Oak National Academy’s Aila, Education AI Companies and the Anthropomorphising of AI

In recent years, the integration of Artificial Intelligence (AI) in education has shown transformative potential across various educational levels, from primary school to university. This paper examines the multifaceted applications of AI in education, highlighting its role in enhancing teaching and learning experiences, as well as personalizing educational content. The aim of this paper is to shed light on the implementation of various AI tools in primary, secondary and tertiary education through practical examples gained through action research. At the primary school level, AI tools are employed to create engaging and adaptive learning environments, catering to the diverse needs and learning paces of young students. In secondary education, AI facilitates the development of critical thinking and problem-solving skills through interactive and personalized learning platforms. At the university level, AI is revolutionizing research methodologies, providing sophisticated data analysis tools, and supporting the creation of innovative learning management systems. Additionally, the paper highlights the challenges and ethical considerations associated with AI integration in education, such as data privacy, algorithmic bias, and especially the need for teacher training in AI literacy. Conclusively, we provide an overview of the benefits and limitations of AI in education, offering insights into future trends and implications for educational stakeholders.

The integration of Artificial Intelligence (AI) in higher education has gained significant momentum, particularly in enhancing teaching methodologies and student learning outcomes. In higher education, AI enhances personalized learning, boosts student motivation, and improves academic achievement. In the context of Arts and Science colleges in Erode, there is a growing interest in adopting AI tools such as chatbots, virtual labs, and personalized learning platforms. However, the actual impact of these technologies on students’ academic performance and learning experiences remains underexplored. The integration of Artificial Intelligence in education faces several challenges in Arts and Science colleges in Erode. One major issue is the lack of awareness among students about the available AI tools and their potential academic benefits. Additionally, unequal access to AI resources across colleges hampers consistent usage. Students also exhibit varying levels of engagement with AI tools, which may affect their academic outcomes. Hence, the researchers developed a study for exploring the role of artificial intelligence in enhancing educational outcomes of college students in Erode, Tamilnadu. A descriptive research design is employed to align with the study’s objectives. Both primary and secondary data sources are used to gather information. The study targets students from Arts and Science colleges in Erode, Tamil Nadu, with a sample size of 185 selected through random sampling. The necessary data is collected using a structured questionnaire that covers students’ demographic profiles, AI tool usage, and their perceptions of AI’s role in enhancing educational outcomes, assessed through a 5-point Likert scale. The data are organized using MS Excel and analyzed using statistical techniques such as percentage analysis, mean scores, standard deviation, and ANOVA via SPSS 26.0 software. Additionally, null hypotheses are formulated to examine significant differences in the perceived role of AI across selected independent variables. This study mentioned from analysis that maximum level of experience with AI’s role in enhancing educational outcomes is perceived by the students belong to male, Science stream, studying second-year, using Virtual Labs (AI tool) and using AI tools frequently.

The integration of Artificial Intelligence (AI) in education has rapidly transformed sectors including English as a Second Language (ESL) learning. However, there remains a significant gap in adapting these global AI innovations to local educational contexts, particularly in ESL classrooms. This paper proposes a conceptual framework linking global AI advancements with local ESL practices by focusing on the development of adaptive learning tools to meet the diverse needs of ESL learners. The study synthesizes existing literature on AI applications in language learning and adaptive learning models, addressing both global trends and local educational challenges. Through this literature review, the paper explores AI’s potential to personalize learning, enhance language acquisition, and overcome barriers like the digital divide. Expected outcomes suggest that while AI shows promise in fostering engagement and personalized learning, its effective implementation in local ESL classrooms requires attention to contextual factors such as internet access, teacher involvement, and cultural relevance. The proposed framework recommends a hybrid approach that integrates AI tools with traditional teaching practices, ensuring an effective, contextually relevant learning environment. In conclusion, the paper advocates for collaboration among AI developers, educators, and policymakers to adapt AI tools to local needs, offering a direction for future research and implementation of adaptive language learning tools in ESL education.

The integration of Artificial Intelligence (AI) tools in higher education has the potential to revolutionize teaching and learning. However, there is a lack of pedagogical integration when using these tools, which hinders their full potential. This paper provides an overview of the research on AI applications in higher education and highlights the challenges of using AI in the classroom. The study will also look at the ethical issues that occur when using artificial intelligence in higher education, as well as the benefits of this technology and how it impacts student- teacher interaction in online learning environments. The impact of AI on student-teacher interaction in online learning environments is also observed. AI systems have the potential to affect the way student-teacher interaction occurs, but there can be barriers to the effective use of AI systems due to students’ unrealistic expectations and misunderstandings about AI. More research and exploration are needed to fully understand the potential and consequences of AI in educational settings. In conclusion, it is crucial to carefully weigh the benefits and challenges of incorporating AI tools into the education system. It is important to note that AI should be used as a tool to enhance education and support teachers, rather than replacing human educators. Further research, teacher training, and fostering AI literacy are necessary to fully harness the potential of AI in education and create meaningful learning experiences for students.

