Reviewerly/exHarmony huggingface dataset:
Upaya perpustakaan dalam penguatan literasi di Perpustakaan Archivelago di Kementerian Kelautan dan Perikanan

This paper investigates and analyze Archivelago Library efforts in literacy about marine and fisheries. This research focuses on program participated by the Bunayya Integrated Play Group, on November 16, 2022 in Jakarta. This research is qualitative type with descriptive study approach. Data collection method by interview, documentation and literature study. The data is discussed with the theory of literacy, namely the theory of emergent literacy. Data analysis techniques in the form of data reduction, data presentation, and conclusions. The research subjects consisted of head librarians, librarians, and teachers from schools participating in this program. The results of this study showed that 39 childrens participated and were accompanied by 7 teachers. This program is carried out based on the planning concept in accordance with the Terms of Reference and the Minister of Maritime Affairs and Fisheries Regulation Number PER. 08/PERMEN-KP/2014 concerning Guidelines for Organizing Special Libraries. Based on the findings, the concept of this program focuses on forming mindsets, perspectives on oneself and the environment as a maritime nation. The various activities carried out include library tours, storytelling, watching movies, and coloring. The benefits of this program are not only felt by the participants, but also the Archivelago Library.
THE EIGHTH GRADE STUDENTS' VOCABULARY MASTERY AND WRITING DESCRIPTIVE TEXT ABILITY

The purposes of this research were to find out the correlation between students’ vocabulary mastery and writing descriptive text and the contribution of vocabulary mastery on writing ability. The population of the study was all of the 8th grade students in SMP Negeri 6 Lempuing. In choosing the sample, random sampling was used that involved 134 students. The data were collected by using vocabulary mastery and writing descriptive text ability tests. The data were analyzed by using Pearson Product Moment to investigate the correlation between both variables and regression analysis. The results showed that the coefficient of R-value was 0.557. The category of correlation between vocabulary mastery and writing ability showed a moderate correlation. It was found that there was significant correlation between students’ vocabulary mastery and writing descriptive text ability of the eighth-grade students in SMP Negeri 6 Lempuing. There was also contribution of vocabulary mastery to writing descriptive text ability of the eighth-grade students as much 31%. Therefore, the null hypothesis (Ho) was rejected and the alternative hypothesis (Ha) was accepted. In other words, having a rich vocabulary mastery can make students easier for students to write especially for writing descriptive text.
A Semantic Analysis of Blends in Promotional Advertisements During the 2021 Chinese New Year in Malaysia

This paper presents the word-formation of blending in promotional advertisements, specifically for Chinese New Year celebrations in Malaysia. Blending is a process that combines two or three parts of source words (SWs) which either one has shortened infuse and/or where there is a phonological or graphic overlap of source words (e.g., moo-tastic  moo + fantastic, and Ox-picious  Ox + auspicious). These kinds of words describe a new invention or phenomenon that combines the definitions of the attribute of the two existing things. This study, which applied qualitative methods, examines the meaning of blends and the blending creativity in coining new words in promotional advertisements during the 2021 Chinese New Year or Lunar New Year which is also the Year of Golden Ox. In other words, the Lunar New Year which falls on February 12 in 2021 says hello to the Year of the Golden Ox and bids farewell to the Year of the Golden Rat in the previous year. Hence, this paper analyses 70 blends from promotional ads to measure the semantic, phonological, graphemic, and/or formal motivation of blending and investigate the meaning of blends. Researchers conclude the distinguishing features of blends in promotional ads overlap full words and wordplay, examining the graphological, phonological, stylistic, and semantic motivations. This study highlights that a set of words are chosen as the theme to coin new words each year, especially during the festival season (e.g., ox, moo). Blends are believed to effectively spread a message and attract attention to an idea or a product.
A Study on High School 『Chinese Reading and Writing』 Based on the Digital Literacy Education Model: Focusing on the ‘玩一玩’ Area

本文根据数字素养教学模式对韩国高中汉语教学大纲和现行教科书进行分析, 再根据分析结果针对汉语教科书中的教学活动提出一些建议, 以便提高高中生的数字素养技能。韩国高中汉语教科书≪汉语阅读与写作I≫和≪汉语阅读与写作II≫是适合衔接数字素养教学的教材。因此本文以此两本教科书定为研究对象, 进行研究。首先, 探讨了数字素养相关理论, 而选定“STCPR”模式。再来, 根据“STCPR”模式, 探讨了高中汉语教学大纲。结果发现：教学大纲中提及了数字素养教育, 还包含了一些相关内容。接下来, 根据“STCPR”模式以及教学大纲, 针对两本教科书的“玩一玩”领域进行了分析。分析结果显示：两本教科书都包含了一些适用于数字素养的教育活动, 但从教学活动的类型以及媒体方面来看, 存在着一些不尽之处。因此最后本文提出了若干建议。希望通过汉语课程, 不仅能有效提高学生的汉语能力, 还能同时有效提高学生的数字素养能力。
Open Data Parliament: Implementation And Challenges In Indonesia

