Reviewerly/exHarmony huggingface dataset:
The application of educational assistive devices by special teachers for the positive change of learning and school life of students with developmental disabilities

Objectives The purpose of this study is to examine the application experiences of assistive devices for the pos-itive change of learning and school life of students with developmental disabilities in special schools, and to ex-plore the significance of these experiences. Based on this, we aim to derive measures to activate the use of edu-cational assistive devices.&#x0D; Methods To achieve this, in-depth interviews were conducted with six special education teachers who have ex-perience applying assistive devices to students with developmental disabilities. The meaning of these experi-ences was analyzed following a comprehensive analytical procedure for qualitative data, and based on the ana-lyzed meaning of the experiences, measures for activation were also derived.&#x0D; Results The results of this study are as follows. First, for future participation in digital educational activities and communication, it is essential to utilize educational assistive devices for students with developmental disabilities. There's a need not just for support centered on special education teachers but for structural support at the school level. In particular, to address the issues revealed in remote learning due to COVID-19, there's a need to expand support for educational assistive devices, provide guides, develop curriculum content based on universal learning design, and increase home support through measures like digital tutors. Second, to enhance the usability of edu-cational assistive devices in school settings, it's necessary to conduct assistive technology assessments for stu-dents with disabilities based on their life stages. For systematic support of educational assistive devices at the national level, there's a need to establish structures like an “Educational Assistive Device Center.”&#x0D; Conclusions To apply educational assistive devices for students with developmental disabilities, there's a need to reframe not just as simply providing the devices but as offering individual-centered tailored service support. There's also a necessity to place assistive device experts within special education support centers or similar in-stitutions to ensure comprehensive and continuous assistive technology assessments and post-management at the local level.
Analysis of the path between the working environment, turnover intention, and work-life balance of early childhood teachers

Objectives This study examines the path relationship between early childhood teachers' working environment, turnover intention, and work-life balance, and then confirms the mediating effect of early childhood teachers' work-life balance.&#x0D; Methods To this end, questionnaires were distributed to 285 teachers working at kindergartens and daycare cen-ters in Area B, and 257 people were selected for analysis, excluding uncollected and unfaithful responses. Frequency analysis, path analysis, and mediating effect analysis were performed on the recovered data using SPSS 25.0 and PROCESS macro 4.0 versions.&#x0D; Results The results of the study are as follows. First, it was found that the working environment of early childhood teachers had a positive effect on the work-life balance. Second, it was found that the working environment had a negative effect on turnover intention. Third, it was found that work-life balance had a negative effect on turnover intention. Fourth, the work-life balance of early childhood teachers showed a partial mediating effect in the rela-tionship between early childhood teachers' work environment and turnover intention.&#x0D; Conclusions It is believed that lowering the intention of teachers to change jobs through systematic support and education for early childhood teachers' working environment and work-life balance can contribute a lot to improv-ing the quality of early childhood education institutions.
Proposal for Writing Education for Myanmar Korean Learners’: Focus on a Beginner Learner Needs Survey

Objectives The purpose of this study was to propose writing education based on the survey results on the needs of beginner Korean learners in Myanmar.&#x0D; Methods This survey involved 39 beginner learners attending the Yangon University of Foreign Languages in Myanmar and utilized research tools such as optional tasks, four-scale tasks, short-answer tasks, and multi-re-sponse tasks to examine how the learners recognized the writing and how the writing difficulty and demands changed. Except for the short-answer and multi-response tasks, frequency analysis was performed using the SPSS 26.0 program.&#x0D; Results Myanmar beginner learners are learning Korean intending to get a job or study abroad. Moreover, they recognized the importance of writing in Korean and were highly interested in writing. However, it took work to ac-tivate the schema when writing. When examining the preferences of writing teachers, many students preferred having both a native speaker and a Myanmar teacher in the same class, especially if they preferred a Myanmar teacher. Regarding learning topics and content preferences, preferences for daily life and dreams were high, while preferences for writing forms were diverse. Among them, it was found that travelogue writing, essays (letter or e-mail writing), and descriptive writing were the highest.&#x0D; Conclusions Through this study, we found out how Myanmar beginner learners' perceptions, difficulties, and de-mands for writing were achieved and presented educational proposals by reflecting on them. It has been con-firmed that learners require writing skills such as schema activation, topic-related vocabulary or target grammar, collaboration with fellow learners, social media to generate ideas related to writing topics, daily life and dreams, travel writing, and letter or e-mail writing. Therefore, it was suggested that teachers conduct writing classes con-sidering these points.
An Instruction for Pre-Service English Teachers’ Assessing Expertise Development: Process-Based Assessment Approach

