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Journal articles on the topic 'AI-Assisted Learning'

Author: Grafiati

Published: 7 June 2025

Last updated: 2 August 2025

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1

Miller, Adam L. "AI Assisted Learning." Journal of e-learning Research 2, no. 2 (2023): 52–65. http://dx.doi.org/10.33422/jelr.v2i2.510.

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Both Web 4.0 and EDU 4.0 are malleable terms, that while difficult to define, set the basis for contemporary learning environments. Within these boundaries, AI (Artificial Intelligence) and AIEd (Artificial Intelligence in Education) have further complicated modern pedagogy with an ever-increasing list of potential benefits and pitfalls. This paper argues that to utilize AI and AIEd to its fullest potential, it must first be understood before it is implemented, and that while the increased presence of AI in our daily lives may be inevitable, the path it follows is not predetermined. This paper

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Dr., Amartya Saha. "Understanding the Scope and Problems of Artificial Intelligence and Assisted Learning in Higher Education." Social Science Journal for Advanced Research 4, no. 5 (2024): 1–9. https://doi.org/10.5281/zenodo.13637234.

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Learning is a dynamic experience. We need to create learning experiences that assist all kinds of learners. Human beings have different patterns of learning. Assisted learning helps in decentralizing the learning experience in a more individualistic approach. Artificial Intelligence has helped in automating many tasks of administrative nature, evaluation and has even helped personalize learning, countering the problems of teacher exhaustion. Not just efficient grading use of AI through educational chatbots and applications can help in helping students get a 24/7 mentoring option which in a rea

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Tian, Jingxiao, Hanzhe Li, Yaqian Qi, Xiangxiang Wang, and Yuan Feng. "Intelligent medical detection and diagnosis assisted by deep learning." Applied and Computational Engineering 64, no. 1 (2024): 116–21. http://dx.doi.org/10.54254/2755-2721/64/20241356.

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The integration of artificial intelligence (AI) in healthcare has led to the development of intelligent auxiliary diagnosis systems, enhancing diagnostic capabilities across various medical domains. These AI-assisted systems leverage deep learning algorithms to aid healthcare professionals in disease screening, localization of focal areas, and treatment plan selection. With policies emphasizing innovation in medical AI technology, particularly in China, AI-assisted diagnosis systems have emerged as valuable tools in improving diagnostic accuracy and efficiency. These systems, categorized into

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Guan, Heyuan. "The impact of artificial intelligence on English learning among Chinese undergraduates." Advances in Engineering Innovation 14, no. 1 (2024): 12–29. https://doi.org/10.54254/2977-3903/2024.18123.

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With the introduction of artificial intelligence (AI) into education, Chinas English education in the university has also been affected. The COVID-19 pandemic accelerated the application of AI tools in education. This study investigates the practical use of AI tools in English learning among Chinese undergraduates before, during, and after the pandemic. Students perspectives were collected through questionnaires. And its data was analyzed by using frequency analysis and multiple response analysis in SPSS. Teachers perspectives were gathered through interview. The study explored their views, at

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Supadi Supadi. "Implementation of Data-Based Management in Improving the Effectiveness of AI-Assisted Learning in Senior High School." Jurnal Ilmiah Rumpun Ilmu Pendidikan 1, no. 4 (2024): 61–82. https://doi.org/10.63760/jirip.v1i4.31.

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This study aims to analyze the implementation of data-based management in improving the effectiveness of AI-assisted learning in Senior High School. The unit of analysis in this study is a school that implements a data-based management system in AI-assisted learning. The research design used is a qualitative study with a case study approach. The research data sources consist of school principals, teachers, and students involved in the implementation of AI-assisted learning. Data collection techniques include in-depth interviews, participatory observation, and analysis of school documents. The

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N, Moulieswaran, and Prasantha Kumar N S. "Investigating ESL Learners’ Perception and Problem towards Artificial Intelligence (AI) -Assisted English Language Learning and Teaching." World Journal of English Language 13, no. 5 (2023): 290. http://dx.doi.org/10.5430/wjel.v13n5p290.

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The contemporary language learning strategy, Artificial Intelligence (AI) Assisted Language Learning (AI-ALL), incorporates AI-powered applications to support learners' learning activities. Many scholars have been experimenting with AI applications concerning activities relevant to education. The major objectives of this study are 1) The ESL learners' perspectives concerning AI-assisted English language learning and teaching; 2). ESL learners’ problems concerning artificial AI-assisted English language learning and teaching. The present investigation employed a quantitative methodology utilizi

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Okata, Ngozi Gift, and Akinsanya Atchrimi Adebayo. "Exploring (AI) Artificial Intelligence's Role in Language Teaching and Learning: A Review of Key Technologies and Their Applications." Beyond Babel: A Publication of the Dept. of Languages and Literary Studies Babcock University, Ogun State, Nigeria 8, no. 2 (2025): 50–73. https://doi.org/10.5281/zenodo.14599743.

