Educational Intelligence Research Articles

Artificial intelligence applications in cataract and refractive surgeries.

This review highlights the recent advancements in the applications of artificial intelligence within the field of cataract and refractive surgeries. Given the rapid evolution of artificial intelligence technologies, it is essential to provide an updated overview of the significant strides and emerging trends in this field. Key themes include artificial intelligence-assisted diagnostics and intraoperative support, image analysis for anterior segment surgeries, development of artificial intelligence-based diagnostic scores and calculators for early disease detection and treatment planning, and integration of generative artificial intelligence for patient education and postoperative monitoring. The impact of artificial intelligence on cataract and refractive surgeries is becoming increasingly evident through improved diagnostic accuracy, enhanced patient education, and streamlined clinical workflows. These advancements hold significant implications for clinical practice, promising more personalized patient care and facilitating early disease detection and intervention. Equally, the review also highlights the fact that only some of this work reaches the clinical stage, successful integration of which may benefit from our focus.

The Next Generation of Learning: AI Mentorship for a Transformative Educational Experience

Developers of this augmented reality-based artificial intelligence education program aim at augmenting student engagement in learning through the incorporation of virtual mentors and the overall experience being made engaging, efficient, and personalized. Therefore, the application provides contextual support, tailored learning pathways, and real-time feedback that significantly enhance users' understanding of complex AI concepts with customized AI avatars and augmented reality technologies. These artificial intelligence mentors and assistants act as learning facilitators for both engineering and non-engineering students while enhancing the educational experience. The software features natural language processing to enable smooth communication; it introduces gamification into the courseware, adds quizzes, and provides rewards for a better learning experience, among other features

Unmasking teachers’ proficiency in harnessing Artificial Intelligence (AI) for transformative education

This paper examines the awareness of artificial intelligence (AI) among school teachers in Nepal. We interviewed twenty teachers from ten urban schools in Nepal over four weeks using a semi-structured interview tool. The analysis of interview data reveals the teachers’ mixed perception of AI, including their understanding of innovative technologies in education, the potential challenges for new-generation teachers, and the opportunities for pedagogical transformations. The findings suggest that although the teachers have limited awareness of how AI can be used in teaching and learning, they possess some level of understanding that has opened up new opportunities for exploring innovative ways of teaching and learning. Notably, participants discussed tools, such as Education Management Information System (EMIS) for record keeping and automated grading and AI-driven chatbots for student tutoring. However, teachers also expressed concerns about the possibility of AI replacing human teachers. These insights provide valuable implications for policymakers and educators regarding the integration of AI into classroom instructions to promote innovative and equitable learning opportunities.

AI versus human effectiveness in essay evaluation

The evaluation of student essay corrections has become a focal point in understanding the evolving role of Artificial Intelligence (AI) in education. This study aims to assess the accuracy, efficiency, and cost-effectiveness of ChatGPT's essay correction compared to human correction, with a primary focus on identifying and rectifying grammatical errors, spelling, sentence structure, punctuation, coherence, relevance, essay structure, and clarity. The research involves collecting essays from 100 randomly selected university students, covering diverse themes, with anonymity maintained and no prior corrections by humans or AI. An analysis sheet, outlining linguistic and informational elements for evaluation, serves as a benchmark for assessing the quality of corrections made by ChatGPT and humans. The study reveals that ChatGPT excels in fundamental language mechanics, demonstrating superior performance in areas like grammar, spelling, sentence structure, relevance, and supporting evidence. However, thematic consistency remains an area where human evaluators outperform the AI. The findings emphasize the potential for a balanced approach, leveraging both human and AI strengths, for a comprehensive and effective essay correction process.

