Strategi Pemanfaatan Kecerdasan Buatan dalam Pembelajaran Pendidikan Agama Katolik Tingkat SMA

Introduction: Artificial Intelligence (AI) is reshaping education by facilitating adaptive, personalized, and data-informed learning experiences. Through intelligent tutoring systems, predictive analytics, and AI-powered feedback mechanisms, educators can tailor instruction to meet diverse learner needs while enhancing efficiency and engagement across both traditional and digital learning environments.Objective: this study aims to examine the effective use of artificial intelligence (AI) in education for promoting personalized learning, while upholding key ethical standards. Method: A short communication methodology was employed to synthesize recent developments in AI applications in education. Relevant literature published between 2018 and 2025 was identified through searches of databases including PubMed, Scopus, ResearchGate, and Google Scholar. Studies were selected based on criteria related to the use of AI in personalized learning, assessment, instructional design, and administrative automation. Data were thematically analyzed to evaluate the benefits, implementation strategies, and challenges associated with AI integration.Results: AI-driven tools were found to significantly enhance educational outcomes by enabling proactive (e.g., curriculum design, predictive enrollment analysis) and reactive (e.g., real-time tutoring, automated grading) engagement. Platforms like adaptive learning systems, intelligent tutoring tools, and AI-driven assessment software have enabled personalized learning experiences and eased administrative tasks. However, significant challenges persist, including concerns over data privacy, algorithmic bias, digital literacy gaps, and unequal access to technological infrastructure.Conclusion: AI technologies hold substantial promise in creating more personalized, inclusive, and effective educational ecosystems. By streamlining teaching processes and supporting learner-centered models, AI enhances both pedagogical impact and academic performance. However, ethical concerns and infrastructural barriers must be addressed to ensure responsible and sustainable adoption. Future efforts should focus on aligning AI development with equity, transparency, and accessibility in education.

This study aims to understand the perception and utilization of artificial intelligence (AI) by Catholic Religious Education teachers in learning, as well as identify factors that influence the effectiveness of using this technology. The role of AI in the era of technology 5.0 is not only as a tool, but also as a breakthrough that helps in designing innovative learning. However, many teachers still lack the ability to utilize AI appropriately. Based on this condition, it is necessary to conduct an in-depth study related to teachers' perceptions and their ability to utilize AI in learning, especially in Catholic religious education. A qualitative research method with a phenomenological approach was used to explore the experiences and views of teachers from various levels of tenure. Data were collected through semi-structured interviews, participatory observation, and documentation, then analyzed using thematic analysis techniques and data triangulation to increase the validity of the findings. The results show that there are variations in perceptions related to AI, where teachers with less than five years of service tend to be more open and actively use AI in learning, while teachers with more than 15 years of service show skepticism and limited use. The main influencing factors were technical skills and anxiety related to changing teacher roles as well as the unsuitability of AI in conveying the spiritual and moral values of Catholicism. Training limitations and lack of in-depth understanding of AI were also significant barriers to its utilization. This study highlights the importance of continuous training that integrates technical aspects and religious values to improve teacher readiness. In addition, there is a need to develop AI content that is in line with Catholic teachings as well as learning approaches that emphasize the role of the teacher as a moral and spiritual guide. This research provides a basis for developing teacher professional development strategies and AI-based learning innovations that are aligned with the values of faith in religious education.

This study aims to explore the integration of ChatGPT in Catholic Religious Education and Character Development, focusing on students’ learning experiences, usage patterns, levels of awareness, and reasons for adopting the tool as a learning support. A qualitative phenomenological approach was employed to capture students’ lived experiences in using generative artificial intelligence in learning activities. The participants consisted of six junior high school students from Grades VII, VIII, and IX who were purposively selected based on their experience using ChatGPT in academic contexts. Data were collected through in-depth interviews, classroom observations, documentation, supplementary questionnaires, and field notes. Data credibility was ensured through method and source triangulation, as well as member checking. The data were analyzed thematically through the stages of data reduction, data display, and conclusion drawing and verification. The findings indicate that students use ChatGPT to deepen their understanding of learning materials and to support the completion of academic tasks. Two main patterns of use emerged, namely reflective and pragmatic, which shape how students engage with the technology. The integration of ChatGPT appears to contribute more strongly to the development of integrity-related values than relational values, underscoring the importance of sustained pedagogical guidance from teachers. These findings suggest that the purposeful integration of generative artificial intelligence, supported by reflective educational guidance, can promote both academic understanding and character formation. This approach also offers a transferable framework for the responsible integration of AI in faith-based educational institutions.

