The impact of artificial intelligence on logic skills, critical thinking, and student creativity

Artificial Intelligence (AI) is revolutionizing the field of health sciences, reshaping how we teach, learn, and practice medicine. As AI technologies become increasingly integrated into healthcare systems, their impact on health sciences education cannot be overstated. From personalized learning experiences to advanced diagnostic training, AI is poised to enhance the quality and accessibility of education for future healthcare professionals. However, this transformation also raises critical questions about ethics, equity, and the future role of educators in an AI-driven world. The transformative role of Artificial Intelligence (AI) in health sciences education is increasingly recognized as a pivotal factor in shaping the future of medical training and practice. As AI technologies continue to evolve, their integration into educational curricula presents both opportunities and challenges that must be carefully navigated to enhance the learning experience for future healthcare professionals. One of the most significant contributions of AI to health sciences education is its ability to personalize learning. Traditional teaching methods often follow a one-size-fits-all approach, which can leave some students struggling to keep up while others are not sufficiently challenged. AI-powered platforms, such as adaptive learning systems, analyze individual student performance and tailor content to meet their unique needs. For example, tools like Osmosis and AMBOSS use AI to provide customized study plans, ensuring that students focus on areas where they need the most improvement (Topol, 2019). This personalized approach not only improves learning outcomes but also fosters a more inclusive educational environment. AI is also transforming clinical training by simulating real-world scenarios. Virtual patient simulations, powered by AI, allow students to practice diagnosing and treating conditions in a risk-free environment. These simulations can replicate rare or complex cases that students might not encounter during their clinical rotations. For instance, platforms like Touch Surgery and SimX use AI to create immersive surgical and emergency care simulations, providing students with hands-on experience before they enter the operating room (McGaghie et al., 2011). Such tools bridge the gap between theory and practice, preparing students for the complexities of modern healthcare. Moreover, AI is enhancing the role of educators by automating administrative tasks and providing data-driven insights into student performance. Grading, attendance tracking, and even curriculum design can be streamlined using AI, allowing educators to focus on mentoring and engaging with students. AI-driven analytics can also identify at-risk students early, enabling timely interventions to support their academic success (Wartman & Combs, 2018). By augmenting the capabilities of educators, AI empowers them to deliver more impactful and student-centered teaching. AI's potential to revolutionize health sciences education lies in its ability to personalize learning experiences and improve educational outcomes. For instance, AI-driven tools can facilitate realistic simulations and automated assessments, allowing students to engage in practical scenarios that mimic real-world clinical situations (Santos & Lopes, 2024). This capability not only enhances the learning process but also prepares students for the complexities of patient care in a technology-driven environment (Grunhut et al., 2022). Furthermore, the incorporation of AI into curricula can foster critical thinking and decision-making skills, essential for navigating the ethical dilemmas that arise in medical practice (Grunhut et al., 2022). Despite the promising applications of AI in education, the integration of these technologies into medical curricula has been slow. A scoping review highlighted that many medical schools have yet to adopt AI training, primarily due to a lack of systematic evidence supporting its implementation (Lee et al., 2021). Additionally, concerns regarding data protection and the ethical implications of AI use in healthcare education have been raised, indicating a need for comprehensive AI education that addresses these issues (Veras et al., 2023; Frehywot & Vovides, 2023). Students have expressed a desire for more robust training in AI, emphasizing the importance of understanding its role in healthcare delivery and decision-making processes (Ahmad et al., 2023; Derakhshanian et al., 2024). Moreover, the rapid advancement of AI technologies necessitates continuous curriculum updates to keep pace with emerging trends. As noted in recent literature, the integration of AI into biomedical science curricula should include subjects related to informatics, data sciences, and digital health (Sharma et al., 2024). This approach not only equips students with the necessary skills to utilize AI effectively but also prepares them for the evolving landscape of healthcare, where AI will play an integral role in diagnostics, treatment personalization, and patient management (Santos & Lopes, 2024; Secinaro et al., 2021). However, the implementation of AI in health sciences education is not without challenges. Ethical considerations surrounding AI's impact on healthcare equity and the potential for bias in AI algorithms must be addressed (Frehywot & Vovides, 2023; Han et al., 2019). Ensuring that AI technologies are used responsibly and equitably in education and practice is crucial to avoid exacerbating existing disparities in healthcare access and outcomes (Rigby, 2019). Furthermore, the lack of faculty expertise in AI poses a significant barrier to its integration into medical education, highlighting the need for targeted training and resources for educators (Derakhshanian et al., 2024). However, the integration of AI into health sciences education is not without challenges. Ethical concerns, such as data privacy and algorithmic bias, must be addressed to ensure that AI tools are used responsibly. Additionally, there is a risk of over-reliance on AI, potentially undermining the development of critical thinking and clinical judgment skills. Educators must strike a balance between leveraging AI’s capabilities and preserving the human elements of teaching and learning. Equity is another pressing issue. While AI has the potential to democratize education, access to these technologies remains uneven. Institutions in low-resource settings may struggle to adopt AI-driven tools, exacerbating existing disparities in global health education. Policymakers and educators must work together to ensure that the benefits of AI are accessible to all, regardless of geographic or socioeconomic barriers. In conclusion, AI is a powerful tool that holds immense promise for transforming health sciences education. By personalizing learning, enhancing clinical training, and supporting educators, AI can help prepare the next generation of healthcare professionals to meet the demands of an increasingly complex healthcare landscape. However, its integration must be guided by ethical principles and a commitment to equity, However, the successful integration of AI into educational curricula requires a concerted effort to address ethical concerns, update training programs, and equip both students and faculty with the necessary knowledge and skills. As the healthcare landscape continues to evolve, embracing AI in education will be essential for fostering a new generation of healthcare providers who are adept at leveraging technology to improve patient care. As we embrace this technological revolution, we must remember that AI is not a replacement for human expertise but a complement to it. The future of health sciences education lies in the synergy between human ingenuity and artificial intelligence.

