Reviewerly/exHarmony huggingface dataset:
Finding a Path Forward for Integrating Augmented Reality Into K-12 Classrooms

The potential of augmented reality (AR) as a transformational tool has long been touted in academic circles. However, in order for AR to attain this goal, we must seriously examine previous research to determine if we are on the right path. This study examined 87 AR research studies situated in K-12 environments to determine what grade levels were involved, where the research being done was what content areas were involved, what kinds of triggers were used, and what learning environments were created through the use of AR. This research found that the majority of studies were situated in elementary contexts in science and math. Diverse learning environments were found including inquiry, problem-based learning, visualization, and gamification. Based on these findings, suggestions were made for future research including more research on students creating AR experiences, broadening the grade levels and content areas that are involved, and aiming future AR projects at the transformational level of the SAMR model.
Is an Artificial Teacher Possible?

The article is devoted to the urgent problem – the prospect of partial or complete substitution of teachers for artificial intelligence. With the progress of technologies related to the artificial intelligent systems development the reality of such substitution is estimated as increasing one. At the same time, even the potential substitution of human teachers for artificial intelligence and robotics raises zillion of questions which should be considered from different points of view: cognitive, social, technological, etc. The philosophical perspective provides a reflective integration of these points of view. The most prominent contemporary projects of using artificial intelligence in education have been revealed in the article. The types of intelligent systems used in education are systematized. It is shown that all of them have a different degree of anthropology. Primarily cognitive aspects of the problem of artificial intelligence in education have been considered in the article. The connection of ideas about the possibility of teachers’ substitution for the artificial systems with various approaches to understanding the key principles of education and training is investigated. At the same time, there is a socially critical approach showing that the substitution of teachers for the artificial intellectual systems is a component of cognitive capitalism. The author of the article proposes to reformulate the problem and consider the use of artificial intelligence in education not as a substitutional but as a supplementing technology. This means that artificial systems assume certain functions working in symbiosis with a human teacher and partly playing the role of a tutor. Using the actor-network theory and the ontology of assemblages, referring to the cyberand xenofeminist interpretation of the concept of "cyborg" the author shows that the teacher together with the artificial intelligence can form a human-machine system. In this case artificial intelligence shows emancipation potential but not alienating one.
Align-and-Attend Network for Globally and Locally Coherent Video Inpainting.

We propose a novel feed-forward network for video inpainting. We use a set of sampled video frames as the reference to take visible contents to fill the hole of a target frame. Our video inpainting network consists of two stages. The first stage is an alignment module that uses computed homographies between the reference frames and the target frame. The visible patches are then aggregated based on the frame similarity to fill in the target holes roughly. The second stage is a non-local attention module that matches the generated patches with known reference patches (in space and time) to refine the previous global alignment stage. Both stages consist of large spatial-temporal window size for the reference and thus enable modeling long-range correlations between distant information and the hole regions. Therefore, even challenging scenes with large or slowly moving holes can be handled, which have been hardly modeled by existing flow-based approach. Our network is also designed with a recurrent propagation stream to encourage temporal consistency in video results. Experiments on video object removal demonstrate that our method inpaints the holes with globally and locally coherent contents.
Innovative and information technologies in the educational process at the pedagogical university

Education is one of the most important human values in the modern world. It has become the key thing that helps people determine their life orientations, enrich their culture, promote their professional growth, and achieve their social status. It concerns all the stages of the educational system especially higher pedagogical education. The traditional approaches used in the educational process are changing under the influence of intensive developing the computer technologies and improving the educational technologies. The application of interactive, information and communication technologies to the modern education system is becoming wider and wider. The article discusses the key issues of the innovation policy in the modern education and the practical experience gained when using the innovative and information technologies at the Naberezhnye Chelny State Pedagogical University (NSPU).
A Novel Framework for Identifying Twitter Spam Data Using Machine Learning Algorithms

Nowadays, Twitter has become one of the most popular social media in the world. However, its popularity makes it an attractive platform for spammers to spread spam. Twitter spam becomes a severe issue. It is referred to as unsolicited tweets containing malicious links that direct victims to external sites containing malware downloads, terrorists, phishing, drug sales, scams, etc. Previous studies have approached spam detection as a classification problem, high dimension, time-consuming problem, which requires new methods to address the problems. This study introduces a novel framework for identifying Twitter spam data based on machine learning algorithms. By initializing data pre-processing for clean-up, noise removal, and unpredictable unfinished data, reducing the number of features in the tweet dataset using mutual information is the study's methods. The feature selection is introduced to select the most important from the extracted high-dimensional best features and feed the selected features into the minimum Redundancy and Maximal Relevance algorithm and apply random forest for classification. This study allows us to achieve higher classification accuracy and speed. The effectiveness evaluation being confirmed by experiment results show that accuracy is improved by 90% in 0hr 0m 20s time, compared with the existing system, the completion time is 2.022 seconds, and the accuracy is 80%. The research results contribute significantly to the field of cyber-security by forming a real-time system using machine learning algorithms.
Unsupervised Word Alignment via Cross-Lingual Contrastive Learning

