Reviewerly/exHarmony huggingface dataset:
Artificial Intelligence in education: What are the opportunities and challenges?

Objective:The paper aims to explore the integration of Artificial Intelligence (AI) tools in the educational sector. It underscores the urgent need for establishing proper regulations and checks to ensure the ethical and effective use of these tools.&#x0D; Method:&#x0D; &#x0D; The insights are based on a think piece authored by UNESCO Assistant Director-General for Education, Stefania Giannini.&#x0D; Data was collected through a global survey involving over 450 educational institutions, including schools and universities.&#x0D; &#x0D; Results:&#x0D; &#x0D; A mere 10% of the institutions surveyed have formulated policies or guidelines concerning the deployment of generative AI.&#x0D; The scrutiny for validating textbooks is found to be more stringent than the introduction of generative AI tools in educational settings.&#x0D; Criteria for textbook evaluations encompass content accuracy, relevance to teaching, age suitability, cultural and social appropriateness, and protection against biases.&#x0D; &#x0D; Conclusions:&#x0D; &#x0D; The paper suggests that educational institutions should not be solely dependent on AI corporate entities for setting regulations.&#x0D; While education continues to be a profoundly human endeavor, the surge of digital tools during the COVID-19 crisis underscored the academic and societal challenges students encounter in the absence of human touch.&#x0D; There's a risk that generative AI might diminish the significance of educators and pave the way for increased automation in the educational domain.&#x0D; Addressing the prevailing challenges in education necessitates investments in both schools and educators, rather than just technology.&#x0D; &#x0D; Practical Implications:&#x0D; &#x0D; It's imperative for education ministries to join forces with other regulatory bodies, particularly those overseeing technological advancements, to assess and approve AI tools.&#x0D; UNESCO is at the forefront of global dialogues with stakeholders and is in the process of framing policy guidelines on the use of generative AI in education.&#x0D; UNESCO's 'Recommendation on the Ethics of Artificial Intelligence', released in November 2021, accentuates the principles of safety, inclusivity, diversity, transparency, and excellence.&#x0D;
Typing speed and fluency as cues to uncertainty in the real-time production of written messages

In spoken communicative contexts, speakers often convey uncertainty via intonation and through paralinguistic behaviours such as speech rate and gesture—and addressees can use these behaviours to generate inferences about the speaker’s epistemic state. In text-based contexts, however, cues of this sort are more restricted. In this study, we examine the expression and reception of epistemic information in the context of real-time written message production. We hypothesised that real-time typing dynamics (like those available in text-based collaborative contexts, such as Google Docs) can function as a rich paralinguistic cue about a partner’s epistemic state. In Experiment 1, we collected production data showing that manipulations of typist certainty, instantiated through both the ease of message formulation and repeated experience with the task, are reflected in measures of typing fluency and speed. Then, in Experiment 2, we presented select screen recordings of the typing behaviours from Experiment 1 to a group of independent observers who made epistemic judgements about the typist. Our results show that observable differences in typing speed and fluency contribute to perceptions of typist knowledge and confidence, which has implications for interfaces that enable real-time text-based collaboration.
Ticket Sales Accounting Information System Design at PT. Taman Rekreasi Sengkaling UMM

The diverse tourism sector with its uniqueness and supported by the facilities and means of transportation available in tourist areas can make it easy for tourists to visit tourist attractions. The development of information and communication technology marked by the existence of the internet has brought society into a new era. The information and communication technology revolution has been marked in which information has become a commodity and a force for those who control it. Based on observations and interviews that the authors conducted in the field and on the internet, there is no website-based application that can map tourist attractions at PT. Taman Rekreasi Sengkaling UMM. This study aims to design and build a website-based tourism ticket sales accounting information system to make it easier for local and foreign tourists to access information and visit tourism objects at PT. Taman Rekreasi Sengkaling UMM. The system design model uses ADDIE. Based on the results of the application design that has been done, namely a website-based ticket booking application. The application can be accessed using the website from a smartphone computer or laptop and can provide information related to existing tourist objects and assist relevant agencies in promoting tourism at the PT. Taman Rekreasi Sengkaling UMM.
THE EFFECT OF TREFFINGER, LAPS-HEURISTIC MODELS, AND MOTIVATION ON STUDENTS’ WRITING ACHIEVEMENT

