Understanding Of Ability Research Articles

PENINGKATAN PEMAHAMAN PENJUMLAHAN DENGAN TEKNIK MENYIMPAN MENGGUNAKAN ALAT PERAGA DI KELAS II SD NEGERI 218/LIMBUR BARU

ABSTRACT The research problem is the lack of understanding of the material for calculating sequential additions. The aim of this research is to improve understanding of compound addition material by storing techniques through the use of number value racks. Class II students at SD Negeri 218 Limbur who have mild intellectual disabilities will benefit from a better understanding of the concept of multilevel addition operations. This type of research is called Classroom Action Research (PTK). This research was carried out in two cycles, each cycle being carried out in three meetings. Each cycle has four interrelated phases: observation, reflection, action implementation, planning phase, and reflection. The research subjects were four students of SD Negeri 218 Limbur class II. Data was collected through test and observation methods. Quantitative analysis was carried out on the data, and a table was presented showing student learning outcomes. Based on the results of research conducted in cycle I and cycle II, the results of data analysis and reflection show that cycle I research has not met the expected indicators of success, namely better understanding of mathematical concepts because it shows learning outcomes and students' abilities in understanding and carrying out sequential addition operations. using the saving technique, then the average result in cycle II was 62.5%. By using the saving technique, students were able to understand the concept of sequential addition, which not only achieved the desired goal but also improved. This shows that the use of the number value rack display tool can improve students' understanding of the addition material using storing techniques. Keywords : stacked addition, rack of number values.

PENGARUH MINAT BELAJAR TERHADAP KEMAMPUAN PEMAHAMAN MATEMATIS PESERTA DIDIK SEKOLAH DASAR

This research was motivated by the low mathematical understanding abilities of elementary school students. The formulation of the problem in this research is: 1) Is there a positive correlation between learning interest scores and the acquisition of mathematical understanding abilities? 2) Does students' interest in learning have a positive effect on the acquisition of mathematical understanding abilities? The aim of this research is to determine the influence of interest in learning on students' mathematical understanding abilities. The research method used in this research is a quantitative method. The research instruments used were a learning interest questionnaire and a mathematical understanding ability test. Based on the results of data analysis and hypothesis testing using SPSS version 29.0 software, there is a significant positive correlation between learning interest scores and mathematical understanding ability scores, with a correlation coefficient value of 0.498, which means that it is 0.248 or 24.8% of students' mathematical understanding ability. determined by interest in learning. So it can be concluded that interest in learning has a positive effect on the mathematical understanding ability of elementary school students.

Development of Interactive Multimedia Based on ISpring Suite with Corrective Feedback to Improve Student’s Conceptual Understanding Ability

The ability to understand mathematical concepts are one of the abilities that must be achieved. Based on the results of the initial test, the conceptual understanding ability of class IX students at one of schools in Magelang are relatively low. The aim of this research was to produce iSpring Suite-based learning multimedia products with valid, practical and effective corrective feedback in improving students' concept understanding abilities. The research belongs to research and development using the Borg and Gall model. The results of the validity test were 88.44% by material experts in the "very valid" category, and 80.77% by multimedia experts in the "very valid" category. The results of the practicality test were based on the results of the student response questionnaire with an average score percentage of 90% in the "very practical" category, then based on the teacher response questionnaire with a percentage of 88% in the "very practical" category, and based on learning implementation questionnaire, the score was 93.33% with the "very good" category. The results of the test involving 32 students based on the N-Gain were 0.71 in the high improvement category, and the Wilcoxon test obtained Z = -4.941. So, interactive multimedia based on ISpring Suite with Corrective Feedback are valid, practical and effective to improve junior high school students' concept understanding skills in quadratic equation material.

A crossword solving system based on Monte Carlo tree search

Although the development of AI in games is remarkable, intelligent machines still lag behind humans in games that require the ability of language understanding. In this paper, we focus on the crossword puzzle resolution task. Solving crossword puzzles is a challenging task since it requires the ability to answer natural language questions with knowledge and the ability to execute a search over possible answers to find an optimal set of solutions for the grid. Previous solutions are devoted to exploiting heuristic strategies in search to find solutions while having limited ability to explore the search space. We build a comprehensive system for crossword puzzle resolution based on Monte Carlo Tree Search (MCTS). As far as we know, we are the first to model the crossword puzzle resolution problem as a Markov Decision Process and apply the MCTS to solve it. We construct a dataset for crossword puzzle resolution based on daily puzzles from The New York Times with detailed specifications of both the puzzle and clue database selection. Our method achieves state-of-the-art performance on the dataset. The code of the system and experiments in this paper is publicly available: https://www.github.com/lhlclhl/CP.

