Background of study: The development of educational technology encourages the use of the Learning Management System (LMS) as a means of supporting innovative learning. Moodle, as a widely used LMS, has the potential to be integrated with Project-Based Learning (PjBL) to create student-centered learning while supporting the development of self-regulated learning.
Aims: This article systematically examines how teachers integrate Moodle into the implementation of PjBL and its role in supporting students' self-regulated learning. The study focused on the form of Moodle integration, the use of Moodle features, and its impact on self-regulation, engagement, and student learning outcomes.
Methods: This study uses the Systematic Literature Review (SLR) approach and follows the PRISMA guidelines. Articles are obtained from the Google Scholar database through the Publish or Perish application with a publication range of 2017–2025. The selection process was carried out through the identification, screening, feasibility assessment, and inclusion stages, resulting in 26 articles that were analyzed and synthesized thematically.
Result: The results of the synthesis show that the integration of Moodle in PjBL is carried out through the design of project assignments, management of project stages, facilitation of group collaboration, and monitoring of student learning progress. Moodle features such as assignments, discussion forums, resources, and calendars play an important role in supporting student learning, planning, monitoring, and reflection. In general, the integration has a positive impact on improving self-regulated learning, active engagement, responsibility, and the quality of student project results.
Conclusion: The integration of Moodle by teachers in Project-Based Learning not only serves as a technical support for learning, but also as a learning environment that encourages students' self-regulation. These findings confirm the importance of teachers' pedagogical roles in optimizing Moodle to create meaningful and sustainable project-based learning.

Background of study: The global higher education landscape is undergoing profound disruption due to the Fourth Industrial Revolution, demanding comprehensive integration of digital technology. Hindu religious education faces unique challenges in bridging the gap between complex ancient sacred texts and the learning styles of Generation Z students. Limited physical access to Purana literature at IAHN Tampung Penyang Palangka Raya exacerbates this challenge.
Aims: This study aims to evaluate the effectiveness, obstacles, and transformative impact of implementing the Śiva Purāṇa mobile application as a digital learning medium. The scope of the study includes pedagogical, technical, and academic cultural analysis in the context of religious higher education.
Methods: The research uses a qualitative descriptive design with a case study approach. Data were collected through participatory observation, in-depth interviews with lecturers and students, and document analysis during one academic semester. Data analysis was conducted using the interactive model of Miles, Huberman, and Saldaña.
Results: The implementation proved effective, characterized by high user acceptance and a shift in learning culture. The application successfully overcame the obstacle of physical book scarcity, changed classroom interaction patterns to be more dialectical, and supported the ubiquitous learning model.
Conclusion: The digitization of sacred texts through the “Text to Tech” approach is not merely a modernization of tools, but a vital hermeneutical bridge that democratizes access to theological knowledge without diminishing its sacredness.

Background: The world's demand for multimedia content is growing rapidly as digital platforms advance. However, the traditional content creation process, which includes ideas, writing, design, and post-production, still tends to be slow, expensive, and difficult to scale. While Generative AI has provided the ability to automatically create text, images, audio, and video, its fragmented use leads to fragmentation of the work process and does not provide a unified quality consistency mechanism.
Aims: This research aims to analyze the progress of Generative AI as well as design a systematic framework that can combine multi-modal models in one automated process for the production of multimedia content as a whole. This framework aims to improve the effectiveness, consistency, and scalability of content creation.
Methods: This study adopts a comprehensive literature review approach to 20 indexed scientific articles (2022–2025) that discuss generative models, multimodal large language models, workflow automation, model evaluation, and integration between modalities. Literature analysis was carried out through thematic synthesis to identify key trends, research gaps, integration challenges, as well as the need for generative model orchestration systems.
Results: The results show that although Generative AI models are undergoing rapid development, including diffusion models, multimodal LLMs, and knowledge-enhanced systems, there is no comprehensive framework that governs task chaining, quality control, and brand consistency in content creation.
Conclusion: This study shows that Generative AI has significant opportunities for content creation automation, but it requires structured integration through a comprehensive framework. The proposed framework offers an integrative structure for text-image-audio-video models, combining automation, style consistency, and quality control in a single workflow.

Background: Multimedia signals such as imagery and audio have a critical role in a variety of modern applications, including medical, industrial, and digital security fields. However, signal quality often degrades due to noise interference caused by environmental factors and hardware limitations, while conventional signal processing methods still face challenges in handling noise that is non-stationary and complex.
Aims: This study aims to examine and compare the effectiveness of noise reduction techniques based on Advanced Signal Processing (ASP) and Artificial Intelligence (AI), as well as identify research trends, challenges, and development directions in the field of multimedia noise reduction.
Methods: This study uses a literature study method by reviewing 20 international journals indexed by Scopus. The analysis was conducted comparatively based on the methods used, evaluation metrics, and application domains discussed in each study.
Results: The results show that ASP-based methods excel in computing efficiency and real-time performance, but have limitations in handling non-linear noise. In contrast, Deep Learning-based approaches such as Convolutional Neural Networks and Transformers are able to produce higher noise reduction accuracy, but require large data and computing resources. The DSP–AI hybrid model has been proven to be able to balance signal quality and system efficiency.
Conclusion: This study concludes that the integration of advanced signal processing and artificial intelligence is the most prospective solution for building an adaptive, efficient, and reliable multimedia noise reduction system in future applications.

Background: Learning in elementary schools still faces challenges in developing students’ critical thinking skills, especially when learning approaches do not provide opportunities for students to be actively involved in the learning process. The Guided Discovery Learning strategy directs student involvement to gain understanding through gradual exploration and reasoning. The use of PhET simulations as interactive digital media helps present concepts visually, making them easier for students to understand.
Aims: This article aims to examine the use of PhET Simulations in the Guided Discovery Learning Strategy as an effort to develop critical thinking skills in elementary school students.
Methods: This study employed a literature review, analyzing various relevant sources from national journals.  
Result: The results of the study indicate that the integration of PhET Simulation with the Guided Discovery Learning Strategy has strong potential to support the development of students’ critical thinking skills. These skills include problem analysis, information evaluation, conceptual interpretation, and the ability to draw logical conclusions. The reviewed literature consistently shows that interactive simulations encourage active learning, improve conceptual understanding, and support inquiry-based learning processes at the elementary school level.
Conclusion: This study provides an overview for elementary school educators in designing more active, meaningful learning that utilizes technology.