Objectives Given the necessity and importance of improving the pre-service English teachers’ assessing ex-pertise, this study was to propose an instruction for improving their assessing expertise through process-based assessment, to conduct the instruction to them, and to examine their perceptions of it.&#x0D; Methods For this purpose, based on the literature on assessment theory and process-based assessment, an in-struction plan for improving assessing expertise through process-based assessment was devised. This was con-ducted on 20 pre-service English teachers at a university in Seoul in the second semester of 2022, and their per-ceptions of the instruction were analyzed through self-assessment, self-reflection reports, and a questionnaire survey.&#x0D; Results As for the instruction, six types of process-based assessing methods were used to organically link teach-ing, learning, and assessment throughout the semester, to manage the learner-centered class, and to provide them with individual feedback. As a result, the prospective English teachers were found to perceive that their as-sessing expertise was changed and developed in various aspects.&#x0D; Conclusions This study revealed that compared to the instruction through product-based assessment, focusing on paper-and-pencil tests, the suggested instruction was conducive to developing the prospective teachers’ knowledge, skills, and attitude toward the assessment field. Therefore, it was concluded that the instruction through process-based assessment could be a way to enhance prospective English teachers’ assessing ex-pertise and related research should continue to be conducted in the future.
The Possibility of high school credit system and ‘Chinese’ in the IB diploma program

Objectives According to the implementation of the high school credit system, we pay attention to the lack of dis-cussion on the opening of Chinese subjects in relation to the introduction of the IB diploma program, which has recently become a big issue in the education world. And We searched for the possibility of opening a IB Chinese subjects when operating an IB doploma program in a public high school in Korea.&#x0D; Methods For this study, through literature analysis, we introduce cases of schools that operate the IB curriculum among domestic high schools and compare and analyze them with cases of foreign IB World Schools to reveal the justification for opening IB Chinese courses and the necessary requirements for opening IB Chinese courses. Policy support was proposed.&#x0D; Results As a result of the study, there are many IB World Schools in Asia that open IB Chinese subjects, and con-sidering China's global status is gradually increasing, it is justified to open an IB Chinese subjects. However, there is no case of opening a Chinese subject in public high schools that currently operate an IB diploma grogram in Korea. It revealed that this was caused by the decision of English as a second foreign language based on the regu-lations governing DLDP in Korea.&#x0D; Conclusions In order to solve this problem, various programs such as fostering English-speaking Chinese teach-ers, producing IB Chinese textbooks, guaranteeing students' right to choose subjects through opening various foreign language subjects, opening courses tailored to the IB subject system, and providing social policy support in connection with universities and companies, etc. It was suggested that a level of political support is needed.
Machine Learning Approaches for Fake Reviews Detection: A Systematic Literature Review

These days, most people refer to user reviews to purchase an online product. Unfortunately, spammers exploit this situation by posting deceptive reviews and misleading consumers either to promote a product with poor quality or to demote a brand and damage its reputation. Among the solutions to this problem is human verification. Unfortunately, the real-time nature of fake reviews makes the task more difficult, especially on e-commerce platforms. The purpose of this study is to conduct a systematic literature review to analyze solutions put out by researchers who have worked on setting up an automatic and efficient framework to identify fake reviews, unsolved problems in the domain, and the future research direction. Our findings emphasize the importance of the use of certain features and provide researchers and practitioners with insights on proposed solutions and their limitations. Thus, the findings of the study reveals that most approaches focus on sentiment analysis, opinion mining and, in particular, machine learning (ML), which contributes to the development of more powerful models that can significantly solve the problem and thus enhance further the accuracy and efficiency of detecting fake reviews.
A Hardware Realization Framework for Fuzzy Inference System Optimization

The effectiveness of Fuzzy Inference Systems (FISs) in manipulating uncertainty and nonlinearity makes them a subject of significant interest for decision-making in embedded systems. Accordingly, optimizing FIS hardware improves its performance, efficiency, and capabilities, leading to a better user experience, increased productivity, and cost savings. To be compatible with the limited power budget in most embedded systems, this paper presents a framework to realize ultra-low power FIS hardware. It supports optimizations for both conventional arithmetic as well as MSDF-computing to be highly consistent with MSDF-based sensors. In MSDF-computing FIS all the processes of fuzzification, inference, and defuzzification are done on serially coming data bits. To demonstrate the efficiency of the proposed framework, we utilized Matlab, Chisel3, and Vivado to implement it from high-level descriptions of FIS to hardware synthesis. We also developed a Scala library in Chisel3 to establish a connection between these tools, bridging the gap, and facilitating design space exploration at the arithmetic level. Furthermore, we realized an FIS for the navigation of autonomous mobile robots in unknown environments. Synthesis results show the superiority of the output of our suggested design framework in terms of resource usage as well as power and energy consumption compared to the Matlab HDL code generator output.
Harnessing Syntactic Feature for Code Representation Learning