Climate change and gastroenteritis projections in Albanian children

Abstract Background Human health can be affected by climate in direct and indirect ways. Increasing temperatures may affect ecosystems, water safety, and exposure to waterborne diseases. This is the first work in Albania aiming to demonstrate the link between gastroenteritis rate and climate in the country. This research was supported by UNICEF Albania through the WASH Global Thematic Fund, but it doesn’t necessarily represent UNICEF’s position. Methods Epidemiological surveillance reports of the period 2006-2022 were used for the yearly incidence of gastroenteritis in children 0-14 years old. Years 2020 and 2021 were not included because of pandemic confounding potential. Historic data for calculating the average summer temperatures were retrieved from timeanddate.com repository. Pearson coefficient is calculated to quantify the associations and linear regression is applied to project the increased rate in the future. Results There was a statistical association between gastroenteritis rate and summer temperatures during the study period (Pearson coefficient=0.78, p = 0.001). There was a tendency that in years with hotter summers higher incidence of gastroenteritis was reported by the health system. For each degree (Celsius) increase in the average summer day temperatures, the risk of gastroenteritis in children is expected to increase by 644/100 000 (CI 95%: 317 - 972). An excess rate of 966/100 000 is expected in the case of Intergovernmental Panel on Climate Change medium scenario projection of 1.5o C average temperature increase. That implies more than 4830 additional new cases every year in children 0-14 years old, attributed to climate change in the future in Albania. Conclusions The analysis demonstrated excess gastroenteritis risk may be related to higher summer temperatures observed in Albania. The expected gastroenteritis risk increase in a warmer future should be addressed by improvements in sanitation, education of parents and epidemiological intelligence. Key messages • A warmer climate is expected to affect the health by increasing the risk for diarrheic diseases. • Children will be the most at-risk population category.

Analysis of Studies Based on Türkiye Examining the Relationship between Artificial Intelligence and Education: A Meta Synthesis Study

Artificial intelligence is defined as human-made systems that mimic the thinking, perception, and learning abilities of the human brain, using the information they gather and having the ability to improve themselves. With the changes and developments in the field of technology, the use of artificial intelligence has also expanded. The increasing popularity of artificial intelligence in the field of education has led to a rise in research on this topic. This paper aims to synthesize the existing literature on the applications of artificial intelligence in education within a specific time frame and to develop a holistic perspective. In the paper, 20 studies written in the last five years on artificial intelligence and education were examined using the metasynthesis method. The research question is defined as: "What trends exist in academic research on artificial intelligence and education conducted in Turkey over the past five years?" The data source for the research was determined using the criterion sampling method. For this purpose, a detailed search was conducted in databases such as Google Scholar, Academia, TÜBİTAK ULAKBİM, and Dergipark using the keyword "artificial intelligence and education." As a result of the analyses, it was found that while the study emphasizes the contributions of artificial intelligence to the field of education, there are also some concerns on the subject. The contributions of artificial intelligence, particularly in terms of providing personalized learning experiences, saving time, and improving student performance, were highlighted, but concerns were raised regarding data privacy and the ethical principles in the use of artificial intelligence. Additionally, it was found that there are educational and developmental needs for artificial intelligence users.

The Effect of Artificial Intelligence (AI) on Students' Learning

Various studies have been conducted to identify factors that contribute to student engagement, personalized learning experience, and student academic performance. The evolution of technology offers various benefits including in the education sector. To date, the use of Artificial Intelligence (AI) in education has been seen to provide various benefits. This study aims to identify the relationship between the usage of AI with student engagement, personalized learning experience, and student academic performance. Data was collected from 110 undergraduate students from the Faculty of Business and Management, UiTM Puncak Alam Campus using a questionnaire. 106 data were analyzed using SPSS version 29. The findings show that AI usage for study purposes significantly influences student’s engagement and academic performance. On the other hand, the usage of AI and personalized learning experience show no significant influence. This study not only provides a deeper understanding of the context of AI usage for better student engagement and academic performance but also gives valuable insight for UiTM and faculty specifically to develop strategies and modules that enhance the implementation and usage of AI in their learning activities.

Research trends in the use of artificial intelligence in higher education

The latest technological advancements have greatly interested researchers in artificial intelligence (AI) in education. In parallel, researchers have expressed concern about using and applying AI in education. However, there is a shortage of research that comprehensively and holistically examines trends in the use of AI in higher education. Hence, this study aimed to comprehensively analyze and assess AI research trends in higher education. In the SCOPUS database, we conducted a bibliometric analysis of 1,563 articles on research on AI in education. Our results revealed that the use of AI in education has increased dramatically from 2004 to 2023. In particular, a dramatic increase and peak exist after 2019. We also found limited interaction among scholars studying AI. Furthermore, our findings indicate that most of the most influential institutions are located in developed countries. Moreover, our findings demonstrated that AI research primarily concentrated on comprehending the impact of AI-based instruction, with the majority of these studies taking place in engineering education between 2017 and 2020. We also noticed that research on medical education in higher education occurred between 2015 and 2017. In addition, before 2015, research used AI in medical education as a teaching method to implement problem-based learning in higher education.