Open Parliament is a movement that encourages transparency, participation, and accountability in the legislative process in parliament. One form is data openness, which is a tool for the public to understand the programs and performance of the legislature. Data disclosure in parliament is also carried out to answer public unrest over parliament's attitude which is considered closed in discussing legislation products. The research will reveal how parliamentary data disclosure has been running in Indonesia and other countries, namely Norway, Sweden, and Denmark. The research paradigm is carried out qualitatively and to answer research questions, data collection methods use interviews and literature studies. The results of the study revealed that data openness in Indonesia currently does not fully meet the principles of government data openness, namely primary, timely, license-free, non-discriminatory, and supports the data processing process using machines. Therefore, the Indonesian Parliament needs to make efforts to improve data disclosure services based on the above principles, with the aim of providing easy access to data and meeting people's data needs.
Relationship of Conversational Artificial Intelligence with Academic Anxiety and Academic Motivations in Indian Students

The study investigated the correlation between use of Conversational Artificial Intelligence (CAI) and Academic Anxiety, as well as Academic Motivations among Indian students. A review of the literature indicates that technology plays a crucial role in alleviating academic anxiety. The primary objective of this study was to ascertain if there is an existence of a relationship between the use of CAI and Academic Anxiety in Indian students. To achieve this, data were gathered from students in Indian educational institutions, utilizing two standardized psychometric tools measuring both the use of Chatbots and levels of Academic Anxiety. Pearson Product Moment correlation was computed, the findings from this study revealed a non-significant correlation between these two variables, r(119)= .06, p&gt;.05. Subsequently, a second study was conducted to assess the authors’ adapted theory, integrating Igbaria’s Technology Acceptance Model with Intrinsic and Extrinsic Motivation, specifically in the context of Chatbot usage. Data were again collected from Indian students across various educational levels, employing two standardized psychometric tools measuring the use of Chatbots and Academic Motivation. After the results from Multiple Linear Regression were found non-significant, F(2,134) = 0.87, p &gt; 0.05, a linear regression between Extrinsic Motivation and Use of Chatbots indicated that Extrinsic Motivation was a weak but a statistically significant predictor of Chatbot usage among Indian students, F(1,135)=4.855, p &lt; .05. Consequently, the authors conclude that Extrinsic Motivation constitutes a noteworthy factor influencing students’ engagement with Chatbots, being used by students to enhance academic performance and, concurrently, leading to the reduction of academic anxiety.
Critical reading research and its implications for critical reading skills for Indonesian language teachers: A systematic literature review

The abundance of information sources is the result of rapid technological advances. Rapid technological advances must be balanced with reading skills, one of which is critical reading skills used to filter information sources. This systematic literature review aims to compare the findings of research articles published by the Science and Technology Index (SINTA). The keyword used to find articles in the SINTA database is "critical reading." The search results found 78 articles, then 23 articles were selected that met the criteria for analysis. The reporting items selected for the systematic literature review and meta-analysis were the inclusion and exclusion models. In the last ten years, the number of publications dominated in 2016 with six articles. The types of research used by researchers in reviewing critical reading skills are R &amp; D, quantitative, qualitative, and CAR. The research subjects used by the researchers consisted of class X high school students, class VII junior high school students, class VIII junior high school students, fifth-grade elementary school students, and junior high school teachers. The publication and citation structure reveals that, out of 23 articles, they have been cited 114 times, with the 2016 publication having the most citations, a total of 46 times. Writers who have a track record of publications covering critical reading skills are (1) Nuria Reny Hariyati, (2) Hespi Septiana, and (3) Endah Tri Priyatni, all three of whom have a publication track record of 10 articles. The writing institutions are divided into two institutions, namely schools (13%) and colleges (87%), and the collaboration of writers shows a number that is quite far apart, where 14 authors collaborate and nine single authors. There are eight ideas for reflection by Indonesian teachers in teaching critical reading skills.&#x0D; &#x0D;
The Effect of Show and Tell Toward Students’ Speaking Skill at The Eighth Grade Students of Islamic Junior High School Darul Ulum West Jakarta in Academic Year 2021/2022