The paradigm of leveraging code as a dataset has recently gained traction, offering innovative solutions in domains such as automated commit message generation, pull request description automation, and program repair mechanisms. Consider the challenge in generating commit messages: traditional methods treat source code as a mere token sequence, applying neural machine translation models. This approach, however, overlooks the critical syntactic structures inherent in programming languages, which could offer deeper insights and improved accuracy. Building upon prior research, specifically the Code2Seq framework, which utilized Abstract Syntax Tree (AST) structural data for source code representation to automate method name generation, this paper extends and refines this concept. We introduce "CSR", a novel methodology adapted to represent code edits effectively. This paper investigates the impact of employing syntactic structure, focusing on the classification of code edits. Drawing inspiration from Code2Seq, "CSR" utilizes AST's structural properties, particularly the paths connecting leaf nodes, to enhance the task of code edit classification. This approach is rigorously evaluated on two distinct datasets, comprising fine-grained syntactic edits. Our comprehensive experiments reveal that incorporating syntactic structures does not significantly outperform simpler methodologies. While methods like Code2Seq and our proposed "CSR" show potential, our findings highlight that there is considerable scope for improvement and refinement before such techniques can be universally applied for learning representations of code edits. We anticipate that our findings will spark further research in this field, paving the way for more effective use of syntactic structures in code representation.
A NOVEL MULTIFREQUENCY GPS APP FOR STUDYING OLDER ADULTS: IMPROVING ACCURACY AND RELIABILITY OF DATA

Abstract Acquiring global positioning system (GPS) data can help researchers understand the relationship between older adult’s location/activity and their health, but existing GPS data collection modes suffer from issues with precision, consistency, and acceptability. Some limitations of current GPS mobile apps are satellite service disruption, power saving mode interference, miscalibration of device’s compass, and user-error during data collection which result in missing or inaccurate data. We present a novel multilingual GPS mobile app and live administrative dashboard to address these limitations. The app performs triangulation between GPS satellite data, nearest cellular tower, and WiFi router location data which are processed through a unique GPS algorithm with a mean error of only 1.5 meters. Since GPS data results in coordinates commonly reverse geo-coded to place-based datasets, the accuracy is critical in determining place type or other characteristics. The app is additionally designed with redundancy and fault tolerance in mind to run continuously in the background of a user’s smartphone, so there is no data loss from accidentally closing the application or restarting the phone. Moreover, this new application has a flexible sampling rate ranging from 1 second to 20 minutes. Sampling frequency flexibility can adjust the battery life and reduce the need to charge as frequently. Last, application programming interface (API) integrations allow for live data stream, which can improve monitoring and troubleshooting in the field. For research with older adult populations, these features can not only improve the accuracy of collected data but also increase the acceptability of collecting GPS data.
ONLINE AUTHENTIC MATERIALS IN TEACHING ENGLISH FOR EFL STUDENTS

This qualitative case study investigates the use of online authentic materials in teaching English at SMPN 2 Tinambung . The study aims to identify the types of online authentic materials used, teachers’ perceptions of their use, and the challenges faced by teachers in using them. Two English teachers were selected using purposive sampling. The results show that teachers used various types of online authentic materials such as YouTube videos, Google pictures, online articles, online news, podcasts, and web short stories. The teachers perceived online authentic materials to be similar to face-to-face authentic materials, but with different media. They were able to adapt the materials based on their needs and purposes. However, they preferred face-to-face meetings due to fewer problems. Challenges in the implementation of online authentic materials included internet connection, classroom management, and language difficulty.
UNDERSTANDING THE NEW NIH DATA SHARING REQUIREMENTS: WHY THEY IMPROVE THE QUALITY OF RESEARCH

