Use Of Artificial Intelligence Tools Research Articles

Importance of University Students’ Perception of Adoption and Training in Artificial Intelligence Tools

Undoubtedly, artificial intelligence (AI) tools are becoming increasingly common in people’s lives. The educational field is one of the most reflective on the importance of its adoption. Universities have made great efforts to integrate these new technologies into their classrooms, considering that every future professional will need AI skills and competencies. This article examines the importance of student perception and acceptance in adopting AI tools in higher education effectively. It highlights how students’ positive perceptions can significantly influence their motivation and commitment to learning. This research emphasizes that to integrate AI into university curricula successfully, it is essential to include its technologies in all areas of study and foster positivity among students regarding their use and training. This study’s methodology applied the validated instrument “Perception of Adoption and Training in the Use of Artificial Intelligence Tools in the Profession” to a sample of Mexican students. This exploratory analysis highlights the need for educational institutions to understand and address student perceptions of AI to design educational strategies that incorporate technological advances, are pedagogically relevant, and align with the students’ aspirations and needs.

Evaluating the Impact of AI-Personalized Learning Systems in Higher Education; Examining how They Affect Academic Performance across Different Age Groups at Kumasi Technical University

Revolutionizing education by introducing innovative methods to enhance student experiences has birthed Artificial Intelligence (AI). This article provided an in-depth overview of AI's educative and transformative influence, particularly concentrating on learning outcomes for students of all ages at Kumasi Technical University. AI amalgamation in education has enabled modified learning experiences tailored towards each learner's unique needs. The purpose of this study sought to investigate the effects of AI-personalized learning systems on academic performance across different age groups in higher education institution. The researcher employed a quantitative research design, using a face-content verified structured questionnaire to collect data from respondents, with expert consultation. Forty-five students from Kumasi Technical University's engineering and procurement departments were selected using the convenience sampling technique. The findings provided valuable insights into the use of AI-driven personalized learning platforms in higher education. The data revealed higher adoption rates among undergraduates compared to postgraduates, and a greater likelihood of use among men than women, highlighting gender disparities and potential areas for targeted support. The predominant use of AI tools by younger students demonstrated their comfort with emerging technology, while the low participation of older students suggested potential adoption barriers. Statistical analyses (Pearson correlation; (r (43) = 0.166, p = 0.265) and linear regression; (R^2 of 0.03), (F (1, 45) = 1.25, p = 0.265) indicated that age did not significantly correlate with academic success in the context of AI use, despite extensive integration of AI learning systems in academic courses. Contrary to expectations that younger students' engagement with AI tailored learning systems would positively impact their academic performance compared to those over thirty, no significant correlation between age and academic achievement was found. These findings underscore the need for further research into other factors that may influence the effectiveness of AI learning systems.

Digital skills in the use of artificial intelligence tools for the formulation of formative research projects from the TECSIS Research Seminar.

Artificial intelligence (AI) has promoted a change in the way research and innovation (R&D) is performed bringing new perspectives, automating time and routine tasks contributing to the generation of knowledge. To take full advantage of the potential of AI, it is proposed to develop strategic digital skills for the use of artificial intelligence tools in the formulation of formative research projects from the TECSIS Research Seminar. The methodology corresponds to a qualitative research with a descriptive analytical approach with a cross-sectional approach in four stages: analysis, design, evaluation and dissemination. The population under study includes the students of the special programs of Computer Engineering and Systems Technology of the University of Caldas. The expected result is the characterization of strategic digital skills of use for the formulation of formative research projects. This project will contribute in the development of a methodological route that exposes in a practical and applied way the strategic digital skills of use of AI tools for the formulation of formative research projects for the special programs of the University.

Формування графічної компетентності майбутніх фахівців технічних спеціальностей засобами штучного інтелекту

The article considers the use of artificial intelligence tools to improve the efficiency of teaching graphic disciplines. The article analyses the possibilities of AI for personalising the learning process, automated assessment, providing interactive tasks and real-time feedback. Such approaches can increase student motivation, improve the quality of learning outcomes, and make the learning process more adaptive to the individual needs of each student. Special attention is paid to the impact of AI on the development of professional skills of students of technical specialities. The use of interactive simulations and virtual environments controlled by artificial intelligence helps students to better master complex graphic and spatial concepts. Students have the opportunity to independently work on graphic tasks in a virtual environment that simulates real-world professional conditions, while receiving instant feedback from the system. This approach also promotes critical thinking and creativity in solving graphic problems. The article also discusses methodological approaches to the introduction of AI into curricula, in particular, the integration of new technologies into the educational process without disrupting traditional educational methods. It is noted that effective integration of AI requires an integrated approach, where technologies work in cooperation with the teacher, complementing traditional teaching methods and creating conditions for the development of the necessary competencies in students. The importance of an integrated approach to the use of artificial intelligence, where technologies complement traditional teaching methods, contributing to the development of graphic competence, is substantiated. Future research will be aimed at an in-depth study of ways to improve the teaching of graphic disciplines using artificial intelligence, as well as their integration into programmes for students with special educational needs.

