Reviewerly/exHarmony huggingface dataset:
The Necessity and Direction of Improving ‘Field Suitability’ in the History Teacher’s Recruitment Examination Questions Based on the Perception of Teachers

The Recruitment Examination aims to select teachers necessary for the school. Therefore, it is necessary to provide Recruitment Exam questions to measure the abilities needed in the school field.BR Even though the exam system has been improved several times, the content of the evaluation elements has not changed. The questioning principles were also insufficient to reflect the suitability of the school field. Therefore, I looked into the need to improve the suitability with the school field in the Recruitment Exam questions and to understand the specific contents, interviews were conducted with teachers. BR The teachers who participated in the interview had more than 10 years of educational experience, passed the Recruitment Exam, worked at national or public schools, and had experience working at an educational practice school. Three implications were obtained through interviews with them. BR First, it is necessary to reflect the ‘teacher’s abilities needed in the school field’ in the exam questions asked. Its capabilities are organizing and designing history classes, understanding pedagogy content knowledge based on subject knowledge, developing evaluation instruments, and providing feedback. Second, it is necessary to revise and supplement the Evaluation Content Standards. Third, it is necessary to strengthen the capabilities of examiners and secure and utilize human resources.BR Also, improving the Recruitment Examination questions will help strengthen the field suitability of the Teacher Education Curriculum. In addition, as well as selecting excellent teachers, the system should be improved so that teachers who pass the test can adapt well to the school field.
On The L2 LSTM LM’s Knowledge of Implicit Causality

Recently, neural language models (NLMs) trained on vast amounts of raw text have been shown to acquire abstract linguistic representations. In this study, we tackled the robustness of these abstractions by focusing on discourse information determined by implicit causality verbs. Comparing the observed behaviors from human experiments and L1 NLMs, we evaluated the extent to which discourse structure could be acquired by the L2 NLM. We especially probed whether implicit verb biases could influence the probability of pronouns. We discovered that the L2 Long-Short Term Memory NLM is unable to demonstrate knowledge of implicit causality when resolving reference. In other words, the L2 LM has difficulty encoding semantic information in its abstract representational space. The mismatches in syntactic representations and behavior suggest that the L2 LM passes over the learned abstract categories from the data. Our results further indicate that the observed the L2 LM’s behaviors can contradict learning representations of discourse/semantic information, pointing to limitations of language modeling.
Preference of Chalkboard or PowerPoint Teaching as a Teaching Tool in Undergraduate MBBS students in Anatomy: A Comparative Study

Introduction: Traditional chalkboard lectures and modern PowerPoint presentations are integral components of medical education, each possessing distinct attributes and advantages. The primary objective is to ascertain whether students exhibit a preference for one method over the other in terms of facilitating better understanding and ensuring long-term retention. This study investigates the preferences of 2nd and 3rd-year Bachelor of Medicine, Bachelor of Surgery students at B.P. Koirala Institute of Health Sciences, Dharan, Nepal, regarding the teaching methods employed in anatomy classes.&#x0D; Methods: The study was conducted in the Department of Human Anatomy of B.P. Koirala Institute of Health Sciences as a part of coursework. The research duration extended from April 21st to May 18th, 2019. Ethical clearance was obtained, and data collection utilized a pre-validated questionnaire, employing simple random sampling with an expected size of 120 among the 150 students. Statistical analysis was performed using Statistical Package for the Social Sciences version 11.5.&#x0D; Results: The study revealed varied student preferences for chalkboard and PowerPoint teaching methods. PowerPoint was favored for structured lectures, content clarity, and visual aids, while chalkboards were preferred for natural pauses, facilitating note-taking, and promoting long-term retention. Advantages cited included simplicity, interest stimulation, and ease of notetaking or diagram creation.&#x0D; Conclusions: The analysis of data led to the conclusion that both methods have unique merits in anatomy teaching. PowerPoint excels in clarity, organization, and visual aids, while chalkboards shine in student engagement, note-taking, and lecture continuity. A holistic, integrative approach that harnesses the strengths of both methods is recommended for optimal understanding and effectiveness in teaching anatomy.
Relationship between mateverse cryptocurruncies (meta coins) and sustainability indices

