Use Of Tool Research Articles

Engineering students' perceptions and actual use of AI-based math tools for solving mathematical problems.

Engineering students' perceptions and actual use of AI-based math tools for solving mathematical problems.

A phase I pilot study of a mobile education tool for supporting pregnant women with opioid use disorder.

A phase I pilot study of a mobile education tool for supporting pregnant women with opioid use disorder.

“Exploring the Use of Artificial Intelligence Tools in Teaching and Learning by Degree College Faculty”

This study investigates the adoption and utilization of Artificial Intelligence (AI) tools in teaching and learning among degree college faculty in Vijayapur District. Utilizing a structured questionnaire, data were collected from 100 faculty members across various disciplines. The research examines faculty perceptions, frequency of AI tool usage, challenges faced, and the impact on teaching efficacy. Statistical analyses, including descriptive statistics and chi-square tests, were employed to interpret the data. Findings indicate a growing interest in AI tools, with significant variations in usage patterns across disciplines and demographic factors. The study concludes with recommendations for enhancing AI integration in higher education.

Utilization and Satisfaction with Three Languages of Dental Terminology E-book

Objectives: With the rising number of Chinese residents in Thailand and Chinese becoming a global language, compelling messages and communication in healthcare are crucial for accurate information and optimal treatment. This pilot study investigated Thai dentists' utilization and satisfaction with the developed electronic “Three Languages of Dental Terminology (TLDT)” book. Methods: Three hundred and thirteen dentists who graduated from the College of Dental Medicine, Rangsit University, were invited to the online survey using Google Forms. Demographic data, translation tool usage data, initial TLDT experience, and objectives in using TLDT were explored. TLDT utilization and satisfaction were assessed. Fisher's exact test and Pearson's Chi-Square were utilized to analyze the data. Results: Eighty-eight (28.1%) dentists responded to the questionnaire. Respondents met foreign patients monthly, with Chinese patients being the most common group. Most dentists lacked Chinese fluency and relied on translation tools (68.2% use Google Translate). Dentists primarily used TLDT to translate Thai to English (53.4%) and English to Thai (42.0%). Thai, English, and Chinese usage patterns aligned with TLDT's goals, indicating successful implementation (p<0.05). Regarding utilization, TLDT was significantly associated with all objectives (p<0.05) except for spelling accuracy (p=0.06). Most respondents reported high satisfaction scores related considerably to finding words, word pairings, and text accuracy (p<0.05). Postgraduate levels respectively correlated with increased TLDT content satisfaction (p=0.02). Conclusions: The TLDT e-book demonstrates promise as a valuable resource for healthcare personnel, improving dental terminology communication in English and Chinese and might optimize dental care and postgraduate dental education in Thailand.

Empowering the Workforce: Evaluating AI-Driven Employee Self-Service Portals in the Digital HR Era

ABSTRACT: This study investigates how Artificial Intelligence (AI) is transforming Employee Self-Service (ESS) portals and their impact on empowering employees in today’s digital HR environment. The main aim is to evaluate how AI features such as automation, chatbots, and smart assistance help employees manage HR tasks independently, leading to greater efficiency, satisfaction, and engagement. A mixed-method approach was adopted, combining quantitative data from 150 employee questionnaires and qualitative insights from interviews with HR professionals. Descriptive statistics (mean and standard deviation) and inferential methods (correlation and regression analysis) were used to analyze survey data using SPSS. Thematic analysis was applied to qualitative data to identify patterns and employee perceptions. Findings reveal that AI-driven ESS portals significantly improve service speed, employee autonomy, and overall satisfaction. There is a strong positive relationship between the usability of AI tools and employee empowerment. However, challenges such as data privacy concerns, limited training, and occasional technical issues were also reported. A small percentage of employees prefer traditional human interaction for certain HR processes. The study concludes that AI-powered ESS portals are effective tools for improving employee empowerment and HR service delivery. To maximize impact, organizations must focus on user-friendly design, continuous training, and ethical data handling to ensure trust and inclusive benefits for all users. Keywords: Artificial Intelligence, Employee Self-Service, Digital HR, Employee Empowerment, HR Technology, Automation, Chatbots.