The Dark Side of Artificial Intelligence in Education: A Critical Analysis of its Impact on Learners Aged 12-14 Years

This research explores the connections between Teacher-Led Instruction (TLI), Peer Collaboration (PC), and Artificial Intelligence Assistance (AIA) in influencing Student Cognitive and Social-Emotional Development (SCED). Through exploratory and confirmatory factor analyses, the study found that TLI and PC are important positive predictors of SCED, highlighting the crucial role of collaborative and teacher-led approaches in promoting overall student development. Contrastingly, there is a negative association between AIA and SCED, underscoring the potential disadvantages of excessive dependence on technology at the cost of meaningful human connections. The results indicate that educational settings should give precedence to incorporating effective teaching approaches while utilizing technology as an auxiliary instrument rather than a replacement for conventional teaching methods. By embracing a multifaceted approach to instruction, this study contributes to the ongoing discourse on enhancing educational practices in an increasingly digital landscape, ultimately advocating for a future where students thrive both academically and emotionally while studying with Artificial Intelligence cautiously.

Finding the human in an era of machine intelligence: A flat ontological analysis of generative AI and language learning

Amid the optimism of generative Artificial Intelligence (gen-AI) in language education, there remains a weak connection to learning practices. The emergence of gen-AI has preceded considerations of how it should be applied in teaching and learning. However, while gen-AI has been justified in terms of the possibilities to enhance learner agency by expanding opportunities to engage with language, such as through the generation of content or the translation of texts, it can also take power away from learners. How can learners be self-determining in light of how choices become increasingly guided by Artificial Intelligence? In this paper, I conceive the arrangements of humans and software as an assemblage of complex and dynamic social, and technical processes. Drawing on a flat ontology, where all agents (human and non-human, material and subjective) have equal ontological status, I argue that learner agency has its origins in the messy and lively interactions between heterogenous actors. In particular, I consider active and passive affects as being part of the same process: active when we bring something into effect ourselves, passive when our self-determination is changed not by our own power, but through external forces acting on it (such as gen-AI). From this, I explore the constraining and enabling potential of artificial intelligence. Finally, I extend this discussion to the emergence of learner agency.

Artificial Intelligence and its relations with digital competencies and Education

This paper investigates the relationship between digital skills and the use of artificial intelligence (AI) in higher education, with an emphasis on the role of teachers. The research, through content analysis, explored 15 articles from the Web of Science and Scopus databases (2020-2024), using the Iramuteq software. The searches were carried out using the search terms “Artificial Intelligence” and “Digital Competence”. The results allowed us to verify that AI plays a relevant role in several stages of the teaching and learning process, from pedagogical planning to learning assessment processes. This ultimately highlights the need for teachers to develop digital skills, as a training that makes them more effective in using AI efficiently in developing students' skills. AI is seen as a tool that can enhance learning, helping students develop knowledge-based skills, such as problem-solving and content application. The study concludes that preparing educators to integrate these technologies is essential, ensuring that digital skills are taught and applied effectively, benefiting the teaching and learning process.

The Application, Challenges, and Reflection of Generative Artificial Intelligence in the Field of Education

The rapid development of Generative Artificial Intelligence technology has brought new opportunities to the field of education, giving rise to a large number of intelligent teaching applications and improving the quality and efficiency of teaching. However, the education industry has also encountered unprecedented challenges and tests, including new adjustments and changes in educational concepts, curriculum content, teaching methods, allocation of educational resources, educational evaluation systems, and teacher career transformation. These challenges urgently need to be faced and overcome by educators together. Therefore, while facing the heat of artificial intelligence technology, it is necessary to maintain rational thinking and reflect on some of the problems exposed in the application process of artificial intelligence, ensuring that artificial intelligence technology is applied reasonably and truly serving the essence and goals of education, achieving a dynamic balance between technology and humanistic education.