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<strong>Abstract</strong> Artificial Intelligence (AI) is revolutionizing various aspects of education and is increasingly being integrated into language teaching and learning. This article reviews the literature to examine key trends and findings related to AI technologies and their applications for second and foreign language education. It focuses on Natural Language Processing (NLP), Data-Driven Learning (DDL), Automated Writing Evaluation (AWE), Computer-assisted Dynamic Assessment (CDA), Intelligent Tutoring Systems (ITSs), Automatic Speech Recognition (ASR), and chatbots, all within the

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Grednev, Sergej, Henrik S. Steude, Stefan Bronder, Oliver Niggemann, and Anne Jung. "AI-assisted study of auxetic structures." Acta Polytechnica CTU Proceedings 42 (October 12, 2023): 32–36. http://dx.doi.org/10.14311/app.2023.42.0032.

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In this study, the viability of using machine learning models to predict stress-strain curves of auxetic structures based on geometry-describing parameters is explored. Given the computational cost and time associated with generating these curves through numerical simulations, a machine learning-based approach promises a more efficient alternative. A range of machine learning models, including Artificial Neural Networks, k-Nearest Neighbors Regression, Support Vector Regression, and XGBoost, is implemented and compared regarding the aptitude to predict stress-strain curves under quasi-static c

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Wibowo, Setyo Aji, and Intan Faizah. "Pengaruh Model Pembelajaran Berbasis Masalah berbantuan Chatbot AI terhadap Higher Order Thinking Skill." Jurnal Nyanadassana: Jurnal Penelitian Pendidikan, Sosial dan Keagamaan 2, no. 2 (2023): 73–85. http://dx.doi.org/10.59291/jnd.v2i2.36.

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This study aims to determine the effect of problem-based learning models assisted by AI chatbots on higher-order thinking skills in Class IV at SDN 1 Genteng Kec. Genteng, Kab. Banyuwangi, East Java. This type of research uses a quantitative approach with a quasi-experimental research method and a Non-equivalent Control Group Design. Non-probability sampling was used. The population and sample consisted of 33 students in class IV-A as the experimental class and 39 students in class IV-B as the control class in SDN 1 Genteng, Kec. Genteng, Kab. Banyuwangi, East Java. The data-collection instrum

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Çela, Eriona, Mathias Mbu Fonkam, and Rajasekhara Mouly Potluri. "Risks of AI-Assisted Learning on Student Critical Thinking." International Journal of Risk and Contingency Management 12, no. 1 (2024): 1–19. http://dx.doi.org/10.4018/ijrcm.350185.

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Artificial Intelligence (AI) has increasingly become a transformative force in the education sector, offering unprecedented opportunities to enhance learning experiences and outcomes. This study examines the potential adverse effects of AI-assisted learning on critical cognitive skills, particularly critical thinking and problem-solving, within the context of Albania's educational landscape. Employing a quantitative methodology, a survey of 53 students was conducted across various educational institutions in Albania to gather data on their experiences and perceptions regarding AI-assisted lear

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Pham, Thanh, Thanh Binh Nguyen, Son Ha, and Ngoc Thanh Nguyen Ngoc. "Digital transformation in engineering education: Exploring the potential of AI-assisted learning." Australasian Journal of Educational Technology 39, no. 5 (2023): 1–19. http://dx.doi.org/10.14742/ajet.8825.

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This research explored the potential of artificial intelligence (AI)-assisted learning using ChatGPT in an engineering course at a university in South-east Asia. The study investigated the benefits and challenges that students may encounter when utilising ChatGPT-3.5 as a learning tool. This research developed an AI-assisted learning flow that empowers learners and lecturers to integrate ChatGPT into their teaching and learning processes. The flow was subsequently used to validate and assess a variety of exercises, tutorial tasks and assessment-like questions for the course under study. Introd

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Qiuyang, Huang, Li Wenling, and Zhao Yanmei. "Enhancing Deep Learning and Motivation in University English Education through AI Technology: A Quasi-Experimental Study." Asian Journal of Education and Social Studies 51, no. 4 (2025): 452–63. https://doi.org/10.9734/ajess/2025/v51i41883.