"Exploring Student Perspectives on AI-Driven Entrepreneurship- a Study in Incubator Centers"

The rapid evolution of Artificial Intelligence (AI) is reshaping entrepreneurship, particularly within academic incubator centers where student-led startups are emerging as significant contributors to innovation. The study investigates student entrepreneurs’ awareness, perception, and usage of AI tools in incubator centers in Bangalore. With a structured questionnaire administered to 128 student entrepreneurs, the research evaluates the relationship between students’ AI awareness and tool usage, the perceived impact of AI on entrepreneurial success, and how accessibility and affordability influence attitudes toward future AI integration. Findings reveal a strong correlation between AI awareness and usage, with AI users reporting enhanced decision-making and greater perceived startup success. The study also highlights that students’ favourable perceptions of AI accessibility significantly influence their willingness to adopt AI in future ventures. These insights emphasize the critical role of AI readiness in academic entrepreneurship and call for policy and educational frameworks that strengthen AI fluency among students in incubator ecosystems.

Performance and Developer Experience Comparison of Redux, Zustand, and Context API in React Applications

React applications gain their efficiency and scalability through a fundamental principle called state management. This study achieves a comparison of Redux along with Context API and Zustand based on their performance, scalability and developer experience combined with practical usage characteristics. The study conducts research on application responsiveness and re-rendering efficiency, and maintainability based on benchmarking alongside usability tests and actual tool usage during evaluations. Programs requiring complex data flow should use Redux yet Zustand works best for projects with moderately complex state management needs. Context API provides an acceptable state management tool for small projects while resolving prop-drilling issues. This study investigates multiple solution combinations to fulfill projects of different complexity. This output will enable developers and engineering teams to determine appropriate state management techniques which meet their project needs including complexity level and scaling expectations.

Technology Readiness Drives Digital Adoption in Dentistry: Insights from a Cross-Sectional Study.

Background/Objectives: Digital transformation is reshaping dentistry by improving clinical efficiency, diagnostic accuracy, and patient care. However, the adoption of digital technologies in dental clinics varies widely, influenced by multiple factors, including technology readiness. This study aimed to assess the relationship between technology readiness and digital technology adoption among German dentists, focusing on the impact of clinic characteristics and professional development. Methods: A cross-sectional survey was conducted among 200 licensed German dentists. Technology readiness was measured using the validated Technology Readiness Index (TRI 2.0), encompassing four dimensions: optimism, innovativeness, discomfort, and insecurity. Data on the current use of digital technologies were collected, including digital radiography, CAD/CAM systems, AI-supported tools, and patient management solutions. Statistical analyses included correlation and quartile-based comparisons to identify patterns and significant associations. Results: Clinics with higher TRI scores demonstrated significantly greater adoption of digital technologies. Larger clinics (MVZs) showed higher levels of digital integration compared to solo practices. Younger dentists and those engaged in continuous professional development exhibited higher technology readiness and usage of advanced digital tools. No significant gender-based differences were identified in technology readiness or digital adoption. While basic technologies like digital radiography and CAD/CAM systems were widely used, AI-based diagnostics and 3D printing remained underutilized. Key barriers included financial constraints and limited training opportunities. Conclusions: Technology readiness plays a critical role in shaping digital adoption in dental clinics. The findings highlight the need for targeted support, especially for smaller clinics, through professional training and investment in digital infrastructure. This study contributes to a better understanding of digital transformation in dentistry and supports strategies aligned with global health goals to improve access to digital care.