PurposeThis paper aims to explore the intricate relationship between artificial intelligence (AI) and health information literacy (HIL), examining the rise of AI in health care, the intersection of AI and HIL and the imperative for promoting AI literacy and integrating it with HIL. By fostering collaboration, education and innovation, stakeholders can navigate the evolving health-care ecosystem with confidence and agency, ultimately improving health-care delivery and outcomes for all.Design/methodology/approachThis paper adopts a conceptual approach to explore the intricate relationship between AI and HIL, aiming to provide guidance for health-care professionals navigating the evolving landscape of AI-driven health-care delivery. The methodology used in this paper involves a synthesis of existing literature, theoretical analysis and conceptual modeling to develop insights and recommendations regarding the integration of AI literacy with HIL.FindingsImpact of AI on health-care delivery: The integration of AI technologies in health-care is reshaping the industry, offering unparalleled opportunities for improving patient care, optimizing clinical workflows and advancing medical research. Significance of HIL: HIL, encompassing the ability to access, understand and critically evaluate health information, is crucial in the context of AI-driven health-care delivery. It empowers health-care professionals, patients and the broader community to make informed decisions about their health and well-being. Intersection of AI and HIL: The convergence of AI and HIL represents a critical juncture, where technological innovation intersects with human cognition. AI technologies have the potential to revolutionize how health information is generated, disseminated and interpreted, necessitating a deeper understanding of their implications for HIL. Challenges and opportunities: While AI holds tremendous promise for enhancing health-care outcomes, it also introduces new challenges and complexities for individuals navigating the vast landscape of health information. Issues such as algorithmic bias, transparency and accountability pose ethical dilemmas that impact individuals’ ability to critically evaluate and interpret AI-generated health information. Recommendations for health-care professionals: Health-care professionals are encouraged to adopt strategies such as staying informed about developments in AI, continuous education and training in AI literacy, fostering interdisciplinary collaboration and advocating for policies that promote ethical AI practices.Practical implicationsTo enhance AI literacy and integrate it with HIL, health-care professionals are encouraged to adopt several key strategies. First, staying abreast of developments in AI technologies and their applications in health care is essential. This entails actively engaging with conferences, workshops and publications focused on AI in health care and participating in professional networks dedicated to AI and health-care innovation. Second, continuous education and training are paramount for developing critical thinking skills and ethical awareness in evaluating AI-driven health information (Alowais et al., 2023). Health-care organizations should provide opportunities for ongoing professional development in AI literacy, including workshops, online courses and simulation exercises focused on AI applications in clinical practice and research.Originality/valueThis paper lies in its exploration of the intersection between AI and HIL, offering insights into the evolving health-care landscape. It innovatively synthesizes existing literature, proposes strategies for integrating AI literacy with HIL and provides guidance for health-care professionals to navigate the complexities of AI-driven health-care delivery. By addressing the transformative potential of AI while emphasizing the importance of promoting critical thinking skills and ethical awareness, this paper contributes to advancing understanding in the field and promoting informed decision-making in an increasingly digital health-care environment.

