Reviewerly/exHarmony huggingface dataset:
Academic Achievement of Undergraduate Nursing Students in The Faculty of Nursing Before And During Corona Pandemic

Background: Universities were abruptly obliged to move to e-learning as a result of the Corona pandemic, and the University of Tripoli's College of Nursing was one among such institutions. From there, the research came to show the reality of using e-learning in the College of Nursing at the University of Tripoli, Libya. Under these circumstances. Purpose: The purpose of this study is to compare the academic achievement of second semester nursing students in the faculty of nursing before and during the Corona pandemic. Method: Using the quantitative comparative research design with all population sampling, a total of 148 nursing students were utilized as the sample. 88 of which were allotted before Corona pandemic while samples of 60 during the Corona pandemic. Data were collected from the college study and exams office, which were the final grade of the selected course in the second semester of the academic year 2019-2020 and the first semester of the academic year 2020-2021. The collected data were statistically analyzed using SPSS version 24, with t-test used to compare the effect of e-learning on student achievement in Fundamentals of Nursing 2 course (NU113) during the Corona pandemic to that of face-to-face learning prior to the Corona pandemic. Results: The results revealed that the average academic achievement scores for students before the Corona pandemic with face-to-face education was 56.76 and that the average academic achievement scores for students during the Corona pandemic with e-learning was 56.23. Significance levels were set at α≤ 0.05 was considered as statistically significant for all analyses of comparison between student scores before and during the Corona pandemic. The results showed that there is no statistically significant difference in academic achievement between students who studied e-learning and face-to-face education, with (p=0.868 &gt; α). Ho is accepted, which means that the transition to e-learning rather than face-to-face education had no negative impact on academic achievement, it was found that nursing students academic achievement is not negatively affected by the Corona pandemic. Conclusion: In this way, e-learning can be harnessed and developed to advance the nursing education agenda. Further study is recommended to assess the impact of e-learning on students’ academic achievement on other courses.
Lightweight Certificateless Signature Scheme for Resource-Constrained IoT Environment

With the widespread application of the Internet of things (IoT), the resource-constrained nature of IoT devices makes the security issues increasingly emerge. Certificateless cryptography has received significant attention due to the avoidance of complex certificate management and the removal of key escrow issues. A large number of certificateless signature schemes have been proposed; however, most of them have been shown to be insecure against public-key replacement attacks or malicious-but-passive KGC attacks. It is a challenge how to construct a secure and light certificateless signature suitable for the IoT yet. Recently, Xiang et al. proposed a lightweight certificateless signature scheme for the IoT which is claimed to be secure. However, by analyzing it, we find that it is vulnerable to public key replacement attacks. To overcome the above issue, we construct a secure and lightweight certificateless signature scheme in this work. It not only proves to be secure against two types of adversaries but also avoids time-consuming pairing. Finally, compared with recent several CLS signature schemes, evaluation results show that our scheme is comparable to the other schemes in terms of overall performance and security.
DEVELOPMENT OF DIGITAL COMPETENCE OF YOUNGER SCHOOL STUDENTS IN THE CONDITIONS OF INFORMAL EDUCATION

Martial law conditions do not create favorable conditions for the education and development of children, but at the same time encourage the search for innovative tools. Temporal challenges determine the need to develop digital competence in younger schoolchildren. Modern society increasingly uses digital technologies in various aspects of life, including education and communication. In addition, the ability to use digital resources is also determined by the requirements for the professional skills of a modern teacher, because today mastering the basics of computer literacy is the basis of educational activity. The importance of non-formal education in the digital competence formation, especially in summer camps, increases. The article presents the authors’ practical experience in the development of digital skills of school-aged children in the summer camp «IT for Kids», which was organized by the NGO «Megasocium» in cooperation with the Center for Information Technologies of Uzhhorod National University with the support of the international humanitarian organization «People in Need Slovakia». Educational content included the basics of computer literacy, cyber security, internet safety, media literacy, programming and robotics. The main educational research goals: determination of key aspects of digital competence, approbation of pedagogical tools effective in the conditions of a military conflict; analysis of scientific research and European practices; assessment of the effectiveness of the application of these methods and approaches in the educational process; designing further work on the development of IT competence in conditions of non-formal education; outlining prospects and opportunities for digital skills developing of school-age children vis summer camps.
KESULITAN MEMBACA PEMAHAMAN SISWA KELAS IV SDN 112 PEKANBARU