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Aims: This study explores the impact of AI-assisted learning on academic achievement and learning motivation in university English education. It aims to analyze the effectiveness of different AI-integrated learning environments in enhancing students’ engagement and performance. Study Design: A mixed-methods approach was employed, incorporating both exploratory and confirmatory quasi-experimental designs. Twenty-four students (six from each group) are selected for eye-tracking. Place and Duration of Study: The study was conducted at University in China over a period of four months. Methodology:

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Chen, Chen, and Yang (Frank) Gong. "The Role of AI-Assisted Learning in Academic Writing: A Mixed-Methods Study on Chinese as a Second Language Students." Education Sciences 15, no. 2 (2025): 141. https://doi.org/10.3390/educsci15020141.

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This mixed-methods study examines the role of artificial intelligence (AI)-assisted learning in academic writing for Chinese as a Second Language (CSL) students in a Chinese university context. Fifty international CSL students were randomly assigned to experimental—AI-assisted learning using ChatGPT—and control—traditional learning—groups. Writing samples from the participants were evaluated using established scoring rubrics for Chinese academic writing. Based on pre- and post-test quantitative data and supplementary qualitative interviews with six participants from the experimental group, thi

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N, Moulieswaran, and Prasantha Kumar N S. "Google Assistant Assisted Language Learning (GAALL): ESL Learners’ Perception and Problems towards AI-powered Google Assistant-Assisted English Language Learning." Studies in Media and Communication 11, no. 4 (2023): 122. http://dx.doi.org/10.11114/smc.v11i4.5977.

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The New-fangled strategy called Artificial Intelligence (AI) Assisted Language Learning (AI-ALL) incorporates Google Assistant (GA) to support the learning activities of learners. At present, it is considered Google Assistant Assisted Language Learning (GAALL). For many years, academicians have been exploring ways to use AI for tasks that are related to education. The major objectives of this study are to emphasize 1) The ESL learners' perceptions of using AI-powered Google Assistant for learning the English language; 2). The ESL learners’ problems are concerned with utilizing AI-powered Googl

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Semerikov, Serhiy O., Andrii M. Striuk, and Hanna M. Shalatska. "AI-assisted language education: critical review." Educational Dimension 4 (June 22, 2021): 1–7. http://dx.doi.org/10.31812/ed.623.

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This paper reviews the current research on AI-assisted language education (AILE). AI has greatly influenced education, especially language learning. AILE, an interdisciplinary field combining AI technology and language education theory, aims to improve foreign language learners’ experiences through personalized, interactive, and collaborative learning. This review classifies AILE research into four key domains: language-specific applications, comprehensive teaching modes, new educational ecosystems, and identification technology integration. It analyzes the strengths, weaknesses, opportunities

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Alanazi, Manal, Ben Soh, Halima Samra, and Alice Li. "The Influence of Artificial Intelligence Tools on Learning Outcomes in Computer Programming: A Systematic Review and Meta-Analysis." Computers 14, no. 5 (2025): 185. https://doi.org/10.3390/computers14050185.

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This systematic review and meta-analysis investigates the impact of artificial intelligence (AI) tools, including ChatGPT 3.5 and GitHub Copilot, on learning outcomes in computer programming courses. A total of 35 controlled studies published between 2020 and 2024 were analysed to assess the effectiveness of AI-assisted learning. The results indicate that students using AI tools outperformed those without such aids. The meta-analysis findings revealed that AI-assisted learning significantly reduced task completion time (SMD = −0.69, 95% CI [−2.13, −0.74], I2 = 95%, p = 0.34) and improved stude

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Sako, Takayoshi. "Enhancing Critical Thinking through AI-Assisted Collaborative Task-Based Learning: A Case Study of Prospective Teachers in Japan." Journal of English Language Teaching and Linguistics 9, no. 2 (2024): 157. http://dx.doi.org/10.21462/jeltl.v9i2.1319.

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<div><p><em>This study explores the potential of integrating generative AI into collaborative task-based language learning to foster critical thinking (CT) skills in computer-assisted learning environments. Employing a mixed-methods approach, the research examines the experiences of 18</em><em> pre-service teachers engaging in AI-assisted collaborative activities. Quantitative analysis of the Critical Thinking Disposition Scale and qualitative analysis using the modified grounded theory approach (M-GTA) reveal that AI tools can alleviate collaboration challenges b

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Biradar, Shivkumar L., and Aishwarya J. Goyal. "Impact of Dependence on AI Assisted English Language Tools on Retention and Proficiency of English Communication among UG and PG Students." InSight Bulletin: A Multidisciplinary Interlink International Research Journal 2, no. 3 (2025): 13–20. https://doi.org/10.5281/zenodo.15421811.