Artificial intelligence in scientific medical writing: Legitimate and deceptive uses and ethical concerns

The debate surrounding the integration of artificial intelligence (AI) into scientific writing has already attracted significant interest in medical and life sciences. While AI can undoubtedly expedite the process of manuscript creation and correction, it raises several criticisms. The crossover between AI and health sciences is relatively recent, but the use of AI tools among physicians and other scientists who work in the life sciences is growing very fast. Within this whirlwind, it is becoming essential to realize where we are heading and what the limits are, including an ethical perspective.Modern conversational AIs exhibit a context awareness that enables them to understand and remember any conversation beyond any predefined script. Even more impressively, they can learn and adapt as they engage with a growing volume of human language input. They all share neural networks as background mathematical models and differ from old chatbots for their use of a specific network architecture called transformer model [1]. Some of them exceed 100 terabytes (TB) (e.g., Bloom, LaMDA) or even 500 TB (e.g., Megatron-Turing NLG) of text data, the 4.0 version of ChatGPT (GPT-4) was trained with nearly 45 TB, but stays updated by the internet connection and may integrate with different plugins that enhance its functionality, making it multimodal.

Use of the artificial intelligence in teaching the concept of magnetism in preschool education

This paper presents the design, implementation, and results of a teaching intervention in a Greek kindergarten where the researcher works, highlighting the significant positive impact of artificial intelligence (AI) tools on children’s learning of the concept of Magnetism. The teaching intervention was implemented as an extension of the specific thematic unit that had already been the subject of processing in kindergarten, using STEM tools and new technologies. A total of 3 activities with AI applications were implemented, with a total duration of 8 teaching hours. The methodology was based on the experiential and interdisciplinary approach and cooperative and playful learning. The role of the kindergarten teacher was helpful and supportive during the implementation of the action and its evaluation by the children. The children worked in small groups, where their group members mainly supported them in any difficulty. Children turned to the kindergarten teacher only for issues related to technical difficulties in handling the software. The educational intervention was evaluated through presentations of each group’s work in plenary. At the end of the educational intervention, the children were asked what they liked and what they found difficult. The results of the present action are very encouraging, as the use of artificial intelligence tools particularly activated children’s participation in the whole process and worked supportively and creatively in their mental potential.

Exploring The Role of Digital Literacy in University Students' Engagement with AI through the Technology Acceptance Model

Through the last decades, Artificial Intelligence (AI) has revolutionized the field of education and transformed traditional teaching approaches. This study aimed to examine how university students adopt AI tools in their learning processes and the role of digital literacy (DL) in this process through the lens of the Technology Acceptance Model (TAM). In this context, this study measured the impact of DL on university students' acceptance of AI technologies and their intention to use such technologies in the future. The data was collected from university students (N = 154) at a university in Western Türkiye during the fall semester of 2023. Data collection was conducted using two separate online forms; the first form included items adapted from the Digital Literacy Scale developed by Bayrakçı and Narmanlıoğlu (2021) to measure digital literacy levels, while the second form included items adapted from the UTAUT study by Venkatesh et al. (2003). The hypothesis testing results showed that students with higher levels of DL perceived the usefulness and ease of use of AI tools more positively, which positively affected their intention to adopt AI-based tools. The study also found that perceived usefulness and ease of use were important in shaping students' attitudes and behavioural intentions towards AI. When students perceive AI as a valuable tool for learning and find it easy to interact with, they are more willing to use it. This study suggests that DL plays a significant role in the acceptance of AI-based tools among university students, and accordingly, the TAM is a practical and accurate model to explore students’ potential engagement with AI in the learning process.

Can novice teachers detect AI-generated texts in EFL writing?

Abstract The introduction of generative artificial intelligence (AI) to the wider public could have a huge impact on EFL learning and teaching. Researchers have voiced concerns that learners might lean too much on technology. Previous studies have investigated the use of AI tools in L2 writing with various populations and found that it was difficult for teachers to detect use of AI and that teachers mainly relied on linguistic strategies to detect AI-generated texts. This paper reports on a qualitative study that investigated whether novice English teachers were able to detect AI-generated writing and which strategies they used to do this. The results show that some novice teachers are quite good at detecting AI-generated texts, while others proved to have more difficulties. The teachers used both linguistic and content-related strategies to detect AI-generated writing. The results point towards the value of including this topic in teaching methodology courses in (initial) teacher training programmes.

