Aug 2026· Australian Journal of Business and Social Science· Vol 1, pp. 53-65· 0 citations· 23 references
TL;DR
This article presents a case study of AI-powered intelligent transformation in teaching, drawing upon practical implementations in both science and humanities education, and illustrates how generative AI tools can be strategically deployed to enhance diagnostic assessment, personalize learning, create interactive content, and facilitate conver sational inquiry.
Abstract
nature of certain concepts that elude conventional pedagogical approaches. As noted in a systematic review of educational transformation with AI, research in this domain can be organized into four categories: AI as a transformative tool in education, personalization of learning, ethical challenges and digita l divides, and the impact of AI. The personalization dimension is particularly significant. AI systems can analyze individual learner data to identify knowledge gaps, generate targeted interventions, and adapt instructional content to match learners' readiness levels. AI can scale personalized learning (Katiyar et al., 2024), all while gaining students' trust, representing a step toward precision education, meaning the tailoring of instruction to each learn er's specific needs and context . This capacity for precision education addresses a fundamental limitation of Abstract The integration of artificial intelligence (AI) into educational practice represents one of the most significant pedagogical shifts of the twenty -first century, yet the translation of AI capabilities into actionable classroom strategies remains inadequatel y documented. This article presents a case study of AI-powered intelligent transformation in teaching, drawing upon practical implementations in both science and humanities education. Through detailed examination of two instructional cases -a second- grade science lesson on magnets and a fifth-grade humanities lesson on Li Shizhen-the study illustrates how generative AI tools can be strategically deployed to enhance diagnostic assessment, personalize learning, create interactive content, and facilitate conver sational inquiry. The findings demonstrate that AI integration need not be comprehensive to be transformative; rather, targeted deployment at specific instructional junctures-pre-class diagnostics, misconception remediation, and interactive exploration- can yield significant pedagogical benefits while respecting teachers' limited preparation time. The article contributes to the growing body of literature on AI-enhanced pedagogy by providing concrete, replicable examples of AI integration across disciplinary contexts, and by articulating a framework for thoughtful, balanced AI adoption that preserves teacher agency while leveraging AI's unique capabilities for personalization, scalability, and interactive engagement. The study also critically examines the limitations and ethical considerations surrounding AI integration in education, including concerns about content quality, algorithmic bias, data privacy, and the digital divide, thereby offering a balanced perspective on the promises and perils of AI in teaching.
The findings show that AI is increasingly seen as a transformative academic tool, especially for research, language learning, writing support and problem‐solving, and despite widespread AI adoption, the study identifies significant gaps in institutional infrastructure and the absence of systematic training programmes.
M. Doğan, B. Kashkhynbay, Zhaniyat Baltabayeva· European Journal of Educatio...· 0 citations
This study addressed the urgent need to develop a new epistemological model to understand the philosophy of education in light of the profound transformations imposed by the artificial intelligence (AI) revolution. It explored how AI technologies have reshaped educational environments, shifting from traditional models focused on content and lecturers to interactive learning systems that rely on big data and provide personalized learning paths. Using an exploratory qualitative research approach, the study examined the readiness of the Jordanian education system to accommodate these transformations and identified the most prominent philosophical and ethical challenges hindering the integration of AI into education by applying it to a sample of 80 educational experts. The results revealed significant gaps between prevailing educational philosophies and the requirements of future skills such as innovation, critical thinking, and lifelong learning. The study presented a balanced epistemological model that promotes the integration of technology and human values, ensures the ethical use of AI, and achieves equity in educational opportunities. This model also calls for reformulation of educational policies to enable future generations to meet the challenges of the digital economy with confidence and competence while preserving their cultural and ethical identity.
A. Jarrar· International Journal of Exc...· 0 citations
This qualitative study examines the perspectives of in-service teachers regarding the integration of Artificial Intelligence (AI) into educational settings. A purposive sampling framework combining criterion and snowball sampling strategies was employed, semi-structured interviews were conducted with 23 in-service teachers. Data were analyzed through content analysis. The analysis revealed three themes: teachers’ current digital practices, AI acceptance and integration of AI. The findings showed that teachers currently use digital technologies for various pedagogical purposes and have also begun using AI technologies in educational settings. Also, teachers perceived AI as useful because of easier access to information, time efficiency, decision-making support, personalized feedback, and professional development. However, they also expressed pedagogical and ethical concerns regarding student overreliance, academic dishonesty, the potential misuse of AI, data security, and the digital divide. The results indicate that, given the multifaceted nature of AI technologies successful AI integration requires specific teacher competencies, particularly critical AI literacy and ethical awareness competencies. Findings also suggest that successful integration requires practical, subject-specific training for both in-service and pre-service teachers, training for students, family engagement, and financial support. This study provides insights into how teachers use AI technologies, their perceptions of required competencies, the challenges and concerns they perceive. Limitations and suggestions for future research are also discussed.
Feray Uğur Erdoğmuş· Participatory Educational Re...· 0 citations
In the digital era, where the world of education is rapidly transforming with the advent of Artificial Intelligence (AI) and robotics, a new perspective on teacher-led innovation is required. The study focuses on a key mechanistic question of how AI integrated environments predict pedagogical innovations, complementing existing research that tends to center on the student. The research draws on the Sociotechnical Systems (STS) Theory and examines the effects of four key 21st century skills namely Problem Solving (PS), Critical Thinking (CT), Communication (COM) and Teamwork (TW). A purposive sample of size N = 150 teachers in Lahore, Pakistan were sampled to obtain the necessary data. The direct relationships hypothesized were tested using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results suggest that individualized learning and administrative efficiency are the most beneficial effects of the use of AI-based tools, with the greatest predictor being the use of Teamwork. These results imply that AI is a collaborative stimulus, which assists networked intelligence among educators as opposed to automating the tasks. This paper proposes evidence-based recommendations for policy makers to go beyond automation and shift to a sociotechnical approach to integrating AI to create human-centered innovation. Finally, the article has been presented in an impartial manner, as it has covered the ethical impact, as well as the drawbacks of the digital-first classrooms methodologies.
Arooj Zahra, Nadia Saleem, S. Yasin et al.· Aposta: Revista de Ciencias...· 0 citations
A systematic review of peer-reviewed studies published between 2015 and 2024 concludes that while tools such as generative artificial intelligence, intelligent tutoring systems, virtual and augmented reality, and predictive analytics are increasingly present, their adoption is concentrated in specific areas, particularly problem-solving, simulation, and assessment.
Firas Almasri· International journal of tec...· 0 citations
Different disciplinary differences emerged: students in language-focused disciplines exhibited cautious attitudes regarding AI’s influence on authorship and creativity, whereas those in technical sciences generally regarded AI as a neutral assistant with minimal concern for ethical or cognitive implications.
A. Kereibayeva, Fariza Abdraimova, T. Toktarova et al.· AI@DTESI· 0 citations
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