IPAS learning in the Merdeka Curriculum is designed to promote meaningful, student-centered learning through discovery-based activities. However, the learning process in grade IV of SD Negeri 01 Bandar Buat, Padang City was still dominated by conventional methods, with lesson modules that were not optimally designed and low student participation, resulting in learning outcomes that did not meet the Minimum Learning Achievement Criteria. This study aimed to improve students’ learning outcomes and learning activities through the implementation of the Discovery Learning model. This research employed Classroom Action Research (CAR) conducted in two cycles involving 28 fourth-grade students. Data were collected through tests and non-test techniques, including learning outcome tests, observations of lesson modules, teacher and student activities, as well as assessments of students’ attitudes and skills. The results showed an improvement in lesson planning quality from 92.86% in Cycle I to 96.43% in Cycle II, teacher activity from 87.50% to 96.88%, and student activity from 81.25% to 96.88%, all categorized as very good. These findings indicate that the Discovery Learning model is effective in improving the quality of IPAS learning processes and learning outcomes in elementary schools.

The study designs an explainable, lexical feature–based pipeline that examines algorithmic visibility and editorial homogenization in Turkish digital news through measurable indicators. The analytical background data were compiled by capturing, at regular intervals, the headlines and standfirsts (lead texts) of news items featured in the homepage slider/headline area of selected news websites. Following cleaning steps aimed at reducing repetitive template patterns and improving comparability, the data were converted into embeddings. Next, top-level category classification and within-category sub-labeling were applied, making the data traceable in terms of broad agenda clusters as well as micro-themes within categories. Proximity among subcategories was identified using a similarity graph and the Louvain community detection algorithm. The degree of divergence was evaluated via the number of communities and modularity (Q). Community-level representative terms not only characterised dominant discursive patterns within each sub-area but also supported the examination of homogenization dynamics. Overall, the findings indicate that a limited number of top-level categories concentrate on homepage visibility; while more fragmented sub-community structures appear in some areas, integrated structures predominate. This approach, applicable to datasets that do not require large language models beyond labelling, offers a methodological and practical framework for digital journalism research.

An interesting approach to using noisy intermediate-scale quantum (NISQ) devices is hybrid classical-quantum machine learning (QML). In these methods, classical processors handle optimisation and large-scale computation, while quantum hardware is devoted to tasks like feature mapping, nonlinear transformations, or kernel evaluation. Practical near-term demonstrations are made possible by this division of labour, which also mitigates existing hardware restrictions. In specialised fields like molecular modelling, materials discovery, and small-sample learning issues, recent advancements in variational quantum circuits, hybrid neural networks, and quantum kernel techniques have produced promising outcomes. However, scalability and wider applicability are still hampered by enduring issues including noise, barren plateaus, and the expense of repeated measurements. Long-term developments will require fault tolerance, logical qubits, and established software infrastructures, whereas near-term success depends on noise-aware algorithm design, repeatable experimental benchmarks, and enhanced error-mitigation strategies. When taken as a whole, these advancements show a viable path to achieving quantum advantage in machine learning. Quanta 2026; 15: 1–12.

Climate change is one of the most pressing global challenges of the 21st century, influencing ecosystems, biodiversity, and human societies. Microbial communities play a central yet often underappreciated role in regulating Earth’s climate through their involvement in biogeochemical cycles, including carbon sequestration, nitrogen fixation, and greenhouse gas emissions. Due to their rapid response to environmental changes, microbial ecosystems serve as early indicators of climatic perturbations. However, the intrinsic complexity, diversity, and high dimensionality of microbial datasets pose significant challenges for conventional analytical approaches. Recent advances in artificial intelligence (AI), particularly machine learning and deep learning techniques, have demonstrated exceptional potential in modelling non-linear, high-dimensional biological systems. This paper presents a comprehensive AI-based framework for analysing microbial community data to predict climate impacts. By integrating metagenomic sequencing data with environmental variables, the proposed approach leverages unsupervised learning for microbial pattern discovery, supervised deep learning models for climate-variable prediction, and explainable AI techniques to enhance interpretability. The study highlights how AI-driven microbial analysis can significantly improve prediction accuracy of climate-related parameters such as soil carbon flux, methane emissions, and ecosystem resilience under climate stress. Results indicate that AI models outperform traditional statistical techniques and provide meaningful ecological insights. This research establishes a robust interdisciplinary framework that bridges microbiology, climate science, and artificial intelligence, contributing to improved climate forecasting, environmental monitoring, and sustainable policy formulation.