This study aims to investigate the effect of Show and Tell Toward Students’ Speaking Skill at The Eighth Grade Students of Islamic Junior High School Darul Ulum West Jakarta in Academic Year 2021/2022. This study used quantitative approach with quasi experimental method using pre-test post-test control and experimental group design. In this research the researcher used cluster random sampling technique with total of sample is 60 students. In order to analyze the data, the researcher used statistical computation by using SPSS software. After conducting the research by giving pre-test and post-test to experimental class by using show and tell and storytelling in control class, the researcher calculate the pre-requirement of research analysis (normality and homogeneity test). The result of normality test shows that p-value (0.069, 0.066, 0.062, and 0.086) are higher than α = 0.05, on the other word the data is normally distributed, while the result of homogeneity test shows that p-value of Pre-Test is (0,756) &gt; α = 0.05 and p-value Post-Test is (0,288)&gt; α = 0.05, on the other word, the data are homogenous. The last step is calculating the t-test, the kind of t-test used is Paired Sample T-test. The result shows that sig. (2-tailed) = 0.000 &lt; 0.05, it means that Show and Tell has significant effect to increasing students’ speaking skill.
Malaria Disease Prediction Using Frequency-Based Machine Learning Algorithms and Ensembles Algorithms

Malaria is one of the most serious and threatening diseases in Sub-Saharan Africa. Its cases increase drastically during the rainy season. It can spread throughout an infected person's entire body in less than an hour. The diagnosis process is time-consuming, and its accuracy is negatively affected due to the lack of technical tools and infrastructure in many laboratories in malaria-prone countries. Hospitals, however, keep patient data during the diagnosis period. Due to the vast amount of diagnostic data gathered and stored on a daily basis in various mediums such as files, it has become increasingly crucial to develop powerful techniques for analysing and interpreting the data. This analysis aims to extract meaningful knowledge and insights that can significantly contribute to malaria diagnosis and decision-making processes. This paper selected four frequency-based algorithms, namely Naïve Bayes, (J48) Decision Tree, ZeroR, and the OneR algorithm, to develop a hybrid model for frequency-based classification algorithms using the available dataset of malaria diagnoses collected from the Federal Medical Centre in Yola, Adamawa state. The research results indicate that the highest accuracy, 88.4%, was achieved by the (J48) Decision Tree model. Additionally, this research employed ensemble methods to enhance the performance of each classification model. The results demonstrated that the accuracy of the Decision Tree and ZeroR models remained the same at 88.4% and 60.9% before and after boosting, respectively. In contrast, the accuracy of the Naïve Bayes and OneR models increased from 79.9% to 87.0% and from 79.8% to 87.6% before and after boosting, respectively. In conclusion, among the frequency-based classification models, the Decision Tree model consistently exhibited the highest accuracy both before and after boosting.
Use of SecureED as a Tool for Software Security Education: An Experience Report

In introducing students to cybersecurity, it is essential to go beyond the theoretical exploration of software vulnerabilities. This paper highlights the importance of hands-on practices in cybersecurity education and introduces SecureED as a tool to facilitate practical learning of software vulnerabilities. SecureED was utilized in a secure software development course to facilitate the practical exploration of threat modeling, security requirements, vulnerability exploitation, and vulnerability mitigation. By incorporating SecureED into the curriculum, students were able to actively engage with real-world security challenges and gain a deeper understanding of the subject matter. Course performance and student feedback supported the effectiveness of SecureED for software security education. However, improvements are needed to enhance accessibility and cross-platform compatibility.
Work in Progress Paper: Learning Software Quality Assurance using Audits

Despite the role that Software Quality Assurance (SQA) plays in developing a quality software product, the techniques taught in undergraduate software engineering (SE) courses are learned superficially. This is evident from new professionals entering industry who lack the skills to consistently implement SQA practices [2] The purpose of this study is to assess the effectiveness of a technique called audits in improving students' ability to learn the SQA process. Organizations such as the International Organization for Standardization (ISO) use audits to assess an organization's development process maturity [17]. These audits follow a systematic process which involves a verbal inquiry of the workflow of the specified development process to produce product feature(s). In this work-in-progress (WIP) paper, we hypothesize that the use of audits as a pedagogy technique improves students' ability to learn SQA techniques and will allow them to apply them in industry projects. We also hypothesize that students' learning of SQA through audits will have a positive correlation with their ability to develop quality products. This paper advances the literature on the use of audits, used in industry to institutionalize processes effective in producing quality products, as a pedagogical technique in an undergraduate SE course at Texas A&M University, a large R1 university.
Proposals for the Promotion of Computing in K-12 Studies in Spain

The information society requires new skills and knowledge about how to cope in a computerized world. Although it is fully assumed in the political and social discourse, it is a neglected subject in formal education. Each nation should analyze how computing is learned in its K-12 education system. This research-to-practice paper presents the report carried out in Spain promoted by two academic associations, which analyzes the state of computing education in Spain in K-12 studies, summarizes some elements of the didactics of computing and analyzes the training received by teachers who will train K-12 students. The report also presents some reflections of the working group in charge, and nine proposals for improvement oriented to policy makers are pointed out.
The Attitudes of EFL Teachers in Kazakhstan towards Continuous Professional Development