Word alignment is essential for the down-streaming cross-lingual language understanding and generation tasks. Recently, the performance of the neural word alignment models has exceeded that of statistical models. However, they heavily rely on sophisticated translation models. In this study, we propose a super lightweight unsupervised word alignment model, dubbed MirrorAlign, in which bidirectional symmetric attention trained with a contrastive learning objective is introduced, and an agreement loss is employed to bind the attention maps, such that the alignments follow mirror-like symmetry hypothesis. Experimental results on several public benchmarks demonstrate that our model achieves competitive, if not better, performance compared to the state of the art in word alignment while significantly reducing the training and decoding time on average. Further ablation analysis and case studies show the superiority of our proposed MirrorAlign. Notably, we recognize our model as a pioneer attempt to unify bilingual word embedding and word alignments. Encouragingly, our approach achieves 16.4X speedup against GIZA++, and 50X parameter compression compared with the Transformer-based alignment methods. We released our code to facilitate the community: https://github.com/ICLR20anonymous/mirroralign
Actividades para el desarrollo de la competencia comunicativa en inglés a través de la plataforma Moodle

The introduction of the Information Communication Technologies (ICT) in the different social processes has generated changes. In response to these changes and in alignment with the regulations expressed in the economic and social policies of the Cuban government, the Ministry of Higher Education has improved the teaching process by means of the use of diverse technological resources available in our context. The use of Moodle in Las Tunas University is essential. However, there are some deficiencies concerning this, since the activities developed in that platform are insufficient, in addition, they need to support a higher level of social interaction to contribute to the development of the communicative competence. The aim of this work is to propose a set of tasks to contribute to improve the teaching learning process of English language by means of Moodle.
МЕТОДИЧНА ХАРАКТЕРИСТИКА АНГЛОМОВНИХ АВТЕНТИЧНИХ ТЕКСТІВ ПЕРІОДИЧНИХ ОН-ЛАЙН ВИДАНЬ ЯК МАТЕРІАЛУ ДЛЯ ФОРМУВАННЯ КОМПЕТЕНТНОСТІ В ЧИТАННІ УЧНІВ ПРОФІЛЬНОЇ ШКОЛИ

Introduction. Nowadays the society puts high demands to the level of reading competence of profiled school students that requires applying new effective educational technologies. The English authentic texts of online edition present a panoramic view of the national culture, a wide choice of authentic vocabulary and grammar structures, as well as a variety of motivating, thought-provoking information that is interesting and meaningful to students and meets their needs and interests. When used in teaching reading in profiled senior school, this type of texts develops critical thinking, stimulates the mental activity. Purpose. The article tackles the problem of forming reading competence of profiled school students with the help of English authentic texts of online editions. Methods. The study provides theoretical substantiation backed up with results of empirical research for organizing the process of forming reading competence of profiled senior school students with the help of English authentic texts of online editions. Results. The article contains an overview of the modern scientific ideas regarding the problem of forming reading competence of profiled senior school students with the help of English authentic texts of online editions. It defines the aim and the structural components of reading competence of the profiled school students and considers the advantages of using English authentic texts of on-line editions. Dealing with the notion of text authenticity it also dwells upon characteristics of authenticity peculiar to English authentic texts of online editions. The interactive foreign language teaching and its techniques are suggested as a methodological bases and tool adequate to the tasks of forming reading competence of profiled school students using English authentic texts of online editions. Conclusion. The research has shown that English authentic texts of online editions are an effective means of forming reading competence of profiled school students. English authentic texts of online editions have a powerful lingua-sociocultural, psychological and pedagogical potential; when used as teaching material, authentic texts of newspaper and magazine publications stimulate learners’ motivation and interest to the country of the target language that increases the effectiveness of forming reading competence of profiled school students.
Easy Data Augmentation Method for Classification Tasks