Purpose- The purpose of this study is to determine the relationship between metaverse and sustainability indices. MANA token was used as a metaverse indicator in the study. Dow Jones Sustainability Emerging Markets Index (DJS_EMI), Dow Jones Sustainability World Index (DJS_WI), Dow Jones Sustainability Europe Index (DJS_EI) were used as sustainability indices. Methodology- In this research, the dynamic relationships between Metaverse and 3 sustainable indices used in the study were analyzed with a time-varying parameter vector autoregressive (TVP-VAR) model. This method is based on the fixed parameter sliding window VAR approach, first developed by Antonakakis and Gabauer (2017) and later updated by Diebold and Yılmaz (2009, 2012, 2014). Findings- DSJ_EMI variable carries a volatility spread of 24.85% to “DSJ_WI”, 24.81% to “DSJ_EI” and 25.40% to “METAVERSE”. “DSJ_WI” has a 59.68% volatility spread to other variables. The variables “DSJ_EMI” 25.04%, “DSJ_EI” 25.10% and “METAVERSE” 24.69% carry out volatility spread. Finally, while 70.79% of the volatility change in the "METAVERSE" variable is due to itself, a total of 29.21% is due to other variables. The variables “DSJ_EMI” 9.74%, “DSJ_WI” 9.74% and “DSJ_EI” 9.73% perform volatility spread. Conclusion- Mana (Decentraland Token) is the cryptocurrency used in the virtual reality platform called Decentraland. Metaverse refers to a digital universe called virtual reality, augmented reality and virtual world. Decentraland is a decentralized virtual reality platform that allows users to create, trade and interact with their own digital content.As a result of the analysis, it was determined that MANA, a Metavarse crypto asset, spreads volatility to sustainability indices. In other words, the MANA token spreads volatility to sustainability indices. Keywords: Metaverse, metaverse cryptocurrincies, meta coins, sustainability ındex, TVP-VAR JEL Codes: C32, C55, C58
Employees engagement on the performance of Tanzanian public higher learning instıtutions: a case of institute of social work

Purpose-This article aimed at analyzing the influence of employees’ engagement on public higher learning ınstitutions performance in Tanzania. The performance of organizations worldwide depends on many factors including the availability of talented, committed and engaged employees. Hence, employees’ engagement has an impact on organizational performance and national development at large. Methodology- A quantitative research strategy and a positivism approach were used in the study. The article applied the correlation research design. Multiple regression analysis was used to analyze data from 84 questionnaires from the Institute of Social Work, Dar es Salaam. Three hypotheses were tested to verify the model on the Employees’ engagement on organizational performance. Findings-The results demonstrate that Employee Involvement (EI), Employee Working Environment (EWE) and Employee Motivation (EM) have positive influence on Organizational performance (OP). Conclusion- Managers in public and private organizations should seriously consider engaging employees in various decisions and duties performed at work in order to continue improving the performance of the organizations. Keywords: Employees’ engagement, organizational performance, working environment, involvement, motivation JEL Codes: M31, E21, D11
The Role of Knowledge Management Processes in Enhancing the Quality of Banking Information Systems: An Applied Study in the Iraqi Islamic Banking Sector

The study aimed to identify the role of knowledge management processes in enhancing banking information systems in Iraqi Islamic banks (Iraqi Islamic Bank for Investment and Development, National Islamic Bank, Al-Elaaf Islamic Bank, Islamic Cooperation Bank for Investment, Al-Ataa Islamic Bank for Investment and Financing). The total number of employees in these banks was 2,300 across all branches. A random sample representing senior, middle, and executive management was selected, totaling 320 individuals. Various statistical methods were used to achieve the study objectives, relying on structural equation modeling using the SmartPLS3 software. The study reached several results, the most important of which was the statistically significant relationship. It was found that Islamic banks in Iraq have shown an acceptable level of attention to knowledge management processes. However, they still need to exert more effort in practicing knowledge generation, storage, and sharing to activate and enhance banking information systems. The study recommends that Islamic banks in Iraq provide continuous training and educational programs for employees to increase awareness of the importance of knowledge management and enhance effective practices in knowledge generation, storage, and sharing. Furthermore, the study suggests conducting future research by introducing other variables, such as financial technology and artificial intelligence, to enhance banking information systems
“Third mission” of the university in the context of interaction between the academic community and the NPO-sector

The article actualizes the problem of the “third mission” of universities. Referring to the relevant foreign and domestic scientific works, the author considers the definition of the “third mission” and proposes to dwell on the peculiarities of the realization of the “third mission” by Russian universities — the social orientation of domestic universities and the interaction with the NPO-sector, the refusal of commercial understanding of the “third mission”. As part of the development of the scientific concept of the “third mission” of universities, an attempt is made to justify the need to include in its third element (“social component / social involvement of the university”) an additional criterion — the development and introduction in the curricula of modern Russian universities of courses/subjects aimed at studying various forms of social activity of citizens (whether it is volunteer activity or participation in the work of public organizations). In the author’s opinion, it is the presence of this indicator in the work of modern universities that will allow to consider the concept of the “third mission” more complete, comprehensive, and accomplished. The theoretical material of the article is diluted by practice: using sociological methods of research, the author conducted a survey of full-time and part-time university students who studied the course “Sociology of NPO”. The results of the study are characterized by relevance and scientific novelty, implemented in university courses to promote harmonious interaction between the academic and NPO-community, and, consequently, the successful implementation of the ‘third mission’ of universities.
Influence of the accuracy of academic performance assessment on the effectiveness of education at University

