Abstract
Artificial Intelligence (AI) is revolutionizing the potential of education in its initiatives in personalized learning modules, curriculum designs, evaluation methods, teacher assistance and above all educational management. The rapid deployment of AI-driven technologies demands a proactive approach to education policies, ensuring responsible, fair, and efficient use of AI. Extensive student data is processed by AI systems, enabling adaptive learning models that cater to their learning needs, which in turn optimizes engagement and academic performance. That said, this transition also raises issues in terms of data privacy, cybersecurity, algorithmic bias and the digital divide. This article explores the evolution of AI in education and its impact on learning policies, governance frameworks, accessibility and ethical issues. It examines how AI is influencing the decision-making process in the policymaking of education and relates to the issue of transparency, accountability and equity. In addition, the research stresses mainstream policy recommendations aimed at fostering responsible AI integration, making sure that the students, educators, and educational institutions can benefit from the advantages of AI, without facing its associated issues. By implementing well-defined education policies, governments and institutions can create a framework that promotes innovation around AI, balancing the need for innovation with the need to protect the integrity and inclusiveness of the education system.
Keywords
Artificial Intelligence, Education Policy, Personalized Learning, AI in Education, Cybersecurity, Ethical AI, Adaptive Learning, Data Privacy, Teacher Support
1. Introduction
Artificial Intelligence (AI) plays a transformative role in reshaping modern education. The integration of AI-driven tools in classrooms, learning management systems, and administrative processes has opened new possibilities for enhancing educational quality, accessibility, and efficiency. AI applications such as personalized learning platforms, automated grading, virtual tutors, and predictive analytics are revolutionizing the way students learn, and educators teach.
| [1] | Aoun, J. E. (2017). Robot-proof: Higher education in the age of artificial intelligence. MIT Press. |
[1]
As AI continues to evolve, it presents both opportunities and challenges for education policymakers. While AI enhances the personalization of learning, streamlines administrative tasks, and offers data-driven insights, it also raises concerns regarding data privacy, algorithmic bias, and the digital divide. It is crucial to establish policies that guide the ethical, fair, and effective use of AI in education to ensure that its benefits are maximized while minimizing potential risks.
This article explores the role of AI in shaping future education policies, focusing on key areas such as personalized learning, assessment methods, teacher support, accessibility, governance, cybersecurity, and ethical considerations. It also provides recommendations for policymakers to develop AI-driven educational frameworks that promote equity, transparency, and sustainability.
2. Evolution of AI in Education
AI has gradually transformed education through adaptive learning platforms, virtual assistants, and automated grading systems. From early expert systems to modern machine learning models, AI is now capable of analyzing student performance, customizing curricula, and predicting learning outcomes
| [5] | Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign. |
| [6] | Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. Pearson. |
[5, 6]
. As AI adoption grows, policies must adapt to ensure its responsible use in education.
Table 1. Evolution of AI in Education.
Era | Key AI Developments in Education | Impact on Education |
1980s- 1990s | Expert Systems & Rule-Based AI | Basic tutoring programs, automated problem-solving tools |
2000s | Early Machine Learning & Adaptive Learning | Personalized learning paths, intelligent tutoring systems |
2010s | Deep Learning & Natural Language Processing | AI-driven chatbots, automated grading, speech recognition |
2020s-Present | Advanced AI, Big Data & Predictive Analytics | Real-time student performance tracking, AI-generated curricula, AI-powered assessments |
3. AI and Personalized Learning Policies
AI has transformed education by facilitating personalized learning, as AI-driven systems evaluate student data to customize instruction based on unique learning styles, speeds, and skill levels
| [7] | Selwyn, N. (2020). Should robots replace teachers? AI and the future of education. Polity Press. |
[7]
. Nonetheless, proper educational policies need to be established to guarantee the responsible and fair utilization of AI in educational settings. Adaptive learning strategies must guarantee that AI-enabled systems modify content and speed according to student advancement, facilitating more adaptable and effective learning. Policies focused on competency-based education should encourage learning pathways that allow students to progress after mastering concepts instead of following a strict curriculum. Moreover, equity and inclusion policies are crucial to ensure that every student, including individuals with disabilities or from marginalized communities, can access AI-driven educational resources, making certain that no one gets overlooked. Additionally, data privacy policies should create explicit rules regarding data collection, usage, and protection to secure student information and uphold trust in AI applications
| [8] | West, D. M. (2018). The future of work: Robots, AI, and automation. Brookings Institution Press. |
[8]
. Ultimately, policies regarding teacher-AI collaboration ought to promote the incorporation of AI tools in educational settings, while safeguarding human supervision, guaranteeing that AI acts as a supplement instead of a substitute for educators. By tackling these essential policy areas, education systems can leverage the advantages of AI while guaranteeing fairness, security, and efficiency in personalized learning.
