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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.

The current practice of Islamic Religious Education (PAI) learning in schools still faces the challenge of the dominance of conventional methods that tend to be teacher-centered, so that the aspect of internalization of values by students is often not optimal . This article aims to describe the characteristics and conceptual relationships between the Social Interaction and Personal learning models in the context of PAI, while also examining the relationship between the two models with constructivist and humanistic learning theories . Through a literature study, the analysis shows that the Social Interaction model based on constructivist theory emphasizes the construction of knowledge through group dynamics, collaboration, and social interaction . Meanwhile, the Personal model based on humanistic theory is oriented towards the development of individual potential, self-awareness, and spiritual reflection . The results of the study conclude that the integration of these two models offers a holistic learning approach, where students not only understand PAI material cognitively, but are also able to actualize religious values through real social experiences and deep personal appreciation .

Social Studies (IPS) learning in elementary schools has tended to be theoretical and memorization-oriented, resulting in students being less able to connect the material with social and environmental realities. This study aims to examine the implementation of field projects as a contextual learning strategy in understanding the dynamics of humans, places, and the environment at the elementary school level. The research method used is a qualitative approach with literature studies, with data sources in the form of SINTA-indexed national journal articles, reputable international journals, and scientific books published in the last five to ten years. Analysis was carried out through literature selection, content analysis, and synthesis of findings. The results of the study indicate that field projects contribute to improving students' critical thinking skills, spatial understanding, social empathy, and ecological awareness. In addition, direct involvement in observation, interviews, and thematic project creation encourages students to see the relationship between humans, space, and the environment more holistically. The novelty of this study lies in the emphasis on the integration of field projects as an approach to elementary school social studies learning that unites social, geographical, and ecological aspects within the framework of the Independent Curriculum. These findings contribute to the development of project-based social studies learning models as well as practical recommendations for PGSD teachers in integrating field experiences into daily learning.

This research aims to determine the effect of learning using the Problem Based Learning model assisted by the Powtoon application on the learning outcomes of Class XI Madrasah Aliyah at the Islamic Education Park (TPI) Sawit Seberang. This research is a type of quantitative research with a Quasy Experimental Design. The research population was 36 students in class XI MIA A and 36 students in class XI MIA B, 36 students in class XI MIA C and 36 students in class, and X MIA C totaling 36 people as the control class. The instrument in this research is in the form of a test in the form of 30 multiple choice questions. Data analysis of student learning outcomes using the t-test formula, also with the help of SPSS version 25 data processing. Data analysis of student learning outcomes with the results of calculating the average learning outcomes shows that the experimental class which uses the Problem Based Learning models is higher than the control class. The prerequisite test is proven that the data is normally distributed and homogeneous. The results of the test calculation were obtained under count worth 9.709 and table worth 1.668 so that it shows tcount > table so Ha2 is accepted. The conclusions in this research explain that there are influences and differences before and after the implementation of the Problem Based Learning model on student learning outcomes in class XI Madrasah Aliyah at the Islamic Education Park (TPI) Sawit Seberang.

The research intends to formulate an integrative approach for designing the Merdeka Curriculum based on Deep Learning in the Economics subject at SMA N 1 Boyolali. The rapid advancement of digital technology demands more adaptive, contextual, and student-centered learning models aligned with 21st- century competencies. Using a an exploratory research approach supported by a structured assessment of prior studies (SLR), this research synthesizes theoretical perspectives and previous studies related to curriculum design, deep learning, and educational innovation. The results reveal that the incorporation of Deep Learning into the Merdeka Curriculum offers a more responsive and data-driven framework, enabling deeper conceptual understanding, critical thinking, and problem-solving skills in Economics learning. However, several challenges were identified, including teachers limited digital competence, insufficient infrastructure, and minimal curriculum innovation training. The study emphasizes the significance of combining technological and pedagogical innovation to strengthen learning quality. The results provide a conceptual model that educators can adopt to design an adaptive curriculum aligned with students’ characteristics and contemporary educational demands.