The use of corpora and artificial intelligence (AI) tools into education marks a significant evolution in teaching and assessment methodologies. Historically, Arabic corpora have been pivotal in linguistic research, expanding notably through scholarly publications and symposia since the late twentieth century. However, the scarcity of specialized resources such as parallel corpora and the prevalence of web-generated Arabic corpora have restricted thorough empirical studies of authentic Arabic texts and their application in educational settings. Additionally, while the integration of AI into Arabic pedagogy has increased, its application in Arabic/English legal translation remains scarce and underdeveloped. To address this gap, this paper aims to showcase the use of corpus tools and AI to advance research-driven and blended-learning approaches in Arabic/English legal translation. It uses advanced corpus tools and diverse corpora (large datasets) available on Sketch Engine, including the Leeds Monolingual and Parallel Corpora of Arabic and English Countries’ Constitutions and the UN Parallel Corpora. These resources, integral to research and instruction, have supported the MA translation programmes at the University of Leeds for five years. Moreover, ChatGPT 4 is applied as an interactive tool in designing teaching activities around legal documents such as contracts and agreements. This method not only mitigates the lack of specialized corpora in this genre but also explores new possibilities for using AI in education. The paper utilises a descriptive methodology to showcase how monolingual and parallel corpora can enhance interactive legal text learning, highlighting the educational and scientific innovation. Theoretical frameworks like Vinay and Darbelnet’s (1995) contrastive linguistic analysis and Vermeer’s Skopos theory (1978) provide foundational insights for designing and interpreting pedagogical activities involving corpus-based tools. Although the study illustrates the tools’ potential to enrich the learning environment and meet diverse educational demands, it acknowledges AI's limitations in ensuring accuracy and stylistic precision in complex legal texts. The scope of this study does not include an exhaustive evaluation of pedagogical impacts or a comparison with traditional methods, suggesting the need for further research to validate these findings and expand upon them.

This study explores teachers’ readiness and perceptions regarding the integration of artificial intelligence (AI) tools in education. The study was conducted among 3,848 Estonian teachers. Given AI’s transformative potential in enhancing teaching effectiveness, automating administrative tasks, and supporting personalized learning, it is critical to assess whether teachers are equipped to effectively utilize these technologies. Utilizing a comprehensive framework informed by human-centered approaches, this research investigates teachers’ familiarity, attitudes, perceived usefulness, and readiness to implement AI-driven tools in educational settings. A survey conducted among teachers reveals a balanced perspective characterized by interest, openness, and awareness of both opportunities and potential risks associated with AI. Findings indicate significant predictive relationships between perceived usefulness and readiness, as well as attitudes toward AI tools and actual adoption intentions. Teachers’ confidence and perceived relevance of AI in educational contexts emerge as key factors facilitating their willingness to engage with AI technology. Conversely, factors such as AI anxiety and limited training opportunities are identified as barriers to effective implementation. The study underscores the need for targeted professional development programs, ethical guidelines, and policy support to enhance teachers’ readiness and facilitate the responsible integration of AI into educational practices.

The integration of Artificial Intelligence (AI) tools in education has the potential to transform learning experiences. However, the extent to which students find these AI tools useful may depend on the level of their AI Literacy (AIL). This study investigates the association between AI literacy level and the perceived usefulness of AI in the academe. A survey was conducted among 172 students from five colleges at Rizal Technological University – Boni Campus during the second semester of the academic year 2023-2024. The researchers collected data on their demographic profile, AI literacy level (AILL), and perceived usefulness (PU) of AI tools in the academe, which is then analyzed using statistical methods to identify significant differences and associations. The results indicated a positive association between AI literacy levels and students’ perceptions of AI usefulness in the academe. Additionally, a significant difference in AILL, particularly in AI ethics, was observed when respondents were grouped by year level. These findings suggest that promoting AI literacy can enhance students’ engagement with AI tools in educational contexts. The study offers valuable insights for educators and policymakers in designing AI-related curricula and resources. However, the researchers acknowledge that the sample size may have affected the normality of the data. Future research is recommended to develop a more comprehensive AI literacy questionnaire to assess students’ readiness for AI use and to include a larger sample size, potentially incorporating other universities in the Philippines.