In recent years, the rapid development of deep learning has made great progress in artificial intelligence-related technologies. With the deepening of artificial intelligence research, machine learning is applied to more and more fields. Although machine learning has many advantages and has achieved considerable results, machine learning and its related learning algorithms still face some related challenges. That is, the lack of sufficient training data or uneven class balance in the data set. In deep artificial neural networks, a large amount of training data is needed to learn effectively, and collecting such training data is often expensive and laborious. Data Augmentation overcomes this problem by artificially expanding the training set and label retention conversion. In this article, we propose a method to expand the data set based on ball k-means. The experiments on the Four-class, Digits, Iris and Breast-cancer data sets prove the efficiency of the method-fast execution speed, low computational complexity, and the effectiveness of the method. In these experiments, the quality of the training model has been improved, but the learning time stays the same as when the enhancement method is unused.
EFFECT OF USING AUDIOVISUAL MEDIA ON STUDENTS’ SPEAKING ABILITY AT SMP NEGERI 1 BAUBAU

This research was conducted to find out the significant effect of audiovisual media on students’ speaking ability. This research used a quasi-experimental design, and the sample of this research was class VIII.1 as an experimental class that consists of 22 students, and class VIII.12 as a control class with 22 students. The instrument of this research was a test, it was in the form of pre and post-test. The data analysis in this research was descriptive statistics and inferential statistics. The score of student’s basic speaking ability was calculated using Microsoft Excel 2010. The data resulted through that calculation was analyzed using the Statistical Package for Social Science (SPSS) 21.0 versions. The findings could be concluded that there was a significant effect of using Audio-Visual Media toward students’ speaking ability at second-grade students of SMP Negeri 1 Baubau. It can be seen based on the score of the t-test in the appendix, it showed that there was a significant effect on the students’ speaking ability in speaking. It was proved by the finding t-test (2.696) which was higher than ttable at 5% level of significance (2.04). It could be stated that 2.04&lt;2.696 for students’ speaking ability. It meant that the null hypothesis (Ho) was rejected, while the alternative hypothesis (Ha) was accepted. In conclusion, teaching speaking by using Audio Visual at the second-grade students of SMP Negeri 1 Baubau better than without using Audio-Visual Media.
THE ANALYSIS OF THE STUDENTS’ PERCEPTION TOWARD ONLINE LEARNING IN LISTENING SUBJECTS DURING PANDEMIC TIME OF COVID 19

Online learning was the best choice every educators and learnes could access during pandemic time of Covid 19. Aligned with health protocols, the use of online learning was suggested to keep up with the education field. Since the language laboratory was temporarily closed during pandemic time, the Listening subjects were accessed via online platform applications. The purpose of the research was to reveal and analyze the students’ perception toward online learning system in Listening subjects. The subject of the research was selected students of the 1st and 3rd semester of all classes in English Education Study Program at IKIP Gunungsitoli year 2020/2021. The instrument used was the unstructured interviews via WhatsApp chats, and were analyzed through descriptive qualitative analysis.The result of the research revealed that the students’ perceptions were positive, cooperative and motivated towad online learning system in Listening subjects.
MIND MAP AS A MEANS OF VISUALIZATION TECHNOLOGICAL PROCESSES

A strong increase in the amount of information requires improved approaches to its location and transmission in the educational process. One way to overcome this problem is to use visualization tools, including mind maps, which have didactic effectiveness, especially in combination with the capabilities of computer technology. The aim of the article is to study the modern possibilities of visualization of scientific information during the study of technical disciplines. The concept of visualization, which has become an integral part of processing complex information about the structure of the studied objects, is analyzed; methods, principles and scientific approaches to visualization. The expediency and efficiency of using a mind map to visualize technological processes are substantiated. It is proved that the use of computer mental maps helps to increase the level of memorization of information by detailing the basic concepts, their systematization, classification and generalization; formation of skills of work with graphic information. The conditions of effective use of multimedia mental maps are determined, the observance of which harmonizes the educational process for all its participants. The advantages of using mental maps are determined, among which – active comprehension of educational material in the process of independent creation of own mind maps, which gives the chance to actively assimilate scientific information, acquire skills of its independent structuring, trace logic of connections of various units, find new ideas and develop associative thinking. . The use of visualization tools, including intelligence maps, in the educational process is possible both during the study of new material in lectures, independent work and during the control of assimilation and understanding of scientific information, establishing links between its components, the ability to structure information. Mind map is a productive alternative to traditional methods of processing and transmitting information in the educational process, which turns the student into an active student of higher education. Key words: scientific information, visualization, mind map, technological process.
N3MO: The Missing Easy Button for Model Serving at Scale