Comparing the Use of AI Tools in Mathematics and English Education: The Potential and Challenges of AI as Learning Assistant for FKIP UQ Students in Completing Academic Tasks

This study investigates the utilization of Artificial Intelligence (AI) among students enrolled in Mathematics and English Language Education programs at higher education in completing their academic tasks. Through a qualitative method, the study examines students' attitudes towards AI, their preferred AI tools, and the perceived benefits and challenges associated with AI integration in academic tasks. The findings reveal that the majority of students in both programs view AI as a valuable tool for enhancing learning outcomes and academic performance. Chat GPT emerges as the most favoured AI tool, particularly among Mathematics students. Moreover, students acknowledge the potential of AI to improve their motivation in learning and provide personalized feedback. However, students also express concerns regarding AI's limitations, including its inaccuracy and potential biases in data and information. Overall, this study underscores the importance of integrating AI responsibly and equitably to optimize its benefits and address potential drawbacks

Ready to Grip AI's Potential? Insights from an Exploratory Study on Perceptions of Human-AI Collaboration

<p>One of the emerging technologies arising with Industry 4.0 is generative artificial intelligence (AI). Despite its disruptive nature and controversies, the effective and ethical use of AI is increasingly preoccupying organizations of all sizes as well as their employees. Focusing on generative AI, this paper presents findings from a qualitative study that provides insights into how Generation Z, the newest workforce, perceives human-AI collaboration. Based on in-depth interviews and a micro-meso-macro approach, the study reveals a dual perspective. Participants recognized the advantages AI brings, such as increased efficiency, productivity, and information availability. However, they were concerned about various risks such as: technology addiction, job loss, data privacy and ethical issues. At the micro level, generative AI was seen as beneficial for providing information and inspiration, but over-reliance could limit people's skills and create dependency. At the meso, organizational level, it could increase efficiency and productivity, but potentially replace jobs. At the macro, societal level, generative AI could support innovation but risks dehumanizing communication and relationships. Data privacy and ethics concerns were expressed at all three levels, indicating that a combination of institutional safeguards and awareness of data privacy and ethics at all levels is required to achieve the full benefits of generative AI. This would help organisations to capitalise on technological advances and support the development of ethical use of AI tools.</p>

Artificial intelligence in ophthalmology: the present and the future

The medical industry is undergoing an active digital transformation, including the creation of electronic databases, cloud security systems, mobile health monitoring devices, and telemedicine tools. Artificial intelligence (AI), one of the most important technological achievements of the last decade, is gradually gaining momentum in various areas of practical medicine. The cutting edge of AI, neural networks, offers promising approaches to the improvement of clinical examination quality. The review presents data of studies focusing on the use of AI tools in the diagnosis of the most common ophthalmic diseases: diabetic retinopathy, macular degeneration, retinopathy of prematurity, glaucoma, cataracts, and ophthalmic oncology. We discuss both the advantages of neural networks in the diagnosis and monitoring of eye diseases, and outline the difficulties of their implementation, including ethical and legal conflicts.

Impact of Digital Literacy, Use of AI tools and Peer Collaboration on AI Assisted Learning- Perceptions of the University students

The technology-supported education systems seamlessly integrated throughout the globe in response to the challenges posed by the Covid-19 pandemic. The swift developments of the digital tools with Artificial Intelligence (AI) support are also readily diffused among the educational communities. This research paper investigates the synergistic impact of digital literacy, the incorporation of AI tools, and Peer Supported Collaborative Learning (PSCL) on the learning perceptions of university students. The research aims to discern the implications of these technological and social facets on students' attitudes towards AI assisted learning process. Structured questionnaire-based survey among the University students were done for this descriptive research. 409 responses collected were analysed with SPSS, Excel and Process Macro. It is found that the students’ Digital Literacy, Use of AI tools and PSCL on AI assisted learning were positively correlated. The partial mediatory path through the PSCL and AI tool usage has a significant positive influence on students learning process. The insights gathered from this study can inform educators, policymakers, and institutions on optimizing the amalgamation of digital literacy, AI tools and PSCL to enhance the contemporary learning environment. As universities navigate the digital age, this research provides a nuanced understanding of the dynamics shaping students' perceptions, offering valuable insights into the multifaceted aspects of AI influencing the educational landscape

Assessing Public Knowledge and Acceptance of Using Artificial Intelligence Doctors as a Partial Alternative to Human Doctors in Saudi Arabia: A Cross-Sectional Study.