AI‐Mediated Communication in EFL Classrooms: The Role of Technical and Pedagogical Stimuli and the Mediating Effects of AI Literacy and Enjoyment

ABSTRACTThis study leverages the Stimulus‐Organism‐Response (S‐O‐R) framework to investigate the effects of teacher and technical support (TCHS) on learners' willingness to communicate (WTC) in artificial intelligence (AI)‐enhanced English as a foreign language (EFL) contexts, considering the mediating effects of learners' artificial intelligence literacy (AIL) and foreign language enjoyment (FLE). A quantitative survey encompassing 637 non‐English major university students across four institutions was conducted. Structural equation modelling (SEM) results demonstrated that teacher support (TEAS) exerts a direct influence on learners' WTC, whereas TCHS does not. The study also revealed that AIL and FLE significantly mediate the relationship between teacher and TCHS and learners’ WTC. The findings underscore the pivotal role of cognitive and affective factors, emphasising the substantial impact of TEAS and the value of nurturing learners’ AIL and enjoyment of foreign languages. This research offers strategic implications for educational practitioners and policymakers, advocating for the integration of innovative educational technologies and fostering sustainable growth in artificial intelligence in education.

An Early Snapshot of Attitudes Toward Generative Artificial Intelligence in Physical Therapy Education

Introduction. Generative artificial intelligence (AI) is rapidly gaining popularity across health care, education, and society. The purpose of this study was to assess perceptions and use of generative AI in academic physical therapy (PT). Review of Literature. Generative AI became one of the fastest-growing technologies ever after the public release of ChatGPT in November 2022. Early data indicate that attitudes toward generative AI in higher education are mixed and rapidly evolving, with significant ethical concerns around use and potential misuse. There are no published studies investigating perceptions and use of generative AI in PT education. Subjects. A total of 175 surveys were completed and analyzed. Respondents included PT educators, administrators, and students. Methods. An anonymous, online survey on use and perception of AI was distributed through email and social media. Descriptive statistics and cross-tabulations were performed to analyze respondent characteristics and responses to survey questions. Results. Most respondents (61.1%) reported they did not use generative AI during the 2022-2023 academic year, whereas 35.4% were generative AI users. More than 40% of respondents were optimistic or very optimistic toward generative AI. Users of AI were more likely to report an optimistic or very optimistic disposition toward AI compared with nonusers. AI users were more likely to agree or completely agree that generative AI has more benefits than drawbacks compared with nonusers. Discussion and Conclusion. Results of this survey suggest that, despite the rapid uptake of generative AI in society, many PT educators and students harbor reservations and uncertainties toward its use. Artificial intelligence users were less likely to hold negative perceptions toward it and were more likely to find it useful. Understanding use and perceptions of generative AI in PT education may inform strategies to promote innovation, policy-making, and ethical integration of this new and rapidly evolving technology.

Integration of Artificial Intelligence in Islamic Higher Education: Comparative Responses between Indonesia and Thailand

This study aims to compare the responses of Islamic Universities in Indonesia and Thailand to the adoption of artificial intelligence (AI) in Islamic education learning. This comparative qualitative research collected data from in-depth interviews, participatory observation, and analysis of relevant documents at UIN Walisongo Semarang (Indonesia) and Darul Maarif Islamic College Patani (Thailand). The collected data were analyzed thematically using triangulation, member checking, and audit trail validation models. The findings of this study show similarities and differences; both institutions have not specifically incorporated AI into the formal curriculum as a course, only integrating it implicitly in the hidden curriculum such as research, workshops, and seminars. Indonesian Islamic universities view AI as an important tool for modernizing Islamic education, especially in distance learning and the digitalization of Qur'anic teaching. In contrast, although AI is not explicitly banned in Thailand, there are concerns about its impact on the role of traditional teachers and Islamic cultural values. Regarding ethics, Indonesian students are less likely to consider the potential bias of AI towards Islamic religious information. In contrast, Thai students are more wary of the impact of technology on their religious values. Mastery of AI technology also showed significant differences, with Indonesian students being more advanced.

The role of artificial intelligence in higher medical education and the ethical challenges of its implementation

Artificial intelligence (AI) is penetrating higher medical education; however, its adoption remains low. A PRISMA-S search of the Web of Science database from 2020 to 2024, utilizing the search terms “artificial intelligence,” “medicine,” “education,” and “ethics,” reveals this trend. Four key areas of AI application in medical education are examined for their potential benefits: Educational support (such as personalized distance education), radiology (diagnostics), virtual reality (VR) (visualization and simulations), and generative text engines (GenText), such as ChatGPT (from the production of notes to syllabus design). However, significant ethical risks accompany AI adoption, and specific concerns are linked to each of these four areas. While AI is recognized as an important support tool in medical education, its slow integration hampers learning and diminishes student motivation, as evidenced by the challenges in implementing VR. In radiology, data-intensive training is hindered by poor connectivity, particularly affecting learners in developing countries. Ethical risks, such as bias in datasets (whether intentional or unintentional), need to be highlighted within educational programs. Students must be informed of the possible motivation behind the introduction of social and political bias in datasets, as well as the profit motive. Finally, the ethical risks accompanying the use of GenText are discussed, ranging from student reliance on instant text generation for assignments, which can hinder the development of critical thinking skills, to the potential danger of relying on AI-generated learning and treatment plans without sufficient human moderation.