Exploring Science and Technology Teachers’ Experiences with Integrating Simulation-Based Learning

Science and technology require learners to engage in practical work and inquiry-based learning. In South Africa, schools still need laboratories, textbooks, and equipment for practical work. Considering the above contextual challenges, this paper calls for integrating computer simulation-based learning (SBL) into science and technology education. Very little is known about science and technology teachers’ experiences of simulation-based learning in rural settings. This interpretative study, located at a teacher training institution in South Africa, aimed to explore science and technology teachers’ experiences of integrating simulation-based learning in their teaching. The study was framed within Kolb’s experiential learning theory, which posits that learning is a process of creating knowledge through the transformation of experience. Sixteen practicing teachers enrolled for their honors degree were purposively selected. Data were generated via semi-structured interviews, online interactive discussion forums, and reflective journals. All ethical protocols were observed. NVIVO was used to create tag clouds before thematic analysis could begin. The findings illuminated participant experiences as learning, unlearning, disrupting pedagogies, revisioning best practices in a community of inquiry, and promoting conceptual understanding and spatial visualization. The findings demonstrated an authentic practice of educating and training teachers to integrate SBL into their teaching and the use of SBL in promoting the conceptual understanding and spatial ability of learners in school settings that lack laboratories and functional equipment.

Development of Blog-Based Learning Media With Sarong Context on Lines and Angles Material

This study aims to produce learning media based on blogs with the context of covers on lines and angles material using the PMRI approach which was valid, practical and has a potential effect on the ability to understand mathematical concepts in class VII students of SMP LTI IGM Palembang. The research method used was the development research method using the Tessmer flow (1993) which consists of the preliminary stage (preparation and design stages) and the formative evaluation stage, namely self-evaluation, expert review, one-to-one, small group and field tests). Data collection was carried out using validation sheets, questionnaires, interviews and tests. From the results of the study it was concluded that the blog-based mathematics learning media developed was qualitatively valid in terms of comments and suggestions from the validator, besides that quantitatively the percentage of validity was 4.129 and practically both qualitatively and quantitatively by looking at the comments and suggestions it was stated that blog-based learning media was practically used and the result of the analysis of the practical average of the questionnaire calculation is 76.263. Then the results of a high potential effect on students' conceptual understanding abilities with an average of 82.033.

The Impact of ChatGPT-like Artificial Intelligence on Ideological and Political Education

The rapid development of artificial intelligence technology and application led by ChatGPT has brought a strong impact on all walks of life, and has also brought application possibilities for the ideological and political education work in colleges at the forefront of the Internet to build an "intelligent core". ChatGPT can provide information and knowledge, promote interaction and exchange, assist teaching and research, and provide more comprehensive and diversified support and services for the ideological and political education. However, due to its lack of emotional understanding ability, lack of experience and intuition of human teachers, its application will be accompanied by some risks. In this context, this paper studies the opportunities and challenges of the application of ChatGPT in the network ideological and political education in colleges and universities, in order to improve the quality of the ideological and political education in colleges.

Augmented reality's impact on STEM learning

Introduction: Augmented Reality (AR) is an emerging technology with potential to enhance STEM (Science, Technology, Engineering, and Mathematics) education. This study investigates the impact of implementing AR in STEM learning. Objectives: To evaluate the effectiveness of AR in enhancing students' motivation, understanding, academic performance, and problem-solving abilities in STEM disciplines. Methods: A mixed methods approach with a quasi-experimental design was employed. The study involved 180 university students and 12 STEM instructors from various programs. Data collection methods included standardized tests, questionnaires, interviews, observations, and artifact analysis. Results: The AR group showed significant improvements in academic performance, motivation, and attitudes toward STEM subjects compared to the control group. Qualitative data supported AR's potential to create more engaging and interactive learning experiences. Students reported better understanding of complex concepts and increased interest in STEM fields. Conclusions: Integrating AR in STEM education can enhance academic performance, motivation, attitudes, and comprehension of complex concepts. These findings support the importance of exploring and implementing AR technology in STEM educational settings to improve learning outcomes and foster student engagement.