Catholic religious education is an educational process that helps Catholic students grasp the knowledge of the Christian life and identity. In Indonesia, national education law pushes students to learn their religion. Religious education then becomes a mono-religious education that does not suit the Indonesian plurality. It will elevate exclusivism. Indonesian Catholic religious education promotes respect, dialogue, and collaboration between religious adherents. The foundation for this effort is Catholic respect toward other religions, explicitly stated in the declaration of Nostra Aetate. Every grade has a topic that introduces different cultures and religions. It is the application of Indonesian Catholic religious education to educate students to respect other beliefs. It is a good start for multicultural education, and at the same time, it raises questions about the probability of modifying a mono-religious education into an interreligious one. This research was conducted in the diocese of Surabaya, while Jombang, Blitar, and Surabaya were chosen as the diocese's representatives. Interviews with Catholic religious teachers used a semi-structured mode. These are some findings from this research. Practices of Catholic religious education in Indonesia open the possibility of modifying a mono-religious education becomes interreligious education. It needs teachers' commitment and school policy that allows the teacher to modify the curriculum. The teachers' creativity to alter the curriculum needs the principal's goodwill. It also needs reformation from every aspect of school as a social system to support multicultural education. On the other side, the environment outside the school is hoped to give positive support for the reformation by giving broader experience. Through this process, Catholic religious education in Indonesia fulfill its destiny to cultivate faith and promote respect toward other religions.

Humans, who are living creatures with intelligence, have the potential to continue to develop. One way of human development is through education. Education for humanity is an absolute need that must be fulfilled throughout life. With education, humans can broaden their insight, be creative, prosperous, happy and be free from being left behind by the increasingly developing times. One of the education children receive is Catholic religious education at school. Studying Catholic Religious Education encourages students to become believers who are able to live and realize their faith in everyday life. In achieving the goals of Catholic religious education, a teacher must have skills in teaching, make careful plans and actively increase knowledge and experience in carrying out his duties. The success of learning depends on the teacher's success in activating students through the teaching and learning process which is supported by educational facilities and infrastructure, appropriate learning models and curriculum. The independent curriculum gives educators the freedom to create quality learning that suits students' needs and learning environment. The independent curriculum emphasizes the Pancasila student profile. In this classroom action research, the researcher focuses on the dimension of having faith in God Almighty and having noble morals and the dimension of critical reasoning. In the process of implementing Catholic religious education, a teacher often encounters problems, for example students are less active in the Catholic religious education learning process, students lack understanding of a concept and low student learning outcomes. There are many factors that cause low student learning outcomes, for example inappropriate learning models, lack of student involvement, the learning process is still teacher-centered and low student interest in reading PAK textbooks. Based on the problems above, teachers can provide meaningful learning experiences by designing the learning process. The learning model that can be applied is Discovery Learning. The use of the Discovery Learning model according to syntax includes providing stimulation, problem statement/identification, data collection, data processing. proof (verification), drawing conclusions/generalization (generalization). The objectives of this research are (1) To find out how to improve student learning outcomes through Discovery Learning for Class VIII SMP Negeri 6 Sibolga. (2) Knowing the increase in achievement targets through the Discovery Learning model in Class VIII of SMP Negeri 6 Sibolga. The type of research used is qualitative with a descriptive approach. Data collection techniques in this research use tests, observation and documentation. The data analysis technique used is comparative descriptive, namely comparing the test scores for action 1 and the test scores after action 2 and then reflecting on them. The research results can be concluded that the Discovery Learning model can improve learning outcomes for class VIII Catholic Religious Education at SMP Negeri 6 Sibolga. This is mainly because through the discovery learning model students learn directly to find new understanding through learning activities designed with various sources. The interaction and communication between teachers and students and communication between students really supports learning activities.

