Reviewerly/exHarmony huggingface dataset:
Pedagogical Model for Creating Individual Learning Paths Based on Educational Maps

The problem of the structure of the learning environment, its properties and the technological basis for its creation is extremely urgent at present. This issue is addressed in numerous studies. An essential role in such an environment is played by individual learning paths. The question of developing a pedagogical model for creating individual learning paths based on educational maps, to which this study is devoted, remains open. The purpose of this study is to develop a pedagogical model for creating individual learning paths based on educational maps. The leading approach to researching the problem is based on ideas of project-based and student-centered active learning. The developed pedagogical model for creating individual learning paths on the basis of educational maps includes four main blocks - target, content, procedural and algorithmic and the block of implementation and evaluation.The target block consists of goals, requirements, methodological approaches and guidelines for creating individual learning paths based on educational maps. The goal is to increase the student’s activity and independence, support positive motivation, and individualize the learning process. As leading principles, we define adaptability, projectivity, and subjectivity. The content block includes a description of the structure of educational maps, technology for creating individual learning paths based on those maps. The procedural and algorithmic block includes a description of the scenarios practical implementation of individual learning paths based on educational maps. The block of implementation and evaluation contains a description of the methods, criteria and the corresponding performance indicators for creating individual learning paths based on educational maps.
The model of export support of Russian education

The article is devoted to the development of educational export, which is one of the priorities of state policy. In 2018, the Federal project ‘Export of education’ of the national project ‘Education’ was launched, which set the task of doubling the number of international students in Russia by 2024. The tasks set are impossible without state support, which is to create favorable conditions for its development at the national (system of support and development of export of Russian education) and interstate (in the framework of cooperation with foreign countries, participation in regional integration associations, international organizations and forums) levels. Taking into account the analysis of international and Russian experience of export support, the author of the article developed and described a model of export support for Russian education, which has its own specific industry characteristics. The model for supporting the export of Russian education includes organizational, legal, informational, financial, and content blocks.
Deep learning models based on automatic labeling with application in echocardiography

Our goal is to apply deep learning (DL) based techniques in the context of medical imaging in order to perform automatic data labeling. Generally, training a neural network requires large amounts of (annotated) data, which is often very difficult to obtain, especially in the medical field. To alleviate this problem, we propose the use of pre-trained models. In this paper, we present two pre-training methods, formulated as self-supervised classification problems. The first one is a binary classification problem, which aims to label echocardiographies according to how they are represented: flipped or non-flipped. For this first task, we achieved 95.83% accuracy. In the second approach we aim to sort into chronological order a tuple of three randomly shuffled frames from a cardiac ultrasound DICOM file. Even though DICOM videos have no semantic labels, we use the temporal dimension as a supervisory signal. Since for each tuple of three frames there are 6 possibilities of arranging them, the sequence sorting task is formulated as a multi-class classification task with 6 classes. For this task we obtained 92.38% operating accuracy. In order to improve the learning performance for this second task, we employ transfer learning methods by re-using learned layers from the first classification task. As a result of the knowledge transfer process, the accuracy increased to 95.43%. This way, we showed that transfer learning and self-supervision hold the potential to yield significant improvements in the learning process of the target task.
Show, Don’t Tell: Visualising Finnish Word Formation in a Browser-Based Reading Assistant

This paper presents the NiinMikäOli?! reading assistant for Finnish.The focus is upon the simplified presentation and visualisation of a wide range of word-level linguistic phenomena of the Finnish language in a unified form so as to benefit language learners.The system is available as a browser extension, intended to be used in-context, with authentic texts, in order to encourage free reading in language learners.
A Needs Analysis in Teaching ESP Writing at Igor Sikorsky Kyiv Polytechnic Institute