This study aims to conduct a comparative analysis of curriculum development and teaching methods in Islamic education in Indonesia and Egypt. Both countries have a long tradition in the development of Islamic sciences, but they demonstrate different approaches in accordance with their respective social, cultural, and educational policy contexts. This study uses a literature review method with a descriptive qualitative approach through a review of journals, books, and Islamic education policy documents. The results of the analysis show that the Islamic education system in Indonesia emphasizes the integration of religious and general knowledge in its curriculum, in line with the spirit of religious moderation and the demands of modern society. Meanwhile, Islamic education in Egypt, especially through Al-Azhar University, emphasizes a traditional approach based on tafaqquh fi al-din with a focus on mastery of classical Islamic sciences. In terms of teaching methods, Indonesia is more adaptive to active and technology-based learning models, while Egypt maintains the talaqqi and memorization methods, but has begun to adopt modern pedagogical innovations. Overall, both education systems have their own strengths; Indonesia excels in contextualizing the curriculum, while Egypt sets an example in maintaining the authority and continuity of Islamic scholarship. These findings are expected to contribute to the development of a balanced Islamic education that integrates values and modernity.

The rapid advancement of digital technology has transformed the landscape of education, particularly in secondary schools. This study investigates the influence of digital learning innovation on enhancing deep learning and student engagement. Using a quantitative survey method, data were collected from 150 secondary school students in Indonesia who actively use digital learning platforms such as Learning Management Systems (LMS), mobile learning applications, and hybrid learning models. The research instrument consisted of a closed-ended questionnaire using a five-point Likert scale, which measured students’ perceptions of digital learning innovation, their engagement levels, and indicators of deep learning. Data were analyzed through simple linear regression using SPSS version 25. The results indicate a strong and significant positive relationship between digital learning innovation and both deep learning and student engagement, with a correlation coefficient (R) of 0.732 and an R² value of 0.536. This finding suggests that digital learning innovation explains 53.6% of the variation in students’ deep learning and engagement levels. Students who frequently use digital learning technologies tend to show higher motivation, independence, critical thinking, and reflective learning behavior. The study concludes that digital learning innovation plays a crucial role in supporting meaningful learning and active participation. It highlights the importance of integrating technology strategically into school-based learning to foster adaptive, collaborative, and lifelong learners in the digital era.

Students' critical thinking skills in colloid material are still low, possibly due to a lack of problem-solving abilities. Therefore, the application of various learning models is considered necessary, one of which is Problem-Based Learning (PoE). This study aims to investigate the impact of PoE on students' critical thinking skills at Granada Polytechnic (SMA IT Granada) in colloid material. A quasi-experimental design and quantitative experimental methods were used. Fifty students from grades 11 A and B were selected as research subjects through census sampling. A post-test control design was used. Data collection used post-test data as primary data, supplemented by observation sheets of student classroom activities. The results showed that the average post-test score of the experimental group was 78, while the average post-test score of the control group was 59. The t-test results showed that the hypothesis Ha was true, therefore, it can be concluded that the application of the PoE model at Granada Polytechnic can improve students' critical thinking skills in colloid material.

An answer to the worldwide need for solutions to food security, data fusion technology that combines climate data with satellite imagery greatly improves the accuracy of agricultural yield predictions; this study intends to examine the advancements, methods, and key contributions of this area. By sifting through 62 papers pulled from Scopus, this research employs the SLR methodology. Document type, data source, open access, subject area, and year of publication (2020–2024) are some of the categories filtered through by Boolean keywords in the selection process. To assess patterns in publications, the efficacy of machine learning models, and key contributions, bibliometric analysis was performed. An upward tendency in publication has been identified by the analysis, particularly beyond the year 2023. Integrating geographical and temporal data has been a great success with machine learning models like Random Forest, Random Forest, and Gradient Boosting. Data resolution, integration of data from several sources, and a real-time framework are still missing pieces to the puzzle when it comes to generalizing research outcomes. More complex data fusion approaches, multiregional datasets, and advanced machine learning models to back more accurate agricultural predictions are all things that this study notes as needing additional investigation in the future. To further innovate agricultural yield prediction, multidisciplinary collaboration is also crucial.