This study aims to analyze the trends, opportunities, and challenges of implementing Artificial Intelligence (AI) in primary education based on a systematic literature review. The research method employed the Systematic Literature Review (SLR) approach with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). Data collection techniques involved searching references from reputable journal databases such as Scopus, Web of Science, ERIC, Google Scholar, IEEE Xplore, Taylor & Francis Online, and Wiley Online Library, resulting in 45 studies (2016-2024) selected based on relevance to AI in primary education. The study results indicate that (1) AI trends in primary education are dominated by Augmented Reality (AR), Virtual Reality (VR), Learning Management Systems (LMS), and Adaptive Learning Systems; (2) Opportunities for AI in primary education include the development of more effective and measurable AI technology innovations and their widespread application to improve student learning outcomes; and (3) Challenges in implementing AI in primary education include technological disparities, high costs, uneven infrastructure, lack of teacher training, and insufficient technological and budget support, and student data privacy. The study concludes that AI in primary education has the potential to enhance learning quality through AR, VR, LMS, and Adaptive Learning, yet still faces challenges related to technological disparities, costs, infrastructure, and teacher training. This study offers insights for policymakers and educators to strengthen teacher competence, improve infrastructure, and ensure equitable AI access in schools.

The integration of artificial intelligence in education is a significant advancement that fundamentally transforms education delivery and reception. Artificial intelligence relies on technologies like machine learning and big data analysis to offer customized and interactive learning experiences. Analyzing students' performance and providing individualized advice may improve their knowledge. Artificial intelligence (AI) may also enhance the creation of cutting-edge educational materials using technologies like augmented and virtual reality, making the learning experience more engaging and interesting. Nevertheless, further comprehensive research is necessary to fully understand the lasting impact of AI approaches on student learning results. In order to address this deficiency, the present work proposes a novel strategy that integrates bibliometric analysis with systematic literature review (SLR) utilizing the PRISMA methodology. The first stage focused on a comprehensive bibliometric, which included key nations, educational establishments, publications, keywords, and influential authors in the realm of artificial intelligence in education. This phase facilitated a comprehensive understanding of the overall state of this field across different disciplines. The subsequent phase was a systematic literature review (SLR) of 12 specifically chosen scholarly articles. This review focused on the current use of artificial intelligence (AI) in education. This review also examined the impact of implementing artificial intelligence (AI) in education, specifically focusing on its influence on student motivation and the desire to learn.The present study aims to implement artificial intelligence (AI) technology in education and explore strategies for achieving sustainable education for future generations.

This research aims to improve student learning outcomes through the application of Problem-Based Learning (PBL) in Catholic Religious Education, especially in the material "The Church as a Sign and Means of Salvation". Using a classroom action research approach, this study was conducted in two cycles with 18 grade VIII students at SMP NEGERI 1 PABULUAN during the 2024/2025 school year. Data is collected through observation, tests, questionnaires, and documentation. The results showed that the implementation of PBL increased student engagement, with 70% of students actively participating in discussions and 65% showing improved critical thinking skills. The average test score increased from 65 in the initial condition to 72.5 in the first cycle, with 65% of students achieving the minimum completeness criteria. Character development in terms of Caring, Confident, and Professional (P3) also shows a positive trend. Although not all success indicators were achieved in the first cycle, significant improvements were observed in several aspects. The study concluded that PBL has the potential to improve student engagement and critical thinking skills in Catholic Religious Education, with recommendations for further optimization in the second cycle.