Purpose: The purpose of the study is to examine the challenges faced by businesses in integrating and effectively utilizing artificial intelligence (AI) technology. It aims to provide a comprehensive understanding of how AI technologies generate business value and the anticipated benefits they offer. The study also seeks to identify the facilitators and inhibitors of AI adoption and usage, explore different types of AI use in the organizational environment, and analyze their first- and second-order impacts.
 Methodology: The study employed the comprehensive literature review research design. The researchers conducted a systematic search using predefined criteria in databases such as Scopus and Web of Science. The search yielded 21 relevant papers that were analyzed and synthesized for this study. The data collection method relied on the examination of existing literature. Data analysis involved identifying key themes, trends, and insights from the selected papers. The researchers conducted a qualitative analysis to extract relevant findings and synthesized the information to derive meaningful conclusions.
 Findings: The study revealed several insights regarding the integration and use of AI in businesses. This indicated that organizations struggle with understanding how AI technologies can generate value and how to effectively incorporate them into their operations. Lack of comprehensive knowledge about AI and its value generation processes was identified as a major barrier. Additionally, the study highlighted the facilitators and inhibitors of AI adoption and usage. It identified various types of AI applications in the organizational environment and explored their impacts on business operations. The findings shed light on the challenges businesses face in leveraging AI technology and suggested areas for further research.
 Recommendations: To practitioners: The study emphasizes the importance of acquiring comprehensive knowledge about AI technologies and their potential value generation processes. To policy makers: The study highlights the need for supportive policies and regulations to foster AI adoption. It suggests creating an enabling environment that promotes AI research and development. Theory and Validation: The study may have been informed by existing theories related to AI adoption, organizational change, or innovation. Practice: To practitioners, the study underscores the importance of understanding the value and potential of AI technologies. Policy: To policy makers, the study emphasizes the need for policy frameworks that promote AI adoption and address associated challenges.

Proficiency in critical and creative thinking are fundamental skills that students must have to face the challenges of the 21st century. This study compared the effectiveness of STEM (science, technology, engineering and mathematics) education and CRT based on Sasambo education in improving students' critical and creative thinking skills in elementary schools. This study used a quantitative approach with a quasi-experimental design and a pre-test-post-test control group. A total of 31 students participated in this study and were divided into two experimental groups. The first experiment used the STEM approach, while the second experiment used CRT based on Sasambo culture. Data was collected through an essay test that evaluated students' critical thinking (10 questions) and creative thinking (4 questions). In addition, descriptive statistics, homogeneity, normality, paired sample t-test, and N-Gain scores were used to evaluate students' improvement. This study shows that different learning approaches can have diverse impacts on students' cognitive skill development. STEM education proved to be more effective in improving critical thinking, while culture-based CRT was superior in encouraging students' creativity. The findings showed that STEM-based education significantly improved students' critical thinking skills more than CRT-based education. Conversely, CRT was more effective in improving students' creative thinking skills. This highlights the importance of integrating educational innovations with local customs to support the growth of students' critical thinking and creativity.

