Reviewerly/exHarmony huggingface dataset:
The Use of ICT in Educational Institutions in Paraguay and the Factors That Intervene

Research in education has produced vast information about the use of technology for the development of classes around the world. In Paraguay, there have been in-itiatives that promote the use of technology in schools to enhance the teaching and learning process. The objective of this study is to examine the use and scope of ICT in the classroom and to better understand teaching experiences in secondary education in Paraguay. The methodology used was quantitative and qualitative by means of an online questionnaire with closed and open-ended questions consist-ing of 30 questions on access to and use of technology in the classroom, teacher skills and training, and level of institutional support. Results include three factors associated with the professional perception of ICTs and 7 factors associated with the degree of appropriation of ICT as well as factors related to teachers’ compe-tency levels and differences between rural and urban areas. These findings call for first of all a stronger emphasis on universal access from the public policy point of view in order for the affordances of ICT to be available to all.
Exploring the Balance of Using Dispositional and Situational Attribution in Reading

The boom in education industry is further supported by the added convenience of distance and online learning has encouraged adult learners to pursue their studies.Reading is the most important skill for undergraduates in higher institutions.Reading skills are required to access knowledge for learning.Reading skills are needed to write assignments in higher institutions of learning.This study is therefore done to investigate adult learners' perception of reading strategies used.The use of strategies portrays the attribution portrayed by the learnersdispositional and situational attributions.This quantitative pilot study is done to investigate adult learners' perception on their use of reading comprehension strategies.38 adult learners taking online undergraduate courses took part in this study.The instrument used is a survey with 5 Likert scales.The survey has 2 main sections; dispositional and situational attribution.A summary of findings revealed that the dispositional attribution that is evident during reading comprehension activity are the readers' perception of difficulties they encounter and also their perception of their use of metacognitive strategies.Next, for situational attribution, this study focused on the use of (a) cognitive and (b) social-affective reading strategies among academic readers.Findings in this study bear interesting implications in the teaching of academic reading for adult learners.
Fuzzy AHP-TOPSIS approaches to prioritize teaching solutions for Intellect Errors

Abstract: The teaching fraternity and intellects play an important role in students’ careers as they make students industry-ready. During their teaching, they make different types of errors. One of the neglected aspects during teaching is intellect errors and these directly or indirectly impact students learning capabilities. The scattered literature shows that there are twelve types of intellect errors like ‘error of coincidence’, ‘senses error’, ‘analogy error’, ‘subjectivity error’, etc. To minimize these errors, six solutions have been identified like ‘selection of right instruments’, ‘developmeand least rated intellect errors respectively. Thent of critical thinking in the students’, ‘aware about knowledge engineering development’ etc. This study aims to identify and prioritize the solutions to overcome the errors of the intellect that has been the ignored aspect of the teaching till now. A hybrid approach of fuzzy AHP (Analytical Hierarchy Process) and Fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) has been proposed to rank the solutions that minimize the intellect errors. Fuzzy AHP is used to compute the weights for intellect errors by doing the pairwise comparison and fuzzy TOPSIS is used to rank the identified solutions with the help of generated weights of fuzzy AHP. The results show that “error of proximity” and “senses error” are the highest topmost rated solution to handle errors of the intellect is “development of critical thinking in the students”. Keywords: Intellect errors, fuzzy AHP, fuzzy TOPSIS, industry-ready
IMPLEMENTING QUIZZIZ AS GAME BASED LEARNING IN TEACHING GRAMMAR IN WRITTEN DISCOURSE

Quizizz is an online assessment tool as a fun multiplayer classroom activity that allows all students to practice together with their computer, Smartphone and I Pad. The main purpose of this research was to find the effect of implemening quizziz in the discourse classroom of Universitas Majalengka. The population of this research were semester four studens of English department, and the samples were 22 students. This research belongs to pre-experimental research and one group pre and pos test design. It described about a study that cast about the effect of giving treatment of using quizziz in single group only.A pre-experimental research was conducted by comparing the means of the participants’ scores in both pre-test and post-test. The analysis figured out that there was a significant improvement, proven by the paired t-test analysis.The p-value 0.00 was less than alpha 0.05. This research concluded that quizziz was effective to assist the students to learn grammar in written discouse.After implementing quizziz, most of studentsfound that were very active to answer the questions which provided by researches, and more concentrated on the topic. And the results of the questioners shows that the students displayed the position attitude for quizizz as a online teaching and assessment tool during the Grammar in Written Discourse class.
Influence of Corporate Governance on Sustainability Disclosure in Bangladesh