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<strong><em>Synopsis</em></strong> <em>The use of artificial intelligence (AI)-assisted English language learning tools has become increasingly popular among UG and PG students. One of the main concerns about AI-assisted English language learning tools is that they can make students over dependent on the tools and less likely to think critically about their own language use. For example, students who use AI-assisted English language learning tools to translate text from their native language to English may not learn how to express themselves effectively in English.</em> <em>Another concern abo

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Basir, Sitti Nurfadhilah, Rahayu Pristiwati, and Wagiran . "E-Book Text Description Assisted by Artificial Intelligence (AI) Contains Pancasila Student Profile Dimensions of Global Diversity." International Journal of Research and Review 11, no. 7 (2024): 378–87. http://dx.doi.org/10.52403/ijrr.20240739.

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This research focuses on the development of an e-book of description text assisted by artificial intelligence for Indonesian language learning. This research will explore the use of e-books in the context of learning descriptive texts, with the content of Pancasila student profiles and global diversity. This study uses a Research and Development (R&D) research design. The use of R&D research design is because the researcher will develop an e-book of descriptive text assisted by Artificial Intelligence (AI). The results of the research presented in this chapter include 4 things includin

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Xiao, Bona, and Jun Cui. "A Critical Review of AI-Assisted English Education in Cognitive Rehabilitation." Life Studies 1, no. 2 (2025): 1–12. https://doi.org/10.71204/wex4vr14.

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This paper examines the influence of AI-assisted English education on patients, particularly focusing on cognitive development and brain function. With the increasing integration of artificial intelligence in educational settings, AI-driven tools have emerged as effective resources for enhancing language learning experiences. This study highlights how personalized and interactive learning experiences can significantly benefit patients, especially those with language disorders, cognitive impairments, or various neurological conditions. Engaging in structured language learning exercises not only

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Mohammad Aniq Bin Amdan, Naldo Janius, Mohd Norhazli Bin Jasman, and Mohd Aidil Hazidi Bin Kasdiah. "Advancement of ai-tools in learning for technical vocational education and training (TVET) in Malaysia (empowering students and tutor)." International Journal of Science and Research Archive 12, no. 1 (2024): 2061–68. http://dx.doi.org/10.30574/ijsra.2024.12.1.0971.

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The potential of Artificial Intelligence (AI) in Technical and Vocational Education and Training (TVET) in Malaysia, has an advantage in Education. Given the swift progress of AI technology, Malaysia’s TVET sector can utilise AI-assisted learning to improve teaching and learning. Malaysia’s TVET institutions can enhance skill acquisition among students by adopting advanced tools like adaptive learning algorithms, virtual simulations, and intelligent tutoring systems, which cater to diverse learning styles. Nevertheless, like any other area, Malaysia encounters obstacles such as ethical dilemma

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Saptiany, Shella Gherina, Syamsul Hadi, Benedectta Arsenia Nanda Hardian, and Muhammad Madchan Nashir. "Artificial Intelligence-Moderated Gamification Apps: Elevating Gen Z’s English Vocabulary Mastery." AL-ISHLAH: Jurnal Pendidikan 16, no. 4 (2024): 4969–83. https://doi.org/10.35445/alishlah.v16i4.5957.

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Generation Z students are increasingly adopting gamification in language learning, often enhanced by Artificial Intelligence (AI). Gamified language learning applications are touted for their ability to improve vocabulary acquisition effectively. This study aimed to evaluate the efficacy of AI-assisted gamification in vocabulary learning among Generation Z students in Semarang, Indonesia. A descriptive cross-sectional survey design was employed, involving 400 participants. Data were collected via questionnaires and analyzed using Structural Equation Modeling (SEM) to identify the effectiveness

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López-Meneses, Eloy, Luis López-Catalán, Noelia Pelícano-Piris, and Pedro C. Mellado-Moreno. "Artificial Intelligence in Educational Data Mining and Human-in-the-Loop Machine Learning and Machine Teaching: Analysis of Scientific Knowledge." Applied Sciences 15, no. 2 (2025): 772. https://doi.org/10.3390/app15020772.

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This study explores the integration of artificial intelligence (AI) into educational data mining (EDM), human-assisted machine learning (HITL-ML), and machine-assisted teaching, with the aim of improving adaptive and personalized learning environments. A systematic review of the scientific literature was conducted, analyzing 370 articles published between 2006 and 2024. The research examines how AI can support the identification of learning patterns and individual student needs. Through EDM, student data are analyzed to predict student performance and enable timely interventions. HITL-ML ensur

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Zhong, Ruikang, Yuanwei Liu, Xidong Mu, Yue Chen, and Lingyang Song. "AI Empowered RIS-Assisted NOMA Networks: Deep Learning or Reinforcement Learning?" IEEE Journal on Selected Areas in Communications 40, no. 1 (2022): 182–96. http://dx.doi.org/10.1109/jsac.2021.3126068.

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Zhu, Yunyi. "The Impact of AI-Assisted Teaching on Students' Learning and Psychology." Journal of Education, Humanities and Social Sciences 38 (September 28, 2024): 111–16. http://dx.doi.org/10.54097/k7a37d11.