4. AI in Curriculum Development and Assessment
AI is essential in curriculum development by examining educational trends, pinpointing deficiencies in learning resources, and suggesting required modifications to improve learning experiences. Furthermore, AI-powered assessment tools enhance the evaluation process by offering immediate feedback and automating grading, greatly lessening the burden on teachers and enabling them to concentrate more on student interaction and teaching
| [10] | Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education. International Journal of Educational Technology in Higher Education, 16(39). https://doi.org/10.1186/s41239-019-0171-0 |
[10]
. Nonetheless, the integration of AI in evaluation necessitates thoughtful policy deliberations to guarantee its efficacy and equity. The standardization of AI-based evaluations is crucial for ensuring consistency and precision among different educational organizations. Moreover, guaranteeing fairness and transparency in AI-generated assessments is essential to avoid biases that may harm specific groups of students
| [7] | Selwyn, N. (2020). Should robots replace teachers? AI and the future of education. Polity Press. |
[7]
. Additionally, policies should strike a balance between AI and human supervision in grading processes to uphold the reliability and ethical integrity of evaluations, guaranteeing that AI functions as an aid rather than the only decision-maker.
In addition to assessments, AI provides significant assistance to educators by automating administrative duties, delivering real-time insights on student performance, and presenting AI-enhanced professional development options. Tools enhanced by AI can help teachers tailor instruction, recognize students requiring extra assistance, and simplify classroom management. Future policies ought to emphasize the incorporation of AI-driven teaching assistants to improve teaching effectiveness while preserving the significance of educators
| [8] | West, D. M. (2018). The future of work: Robots, AI, and automation. Brookings Institution Press. |
[8]
. Moreover, it is essential to train educators in effectively utilizing AI tools to fully harness the advantages of AI in the classroom and guarantee that teachers can confidently employ technology to enhance student results. A further important point is tackling worries about AI taking the place of human instructors by highlighting that AI ought to serve as an addition instead of a substitute for educators, making sure that the human element continues to be fundamental to the educational experience
| [9] | Woolf, B. P. (2010). Building intelligent interactive tutors: Student-centered strategies for revolutionizing e-learning. Elsevier. |
[9]
. Through the adoption of well-organized policies, educational institutions can leverage AI’s capabilities to assist both learners and educators while preserving ethical and pedagogical standards.
5. AI for Education Accessibility and Inclusion
AI significantly transforms education by dismantling obstacles that have historically restricted access to learning materials for students with disabilities. AI-driven tools like speech-to-text, text-to-speech, and instant translation greatly improve accessibility, enabling students facing visual, auditory, or language difficulties to interact with educational materials in ways that accommodate their requirements
| [4] | Graham, R., Woodfield, S., & Harrison, B. (2019). Accessibility and AI in education: Challenges and opportunities. Springer. |
[4]
. These technologies facilitate the development of a more fair learning atmosphere in which every student, irrespective of their physical or mental capabilities, can engage completely in educational pursuits. Nonetheless, for AI-powered accessibility tools to create a significant effect, it is essential to establish policy measures that guarantee their accessibility and affordability, particularly for students in underprivileged communities or institutions with restricted funding
| [10] | Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education. International Journal of Educational Technology in Higher Education, 16(39). https://doi.org/10.1186/s41239-019-0171-0 |
[10]
. Authorities and educational bodies ought to partner with tech suppliers to subsidize or provide open-access AI resources, guaranteeing that financial limitations do not hinder inclusive education.
