Reviewerly/exHarmony huggingface dataset:
PENERAPAN MODEL STUDENT TEAMS ACHIEVIEMENT DIVISIONS (STAD) PADA PEMBELAJARAN IPS SISWA KELAS IV SD NEGERI 2 PETUNANG

The research objective was to find out using the Student Teams Achieviement Divisions model in social studies learning for grade IV Elementary School 2 Petunang students significantly complete. The research method used was quasi-experimental, the research design was pretest-posttest group design. The population was all students in grade IV Elementary School 2 Petunang and a sample of 22 students in grade IV which was determined by simple random sampling. The data collection technique used a test technique in the form of 7 essay questions. The average final test score of students was 76.62 with the percentage of the number of students who completed 59.09%. The collected data were analyzed using the t test. based on the results of t-test analysis at a significant level α = 0.05, the value obtained is tcount (1.93) ≥ t_ (table) (1.72), because tcount ≥ t_ (table), it can be concluded that the social studies learning outcomes of students use The Students Teams Achieviement Divisions' learning model was significantly complete.&#x0D; Keywords: Model Student Teams Achieviement Divisions, Social Studies Learning, Learning Outcomes.
PENERAPAN MODEL PEMBELAJARAN COOPERATIVE SCRIPT DALAM PEMBELAJARAN IPS SISWA KELAS IV SD NEGERI NAWANGSASI

This study aims to determine the completeness of social studies learning outcomes for fourth grade students of SD Negeri Nawangsasi for the 2020/2021 academic year after the application of the Cooperative Script learning model. The method used in this research is an experimental method with a pre-experimental research design. The population in this study were all fourth grade students of SD Negeri Nawangsasi and the sample in this study amounted to 28 students who were determined by saturated sampling. The data collected were analyzed using the z-test at the significant level α = 0.05, the zcount was 2.52 and&gt; ztable was (1.64), so it could be concluded that the social studies learning outcomes of the fourth grade students of SD Negeri Nawangsasi used the Cooperative Script learning model. significantly complete.&#x0D; Keywords: Cooperative Script Model, Social Studies Learning, Learning Outcomes, Elementary School
Analisis Bibliometrik Terhadap Publikasi pada Program Pengembangan Profesi Guru dalam Pembelajaran Matematika di Sekolah Dasar

It is still uncertain whether teacher professional development is still in great demand, especially in the field of educational research. This research is aimed as preliminary research to determine the research gaps to be taken, especially those related to teacher professional development programs (PDPs) at the elementary level during last decade. The research method used was a computational mechanism using several applications such as Publish or Perish, Microsoft Excel, and VOS viewer. The number of PDP studies in mathematics learning at the elementary level during this period was 1038 but due to the limited results of the Publish and Perish software, sampling was carried out and 999 data were filtered. The results show that the trend has experienced a downgrade in the last five years, the most research in this focus was conducted in 2015 with 173 works, followed by 2013 with 170. The data showed a fluctuating trend from 2013 to 2017 before declined drastically with only 5 publications in each of the last two years. VOSviewer was used for computational mapping and showed that research opportunities for PDPs should be increased, especially at the elementary level. Based on network visualization, PDP is closely to several other keywords.
Pengembangan LKPD Menggunakan Book Creator Berbasis RADEC di Kelas III SD

The lack of use of technology in developing LKPD makes the appearance of LKPD less attractive for students to work on. Therefore, it is necessary to use appropriate technology and learning models as well as interesting worksheets to increase students' interest in learning. One of them is by using Book Creator. This type of research is development research using the Research and Development (R&amp;D) method using the ADDIE model. The material validity test in the development of this LKPD obtained results of 93.75%, in the very valid category, the linguistic validity test results were 91.6% in the very valid category, and the media validity test results were 96.87% in the very valid category. The percentage of 91.6% for the teacher's response questionnaire and 92.8% was obtained from the results of the practicality test for the student's response questionnaire in the pilot school. The percentage of 95.83% for the teacher response questionnaire and 93% was obtained from the practicality test results for the student response questionnaire in research schools.
Pemahaman Membaca Dan Siswa Kesulitan Memahami Soal Cerita Matematika di Sekolah Dasar

Reading is an attempt to get information from the content of the reading read, by reading a person will get the meaning he is looking for. The low level of reading comprehension of students is a measure of student success in getting a content or information from the Reading, plus in math story problems, of course there are things that students need to understand in order to understand the reading of the math story problem. The purpose of this study is to determine how far the students understand the reading of the text and its relationship with the problem of mathematical stories. The research method used by using literature literature review as many as 30 articles with the latest issue and indexed, adapaun the article to find out and associate concepts and theories on this subject accompanied by the collection of initial data. The results of the study are various speculations emerged from the results of the initial data tests that have been done by the author, such as students do not rewrite the content of the story, students do not answer questions, and student answers are wrong and it turns out there is a link between reading comprehension with understanding math story problems. So this article discusses the ability of students to be able to understand the reading of math story problems, in order to know the problems that exist in the problem.
Movie Recommendation Based System Using Time Series Data