Abstract In 2021, NIH began a long period of planning, drafting, and requesting public comment to create a new data-sharing policy, beginning with a Request For Information (RFI). The new policy, beginning January 25, 2023, will apply broadly to all scientific data produced with NIH funding. NACDA and (ICPSR), drawing upon our expertise and understanding of best practices for data sharing, have been working actively to develop tools and resources to assist NIH grant recipients in complying with federal data-sharing expectations with minimal disruptions to their research. This presentation will provide a detailed overview of the new data-sharing requirements and how to incorporate them into the required data-sharing plan. We will offer examples of successful data-sharing plans, identifying an appropriate repository, budgeting for the data preparation process, and creating informed consent documents consistent with the spirit of the NIH Data Sharing requirements. In addition to explaining the new data-sharing policy, the presentation will discuss the rationale behind the requirements and how they contribute to data equity using the FAIR principles. By increasing access to federally funded data, we contribute to a multidisciplinary approach that enhances cross-disciplinary communication and a broad understanding of different ways of knowing when working collaboratively with other researchers. Team Science has facilitated substantive discourse between qualitative and quantitative specialists. Multidisciplinary research increasingly represents a critical aspect of overall knowledge creation. Finally, the presentation will illustrate how data-sharing increases the impact of studies and enhances the credentials of researchers who engage in data-sharing.
EXPLORING THE POTENTIAL OF CHATGPT FOR ASSESSING DELIRIUM SYMPTOMS IN OLDER ADULTS WITH COGNITIVE IMPAIRMENT

Abstract Delirium is a common and serious geriatric syndrome, especially in older adults with cognitive impairment. Accurate caregiver assessment and reporting of delirium in community-dwelling older adults can help healthcare providers diagnose and treat delirium more effectively. Yet, caregivers often lack confidence in their ability to accurately assess and report delirium. An automated method to detect the presence and symptoms of delirium could potentially boost caregiver confidence and assist with more accurate delirium assessment and reporting. This study explored the use of ChatGPT, a generative AI based on the Large Language Model (LLM), to detect the presence and symptoms of delirium. We trained ChatGPT using a series of prompts specifically designed to enhance its understanding of the domain knowledge and the scoring mechanism of a caregiver-centered, seven-item delirium assessment, the Sour Seven. The trained ChatGPT model was asked to identify and score various delirium symptoms in five previously validated geriatric case vignettes using the Sour Seven scale. Each case was repeated three times to test for reliability. The ChatGPT assessment results were compared against those of human experts. The preliminary analysis showed that items 3, 6 and 7 were scored correctly in all cases, but mixed results were found on items 1, 2, 4, and 5, mostly because the AI applied a single symptom statement to multiple items. Overall, the results indicate that generative AI has the potential to accurately capture and represent complex delirium symptoms in natural language, which could assist caregivers in accurately identifying and reporting delirium symptoms.
CHATGPT, WHAT IS A DEDUCTIBLE? DIGITAL ASSISTANTS AS AN INFORMATION SOURCE FOR MEDICARE QUERIES

Abstract Since being first introduced to the public in late 2022, chatbots that are based on large language models (LLMs) have attracted a great deal of attention. However, despite their popularity, these chatbots have been shown to give inaccurate information in response to user queries. Several polls conducted in 2022 suggest that the public is generally skeptical about the use of Artificial Intelligence (AI), particularly in the context of healthcare, and older adults are the most distrustful age group, despite the fact that they are the least likely to have interacted with an LLM such as ChatGPT. Meta-analysis on trust in AI has shown that users are most influenced by the accuracy and reliability of the AI trustee. In our study, we assessed the accuracy of speaker-based assistants, Alexa and Google Assistant, as well as two LLMs, Bard and ChatGPT4 on Medicare terminology and knowledge and compared their accuracy to that of a large representative sample of Medicare beneficiaries. Google Assistant was found to perform significantly worse than beneficiaries on both terminology and knowledge questions. Alexa was found to perform significantly worse than beneficiaries on terminology questions. Conversely, both Bard and ChatGPT4 were found to perform significantly better than beneficiaries on both terminology and knowledge questions. We conclude that Medicare beneficiaries should not rely on Google Assistant for terminology help or general knowledge queries, nor should they rely on Alexa for terminology help. ChatGPT4 and Bard are potentially valuable resources for beneficiaries with terminology-based and general knowledge queries.
A Study on the Use of Plastic Instruments in Music Curriculum towards the Plastic-Free Era

The purpose of this study is to find plastic instruments used in music curriculum and provide alternative instruments, which are the cause of environmental pollution. For this purpose, the plastic instruments used in 72 music textbooks published from the 1st to the 2015 revised curriculum were organized and analyzed. As a result of this study, first, plastic recorder and melodica(melodion) were used for the first time in music textbooks applied to the 2nd curriculum(1963-1973). Second, plastic instruments such as recorder, melodion, tambourine, sogo drum, egg shakers, and boomwhackers were found in music textbooks. Lastly, the number of musical instruments made of plastic has increased slightly in authorized music textbooks. For ecological sustainability, it is necessary to reduce the use of plastic instruments in music textbooks and provide instruments made of eco-friendly materials and wood.