Abstract. Problem. The rapid advancement of artificial intelligence (AI) has significantly impacted various domains, particularly education. AI-driven tools are increasingly being integrated into teaching methodologies, assessment frameworks, and curriculum design. However, despite the growing research interest in Artificial Intelligence in Education (AIED), the field remains fragmented, lacking a comprehensive analysis of dominant research themes and emerging trends. Understanding these trends is crucial for optimizing AI applications in education and shaping future developments in the field. Goal. The primary goal of this study is to analyze the current landscape of AIED research by identifying key thematic clusters, evaluating dominant research directions, and predicting future trajectories in AI-driven education. Methodology. This study employs network analysis, topic modeling, and global research trend evaluation to analyze scientific publications in AIED. The Latent Dirichlet Allocation (LDA) algorithm is applied to classify research articles into thematic categories, enabling the identification of primary topics shaping the field. Data is sourced from the Web of Science database, and hierarchical clustering techniques are used to determine semantic similarities between thematic models. Results. The analysis reveals five major research clusters in AIED, including AI applications in medical education, machine learning in education, adaptive learning technologies, large language models in learning, and student-centered AI-driven educational strategies. The study identifies increasing trends in the adoption of generative AI and chatbot-based learning support, while traditional AI-driven assessment methodologies show moderate growth. The results also highlight strong interconnections between AI-driven personalization and intelligent tutoring systems, emphasizing the shift toward adaptive and student-centric learning environments. Originality. This research provides a structured and systematic analysis of AIED trends, leveraging advanced topic modeling techniques. Unlike previous studies focusing on isolated AI applications in education, this study presents a holistic view of thematic structures in AIED research, offering a quantitative and data-driven approach to understanding the evolution of the field. Practical Value. The findings can serve as a strategic reference for educators, policymakers, and AI developers in shaping future educational technologies. By identifying key thematic directions, this research supports evidence-based decision-making for integrating AI into educational systems. The results can also guide further research in AIED, helping scholars explore emerging AI-driven teaching methodologies, adaptive learning models, and ethical considerations in AI-powered education.

The integration of Artificial Intelligence (AI) technologies into educational environments—particularly through Adaptive Learning Systems (ALS)—has fundamentally transformed the delivery of instruction and personalized learning. These intelligent systems leverage machine learning algorithms to continuously analyze learner data and adapt content, pacing, and pedagogical strategies to individual student needs, leading to enhanced engagement and improved learning outcomes. However, this rapid digital evolution has surfaced critical concerns about the opacity, fairness, and accountability of AI-driven decisions. Often referred to as “black-box” systems, many AI models offer little to no insight into how they arrive at recommendations or interventions, thereby posing challenges related to transparency, interpretability, trust, and ethical governance. This paper argues that to responsibly integrate AI in education, especially in contexts where student data and futures are at stake, it is essential to move beyond system performance and embrace Explainable AI (XAI)—a design philosophy and technical paradigm focused on making AI decision-making understandable to humans. We propose a student-centric framework for XAI in ALS, which places learners and educators at the center of AI design and deployment processes. The framework is informed by interdisciplinary literature and practical case studies in educational technology and AI ethics. It emphasizes three foundational pillars: (1) Human-centered design, which ensures that AI interfaces and feedback mechanisms are accessible and usable by students and educators alike; (2) Stakeholder collaboration, which fosters ongoing dialogue between developers, teachers, learners, ethicists, and policymakers; and (3) Ethical integration, which embeds principles such as fairness, inclusivity, data privacy, and algorithmic accountability into the development lifecycle of adaptive learning tools. The framework also outlines actionable strategies to ensure that explanations provided by AI systems are contextually meaningful, developmentally appropriate, and pedagogically aligned. It considers the differentiated cognitive needs of various learner groups and promotes educational transparency as a right, not a privilege. Ultimately, this student-centric XAI framework aims to cultivate trustworthy, ethical, and pedagogically sound AI systems that not only support learning but also uphold the rights, agency, and dignity of learners in the digital age. By advocating for transparency and ethical accountability, this work contributes to the growing body of research on responsible AI in education and offers practical guidance for institutions aiming to deploy adaptive technologies in equitable and explainable ways.