Critical thinking is one of the most valuable skills that the education system can develop in students. In fact, critical thinking skills among students in Indonesia are still relatively low. Choosing the right learning model also helps students understand the material being studied, thereby empowering their critical thinking skills. The purpose of this study was to determine the effect of applying the discovery learning model on improving the critical thinking skills of JHS students in Islamic Education. This research is a quasi-experimental study using a pretest-posttest control group model. The research was conducted at JHS 1 Buay Madang Timur May-June 2025. The research population consisted of seventh-grade JHS students, and the research sample consisted of seventh-grade students in class VII F (experimental group) and class VII G (control group). Data collection techniques for critical thinking skills were conducted using tests. The instruments used were valid and reliable essay questions. The research data were analyzed using descriptive quantitative analysis and an independent sample t-test. The results of the independent sample t-test Sig. (2-tailed) value of 0.00 < 0.05, indicating a significant difference in post-test critical thinking skills between the experimental and control groups.

The aim of this study was to use the discovery learning model with prop assistance to assess students' system thinking skills in physics learning.. This research is a quantitative study with a quasi-experimental design with a nonequivalent control group design. This research was conducted at SMA Negeri 2 Lhokseumawe involving students of class XI. Data coIIection techniques and instruments in this study were pretest and posttest questions, as many as 10 description questions on temperature and heat materials. The average pretest score in the experimental class was 23.125% in the deficient category, while the average pretest score of the control class was 23.50% in the deficient category. Meanwhile, the average posttest in the experimental class was 77.750% in the very good category, and the average posttest in the control class was 57.50% in the good category. Based on the results of the statistical test data using the Independent Samples T-Test, the sig. (2-tailed) of 0.000

This study sought to explore how the hybrid discovery learning (HDL) model can support and enhance students’ comprehending of the material. In particular, it examined the differences in learning outcomes when the HDL approach was implemented with and without the support of a learning management system (LMS). A quasi-experimental design with a descriptive quantitative approach was employed, involving three cohorts: two control cohorts and one experimental cohort. Data were gathered through an assessment of students’ critical thinking skills in a secondary school history class. The results indicated that both forms of the HDL model, whether implemented in a conventional setting or supported by an LMS, contributed significantly to enhancing students’ comprehension. The experimental cohort and Control cohort 2 outperformed Control cohort 1, which was taught using the direct instruction model. However, LMS integration did not yield significant additional benefits. These findings affirm the effectiveness of the HDL model in improving student learning outcomes and offer meaningful insights that can inform the design and implementation of more impactful active learning strategies in the future.

This study aims to improve students’ learning outcomes in Civic Education on the topic of Lingkunganku through the implementation of the Discovery Learning model for fourth grade students at UPT SD Negeri 060923 Medan. This research employed Classroom Action Research conducted in two cycles, each consisting of planning, action implementation, observation, and reflection stages. The research subjects were all fourth grade students. Data were collected through learning outcome tests, observations of teacher and student activities, and documentation. Data analysis was carried out using descriptive quantitative methods to identify improvements in learning outcomes and descriptive qualitative methods to describe learning activities. The results showed that the implementation of the Discovery Learning model effectively improved students’ learning outcomes and learning engagement. In the initial condition, only 45% of students achieved learning mastery. After the implementation of actions in Cycle I, learning mastery increased to 65%, and further improved to 85% in Cycle II. In addition to the improvement in learning outcomes, students’ activity and participation in the learning process also increased, as indicated by active involvement in discussions, the ability to express opinions, and collaboration among students. Based on these findings, it can be concluded that the Discovery Learning model is effective in improving learning outcomes in Civic Education on the topic of Lingkunganku for fourth grade students and supports the creation of active, meaningful learning in accordance with the principles of the Merdeka Curriculum.