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The integration of artificial intelligence (AI) in education has garnered significant attention, yet its implications on student outcomes require further exploration. This paper analyzes the impact of AI-assisted teaching on students' learning and psychological well-being. Through a comprehensive review of existing AI applications in education, including intelligent tutoring systems and educational chatbots, the study examines how these technologies influence academic performance and psychological health. The findings indicate that AI-assisted teaching enhances learning outcomes by providing p

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Georgiev, Svetoslav, and Joseph Tinsley. "Exploring Student Acceptance and Perceptions of AI-Assisted PowerPoint Creation." African Journal of Inter/Multidisciplinary Studies 6, no. 1 (2024): 1–13. https://doi.org/10.51415/ajims.v6i1.1521.

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Generative AI (GenAI) has had a disruptive effect on teaching and learning in Higher Education contexts. This paper addresses the need to examine students’ perceptions and acceptance of teacher GenAI usage in real world classroom settings. Using a qualitative research design, we explore the student acceptance and perceptions of AI-assisted learning materials (i.e., presentation slides generated by Microsoft PowerPoint Designer). The study draws its sample from one of the top transnational universities in China. Two rounds of focus group interviews with a total of 11 final-year undergraduate st

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Narongsaksakul, Watsachol. "AI-based Assessment for Learning on Students’ Critical Thinking." Journal of Ethics in Higher Education, no. 6.2 (July 22, 2025): 237–49. https://doi.org/10.26034/fr.jehe.2025.8443.

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Critical thinking is essential for state standards and culturally relevant pedagogy (CRP). This paper explores AI-based assessment in education (AIED), focusing on its benefits and challenges for assessing critical thinking in diverse students post-Chat GPT. It covers AI-enhanced assessment for learning to promote diversity and cultural responsiveness, biases in AI technologies, and AI-assisted critical thinking assessment. Three benefits of AI include adaptive assessments, multimodal assessments, and personalized feedback. Ethical concerns include understanding AI limitations, ensuring ethica

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Lutfi, Rania. "Neutrosophic Clustering in Adaptive AI Learning for Students with Down Syndrome." Journal of Digital Learning and Education 5, no. 1 (2025): 53–66. https://doi.org/10.52562/jdle.v5i1.1539.

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Students with Down syndrome respond positively to adaptive AI learning systems, but existing models struggle to effectively accommodate their unique challenges in working memory and attention control. These limitations stem from rigid clustering methods, which fail to personalize learning pathways according to the individual cognitive needs of students. This paper proposes a theoretical framework integrating Neutrosophic C-Means Clustering (NCM) into adaptive AI for special education. Grounded in cognitive theories on Down syndrome, the framework applies neutrosophic logic to refine membership

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Maanu, Vivian, Francis Ohene Boateng, and Ernest Larbi. "AI-assisted instructions in collaborative learning in mathematics education." American Journal of STEM Education 7 (March 4, 2025): 11–36. https://doi.org/10.32674/68zzkz60.

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This qualitative study, grounded in an interpretive paradigm, used a phenomenological methodology to explore the experiences of pre-service math teachers in three colleges of education in Ghana's Ashanti region. The sample included 50 participants. The results showed that people have positive views and attitudes about AI-assisted instruction. These views and attitudes can be broken down into four groups: general views, attitudes toward AI tools, the effects on collaboration, and ethical concerns. Factors influencing engagement in the learning experience included technological, pedagogical, soc

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Chen, Bang, Mao-Nian Wu, Shao-Jun Zhu, et al. "Artificial intelligence assisted pterygium diagnosis: current status and perspectives." International Journal of Ophthalmology 16, no. 9 (2023): 1386–94. http://dx.doi.org/10.18240/ijo.2023.09.04.

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Pterygium is a prevalent ocular disease that can cause discomfort and vision impairment. Early and accurate diagnosis is essential for effective management. Recently, artificial intelligence (AI) has shown promising potential in assisting clinicians with pterygium diagnosis. This paper provides an overview of AI-assisted pterygium diagnosis, including the AI techniques used such as machine learning, deep learning, and computer vision. Furthermore, recent studies that have evaluated the diagnostic performance of AI-based systems for pterygium detection, classification and segmentation were summ

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PRATAP SINGH, DIVYANSH. "Impact of Artificial Intelligence on the Academic Environment." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 04 (2025): 1–9. https://doi.org/10.55041/ijsrem44260.