Classroom Teachers' Competencies in Using Web 2.0 Tools: Predictive Roles of Individual Innovative Characteristics and Socio-demographic Variables

This study aims to examine the level of competence in using Web 2.0 tools and individual innovativeness of classroom teachers and to determine the relationship between these variables. The sample of this relational survey-type study consisted of 309 classroom teachers working in two districts of Şırnak province in the 2023-24 academic year. Individual Innovation Scale and Web 2.0 Tools Usage Competence Scale were used as data collection instruments. In the data analysis, classroom teachers' Web 2.0 Tools Usage Competence and Individual innovativeness levels were examined using descriptive statistics, also the total Web 2.0 Tools Usage Competence scores were modeled in a linear regression equation. The study revealed that both the classroom teachers' competency levels in using Web 2.0 tools and their individual innovativeness levels were at a moderate level. While male teachers had a higher average in terms of competence in using Web 2.0 tools, female teachers had a higher average in terms of individual innovativeness levels. Another noteworthy finding is that both of the average scores of the competency levels in using Web 2.0 tools and individual innovativeness levels for teachers with postgraduate education were higher than all other categories. As a result of the regression analysis, it was concluded that individual innovativeness was not a significant predictor affecting the Web 2.0 tools usage competence score. However, having postgraduate education, teaching 4th grade, and receiving in-service training were significant predictors that positively affected the Web 2.0 tools usage competence. Some suggestions were made in the context of the findings.

Applying generative artificial intelligence applications for academic research on firms’ nonlinear internationalization

Purpose This study aims to critically evaluate the applicability of generative artificial intelligence (GenAI) tools for academic research in international business (IB), specifically focusing on the topic of firms’ nonlinear internationalization. It assesses these tools’ key performance dimensions: correctness, hallucinations and thoroughness. Design/methodology/approach This research adopts an exploratory approach, examining a comprehensive set of GenAI tools: eight chatbots and four AI-driven applications designed for academic purposes. The evaluation focuses on the capabilities and limitations of these tools in generating accurate research-related content for IB scholars. Findings This study finds that while GenAI tools capture some aspects of nonlinear internationalization, they often produce partially accurate and/or biased results. Common issues include providing fictitious sources, incorrect publication data and vague or incorrect answers. Thus, substantial development is still needed for GenAI tools to become reliable for scientific research. Practical implications Researchers should use GenAI tools with caution, verifying the accuracy of generated content and citations independently. A cautious approach is crucial to maintain the integrity and quality of academic research. Social implications This study raises awareness about ethical and practical challenges of using AI in academia, including issues related to plagiarism and misinformation. It underscores the importance of critical evaluation when using GenAI tools for research. Originality/value This paper contributes to the emerging literature on the role of GenAI in academic research by providing a critical assessment of the usability and limitations of current tools in studying complex IB phenomena. By using nonlinear internationalization as an example, it demonstrates how GenAI may support or hinder IB scholarship.

Generative AI tool use enhances academic achievement in sustainable education through shared metacognition and cognitive offloading among preservice teachers

The integration of generative artificial intelligence tools in education has emerged as a transformative approach to enhancing learning outcomes, particularly in the context of sustainable development goals (SDG4). Therefore, the present study investigates the connection between generative artificial intelligence tool usage (GenAITU) and academic achievement (AA) in the context of SDG4. We assessed the mediating role of shared metacognition (SMC) and cognitive offloading (COL) in this relationship among preservice teachers (PSTs). The indicators, including performance expectancy (PE), effort expectancy (EE), facilitating conditions (FC), and use behavior (UB), are derived from adapting the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) for GenAITU. The authors surveyed 465 students from five universities in Wuhan, China, using a 7-point Likert scale through a time-lag design. Statistical analysis was performed through partial least squares structural equation modeling (PLS-SEM), to determine the relationship between variables. Findings indicated that two components of GenAITU, namely PE and UB, showed significant positive associations with AA, while the other two, EE and FC, did not show significant and positive relationships with AA. Results also showed that three dimensions of GenAITU, namely EE, FC, and UB have a positive and significant association with SMC while PE has a positive and significant connection with SMC. All four components of GenAITU like PE, EE, FC, and UB have positive and significant links with COL. SMC and COL have a positive and significant relationship with AA. Results also indicated that SMC mediated the connections between GenAITU (EE, FC, and UB) and AA. Outcomes also indicated that COL mediated the connections between GenAITU (PE, EE, FC, and UB) and AA. The current study shows that SMC and COL were strong mediators of the association between GenAITU and AA. The results of our study provide guidance to teachers, curriculum planners, and university management to successfully integrate GenAITU into the education for PSTs.

