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Science lessons in primary school significantly contribute to the early development of logical, scientific and systematic reasoning skills.   However, learning science can be challenging, especially when it comes to understanding abstract concepts and cause-and-effect interactions.   This is due to the fact that, as per Piaget's theory, primary school students are still in the concrete operational stage and have limited cognitive growth. Data regarding abstraction ability and causal reasoning in the context of science education were collected from various scientific sources using the literature review research methodology.  According to the research findings, STEAM integration, project-based learning strategies such as Project Based Learning (PBL), and the use of real and visual aids can help lower learning barriers. Successful learning is also influenced by the teacher's role as facilitator, which involves presenting the material in a relevant and contextualized way and fostering a positive learning environment. Real-world examples and exceptional examples, such as the use of worksheets based on cause-and-effect relationships and basic experiments, demonstrate how useful these strategies are for improving abstract thinking and understanding of cause-and-effect relationships. Developing innovative teaching methods based on practical, exploratory and integrative experiments is essential for maximizing the scientific understanding of primary school students.

This study compares the scalability and maintainability of three prominent programming paradigms-functional programming (FP), object-oriented programming (OOP), and declarative programming (DP)-in the context of distributed data processing systems. The research aims to evaluate how each paradigm performs under increased data volume and its ability to handle complex operations, while also assessing the ease of maintenance through code readability, modularity, and the flexibility of updating and debugging. The study employs a comparative experimental design, implementing identical data processing tasks, such as data aggregation, filtering, and transformation, across each paradigm. Key findings indicate that FP and DP outperform OOP in terms of scalability, with their stateless nature and high-level abstractions enabling efficient parallel processing and task distribution. FP, with its emphasis on immutability and concurrency, and DP, with its focus on describing desired outcomes rather than implementation specifics, both demonstrate superior performance in handling large datasets. However, while OOP excels in modularity and flexibility, its reliance on mutable state and shared resources hampers its scalability in distributed environments. In terms of maintainability, both FP and DP offer clearer, more maintainable code due to their abstraction levels, making them easier to update and extend. OOP, while modular, presents challenges in managing mutable state, complicating maintenance. This paper concludes with practical recommendations for developers on when to use each paradigm based on system requirements and suggests areas for future research, such as hybrid paradigms and long-term maintainability studies in real-world applications.

Computational thinking is the process of solving issues by using mathematical ideas and concepts. Systems problem solving, data analysis, abstraction, algorithms, and information representation are some of these ideas. The purpose of this study is to determine how mathematical problem-solving techniques for computational thinking function. Systematic literature observation was the research methodology employed in this study. A topic area of interest's existing research as well as pertinent, targeted research questions are found, reviewed, disseminated, and interpreted using the systematic literature review (SLR) technique. Journals may be found and evaluated methodically using the SLR approach, with each stage according to preset guidelines or rules.

Computational thinking is the ability to solve problems and design systems using concepts and techniques generally associated with computers and computer programming. The aim of this research is to conduct a literature review, namely to determine the application of computational thinking in mathematics learning. The technique used is the Systematic Literature Review (SLR) strategy. SLR is a research method that aims to identify, study and interpret data in journals systematically with specified stages. The conclusion obtained from the research results is that the application of computational thinking in mathematics learning can be done using four foundations of computational thinking, namely: (1) Decomposition, namely the problem is divided into small parts, (2) Pattern recognition, namely the process of identifying patterns or sequences of problems, (3) Abstraction, namely consideration of the important parts of a problem, and (4) Algorithm, namely a series of instructions for solving the problem. Examples of its application include the use of interactive mathematics software, mathematical simulations, problem-based learning with technology, adaptive learning and the use of educational games.  

During the period of compulsory education in Indonesia, which is 12 years, the government requires mathematics as the main learning subject for extracts which will continue to have an impact on people’s lives. The level of ability in a field of science must be measured to obtain valid data for the development of education in Indonesia. The use of Geogebra Mathematics Software in schools in Indonesia is not surprising at this time, technological developments have made the use of Geogebra mathematics software commonplace. This research is a Systematic Literature Review, in this research the author analyzes and compares several articles obtained from the internet or digital databases, for example Semantic Scholar or Sprinter Link. The articles that have been found are then selected according to the title researched, so that several reference articles are obtained. The research results show that the use of Geogebra mathematics software in learning has a great influence on students’ computing abilities. Geogebra is a media with a visual, analytical and numerical approach that can be solved using algorithms that require computational capabilities to operate. There is empathy in computational thinking, namely algorithmic thinking problem solving, pattern recognition, and abstraction and generalization.