The integration of Artificial Intelligence (AI) in teacher education has raised important questions about its impact on higher-order cognitive skills, particularly critical thinking and creativity. This study investigates the mediating role of critical thinking in the relationship between AI usage and creativity among pre-service teachers. Grounded in Cognitive Load Theory (CLT) and Dual-Process Theory, the research conceptualizes critical thinking as a second-order reflective construct comprising adaptive exploration (AE) and systematic validation (SV). Using a cross-sectional survey design, data were collected from 107 pre-service teachers at a teacher training institution in Southwest China. Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed to analyze the relationships among AI usage, critical thinking, and creativity. Results indicate that AI usage significantly enhances critical thinking (β = 0.560, p < 0.001), which, in turn, has a strong positive effect on creativity (β = 0.707, p < 0.001). Moreover, critical thinking serves as a partial mediator, amplifying the effect of AI usage on creativity (β = 0.397, p < 0.001, VAF = 65.89%). These findings underscore the necessity of fostering AI-supported critical thinking skills in teacher education. As generative AI technologies become increasingly prevalent in digital learning environments, integrating adaptive exploration and systematic validation into pedagogical strategies is essential for cultivating both critical thinking and creativity. The study contributes to the discourse on digital learning innovations and teacher education by providing empirical evidence on AI’s role in enhancing cognitive development.

This study aims to determine the effectiveness of using the CPS (Creative Problem Solving) learning model to improve students' critical and creative thinking skills. This research is an experimental study using a quasi-experimental research design with a non-equivalent control group design. The sampling technique used purposive sampling and obtained class VIII A and VIII F. Improving students' critical thinking skills based on T-Test test data pretest and posttest were 4.01 in the control class and 10.29 in the experimental class, both of which were higher than the Ttable, which was 1.99. Improving students' creative thinking skills based on the STUDENT WORKSHEET T-Test Test of 5.035 in the control class and 10,041 in the experimental class, and the T-Test mind mapping of 6,428 in the control class and 6,240 in the experimental class. From the test results, it was found that H0 was rejected so that there was an increase in students' critical and creative thinking skills. Thus, the application of the CPS (Creative Problem Solving) model on the Science material is effectively used to improve students' critical and creative thinking skills.

Project-based learning is a learning approach that emphasizes students as learning actors who facilitate students to construct their knowledge. However, the application of project-based learning to learning at the tertiary level is a learning syntax that has not been designed by adjusting the characteristics of learning for the tertiary level. This study aims to analyze the effectiveness of case study-based learning conducted using a hybrid project-based learning model in improving students' critical thinking and creative thinking skills. This study used a non-equivalent control group research design with 70 samples divided into the experimental and control groups. The instruments used are standard critical thinking skills tests, namely Cornell Critical Thinking Test (CCTT) level X, creative thinking skills test instruments, and observation sheets. The results showed that hybrid project-based learning effectively improved students' critical and creative thinking skills. The increase in students' critical thinking skills is higher than students' creative thinking skills.

In recent years, the rapid integration of artificial intelligence (AI) technologies into education has sparked intense academic and public debate regarding their impact on students’ cognitive development. One of the central concerns raised by researchers and practitioners is the potential erosion of critical and independent thinking skills in an era of widespread reliance on neural network-based technologies. On the one hand, AI offers new opportunities for personalized learning, adaptive content delivery, and increased accessibility and efficiency in the educational process. On the other hand, growing concerns suggest that overreliance on AI-driven tools in intellectual tasks may reduce students’ motivation to engage in self-directed analysis, diminish cognitive effort, and lead to weakened critical thinking skills. This paper presents a comprehensive analysis of current research on this topic, including empirical data, theoretical frameworks, and practical case studies of AI implementation in academic settings. Particular attention is given to the evaluation of how AI-supported environments influence students’ cognitive development, as well as to the pedagogical strategies that can harmonize technological assistance with the cultivation of autonomous and reflective thinking. This article concludes with recommendations for integrating AI tools into educational practice not as replacements for human cognition, but as instruments that enhance critical engagement, analytical reasoning, and academic autonomy.