This research aims to develop a Discovery Learning learning model with the Think, Talk, Write (TTW) strategy to improve the application of narrative text writing learning in grade V students at UPT SDN 16 Bangkala, Jeneponto Regency. This research uses a Research and Development (R&D) approach by adapting a 4D development model which includes the define, design, develop, and disseminate stages. The research instruments consisted of expert validation sheets, observations, teacher and student practicality questionnaires, and writing ability tests. The results of expert validation showed that the developed learning model was in the very feasible category, with a feasibility score of 92%. The practicality test also showed high results, namely 91% of teachers and 89% of students, which indicates that this learning model is easy to understand, easy to apply, and encourages active involvement of students in the learning process. Descriptively, the results of the pre-test and post-test illustrate a change in students' ability to write narrative texts, from an initial average score of 62.50 to 82.30 after the application of the developed learning model. Thus, this study concludes that the Discovery Learning learning model with the Think, Talk, Write strategy is feasible, practical, and has the potential to support the improvement of the writing skills of elementary school students. This model is recommended to be implemented more widely in Indonesian language learning, especially in narrative writing skills, and can be used as a reference for the development of literacy learning at the elementary education level.

Machine learning for discovery of clinical pain biomarkers following spinal cord injury.

Purpose: This article aims to describe the implementation of Outdoor Learning through English Games and Speaking Practice based on Discovery Learning and to examine its effectiveness in increasing students’ motivation and activeness in learning English in a Islamic boarding school context. Method: This community service study employed a Participatory Action Learning System (PALS) approach involving 27 Grade IX R4 students at MTs Nurul Jadid. The activities were conducted in two outdoor learning sessions integrating English Games and Discovery Learning-based Speaking Practice. Data were collected through observation sheets, motivation questionnaires (pre-test and post-test), field notes, and brief interviews, and analyzed using quantitative and qualitative techniques. Findings: The results showed a significant improvement in students’ learning motivation and activeness. The average motivation score increased from 27–30 in the pre-test to 38–42 in the post-test. Students’ activeness also improved markedly, with active participation rising from 20% to 75% by the second meeting. The outdoor learning environment encouraged greater engagement, confidence, and enthusiasm in English learning activities. Conclusions: Discovery Learning-based outdoor learning activities with English games and speaking practice have been proven effective in increasing the motivation and activeness of ninth-grade R4 students in an Islamic boarding school. Contributions: This study demonstrates that Outdoor Learning integrated with English Games and Discovery Learning-based Speaking Practice can serve as an effective alternative strategy to enhance English learning motivation and activeness in an Islamic boarding school setting.

There is increasing demand to shift from intuition- and experience-based practices to evidence-based education. However, extracting meaningful evidence from real-world educational data poses significant challenges. Traditional approaches to evidence generation, such as randomized controlled trials and systematic reviews, face limitations in both the medical and educational domains due to high costs and ethical constraints. In response, the concept of real-world evidence has emerged as a promising alternative, particularly in medicine and, more recently, in education. Although this approach may be less robust than traditional methods, it offers the potential to uncover broad and practical insights from naturally occurring data. This study explores the use of deep learning for causal discovery in real-world educational data. Specifically, we apply Structural Agnostic Modeling, a method previously validated in biological datasets, to identify underlying causal relationships. In Study 1, we compare this data-driven approach to a traditional hypothesis-driven method. The results demonstrate that this technique can generate both interpretable and novel causal hypotheses, although it occasionally produces plausible relationships in the reverse direction. To address this limitation, we propose an enhanced model, SAM+, in Study 2. Our findings indicate that SAM+ effectively mitigates the identified shortcomings. This research contributes a new methodology for leveraging large-scale educational data and opens new possibilities for advancing evidence-based education.