This research was conducted with Quantitave research aimed to find out the students’ writing achievement taught by using Treffingers’ Learning Model and LAPS Heuristic Model and also to find out the students’ writing achievement with high and low motivation. The method of this research used was experimental research with factorial design 2x2. The sample of this study was XI IPA of SMA Negeri 1 Kota Lhokseumawe, which consisted of 36 students XI IPA, the sample was applied by random sampling technique. The instruments of this study were obtained by writing test and questionnaire sheet. The summary of post-test data description in each group of learning model showed in statistical is Treffingers’ Learning Model = 17.50 and LAPS Heuristic = 16.03. So, Treffingers’ Learning Model (17.50) &gt; (16.03) LAPS Heuristic Model. Then, the data were analyzed by using ANOVA test at the level of significant ? = 0,05. Based on the data analysis, the findings proved that the students’ writing achievement taught by using Treffingers’ Learning Model was higher than that taught by using LAPS Heuristic Model, with Fobs (20.13) &gt; Ftab (3.13).
Models of formation of professional competence of future teachers

The aim of the work was to develop and determine the effectiveness of the model for building future teachers’ professional competence. The aim was achieved through the use of calculations of the efficiency coefficient, the coefficient of practical effectiveness, the Cohen’s kappa coefficient. It was established that the interactive approach, which was used before the beginning of studies among 15% of students, enabled obtaining a higher level of their knowledge. The traditional education system made it possible to achieve a high level of knowledge among 31% of students. The development of a model for building professional competence of future secondary school teachers provided for the use of non-standard approaches and digital technologies (Coursera, Prometheus). It was found that students showed a high quality of material presentation (3.41) and a lower level of organization of the educational process (0.91) during teaching practice. The results contributed to highly effective knowledge of ecology, informatics, pedagogy/educational methodology acquired by high school students. It was determined that 62% of students developed high professional competence skills. The practical significance of the work is the developed system of future teachers’ professional competence through the introduction of non-standard approaches. The prospects of the research may be related to the provision of options for increasing the level of professional competence for future teachers of secondary and higher educational institutions.
The Development of Constructivist Flipped Classroom Learning Environments on Metaverse to Promote Problem Solving and Reasoning Skills in Mathematics of Secondary Education Grade 10th Students

This study investigates the effectiveness of a constructivist flipped classroom learning environment on Metaverse in promoting problem-solving and reasoning skills in secondary education Grade 10 mathematics students. Utilizing a one-group experimental design, a mixed-methods approach was employed to analyze the results, with a T-test yielding a significant value of .000. Results showed significant improvements in students' problem-solving and reasoning skills, as well as high levels of engagement and motivation in the virtual learning environment. The study suggests that the use of the Constructivist Flipped Classroom Learning Environments on Metaverse is a promising approach to enhance mathematics education, specifically in developing students' problem-solving and reasoning skills in a secondary education setting.
Entity Linking among Categorized Knowledge Resources for Computer Science Curricula

In educational information processing, both humans and computers require more effective information access than ever. However, there is one serious issue in text processing in higher education. The quantity of digitized text resources is not sufficient to develop large language models in specialized areas. General purpose language models often create unreliable results when the training data do not cover the target domain. To deal with this problem, our proposed method is designed to establish links between lecture course information and entities for real world knowledge. Owing to this entity linking, the meaning of text data can be more easily understood by humans and computers. Our method employs curriculum standards and university syllabus information to associate important keywords with text entities defined in Wikipedia articles. The results of evaluation experiments suggest the effectiveness of the proposed method in feature selection and entity linking for educational information. The contributions of this study include detailed comparison among dictionaries in Japanese morphological analysis. Our findings are expected to provide useful insights for researchers engaging in educational data analysis.
Semi-supervised Multi-class Classification Methods Based on Laplacian Vector Projection

Laplacian pair-weight vector projection (LapPVP) is a binary classifier for semi-supervised learning, which seeks a pair of projection vectors only for two-class data. This paper extends LapPVP to semi-supervised multi-class classification tasks and proposes two novel semi-supervised multi-class methods, named one-versus-one LapPVP (OVO-LapPVP) and one-versus-rest LapPVP (OVR-LapPVP). By using the strategy of “one-versus-one”, OVO-LapPVP decomposes a semi-supervised multi-class classification task into multiple binary problems that can be directly solved by multiple LapPVPs. Considering the concept of “one-versus-rest”, OVR-LapPVP is designed for generating multiple hyperplanes for multiple classes, one for each class. The above proposed semi-supervised multi-class classification methods both consider the discriminative information of labeled data and graph structure of unlabeled data. Experiments are conducted on nine UCI datasets to display the classification performance for multi-class data. Compared with other popular semi-supervised multi-class classification methods based on manifold regularization, the proposed semi-supervised multi-class classification methods hold the advantage of LaPVP and have better performance.
Enhancing Speech Translation in Medical Emergencies with Pictographs