Education is important to meet students needs. This is in line with Article 5 of Law Number 20 of 2003 concerning the National Education System which states that everyone has the right to obtain a decent education. Early basic education is very important in the development of students' personalities. Elementary school is the initial stage of basic education and functions as a foundation for students linguistic development. Reading, writing, listening and speaking are part of the language skills that must be mastered. Reading is a key element of language ability. Reading is very important for gathering knowledge and gaining understanding. Reading comprehension is an activity carried out seriously by the reader in order to obtain various information, messages and meanings contained in a text. The purpose of this research is to describe students reading comprehension difficulties, factors that influence students reading comprehension difficulties, solutions to students reading comprehension difficulties. The method used is qualitative to analyze data with a descriptive case study approach, with data collection techniques of tests, observations, interviews with teachers and class IV students.
Rethinking Platform-Based Internet: Possibilities of New Technology Routes

Rethinking the ‘Internet’ refers to a reflection on the current state of technology in the Internet, or ‘cyberspace,’ which includes both ‘speculation’ on other technological solutions that have not historically emerged or been mainstreamed and ‘speculation’ on the multiple Technology Routes that may emerge in the future development of the Internet. This includes ‘speculation’ about other technological solutions that have not historically emerged or been mainstreamed and ‘speculation’ about the multiple Technology Routes that may emerge in the future development of the Internet.
SUPPORTING LAW TEACHERS’ IN THE DEVELOPMENT OF MOOCS

Modernising law and legal education are inevitable in today’s society. Possible arguments for not taking such steps disappeared with the pandemic which fostered processes which were postponed or were found as not applicable. Onwards, the COVID-19 pandemic has further accelerated the existing trend toward online and hybrid learning. It uncovered new and innovative ways for students and educators to organise their teaching and learning activities and to interact in a more personal and flexible manner online. Several papers and policies on the European level, among them Digital Education Action Plan highlight the importance of developing a high-performing digital education ecosystem and higher levels of digital capacity of education and training systems and institutions. Still, the process of modernisation and digitalisation of law and legal education is complex and requires significant efforts and resources from all stakeholders involved. The important aspect in this process is teachers’ preparedness and ability to implement digital technologies in teaching and learning, the support they need in this process as well as their training in digital skills to be able to properly use and implement digital technologies using new teaching methods and digital pedagogies. This paper discusses how to support teachers in the digitalisation of law and legal education and teachers’ training in acquiring necessary digital competences. This is part of the Erasmus+ project Digital in Law Education (DIGinLaw) where one of the results is the development of 12 MOOCs on the topic of law and legal education in higher education. The aim of this paper is to reveal the significance of organizational support for teachers and the importance of developing teachers’ digital skills and competences for successfully meeting the challenges of the digitalization of legal education. The paper describes the process taken to support teachers in the development of MOOCs including their training in digital skills. The results of the research – the proposed model of supporting and training teachers in MOOC design - can be applied to similar requirements for higher education teachers’ support in implementing digital technologies in teaching and learning. Using the survey as a quantitative research method and in-depth semi-structured interviews as a qualitative method, the paper gives insight into teachers’ readiness to use digital technologies and what kind of support and training they need to sufficiently implement digital technologies in the educational process.
ALGORITHMIC DISCRIMINATION : A BLUEPRINT FOR A LEGAL ANALYSIS

The paper aims at providing an overview of the issues raised by algorithmic discrimination, and the key contributions proposed in the literature to address them. It is intended to be used as a starting point for those interested in approaching the topic for the first time or as a syllabus for the students taking the Erasmus+ Strategic Partnership MOOC “Time to Become Digital in Law”. First, the contribution will outline what algorithms are and what we consider algorithmic bias and what are its causes. Second, it will investigate the ethical and social implications of algorithmic bias. Then, the paper will focus on how existing laws and regulations can be applied to algorithmic discrimination. This contribution will focus in particular on the two branches of law that have been identified in the literature as the most relevant in this context: anti-discrimination law and data protection law. The work will outline their potentialities and limitations, presenting some proposals advanced in the literature to fill the new and emerging gaps of protection.
PROPERTY RIGHTS OVER CRYPTOCURRENCIES : A CONFLICT-OF-LAWS PERSPECTIVE