Finding the right movie from a wide selection can be difficult, leading to frustration and wasted time. Recommendation systems offer a solution by providing personalized movie recommendations based on users' interests and preferences. These systems use data analytics, machine learning algorithms and temporal analysis techniques to understand user behavior and provide accurate recommendations. Collaborative filtering algorithms identify similarities between users or movies, while content-based filtering separates movie features based on user preferences. Time series analysis methods collect temporal patterns for dynamic recommendations. The results of the literature review support the effectiveness of movie recommendation systems based on time series data, showing their ability to provide accurate recommendations despite changing information and changing preferences. Real-time data collection improves system efficiency. Overall, the proposed solution aims to improve the movie selection process, save users time and effort, and at the same time improve the movie viewing experience.
Hubungan antara Kebiasaan Membaca dengan Keterampilan Berpikir Kritis Peserta Didik Di Sekolah Dasar

The purpose of this study was to determine the relationship between reading habits and critical thinking skills of students in elementary school. The practice of reading has an impact on the increase of one's knowledge and also on the ability to think critically.This study used quantitative research with the correlational analysis method. The research targets are 50 students in SDN Batu Ampar 09 East Jakarta grade 3. The study was conducted from November 2022 to July 2023 in the even semester of the 2022/2023 school year. In this study, non probability sampling techniques with saturated sampling techniques were used. The results of this study showed the value of r count is 0.618 while r table is 0.288 at the 5% significance level. Therefore, the null hypothesis (h0) is rejected, while the research hypothesis (h1) is accepted, meaning that there is a positive who have level interpretations moderate or sufficient correlation between reading habits and critical thinking skills The results of this study can be used as a reference for the development of learning strategies in primary schools.
Pengembangan Video Pembelajaran Berbantuan Aplikasi Plotagon Pada Materi Memaparkan Informasi Dari Teks Narasi Sejarah

Learning media is an absolute necessity in a learning process. Unfortunately, the learning media available on the market or even schools have not been able to answer the needs of teachers in delivering learning material. Including the absence of learning videos specifically designed for historical narrative text material. The purpose of this study was to determine the analysis of the needs, characteristics, and student responses to the Plotagon application-assisted learning videos. This study uses the Research and Development method. Collecting data using the method of documentation, interviews, observation, questionnaires (questionnaire). The results of the study show that the Plotagon application-assisted learning videos are declared very feasible to be tested on students. The validation results from material experts obtained an average value of 86.8% and from media experts obtained an average value of 89.28%. The results of the teacher's response to the Plotagon application-assisted learning video media received an "Agree" response of 66.7% and a "Strongly Agree" response of 33.3%. The results of student responses received "Agree" responses of 34.72% and "Strongly Agree" responses of 65.28%. The conclusions from this research are Plotagon-assisted learning videos can be well received by users and are a novelty in learning media that are in accordance with the needs of teachers and students so that they have a good impact on the learning process.
Pengembangan Medıa Swıvel Wheel Untuk Menıngkatkan Hasıl Belajar Sıswa Pada Mata Pelajaran IPS Dı Kelas VI Sekolah Dasar

The background of this research is the low student learning outcomes in social studies learning in class VI of elementary school. This study aims to develop Swivel Wheel media in improving student learning outcomes in social studies subjects in class VI SDN No 050668 L. Dalam. The method used in this study is the ADDIE Research and Development model which consists of 5 stages, namely the Analysis, Design, Development, Implementation, and Evaluation stages. The research data was collected using test and non-test instruments. The test instruments were in the form of descriptive questions to measure higher-order thinking skills and student learning outcomes, while the non-test instruments used in this study were (1) questionnaires; (2) interview guidelines; (3) field notes; (4) documentation; (5) literacy assessment. After the data is collected, the data is processed using a qualitative approach using inductive techniques and a quantitative approach using statistical tests. The results of the study show that Learning Media makes the classroom atmosphere come alive, students are enthusiastic about asking and answering questions, and students are also more enthusiastic about participating in learning so it has a very significant effect on student learning outcomes
Analisis Kebutuhan Pengembangan Bahan Ajar Menulis Teks Deskripsi Di Sekolah Dasar