This research aims to investigate the relationship between an organization’s corporate governance and sustainability disclosure in Bangladesh. The study further designates sustainability reporting disclosure practices. The study used content scrutiny of the yearly statement of 175 companies listed in Dhaka Stock Exchange (DSE) for the year 2018, applying determinants count procedure and ordinary least square (OLS) regression analysis. Findings revealed that the level of sustainability reported among the listed companies in Bangladesh is deficient. Board independence and audit independence have a positive relationship with sustainability reports, but the female members in the board, audit committee size, and corporate governance compliance index have a negative relationship with sustainability as reporting. The board size of the companies is not a significant determinant of sustainability reported. The use of content analysis method for the measurement of sustainability report considering the quantity and ignoring the quality of disclosure, data consideration for only one year may contain subjectivity matter from the researcher’s perspective. Future research should be conducted based on content analysis with a mixed method to increase the quality. The findings of this study guided the essentials for step-up and the pursuance of corporate governance on sustainability exposure. This study contributes to works of literature on the association of corporate governance with sustainability disclosure.
Data Integrity Attacks in Cloud Computing: An Overview of Identifying and Protecting Techniques

Сlоud Соmрuting is а range of services delivered over the internet or "the cloud".In recent years, Сlоud Соmрuting has beсоme fastest emerging technology.Beсаuse of its lоw соst аnd раy-аs-yоugо mаnner mаny оrgаnisаtiоns аre shifting their trаditiоnаl соmрuting mоdel tо а сlоud-bаsed mоdel.Even thоugh СSР (Сlоud Serviсe Рrоvider) ensures thаt the dаtа thаt is stоred аnd seсure in their сlоud server, there аre various dаtа integrity issues whiсh аre essentiаl tо be addressed.Lасk of dаtа integrity in сlоud environment is а serious соnсern.In this рарer, I have surveyed previous studies whiсh identifies the issues related tо сlоud dаtа storagesecurity like unavailability, dаtа breасh of сlоud server dаtа аnd dаtа theft.
ELM-Based Active Learning via Asymmetric Samplers: Constructing a Multi-Class Text Corpus for Emotion Classification

A high-quality annotated text corpus is vital when training a deep learning model. However, it is insurmountable to acquire absolute abundant label-balanced data because of the huge labor and time costs needed in the labeling stage. To alleviate this situation, a novel active learning (AL) method is proposed in this paper, which is designed to scratch samples to construct multi-class and multi-label Chinese emotional text corpora. This work shrewdly leverages the superiorities, i.e., less learning time and generating parameters randomly possessed by extreme learning machines (ELMs), to initially measure textual emotion features. In addition, we designed a novel combined query strategy called an asymmetric sampler (which simultaneously considers uncertainty and representativeness) to verify and extract ideal samples. Furthermore, this model progressively modulates state-of-the-art prescriptions through cross-entropy, Kullback–Leibler, and Earth Mover’s distance. Finally, through stepwise-assessing the experimental results, the updated corpora present more enriched label distributions and have a higher weight of correlative emotional information. Likewise, in emotion classification experiments by ELM, the precision, recall, and F1 scores obtained 7.17%, 6.31%, and 6.71% improvements, respectively. Extensive emotion classification experiments were conducted by two widely used classifiers—SVM and LR—and their results also prove our method’s effectiveness in scratch emotional texts through comparisons.
Impact of Media: Spreading Web Information

False information can be created and spread easily through the web and social media platforms, resulting in widespread real-world impact.Characterizing how false information proliferates on social platforms and why it succeeds in deceiving readers are critical to develop efficient detection algorithms and tools for early detection.A recent surge of research in this area has aimed to address the key issues using methods based on feature engineering, graph mining, and information modelling.Majority of the research has primarily focused on two broad categories of false information: opinion-based (e.g., fake reviews), and fact-based (e.g., false news and hoaxes).This research article attempts to understand the current situation of fake news on social media in India.The study focused on four characteristics of fake news based on four research questions: subject matter, presentation elements of fake news, debunking tool(s) or technique(s) used, and the social media site on which the fake news story was shared.A systematic sampling method was used to select a sample of 90 debunked fake news stories from two Indian fact-checking websites, All News and Fact, from December 2019 to February 2020.A content analysis of the four characteristics of fake news stories was carefully analysed, classified, coded, and presented.The results show that most of the fake news stories were related to politics in India.The majority of the fake news was shared via a video with text in which narrative was changed to mislead users.For the largest number of debunked fake news stories, information from official or primary sources, such as reports, data, statements, announcements, or updates were used to debunk false claims.
An Empirical Evaluation of Constrained Feature Selection