Additionally, AI applications should address varied learning needs, acknowledging that students possess distinct cognitive abilities, learning preferences, and support necessities. This involves creating adaptive AI-powered learning platforms that tailor instruction according to personal preferences, utilizing visual aids, auditory methods, or hands-on exercises
| [11] | Gerold, E., Antrekowitsch, H. A Sustainable Approach for the Recovery of Manganese from Spent Lithium-Ion Batteries via Photocatalytic Oxidation. International Journal of Materials Science and Applications. 2022, 11(3), 66-75. https://doi.org/10.11648/j.ijmsa.20221103.12 |
[11]
. AI ought to assist students with learning disabilities like dyslexia, ADHD, or autism by offering personalized help, organized learning opportunities, and immediate feedback.
To guarantee the ethical and efficient application of AI for inclusivity, well-defined guidelines for implementing inclusive AI in educational institutions are crucial. These guidelines must focus on data privacy, ethical use of AI, and adherence to accessibility standards, making sure that AI tools do not inadvertently exclude or disadvantage specific groups. Moreover, teacher training initiatives need to highlight the efficient application of AI for inclusive education, providing educators with the expertise to incorporate these technologies into their classrooms.
Through the development of thorough policies and frameworks, educational systems can enhance AI's ability to foster a more inclusive, accessible, and fair learning environment for every student.
6. AI in Education, Governance and Decision-Making
Education policymakers can leverage AI's capabilities to inform data-driven choices, enhance resource distribution, and anticipate upcoming trends in the education field. Through the analysis of large datasets, AI can uncover shortcomings in educational systems, recognize variances in student achievement among various demographics, and propose specific interventions to improve learning results. Analytics powered by AI can help forecast student dropout rates, assess the success of teaching strategies, and enhance curriculum development to meet changing industry demands
| [12] | Smith, J., & Brown, K. (2021). AI in education: Ethical considerations and policy implications. Journal of Educational Technology, 45(2), 123-135. https://doi.org/10.1016/j.jet.2021.03.005 |
| [13] | Johnson, L., & Adams, S. (2020). The impact of AI on global education systems. International Journal of AI in Education, 30(1), 45-60. https://doi.org/10.1007/s40593-020-00210-6 |
[12, 13]
. Additionally, AI can enhance the allocation of educational resources, making certain that schools with the highest demand obtain sufficient funding, technology, and support services. This data-focused methodology enables policymakers to develop more adaptive and efficient educational systems that tackle challenges in advance.
Nonetheless, the incorporation of AI into education policy should be directed by ethical factors concerning AI-based policymaking to avoid unintended outcomes like discrimination or data misappropriation. Decision-making processes must stay clear and responsible to prevent excessive dependence on AI without human supervision. Additionally, transparency in AI-generated suggestions is vital to guarantee that educational institutions, educators, learners, and other parties comprehend how AI-based insights influence policy formulation. Decision-makers need to mandate that AI models are explainable and interpretable, offering transparent justifications for the suggestions they generate.
Moreover, measures should be established to ensure that biased AI models do not unduly affect decisions
| [1] | Aoun, J. E. (2017). Robot-proof: Higher education in the age of artificial intelligence. MIT Press. |
[1]
. AI algorithms are learned from historical data, which can include biases linked to socioeconomic status, race, gender, or geography. If not adequately handled, these biases might strengthen current inequalities instead of diminishing them. To address this risk, AI models must be routinely examined for bias, and human judgment should be included in the decision-making processes along with insights generated by AI. Moreover, regulatory standards must mandate the utilization of varied and representative datasets for training AI systems, guaranteeing that they mirror the diverse experiences of students and educators. By putting these safeguards in place, education policymakers can successfully utilize AI’s capabilities while ensuring fairness, accountability, and ethical integrity in their decision-making processes.