The present study aims at considering a questionnaire as an instrument of needs analysis in teaching English for special purposes (ESP).One of key factors in implementing market oriented changes into educational process lies in specifying both employers' and students' needs in teaching ESP.A needs analysis in the form of questionnaires is used to identify the most needed abilities in oral and written specialism oriented communication in English, thus, contributing to determining the content of learning.In National ESP Curriculum, the content covers professional and academic content; situational content (the context within which the materials, activities, etc., are presented); and pragmatic content (necessary practical and useful skills).It also takes into account students' backgrounds and their study and target needs.The content selection for ESP syllabi is specified by questionnaires for university students, young professionals, ESP and subject teachers, administrators.The paper focuses on the surveys conducted in the Institute of Publishing and Printing and the Faculty of Chemical Engineering with the aim to gather information about students' needs in learning written specialism-oriented writing.Examining studies in the field of ESP in general and needs analysis in particular was accepted as the theoretical basis of the study.The research results show that questionnaires are effective tools in specifying the content of learning, defining students' motives in learning written communication.The interpretation of the survey helped to improve the process of teaching and learning outcomes.The findings suggest that students' feedback in the form of answering the questions of questionnaires should be regular practice in the process of teaching.It became clear that writing and using questionnaires as well as analyzing and interpreting their results require special knowledge and skills and should be implemented in the process of developing writing skills in ESP teaching.
Lab 7: Managing and Monitoring Azure Kubernetes Service (AKS)

In this next lab of this workshop, we will focus on common operations related to AKS. This includes enabling the basics of container scalability within the platform, as well as configuring the new Azure built-in monitoring capabilities for these services, using Azure Monitor for Azure Kubernetes Service.
Education Management Information System - Three-Tier Web Application Prototype for Education Workflow

Agriculture education in India is unique with a flexible course credit system.The workflow behind this unique education system needs customizededucation management information software for educational planningand management with a reduced process time in education workflow. Thispaper put forth a prototype of the Education Management InformationSystem (EMIS) developed for Forest College and Research Institute (FCRI),Tamil Nadu Agricultural University, Mettupalayam. Three-tier architectureis used for FCRI-EMIS to be an effective distributed client/server system.The development is carried out in an open-source development platform.FCRI-EMIS is developed with four modules namely: College ManagementInformation System, Degree Management Information System, SyllabusManagement Information System and Student Management InformationSystem to access, generate a report and analyze the identified entities. Thedeveloped prototype is executed and found an effective tool for decisionmaking towards education planning and management
Blockchain Technology Adoption Decisions: Developed vs. Developing Economies

Blockchains as digitized, decentralized ledgers allow recordkeeping of peer-to-peer transactions, thus eliminating the need for intervening trusted third parties. This makes the technology useful in altering business processes and transactions not just across industrial sectors but also across economies. However, little research exists on the factors that impede and sponsor blockchain technology adoption in developed relative to developing country contexts. We highlight blockchain technology issues which sponsor/impede its adoption across developing/developed economic contexts. We focus on assessing the flow of money and land registries in these contexts in relation to the propensity to deploy blockchain systems. We then apply our analytical frame resting on real options principles to explore the decision point at which blockchain would be adopted relative to economic development.
E-Archive Development In PT Haleyora Powerindo Sorong

The development of e-archives is a part of an effort to completely manage to archive at PT Haleyora Powerindo Sorong. This research aims to see the factors that cause e-archives cannot be used optimally and also to develop e-archives as needed. The analytical method is a prototype method. The result of this research is the creation of electronic archives that have been developed with innovative and solutive design, menus and function that answer the factors that cause e-archive not be used optimally.
Analysis Models of Pupil Class Collectives Focused on Efficiency of the Educational Process

The paper presents four models, references for analysis, and approaches of the most important social micro-groups in an educational unit, i.e. the groups of pupils’ classes. The micro-research carried out, consisting in the application of a questionnaire with closed and open questions applied on a group of 711 teachers in Romanian pre-university education, identifies the socio-psychological and socio-pedagogical model as the most effective models for approaching the pupil class and the pandemic period that everyone went through as the determining cause of some changes of approach of the social actors of the Romanian pre-university education system. In order to increase the efficiency of the educational process, it is recommended to digitize it by increasing connectivity in schools, the digital literacy of pupils, the training and development of digital skills among teachers, according to the priorities set by the European Commission for the next period.
PENGARUH MEDIA PEMBELAJARAN ONLINE, MOTIVASI BELAJAR, DAN KOMPETENSI DOSEN TERHADAP KUALITAS PEMBELAJARAN