The paper tackles the conflicts of laws on property rights over cryptocurrencies, starting from characterization issues. Building upon the distinctive nature of cryptocurrencies as “pure” de facto assets, that do not give a claim against an issuer, and the relevance of control over said assets as a suitable alternative to the traditional possession, the paper supports the characterization in terms of “assets”, over which property rights may, subject to the relevant lex causae, be constituted and enjoyed. By examining the available options for a conflict-of-law regime and considering the first legislative efforts conducted in this area of law both at the supranational and national level, the elective situs approach is identified as the most appropriate, possibly backed by some regulatory requirement, whilst different approaches are envisaged for the fall-back rule applicable to cryptocurrencies originated in, respectively, permissioned and permissionless DLT systems.
The Contextual Environment as a Catalyst for Change in the Learning Process and Learning Styles of Students

This study aims to assess whether students’ learning styles have changed due to the environmental context changes caused by the COVID-19 pandemic outbreak. This analysis is important because learning styles, in addition to predicting vocational outcomes, must inform the design of pedagogical practices and supports used in the teaching environment. To achieve this objective, a cross-sectional analysis was conducted on three cohorts of students who enrolled in an engineering course. Students in group 2 have been under confinement conditions during the previous year, while students in group 3 have been under confinement conditions for the previous two years. Group 1 consists of students who did not experience any confinement. The obtained results lead to the following conclusions: (i) The pandemic outbreak has led to environmental changes, pedagogical practices, and changes in the personality profiles of students, which can significantly impact the learning styles of students entering an engineering degree. (ii) While some learning styles are more susceptible to change, others remain resilient. (iii) The duration of exposure to the environmental changes caused by the pandemic outbreak has a greater impact on the changes in these learning styles.
OPEN EDUCATIONAL PLATFORMS FOR THE PROFESSIONAL DEVELOPMENT OF TEACHERS OF SCIENCE, MATHEMATICS AND TECHNOLOGY

The article is devoted to the problem of studying the professional development of teachers of science and mathematics education and technology in the conditions of martial law. The purpose of the article is to characterize open educational platforms for the professional development of teachers of science and mathematics education and technology. These platforms include: the social project «Coaching for Ukraine» created by the AcademyOcean team, which operates with the support of the state; training courses for teachers on the Prometheus+ platform; professional development courses on the Iteacher platform; the Ukrainian educational online portal for teachers «Na urok»; the educational project «Vseosvita»; and the online education studio Educational Era (EdEra). The experience of the Institute of Postgraduate Education of Borys Grinchenko Kyiv University, where instructors have developed and implemented original training courses for teachers with different levels of digital competence, is highlighted. It is emphasized that the professional development of teachers with the active use of open educational platforms takes place in accordance with the principles of open education. It has been found that the content of the in-service training of teachers of science and mathematics education and technology in the context of the use of digital tools in the educational process contributes to the renewal of the organization of the educational environment of a general secondary education institution in a remote mode, highlights the features of the learning process organization of students in synchronous and asynchronous modes. It has been proven that the use of digital tools by a teacher is closely related to his digital competence, which needs attention from the professional development system.
GAMIFICATION AS A MEANS OF IMPROVING THE EFFICIENCY OF THE LEARNING PROCESS IN SECONDARY EDUCATION

The article presents the essence and advantages of gamification and its implementation in the educational process; the use of game design elements by teachers in the educational environment. The purpose is to study and present the essence and benefits of gamification and its implementation in the educational process. To reveal the main functions of gamification as a method, the author used the method of induction and deduction, which made it possible to draw conclusions about the details of the gamification procedure and the possible results achieved in the game; the method of comparison, which helped to compare the results of using traditional teaching in lessons in a general education institution and lessons involving gamification techniques. Gamification as a tool that uses different types of student motivation is revealed. Gamification is shown as a complex of game methods and technologies aimed at developing skills and improving the learning process and quality of education. Gamification is revealed as a tool that helps teachers, regardless of the discipline they teach, to make learning interactive and engaging. The potential of using gamification methods to increase students’ motivation, engagement, and performance is presented, mainly by creating a comparative learning environment that affects how students learn. It is concluded that improving students’ motivation and engagement in learning activities is important for the development of skills and competencies. A teacher’s understanding of how gamification methods affect student behavior can help them choose the appropriate methods for their students.
Dissertation Abstract: Taming Exact Inference in Temporal Probabilistic Relational Models

