learning-based industrial machine fault diagnosis system integrated with an Explainable Artificial Intelligence (XAI) approach to improve diagnostic accuracy while providing interpretable insights for users. Method: The research method involves collecting data from industrial machine sensors consisting of vibration signals, temperature measurements, and acoustic signals, followed by data preprocessing and feature extraction processes. The processed data are then used to train a deep learning-based diagnostic model, after which explainability methods such as SHAP or LIME are applied to analyze the contribution of each feature to the model’s prediction results. Model performance is evaluated using accuracy, precision, recall, and F1-score metrics. Results: The results indicate that the proposed deep learning model achieves better performance compared to conventional machine learning methods such as Support Vector Machine and Random Forest. Furthermore, the explainability analysis reveals that vibration amplitude, increases in machine component temperature, and anomalies in acoustic signals are the main factors influencing machine fault detection. Therefore, the proposed system not only improves the accuracy of machine fault diagnosis but also provides transparency in the decision-making process, thereby supporting the implementation of predictive maintenance in smart manufacturing environments.

The integration of Artificial Intelligence (AI) into educational settings, particularly in formative assessments, offers significant benefits in terms of personalized learning, real time feedback, and increased efficiency. However, the successful implementation of AI driven formative assessments depends not only on technological capabilities but also on socio cultural and organizational factors that shape its adoption. This study explores the socio technical factors influencing the use of AI in formative assessments, emphasizing the importance of considering cultural diversity, institutional culture, and educators' beliefs. AI technologies, while powerful in automating grading and providing personalized assessments, often face limitations in addressing complex student responses that require human judgment. Furthermore, cultural factors, such as students' prior exposure to technology and different cultural attitudes towards AI, play a critical role in the acceptance and effectiveness of these tools. Organizational factors, including leadership support, digital literacy, and the readiness of institutions to adopt AI, are also key determinants in the successful implementation of AI systems in education. Teachers’ beliefs about assessment influence their acceptance and use of AI tools, highlighting the need for professional development and training to ensure that AI enhances pedagogical goals rather than replacing human expertise. The study concludes that the alignment of technology, culture, and assessment beliefs is essential for the effective use of AI driven formative assessments in educational settings. Recommendations for educational institutions include adopting a socio technical approach to AI integration, with a focus on providing resources, training, and fostering a culture of innovation. Future research directions should focus on expanding studies to diverse educational contexts, conducting longitudinal research on AI’s impact on learning outcomes, and exploring additional socio technical frameworks to guide AI adoption in education.

This study explores the integration of critical pedagogy with digital literacy, aiming to reconceptualize digital literacy beyond its traditional focus on technical proficiency and operational skills. Traditional digital literacy models emphasize the ability to navigate and use technology, primarily focusing on operational tasks such as managing digital devices, utilizing software, and performing specific functions. However, these models often overlook the broader implications of technology on society, including its role in shaping power dynamics and perpetuating social inequalities. By integrating critical pedagogy, this study argues that digital literacy should not only encompass technical skills but also encourage learners to critically assess the social, political, and cultural implications of digital tools. The critical digital literacy approach promotes social justice, equity, and empowerment by encouraging learners to question, reflect on, and challenge the ways in which technology influences their lives and society at large. Through critical engagement with digital tools, learners are empowered to challenge existing power structures, fostering social transformation. The study discusses how educators can integrate critical digital literacy into teaching practices, moving beyond traditional skill based models by encouraging critical thinking, ethical use of technology, and a deeper understanding of the role digital technologies play in shaping societal structures. Moreover, the study highlights the transformative potential of critical digital pedagogy, proposing it as a tool for educational equity and social change. By reconceptualizing digital literacy through a critical pedagogical lens, this study offers a framework that empowers students to become not just proficient digital users but active participants in societal transformation, contributing to a more inclusive and just digital future. The study also suggests areas for future research, including empirical investigations on the practical implementation of critical digital literacy frameworks across various educational settings and contexts.