The aim of this research are: 1) know the direct effect of e-learning/online learning media to quality of learning in economic education students at Unirow Tuban 2) know the direct effect of learning motivation to quality of learning in economic education students at Unirow Tuban, 3) know the direct effect of lecturer competence to quality of learning in economic education students at Unirow Tuban, 4) know the indirect effect of online learning media to quality of learning through learning motivation in economic education students at Unirow Tuban, and 5) know the indirect effect of lecturer competence to quality of learning through learning motivation in economic education students at Unirow Tuban. The sample of this research was part of the Economic Education students at Unirow Tuban in the even semester of the 2019/2020 academic year, amounting to 140. The data in this research were collected through a questionnaire and documentation, then analyzed using path analysis. The results showed that online learning media had a positive direct effect to quality of learning by 10%, and had an indirect positive effect on the quality of learning by 4,2%. Learning motivation had a positive direct effect on the quality of learning by 13.6%, Lecturer competence had a positive direct effect on the quality of learning by 73.7%, and had a positive indirect effect on the quality of learning through learning motivation by 8.4%.Keywords: Learning motivation, Lecturer competence, and Online learning media.
Promotion Media Recommendations on The Acceptance of New Students In Private Educations With The Simple Additive Weighting Method

Ensuring the existence of private universities (PTS) is the number of new students who enrol in each new academic year. One of the ways that private universities STMIK Pelita Nusantara to attract new student candidates is through promotion. Promotion is a communication activity carried out to introduce something to the public and simultaneously influence the wider community to buy and use the product. The purpose of this study was to determine which promotional media was more effective which had an impact on the number of new student enrollments at the private tertiary education institution STMIK Pelita Nusantara using the SAW method as a measuring instrument. The steps taken are: determining the value of the criteria for each alternative, determining the weight, normalizing the matrix, and normalizing the decision matrix to a scale that is compared to all the alternative ratings. The result of the research is the promotion mix with the alternative Worth of Mouth promotion as the best media with a value of 1.
Learning Process Visualization for Distance Learning Teachers: Design Requirements and Visual Encodings.

In distance learning, receiving feedback is critical not only for students but also for teachers — from students. However, there is a lack of empirically validated recommendations for designing visualizations of process-oriented feedback for distance learning teachers. In this work, we propose design requirements and visual encodings for process-oriented feedback, obtained through an iterative design-based method involving intense participation of teachers from online vocational courses. Our results show that i) the prototypes built according to the proposed requirements were perceived as useful by teachers and ii) granularity level control, context, data pre-processing transparency, and correlation of process data to outcome data are essential for a successful visual learning analytics system in the studied domain.
Identificación de brechas digitales en pandemia: Dos experiencias de grados superiores en la disciplina Informática

The global health crisis caused by COVID-19 forced the anticipated shift from the face-to-face to the paradigm. The article proposed to determine different digital gaps in the educational system of the National University of the Northeast. In order to validate the proposal, we chose two higher-level subjects from the Bachelor's Degree in Information Systems. An online survey was designed to quantitatively infer and characterize individuals in relation to certain aspects that affect a typology of digital divide: connectivity, availability of relevant communication and computer equipment, and knowledge of synchronous and asynchronous tools in a learning environment or virtual classroom, the data were processed and descriptive statistical measures applied. The information produced determined the non-existence of evidence regarding the use gap, however, the presence of the access gap and skills gap was observed in 29% of the total number of students interviewed. The proposal was aimed at proposing to implement in other educational areas (for example, in the teaching sector, administrative and teacher personnel), the design of strengthening projects in information and communication technologies in order to ensure having trained human capital in the face of possible emerging.
LiteRate: A Shiny R app for improving data literacy in Indonesia1

The longer a decision-maker has to wait for the statistics, the less useful they are likely to be. This statement is not only related to how fast the data is available, but also how fast the data can be understood. As the leading portal in presenting trusted data in Indonesia, the Badan Pusat Statistik (BPS) website provides complete data that covers various areas, subjects, and domains. However, the visualization of these data seems to be lagging. These data are presented in the form of tables and static graphs that are monotonous and the lack of interactivity discourages users from exploring the data more. To tackle this gap, we developed liteRate which is an interactive web-based visualization/exploration tool that is based on the Shiny R. LiteRate aims to improve the public’s ability to understand the online data of the BPS’ by utilizing web scraping and headless browsers to produce ready-to-visualize data frames. Effective visualization techniques will empower users to quickly gain insight, see patterns, correlation, outliers, and view statistics across topics and areas. LiteRate hopes to increase statistical literacy in Indonesia as BPS continues to generate statistics that leave no one behind.
A tutorial on verifying LinkedList using KeY: Video material