DLSW-YOLOv8n: A Novel Small Maritime Search and Rescue Object Detection Framework for UAV Images with Deformable Large Kernel Net

Unmanned aerial vehicle maritime search and rescue target detection is susceptible to external factors, which can seriously reduce detection accuracy. To address these challenges, the DLSW-YOLOv8n algorithm is proposed combining Deformable Large Kernel Net (DL-Net), SPD-Conv, and WIOU. Firstly, to refine the contextual understanding ability of the model, the DL-Net is integrated into the C2f module of the backbone network. Secondly, to enhance the small target characterization representation, a spatial-depth layer is used instead of pooling in the convolution module, and an additional detection head is integrated into the low-level feature map. The loss function is improved to enhance small target localization performance. Finally, a UAV maritime target detection dataset is employed to demonstrate the effectiveness of the proposed algorithm, whose results show that DLSW-YOLOv8n achieves a detection accuracy of 79.5%, which represents an improvement of 13.1% compared to YOLOv8n.

Identifying the Mathematical Concept Understanding Ability of Junior High School Students in Learning Linear Function Material

Understanding mathematical and mathematical concepts is one of my fundamental abilities. Therefore, it is necessary to teach mathematics by emphasizing concept understanding so that students are trained to solve problems with the concepts they understand appropriately. This study aims to analyze the knowledge of mathematical concepts of students at junior high school level grade VIII on linear function material. This research is qualitative research with a descriptive method. The research subjects were VIII grade students, as many as 33 students. Data collection through two description questions was then analyzed according to the ability of high, medium, and low student categories. Furthermore, direct interviews were conducted to obtain more in-depth information about students' understanding of mathematical concepts. The results showed that 39.39% of students had high-category mathematical concept understanding ability (ST), 6.06% of students in the medium category (SS), and 54.55% of students in the low category (SR). ST fulfills all indicators with the correct answer, and SS fulfills all indicators, but the answers produced could be more precise. SR cannot apply concepts, so it only fulfills some indicators, which results in errors in solving problems.

Penerapan model pembelajaran RADEC untuk meningkatkan pemahaman konsep pada materi sistem pernapasan manusia Siswa Kelas V SD

Conceptual understanding ability is a skill in which students can explain a matter or concept of knowledge with their personal understanding. However, students' conceptual understanding related to science learning, especially on the material of the human respiratory system is still lacking. This study aims to determine how the application of the RADEC learning model in improving concept understanding in human respiratory system material for grade V elementary school students. This research used experimental method with quasi experimental design nonequivalent control groups design. The results showed that the pretest of students' concept understanding ability was highest with a score of 60 with an average score of 33. After the application of the RADEC learning model, the posttest value of students' concept understanding was highest in the very good category with a score of 100 with an average score of 82. The increase in students' understanding of concepts in human respiratory system material after applying the RADEC learning model has increased significantly as evidenced by the n-gain results on students' pretest and posttest scores with a result of 0.72 which is in the high category indicating that there is an increase in understanding of high category concepts after the application of the RADEC learning model of human respiratory system material.

Experimental Design of Wireless Sensor Network Simulation Teaching Based on OBE Concept

In response to the problem that students cannot effectively master the theoretical knowledge of wireless sensor networks, this study proposes an outcome-based education (OBE) guided teaching method and designs a simulation experiment on wireless sensor networks using the NS3 simulation platform. In the experiment, access point (AP) and station (STA) nodes are set up to present different network environments, and the transmission layer protocols (TCP and UDP) are changed to analyze different network performance. Through the analysis of experimental results, students can gain a vivid understanding of the basic knowledge of wireless sensor networks and achieve the expected teaching goals. This teaching method helps improve students' understanding and application ability of wireless sensor network theory, and promotes their learning and research in related fields.