The era of globalization is an era of quality competition, where only thosebwith high competence will be able to compete in the free market. Therefore, developing high-quality human resources is something that cannot be compromised. Education that supports development in this era is education that can foster students’ potential’ enabling them toface and overcome life’s challenges. Thus, in the learning process, teachers should not only serve as models or sources of knowledge but also act as learning managers. As learning managers, teachers play an important role in creating a learning environment that allows students to learn confortably and effectively. Based on observations at SMA Negeri 2 Taniwel, it was found that students in class X-2 have low learning outcomes in sociology. The writer’s observation in class indicated that sociology learning was dominated by lecture methods, resulting in students being less active during the learning process. According to research conducted by Al Muchtar (1991), learning in social studies education does not sufficiently simulate students to be actively involved in the learning process. Furthermore, the teaching and learning process of social studies carried out bye teachers has not been able to faster a learning culture among students, wich in turn significantly affects their learning achievement and outcomes. To support active learning strategies, teachers can apply various relevant learning models. Therefore, the learning process will become more varied, innovative, and constructive, creating interaction between teachers and students, among students themselves, and between students and other learning resources.

This study aims to analyze the role of Kajian Kalam at Gedung Dakwah Kalasan, Sleman, as a community-based Qur’anic literacy practice. The study is motivated by the phenomenon that, although many people in Indonesia are proficient in reading the Qur’an, their understanding of its meaning remains limited. Kajian Kalam addresses this gap through a contextual and participatory tafsir approach, actively involving participants in discussion and reflection. This research employs a qualitative case study method, using direct observation, interviews with the study leader, and documentation of the study activities as data sources. The findings indicate that Kajian Kalam enhances Qur’anic literacy on three levels: textual literacy, meaning literacy, and practical literacy. The study provides participants with opportunities to understand Qur’anic verses contextually and relate them to daily life, while also building an inclusive and egalitarian learning community. The contributions of Kajian Kalam include broadening access to Qur’anic interpretation for participants with diverse backgrounds, implementing participatory learning models, and developing grounded and practical Qur’anic literacy. This research demonstrates that community-based Qur’anic studies can be an effective means to improve understanding and practice of the Qur’an, filling a gap in previous studies that focused primarily on formal institutions. The findings are expected to inform the development of more participatory and practical Qur’anic study models in society.

Based on the results of initial interviews and observations, it was found that several students still experienced difficulties in writing procedural texts effectively. These difficulties included a lack of understanding of the structure and characteristics of procedural texts, challenges in expressing ideas in written form, limited ability to compose coherent and communicative sentences, and the use of monotonous learning models that failed to stimulate student motivation. This study aims to describe the implementation of the Project Based Learning (PjBL) model based on the Tri N approach (Niteni, Niroke, and Nambahake) to improve the procedural text writing skills of fourth-grade students at Sidomukti Elementary School, Ambal Sub-district, Kebumen Regency, as well as to identify the improvement in writing skills after its application. The research employed a descriptive qualitative method with data collection techniques including observation, tests, and documentation. Data analysis was conducted through the stages of data reduction, data display, and conclusion drawing. The findings revealed that the application of the PjBL model integrated with Tri N values significantly improved students’ ability to write procedural texts. The learning process was carried out through six main stages of PjBL: formulating essential questions, planning projects, creating schedules, monitoring student activities, testing results, and evaluating learning experiences. The integration with Tri N principles encouraged students to understand, imitate, and develop their writing skills gradually. Thus, the PjBL model based on Tri N proved effective in helping students overcome writing difficulties while also fostering creativity, independence, and active participation in the learning process.

Teachers are required to adopt a wise and thoughtful approach in teaching, since their perception of students will influence their attitudes and actions. Not all teachers assess students in the same way, and this affects the methods they apply in the classroom. To achieve optimal learning outcomes, teachers must take on new roles as facilitators, mediators, learning partners, and evaluators. This means creating a democratic and dialogical learning atmosphere between teachers and students, as well as among students themselves. One effective way is by applying the PAIKEM learning model (Active, Innovative, Creative, Effective, and Enjoyable). This study aims to: (1) Describe the implementation of the PAIKEM model in Islamic Religious Education for Grade VII at Darul Ishlah Junior High School. (2) Describe the obstacles encountered in applying this model. The research uses a qualitative approach with interviews, observation, and documentation as data collection techniques. Data analysis was conducted through reduction, presentation, and conclusion drawing. The results indicate that the PAIKEM model has been implemented well, through discussions, opportunities for students to express opinions, group assignments, interactive communication, motivation, use of media such as videos, and enjoyable memorization. However, challenges include limited learning media, teachers’ creativity that is not yet optimal, inadequate facilities and infrastructure, and low student motivation.