The Artificial Intelligence (AI) technology is developing quickly and gaining applications in higher education (HE). Existing research on AI in HE is mainly focused on instructional strategies and learning outcomes, with little attention paid to motivation. However, motivation is essential in guiding teaching strategies and promoting learning outcomes. Further research is needed to understand AI's impact on motivation. This article aims to contribute to the existing literature by providing new insights and filling gaps in knowledge. Specifically, the six C's of motivation theory are adopted to guide the investigation. The global survey reports are utilized to analyze students' AI usage in HE and AI's impact on student motivation. The findings reveal that AI has been used in various cases in HE, and AI has dual impacts on student motivation in terms of control, challenge, choice, collaboration, constructing meaning, and consequences (six C's). In the future application of AI in HE, it is recommended that colleges and universities strengthen supervision and training of AI, and students should focus more on what they gain in the learning process rather than overemphasizing learning outcomes when using AI.

The article discusses the training of future computer science teachers to use artificial intelligence (AI) technologies in education. The authors highlight the relevance of this issue in light of the rapid spread of AI technologies in various spheres of life and the need to develop students’ digital competencies related to the use of artificial intelligence. The study aims to identify the essential competencies that future computer science teachers need to effectively use AI in education. It also analyzes the existing problems and challenges in this area, studies the prospects for the use of AI in education, develops recommendations for improving relevant training programs, and overcoming barriers to the implementation of AI technologies. The study identified three main groups of competencies for future computer science teachers in the field of AI: technical, pedagogical, ethical and legal. Technical competencies include knowledge of AI technology principles, algorithms, and software. Pedagogical competencies relate to the ability to adapt teaching materials and methods to the capabilities of AI and to develop appropriate tasks and projects. Ethical and legal competencies involve comprehending the risks and challenges associated with AI usage, as well as being aware of the ethical principles and legal norms in this field. The article analyzes technical, pedagogical, ethical, and legal problems related to introducing AI technologies into computer science teacher training and education. It also explores the potential benefits of AI in education, such as personalized and adaptive learning, improved teaching and assessment effectiveness, and the development of critical thinking and creativity in students. The authors suggest methods to enhance computer science teacher training programs, such as incorporating specialized AI courses, providing practical training, and involving industry experts. They also stress the significance of considering the most effective international practices in this field. To summarize, the article highlights the pressing need to modernize the computer science teacher training system in Ukraine. This is necessary to develop the competencies required for the effective use of AI technologies in the educational process. Such modernization will contribute to the development of students’ digital literacy and ensure the competitiveness of the Ukrainian educational system in the context of digital transformation.

Critical thinking and creative thinking skills are needed to improve the quality and competitive human resources. Therefore, the application of appropriate learning models is expected to stimulate students' critical thinking and creative thinking skills. This research aims to improve critical thinking and creative thinking skill scores using the ASICC learning model. This type of research is classroom action research which is carried out in 2 cycles, with 3 meetings in each cycle. Data on students' critical thinking and creative thinking skills were collected using essay tests on science learning materials. Data analysis was carried out by comparing the N-gain scores in cycle 1 and cycle 2 for students' critical thinking and creative thinking skills. The results of the research revealed that there was an increase that occurred in cycle 2, namely 5.6% in the aspects of moderate critical thinking skills and high creative thinking, as well as in the aspects of critical thinking skills and high creative thinking by 5.6%. Meanwhile, in the previous cycle, these two aspects did not have a high category. Another result found from this research is that students who have low critical thinking skills do not necessarily have low creative thinking skills. This is because students who have low critical thinking skills may have moderate creative thinking skills or vice versa. Thus, the application of the ASICC learning model is effective in improving the scores of critical thinking skills and creative thinking skills of students at Junior High School 5 Kertosono.