Computational Thinking is a way of thinking that refers to the ability to solve problems using concepts used in computing. Computational thinking is a way of thinking in solving problems that students must develop in the digital era. This research aims to examine the importance of computational thinking in improving students' mathematical problem solving abilities. The type of research used is qualitative research using a literature study approach in the form of books, notes, journals, reports of relevant research results, as well as the results of observations. The results of the analysis show that it is very important for students to have computational thinking in order to improve their mathematical problem solving abilities. Computational thinking involves solving problems using a logical and systematic mindset that involves selecting and using algorithms, data representation, problem decomposition, abstraction, pattern recognition and hypothesis testing. Computational thinking has become an important and essential skill for humans in the 21st century. Educators must advocate the importance of integrating learning with computational thinking concepts into the educational curriculum. Computational thinking has an important role in learning. This can be useful for improving mathematical problem solving abilities. Apart from that, computational thinking can also develop critical, creative and analytical thinking skills in solving complex problems, both in the context of computing and everyday life.    

The aim of this research is to provide a study of the computational thinking process of mathematics learning. This research uses library research methods. The data obtained is the publication of research articles in scientific journals. Data analysis includes three stages: organize, synthesize, and identify The result of previous research is students' computational thinking abilities need to be improved in abstraction and algorithms.      

most psychic elements plays a role in the development of individual personality is the self concept, which is an overall self-concept self image that includes a person’s perception of himself, feelings, beliefs, and values associated with him. The self concept is an important aspect in a person, in which the self concept is a frame of reference to interact with the environment. When people perceive themselves, give meaning and shape abstraction assessment of him means he showed self-awareness and the ability to get out of myself to see him as he did to the world outside himself.

In the modern age, technological advancements are undeniably progressing at a rapid pace. Throughout its rapid progress, technology has had an impact on various aspects of life, and education is one of the fields affected by it. In the context of technological advancement, both teachers and students acquire important skills known as computational thinking. Computational thinking refers to the ability to systematically solve problems using logical reasoning and step-by-step decision-making for problem-solving. Computational thinking has a direct relationship with students' mathematical learning, especially in the process of tackling mathematical problems. The purpose of this research is to investigate the influence of computational thinking on mathematics learning, with a specific focus on algorithm analysis in programming. The research methodology involves a comprehensive analysis of related literature to delve into the research topic, using a literature review method. The results of this research indicate that computational thinking can be measured using specific indicators that play a crucial role in mathematics learning. Students' ability to apply computational thinking techniques to solve mathematical problems can be determined based on indicators such as decomposition, pattern recognition, abstraction, algorithmic thinking, and generalization.

According to Munandir, spiritual intelligence is composed of two words, namely "intelligence" and "spiritual". Intelligence is a person's ability to solve the problems they face, especially problems that require the ability of the mind. Various limitations put forward by experts are based on their respective theories. Furthermore, Intelligence can also be interpreted as abilities related to abstractions, the ability to learn something, the ability to handle new situations (Munandir, 2001: 122). In addition to the above understanding, there are a number of experts who argue that spiritual intelligence is the ultimate intelligence or peak intelligence, including Zohar and Marshall in their book entitled: "SQ: Spiritual Intelligence The Ultimate Intelligence"

The aim of this study is to find out the ability to analyze the implied meaning of the text structure of the saga "The Miskin" Muhammadiyah Makassar SMA students. The type of research used in this research is descriptive quantitative research. This research was conducted at SMA Muhammadiyah 1 Unismuh Makassar. This research took the number of subjects as many as 27 students from class X IPA. Selected by using purposive sampling. The results of the analysis are based on the Ability to Analyze Implied Meanings in the Text Structure of the Hikayat "The Miskin" Class X SMA Muhammadiyah 1 Unismuh Makassar. The research results showed that only 11 students achieved the KKM standard with a percentage of 40.74% and students who scored below the KKM still had 16 students with a percentage of 50.26% which was still very low. it is known that the average score in the abstraction analysis is 16.81, the orientation analysis is 15.51, the complication analysis is 14.92, the evaluation analysis is 9.88, the resolution analysis is 9.74, the coda analysis is 8, and the overall average in the assessment and final score 74,66. So the ability to analyze the implied meaning of the text structure is still very low.