Global Health care Professionals' Perceptions of Large Language Model Use In Practice: Cross-Sectional Survey Study.

ChatGPT is a large language model-based chatbot developed by OpenAI. ChatGPT has many potential applications to health care, including enhanced diagnostic accuracy and efficiency, improved treatment planning, and better patient outcomes. However, health care professionals' perceptions of ChatGPT and similar artificial intelligence tools are not well known. Understanding these attitudes is important to inform the best approaches to exploring their use in medicine. Our aim was to evaluate the health care professionals' awareness and perceptions regarding potential applications of ChatGPT in the medical field, including potential benefits and challenges of adoption. We designed a 33-question online survey that was distributed among health care professionals via targeted emails and professional Twitter and LinkedIn accounts. The survey included a range of questions to define respondents' demographic characteristics, familiarity with ChatGPT, perceptions of this tool's usefulness and reliability, and opinions on its potential to improve patient care, research, and education efforts. One hundred and fifteen health care professionals from 21 countries responded to the survey, including physicians, nurses, researchers, and educators. Of these, 101 (87.8%) had heard of ChatGPT, mainly from peers, social media, and news, and 77 (76.2%) had used ChatGPT at least once. Participants found ChatGPT to be helpful for writing manuscripts (n=31, 45.6%), emails (n=25, 36.8%), and grants (n=12, 17.6%); accessing the latest research and evidence-based guidelines (n=21, 30.9%); providing suggestions on diagnosis or treatment (n=15, 22.1%); and improving patient communication (n=12, 17.6%). Respondents also felt that the ability of ChatGPT to access and summarize research articles (n=22, 46.8%), provide quick answers to clinical questions (n=15, 31.9%), and generate patient education materials (n=10, 21.3%) was helpful. However, there are concerns regarding the use of ChatGPT, for example, the accuracy of responses (n=14, 29.8%), limited applicability in specific practices (n=18, 38.3%), and legal and ethical considerations (n=6, 12.8%), mainly related to plagiarism or copyright violations. Participants stated that safety protocols such as data encryption (n=63, 62.4%) and access control (n=52, 51.5%) could assist in ensuring patient privacy and data security. Our findings show that ChatGPT use is widespread among health care professionals in daily clinical, research, and educational activities. The majority of our participants found ChatGPT to be useful; however, there are concerns about patient privacy, data security, and its legal and ethical issues as well as the accuracy of its information. Further studies are required to understand the impact of ChatGPT and other large language models on clinical, educational, and research outcomes, and the concerns regarding its use must be addressed systematically and through appropriate methods.

The Opinions of Academics on the Usage of Artificial Intelligence Tools in Primary Schools

Within the scope of this research, it is aimed to obtain academician opinions on the use of artificial intelligence applications such as ChatGPT in the teaching-learning process and classroom applications in primary schools. In this research, the case study method, which is one of the qualitative research approaches, was used. The study group of the research consists of 10 academicians working in state and foundation universities. A semi-structured interview form prepared by the researchers was used as a data collection tool. The data obtained were analyzed by content analysis method. The findings reveal that artificial intelligence tools make significant contributions to the teaching-learning process in areas such as measurement and evaluation and material preparation; to teachers in terms of saving time and understanding the curriculum; to professional development in terms of following the literature and improving field knowledge; and to students in areas such as increasing motivation and supporting individual learning. However, negative aspects such as ethical and security issues, weakening of higher-order thinking skills in students, and mislearning were also pointed out. In addition, it was stated that artificial intelligence tools can be used effectively in various classroom applications in social studies, Turkish, mathematics and science courses. The study emphasizes the importance of balanced and conscious integration of artificial intelligence in education.