Objective To assess the public acceptance of using artificial intelligence (AI) doctors to diagnose and treat patients as a partial alternative to human physicians in Saudi Arabia. Methodology An observational cross-sectional study was conducted from January to March 2024. A link to an online questionnaire was distributed through social media applications to citizens and residents aged 18 years and older across various regions in Saudi Arabia. The sample size was calculated using the Raosoft online survey size calculator, which estimated that the minimum sample size should be 385. Results Of the 386 participants surveyed, 85.8% reported being aware of AI, and 47.9% reported having some knowledge about different AI fields in daily life. However, almost one-third (32.9%) reported a lack of knowledge about the use of AI in healthcare. In terms of acceptance, 52.3% of respondents indicated they felt comfortable with the use of AI tools as partial alternatives to human doctors, and 30.8% believed AI is useful in the field of health. The most common concern (63.7%) about the use of AI tools accessible to patients was the difficulty of describing symptoms using these tools. Conclusion The findings of this study provide valuable insights into the public's knowledge and acceptance of AI in medicine within the Saudi Arabian context. Overall, this study underscores the importance of proactively addressing the public's concerns and knowledge gaps regarding AI in healthcare. By fostering greater understanding and acceptance, healthcare stakeholders can better harness the potential of AI to improve patient outcomes and enhance the efficiency of medical services in Saudi Arabia.

Requirements for Integrating the Use of Artificial Intelligence Tools into Local Development Practices

Requirements for Integrating the Use of Artificial Intelligence Tools into Local Development Practices

THE APPLICATION OF ARTIFICIAL INTELLIGENCE TOOLS IN THE LEGAL PROFESSION

Artificial intelligence (AI) represents the main characteristic of the Fifth Industrial Revolution and finds its application in numerous aspects of social and work life. One of the areas on which the development of AI, and especially chatbots, can have a significant impact is professions that are based on knowledge, such as the legal profession. In this paper, we analyze the possi-bilities of applying AI tools, primarily ChatGPT, in different legal professions, and give a general view of this issue. Moreover, a survey was conducted among 142 legal professionals regarding their opinion on the use of AI tools in their work. The results showed that the majority of the respondents were familiar with the terms “AI” and “ChatGPT”, but rarely used them while per-forming legal tasks. Furthermore, a positive attitude towards the use of AI was observed, but also the caution regarding its neg-ative aspects. Finally, the respondents showed an affirmative attitude towards the continuance of the legal profession, in which the use of “smart tools” could be implemented in a legally and ethically justified way.

Radiologists’ perceptions on AI integration: An in-depth survey study

PurposeTo assess the perceptions and attitudes of radiologists toward the adoption of artificial intelligence (AI) in clinical practice. MethodsA survey was conducted among members of the SIRM Lombardy. Radiologists’ attitudes were assessed comprehensively, covering satisfaction with AI-based tools, propensity for innovation, and optimism for the future. The questionnaire consisted of two sections: the first gathered demographic and professional information using categorical responses, while the second evaluated radiologists’ attitudes toward AI through Likert-type responses ranging from 1 to 5 (with 1 representing extremely negative attitudes, 3 indicating a neutral stance, and 5 reflecting extremely positive attitudes). Questionnaire refinement involved an iterative process with expert panels and a pilot phase to enhance consistency and eliminate redundancy. Exploratory data analysis employed descriptive statistics and visual assessment of Likert plots, supported by non-parametric tests for subgroup comparisons for a thorough analysis of specific emerging patterns. ResultsThe survey yielded 232 valid responses. The findings reveal a generally optimistic outlook on AI adoption, especially among young radiologist (<30) and seasoned professionals (>60, p<0.01). However, while 36.2 % (84 out 232) of subjects reported daily use of AI-based tools, only a third considered their contribution decisive (30 %, 25 out of 84). AI literacy varied, with a notable proportion feeling inadequately informed (36 %, 84 out of 232), particularly among younger radiologists (46 %, p < 0.01). Positive attitudes towards the potential of AI to improve detection, characterization of anomalies and reduce workload (positive answers > 80 %) and were consistent across subgroups. Radiologists’ opinions were more skeptical about the role of AI in enhancing decision-making processes, including the choice of further investigation, and in personalized medicine in general. Overall, respondents recognized AI’s significant impact on the radiology profession, viewing it as an opportunity (61 %, 141 out of 232) rather than a threat (18 %, 42 out of 232), with a majority expressing belief in AI’s relevance to future radiologists’ career choices (60 %, 139 out of 232). However, there were some concerns, particularly among breast radiologists (20 of 232 responders), regarding the potential impact of AI on the profession. Eighty-four percent of the respondents consider the final assessment by the radiologist still to be essential. ConclusionOur results indicate an overall positive attitude towards the adoption of AI in radiology, though this is moderated by concerns regarding training and practical efficacy. Addressing AI literacy gaps, especially among younger radiologists, is essential. Furthermore, proactively adapting to technological advancements is crucial to fully leverage AI’s potential benefits. Despite the generally positive outlook among radiologists, there remains significant work to be done to enhance the integration and widespread use of AI tools in clinical practice.

