Reviewerly/exHarmony huggingface dataset:
Developing Nurse Educators’ Self-Editing Skills in English Writing through a Checklist

This study investigated the efficiency of self-editing to reduce language errors of nurse educators. To achieve this, a checklist was created and 15 nurse educators from three different universities were educated on how to self-edit throughout 10 weeks. Data were obtained through 3 editing tasks before the 10-week education course and 3 editing tasks after the course. The Wilcox on test analysed pre-tests and post-tests, and found a statistically significant difference in terms of noticing the language errors through self-editing. This study suggests nurse educators use the checklist before submitting a manuscript. Also, this study concludes that self-editing is an efficient way of revealing language errors and increasing accuracy in English writing of nurse educators.
Correction to: Converting STEM into STEAM Programs

Correction to: STEM Education and the Theft of Futures of Our Youth: Some Questions and Challenges for Educators
Learning to Select Question-Relevant Relations for Visual Question Answering

Previous existing visual question answering (VQA) systems commonly use graph neural networks(GNNs) to extract visual relationships such as semantic relations or spatial relations.However, studies that use GNNs typically ignore the importance of each relation and simply concatenate outputs from multiple relation encoders.In this paper, we propose a novel layer architecture that fuses multiple visual relations through an attention mechanism to address this issue.Specifically, we develop a model that uses question embedding and joint embedding of the encoders to obtain dynamic attention weights with regard to the type of questions.Using the learnable attention weights, the proposed model can efficiently use the necessary visual relation features for a given question.Experimental results on the VQA 2.0 dataset demonstrate that the proposed model outperforms existing graph attention network-based architectures.Additionally, we visualize the attention weight and show that the proposed model assigns a higher weight to relations that are more relevant to the question.
Student Creativity In Performing Problem-Solving Experiments In Physics Development Through Innovative Technologies

This article discusses the role and importance of innovative technologies in developing students` creativity on problematic experiments on physics. It has been shown that innovative technologies help students independently find sources of theoretical knowledge, independently read, analyze data, and even develop their creativity while being able to draw conclusions. The features of innovative technologies and engineering methods are analyzed in the formulation of problematic experiments in physics. The content of the application of each interactive method in carrying out problematic experiments in physics is explained.
Low Anisotropy Sense Retrofitting (LASeR) : Towards Isotropic and Sense Enriched Representations

Contextual word representation models have shown massive improvements on a multitude of NLP tasks, yet their word sense disambiguation capabilities remain poorly explained. To address this gap, we assess whether contextual word representations extracted from deep pretrained language models create distinguishable representations for different senses of a given word. We analyze the representation geometry and find that most layers of deep pretrained language models create highly anisotropic representations, pointing towards the existence of representation degeneration problem in contextual word representations. After accounting for anisotropy, our study further reveals that there is variability in sense learning capabilities across different language models. Finally, we propose LASeR, a ‘Low Anisotropy Sense Retrofitting’ approach that renders off-the-shelf representations isotropic and semantically more meaningful, resolving the representation degeneration problem as a post-processing step, and conducting sense-enrichment of contextualized representations extracted from deep neural language models.
The Problem of the Subject in Artificial Nature

The article discusses the situation with the subject and subjectivity that arises in the conditions of scientific and technological progress. The concept of the subject is introduced through the distinction between reflex (natural) and reflexive (artificial) processes of self-awareness, the subject is understood as a way of connecting “worlds” in the sense of K. R. Popper. The forms of reflection that create subjectivity are introduced as philosophical inventions in the sense of I. I. Lapshin as an aphorism, dialogue and system. The research methodology is of a general semiotic and neo-Kantian character: the function of subjectivity for artificial environments of human life is considered as a reflexive basis for constructing theories and carrying out technical activities, the performance of this function leads to a consistent transformation of nature due to the accumulation of artifacts in the sensually accessible physical world (the first artificial nature), in the rational world of logical-grammatical forms (the second artificial nature), in the world of reason or intellectual reflection (the third artificial nature). Based on the analysis of subjectivity in the first, second and third artificial nature, we conclude that the crisis of the subject and human subjectivity observed in the information society, expressed in the models of the subject-free objectivity of the technosphere or technological singularity is evidence of the exhaustion of the methodological resources of the subject’s analysis. The third artificial nature, i. e. a man-made technical environment that includes intellectual artifacts, autonomous intelligent agents of making socially significant decisions, needs a new philosophical invention that allows for self-awareness procedures. In the conclusion, the assumption is formulated that as such a new philosophical invention, the “environment” can be discussed that removes the “system” in the same sense in which the “system” removes the “dialogue”, and the latter – “aphorism”. Keywords: subject, technology, philosophy of technology, artificial nature, second nature, third nature, technological singularity
A Comparative Study of Emergency Remote Education Amid COVID-19