Development, effectiveness, and usability of a home-based exercise education video on neck control among Nigerian children with cerebral palsy

Despite the many proven benefits of home programs, there are many challenges in their effective use and administration by caregivers for children with cerebral palsy (CP), leading to poor adherence and outcomes. This study aimed to develop and test the feasibility of a home-based exercise education video among caregivers of children with CP. This two-phase quasi-experimental study involved 24 purposively selected children with CP and their caregivers attending two randomly selected physiotherapy clinics in Nigeria. Ethical approval for the study was obtained from the Ethics and Research Committee, Obafemi Awolowo University Teaching Hospital, Nigeria (ERC/2024/02/23). An instructional video was developed and administered to caregivers for 6 weeks. Neck control was assessed using the Clinical Rating Scale for Head Control (CRSHC) and Gross Motor Function Measure-88 (GMFM-88). The usability of the video tool was assessed using a feasibility questionnaire. Data were analyzed using descriptive statistics and repeated-measure ANOVA. Alpha value was set at p < 0.05. Results of CRSHC showed significant improvements in neck control in prone (F = 5.32; p = 0.032), supine (F = 11.537; p = 0.000), and supported-sitting (F = 21.421; p = 0.000) positions. The GMFM-88 results also showed significant improvements in neck control in supine (lifts head 45⁰) (F = 7.15; p = 0.004), supine (pull to sitting) (F = 7.000; p = 0.004), prone (lifts head upright) (F = 12.571; p = 0.005) and supported-sitting (F = 18.192; p = 0.001) positions across time points. 12.571; p = 0.005) and supported-sitting (F = 18.192; p = 0.001) positions across time points. Caregivers found the neck exercise video content clear, relevant, and engaging. This study concluded that the video-based exercise tool had good usability among caregivers of children with CP and effectively improved neck control among children with CP.

Digital tools and the learning of mathematics in basic education

In this work, the impact of digital tools on the learning of mathematics in basic education students was evaluated. The methodology combined qualitative and quantitative approaches, using surveys to collect data on the accessibility, usability, effectiveness, and security of digital tools, as well as on math performance. The results indicated that, although students have access to and frequently use digital tools, the perceived effectiveness is moderate due to the lack of teacher training. The perception of security and confidence in these tools varies, and the attitude towards learning mathematics shows an intermediate interest. The conclusions suggest the need to improve teacher training and optimize teaching and assessment strategies in mathematics.

Computer Vision Techniques for Detection and Tracking of Surgical Instruments in the Operating Room

In response to the ever-growing demand for real-time intraoperative intelligence in modern operating rooms, surgical instrument detection and tracking as a part of computer vision techniques for surgical instruments has made significant progress. These methods are applied as tool usage analysis and skill evaluation, autonomous assistance, and surgical workflow optimization. Deep learning architectures like CNNs, transformers, as well as HA, although they have recently emerged for SPTIC, still face challenges associated with occlusion, visual ambiguity, domain variability, or real-time performance. The state-of-the-art approaches, their experimental performance are reviewed, and gaps preventing clinical deployment are identified. The emphasis is made in terms of the evaluation metrics, the algorithmic advancements, and the system integration. The last section concludes with discussions of unresolved issues and possible directions to further develop the clinical utility of these technologies.

Artificial Intelligence Powered Tools Usage and Writing Proficiency of the Junior High School Students of Ambalayat Integrated School