Artificial intelligent tools: evidence-mapping on the perceived positive effects on patient-care and confidentiality

BackgroundGlobally, healthcare systems have always contended with well-known and seemingly intractable challenges like safety, quality, efficient and effective clinical and administrative patient-care services. To firmly confront these and other healthcare challenges, the World Health Organisation proposed a full adoption of artificial intelligence (AI) applications into patient care to stimulate efficiency and guarantee quality in patient management.PurposeThis review aimed to establish the extent and type of evidence of the positive effects of the use of AI tools in patient care. Thus, the review mapped evidence by using articles published between January 1, 2010, and October 31, 2023.MethodsConsistent with the protocol by Tricco et al., a comprehensive literature search was executed from Nature, PubMed, Scopus, ScienceDirect, Dimensions, Web of Science, Ebsco Host, ProQuest, JStore, Semantic Scholar, Taylor & Francis, Emeralds, World Health Organisation, and Google Scholar. Upholding the inclusion and exclusion standards, 95 peer-reviewed articles were included in this review.FindingsWe report that the use of AI tools can significantly improve the accuracy of clinical diagnosis to guarantee better patient health outcomes. AI tools also have the ability to mitigate, if not eliminate, most of the factors that currently predict poor patient outcomes. Furthermore, AI tools are far more efficient in generating robust and accurate data in real time and can help ease and accelerate workflow at healthcare facilities.ConclusionIf properly integrated into the healthcare system, AI will help reduce patients’ waiting time and accelerate the attainment of Sustainable Development Goals 3.4, 3.8, and 3.b. We propose that AI developers collaborate with public health practitioners and healthcare managers to develop AI applications that appreciate socio-cultural dimensions in patient care.

Special considerations for the use of AI tools by PEERs as a learning and communication aid.

There is no doubt that navigating academia is a formidable challenge, particularly for those from underrepresented backgrounds who face additional barriers at every turn. In such an environment, efforts to create learning and training environments that are diverse, equitable, and inclusive can feel like an uphill battle. We believe that harnessing the power of artificial intelligence (AI) tools can help in leveling the playing field. While AI cannot supplant the need for supportive mentorship, it can serve as a vital supplement, offering guidance and assistance to those who may lack access to adequate avenues of support. Embracing AI in this context should not be stigmatized, as it may represent a vital lifeline for underrepresented individuals who often face systemic biases while forging their own paths in pursuit of success and belonging in academia. AI tools should not be gatekept from these individuals, particularly by those in positions of power and privilege within the scientific community. Instead, we argue, institutions should make a strong commitment to educating their community members on how to ethically harness these tools.

Qualitative versus quantitative assessment of electroencephalography in cognitive decline: Comparison in a clinical population

This study aimed to compare the diagnostic performance of visual assessment of electroencephalography (EEG) using the Grand Total EEG (GTE) score and quantitative EEG (QEEG) using spectral analysis in the context of cognitive impairment.This was a retrospective study of patients with mild cognitive impairment, with (MCI+V) or without (MCI) vascular dysfunction, and patients with dementia including Alzheimer's disease, Lewy Body Dementia and vascular dementia.The results showed that the GTE is a simple scoring system with some potential applications, but limited ability to distinguish between dementia subtypes, while spectral analysis appeared to be a powerful tool, but its clinical development requires the use of artificial intelligence tools.

Friend or foe? Artificial intelligence (AI) and negotiation

Generative artificial intelligence (AI) is not new, yet it has recently experienced an explosion of interest and debate. Among the topics of concern is how it will affect human relationships and interactions and how organisations will deploy AI in conducting their external relationships. This paper addresses an ongoing experiment which explores the impact of AI in the field of negotiation. It provides initial observations on the use of machine learning in general and ChatGPT in particular in negotiated outcomes. We provide preliminary recommendations regarding the use of AI tools and systems in negotiation and pose questions related to possible future research.