ARTIFICIAL INTELLIGENCE IN BIOLOGY EDUCATION

Artificial intelligence (AI) in biology education can be defined as the deployment of AI in sections of study that help learners and researchers in their areas of concentration, specifically biological sciences. It gives a significant meaning toward the improvement of biology education since AI contributes toward the improvement of research methods and the expansion of knowledge on the associated biological concepts. Continued advances in artificial intelligence as a powerful tool in biological research will prove a major boon to the further development of biology education. Traditional basic biological sciences and such interdisciplinary fields as computational biology will step up their cooperation and come up with new theoretical predictions. They develop new theoretical frameworks; all these exciting changes that are rocking the biological world today are destined to reshape the face of the education in biology in the twenty-first century.

The Research on the Application of Deep Learning in Education

With the in-depth reform of education, deep learning is gradually being applied to education, which can stimulate students’ initiative in learning and improve their learning efficiency. This article explores some specific applications of deep learning in education, uses the deep learning model LSTM to predict students’ learning abilities and outcomes, and obtains high accuracy. Through deep learning models, we have abstracted the characteristics of students’ learning states and made relatively accurate predictions on their learning outcomes. This paper provides some useful explorations on the application of artificial intelligence and deep learning in education, which can provide valuable references for better research in the future.

Shaping the future: perspectives on the Integration of Artificial Intelligence in health profession education: a multi-country survey

BackgroundArtificial intelligence (AI) is transforming health profession education (HPE) through personalized learning technologies. HPE students must also learn about AI to understand its impact on healthcare delivery. We examined HPE students’ AI-related knowledge and attitudes, and perceived challenges in integrating AI in HPE.MethodsThis cross-sectional included medical, nursing, physiotherapy, and clinical nutrition students from four public universities in Jordan, the Kingdom of Saudi Arabia (KSA), the United Arab Emirates (UAE), and Egypt. Data were collected between February and October 2023 via an online survey that covered five main domains: benefits of AI in healthcare, negative impact on patient trust, negative impact on the future of healthcare professionals, inclusion of AI in HPE curricula, and challenges hindering integration of AI in HPE.ResultsOf 642 participants, 66.4% reported low AI knowledge levels. The UAE had the largest proportion of students with low knowledge (72.7%). The majority (54.4%) of participants had learned about AI outside their curriculum, mainly through social media (66%). Overall, 51.2% expressed positive attitudes toward AI, with Egypt showing the largest proportion of positive attitudes (59.1%). Although most participants viewed AI in healthcare positively (91%), significant variations were observed in other domains. The majority (77.6%) supported integrating AI in HPE, especially in Egypt (82.3%). A perceived negative impact of AI on patient trust was expressed by 43.5% of participants, particularly in Egypt (54.7%). Only 18.1% of participants were concerned about the impact of AI on future healthcare professionals, with the largest proportion from Egypt (33.0%). Some participants (34.4%) perceived AI integration as challenging, notably in the UAE (47.6%). Common barriers included lack of expert training (53%), awareness (50%), and interest in AI (41%).ConclusionThis study clarified key considerations when integrating AI in HPE. Enhancing students’ awareness and fostering innovation in an AI-driven medical landscape are crucial for effectively incorporating AI in HPE curricula.

AI-Enhanced Epidemiology Education: Bridging Technology and Conceptual Understanding

This article explores the integration of artificial intelligence (AI) and innovative teaching methods in epidemiology education, emphasizing a balanced approach to enhance learning outcomes. While traditional teaching focuses on core concepts and rubric-based evaluation offers consistency, overreliance on these methods can lead to superficial understanding. Creative and experiential learning activities, such as poems, cartoons, and ungrading, foster deeper engagement and mastery. Technological tools such as simulated outbreak investigations, virtual epidemiology games, and augmented reality programs provide hands-on experience and inspire motivated learning. Emphasizing critical thinking and practical skills, a balanced approach leveraging rubrics, AI, and innovative methods is essential for comprehensive and effective epidemiology education.