This study aims to analyze the need for teaching materials that are practical and interesting according to the character of fourth grade elementary school students so that they can increase students' optimism in writing. This study uses descriptive qualitative assessment. This technique is used to observe the need to increase the material for writing descriptive texts in elementary schools. This study is for observation and to form patterns of material in order to facilitate learning to write descriptive texts in elementary schools. The data for this study were obtained through questions and answers to class IV teachers as well as distributing questionnaires to all students at SDN Rawasari 05 Pagi. Through the acquisition of questions and answers, the class teacher at SDN Rawasari 05 Pagi showed the need for companion material for theme 3. So according to the needs analysis questionnaire that was carried out, it was shown that 78% of students needed companion material for the theme book. Through the acquisition of questionnaires and questions and answers, this gives the fact that it is necessary to increase the material for theme 3 thematic books which are dominated by technology in order to support the learning stages which have implications for logic and increase the skills of students. The reviewer hopes that the existence of this needs analysis can help students be able to help deal with conflicts in learning to write descriptive texts and this study is a form of educational participation in elementary schools.
The impact of collaborative learning on enhancing speaking skills of college students

Collaborative learning has gained increasing attention in the field of language education, particularly for its potential to enhance spoken English skills and overall learning experiences for college students.This paper provides a comprehensive review of the benefits, implications, and future research directions related to collaborative learning in spoken English classes.The benefits discussed include improved language proficiency, increased motivation, enhanced critical thinking skills, and the development of collaboration competencies.The paper also explores the implications of collaborative learning for both educators and college students, offering practical suggestions for maximizing its benefits.Recommendations for future research focus on examining the impact of different collaborative learning activities, the role of technology, individual and cultural factors.By synthesizing current research and offering practical insights, this paper aims to contribute to the ongoing improvement of spoken English education and promote the effective integration of collaborative learning in language classrooms.
A problem with impulse actions for nonlinear ODEs

In the paper, we consider &nbsp;problem with impulse actions for system of nonlinear ordinary differential equations (ODEs) in the interval. For solving this problem we use a modification of parameterization method by Dulat &nbsp;Dzhumabaev. In the modification of the method we introduce the parameters as the values of the unknown function at the middle of the subintervals of the partition of the considered interval. The problem with impulse actions transfers to an equivalent problem system of nonlinear ODEs with parameters. Conditions for an existence of solution to the equivalent problem are obtained. We also constructed an algorithm for finding of solution to this problem. Finally, we found conditions for solvability to the problem with impulse actions for system of nonlinear ODEs in terms of special matrix composed by the initial data. &nbsp
Extracting generalizable skills from a single plan execution using abstraction-critical state detection

Robotic task planning is computationally challenging. To reduce planning cost and support life-long operation, we must leverage prior planning experience. To this end, we address the problem of extracting reusable and generalizable abstract skills from successful plan executions. In previous work, we introduced a supporting framework, allowing us, theoretically, to extract an abstract skill from a single execution and later automatically adapt it and reuse it in new domains. We also proved that, given a library of such skills, we can significantly reduce the planning effort for new problems. Nevertheless, until now, abstract-skill extraction could only be performed manually. In this paper, we finally close the automation loop and explain how abstract skills can be practically and automatically extracted. We start by analyzing the desired qualities of an abstract skill and formulate skill extraction as an optimization problem. We then develop two extraction algorithms, based on the novel concept of abstraction-critical state detection. As we show experimentally, the approach is independent of any planning domain.
Pose Relation Transformer Refine Occlusions for Human Pose Estimation

Accurately estimating the human pose is an essential task for many applications in robotics. However, existing pose estimation methods suffer from poor performance when occlusion occurs. Recent advances in NLP have been very successful in predicting the missing words conditioned on visible words. We draw upon the sentence completion analogy in NLP to guide our model to address occlusions in the pose estimation problem. We propose a novel approach that can mitigate the effect of occlusions motivated by the sentence completion task of NLP. In an analogous manner, we designed our model to reconstruct occluded joints given the visible joints utilizing joint correlations by capturing the implicit joint connectivity through the attention mechanism. In this work, we propose a POse Relation Transformer (PORT) that captures the global context of the pose using self-attention and a local context by aggregating adjacent joint features. To supervise PORT in learning joint correlations, we guide PORT to reconstruct randomly masked joints, which we call Masked Joint Modeling (MJM). PORT trained with MJM adds to existing keypoint detection methods and successfully refines occlusions. Notably, PORT is a model-agnostic plug-and-play module for pose refinement under occlusion that can be plugged into any keypoint detector with substantially low computational costs. We conducted extensive experiments to demonstrate the advantage of PORT mitigating the occlusion on the hand and body pose PORT improves the pose estimation accuracy of existing human pose estimation methods by up to 16% with only 5% of additional parameters. The code is publicly available at https://github.com/stnoah1/PORT.
Learning Video-Conditioned Policies for Unseen Manipulation Tasks