The integration of artificial intelligence (AI) tools in the educational sector has significantly transformed the learning experiences of students. The experiences of students using AI tools for educational development are increasingly significant as these technologies reshape learning environments. However, there were challenges identified in potential over-reliance on technology, and the ethical implications of using AI tools are significant issues that educators must address. The aim of this study is to examine the experiences of students in the use of AI tools for educational development. This research leverage on qualitative methods as the adopted methodology using design science research which involves interviews of final year students for data collection at a rural university in Eastern cape. The students are comprising of final year students in selected rural university for data collection through focus group discussions. Therefore, the data collected is analyzed using thematic NVivo Software to analyze the findings of the results. The results finding consist of accessibility and inclusivity, personalized learning, and students’ engagement. Furthermore, leveraging on the experiences of students with AI tools in education highlight a transformative shift towards personalized and engaging learning environments. In conclusion, AI continues to evolve within educational settings, its successful integration will depend on balancing technological advancements with ethical considerations and traditional teaching values.

Recently, there has been an increase in studies on the integration of artificial intelligence in educational service delivery. Many scholars believe that the role of teachers will change. They need to be prepared for AI-powered education. For this investigation, a descriptive survey research design was adopted. The principals and teachers in the 274 public senior secondary schools in Rivers State formed the population. Using the stratified random sampling technique, a sample of 407 respondents (69 principals and 338 teachers) was drawn. Two research questions and two hypotheses guided the study. Data was collected with the aid of a questionnaire tagged, “Integration of Artificial Intelligence in Education and Teachers Preparation Strategies Questionnaire”. The instrument, which has 16 items, was well validated by research experts, and using Cronbach's Alpha, the calculated reliability coefficient was 0.83, indicating that it was reliable. Mean, mean set, and standard deviation were used to analyse the research questions, while the z-test was used to test the hypotheses. Results of the study showed that AI can be used to improve learning outcomes by reducing teachers’ workload, providing personalized education to learners, and enhancing accessibility of education. On the other hand, teachers appear not to be prepared for AI-enabled classrooms. They need Artificial Intelligence (AI) literacy and professional development. From the results of the study, a conclusion was drawn, and the researchers recommended, among others; that Artificial Intelligence (AI) awareness and competency should be increased among teachers through teachers' training courses and professional development programs.

The integration of artificial intelligence (AI) tools in education has emerged as a significant paradigm shift. As we navigate this new landscape, it is essential to understand the adoption and use of these technologies in educational settings. Some valuable insights into AI's global trends and potential in education are available from OECD-Education International (2023), highlighting a need to understand privacy concerns and equitable access. Guidelines and advice have also been made available for New Zealand schools from the Ministry of Education (2024). However, there currently needs to be more comprehensive studies of AI in education that focus on the specific context of Aotearoa, New Zealand. This report seeks to meet that need. Educators from throughout Aotearoa were invited to participate in a survey conducted between August and November 2023. The survey aimed to assess the landscape of AI implementation in schools, exploring practices, challenges, and potential positive outcomes associated with AI tools in education. This research seeks to inform policymakers, educators, and stakeholders to facilitate informed decision-making to advance educational practices. Through this research, we hope to contribute to the ongoing dialogue on AI in education and its implications for teaching and learning in Aotearoa.

The integration of Artificial Intelligence (AI) into mental health care within educational settings has the potential to transform how institutions address student well-being. As AI-powered mental health tools scale across diverse educational landscapes, critical challenges related to scalability, localization, data privacy, and cultural adaptation emerge. This chapter explores the development and deployment of AI mental health tools in underfunded and diverse educational contexts, with a focus on ensuring equity in access and the importance of culturally sensitive solutions. The potential of AI to address the growing mental health crisis among students is tempered by concerns regarding ethical guidelines, bias, and the responsible handling of sensitive data. In this context, the collaboration between AI developers, educational institutions, and local mental health experts is emphasized as a key strategy to overcome linguistic and socioeconomic barriers. Ethical and regulatory frameworks must be established to protect student privacy, promote fairness, and ensure that AI tools complement human intervention rather than replace it. By addressing these challenges, AI can become a powerful tool for improving mental health outcomes and enhancing support systems for students globally. This chapter provides an in-depth examination of these critical considerations, offering strategies and recommendations for effective and ethical AI tool implementation in educational environments.