Analysis of Ability to Understand Mathematical Concepts Class Students XI in Geometric Transformation Materials

The low ability of students to understand mathematical concepts is proven by the majority of students not being able to reformulate the solution to the problem given. This research aims to describe students' ability to understand mathematical concepts for each indicator so that it is known which indicators students experience problems with. The method used in this research is descriptive qualitative. The instruments in this research are test and interview instruments. The research subjects were 26 students of class XI Science 1 SMAN 5 Sukabumi City. Data were analyzed using data reduction, data presentation, and drawing conclusions. In data reduction, researchers summarize the data and classify the data. Based on the results of data analysis, it was concluded that students with high and medium abilities had excellent concept understanding abilities in restating a concept, classifying objects according to the concept, and presenting concepts in various forms of mathematical representation. while students with low abilities are in the good category. Highly capable students are able to restate the concepts they have learned and apply concepts or problem solving algorithms very well. Meanwhile, students with medium and low ability are in the sufficient category. In linking various concepts, high, medium and low ability students have quite good ability to understand mathematical concepts.

Analysis of the Development of Augmented Reality Based Learning Media on High School Physics Material

One of the purposes of using information and communication technology is to increase the efficiency and effectiveness of learning. One technology that can be used is augmented reality (AR) technology. One innovation that can be developed is the development of AR-based learning media. This research discusses the effectiveness of developing Augmented Reality (AR)-based learning media in an effort to increase students' understanding of high school physics material. To measure the level of effectiveness, it is seen from the results of the Validation Test from material experts, media experts, as well as responses from surveys conducted among practitioners. This research is due to students' low understanding in studying physics material which is very difficult to imagine or understand because the concepts are abstract. Therefore, there is a need for innovative learning media so that abstract physics concepts can be explained by visualizing them using Augmented Reality (AR). The research method used was a quantitative approach and literature study as a data collection method. This research took 10 references related to research objectives published from 2017 to 2023. From the analysis carried out, it was found that the use of Augmented Reality (AR) in physics learning can improve students' understanding abilities in physics learning.

Comparative Analysis of Students' Biology Learning Outcomes: Memory and Understanding Aspects

Purpose of the study: This research aims to analyze the learning outcomes of 11th-grade students by examining how they answer questions using memory aspects, evaluate the overall learning outcomes of the class, and identify the differences in learning outcomes between students who use memory aspects and those who use comprehension aspects to solve questions. Methodology: This study is a true experimental study. The population in this study were all students of Public High School 6 South Bengkulu totaling 142 people. The sample was taken using a random sampling technique of 42 people was obtained. This study used a learning outcome test instrument in form of multiple choice questions. Data analysis techniques used include descriptive statistics and inferential statistics. Main Findings: The analysis shows that students' abilities are in the moderate category. Biology learning outcomes are in the high category. The results of the hypothesis test show that the significance value is less than 0.05, so Ho is rejected and Ha is accepted, which means that there is a significant difference in the learning outcomes of class XI science students at Public High School 6 South Bengkulu who use memory and understanding aspects in answering questions. Novelty/Originality of this study: This type of study can provide valuable insights into the effectiveness of both cognitive abilities in understanding and remembering information in the context of learning Biology subjects. In addition, this study can also provide information to educators about more effective ways to help students learn and remember subject matter better.

Efektivitas Model Pembelajaran Examples Non Examples dengan Media Geogebra terhadap Kemampuan Pemahaman Konsep Matematika Siswa

This research aims to analyze the effectiveness of students' conceptual understanding abilities at SMPN 16 Semarang in spatial construction material by utilizing the example non-example learning model with GeoGebra media. This research uses an experimental design with a posttest-only control group and is a form of quantitative research. Class VIIIH was used as the experimental class, and class VIIIG was used as the control class. Samples were obtained using a cluster random sampling approach. Tests and documentation are used in research data collection procedures. The results showed that the average post-test score for experimental class students was while the average post-test score for control class students was From the t-test calculations, the values obtained are and with a sig value. 0.05. Students in the experimental class showed a better level of understanding of mathematical concepts than students in the control group; this can be seen from the findings, which show that tcount > ttable. Therefore, it can be concluded that the Example Non-example model, which utilizes geogebra media increases students' conceptual understanding of spatial construction material.