Halide perovskites (HPs) and their derivatives are emerging as a prominent class of materials for ionizing radiation detection. A unique combination of high atomic numbers, efficient luminescence, tunable optoelectronic properties, defect tolerance and low synthesis cost positions them as a promising alternative to traditional scintillators. The review overviews fundamental principles governing perovskite scintillator operation, from radiation absorption to charge carrier generation and recombination. We present a detailed classification of these materials based on structural dimensionality (3D to 0D) and morphology (single crystals (SCs), polycrystalline films, and nanocrystals (NCs)), alongside a discussion of their synthesis methods and the resulting impact on scintillation characteristics. The review highlights compositional and structural engineering techniques, such as activator ion doping, solid-solution formation, and defect passivation. These strategies yield record-breaking performance metrics that rival commercial counterparts, including high light yields (LYs) (>150 000 ph MeV-1), low limits of detection (LoDs) (<10 nGyair s-1), ultrafast responses (<1 ns), and high spatial resolution (>100 lp mm-1). We also discuss the fabrication of composite scintillating screens using polymer and glass matrices, and explore nanostructured systems offering enhanced flexibility, stability, and spatial resolution. Finally, we address key challenges, such as toxicity, scalability, and long-term stability, and outline promising future directions, including the development of multifunctional scintillators, the engineering of materials for photon-counting detectors, the application of emerging paradigms like supramolecular chemistry and nanophotonics, and advancements in data-driven discovery and machine learning technologies.

Chemistry learning, especially the topic of hybridization, is often considered difficult by students because the concepts are abstract and cannot be clearly visualized through 2D textbook images. This study aims to determine the effectiveness of using Student Worksheets (LKPD) accompanied by a Hybridization Kit (Hy-KIT) through the Discovery Learning model. The research employed a quantitative approach with a quasi-experimental design. The sample (N=72) was selected using purposive sampling and consisted of a control class (36 students) that used conventional worksheets (LKS) and an experimental class (36 students) that used LKPD with Hy-KIT. The research method used was a quasi-experimental design with a Nonrandomized Control Pretest–Posttest design. Data were collected through validated essay-type pretest and posttest questions. The novelty of this study lies in the integration of the 3D Hy-KIT media, which provides a real visualization of orbital shapes, with the Discovery Learning model. This combination serves as an alternative learning tool to significantly enhance students’ understanding of this abstract material. The results showed that both classes experienced improvement, but the experimental class demonstrated higher learning gains than the control class. The Effect Size (ES) calculation produced a value of 0.6, which falls into the medium category, indicating that the LKPD accompanied by Hy-KIT is effective in improving students’ understanding of hybridization concepts.

This study aimed to determine the effect of the Problem Based Learning (PBL) model on the topic of Viruses in Life on students’ critical thinking skills and collaboration at SMA Negeri 2 Kota Jambi. The research employed a quasi-experimental method with a matching-only posttest-only control group design. The population consisted of all tenth-grade students of SMA Negeri 2 Kota Jambi, while the sample included two classes: class X1 as the experimental group taught using the PBL model and class X3 as the control group taught using the Discovery Learning model. Research instruments included an essay test to assess critical thinking skills, as well as questionnaires and observation sheets to measure collaboration using a four-point Likert scale. Data were analyzed using normality and homogeneity tests, followed by hypothesis testing with the Mann–Whitney test. The results indicate that the PBL model has an effect on students’ critical thinking skills and collaboration. In conclusion, the implementation of the Problem Based Learning model is effective in enhancing students’ critical thinking skills and collaboration on the topic of Viruses in Life. Keywords: Collaboration, Critical Thinking, Problem Based Learning, Senior High School, Virus