The ability to specify robot commands by a non-expert user is critical for building generalist agents capable of solving a large variety of tasks. One convenient way to specify the intended robot goal is by a video of a person demonstrating the target task. While prior work typically aims to imitate human demonstrations performed in robot environments, here we focus on a more realistic and challenging setup with demonstrations recorded in natural and diverse human environments. We propose Video-conditioned Policy learning (ViP), a data-driven approach that maps human demonstrations of previously unseen tasks to robot manipulation skills. To this end, we learn our policy to generate appropriate actions given current scene observations and a video of the target task. To encourage generalization to new tasks, we avoid particular tasks during training and learn our policy from unlabelled robot trajectories and corresponding robot videos. Both robot and human videos in our framework are represented by video embeddings pre-trained for human action recognition. At test time we first translate human videos to robot videos in the common video embedding space, and then use resulting embeddings to condition our policies. Notably, our approach enables robot control by human demonstrations in a zero-shot manner, i.e., without using robot trajectories paired with human instructions during training. We validate our approach on a set of challenging multi-task robot manipulation environments and outperform state of the art. Our method also demonstrates excellent performance in a new challenging zero-shot setup where no paired data is used during training.
Forming and Controlling Hitches in Midair Using Aerial Robots

The use of cables for aerial manipulation has shown to be a lightweight and versatile way to interact with objects. However, fastening objects using cables is still a challenge and human is required. In this work, we propose a novel way to secure objects using hitches. The hitch can be formed and morphed in midair using a team of aerial robots with cables. The hitch's shape is modeled as a convex polygon, making it versatile and adaptable to a wide variety of objects. We propose an algorithm to form the hitch systematically. The steps can run in parallel, allowing hitches with a large number of robots to be formed in constant time. We develop a set of actions that include different actions to change the shape of the hitch. We demonstrate our methods using a team of aerial robots via simulation and actual experiments.
Emotion Analysis Using Speech

The main goal of our project is to identify the emotions a speaker evokes when speaking. For example, utterances uttered in states of fear, surprise, excite- ment, anger, or joy are loud and fast and have a large and wide pitch range, whereas utterances uttered in states of depression or fatigue are slow and deep. This is us We use deep learning techniques to build models that can identify human emotions through the analysis of speech and language patterns. The main reason for choosing this project is that speech sentiment analysis has become one of the largest commercialization strategies in which client moods and dispositions play a large role. Therefore, there is an increased demand for products or companies to recognize an individual’s emotions and recommend appropriate products or assist him accordingly. It can also be used to monitor status. More recently, speech recognition and analysis have also been applied to medicine and forensics.
Novel Framework for Real-Time Semantic Image Segmentation

Today Computer Vision has taken a major turn in the Artificial Intelligence domain. The image segmentation technique, which is frequently based on the attributes of the image’s pixels, is the most extensively used approach in com- puter vision for dividing an image into multiple portions or regions. In this paper, we present a thorough examination of our semantic segmentation model developed for the classroom scenario. We created a dataset with over 200 class objects, such as chairs, tables, whiteboards, books, pens, and other classroom items, and trained our model on it to segment classroom images accurately. To accurately segment images and achieve a high level of accuracy, our model employs cutting-edge deep learning techniques like the convolutional neural networks (CNNs) and attention mechanisms. The model obtained an overall accuracy of 90% on the test set, indicating its ability to appropriately segment and identify items in a classroom scenario. Overall, our semantic segmenta- tion model’s results on the 200 classes of classroom environment dataset show that it has the potential to improve safety, accessibility, and organization in educational settings.
A Review on Secure Blockchain Integrated System for Technology Oriented Education Structure: Advantages and Issues

In the technology oriented society every arena is looking for Blockchain tech- nology due its revolution and scope of study. Blockchain technology is a digital register of transactions that is replicated and scattered across the entire net- work. This technology is also applied on education sector due to its immutable characteristics. Adopting Blockchain in education is necessary to store the stu- dent record and digitized the transaction with respect to evaluation, credits and certificates taking care of privacy. The main purpose of this paper is to discuss about the issues related to education sector and to overlook with Blockchain based existing application. The paper adopted a systematic approach to find the relevant implementation for education using Blockchain technology. The result of this study makes available of few advantages and issues related to Blockchain adoption. Finally the paper describes the future research scope in online entrance examination for the transparency issue.