Abstract While feature selection helps to get smaller and more understandable prediction models, most existing feature-selection techniques do not consider domain knowledge. One way to use domain knowledge is via constraints on sets of selected features. However, the impact of constraints, e.g., on the predictive quality of selected features, is currently unclear. This article is an empirical study that evaluates the impact of propositional and arithmetic constraints on filter feature selection. First, we systematically generate constraints from various types, using datasets from different domains. As expected, constraints tend to decrease the predictive quality of feature sets, but this effect is non-linear. So we observe feature sets both adhering to constraints and with high predictive quality. Second, we study a concrete setting in materials science. This part of our study sheds light on how one can analyze scientific hypotheses with the help of constraints.
Number recognition development with number card: Single subject research

&lt;span lang="EN-US"&gt;Mentally retarded is a mental disorder with an intelligence quotient (IQ) between 55-70, besides those mentally retarded children are only able to think concretely. For this reason, learning mathematics for mentally retarded students requires learning media that can bridge abstract mathematical material with the abilities of mentally retarded children who are only able to think concretely. The objective of this study was to improve the recognition of 1-20 numbers using number cards for students with mild mental retardation. The research used is single subject research method with basic design non reversal. Study subjects were selected based on a purposive sampling technique, as the researcher had to look for subjects with mild mental retardation. Data collection techniques use documentation to find out subjects with mild mental retardation characteristics, and tests to determine the subject's ability to recognize numbers 1-20. The results of this study indicate that the number card media can improve the ability of mild mentally retarded students to recognize numbers 1-20. This can be seen from the average in the baseline phase of 39 with a percentage of the ability to recognize numbers of 33.3%, and in the intervention phase of 74.44 with a percentage of the ability to recognize numbers of 88.89%.&lt;/span&gt;
Self-efficacy and user behavioral intention to use online consultation management system

&lt;p&gt;&lt;span lang="EN-US"&gt;A consultation is an act of discussing a certain issue between two or more parties. Consultation is considered very important especially in the context of higher education. The Novel Coronavirus 2019 (COVID-19) pandemic has shifted the education paradigm into digital dependency, including consultation management between students and academicians. However, a lack of studies has been conducted on the roles of self-efficacy towards user behavioral intention to use online consultation management systems in the aftermath of a pandemic. Therefore, the purpose of this research is to investigate the relationship between self-efficacy and user behavioral intention to use an online consultation management system. In terms of respondents, 270 students were selected based on convenience sampling. Findings were analyzed using statistical package for social sciences (SPSS) version 26 and SmartPLS version 3.2.8. Hence, this research revealed that proposed hypotheses were all supported. Self-efficacy has a positive and significant relationship with perceived usefulness and perceived ease of use. On the other hand, both perceived usefulness and ease of use were found positively influence attitude towards using online consultation management system.&lt;/span&gt;&lt;/p&gt;
The role of self-learning in the practical training among preschool teachers

&lt;span lang="EN-US"&gt;The article examines conditions for effective implementation of self-learning program in the training preschool teachers. The following research methods were used: pedagogical experiment, testing, observation, activity analysis, Kolmogorov-Smirnov test, Student’s t-test. An independent variable of the experiment was the self-learning program of preschool teachers developed through quality feedback and self-analysis. The professional competence of preschool teachers is studied through a system of components: motivational, cognitive, activity and reflective. Motivational and reflective components are less developed than cognitive and activity ones. It was found that the self-learning program is more effective for the development of cognitive, activity and reflective components, while the motivational component was less developed. It is established that the basic conditions for the effectiveness of professional self-learning is feedback from the program developer and ensuring quality pedagogical reflection of one’s actions. The following blocks of material were the most problematic for the assimilation of in the developed course: the physiological characteristics of children, speech and thinking of preschoolers, various aspects of the organization of learning and play in preschool education. The data can be used in the self-learning practice of preschool teachers and students to stimulate professional development. Further prospects for the study of the problem include improving the self-learning program for implementation in higher educational institutions. It is important to optimize the ways of development of preschool teachers’ pedagogical reflection. The development of standardized forms of assessment of acquired competencies is worth noting.&lt;/span&gt;
An Analysis Of Politeness Strategies Used By Donald Trump And Hillary Clinton Presidential Debate 2016