Abstract Processes in our world are of a temporal probabilistic relational nature. An epidemic is an example of such a process. This dissertation abstract uses the scenario of an epidemic to illustrate the lifted dynamic junction tree algorithm (LDJT), which is a temporal probabilistic relational inference algorithm. More specifically, we argue that existing propositional temporal probabilistic inference algorithms are not suited to model an epidemic, i.e., without accounting for the relational part, and present how LDJT uses the relational aspect. Additionally, we illustrate how LDJT preserves groups of indistinguishable objects over time and have a look at LDJT from a theoretical side.
Event Extraction with Spectrum Estimation Using Neural Networks Linear Methods

The timely extraction of event information from enormous amounts of textual data is a critical research problem. Event extraction using deep learning technology has gained academic attention as a result of the fast growth of deep learning. Event extraction requires costly, expert-level, high-quality human annotations. As a result, developing a data-efficient event extraction model that can be trained using only a few labelled samples has emerged as a key difficulty. Existing research work focuses mainly on the structured data with supervised models. The proposed work focuses on Movie Scene Event Extraction, a practical media analysis problem that seeks to extract structured events from unstructured movie screenplays. We suggest using the correlation between various argument roles in situations where different argument roles in a movie scene share similar qualities. This can be beneficial to the Movie Scene Argument Extraction (argument classification and identification) and film scene trigger extraction (Trigger recognition and classifying). In order to represent the relation between different roles in argument and their respective roles, we propose a Superior Concept of Role (SRC) as a top-level idea of a role that is based on the classic argument role, as well as an SRC-based Graph Attention System (GAT). To assess the efficacy of the model we designed, we constructed the dataset MovieSceneEvent to extract movies’ scene-related events. Additionally, we conducted tests on an existing dataset in order to compare results with different models. Results from the experiments like extraction of words, aspect keywords from the documents indicate that our model does better than other models. Furthermore, the information on the relationship between the argument roles helps improve the effectiveness of film scene extraction of events.
Class Activation Map based Random Erasing for Data Augmentation

Random erasing offers various levels of occlusion for data augmentation. However, due to its uniform distribution of random selection, it sometimes occludes regions that are unrelated to the object of interest. In this paper, we propose a novel method that utilizes Gradient Weighted Class Activation Mapping (Grad-CAM) for estimating the location of the object of interest and selectively erasing the surrounding areas. By utilizing Grad-CAM, we improve random erasing for CNN models without requiring additional modules or architectural changes. We generate Grad-CAM after the intermediate epochs where CNN models have sufficient representational power for the training data. The hyperparameter that restrict the erasing to the vicinity of the object is set based on Grad-CAM, and experiments were conducted accordingly. As a result of our experiments, we observed a 0.33% decrease in error-rate for image classification tasks using ResNet-20 on the CIFAR-10 dataset.
Semantic Super-Resolution Using a Transformer Model

This paper proposes an effective method to improve the performance of SwinIR, a vision Transformer-based super-resolution neural network model, by introducing a Transformer decoder with learnable category queries. The decoder allows to extract semantic information of each dataset belonging to different categories (e.g., text and face); the semantic information can improve category-specific texture reconstruction in the process of super-resolution. Experiments were conducted using decoders of different architectures to analyze the performance of the proposed method. The experimental results confirm that the use of decoder can improve the quality of super-resolution images produced by SwinIR qualitatively and quantitatively, although improvements may vary depending on the depth of the decoder and how semantic information is applied.
DEVELOPMENT OF GIS BASIC KNOWLEDGE MODULES CLASS X IIS MAN 1 BANDAR LAMPUNG

This research is a development study that aims to develop geographic information system on basic knowledge materials geographic information systems and analyzing the level of feasibility and effectiveness of the geographic Information system module. The type of research used is R&amp;D (Research and Development) research with a 4D development model, developed by S. Thiagarajan et al. Based on the results of the study show that (1) the feasibility level of the module based on the assessment of the three experts get an average score of 3.10 with a very feasible category, (2) the feasibility level of the module based on the assessment of students in large group tests get an average score of 3.22 with a very feasible. For the level of effectiveness of the module measured the test results show an increase in value before and after using the module. At Pretest the mean score obtained by students was 60.68 and the mean score increased to 89.72 at Posttest. DOI: http://dx.doi.org/10.23960/jlg.v3.i1.24776