Meningkatkan Kemampuan Pemahaman Matematis Siswa Melalui Model Problem Based Learning di SMA Negeri 2 Medan

Mathematics is a vital discipline, yet it is often considered complicated by students. This results in their low mathematical understanding, which is very important in learning mathematics to solve problems more easily and relate the concepts understood. “This study used a class action research method (PTK) on students of class XI IPA-3 SMA Negeri 2 Medan in the 2023/2024 academic year, totaling 36 people. In this study, data were collected through observation sheets, learning outcome tests, and documentation to evaluate the mathematical understanding ability of students in class XI-IPA 3 at SMA Negeri 2 Medan. The results showed a significant improvement after the application of the Problem Based Learning (PBL) learning model, as seen from the results of the initial ability test, cycle I test, and cycle II test”.

Embedded Technology Teaching Research and Practice under the Model of Integrated Discipline Competition Project

Embedded technology and application, as the core course of the electronic communication major, is an important professional course for students to engage in embedded software and hardware development in the future. Given the difficulty of embedded courses in theory and the high requirement of practical ability, this paper takes the title of the National Electronic Design Competition for College Students as the content of embedded course research project, carries on the innovation and reorganization of embedded course content, integrates multidisciplinary knowledge, and enhances students’ understanding ability and practical ability from the perspective of practice. At the same time, the use of modern information education resources, the introduction of online video teaching resources, and the use of learning platforms allow supervision of students’ learning progress and effect. The teaching practice shows that this teaching model, which integrates competition topics into theoretical learning and project practice, effectively promotes students’ interest in participating in discipline competitions and enhances their recognition of majors and professions.

GeoGPT: An assistant for understanding and processing geospatial tasks

Decision-makers in GIS often need to combine multiple spatial algorithms and operations to solve geospatial tasks. While professionals can understand and solve these tasks by using GIS tools sequentially, developing workflows for various tasks can be inefficient, as even slight differences in tasks require corresponding adjustments in the workflow. Recently, large language models (e.g., ChatGPT) presented a strong performance in semantic understanding and reasoning. Especially, AutoGPT can further extend the capabilities of large language models (LLMs) by automatically reasoning and calling externally defined tools. Inspired by these studies, we attempt to increase the efficiency of developing workflows for handling geoprocessing tasks by integrating the semantic understanding ability inherent in LLMs with mature tools within the GIS community. Specifically, we develop a new framework called GeoGPT that can conduct geospatial data collection, processing, and analysis in an autonomous manner. In this framework, a LLM is used to understand the demands of users, and then think, plan, and execute defined GIS tools sequentially to output final effective results. In this process, our framework is user-friendly, accepting natural language instructions as input and adapting to various geospatial tasks, which can serve as an assistant for GIS professionals. A systemic evaluation and several cases, including geospatial data crawling, spatial query, facility siting, and mapping, validate the effectiveness of our framework. Though limited cases are presented in this paper, GeoGPT can be further extended to various tasks by equipping with more GIS tools, and we think the paradigm of “foundational plus professional” implied in GeoGPT provides an effective way to develop next-generation GIS in this era of large foundation models.

Revealing the Unseen: AI Chain on LLMs for Predicting Implicit Data Flows to Generate Data Flow Graphs in Dynamically-Typed Code

Data flow graphs (DFGs) capture definitions (defs) and uses across program blocks, which is a fundamental program representation for program analysis, testing and maintenance. However, dynamically-typed programming languages like Python present implicit data flow issues that make it challenging to determine def-use flow information at compile time. Static analysis methods like Soot and WALA are inadequate for handling these issues, and manually enumerating comprehensive heuristic rules is impractical. Large pre-trained language models (LLMs) offer a potential solution, as they have powerful language understanding and pattern matching abilities, allowing them to predict implicit data flow by analyzing code context and relationships between variables, functions, and statements in code. We propose leveraging LLMs’ in-context learning ability to learn implicit rules and patterns from code representation and contextual information to solve implicit data flow problems. To further enhance the accuracy of LLMs, we design a five-step Chain of Thought (CoT) and break it down into an AI chain, with each step corresponding to a separate AI unit to generate accurate DFGs for Python code. Our approach’s performance is thoroughly assessed, demonstrating the effectiveness of each AI unit in the AI Chain. Compared to static analysis, our method achieves 82% higher def coverage and 58% higher use coverage in DFG generation on implicit data flow. We also prove the indispensability of each unit in the AI Chain. Overall, our approach offers a promising direction for building software engineering tools by utilizing foundation models, eliminating significant engineering and maintenance effort, but focusing on identifying problems for AI to solve.