Politeness is usually related to speech acts done by the speaker, and this can be seen in everyday life when people are having a conversation. The conversation that we often see in video debate is a conversation that has the value of politeness. This research analyzes politeness introduced by Brown and Levinson in Donald Trump and Hillary Clinton's presidential debate 2016. This research used a qualitative approach with library research. The sources of data were primary and secondary data. The data were in source primary the form of utterances that contain politeness strategies. Donald Trump and Hillary Clinton's presidential debate 2016 script was the data source. Secondary data in this research is the politeness aspect related to the problem in this research. The collecting data techniques are reduction, display, verification, or drawing conclusion. The result of the analysis is bald on record (16), positive politeness (26), negative politeness (34), and off-record (10). So the total politeness that occurred in Donald Trump and Hillary Clinton's presidential debate in 2016 is 86. The dominant utterance varieties politeness in presidential debate 2016 is 34 negative politeness.
Effective Triggering Mechanism for Server less Environment

Cloud technologies are dominating the globe in today's worldwide environment by enabling end users by delivering faultless infrastructure.Every community will benefit from platforms and services.The Server less approach, also known as Function as a Service [FaaS], is
Pelatihan Aplikasi Mendeley sebagai Instrumen Citation dan Reference Manager Artikel Ilmiah bagi Akademisi di Kota Madiun

The community service about training in using Mendeley application as a citation and reference manager instrument in writing article for university students in Madiun aims to share knowledge for academicians in writing article citation and reference manager using Mendeley. The participants of this community service are the university students in Madiun. This activity was done through discussion and simulation in Zoom meeting. It was started with planning and socialization for a month through social media. The simulation was done through Zoom meeting in a day. Evaluation of this activity was done by giving questionnaire for all participants at the end of the training. The results of the evaluation showed that the training of article citation and reference manager in writing article benefits for the university students in writing appropriate APA 7th edition-citation.
Pelatihan Aplikasi Olah Data SmartPLS untuk Meningkatkan Skill Penelitian bagi Dosen Sekolah Tinggi Theologia Batam

This service activity aims to improve the research skills of lecturers in research data processing through Smart PLS training. The output target of the activity is that the participants can independently process research data and understand how to read the results and their interpretation. The training used the lecture and the practical method. The number of training participants was 20 lecturers from five STTs in Batam. The activity evaluation instruments were questions made on the Google Form that the participants must answer. The data analysis compared the participants' abilities before and after this training. The training evaluation results proved an increase in the ability of the participants to use the Smart PLS software. First, the participants already understand how to process data to test the data's validity and reliability. Second, the participants already understood how to test the intervening model hypothesis. Then, the participants understood how to test the moderating model's hypothesis. Thus, participants' research skills have improved significantly after attending this training. This type of training, particularly practice-based training, should be held on an ongoing basis.
Facial Landmark Detection With Learnable Connectivity Graph Convolutional Network

The conventional heatmap regression with deep networks has become one of the mainstream approaches for landmark detection. Despite their success, these methods do not exploit the overall landmarks structure. We present a new landmark detection which is capable to capture the overall structure of landmarks by modeling these landmarks as a graph structure. Our method combines a deep heatmap regression network with Graph Convolutional Network (GCN) into an end-to-end differentiable model. The proposed method can utilize both visual information and overall landmarks structure to localize landmarks from an image. The ad hoc spatial relationships between landmarks are learned naturally with GCN network. Experiments on multiple datasets show the robustness of the proposed method.
‘This novel is not totally full of tears...’: Graduation Resources as Appraisal Strategies in EFL Students’ Fiction Book Review Oral Presentation

Today, scholars in the field of text analysis are increasingly interested in studying evaluative language. However, few, if any, studies on classroom language have examined EFL students' fiction book review oral presentations from the perspective of the appraisal model. This study aimed at examining students’ use of graduation resources as part of appraisal strategies in classroom discourse, as well as lexico-grammatical resources for coding these strategies in texts. Graduation, in functional perspective is the sub-system of appraisal that is connected with force and focus in creating interpersonal meaning. The dataset comprised three transcripts of students’ fiction book review oral presentations in scientific presentation course, comprising 7.593 words in total. The data were examined quantitatively to identify the statistical variations in utilizing graduation resources in EFL students’ oral presentations. The preferences for lexico-grammatical resources for the construal of these strategies were also illustrated through a qualitative analysis. The results of the study reveal that the classroom discourse of EFL students’ fiction book review oral presentation is loaded with graduation resources. The results of the study show that all students used all graduation resources, specifically force and focus. In terms of force, the sub-systems of intensification (e.g., just, so, never, quiet, full of) and quantification (e.g., only, one of, some of, closely, etc) were applied. Meanwhile, in terms of focus, students only used the sharpen sub-system (e.g., originally, especially). The sub-systems within the system of graduation were shown to serve as strong tools developing the student’s skill to have critical thingking competence.