This collection of video material consists of screen recordings of interactive proof sessions with the KeY theorem prover. Each video displays how to create a proof for part of one method contract, or proofs of several method contracts. The method contracts are expressed in the Java Modeling Language with KeY-specific extensions (not shown in the video).
Results of Validity and Practicality Test of ICT-Science Learning Material with Learning Cycle Model for Improving Digital Literacy of Students

The era of industrial revolution 4.0 made a significant impact on various aspects including the world of education. One of these influences is the existence of ICT-based learning material. ICT-based learning material can make learning more effective, interesting, and meaningful. Also, in the era of the 4.0 industrial revolution, a variety of skills must be possessed by someone. However, the real conditions show that the existing science learning material are still lacking to form someone who has skills by the demands of the 4.0 revolution era. An alternative solution to this problem is to develop ICT-science learning material with learning cycle model for improving  digital literacy of students. This type of research is development research. The development model used is the ADDIE model which stands for analyze, design, develop, implement, and evaluate. The instruments used to collect data consisted of validity sheets and practicality sheets given to teachers and students. The data analysis technique used descriptive statistical analysis. Based on the data analysis, two research results were obtained. First, the test results of the validity of ICT-science learning material with learning cycle model are in the very well category with an average value of 91.29. Based on these results it can be indicated that the ICT-science learning material with learning cycle model are valid. Second, the practical results of ICT-science learning material with learning cycle model according to the teacher and students are in the very well category with average scores of 92.08 and 80.69. This indicates that ICT-science learning material with learning cycle model can be said to be practical. Thus, it can be concluded that ICT-science learning material with learning cycle model for improving digital literacy of students are valid and practical.
Nonlinear Normalization Model to Improve the Performance of Neural Networks

An intelligent transportation system (ITS) generally contains an automatic traffic video-surveillance system as a primary subsystem.Such subsystem incorporates the capabilities of neural networks for the efficient and effective recognition and classification of complicated spatial and temporal patterns in real-world traffic scenarios.Notably, the properties of input vectors are the key factors in determining the performance of neural networks.These properties are governed by the method used to normalize these vectors; a simple linear scaling model is widely employed for normalizing input vectors.This study proposes the use of a nonlinear normalization model for input vector normalization.The proposed technique is subsequently applied to neural networks to resolve classification problems encountered when analyzing real-world traffic image data.The experimental results show that the proposed model can produce higher prediction accuracy, when compared to the existing linear-based approach models.This model has the potential to improve the performance in traffic machine vision applications.
The Current State of Progressive Web Apps : A study on the performance, compatibility, consistency, security and privacy, and user and business impact of progressive web apps

Since the late 80s the web has been evolving through new standards, added functionality, device performance and improved user experience. Websites evolved from static information to what is now kno ...
Feature Selection Using Sparse Twin Bounded Support Vector Machine

Although twin bounded support machine (TBSVM) has a lower time complexity than support vector machine (SVM), TBSVM has a poor ability to select features. To overcome the shortcoming of TBSVM, we propose a sparse twin bounded support machine (STBSVM) inspired by the sparsity of the $$\ell _1$$ -norm. The objective function of STBSVM contains the hinge loss and the $$\ell _1$$ -norm terms, both which can induce sparsity. We find solutions in the primal space instead of the dual space and avoid the operation of matrix inversion. All of these can assure the sparsity of STBSVM, or the ability to select features. Experiments carried out on synthetic and UCI datasets show that STBSVM has a good ability to select features and simultaneously enhances the classification performance.
A Study of APIs for Graph Analytics Workloads

Traditionally, parallel graph analytics workloads have been implemented in systems like Pregel, GraphLab, Galois, and Ligra that support graph data structures and graph operations directly. An alternative approach is to express graph workloads in terms of sparse matrix kernels such as sparse matrix-vector and matrix-matrix multiplication. An API for these kernels has been defined by the GraphBLAS project. The SuiteSparse project has implemented this API on shared-memory platforms, and the LAGraph project is building a library of graph algorithms using this API. How does the matrix-based approach perform compared to the graph-based approach? Our experiments on a 56 core CPU show that for representative graph workloads, LAGraph/SuiteSparse solutions are 5x slower on the average than Galois solutions. We argue that this performance gap arises from inherent limitations of a matrix-based API: regardless of which architecture a matrix-based algorithm is run on, it is subject to the same inherent limitations of the matrix-based API.