7. Cybersecurity and Data Privacy in AI-Driven Education
Educational AI systems depend on vast student data to tailor learning experiences, enhance assessments, and offer immediate feedback. Although these features improve education, they also raise major issues related to cybersecurity and data privacy
. The gathering, preservation, and application of sensitive student data—such as academic results, behavioral trends, and biometric information—pose possible risks if not handled securely. Illicit access, data leaks, and cyber assaults on educational organizations can result in the exploitation of personal information, identity fraud, and a decline in trust regarding AI-powered systems. To address these risks, thorough regulations should be implemented for data collection, storage, and usage, guaranteeing that only essential data is collected, kept securely, and utilized exclusively for educational objectives. These policies must require encryption, anonymization, and rigorous access controls to protect student data from harmful individuals.
Additionally, safeguarding against AI-powered cyber threats should be a main concern, since cybercriminals are progressively utilizing AI to execute complex assaults on educational databases and learning systems. Security systems powered by AI ought to be put in place to spot anomalies, recognize possible breaches, and react to threats immediately. Educational institutions, including schools and universities, need to invest in cybersecurity training initiatives for educators and administrators to enhance awareness of best practices in data protection. Moreover, AI developers need to create systems that incorporate security features, like multi-factor authentication and automated threat detection, to guard against unauthorized access to student information.
To uphold worldwide trust and adhere to legal regulations, educational policies must be consistent with international data privacy standards, like the General Data Protection Regulation (GDPR) in Europe, the Family Educational Rights and Privacy Act (FERPA) in the U.S., and comparable frameworks globally
| [3] | Floridi, L., & Cowls, J. (2019). The ethics of artificial intelligence: Principles, challenges, and opportunities. Oxford University Press. |
| [15] | Patel, R., & Williams, T. (2022). The role of AI in bridging the digital divide in education. Journal of Educational Policy, 37(3), 345-360. https://doi.org/10.1080/02680939.2022.2048791 |
[3, 15]
. Institutions utilizing AI in education should guarantee transparency in data usage, secure informed consent from students and parents, and offer individuals control over their personal data. Governments and educational institutions ought to perform regular assessments of AI-based educational technologies to guarantee compliance with privacy regulations and ethical data handling practices. Through the enforcement of these strong policies, education systems can harmonize the advantages of AI with the necessity of safeguarding student privacy and ensuring cybersecurity in a progressively digital educational landscape.
8. Ethical and Societal Implications of AI in Education
Although AI offers transformative possibilities in education, it also brings considerable ethical challenges that need to be thoughtfully tackled to guarantee fairness, inclusivity, and responsible application. A major concern is the bias present in AI algorithms, which can stem from unrepresentative training data or defective coding. If AI systems learn from historical data that indicates societal inequalities, they may continue to discriminate against specific student groups due to factors like gender, socioeconomic background, or ethnicity. To mitigate this risk, ethical AI frameworks should be created to reduce bias and discrimination, necessitating developers utilize varied datasets, perform regular evaluations of AI models, and incorporate fairness assessments in AI-led decision-making procedures. These guidelines must also promote transparency in AI systems, enabling educators and policymakers to comprehend how AI-generated recommendations are produced and to intervene when needed to rectify biases.
A significant challenge is the digital divide, which signifies the differences in technology access and internet connectivity among students from varying socioeconomic backgrounds. Although AI-powered learning resources can improve education, they may worsen inequalities if disadvantaged communities do not have the essential infrastructure to utilize them. Policymakers need to take actions to close the digital gap and guarantee AI accessibility for every student. This includes investing in low-cost internet services, supplying AI-enabled devices to families with limited income, and incorporating AI-based learning tools into public educational systems. Governments and educational bodies should collaborate with tech firms to create affordable, scalable AI solutions suitable for various learning settings, guaranteeing that AI remains accessible and isn't just a privilege of affluent schools.