This research looks into Kazakhstani EFL teachers' attitudes towards continuous professional development (CPD). It looks at both the beneficial and challenging aspects of their CPD involvement. The study analyzed the attitudes of nine EFL teachers who participated in continuous professional training within the last year. The study aimed to understand teachers' perceptions of their ability to self-control their learning, their needs, and their relatedness to colleagues and course instructors. The qualitative method was utilized in the study, which implied thematic analysis and the interpretation of the findings. Overall, the participants have a positive attitude toward CPD, but they have trouble accessing a wider variety of professional development activities that suit their interests and specific professional needs. The study also highlights how crucial it is to develop and establish policies and programs that foster professional development and deal with these issues. The results can direct the creation and implementation of CPD initiatives in Kazakhstan and other comparable settings.
A Topic Modeling Approach to Characterizing Colombian Teachers' Conceptions of Computational Thinking

This work-in-progress paper will explore the effectiveness of topic modeling to support the analysis of Colombian teachers' conceptions of computational thinking (in Spanish) in an online professional development program. Computational thinking has become a form of literacy as it can help individuals to solve problems. Consequently, governments and bodies of accreditation worldwide have supported educational initiatives, primarily at the K-12 level. However, curricular changes are not enough. Teachers need to be prepared, so they develop the content knowledge associated with computational thinking concepts, practices, and applications in the classroom. To contribute to professional development opportunities geared toward the development of computational thinking pedagogical content knowledge, the Colombian National Academy of Exact, Physics, and Natural Sciences and the Global Center for Equitable Computer Science Education implemented an open online professional development program for Latin American early childhood and elementary educators. More than 100 teachers enrolled in a six-week online professional development program to integrate computational thinking activities from early childhood education. The program included two modules focused on conceptual understanding of computational thinking in early childhood and four more modules where the participants adapted, designed, implemented learning activities, and reflected on what happened during the implementation. As part of the participants' weekly interactions, the program included a Jamboard space, where the teachers answered a set of guiding questions, just like a discussion forum, but as a post-it wall, where they could access all their peers' contributions and questions in a single space.
Combining Gamification and Intelligent Tutoring Systems for Engineering Education

This work-in-progress research-to-practice paper provides ongoing results from the development and testing of a personalized learning system integrated into a serious game. Given limited instructor resources, the use of computerized systems to help tutor students offers a way to provide higher quality education and to improve educational efficacy. Personalized learning systems like the one proposed in this paper offer an accessible solution. Furthermore, by combining such a system with a serious game, students are further engaged in interacting with the system. The proposed learning system combines expert-driven structure and lesson planning with computational intelligence methods and gamification to provide students with a fun and educational experience. As the project is ongoing from past years, numerous design iterations have been made on the system based on feedback from students and classroom observations. Using computational intelligence, the system adaptively provides support to students based on data collected from both their in-game actions and by estimating their emotional state from webcam images. For our evaluation, we focus on student data gathered from in-classroom testing in relevant courses, with both educational efficacy results and student observations. To demonstrate the effect of our proposed system, students in an early electrical engineering course were instructed to interact with the system in place of their standard lab assignments. The system would then measure and help them improve their background knowledge before allowing them to complete the lab assignment. As they played through the game, we observed their interactions with the system to gather insights for future developments, which are presented in this work. Additionally, we demonstrate the system's educational efficacy through early pre-post-test results from students who played the game with and without the personalized learning system integration.
Increasing Accuracy in Predicting Student Test Scores with Regression Using Domain Reduction Technique of Principal Component Analysis

It is difficult to predict student test scores and a number of algorithms are often used for such prediction indicating the importance of such research. To improve the accuracy of predicting student test scores, this research combines Principal Component Analysis (PCA) and Regression. PCA is used to reduce the size of the domain before being used in Regression. For this experimental study, the test scores for both Mathematics and Language were extracted from a public dataset. Test scores were then forecasted using Polynomial Regression. The calculated Mean Absolute Error was used as a criterion of measure for accuracy. Domain values were then subjected to PCA using the same splitting of training and test data, and Regression was also used to train the new set of domain values. Utilizing PCA, this process was repeated for all number of attributes of the domain. Training and test data for the datasets were randomly selected. Each number of domain values was tested in 50 trials. An average mean absolute error was calculated. A statistical T-Test was performed to determines if difference between the Mean Absolute Error recorded were statistically significant. The threshold used to determine if the results were not a statistical coincidence was a p-value of 0.05. Results of using PCA in conjunction with Regression have decreased average mean error substantially. For both >0.00001and Languages test scores using PCA can decrease mean absolute errors by more than 50%. But not all domain sizes improved accuracy. Some produce worse results than not using PCA. This is similar to previous published research. This research demonstrates that PCA can significantly improve student test score prediction when using Regression. Results were comparable to previous research that showed PCA can increase accuracy when using Neural Networks for this problem. PCA is a promising technique to increase the accuracy of such predictive models.