The outbreak of the new coronavirus pneumonia severely threatened people's health and safety for a long period.It has caused a serious impact on people's work, life, and learning.Most governments around the world have temporarily closed educational institutions in an attempt to contain the spread of COVID-19.These nationwide closures are impacting over 91% of the world's student population (UNESCO, 2020).As a response to the interruption of education due to the crisis, this study compares emergency remote learning cases in three countries, namely India, China, and the United States, narrating the overall view, reflections, and lessons learnt in the education field.The findings show that there are some common challenges that all of the three countries are facing, like ensuring every student having access to remote education, unprepared teachers, increased burden of parents as well as students' lack of self-discipline when isolated at home.With challenges, come opportunities such as education transformation from a traditional system to a new era as well as improvement of digital literacy.Finally, suggestions on improving remote education from the viewpoint of policymakers, teachers, and students are given to escalate the level of remote education during the pandemic, so as to promote the reform of information-based education.
Potable Water Order Forecasting System Using Data Mining Technique

Potable water order forecasting system using data mining technique. It aims to analyze, design and develop potable water order forecasting system using data mining technique. There is a comparison data mining techniques were compared using the C4.5 algorithm and Bayesian classification algorithm. The researcher found that the C4.5 algorithm is more suitable for drinking water ordering system. This web application system allows the system to predict each customer's drinking water orders. Subscription support ordering, drinking water and bank payment. In terms of user interaction and use the MySQL database program to organize the system database. The result of development potable water order forecasting system using data mining technique. Have tested data mining techniques were compared using the C4.5 algorithm and Bayesian classification algorithm. The researcher found that the C4.5 algorithm is more suitable for drinking water ordering system. From data research results using data in 9 months of training and 2 months of testing, it was found that the accuracy was 85.59%. C4.5 algorithm and test the system from the evaluation of 2 administrators, 3 employees and 5 customers, total 10 people with average mean of 4.20 .
Exploration of Mathematics Classroom Teaching Practice in Middle School under the Concept of Core Mathematics Literacy

With the rapid development of the social economy, people pay more and more attention to receiving education. The traditional duck-filling teaching model is contrary to the quality education concept of the new curriculum reform and does not conform to the trend of the times. With the deepening of the new curriculum reform, people-oriented teaching ideas have gradually become prominent, teachers in various subjects are trying their best to explore new teaching methods and find differentiated teaching methods. Mathematics is an important setting for middle school courses, and it takes a large proportion in the entrance examination. The core literacy of mathematics is formed in mathematics knowledge skills, but it is higher than mathematics knowledge skills. Based on the background of contemporary education, this article analyzes the value of core literacy and the guiding role of strengthening the core literacy of mathematics in an attempt to add benefits to the effective development of mathematics teaching in middle schools.
Utilizing Social Media Networks as Learning Tools for Foreign Languages among Arab Youth in UAE

In the globalized world, social media networks have become popular information sharing platforms used extensively as web-based learning facilitation tools for learning purposes. Taking a multidisciplinary approach, the present study evaluated the usability, usefulness, and impact of social media networks as learning tools for Arab youth. It also explored the attitudes of Arab learners of foreign languages towards the use of social media networking sites as learning tools. Quantitative and qualitative data were collected using an E-questionnaire from (400) Arab youth who come from different countries but reside in UAE. Data was analyzed and the Results revealed that Arab youth held positive attitudes towards social media as useful tools for learning languages as they have extensively embraced these tools to learn foreign languages. They predominantly use Facebook, Snapchat, and Instagram, as their favorite social media networks. The study also revealed that Arab youth have been using social media as learning tools for a period spanning several years demonstrating that they understand its usefulness as learning tools for learning languages; especially because they feel comfortable during their experience on social media networks. In view of this result, the study recommended that teachers of foreign languages should embrace Facebook, Snapchat, and Instagram networks as learning tools in order to capture the interest of their students and make the learning of foreign languages effective.
On ideal and weakly-ideal access structures