Moreover, issues regarding automation taking over educators must be tackled to preserve the vital human aspect in education. Although AI can automate administrative duties, delivering personalized learning experiences, and providing immediate feedback, it cannot substitute the emotional intelligence, creativity, and mentorship offered by human educators. Rather than perceiving AI as a replacement, educational policies ought to emphasize methods that augment human-led instruction with AI, ensuring that AI supports, instead of undermining, the function of teachers
| [2] | Baker, T., & Smith, L. (2019). Educ-AI-tion rebooted? The future of AI in schools. Nesta. |
| [12] | Smith, J., & Brown, K. (2021). AI in education: Ethical considerations and policy implications. Journal of Educational Technology, 45(2), 123-135. https://doi.org/10.1016/j.jet.2021.03.005 |
[2, 12]
. This can be accomplished by preparing educators to effectively incorporate AI into their classrooms, utilizing AI-generated insights to enhance personalized teaching, and ensuring human supervision over AI-facilitated evaluations and learning suggestions. By embracing these policies, educational systems can leverage AI's capabilities while maintaining ethical principles, guaranteeing fair access, and safeguarding the crucial role of teachers in influencing students' educational journeys.
9. Future Trends and Policy Recommendations
As AI advances, educational policies need to be flexible and proactive to match the new technologies that are transforming the learning environment. Future developments in AI are anticipated to transform education via AI-powered virtual classrooms, employing smart chatbots, instantaneous analytics, and immersive learning settings to offer more captivating and individualized remote learning experiences. Moreover, intelligent tutoring systems will advance in complexity, delivering personalized assistance to students, pinpointing areas of learning that need improvement, and offering tailored feedback in real time. Moreover, blockchain-based credential verification will improve academic transparency through the secure storage and verification of academic accomplishments, minimizing fraud, and streamlining the process of credential recognition across institutions and countries. To maximize these advancements, decision-makers need to implement proactive approaches to responsibly and effectively incorporate AI into educational systems.
A crucial suggestion for policymakers is to promote AI research and development in education, which includes funding AI-enhanced learning innovations, backing interdisciplinary research on AI’s influence on teaching methods, and encouraging partnerships between educational organizations and tech firms. Governments ought to allocate resources and incentives for research projects focused on enhancing AI's contribution to education, learning, and evaluation, while also prioritizing ethical considerations and inclusivity.
Furthermore, creating clear regulatory frameworks for AI implementation in education is vital to direct AI usage, safeguard student information, and tackle ethical issues. These regulations ought to outline the limits of AI applications, making certain they are in harmony with human-centered educational principles and do not jeopardize data security or the welfare of students. Regulations must also mandate transparency in AI decision-making processes, obliging institutions and developers to reveal how AI-generated evaluations and recommendations are produced.
Finally, fostering global cooperation on AI-based education policies is essential, since AI's impact on education is a worldwide occurrence that goes beyond national boundaries
| [8] | West, D. M. (2018). The future of work: Robots, AI, and automation. Brookings Institution Press. |
[8]
. Nations need to collaborate in order to exchange effective practices, harmonize AI standards, and create ethical guidelines for the incorporation of AI in education. Global forums and collaborations can promote the sharing of knowledge, making certain that AI-driven educational policies are fair, inclusive, and advantageous for every learner, irrespective of their geographic or socioeconomic status. Through the adoption of these strategic suggestions, policymakers can guarantee that AI persists in improving education while upholding ethical standards, inclusivity, and long-term viability in the changing digital environment.
10. Conclusion
AI is transforming education by enhancing learning to be more tailored, effective, and available to students from diverse backgrounds. By utilizing sophisticated machine learning algorithms, AI can examine personal learning behaviors, modify educational materials based on learner development, and offer personalized suggestions that address various learning preferences. This degree of customization allows students to understand concepts at their own speed, enhancing involvement and retention. Moreover, assessment tools driven by AI can automate the grading process, deliver immediate feedback, and pinpoint areas where students require extra assistance, enabling educators to concentrate more on teaching instead of administrative duties. Moreover, AI is greatly improving accessibility in education by aiding students with disabilities through tools like speech-to-text, text-to-speech, instant translation, and assistive learning technologies. These advancements are aiding in closing educational divides, making certain that students with various needs can engage in learning more efficiently.