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Integrating Artificial Intelligence (AI) in education has significantly transformed teaching methodologies, assessment systems, and student engagement. This study evaluates the impact of AIdriven personalized learning and compares AI-assisted grading systems with traditional methods. The research examines the relationship between AI adoption and student performance using a dataset of 115 respondents and applying statistical techniques such as correlation analysis, chi-square tests, and parabolic distribution modelling. Findings reveal that while AI contributes to improved learning outcomes, it

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Gracema., A. "AI-Assisted Language Learning Tools' Role in Second Language Acquisition." Literary Enigma 1, no. 2 (2025): 66–71. https://doi.org/10.5281/zenodo.15316008.

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Abstract   AI has become an integral part of people’s daily lives. Apps are often integrated with AI to give language learners a human-like approach to learning. As the language acquisition process generally begins at home in Indian households, the demand for a second language grows to build one’s career in alignment with global prospects. The second language acquisition is usually English, which is considered the lingua franca. The growing demand for language learning led to the boom in online platforms, replacing the traditional classroom setting. Online learning is sophisti

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Widada, Wahyu, Khathibul Umam Zaid Nugroho, Masri Masri, et al. "Enhancing PISA-like mathematical literacy through deep learning assisted by mathos ai for junior high school students." Jurnal Math Educator Nusantara: Wahana Publikasi Karya Tulis Ilmiah di Bidang Pendidikan Matematika 11, no. 1 (2025): 1–20. https://doi.org/10.29407/jmen.v11i1.25109.

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Based on PISA, Indonesian students' mathematical literacy skills are very low. This study investigates the effectiveness of Mathos AI-assisted deep learning design in improving PISA-like mathematical literacy among junior high school students. Using design research methodology with validation studies approach. Data were collected through pre-test and post-test, classroom observation, interviews, and analysis of student work. The findings revealed significant improvements in students' mathematical literacy, with positive impacts on their motivation and engagement. The integration of Mathos AI f

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Varma, Dr Vinod. "AI-Assisted Surgical Robotics: A Review of Current State and Future Possibilities." International Research Journal of Computer Science 11, no. 06 (2024): 539–45. http://dx.doi.org/10.26562/irjcs.2024.v1106.04.

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By improving accuracy, decreasing human error, and permitting less invasive operations, artificial intelligence (AI)-assisted surgical robotics is transforming contemporary surgery. The integration of sophisticated algorithms like computer vision, machine learning, and deep learning approaches is the main emphasis of this paper, which examines the state of AI-driven surgical robotics today. Modern approaches like Convolutional Neural Networks (CNNs) for image-guided navigation and Reinforcement Learning (RL) for autonomous decision-making in surgical tasks are contrasted with traditional metho

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Sein Minn. "AI-assisted knowledge assessment techniques for adaptive learning environments." Computers and Education: Artificial Intelligence 3 (2022): 100050. http://dx.doi.org/10.1016/j.caeai.2022.100050.

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Li, Yin, Yueying Ni, Rupert A. C. Croft, Tiziana Di Matteo, Simeon Bird, and Yu Feng. "AI-assisted superresolution cosmological simulations." Proceedings of the National Academy of Sciences 118, no. 19 (2021): e2022038118. http://dx.doi.org/10.1073/pnas.2022038118.

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Cosmological simulations of galaxy formation are limited by finite computational resources. We draw from the ongoing rapid advances in artificial intelligence (AI; specifically deep learning) to address this problem. Neural networks have been developed to learn from high-resolution (HR) image data and then make accurate superresolution (SR) versions of different low-resolution (LR) images. We apply such techniques to LR cosmological N-body simulations, generating SR versions. Specifically, we are able to enhance the simulation resolution by generating 512 times more particles and predicting th

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Duy, Nguyen Binh Phuong, Tran Ngoc My Phuong, Vu Nguyen Minh Chau, Nguyen Vo Huong Nhi, Vo Thi Mai Khuyen, and Nguyen Thi Phuong Giang. "AI-assisted learning: an empirical study on student application behavior." Multidisciplinary Science Journal 7, no. 6 (2024): 2025275. https://doi.org/10.31893/multiscience.2025275.

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In the wake of the fourth industrial revolution, artificial intelligence is gaining momentum and is widely applied in various aspects of life, particularly education. This study investigates the factors influencing students' use of artificial intelligence (AI) in learning, focusing on students at Ho Chi Minh City University of Industry. The research uses a combination of the technology acceptance model and the theory of planned behavior to examine the relationships between subjective norms, image, job relevance, output quality, result demonstrability, self-efficacy, anxiety, perceived playfuln

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Yan, Qiao, Supyan Hussin, and Khairul Azhar Jamaludin. "Students’ Perceptions of AI-Assisted Blended Teaching in A Chinese Translation Class: A Preliminary Study." Arab World English Journal 11 (July 26, 2025): 160–76. https://doi.org/10.24093/awej/call11.10.