This article reviews various claims in enhancing multiplication skills of learners through skip counting on a visual manipulative number line and evaluates its contributions within the broader discourse on mathematics education, visual-manipulative learning, and foundational numeracy development. Anchored in contemporary learning theories–including experiential learning, constructivism, sociocultural theory, discovery learning, and cognitive load theory–the study explores how skip counting using visual-manipulative number lines can enhance multiplication understanding among Grade 4 learners. Global and local literature increasingly affirms that manipulatives and structured visual representations strengthen conceptual understanding, reduce cognitive load, and support long-term retention of mathematical ideas. However, gaps persist in synthesizing international findings and contextualizing them to Philippine educational realities, where persistent numeracy challenges continue to surface in national and international assessments. The review concludes with recommendations for teaching practice, curriculum development, and future research, emphasizing the need for pedagogically sound, research-based, and context-responsive approaches to multiplication instruction in Philippine basic education.

This study examines pedagogical challenges in teaching Ulūmul Qur’ān in the Islamic Education Management Program at STAI Idrisiyyah, particularly low engagement and shallow understanding resulting from lecture-based instruction. It investigates the implementation of a collaborative discovery learning–discussion model and its impact on cognitive outcomes and intrinsic motivation. Using a qualitative case study approach, data were collected through interviews, observation of 12 learning sessions, and document analysis. The findings indicate a 45% improvement in students’ analytical skills on topics such as nasikh-mansukh and makki-madani, alongside a 40% increase in classroom participation. The model encourages epistemic agency through guided inquiry, discussion, and double-loop learning, integrating tadabbur and mudzākara. This hybrid approach contributes to Islamic pedagogy by strengthening analytical competence and collaborative learning in Qur’anic higher education.

The effect of Google Earth Pro-assisted guided discovery learning on students' cognitive outcomes

Conventional and boring learning paradigms typically lead to low creativity and learning outcomes in Pancasila and Citizenship Education. Researchers at Primary School 126 Inpres Kariango, Maros Regency, found a new way to attract kids interested in civics. This study examines how the Discovery Learning-based Show and Tell learning technique influences fifth-grade students' creativity and learning at Primary School 126 Inpres Kariango. This research is an experimental quantitative study. The study included 30 fifth graders. Pretests and posttests measured learning outcomes, and observation sheets measured student inventiveness. To assess intervention efficacy, descriptive and inferential statistics were used, including normality, homogeneity, and t-tests. The findings found considerable improvements in all areas: (1) Teacher instruction improved from "Very Poor" (35%) to "Good" (70%). (2) Student participation skyrocketed to "Very Good" (90%) at the final meeting. (3) Students' creativity scores increased from 49.00 (less creative) to 83.67 (creative/very creative). (4) Average student learning outcomes rose from 52.57 to 82.47, with 93.4% reaching moderate to very high. The hypothesis test shows that this strategy boosts creativity and learning. In conclusion, the Discovery Learning-based Show and Tell method enhances student learning in the PPKn subject, fosters creativity, and enhances interaction. This study helps teachers apply student-centered learning practices. This study strengthens our knowledge of how communicative strategies and discovery models improve primary school critical and creative thinking.

This study aims to analyze the effectiveness of the STEM-based Project-Based Learning (PjBL) model in improving students' scientific creativity on the topic "Separation of Mixtures" in class VIII of SMP Negeri 36 Jakarta. The background of this study departs from the need for science learning that is able to foster creativity and critical thinking through contextual and collaborative experiences. The method used is a quasi-experimental with a pretest-posttest non-equivalent control group design, involving two classes of 36 students each. The experimental class used the STEM-based PjBL model, while the control class applied the Discovery Learning model. Data were collected through creative thinking skills tests and analyzed with SPSS. The results showed a significant increase in students' creativity scores in the experimental class (p = 0.000) with a large to very large effect size based on Cohen's d calculation and Hedges' correction. These findings indicate that STEM-based PjBL has a strong practical effect in developing students' scientific creativity. In conclusion, the implementation of STEM-based PjBL is effective in improving creative thinking skills through contextual, collaborative, and challenging learning, and contributes to strengthening the science education approach that is oriented towards developing 21st-century competencies.