Nevertheless, the effective incorporation of AI in education necessitates meticulous policy development to address potential risks and guarantee that AI-based solutions are utilized responsibly. Ethical issues, like bias in AI algorithms, need to be tackled to avoid discrimination and guarantee that AI suggestions are equitable and clear. Furthermore, data security is a vital concern, since AI depends on extensive student data to operate efficiently. Robust cybersecurity measures are essential to protect personal information, block unauthorized access, and adhere to international privacy laws. Another significant policy challenge is guaranteeing equal opportunities for all students, especially those from low-income backgrounds or marginalized communities. Inadequate infrastructure and lack of access to AI-driven learning resources may deepen the digital divide, worsening current disparities in education. Policymakers need to strive for the broad accessibility and affordability of AI-powered learning tools to avoid disparities in educational opportunities.
As AI progresses and influences the future of education, proactive and inclusive strategies will be crucial to maximizing its potential while tackling related challenges. Governments, educators, and tech developers should work together to establish ethical AI standards, govern its application in education, and guarantee that AI enhances, instead of replaces, human-led instruction. Global collaboration will also be essential to exchange best practices, synchronize AI education policies worldwide, and promote an inclusive digital learning atmosphere. Through the integration of innovation and responsible governance, AI can be utilized to develop a more efficient, fair, and accessible education system for those who will come in the future.
Abbreviations
AI | Artificial Intelligence |
GDPR | General Data Protection Regulation |
ADHD | Attention-Deficit/Hyperactivity Disorder |
FERPA | Family Educational Rights and Privacy Act |
Author Contributions
Sayed Mahbub Hasan Amiri: Conceptualization, Resources, Writing – original draft, Writing – review & editing.
Md. Mainul Islam: Methodology, Formal Analysis, Validation, Data curation, Supervision.
Mohammad Shakhawat Hossen: Project administration, Investigation, Visualization, Funding acquisition, Software.
Conflicts of Interest
The authors declare no conflicts of interest.
References
| [1] |
Aoun, J. E. (2017). Robot-proof: Higher education in the age of artificial intelligence. MIT Press.
|
| [2] |
Baker, T., & Smith, L. (2019). Educ-AI-tion rebooted? The future of AI in schools. Nesta.
|
| [3] |
Floridi, L., & Cowls, J. (2019). The ethics of artificial intelligence: Principles, challenges, and opportunities. Oxford University Press.
|
| [4] |
Graham, R., Woodfield, S., & Harrison, B. (2019). Accessibility and AI in education: Challenges and opportunities. Springer.
|
| [5] |
Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign.
|
| [6] |
Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. Pearson.
|
| [7] |
Selwyn, N. (2020). Should robots replace teachers? AI and the future of education. Polity Press.
|
| [8] |
West, D. M. (2018). The future of work: Robots, AI, and automation. Brookings Institution Press.
|
| [9] |
Woolf, B. P. (2010). Building intelligent interactive tutors: Student-centered strategies for revolutionizing e-learning. Elsevier.
|
| [10] |
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education. International Journal of Educational Technology in Higher Education, 16(39).
https://doi.org/10.1186/s41239-019-0171-0
|
| [11] |
Gerold, E., Antrekowitsch, H. A Sustainable Approach for the Recovery of Manganese from Spent Lithium-Ion Batteries via Photocatalytic Oxidation. International Journal of Materials Science and Applications. 2022, 11(3), 66-75.
https://doi.org/10.11648/j.ijmsa.20221103.12
|
| [12] |
Smith, J., & Brown, K. (2021). AI in education: Ethical considerations and policy implications. Journal of Educational Technology, 45(2), 123-135.
https://doi.org/10.1016/j.jet.2021.03.005
|
| [13] |
Johnson, L., & Adams, S. (2020). The impact of AI on global education systems. International Journal of AI in Education, 30(1), 45-60.