This study investigates the long-term impact of adaptive digital learning ecosystems on students' self-regulated learning (SRL) behaviors and academic persistence. Adaptive learning systems personalize the learning experience by adjusting content and feedback to meet individual students' needs, preferences, and performance. These systems enhance engagement, motivation, and learning outcomes through real-time adjustments and continuous feedback. The research aims to explore how adaptive learning systems influence SRL and academic persistence in university courses over time. Using a longitudinal quantitative design, the study tracks SRL behaviors and academic persistence at multiple points during the semester. Results show significant improvements in SRL behaviors such as goal setting, planning, self-monitoring, and reflection among students engaged with adaptive learning environments. These students exhibited greater autonomy, improved metacognitive awareness, and higher motivation. Additionally, students in adaptive systems demonstrated greater academic persistence, as indicated by more time spent on tasks, higher assignment completion rates, and sustained engagement. The findings suggest that adaptive learning platforms promote SRL and academic persistence by offering personalized, responsive learning experiences. Unlike static, non-adaptive environments, adaptive systems provide dynamic support, enhancing students' ability to regulate their learning and remain engaged despite challenges. The study concludes that adaptive learning systems are vital for long-term academic success, though further research is needed to assess the sustainability of these effects in various educational settings and among diverse student populations.

This study presents an ethical framework for learning analytics aimed at addressing key challenges related to the collection and use of student data in higher education. Learning analytics, a powerful tool for improving student outcomes and institutional decision-making, has raised ethical concerns regarding data privacy, transparency, fairness, and equity. The proposed framework integrates four core principles: data privacy, informed consent, transparency, and fairness, ensuring that institutions use learning analytics responsibly while safeguarding student rights. A central feature of the framework is its focus on promoting equitable decision-making, minimizing bias, and preventing the reinforcement of existing inequalities in algorithmic and data-driven decisions. The framework also emphasizes the importance of continuous ethical oversight, holding institutions accountable for ethical data use and adapting practices as technology evolves. The study concludes that the framework offers a comprehensive solution to the ethical challenges in learning analytics, providing institutions with a practical guide to embedding ethical principles in data practices. Additionally, the research discusses its potential to foster fairness, equity, and transparency in decision-making processes. Future research is recommended to refine the framework and explore its application across various educational contexts, ensuring responsible and inclusive use of learning analytics.

Creative writing plays an important role in developing students’ imagination, self- expression, and language competence in the digital era. However, many learners still struggle with generating ideas, maintaining motivation, and gaining confidence in writing. This study aims to analyze how the use of Wattpad, viewed through the Social Constructivist framework, can enhance students’ creative writing skills, motivation, and confidence. This research applies a qualitative descriptive approach supported by survey data from 30 high school students who actively use Wattpad. The results show that 95.7% of respondents have used Wattpad before, with most of them using it to read and learn from other writers. A total of 60.9% of respondents stated that reading other writers’ works was the most helpful for improving their writing, while 17.4% highlighted peer comments and feedback as additional support. Despite its benefits, 43.5% of students mentioned difficulty in organizing ideas as their main challenge. Open-ended responses revealed that positive feedback and community interaction on Wattpad helped increase students’ motivation and confidence in writing. The discussion emphasizes that the social interaction and feedback features of Wattpad foster collaborative learning, aligning with Vygotsky’s concepts of scaffolding and the Zone of Proximal Development. These findings suggest that integrating Wattpad into writing instruction can effectively enhance students’ creativity, critical thinking, and confidence in producing literary works.

The integration of information and communication technology (ICT) is essential for supporting student-centered learning and developing 21st-century skills. However, many primary school teachers still experience difficulties in implementing ICT meaningfully due to limited digital pedagogical competence and a lack of contextualized professional development, particularly in primary and Islamic school contexts. This study aims to explore the implementation and outcomes of an ICT-based teacher training programs conducted through a field study approach, focusing on its influence on teachers’ digital pedagogical competence and instructional practices. A qualitative descriptive field study design was employed. Participants were primary school teachers from an Islamic public school in Indonesia who took part in a six-session ICT training programs. Data were collected through observations, documentation of teachers’ digital products, and reflective field notes, and analyzed using thematic analysis. The findings reveal improvements in teachers’ pedagogical understanding of ICT, technical skills, and readiness for classroom implementation. Teachers produced various ICT-based learning media aligned with instructional objectives, including interactive quizzes, game-based activities, visual materials, animated videos, and digital classrooms. High levels of engagement and collaboration were observed despite infrastructural challenges. Field-based, practice-oriented ICT training effectively bridges technological skills and pedagogical application, supporting sustainable digital pedagogy in primary education.