In emergency care settings, there is a crucial need for automated translation tools. We focus here on the BabelDr system, a speech-enabled fixed-phrase translator used to improve communication in emergency settings between doctors and allophone patients. The aim of the chapter is two-fold. First, we will assess if a bidirectional version of the phraselator allowing patients to answer doctors’ questions by selecting pictures from open-source databases will improve user satisfaction. Second, we wish to evaluate pictograph usability in this context. Our hypotheses are that images will in fact help to improve patient satisfaction and that multiple factors influence pictograph usability. Factors of interest include not only the comprehensibility of the pictographs per se, but also how the images are presented to the user with respect to their number and ordering. We showed that most respondents prefer to use the interface with pictographs and that multiple factors influence participants’ ability to find a pictograph based on a written form, but that the comprehensibility of the individual pictographs is probably the most important.
Formation of informational and digital competence of the student of primary education by means of robotics

The article examines the problem of forming the information and digital competence of elementary school students by means of robotics. Our research work is aimed at analyzing the modern state of educational robotics, the readiness of educators for its teaching and experimental testing the possibilities of robotics as a means of forming information and digital competence of primary education seekers. The organization of pedagogical experiment meant diagnosis and correction of such components of information and digital competence as motivational, cognitive, active, reflexive, the formation of which took place in the course of pupils’ learning robotics constructors and interactive manuals devoted to the history and development of robots. To measure the level of information and digital competence of primary school pupils the system of expert assessments of its components was used. As a result of observing behavior, accuracy, speed and independence during the fulfillment of special tasks connected with the search and processing of information, computational thinking, work on the Internet, understanding the ethics of working with information etc. the level of information and digital competence of every pupil is defined as the sum of all its indexes. The generalization of the results allowed the conclusions: the use of robotics constructors and interactive manuals, online resources that imitate actions with robots help to increase the level of information and digital competence of education seekers.
Relating Academic Fields and Career Paths after College Education in Japan

This study aims to find efficient ways of future career-path selection by high school students by visualizing the relationship between academic fields and career paths after college graduation. In this study, we examine the relationship between major fields and career paths after college graduation by comparing types of universities: national or local public universities. Through the analyses, some differences were found in the distribution of the ratio of sub-classification of specialized/technical jobs that national and local public university graduates choose, suggesting the relationship between academic fields and career paths after college differs also by type of university. These results imply the value of the information provided for choosing the college and the major academic field in relation to the future career path.
Typology of students graduating from college using dropout probabilities

This study uses dropout probability to identify the degree to which students who graduated came close to dropping out and to examine how students who graduated went from being close to dropping out to graduating. Dropout probability is a number presented by Shiratori that represents how likely a student is to drop out [3]. Although the dropout probability has been used to analyze the patterns of students who dropped out of school, the process by which students graduated has not been analyzed. In this study, the dropout probability was used to quantify the student status of students who graduated, semester by semester and student by student, and the student status up to graduation was summarized as a transition vector. The transition vectors were then typified using k-means to create patterns of graduated student states. Among the students who graduated, we found that about 14% were in a state in which they could have dropped out. By analyzing the above patterns, we were able to determine how many students were in poor condition and at what stage they were likely to graduate.
Development of Android-Based Learning Media in Information Communication Technology (ICT) at Senior High School

Android-based learning media is one of the media that is easy to use by teachers and students in achieving learning objectives. This study aims to produce valid, practical, and effective learning media used for learning. The method used is Research and Development (R&amp;D) with a 4-D development model (four D models). This study used an instrument in the form of a questionnaire. The questionnaires were divided into validation questionnaires, practicality, and effectiveness questionnaires. For data analysis, researchers used Aiken's formula and Gain Score. The validation sheet is filled out by 4 validators consisting of 2 material validators and 2 media validator. The practicality sheet is filled out by 30 students and 2 teacher. For effectiveness data used questions filled out by students. The questionnaire data obtained a validity level of 0.95 which indicates that the developed media is valid. For practicality, the result is 90% with the very practical category. The effectiveness of the developed media is seen from the value of students. After using the media, 100% of students had scores above the KKM, while from the gain score test, they got a value of 0.75 which means that the learning media developed can be said to be effective. Based on these data it can be concluded that android-based learning media in Information and Communication Technology (ICT) subjects is valid, practical, and effective for use as learning media.&#x0D;
A Voice Recognition Based Game Design for More Accurate Pronunciation of English