For more than two decades, proving or refuting the following statement has remained a challenging open problem in the theory of secret sharing schemes (SSSs): every ideal access structure admits an ideal perfect multi-linear SSS. The class of group-characterizable (GC) SSSs include the multi-linear ones. Hence, if the above statement is true, then so is the following weaker statement: every ideal access structure admits an ideal perfect GC SSS. One contribution of this paper is to show that ideal SSSs are not necessarily GC. Our second contribution is to study the above two statements with respect to several variations of weakly-ideal access structures. Recently, Mejia and Montoya studied ideal access structures that admit ideal multi-linear schemes and provided a classification-like theorem for them. We additionally present some tools that are useful to extend their result.
Media Literacy Development At Journalist Students At The Modern Stage

Modern journalism is undergoing changes in the context of functional role status, principles and values, culture, and professional education.Today, journalists, in addition to traditional skills for performing journalistic activities, require specific skills that are characteristic of the post-truth era, first of all, media literacy.The authors pose a problem -future journalists lack sufficient (professional) media literacy due to the predominance of entertaining and destructive models of journalism in Russia, as well as the lack of a system of teaching media literacy in modern conditions.The authors set a goal -to analyze the current state of the profession of journalism, to present methods and technologies for the formation and development of media literacy, where media education plays a key role in their formation.The authors come to the following conclusions: in modern journalism, news journalists fade into the background, authors working in analytical and narrative journalism are in demand.The principles and values of the profession remain unchanged under the influence of information and communication technologies.Vocational education as a factor in ensuring the status quo of a profession in the modern world is not mandatory.In modern Russia, models of entertaining and destructive journalism predominate, which is reflected in the content of mass media texts and media consumption habits.The authors believe that a number of methods can be used in the teaching of journalism that will contribute to the development of media literacy among future journalists.
Using cognitive maps to study issues concerning the improvement of the quality of life of population in the frame of interregional disparities

This paper studies issues of the rise in the standards of living and improvement of the quality of life of the population in the frame of intermunicipal disparities. Simulation and modelling are examined in relation to research of standards of living and quality of life. Tools of cognitive modelling and simulation are used to acquire new knowledge on the regional social and economic, ecological, and political system which determines the standards of living and quality of life. A cognitive model studying the quality of life was designed and its structural properties were analyzed. Scenarios were created to model possible developments of the situation under the influence of various factors. The novelty of the work is in applying a new informational technology of cognitive modelling to studying the improvement of the quality of life in the frame of intermunicipal disparities.
An Initial Study of Tree-Adjoining Grammar Formalism for Parsing Manipuri Language

We present an initial study into the representation of tree-adjoining grammar formalism for parsing Manipuri language. Being a low resource and computationally less researched language, it is difficult to achieve a natural language parser for Manipuri. Treebanks, which are the main requirement for inducing data-driven parsers, are not available for Manipuri. In this paper, we present an extensive analysis of the Manipuri language structure and formulate a lexicalized tree-adjoining grammar. A generalized structure of Manipuri phrases, clauses and the structure of basic and derived sentences have been presented. The sentence types covered in our analysis are that of simple, compound and complex sentences. Using the tree-adjoining grammar we have formulated, one can implement a Manipuri parser whose results can be of immense help in creating a Treebank for Manipuri.
Does Proficiency Level Affect Learners’ Lexical Access in L1 and L2?

Proficiency level is one important factor that contributes to learners’ language performance. Learners with higher proficiency levels tend to perform lexical access better and faster than those with lower proficiency. This study aims to investigate whether proficiency level affects lexical access in L1 and L2. The research involved seven Indonesian university students of master’s and doctoral degree programs at a university in the Netherlands who possess different proficiency levels. Two scrambled texts in the participants’ L1 and L2 were employed to test the participants. Meanwhile, the paired-samples t-test and correlation analysis were used to report the experiment. The results revealed an insignificant difference and a negative correlation between proficiency level and the number of errors and reading time. However, on average, the more proficient learners outperformed the less proficient, thus indicating that they may possess more complex lexical access in L1 and L2. Further studies are needed to provide other useful insights on this topic.
The Effect of Integrating an Educational Robot with Hypermedia on Students’ Acquisition of Scientific Concepts: The Case of Fifth-Grade Students