Search depends on machine learning, which needs production of several models to perform content enrichment like Named Entity Recognition or perform online functions such as semantic matching etc. Typically, converting a deeplearning model into a production grade API takes several months and several people. Typically, a data scientist is not able to independently build and deploy deep learning models which happen to be resource heavy in an optimized manner. Typically, complying to organizational requirements such as availability, security, ops support is a multi-people and a daunting experience. Project N3MO is aimed at changing that, in order to give data scientists an easy button to eliminate most of the DevOps work and give a functioning production grade API within an hour as opposed to months with only engaging one data scientist. In this workshop we will introduce the new super-easy workflow of N3MO: Neural Multi Multi Model Orchestrator. We will also take on a challenge of training a document summarization model, then converting it into production API walking through the usage of Project N3MO, and we will share performance benchmark and scaling tests which would be run towards the very end of the workshop. We will open the floor for an open discussion on the experience through the N3MO framework and ideas to improve upon it.
IMPROVING STUDENTS’ READING COMPREHENSION THROUGH STUDENT TEAM ACHIEVEMENT DIVISION OF VIII GRADE AT SMPN 1 GALANG

The objective of the research is to prove whether the use of STAD is effective or not to improve students’ reading comprehension in narrative text. This pre – experimental research use 27 students as a sample. They are Grade VIII A of SMP NEGERI 1 Galang. The procedure of this research consist of pretest, treatment, and posttest. Pretest and posttest are given to know the use of STAD can improve students’ reading comprehension or not. The result of the analysis data show that STAD contribute greatly to the students’ comprehension in narrative text. It can be seen by the difference of the mean score between pretest and posttest. The mean score of pretest is 57.93 while in the posttest improved up to 80.69. the data of this research are analyzed by SPSS Program 16.0. Moreover, the Minimum Mastery Criterion of English lesson is 75. Then the data of both tests are analyzed by using T-test, and the result showed that the T-test value 41.062 is high than T-table value 2.056. It can be inferred that STAD method is very effective to improve students’ reading comprehension in narrative text. Keywords: Student, Team Achievement Division, Reading
COMPETENCE APPROACH AS THE BASIS OF A NEW PARADIGM OF EDUCATION

The article presents the analysis of the concept of competence approach from modern positions and from the point of view of the possibilities of transition to a new educational paradigm on its basis. The beginning of the new Millennium is characterized by global changes and profound processes in almost all spheres of human activity, especially in the field of communication technologies and education, as they are all closely interrelated. Currently, there is a transition to such an information society, in which the processes of generation, integration and dissemination of knowledge become a priority, and they should have a positive impact on the formation of a new paradigm of both education in General and private educational concepts and systems. This paradigm is aimed at the quality of modern education as a process and result of University practice and its quality management.
On the Application of Blended Teaching Mode in the Course of English Speech

In the era of Internet popularization, teaching approaches have become diversified, online and offline teaching methods have gradually integrated and created a broader learning space for students. Blended teaching mode has emerged. The advantages of this teaching mode have been affirmed by the majority of teachers. This paper focuses on the application value and strategy of blended teaching mode in English speech course.
Pemilihan Padi Terbaik Pada Kelompok Tani Sri Rejeki dengan Metode WP (Weighted Product)

At this time the best rice was very diverse. This makes fertile beautiful village farmers having difficulty choosing the best type of rice that will be made of quality rice. Until recently, this was done in the traditional way, such as waiting for the harvest to find out. So that we need a decision support system used in selecting the best rice type. In this decision making system will use the Weighted Product method to determine alternatives and criteria. The criteria that will be used to determine the best rice are price, quality, harvest time, popularity, maintenance costs and durability. The alternatives that are chosen are Rice Hebrides, Padi Impara, Padi Impari and Padi 64. In testing and implementation, the best rice yields can be obtained with several alternatives, namely hybrid rice which is the first alternative which is made as quality rice
Selective Model for Few Shot Classification

Most few-shot image classification methods learn a feature space from seen classes and simply perform classification for unseen classes with few labeled samples. They extract features from support and query samples independently and treat all features channels equally. In this work, we apply the attention mechanism to few shot image classification, which can learn the related features between support and query samples to deal with new tasks problem. We propose a selective module to select relevant channels for discriminating objects in the query image and the support image. The selective module aggregates the features of both images into a channel descriptor, which is used to generate channel-wise attentions for both images, respectively. In this way, the mutual interdependencies between channels from different images are explicitly modeled and channel-wise responses are adaptively recalibrated. The Selective model is a lightweight embedding module for selecting relevant features between support and query samples in channel dimension and learn the more distinctive features.