https://doi.org/10.1007/s40593-020-00210-6
|
| [14] |
Lee, M., & Kim, H. (2021). AI-driven personalized learning: Challenges and opportunities. Educational Technology Research and Development, 69(4), 2101-2120.
https://doi.org/10.1007/s11423-021-09989-2
|
| [15] |
Patel, R., & Williams, T. (2022). The role of AI in bridging the digital divide in education. Journal of Educational Policy, 37(3), 345-360.
https://doi.org/10.1080/02680939.2022.2048791
|
Cite This Article
-
-
@article{10.11648/j.edu.20251401.14,
author = {Sayed Mahbub Hasan Amiri and Md Mainul Islam and Mohammad Shakhawat Hossen},
title = {The Role of Artificial Intelligence in Shaping Future Education Policies
},
journal = {Education Journal},
volume = {14},
number = {1},
pages = {32-38},
doi = {10.11648/j.edu.20251401.14},
url = {https://doi.org/10.11648/j.edu.20251401.14},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.edu.20251401.14},
abstract = {Artificial Intelligence (AI) is revolutionizing the potential of education in its initiatives in personalized learning modules, curriculum designs, evaluation methods, teacher assistance and above all educational management. The rapid deployment of AI-driven technologies demands a proactive approach to education policies, ensuring responsible, fair, and efficient use of AI. Extensive student data is processed by AI systems, enabling adaptive learning models that cater to their learning needs, which in turn optimizes engagement and academic performance. That said, this transition also raises issues in terms of data privacy, cybersecurity, algorithmic bias and the digital divide. This article explores the evolution of AI in education and its impact on learning policies, governance frameworks, accessibility and ethical issues. It examines how AI is influencing the decision-making process in the policymaking of education and relates to the issue of transparency, accountability and equity. In addition, the research stresses mainstream policy recommendations aimed at fostering responsible AI integration, making sure that the students, educators, and educational institutions can benefit from the advantages of AI, without facing its associated issues. By implementing well-defined education policies, governments and institutions can create a framework that promotes innovation around AI, balancing the need for innovation with the need to protect the integrity and inclusiveness of the education system.
},
year = {2025}
}
Copy
|
Download
-
TY - JOUR
T1 - The Role of Artificial Intelligence in Shaping Future Education Policies
AU - Sayed Mahbub Hasan Amiri
AU - Md Mainul Islam
AU - Mohammad Shakhawat Hossen
Y1 - 2025/02/28
PY - 2025
N1 - https://doi.org/10.11648/j.edu.20251401.14
DO - 10.11648/j.edu.20251401.14
T2 - Education Journal
JF - Education Journal
JO - Education Journal
SP - 32
EP - 38
PB - Science Publishing Group
SN - 2327-2619
UR - https://doi.org/10.11648/j.edu.20251401.14
AB - Artificial Intelligence (AI) is revolutionizing the potential of education in its initiatives in personalized learning modules, curriculum designs, evaluation methods, teacher assistance and above all educational management. The rapid deployment of AI-driven technologies demands a proactive approach to education policies, ensuring responsible, fair, and efficient use of AI. Extensive student data is processed by AI systems, enabling adaptive learning models that cater to their learning needs, which in turn optimizes engagement and academic performance. That said, this transition also raises issues in terms of data privacy, cybersecurity, algorithmic bias and the digital divide. This article explores the evolution of AI in education and its impact on learning policies, governance frameworks, accessibility and ethical issues. It examines how AI is influencing the decision-making process in the policymaking of education and relates to the issue of transparency, accountability and equity. In addition, the research stresses mainstream policy recommendations aimed at fostering responsible AI integration, making sure that the students, educators, and educational institutions can benefit from the advantages of AI, without facing its associated issues. By implementing well-defined education policies, governments and institutions can create a framework that promotes innovation around AI, balancing the need for innovation with the need to protect the integrity and inclusiveness of the education system.
VL - 14
IS - 1
ER -
Copy
|
Download
Share This Article
Twitter
Linked In
Facebook