This study aimed to investigate the impact of AI-powered writing tools, specifically ChatGPT, Grammarly, Chatbot ai, Cici, and Meta AI, on the writing proficiency of Grade 9 students at Ambalayat Integrated School. The primary objectives were to assess the effectiveness of these tools in enhancing various dimensions of writing, including content and ideas, organization and structure, language and style, and grammar and mechanics. Furthermore, the research sought to understand the relationship between students' demographic profiles, their usage of AI tools, and their writing competencies, thereby providing valuable insights into the integration of technology in educational practices. The methodology employed a descriptive-correlational research design, allowing for the exploration of relationships without manipulating variables. A sample of 42 Grade 9 students, actively engaged in writing classes, completed standardized writing assessments and a structured questionnaire that gathered data on their demographic information and AI tool usage. The gathered data were categorized using frequency and percentage distributions, followed by statistical analysis to determine significant relationships between AI tool usage and writing proficiency through Point Biserial Correlation. This rigorous treatment ensured that the findings were statistically grounded and credible, providing a comprehensive evaluation of the effectiveness of the AI tools in improving writing skills. The findings revealed that students showed varying levels of proficiency in their writing abilities, significantly influenced by demographic factors such as access to technology and familiarity with AI tools. Notably, it was found that students who frequently utilized the mentioned AI writing applications demonstrated marked improvements in their writing competencies across multiple dimensions. This positive correlation indicated that while AI tools contributed to the initial stages of writing development, higher-order skills, such as organization and style, still required critical thinking and human guidance. Based on these findings, the study recommended several strategies for the effective implementation of AI in the curriculum, including adopting a Language Policy on the Use of AI in Writing. This policy aimed to ensure ethical usage of AI tools while promoting independent learning among students. The recommendations also stressed the need for professional development for educators and the establishment of a feedback mechanism, enabling continuous improvement in writing instruction. Overall, this research contributed significantly to understanding how AI tools can enhance writing skills in a K-12 educational context and identified areas for future exploration and development.

The Wite Way Forward: Learners’ Experiences on the Utilisation of Artificial Intelligence Tools In Research Writing

This phenomenological study investigates the experiences of Senior High School learners at Glan School of Arts and Trades in utilizing Artificial Intelligence (AI) tools for research writing. Since there are limited studies on AI in K-12 research writing in the Philippines, I conducted in-depth interviews with eight purposively selected learners that delve into their perceptions, challenges, and benefits associated with AI tool usage. The findings reveal a complex interplay of advantages and concerns. While learners appreciate AI's capacity to enhance grammar, generate ideas, and manage citations, they also express concerns regarding overreliance and potential ethical implications, such as plagiarism and lack of original thought. The study highlights the need for a balanced approach to AI integration in academic research, emphasizing the importance of human oversight and critical evaluation. This study contributes to the growing body of research on AI in education, providing valuable insights into the experiences and perspectives of young learners. By understanding the benefits and limitations of AI tools, educators can develop strategies to support students in using these technologies responsibly and effectively. Furthermore, the findings of this study can inform the development of guidelines and policies for the ethical and appropriate use of AI in educational settings.

TDAG: A multi-agent framework based on dynamic Task Decomposition and Agent Generation.

TDAG: A multi-agent framework based on dynamic Task Decomposition and Agent Generation.

Digital health tools in juvenile idiopathic arthritis: a systematic literature review

BackgroundNowadays, digital health technologies, including mobile apps, wearable technologies, social media, websites, electronic medical records, and artificial intelligence, are impacting disease management and outcomes. We aimed to analyse the characteristics and use of digital health tools in juvenile idiopathic arthritis (JIA).MethodsWe conducted a systematic review (SR) to identify articles examining the characteristics, use, and outcomes (feasibility, usability, and effectiveness) of digital health tools in JIA patients. A sensitive search strategy was performed in Medline, Embase, and Cochrane databases until December 2022 (later updated to March 2024). Two reviewers independently selected the studies and collected the data, including study quality. A descriptive analysis was performed.ResultsA total of 21 studies were included, one SR, six randomised controlled trials, four observational studies, four validation studies, one discovery and verification study, and five qualitative studies. Study quality was generally moderate. Most studies focused on patients with JIA (especially young people), but also on parents and health care professionals. Different digital health technologies were investigated, like websites, mobile apps, wearables, and telemedicine. The main objectives of the tools were self-management, symptom and quality of life monitoring, physical activity tracking, disease knowledge improvement, and medication monitoring. Different themes and contents were usually included in the same digital health tool, such as psychological health, lifestyle, intimacy, or shared decision-making. Tool development and validation processes were poorly or not at all described, and data regarding regulatory compliance, security, or privacy were scarce.ConclusionsThere is significant variability in the type, characteristics, objectives, and contents of digital health tools for JIA. They still show limitations and gaps, thus highlighting the need for better critical assessment and reporting.