&lt;p class="0abstract"&gt;This study was designed to reveal the effectiveness of integrating educational robots (ERs) with hypermedia in improving the acquisition of scientific concepts among fifth-grade students in Jordan. The present study utilized a pretest-posttest quasi-experimental design with a control group (CG) and an experimental group (EG). The participants of this study consisted of 50 fifth-grade female students attending a private school in the city of Amman during the 2019/2020 academic year. Participants’ ages ranged between (10-11) years old. The school was selected purposively, and classes were randomly assigned to the EG and the CG. In order to accomplish the aims of this study, a scientific concept test (SCT) was developed and its validity and reliability were ensured. The EG was taught a unit on motion and force by robot and hypermedia instruction, while the CG was taught the same unit by traditional instruction. Data was collected through administration of the presently developed SCT at pretest and posttest points. Then, this data was analyzed through covariance analysis. The findings of this analysis revealed that 66% of the variation in the fifth-grade students’ posttest SCT scores can be ascribed to the effect of teaching method. From this study, one can conclude that the integration of ERs with hypermedia has a positive impact on students’ acquisition of scientific concepts. These results may serve to encourage science teachers to integrate ERs with hypermedia when teaching scientific concepts&lt;span&gt;.&lt;/span&gt;&lt;/p&gt;
Multimodal Weighted Fusion of Transformers for Movie Genre Classification

The Multimodal Transformer showed to be a competitive model for multimodal tasks involving textual, visual and audio signals.However, as more modalities are involved, its late fusion by concatenation starts to have a negative impact on the model's performance.Besides, interpreting model's predictions becomes difficult, as one would have to look at the different attention activation matrices.In order to overcome these shortcomings, we propose to perform late fusion by adding a GMU module, which effectively allows the model to weight modalities at instance level, improving its performance while providing a better interpretabilty mechanism.In the experiments, we compare our proposed model (MulT-GMU) against the original implementation (MulT-Concat) and a SOTA model tested in a movie genre classification dataset.Our approach, MulT-GMU, outperforms both, MulT-Concat and previous SOTA model.
Sentiment Analysis from Tweets using Convolutional Neural Networks

By current improvements of web technology nowadays, usage of social media has increased. Twitter is a web site where millions share their opinions. Political parties, firms and other establishments has been examining data at these social media sites to learn person’s opinions about themselves. Reporting the sharing of millions of persons instantly is done more easily by using machine and deep learning techniques. In this work, sentiment analysis is done by the Convolutional Neural Network which has wide-spread usage in deep learning. Besides other known works, improvements in feature selection have been applied in order to meet higher success rate. Model has been trained by the different data sets and tested in other data sets. The model has reached to 97% success rate by the training data. 90% and 89% success rates have been achieved on the tests applied to other data sets.
Transformation of Teachers to Mentors: Prerequisite of Time is to Excel Innovative Practices in Academics

The perception of Mentoring is definitely not new; indeed, it comes from a character named "Mentor" in Homer's Odyssey.He was a trusted mentor to Odysseus' son.The recent studies and Figures have given rise to prosperous mentoring.Mentoring focuses on the individual's needs, his role is to inculcate and instill skills needed for future roles.Mentors have often had a successful career path, beginning in a similar place as the mentee.They offer assistance through sharing their own experiences, providing valuable feedback and giving the mentee access to their personal network.The technology approaches of teaching and learning are coupled with new techniques viz Case Studies, Student Centered learning, Outcome based learning and problem based learning.Aforesaid approaches are emerged recently and verified to have constructive impact on learning of an individual.Those were the good olden days wherein Professors of the institutes were standing and delivering lecturers via one-way communication, students are listening continuously and preparing their notes, these days are now over and substituted with more innovative and creative ways of facilitating, sharing and disseminating knowledge among the students.The present article summarizes current need of mentors to inculcate skills, nurture talent and build prosperous career of young budding professionals.The highlights of the contents are recent trends of innovative teaching pedagogy to facilitate new breeds and stages of mentoring and its significance in the nation development.
MR4ISL: A Mixed Reality System for Psychological Experiments Focused on Social Learning and Social Interactions

We present MR4ISL (Mixed Reality for Implicit Social Learning), a HoloLens application designed to examine the psychological aspects involved by implicit social learning, a key process responsible for information acquisition at an unconscious level that influences humans’ behavioral, cognitive, and emotional functioning. We describe the engineering details of MR4ISL, present our roadmap for identifying technical solutions for believable animations of virtual avatars relevant for implicit social learning, and exemplify use cases of MR4ISL that emerged from discussions with three researchers from psychology. To date, MR4ISL is the only tool that uses mixed reality simulations to increase the external validity of psychological research in the study of implicit social learning.