This study aims to develop and see the effectiveness of flipbook-based digital pocketbooks on environmental pollution material on the critical and creative thinking skills of grade VII students at SMPN 1 Sojol Utara. The method used in this research is research and development (Research and Development) with 4D instructional design. This research was conducted on grade VII students at SMPN 1 Sojol Utara totaling 40 students. The results of this study showed that: (1) The flipbook-based digital pocket book developed obtained a percentage of 86.96% of the very valid category and for media practicality obtained a percentage of 80% of the practical category for use in science learning, critical thinking skills obtained a value of 70.83% in the critical thinking category (2) The ability to think creatively obtained a score of 84.37% with the category of creative thinking (3) The effectiveness of the book The flipbook-based digital pocket developed is very effective in improving students' critical thinking skills with an effect size value of 1.95 very large categories, (4) The effectiveness of the flipbook-based digital pocketbook developed is very effective in improving students' creative thinking skills with an effect size valueThe 1.95 categories are huge. Based on the results of the development that has been carried out, flipbook-based digital pocketbooks can be a learning medium that can improve students' critical and creative thinking skills in science learning.

Masters or Slaves? AI and the Future of Humanity

Background: Artificial intelligence (AI) has become a transformative force in higher education, reshaping traditional learning paradigms and fostering essential 21st-century skills. AI-powered tools enhance collaboration, communication, critical thinking, and creativity, equipping students with competencies necessary for academic and professional success. However, concerns regarding over-reliance on AI and its potential limitations in fostering independent ideation persist. This study examines the impact of AI on university students' skill development, identifying both opportunities and challenges in AI-integrated learning environments. Objective: The study aims to investigate the extent to which AI contributes to the enhancement of collaboration, communication, critical thinking, and creativity among university students. It further explores the implications of AI usage on cognitive skill development and the necessity of complementary instructional strategies. Methods: A quantitative research approach with a cross-sectional survey design was employed. A self-developed structured questionnaire, validated through a pilot study (Cronbach’s alpha = 0.87), was used for data collection. The sample comprised 300 undergraduate and graduate students from public sector universities in Punjab, selected via stratified random sampling. Data analysis was conducted using t-tests, ANOVA, and multiple regression to determine significant relationships between AI usage and skill development. Results: Significant gender differences were observed in collaboration (p = .034) and critical thinking (p = .006), with female students scoring higher than males. One-way ANOVA indicated that students with high AI usage had significantly better collaboration (p = .002), communication (p = .007), and critical thinking skills (p < .001) compared to those with low AI exposure. Multiple regression analysis confirmed AI usage as a strong predictor of collaboration (β = .29, p < .001), communication (β = .24, p = .005), and critical thinking (β = .36, p < .001), while its impact on creativity was not statistically significant (p = .059). Conclusion: The findings highlight AI’s effectiveness in enhancing collaboration, communication, and critical thinking skills, yet its role in fostering creativity remains inconclusive. While AI enriches structured learning experiences, independent ideation requires complementary pedagogical strategies. Institutions should integrate AI responsibly to maximize its benefits while mitigating its limitations.

Artificial Intelligence (AI) is a technology that can mimic human thinking and learning processes through algorithms and computer systems. AI brings significant changes to the education sector by providing various conveniences. On the other hand, the use of AI technology requires adjustments in the learning process at higher education institutions. This research aims to analyze the impact of Artificial Intelligence (AI) usage on the critical thinking skills of students at Al Washliyah Darussalam University (UNADA) Banda Aceh. This study employs a Mixed Methods approach, utilizing quantitative methods with a descriptive approach to analyze the frequency of AI usage, while qualitative methods are used to analyze changes in thinking patterns and students' analytical abilities in the learning process. Data collection was conducted through surveys. The sampling technique used was purposive sampling, involving 287 students who use AI in their learning. The research findings indicate that the distribution of questionnaire data shows that the usage of Artificial Intelligence (AI) includes 31.3% (ChatGPT), 6.3% (Perplexity), 12.5% (Gemini), and 5% using other AI technologies. The impact of AI usage reveals that AI can enhance students' critical thinking skills, particularly in data analysis, problem-solving, and decision-making. However, negative impacts faced by students include dependency on technology and a lack of active engagement in classroom discussions. The results and findings of this study highlight the importance for university lecturers and policymakers to design effective learning strategies that utilize AI to develop critical thinking skills among students.