Progress control is an essential component of the educational process in universities. Assessment influences students’ motivation and learning strategies, as well as curriculum development. Errors in assessment cause distortions in the feedback of the student-teacher system and lead to a decrease in the effectiveness of teaching. The paper examines the influence of the accuracy and reliability of academic performance assessment on the effectiveness of learning at the university. The methodological basis of the study was the methods of conceptual modeling, analysis of scientific publications and generalized practical experience. A conceptual model of the impact of grades on students’ learning has been proposed and researched. It is shown that with a positive systematic shift in the average teacher error, the quality of learning decreases. The impact of inaccurate assessments on students’ motivation is also considered. Ways to increase the objectivity of academic performance assessment are proposed: formalization of grading criteria, a grade-rating system, the use of standard test programs and collegiate assessment methods. It is anticipated that future research in this area will focus on innovative assessment methods, the impact of technology on assessment accuracy, and the role of collegiate and self-assessment in improving reliability.
GUI Based Advanced Modulation Techniques Using Python

Modulation is a process of modifying a signal to transmit information over a communication channel. It is an essential part of modern communication systems, and it plays a crucial role in wireless, satellite, and optical communications. Modulation techniques can be broadly classified into two categories: analog modulation and digital modulation. In this strategy, we aim to explore different modulation techniques using the Python programming language. Python is a popular language for scientific computing and signal processing, and it provides a rich set of libraries for numerical analysis and data visualization. The main objective of this strategy is to simulate and analyze various Advanced modulation techniques using Python
Personality Detection Based on Tree Drawing Using Convolutional Neural Network

Personality is one of the unique things that humans have. This theory is often used to determine a person's personality condition, including cognitive style. One way to analyze personality is to use psychodiagnostics using the Baum test. This method expresses a person into the image of a tree. This tree image is divided into three large parts, namely the leaf/crown represent the super ego, trunk represents the ego, and the roots represent identity. Currently, the assessment of Baum test results is still carried out manually by psychologists, which takes a long time and is detailed. The Convolutional Neural Network (CNN) method is one of the best methods for classifying image patterns. In this research, we will apply the CNN method to detect personality based on tree image patterns with limitations on the crown/leaf and trunk. Based on the test results, it was found that the CNN method could detect a person's character based on tree image patterns with details of leaf/crown accuracy of 63% and trunk of 79%. The contribution of this research is the use of deep learning to detect a person's personality automatically.
Digital Library Conceptual Design

This research proposes the concept of digital library design at the Nurtanio University Faculty of Social and Political Sciences (FISIP) Library using the Software Development Life Cycle (SDLC) with a waterfall model consisting of planning, analysis, design and implementation and using the Unified Modeling Language (UML) for modelling and documenting the system. Currently, FISIP Nurtanio University manages its library using Senayan Library Management System (SLiMS) 8 Akasia, a free web-based open source software. SLiMS 8 Akasia has provided basic services such as membership management, visitor control, circulation services, and online public access catalogue (OPAC). However, to enrich the library collection, this research proposes a concept that allows lecturers at FISIP to upload their PDF files (e-books) as an additional collection in the library. Although the e-book feature is already available in SLiMS 8 Akasia, currently only librarians or library managers can upload pdf files. This concept aims to provide lecturers with the opportunity to contribute to expanding the digital library collection and increasing access to various information sources.
K-Means Clustering for Crime Cluster Analysis in District Prosecution Office of Indramayu

Crime is a criminal behavior that often causes problems in society with a variety of crimes that often occur such as murder, assault, rape, theft, fraud, embezzlement, narcotics and. In Article 35 paragraph (1) letter K of Law No. 16 of 2004 concerning the Attorney General of the Republic of Indonesia as amended in Law No. 11 of 2021 states that the Prosecution Office is a government institution whose function is related to judicial power to prosecute and other power abide by law. K-Algorithm Means is a non-hierarchical clustering algorithm that has capability to group data in large quantity, quickly and efficiently. In this paper, data from 217 cases tested from Indramayu District Attorney during January 2022 until December 2022. K-Means algorithm was successful to classify relationship between criminal cases and which prosecutors whom handling them. The result using optimal K=3 formed three cluster which consists of Cluster C1 = 9 types of cases, Cluster C2 = 9 types of cases Cluster C3 = 9 types cases with members C2 and C3 have the Global Unique, Domination, and Share characteristics within each cluster.
Application of Agglomerative Hierarchical Clustering (AHC) for Grouping Prospective Scholarship Recipients