The integration of artificial intelligence (AI) in higher education represents a transformative shift in the way teaching and learning are approached, offering unprecedented opportunities to enhance educational outcomes. One significant issue is the potential for bias in AI algorithms, which can perpetuate existing inequalities if not carefully managed. The objective of this study is to explore and evaluate the integration of AI in higher education to enhance teaching and learning processes. The study aims to identify the most effective AI tools and strategies for improving educational outcomes, assess their impact on student engagement and achievement, and provide actionable recommendations for educators and institutions. To effectively assess the integration of AI in higher education, a multifaceted data collection approach is essential. To ensure the successful integration of AI tools in higher education, a structured implementation plan is crucial. Enhancing teaching and learning involves a comprehensive approach that includes meticulous data collection, rigorous data analysis, strategic implementation and continuous improvement. The implementation phase requires thoughtful planning and execution, with a focus on refining AI systems based on feedback and performance metrics to ensure they effectively support educational goals. The findings show that AI integration in education has improved average grades to 88%, increased retention rates to 85%, and achieved 92% in content customisation and implementation using Python software. The future scope for integrating AI in higher education includes developing advanced AI tools that offer personalized and adaptive learning experiences, enhancing predictive analytics for student performance and retention, and fostering innovative pedagogical approaches through AI‐driven insights.

Purpose This study examines how secondary school administrators can lead ethical artificial intelligence (AI) integration within environments demanding technological innovation and educational value preservation. Design/methodology/approach The study conducted a scoping review of literature (2018–2025) to analyze administrative functions across four established leadership dimensions: instructional, managerial, strategic, and relational. Sources were obtained from academic databases and grey literature, with 21 sources selected based on relevance to secondary education and administrative practice. Analysis is grounded in foundational leadership scholarship while examining contemporary AI integration challenges. Findings The analysis reveals a misalignment between AI's most frequent use (relational leadership functions) and where it may be most appropriately suited (managerial and strategic functions). AI integration creates distinct opportunities and risks across each leadership dimension, with equity concerns emerging consistently. Communication represents the primary AI use, despite being the most fundamentally human aspect of educational leadership. Cognitive offloading risks emerge when administrators delegate critical thinking tasks to AI systems, potentially attenuating leadership capabilities essential for educational effectiveness. Research limitations/implications This study relies on secondary data collection and English-language sources, creating Western-centric bias and limiting generalizability beyond North American contexts. The corpus of 21 sources reflects the nascent research state in this emerging field. The rapid evolution of AI capabilities means current findings may prove transitional as technology advances. Future empirical research should examine long-term cognitive effects of AI reliance on administrators, stakeholder trust implications when AI-mediated communications are detected, differential equity impacts across diverse school communities, cross-cultural implementation patterns, and effectiveness of hybrid governance approaches for AI integration in educational leadership. Practical implications Findings support implementing hybrid governance models that combine regulatory oversight with participatory decision-making between administrators and stakeholders. Professional development programs must balance AI literacy training with preserving human capabilities essential for authentic educational leadership. Administrator preparation programs require redesign to address cognitive offloading risks while maintaining relationship-building and cultural competence development. Educational leaders should prioritize AI applications in managerial and strategic functions while preserving human judgment in relational leadership contexts. Policy frameworks must address equity concerns and provide guidance for schools serving vulnerable populations who currently receive less AI implementation support. Social implications AI implementation without critical examination risks amplifying existing educational inequities, particularly affecting Indigenous, newcomer, and racialized communities. Democratic participation in AI boundary-setting becomes essential for maintaining institutional trust and stakeholder engagement. The misalignment between AI deployment and appropriate applications threatens the relational foundations of effective educational leadership. Originality/value The study provides the first systematic examination of AI integration across established educational leadership dimensions in secondary school contexts, addressing a critical research gap given that nearly 60% of K-12 principals use AI tools while fewer than 10% of schools have established AI policies.

The integration of Artificial Intelligence (AI) in non-formal, informal and formal education is an emerging area with great potential to transform the world. However, the capacity of educators, youth workers and teachers to capitalise on this potential remains limited due to a lack of well-defined frameworks for AI integration in practices. The scope of this study is to explore the needs, challenges, and perspectives of youth work professionals regarding AI integration.The research methodology employed mixt research methods. The literature review was followed by four semi-structured focus groups involving 72 youth workers and professionals with diverse backgrounds, nationalities and experience levels. A common guideline was used to ensure consistency, including facilitator instructions, discussion prompts, and reporting templates. The data collected during the focus groups were analysed using a Computer-Assisted Qualitative Data Analysis Software (CAQDAS), ATLAS.ti software dedicated to qualitative research. The authors conducted qualitative analysis, through coding, identification of main categories, thematic map for visualization of results, and interpretation of findings to uncover patterns and deeper insights. The results revealed a generally positive attitude toward AI tools and an awareness of their potential benefits in youth work, particularly in content creation. However, participants reported significant challenges regarding the use of AI for administrative tasks efficiency, for personalised learning, ethical concerns, and difficulty in interpretation of data. Cross-country similarities emerged, suggesting a shared need for capacity building and continuous training, while differences highlighted the influence of national contexts and digital infrastructure.This study provides a foundational understanding of the competence needs of youth workers in relation to AI adoption. The findings are relevant for course designers wishing to offer targeted training for youth workers. Future research is also needed into policy-level support mechanisms that can enhance AI literacy and ethical integration across the sector.