The topics of morphology, anatomy, and physiology are integral to biology learning, yet they often present challenges for students due to their abstract and complex nature. Difficulties in understanding body structures and invisible biological processes lead to low student interest and engagement. This study aims to identify innovative learning approaches through an analysis of national scientific literature over the past decade. The results show that the integration of digital technology and student-centered learning methods can improve conceptual understanding and learning motivation. The most prominent innovations include the use of VR and AR-based media to clarify visualizations, the use of interactive videos and simulations to explain biological functions, and the application of contextual learning models such as Problem-Based Learning (PBL) and Project-Based Learning (PjBL). These approaches have proven effective in creating a more immersive learning experience that is relevant to students' needs.

This study compares the performance of two deep learning models, namely Convolutional Long Short-Term Memory (ConvLSTM) and Long-term Recurrent Convolutional Network (LRCN), in the task of recognizing human activity from videos. Human activity recognition is an important field in computer vision with many applications, such as security monitoring, human-computer interaction, and social media-based video analysis. ConvLSTM is a model that combines convolution operations with long-term memory LSTM, thus capable of capturing spatial and temporal information simultaneously. This approach is ideal for processing video data sequences that have spatial and temporal dimensions. On the other hand, LRCN combines the power of spatial feature extraction from Convolutional Neural Network (CNN) and temporal sequence modeling through Recurrent Neural Network (RNN), specifically LSTM, to understand movement patterns in videos. The study used the UCF50 dataset consisting of 50 activity classes, but was limited to five classes for the focus of the experiment. The dataset was divided into 80% for training and 20% for testing, and the model was drilled for 50 epochs using early stopping to prevent overfitting. The results show that both models have high training performance. ConvLSTM achieved a training accuracy of around 98% and a validation accuracy of 90%, while LRCN achieved a training accuracy of 99.5% and a validation accuracy of 88%. Although ConvLSTM demonstrated good stability on the validation data, further testing using TikTok videos as real-world data showed that LRCN had a higher confidence level in recognizing activities, with most predictions achieving confidence scores above 80%. This difference in performance indicates that while ConvLSTM excels in generalizing on training data, LRCN is more robust to real-world data variations.

This study aims to analyze the correlation between learning models and student achievement at SMA Negeri 1 Kuala by applying the Apriori algorithm in data mining, using Rapid Miner software as the primary tool for analysis. The research is motivated by the shift in educational approaches from conventional teacher-centered methods toward more innovative strategies such as project-based learning and cooperative learning, which are expected to foster higher levels of student engagement and improve academic outcomes. In many schools, particularly at the secondary level, the choice of learning model, availability of facilities, and attendance rates are crucial factors that shape learning effectiveness and student performance. The data collected in this study include student grades, the types of learning models implemented, school facility conditions, and attendance rates for the 2023/2024 academic year, covering a total of 680 students. The Apriori algorithm was employed to discover hidden patterns and associations among these variables, enabling the identification of relationships between learning factors and academic achievement. By applying Rapid Miner software, the research systematically generated association rules that reflect meaningful correlations in the dataset. The results indicated that the use of the Indonesian language subject in combination with a cooperative learning model, adequate and complete school facilities, and good student attendance was strongly associated with the attainment of an A grade. This finding was supported by a support level of 53.33% and a confidence level of 100%, suggesting a robust and reliable relationship between these factors. The implementation of data mining techniques through Rapid Miner not only allowed for efficient data processing but also provided practical recommendations for educators and school administrators in designing effective instructional strategies.

This study examines the role of Artificial Intelligence (AI) in piano education through a qualitative review of six recent academic sources. AI technology has brought about significant transformations in music learning methods, particularly for the piano instrument. Various AI applications such as automated performance feedback systems, musical accompaniment generators, technical error detection devices, and adaptive learning platforms have enabled new approaches to teaching and learning. AI provides instant feedback, tailored exercises to individual abilities, and creates more interactive and flexible learning environments. These innovations are considered to support the development of students' technical skills more effectively, while increasing learning motivation through personalization and ease of access. Furthermore, this study examines the information systems that support these AI applications, including human-computer interaction, audio signal processing, and the use of machine learning models to recognize playing patterns and technical errors. While AI offers significant benefits, concerns arise regarding its limitations in understanding and responding to the emotional aspects of music. AI is not yet capable of fully supporting the development of subjective and complex musical expression. Over-reliance on this technology is also feared to undermine students' critical thinking, artistic sensitivity, and creativity. Therefore, this study emphasizes the importance of a balanced integration between AI technology and human pedagogical roles, with the teacher remaining the primary facilitator in fostering expression, interpretation, and artistic values in piano learning. The study recommends further research on emotionally responsive AI, blended learning models, and long-term evaluation of AI's impact on students' artistic and musical development.