Scholarships are a form of financial aid provided to individuals to support their education. Scholarships can be granted by educational institutions, governments, organizations, or individuals as a means of assisting with educational expenses. Scholarships can take various forms, including cash grants, tuition waivers, assistance in purchasing books or educational supplies, or a combination of these forms of aid. Scholarship recipients are typically selected based on specific criteria such as academic excellence, financial need, special talents or interests, or achievements in a particular field. The current method of selecting scholarship recipients involves evaluating the characteristics of students who are deemed outstanding and actively engaged in the learning process. Due to the large number of students and limited scholarship quotas, this process often consumes a significant amount of time, and the selection of scholarship recipients may not be entirely accurate. To aid in the selection of scholarship recipients, data mining techniques are employed, specifically the clustering method. Agglomerative Hierarchical Clustering (AHC) is one of the clustering algorithms capable of grouping a set of data into specific data clusters. The data analyzed for the determination of scholarship recipients include academic performance data or grades, extracurricular activity data, economic data, and student achievement data. By using data mining and clustering methods, educational institutions or organizations offering scholarships can analyze the data of potential scholarship recipients to identify groups with similarities based on specific criteria. This approach can make the selection and grouping of scholarship candidates more efficient and objective.
Integration of Function Point and Earned Value Management Methods in Information Systems Project Development Evaluation

The management of a software project such as an information system requires control of each activity so that the implementation of the project is always controlled. One of the parameters in software development is its complexity, while in project activities, time and cost elements are the main priorities. This research aims to integrate the function point (FP) method which is intended to measure the complexity of the information system software to be built and earned value management (EVM) to control the time and cost of the project. The research flow begins by identifying the needs of the information system project and measuring the level of complexity, followed by calculating the project development time and cost to ensure that the information system project work can run and be controlled according to the required time and cost. The research results indicate that the function point method and earned value management can be utilized to organize and control information system software development projects and it can provide project work support decisions to make it easier for project managers to see the parameters can be used as solutions to optimize the work of an information system development project.
An Examination of Plastic Bag Consumption by Age, Gender, and Spending Using K-Means and Elbow Method

Indonesia is identified as the second major source of plastic waste in marine ecosystems, an unsettling finding. The present condition of the situation presents a substantial hazard not alone to the varied marine ecology, but also to the existence of coastal populations and sectors such as marine fishing and tourist industry. The extensive usage of plastic bags has become an important component of Indonesia’s dilemma of plastic waste, particularly in relation to plastic shopping bags. This research investigates the consumption patterns of consumer plastic bags through the analysis of factors like age, gender, and expenditure levels. The best number of clusters for grouping comparable customers was identified using K-Means clustering and the Elbow Method. The study revealed six discrete categories of plastic bag consumption, therefore emphasizing the influence of demographic factors such as age, gender, and spending habits on consumer conduct. It is worth mentioning that middle-aged female customers who engage in high levels of expenditure have been seen to have a lower rate of plastic bag usage. The findings of this study can be utilized to develop focused interventions aimed at mitigating the usage of plastic bags.
UMTCSF: A Graduate Forum Platform Utilizing an Ensemble Similarity Model

Online forum platforms have emerged as highly popular digital communities for seeking and sharing valuable information. Within these platforms, searches are typically constrained to keyword-based queries. However, the presence of noise in keywords, such as spelling errors or abbreviations, often impedes accurate information retrieval. The impact of this noise on search results poses challenges to both the effectiveness and efficiency of the retrieval process. This study introduces an ensemble similarity model that combines the Vector Space Model (VSM) with edit distance models to enhance thread analysis within a graduate discussion forum. The UMT Computer Science Forum System (UMTCSF) serves as an online platform for Computer Science students to engage in discussions encompassing questions, answers, and topic exploration. Operating in real-time through a web-based application, UMTCSF employs similarity analysis while effectively addressing keyword search noise. An ensemble similarity model demonstrates its potential and practicality in improving search result rankings. By adeptly combining different models and addressing keyword-related challenges, UMTCSF presents a valuable solution for facilitating efficient and accurate information retrieval within the realm of graduate forum discussions.