The development of technology has made it considerably easier for people to meet a number of needs. Without technology, it is no longer possible to run certain applications. Nowadays, in many countries, the process of speaking English poses some problems in terms of different situations, such as allocating time for people. In this study, a game-based application was developed to help a person anywhere in the world pronounce English better. The application was implemented in C # programming language. The Speech.dll library was used to introduce voice commands to the system and to perform other necessary operations. Voice commands can be sent by the user via the wireless headset from anywhere in the shooting area. There is no need to wait at the computer while using the application because the developed application gives voice feedback to the user that it is right or wrong after the voice recognition process. In this application letter, word or sentence exercises can be done. The program aims to improve the level of pronunciation of people who want to improve their English speaking skills.
Research on key technologies of information-based production for basic surveying and mapping products

With the rapid development of surveying and mapping equipment and technology in the new situation, How to implement the information-based surveying and mapping production of major national projects more efficiently has become an important research content nowadays. This paper analyzed the key technologies of data pre-processing, standardized processing and quality inspection in production. It proposed intelligent solution for batch processing, computer discrimination, etc. Designed and developed the software system which covered the whole production. Verified by some major surveying and mapping production test, this technology roadmap is close to reality and completely penetrates every procedure of the production. It can improve the efficiency of production commendably, and has good practical application value. It has some reference significance for the new basic surveying and mapping which will be rolled out in full scale soon.
A comprehensive dataset for aspect-based sentiment analysis in evaluating teacher performance

Teacher performance evaluation is an essential task in the field of education. In recent years, aspect-based sentiment analysis (ABSA) has emerged as a promising technique for evaluating teaching performance by providing a more nuanced analysis of student evaluations. This article presents a novel approach for creating a large-scale dataset for ABSA of teacher performance evaluation. The dataset was constructed by collecting student feedback from American International University-Bangladesh and then labeled by undergraduate-level students into three sentiment classes: positive, negative, and neutral. The dataset was carefully cleaned and preprocessed to ensure data quality and consistency. The final dataset contains over 2,000,000 student feedback instances related to teacher performance, making it one of the largest datasets for ABSA of teacher performance evaluation. This dataset can be used to develop and evaluate ABSA models for teacher performance evaluation, ultimately leading to better feedback and improvement for educators. The results of this study demonstrate the usefulness and effectiveness of ABSA in evaluating teacher performance and highlight the importance of creating high-quality datasets for this task.
Comparative Analysis of Data Fusion Algorithms for Microscopic Road Traffic State Estimation under Partial-Connected Driving Environment

Connected vehicle data are emerging data sources for estimating urban road performances. However, significant errors can occur at a low market penetration rate of connected vehicles. To improve the accuracy of microscopic road traffic state estimation in a partial-connected driving environment, a generic data fusion framework of roadside fixed detector data and connected vehicle data was proposed. Gaussian Process Regression, Extreme Learning Machine, Random Forest, and Support Vector Machine algorithms were applied to the framework. A comprehensive analysis was conducted and results show that the traffic state estimation accuracy of fusion data is better and the accuracy of the data fusion method is promoted progressively. This method eliminates both the defects of the uneven spatial distribution of fixed detector data and the insufficient representation of low-MPR connected vehicle data. GPR is the most suitable for the data fusion framework and is easily implemented for real-time traffic control and management applications.
Pengaruh Model Pembelajaran Talking Stick Terintegrasi Saintifik Berbantuan Media Charta Terhadap Hasil Belajar Kognitif Peserta Didik Kelas VIII SMP Negeri 16 Halmahera Selatan

The scientifically integrated talking stick learning model assisted by charta media is a learning stage following the steps of the talking stick learning model with charta-assisted media to improve the ability of students' cognitive learning outcomes. This study aims to determine the effect of the scientifically integrated talking stick learning model assisted by chart media on students' cognitive learning outcomes. This research is a quasi-experimental research (Quasy Experiment). The sample of this study consisted of two classes, namely class VIII-1 as the experimental class and VIII-2 as the control class with a total of 35 students. The instrument used is a test to measure cognitive learning outcomes. Data analysis used the SPSS-assisted normality and homogeneity test, while the hypothesis test used the Anacova test. The results showed that the talking stick learning model with chart media had an effect on learning outcomes with a significant level of 0.05 0.001.
Map, Filter and Reduce

Python provides three functions that are widely used to implement Functional Programming style solutions in combinations with collection container types.