This study aims to compare the effectiveness of the Deep Learning and Differentiated Instruction models in improving junior high school students’ mathematical problem-solving and reasoning abilities. The background of this research stems from the low level of mathematical literacy among Indonesian students, which demands innovative and reflective learning approaches. A quasi-experimental method was used with a Nonequivalent Control Group Design. The sample consisted of two eighth-grade classes at SMP Negeri Satu Atap 01 Ciseeng, each receiving different instructional treatments: one class was taught using the Deep Learning approach, and the other using the Differentiated Instruction approach. The instruments employed included mathematical problem-solving tests, observation sheets, and student perception questionnaires. The data analysis results indicated that the class taught with the Deep Learning model experienced a more significant improvement in mathematical reasoning ability compared to the class using Differentiated Instruction. These findings suggest that Deep Learning-based instruction is more effective in promoting students’ higher-order thinking skills. It encourages deeper engagement with mathematical concepts, fosters critical and analytical thinking, and allows students to construct knowledge through meaningful learning experiences. However, Differentiated Instruction remains relevant in providing learning comfort and addressing diverse student needs, making it beneficial in inclusive classroom settings. The theoretical and practical implications of this research highlight the importance of integrating both depth of thinking (Deep Learning) and flexibility in learning (Differentiation) within mathematics instruction. Such integration could offer a balanced learning environment that supports both cognitive development and emotional engagement, leading to more effective and equitable mathematics education. In conclusion, this study recommends educators and curriculum developers to consider incorporating Deep Learning strategies to enhance students’ mathematical reasoning while maintaining the adaptive and student-centered principles of Differentiated Instruction. Future research could explore hybrid learning models that combine the strengths of both approaches to maximize student outcomes in mathematics learning.

Microteaching is an essential component in preparing students of the Primary School Teacher Education (PGSD) program to become competent professional educators. This study aims to analyze effective strategies for mastering teaching materials during microteaching courses for PGSD students. Optimal mastery of subject matter requires not only a deep understanding of content but also the ability to adapt to the characteristics of primary school students, the use of varied teaching methods, and effective communication skills. This study employs a literature review methodology and analyzes best practices from various educational institutions. The results indicate that strategies for mastering teaching materials in microteaching involve five key dimensions: systematic material preparation through curriculum analysis and in-depth literature study; material organization using a logically structured approach; material presentation with diverse learning models and appropriate media; continuous evaluation using assessment for learning techniques; and self-development through continuous learning and consistent practice. The implementation of this integrated strategy has been proven to increase student confidence, improve the quality of material delivery, and optimize teaching readiness in primary school settings. These findings offer significant contributions to the development of PGSD curricula and the enhancement of the quality of future primary school teachers in Indonesia.

The research aimed to analyze the relationship between the financial literacy of financial report users and the required level of disclosure, and to propose an intelligent mechanism based on artificial intelligence techniques to customize report content. The research variables were identified as: financial literacy (high, medium, low) and disclosure level (basic, medium, advanced), with a study of the effects of age and educational level. The research adopted a mixed methodology (descriptive and analytical) using machine learning models (Random Forest) and analysis of a questionnaire consisting of 15 questions. The research sample included 150 participants from Baghdad Bank and Asia Islamic Bank of Iraq, with 155 questionnaires distributed (electronically and on paper), excluding 5 incomplete questionnaires. The results showed a strong positive correlation between financial literacy and the level of disclosure, where 75% of those with high financial literacy preferred advanced reports. The artificial intelligence model also recorded an accuracy of 82% in predicting the optimal level of disclosure. The research recommended adopting intelligent customizable financial reports through artificial intelligence and enhancing users' financial literacy to improve decision quality.