Generative artificial intelligence (AI), particularly tools such as ChatGPT, is transforming education by enhancing self-regulated learning (SRL) and critical thinking skills, two essential competencies in the digital era. This study systematically analyzes the impact of generative AI on these skills using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework to identify, evaluate, and synthesize relevant studies. Document searches were conducted in Scopus, Web of Science, and ScienceDirect, focusing on publications from 2022 to 2024, when ChatGPT was first widely adopted. Of the 3,214 documents identified, 557 met the initial screening criteria, and 38 studies were selected for detailed analysis. The findings reveal that 71.4% of studies reported AI’s positive role in SRL, mainly through personalized learning, metacognitive support, and adaptive feedback. Likewise, 62.5% of studies reported its significant role in critical thinking, supporting the process of analysis, evaluation, and reflection. However, researchers cautioned against an overreliance on technology, which one said could take away some students’ ability to think for themselves. Such findings indicate that educational institutions need to change their ways and include generative AI in a model that focuses on areas that foster learner independence. This approach will assist teachers and decision-makers in harnessing the distinctive kitsch of AI technology by creating new learning spaces that are creative and future-oriented.

Growing population and limited energy resources have impacted energy consumption. Limited fossil fuel resources and increased pollution threaten national and human societies. These elements emphasize energy sources. Renewable energy use affects growth. All new energy sources, including renewables, are crucial for global economic growth. Economic and environmental issues have led to new approaches in international environmental law, including the green economy. This study employs structural vector auto-regression (SVAR) to compare the effects and outcomes of increasing the use of renewable energy in the context of economic growth and greenhouse gas emissions in middle income countries (MICs) and high income countries (HICs). The results show that these indicators demonstrate that the production of energy from renewable sources has positive short-term and long-term economic effects with varying contributions. However, renewable energies have a greater impact on the green economy in selected MICs than in selected HICs. Therefore, the promotion of macroeconomic indicators is viewed as one of the reasons for the development of policies to increase energy production from renewable sources in selected countries.

This study discusses the analysis of various variables affecting vocational students' intention to use a Virtual Laboratory (VL) in remote learning. Based on the Technology Acceptance Model (TAM), perceived ease of use (PEU), and perceived usefulness (PU) as exogenous variables. At the same time, attitudes towards VL (A) as an intervening variable. This research was conducted in the learning process of the Power Electronics Practicum for vocational education students. This study involved 105 vocational students from the Industrial Electrical Engineering Study Program, at Universitas Negeri Padang. Research data were analyzed using Partial Least Square-Structural Equation Modeling (PLS-SEM). The study results showed that the exogenous variables (PEU, PU, & A) had a significant and positive effect (directly and indirectly through intervening variables) on vocational students' intentions to use the virtual laboratory to support the implementation of remote learning in the Power Electronics Practicum Course. These factors can be considered in determining the appropriate virtual laboratory application to be applied in the learning process.

Virtual laboratory (VL) has become increasingly popular in Post-COVID-19 to support practical learning in the remote learning system. The use of VL was responded to by students with different attitudes. This study discusses the factors that influence the perception of Industrial Electrical Engineering (IEE) students in responding to the use of the VL in the learning process of the Electrical Machines Practicum Course. Based on the technology acceptance model (TAM), students’ attitudes toward using VL (are influenced by perceived ease of use (PEU) and perceived usefulness (PU). At the same time, PU also acts as an intervening variable. The research involved IEE students of the Electrical Engineering Department, at Universitas Negeri Padang. Data collection was carried out by survey using a questionnaire. Quantitative data were analyzed using variant-based structural equation modelling (SEM), with partial least square (PLS) or PLS-SEM. The results showed a significant positive effect between PEU and PU from the VL used against A. PU’s role as an intervener was also positive in mediating the effect of PEU on A so it became more prominent. Thus, it can be concluded that PEU and PU are the factors that must be considered in choosing VL to be applied to a practical learning process in the remote learning system.

It is generally agreed that solar energy, which can be converted into usable electricity by means of solar panels, is one of the most important renewable energy sources. An energy and exergy study of these panels is the first step in developing this technology. This will provide a fair standard by which solar panel efficiency can be evaluated. In this study, the MATLAB tool was used to find the answers to the math problems that describe this system. The system’s efficiency has been calculated using the modeled data created in MATLAB. When solving equations, the initial value of the independent system parameters is fed into the computer in accordance with the algorithm of the program. A simulation and a parametric analysis of a thermal PV system with a sheet and spiral tube configuration have been completed. Simulations based on a numerical model have been run to determine where precisely the sheet and helical tubes should be placed in a PV/T system configured for cold water. Since then, the MATLAB code for the proposed model has been developed, and it agrees well with the experimental data. There is an RMSE of 0.94 for this model. The results indicate that the modeled sample achieves a thermal efficiency of between 43% and 52% and an electrical efficiency of between 11% and 11.5%.

Student learning outcomes in learning is very important to be used as a reference for indicate of successful in learning. The observation result at grade X TITL SMKN 1 Pariaman identified that there are several problems that influence student learning outcomes, such as communication in learning process just one - way, the students did not master the contents, students tend to be afraid to ask the question, the students out of the classroom and talk with their seatmate. Consequently most of student learning outcomes were under KKM that seen from the pretest. To overcome this problem, research is conducted which seeks to see  an increase in student learning outcomes in subjects " Using the Measurement Results " in Learning Model Cooperative Script at grade X TITL  SMKN 1 Pariaman. Type of this research was quasi experiment with one group pretest – posttest design. Subjects were students at grade X TITL SMKN 1 Pariaman for 2014/2015 academic year that consists of 40 students. Data were collected through the test of pretest - posttest results, 40 objective questions for the pretest and 34 objective questions for the posttest. Improving student learning outcomes calculated by the formula Gain Score of pretest - posttest. This research indicated that there is an increase in student learning outcomes in subjects “Using Measurement Results” in Learning Model Cooperative Script at grade X TITL SMKN 1 Pariaman.