This study aims to determine the effect of interactive learning media based on Math Playground on student learning outcomes on fraction materials in class IV SDN Kedung Dalem III. The problem studied is whether there is a significant influence between the use of interactive learning media based on Math Playground on student learning outcomes in grade IV SDN Kedung Dalem III. This study uses a quantitative method with a one group pretest-posttest design. The sample of this study were fourth grade students of SDN Kedung Dalem III, totaling 17 students. The research instrument used is a test (Pretest-Postest) of student learning outcomes on fraction material, which consists of 10 multiple choice questions. The results of the analysis using the wilcoxon test show that the sig value (2 tailed) is 0.000 which indicates significance <0.05 so that H0 is rejected and H1 is accepted. This shows that the interactive learning media Math Playground has a significant effect on improving student learning outcomes. The conclusion of this study is that Math Playground interactive learning media can improve student learning outcomes on fraction material. Therefore, teachers and educators can use Math Playground as an alternative learning media to improve student learning outcomes.

The study describes the implementation of the Christian Religious Education teaching module with the theme Allah Creates Man to Manage in grade VI students of SD Negeri 1 Kereng Bangkirai. The qualitative descriptive approach applied direct observation, documentation of activities, and assessment of learning outcomes in the affective, cognitive, and psychomotor domains to the 11 students who attended. The teaching module is aligned with the Learning Outcomes of Phase C of the Independent Curriculum providing a directed learning structure from Genesis 2:8-15. The opening activities include greetings, prayers, praise, Bible readings, as well as students' experiential questions about nature to build a relationship between the material and everyday reality. Core activities utilize explanations, group discussions, presentations, and clipping projects with the theme of loving God's created nature that increase active participation, cooperation, and creativity of students. Assessments showed good results in all three learning domains despite constraints such as the discomfort of cross-gender discussions and the introverted nature of students; The role of teachers in creating a safe atmosphere strengthens the effectiveness of the process. Reflection confirms meaningful learning that shapes an attitude of gratitude, environmental concern, and Christian responsibility.

This study aims to analyze and synthesize research findings related to the integration of Buddhist values in the development of interactive learning media. The research employed a qualitative approach using a systematic literature review method on fifty selected articles published between 2018 and 2025. Data were collected through a structured process of identification, screening, and extraction from primary sources consisting of accredited national journals and reputable international journals. The data were analyzed using thematic and comparative synthesis techniques to identify patterns, effectiveness, and research gaps. The results show that interactive learning media based on Buddhist values can enhance students’ motivation, moral understanding, and engagement through the use of technologies such as gamification, educational animation, augmented reality, and mobile applications. The effectiveness of these media is strongly influenced by the alignment between Buddhist ethical principles, instructional design, and the cultural context of learning. Furthermore, the study reveals that the successful integration of spiritual values into digital media depends on educators’ readiness, digital literacy, and technological infrastructure support.

This study aims to examine the use of artificial intelligence (AI) in transforming Buddhist Sunday School education at the Shimakalingga Temple in Jepara in the digital era. Using a qualitative descriptive approach, data were collected through observation, interviews, and documentation studies. The results show that AI technology is beginning to be utilized in the learning process, such as the use of interactive visual media, Dharma quiz applications, and digital platforms for distance learning. The use of AI has been proven to increase student interest and understanding of Buddhist teachings, as well as support more inclusive and adaptive learning. However, challenges remain, including limited resources, lack of teacher training, and the need for ethical guidelines for the use of AI in the context of religious education. This study concludes that AI plays a significant role in supporting the transformation of Buddhist education, but its use must remain balanced with spiritual values and the role of teachers as moral guides. Therefore, collaboration between the temple, educators, and technology is needed to create a sustainable learning system based on Dharma values.

This study discusses the role of FoGuangShan Humanistic Buddhism in building compassion-based communities through education in Indonesia. As one of the schools of modern Buddhism, FoGuangShan transmits the values of compassion, wisdom, and humanity in educational practices, both formal and informal. Using a qualitative descriptive approach, this study explains how these values are applied in curriculum, learning activities, and social programs involving interfaith and cultural communities. The results of the study show that education based on Humanistic Buddhism plays an important role in fostering tolerance, strengthening moral character, and encouraging social solidarity in Indonesia's multicultural environment. Furthermore, FoGuangShan managed to create a learning space that not only focuses on academic knowledge, but also on the development of empathy, social skills, and collective awareness for living in harmony. In addition, an inclusive and dialogical approach to education is able to strengthen social relations between individuals and minimize potential conflicts based on religious and cultural differences. These findings confirm that the educational model implemented by FoGuangShan can be a significant contribution to the development of character education, interfaith dialogue, and the strengthening of social cohesion in a pluralistic society in Indonesia, as well as an alternative reference for human values-based educational practices.