The purpose of the study is to develop a model of a hybrid intelligent educational environment according to the intellectual partnership between humans and artificial intelligence, based on an analysis of the practice of using artificial intelligence in school and university education. To achieve this goal, it was necessary to solve the following tasks: to assess the opinions of participants in educational relations about the use of artificial intelligence in education, the associated threats and opportunities; to identify the features of using artificial intelligence in higher education; and to develop methodological approaches to forming an intellectual partnership between students and artificial intelligence as the basis for a model of a hybrid intelligent educational environment. Materials and methods. The study used a range of methods, including inductive-deductive, statistical and comparative analysis, modeling, and visualization of graphical data.The information base was compiled from scientific publications, materials of the All-Russian Public Opinion Research Center, research results of the scientists of the Higher School of Economics, open sources of the Internet. Results. The integration of artificial intelligence into the educational environment is accompanied by a number of problems (technological, social, psychological, ethical), which requires the management of educational organizations to take them into account when creating a new pedagogical ecosystem, in which artificial intelligence acts as a new tool of the educational process. An analysis of the parental community’s opinions regarding the use of artificial intelligence in children’s education revealed diverse assessments: while acknowledging the high educational potential of the technology, there were also concerns about the associated threats, with the main concern being the potential decline in the quality of knowledge. The article identifies the broad opportunities for using artificial intelligence by students and teachers in school and university education. It also highlights the fundamental differences in the use of artificial intelligence in higher education, which are related to the depth and complexity of solving scientific and educational tasks. The article proposes methodological approaches to creating an intellectual partnership between students and artificial intelligence, aimed at preventing the passive use of technology that leads to intellectual stagnation. The model of a hybrid intellectual educational environment is developed, which requires not only the modernization of technological infrastructure, but also pedagogical and cultural transformation based on ethical principles. The tasks have been formulated to train new qualified personnel who can use artificial intelligence technology as a tool for their professional activities. Conclusion. In the era of unprecedented growth in technological achievements and the widespread and deep penetration of artificial intelligence into all areas of life, including the educational environment, the modern education system is in the process of reevaluating the role and place of artificial intelligence in the learning, development, and upbringing of young people. Recognizing the need to adapt to new technological trends, educational organizations are carefully assessing the potential and threats associated with the implementation of artificial intelligence in the educational process, as well as evaluating their own resources to implement the concept of “collaborative intelligence”, which combines human and artificial intelligence. The intellectual partnership of participants in educational relationships with artificial intelligence has a high potential for solving pedagogical tasks: artificial intelligence, by solving routine tasks, frees up the teacher for creative work, emotional support, and the development of new methods for forming meta-cognitive competencies among students; artificial intelligence expands scientific and educational opportunities for students in a proactive position of using technology.

The application of artificial intelligence (AI) in education is paving the way to change the methods of teaching and learning mathematics because it brings innovative approaches that were not possible before.Appreciated in mathematics education, AI finds its uses in intelligent tutoring systems, computer grading, adaptive learning systems, and data analysis (Hwang & Tu, 2021;Moore et al., 2023).Such AI applications in mathematics education do not only contribute to the development of learner-centered educational systems but also enable educators to effectively monitor students' learning profiles and adaptively support learning experiences.Using this technological support, it is easier for teachers to identify specific individuals who require guidance through the process or motivated and encouraged to do more within a classroom setting, and AI can help to achieve this goal (Crompton et al., 2024).In this special issue, we present how various aspects of AI are being used, can be used, or can potentially be adopted in theoretical studies as well as practical implementations.