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Tertiary translation education is essential for cultivating talents in cross-cultural communications in the age of language automation. However, the mismatch between current translation pedagogy and the language industry is palpable. While artificial intelligence has emerged as a key impetus of language automation, learners’ perceptions of utilizing educational technologies in their translation learning remain underexplored. Particularly, the underlying factors of learner perceptions that significantly affect learners’ technology acceptance have yet to be thoroughly examined. This study aims t

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Siti Nofiati. "PENINGKATAN KEMAMPUAN MENULIS ESAI MELALUI PROBLEM BASED LEARNING BERBANTUAN MEDIA AI QUANDARY PADA PEMBELAJARAN SOSIOLOGI." Jurnal Inovasi Daerah 3, no. 2 (2024): 188–201. https://doi.org/10.56655/jid.v3i2.298.

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This study aims to improve essay writing skills through the application of PBL assisted by the AI Quandary media in sociology lessons for tenth-grade students at SMA Islam Al Azhar 35 Cilacap. This Classroom Action Research (CAR) was conducted in two cycles, with each cycle consisting of planning, implementation, observation, and reflection stages. The instruments used in this study included observation sheets, essay writing skill assessment sheets, and documentation. The results showed that the implementation of Problem-Based Learning assisted by AI Quandary significantly improved students' e

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Academic, Journal of Manufacturing Engineering. "ARTIFICIAL INTELLIGENCE IN THE CAD PROCESS: MACHINE LEARNING MODELS, GENERATIVE OPTIMISATION, AND THEIR IMPACT ON DESIGN." Academic Journal of Manufacturing Engineering 23, no. 1 (2025): L2. https://doi.org/10.5281/zenodo.15180312.

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: The integration of Artificial Intelligence (AI) into Computer-Aided Design (CAD) is transforming the product development process by enhancing efficiency, accuracy, and innovation. AI-driven approaches, including Machine Learning Models (MLMs) and optimisation algorithms, automate design processes, improve decision-making, and enable the exploration of optimised solutions that transcend traditional design limitations. Despite these advancements, the adoption of AI in CAD presents significant technological, ethical, and professional challenges. This study aims to analyse the impact of AI on CA

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Kim, EunJung. "AI-assisted English learning: A tool for all or only a select few?" Language Learning & Technology 29, no. 1 (2025): 1. https://doi.org/10.64152/10125/73633.

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This study investigated English learner profiles and challenges among 884 Korean 5th-grade students, with a focus on the role of AI-assisted language learning in shaping proficiency outcomes. While AI-based interventions have gained popularity, their effectiveness across diverse learner populations remains insufficiently explored. The study aimed to (a) empirically identify distinct learner profiles based on motivational, contextual, and socio-affective characteristics through latent class analysis (LCA), and (b) examine the predictive effects of AI participation and learner-specific factors o

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Robinson, Brandi. "Harnessing AI for Structured Learning: The Case for Objective-Driven Design in E-Learning." International Journal on E-Learning 23, no. 4 (2024): 457–70. https://doi.org/10.70725/758146udgktc.

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The integration of artificial intelligence in e-learning presents promising avenues for scalable, efficient content creation. However, the prevailing content-first approach in AI course design often compromises educational quality for speed, leading to courses that lack coherence, cognitive alignment, and structured progression. This article argues that an objective-driven approach, guided by educational frameworks like backward design, Bloom's Taxonomy, and constructivist theory, enhances AI-generated courseware to foster meaningful learning outcomes. Through a case study of an AI-assisted cy

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Alex Joseph, A. Franklin, Muhammadu Sathik Raja, Afsal Basha V. A., D. Muthukumaran, and Gowthami V. "Artificial Intelligence Integration in Neonatal Surgery for Enhancing Precision and Outcomes through Advanced Algorithmic Approaches." Journal of Neonatal Surgery 14, no. 4S (2025): 61–71. https://doi.org/10.52783/jns.v14.1738.

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Neonatal surgery has been transformed by artificial intelligence (AI), which has improved intraoperative decision-making, surgical planning, and diagnostic precision. By assessing popular machine learning and deep learning methods like Convolutional Neural Networks (CNNs), Support Vector Machines (SVMs), and Reinforcement Learning models, this study investigates the incorporation of AI in newborn surgical operations. Analysing existing AI-assisted newborn surgical systems, determining their shortcomings, and suggesting an ideal hybrid AI model that combines Reinforcement Learning and Transform

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Desmond, Michael, Michelle Brachman, Evelyn Duesterwald, et al. "AI Assisted Data Labeling with Interactive Auto Label." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 11 (2022): 13161–63. http://dx.doi.org/10.1609/aaai.v36i11.21714.