Aim/Purpose: Evaluate teachers’ perceptions, strategies, and challenges in integrating artificial intelligence (AI) into K-12 education and identify patterns and trends in the data from the reviewed studies. Background: This systematic review examines a decade of innovation to explore the transformative impact of AI on education (2014–2024). Adhering to PRISMA 2020 guidelines, the study uncovers key trends, challenges, and breakthroughs in AI-driven teaching and learning, offering a comprehensive perspective on how AI reshapes educational practices and methodologies. Methodology: The study employs a systematic review to analyze the implementation of AI techniques and tools in primary education, following the PRISMA 2020 guidelines to ensure the reliability and effectiveness of the findings. To achieve this, an extensive search was conducted in academic databases such as Web of Science, Scopus, and ERIC, focusing on empirical studies and peer-reviewed articles published between 2014 and 2024. Only accessible, peer-reviewed articles classified under Education and Educational Research and published in English or Spanish were selected. The search strategy was structured into five categories aligned with the research questions to identify relevant studies accurately. The selection process was carried out in three phases – Identification, Screening, and Inclusion – applying predefined criteria to guarantee the quality and relevance of the selected studies. Of an initial total of 514,919 articles, 488,940 were excluded for not meeting the inclusion criteria. After removing duplicates and evaluating titles, abstracts, and full texts, a final set of 28 studies was included. Contribution: The study explores the integration of AI in primary education, revealing both teachers’ enthusiasm and the challenges they face. While AI is perceived as a tool to enhance critical thinking, problem-solving, and student engagement, its implementation is limited by insufficient training, resources, and institutional support. Despite these obstacles, teachers show confidence in designing AI-integrated curricula, though this is weakened by inadequate infrastructure and technical support, highlighting the need for continuous professional development. The study also stresses the importance of establishing a competency framework for AI literacy and adopting a systemic approach to AI education. Additionally, ensuring safe learning environments by addressing data privacy and AI biases remains a key challenge. Overcoming these issues is essential for the ethical and effective integration of AI, maximizing its benefits while safeguarding student equity and security. Findings: - Educators see the potential of AI to personalize learning. - Barriers are lack of training and resources for teachers. - Importance of continuous training in digital skills. - Need for policies that promote AI literacy. - Collaboration with experts to optimize AI in the classroom. Recommendations for Practitioners: Teachers are encouraged to collaborate in using AI tools to enhance educational outcomes, supported by continuous professional development programs, clear policies that safeguard privacy and promote equality, and a framework that preserves human autonomy in integrating AI technologies. Recommendation for Researchers: The lack of empirical research on AI interventions in education limits understanding of its true impact, highlighting the need for future studies to fill this gap and optimize its application for greater educational benefits. Impact on Society: The integration of AI in K-12 education is not just an opportunity; it is a necessity to prepare future generations for an increasingly digital world. While AI has the potential to revolutionize learning by fostering critical thinking, personalization, and engagement, its impact depends on how effectively it is implemented. To ensure its benefits, it is essential to empower educators and students with AI literacy, address issues like bias and data privacy, and establish robust legal frameworks for fair and transparent use. Without proactive policies, AI could widen educational inequalities instead of reducing them. A responsible, human-centered approach is needed to create an inclusive, ethical, and effective AI-powered education system. Future Research: The article highlights the urgency of future empirical research to better understand the real impact of AI in education, as the lack of intervention studies limits its optimal application. Analyzing how AI influences learning outcomes, teaching dynamics, equity, and accessibility is essential, along with investigating the pedagogical competencies and technological conditions that affect its adoption. To this end, expanding the scope of studies is recommended by incorporating multicultural and multilingual perspectives, exploring AI applications across various disciplines and educational levels, and promoting interdisciplinary approaches that address ethical, social, and pedagogical dimensions.