General Background: The integration of artificial intelligence in education, particularly GeoAI, represents a significant advancement in geography learning within the context of the Industrial Revolution 4.0. Specific Background: GeoAI combines geospatial technologies and artificial intelligence to support spatial analysis and interactive learning; however, its classroom utilization depends heavily on teachers’ perceptions and competencies. Knowledge Gap: Previous studies have emphasized artificial intelligence in general education, yet limited research specifically examines geography teachers’ perceptions of GeoAI utilization at the senior high school level. Aims: This study aims to analyze the levels of understanding, implementation, and reflection of geography teachers regarding GeoAI utilization in geography learning at public senior high schools in Coblong District, Bandung City. Results: The findings reveal that teachers’ understanding of GeoAI is uneven, implementation is generally adequate—primarily through Google Maps—and reflective ability is very strong in supporting learning processes. Novelty: This study provides a contextual analysis of teachers’ perceptions encompassing understanding, implementation, and reflection of GeoAI within geography education. Implications: The results highlight the need for strengthening conceptual understanding, digital competence, and geospatial literacy through training programs and policy support to advance GeoAI integration in geography learning. Highlights• Uneven conceptual mastery of GeoAI among geography teachers• Classroom practices dominated by accessible geospatial platforms• Strong reflective capacity supports technology-based learning development KeywordsGeoAI; Teacher Perception; Geography Learning; Digital Competence; Geospatial Literacy

This study explores the implementation of artificial intelligence (AI) in an educational context and its impact on data-driven decision-making related to student engagement, academic success, and creativity. Contextually, considering the necessity of utilization AI tools in education as a predominant factor in educational practice, this research provides full-fledged knowledge and approach on the overall implementation and significance of AI tools using hypothetical situation evidence (background materials), which are required to understand their prominence. We use a mixed-methods approach, combining quantitative analysis of institutional records and surveys capturing student engagement, academic performance and innovative thinking pre-post AI implementation with qualitative case studies which provide detailed insights into how AI tools can be implemented effectively in educational settings. This study is based on secondary data source, major publications available in the Scopus database related to AI in education. Search terms for data search were "Artificial Intelligence in Education," "AI-driven tools," "Impact of AI on classroom dynamics", "Personalized learning", "Educational technology, AI, and creativity in education", Critical thinking in the classroom, Adaptive learning systems), intelligent tutoring systems)." Student engagement. The results demonstrate significant gains in multiple metrics, with engagement scores increasing by 20–23%, GPA from 9% to 14%, and innovative thinking skills levels swelling from 44% to 57%. About 65%-75% of teacher surveys indicated a positive impact of AI on teaching and learning. The study also notes constraints including confounding whereby the inability to control for factors that may affect odds of innovative thinking and conceptualization in measuring innovative thinking. This is role, it should also advocate for longitudinal inquiries, establish standardized ways of assessing, and be analytical about the ethical implications raised by AI in education. Overall, this study underscores that AI has considerable potential to improve educational achievement and the necessity of systematic research in order to actualize its benefits. This study reinforces the possibility of AI making a big difference in improving educational results. As such, it illuminates the importance of systematic investigations into AI´s function in education to obtain full knowledge on how best to take advantage.

This study responds to the increasing call for thoughtful theological and ethical engagement with Artificial Intelligence (AI) by examining the role of personal theological reflection using Generative Artificial Intelligence (GenAI) content in Catholic theological education. It investigates how both educators and students might utilize AI-generated imagery as a pedagogical resource with which to enrich theological insight and foster ethical discernment, particularly through the lens of theological virtue ethics. AI is not a substitute for all human tasks. However, the use of AI holds potential for theology and catechetical religious education. Following Gläser-Zikuda’s model of Self-Reflecting Methods of Learning Research, this study systematically engages in reflective observation to examine how the use of GenAI in theology classrooms has influenced personal theological thinking, pedagogical practices, and ethical considerations. It documents experiences using common generative AI tools such as ChatGPT, Canva, Meta AI, Deep AI, and Gencraft in theology classes. The principles of virtue ethics and Human-Centered Artificial Intelligence (HCAI) offer a critical framework for ethical, pedagogical, and theological engagement. The findings contribute to the emerging interdisciplinary discourse on AI ethics and theology, and religious pedagogy in the digital age.