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We demonstrate an AI assisted data labeling system which applies unsupervised and semi-supervised machine learning to facilitate accurate and efficient labeling of large data sets. Our system (1) applies representative data sampling and active learning in order to seed and maintain a semi-supervised learner that assists the human labeler (2) provides visual labeling assistance and optimizes labeling mechanics using predicted labels (3) seamlessly updates and learns from ongoing human labeling activity (4) captures and presents metrics that indicate the quality of labeling assistance, and (5) p

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Joseph, Genimon Vadakkemulanjanal, Athira P, Anit Thomas M, Dawn Jose, Therese V Roy, and Malavika Prasad Prasad. "Impact of Digital Literacy, Use of AI tools and Peer Collaboration on AI Assisted Learning- Perceptions of the University students." Digital Education Review, no. 45 (July 1, 2024): 43–49. http://dx.doi.org/10.1344/der.2024.45.43-49.

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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 studen

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Asamoah, Paul Boadu, and Ibrahim Adeiza Ahmed. "AI-Assisted Forecasting of Energy Prices." International Journal of Research and Scientific Innovation XI, no. IX (2024): 626–49. http://dx.doi.org/10.51244/ijrsi.2024.1109057.

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This study explores the application of artificial intelligence (AI) in forecasting energy prices by developing advanced models that integrate diverse data sources, including market data, weather patterns, and geopolitical events. Traditional forecasting methods, such as ARIMA and GARCH, have shown limitations in handling energy markets’ complex, non-linear relationships. In contrast, AI models demonstrate superior accuracy and adaptability, particularly deep learning and ensemble methods. The research findings indicate that AI-assisted models outperform traditional approaches, providing more r

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Choudhary, Muqaddas Waris, Madiha Ashraf, Syeda Maryam Fatima, and Muhammad Zahid. "Impact of AI-Assisted Flipped Classroom on Speaking Skills of Pakistani ESL Learners." ACADEMIA International Journal for Social Sciences 4, no. 2 (2025): 593–601. https://doi.org/10.63056/acad.004.02.0200.

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The current study investigates the effectiveness of an Artificial Intelligence (AI)-assisted flipped classroom model on the speaking skills of Pakistani L2 learners. In a flipped classroom, traditional teaching methods are inverted where learners first encounter new content independently through technology and then engage in interactive, collaborative learning activities during face-to-face sessions. AI tools offer the potential to enhance speaking skills in an ESL context by providing immediate feedback, personalized practice, and engaging learning experiences. This research explores how the

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Nayak, Ashu, Dr D. Kalidoss, and Rajender Sharma. "AI-Assisted Predictive Maintenance of Renewable Energy Infrastructure." International Journal of Environmental Sciences 11, no. 6s (2025): 1–7. https://doi.org/10.64252/qqdv1613.

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This study examines the role of Artificial Intelligence (AI) in Predictive Maintenance (PdM) for Renewable Energy (RE) infrastructure, with a focus on wind turbines and solar Photovoltaic (PV) systems. The aim is to illustrate how AI-based algorithms can predict failures to maximize operational expenditure by reducing unscheduled equipment downtime. The approach taken focuses on remotely supervised and controlled SCADA systems, along with sensor data, implementing machine learning (ML) and deep learning (DL) for anomaly detection and remaining useful life (RUL) prediction. Findings demonstrate

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Supadi Supadi. "Implementation of Data-Based Management to Enhance AI-Assisted Learning Effectiveness for Senior High School Students in Jakarta." Jurnal Ilmiah Rumpun Ilmu Pendidikan 2, no. 1 (2025): 01–30. https://doi.org/10.63760/jirip.v2i1.26.

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This study aims to analyze the implementation of data-based management in improving the effectiveness of education in AI-assisted learning at the high school level. The analysis units in this study are data management systems and AI learning strategies in schools. The research design used is a qualitative study with a descriptive approach. The main data sources consist of principals, teachers, and high school students involved in the use of AI in learning. Data collection techniques include in-depth interviews, observations, and document analysis. The data is analyzed using thematic analysis t

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Yang, Ting. "Impact of Artificial Intelligence Software on English Learning Motivation and Achievement." SHS Web of Conferences 193 (2024): 02011. http://dx.doi.org/10.1051/shsconf/202419302011.

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The influence of Artificial Intelligence (AI) tool usage on students' learning ability has received much attention from the society. The present study reviews prior studies examining the effect of AI on learning motivation in English as a Foreign Language (EFL) classrooms. Previous studies examinethe effects of AI on EFL students' motivation using a mixed-methods approach. The findings reveal a significant correlation between AI usage and student motivation. Other studies focuses on AI-assisted language learning's impact on English learning outcomes, self-regulated learning as well as L2 motiv

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