AI-LED EDUCATION, A NEW NORMAL

THE CONTEXT: The global education technology market, valued at $254.80 billion in 2021, is projected to reach $605.40 billion by 2027, growing at a CAGR of 15.52%. It underscores the increasing integration of AI in education systems globally. AI in education offers personalized learning experiences, intelligent tutoring systems, and automated administrative tasks. However, AI in education also raises concerns about equity, data privacy, and the changing role of educators.

ADVANTAGES OF AI IN EDUCATION:

• • Self-training and adaptability: AI systems in education demonstrate remarkable self-training capabilities, continuously improving their performance through machine learning algorithms. Carnegie Learning’s MATHia platform uses AI to provide personalized math instruction, resulting in 2-3 times better learning outcomes than traditional methods.
  • Personalized learning experiences: AI algorithms analyze data and provide insights that inform the customization of learning materials, ensuring students engage with relevant and meaningful content. SMART SPARROW at the University of Sydney allows educators to create adaptive learning pathways within their courses, tailoring content delivery to individual learning styles and needs.
  • Real-time adjustment to student needs: AI-powered educational tools can provide real-time feedback and adjust learning pathways based on student progress. This immediate responsiveness allows for timely interventions and support, ensuring that students receive the help they need when they need it most.
  • Scalability for many students: Georgia Institute of Technology implemented an AI-powered teaching assistant named “Jill Watson” to automatically respond to students’ frequently asked questions in an online master’s in computer science course. This AI assistant was trained on a dataset of over 40,000 forum posts from previous course iterations, demonstrating the scalability of AI in managing student inquiries.

CHALLENGES AND CONCERNS OF AI IN EDUCATION:

• • Impact on Children’s Creativity: AI leads to “fixation of the mind,” where students struggle to think independently after seeing AI-generated suggestions. This raises concerns about originality and self-confidence. Children may abandon ideas prematurely if AI fails to generate desired outputs, which could stifle their perseverance—a crucial aspect of creativity.
  • Potential Replacement of Teachers: While AI can automate administrative tasks and provide personalized learning experiences, it cannot replicate the nuanced human connection essential for effective teaching. Human educators must remain central to education, advocating for AI as a supplementary tool rather than a replacement.
  • Increased Plagiarism: Students increasingly use AI for assignments without proper attribution, blurring the lines between legitimate assistance and unethical practices. The University Grants Commission (UGC) in India mandates technology-based mechanisms for plagiarism detection and imposes penalties for violations.
  • Assessment Malpractices: Generative AI can produce answers that outperform even advanced students, undermining genuine learning and academic integrity. Institutions are shifting towards open-ended questions, oral exams, or field-based assessments to make cheating harder while emphasizing critical thinking skills.
  • Broader Implications: Over-reliance on AI may widen educational disparities, as not all students have equal access to advanced technologies. AI systems’ use of student data raises concerns about security and potential misuse. Biases in AI algorithms could perpetuate existing inequalities in education.

NAVIGATING THE GREY ZONE OF AI IN EDUCATION:

• • Determining Appropriate AI Usage: Tasks such as grading, scheduling, and data analysis can be efficiently managed by AI, freeing educators to engage in more meaningful interactions with students. Skills like emotional intelligence, ethical reasoning, and interpersonal communication remain irreplaceable by AI. These skills are crucial for fostering a supportive and inclusive learning environment.
  • Rethinking Educational Assessments: Traditional assessments may not effectively differentiate between independent student work and AI-generated content. Innovative approaches such as project-based assessments, oral exams, and collaborative tasks can better capture student understanding and creativity4. These methods encourage critical thinking and problem-solving skills that are less susceptible to automation.
  • School-Level Policies and Guidelines: Engaging educators, students, and policymakers in developing guidelines ensures a shared understanding of acceptable AI use. Schools should implement monitoring systems to track AI usage in assignments and assessments. This includes maintaining drafts of student work and requiring evidence of originality when necessary.
  • Enhancing Teacher Roles with AI: AI can help teaching by automating routine tasks, allowing educators to focus on more impactful aspects of their roles. Teachers can better evaluate student learning through diverse methods by shifting focus towards interactive assessments like discussions, role plays, and field visits.
  • Triangulating Evidence of Student Learning: Combining teacher-led assessments with AI-generated insights provides a holistic view of student progress. This approach ensures that both quantitative data and qualitative observations inform educational decisions.

FUTURE OUTLOOK:

• • Lifelong Learning for Educators: AI-driven tools require teachers to develop new competencies, including digital literacy and data interpretation skills. Over 54% of educators globally support AI training programs for teachers to ensure they can effectively leverage these tools.
  • Curriculum Redesign: Integrating AI literacy into curricula prepares students for an AI-dominated future. For example, Singapore’s Ministry of Education has introduced coding and AI modules at the school level. UNESCO emphasizes the need for human-centered education that fosters an understanding of ethics and human rights alongside technical skills.
  • Policy Frameworks: The European Commission’s Digital Education Action Plan advocates for equitable access to AI technologies across member states. India’s National Education Policy (NEP) 2020 highlights the role of technology in democratizing education but stresses the importance of teacher-led pedagogy.
  • Continuous Feedback Loops: Continuous learning models enable AI platforms to refine their algorithms based on new data streams. Institutions must implement mechanisms to monitor the effectiveness of AI tools, ensuring they align with educational goals.
  • Equity-Focused Design: Ensuring access to affordable connectivity, hardware, and digital platforms is critical to bridging the digital divide. Initiatives like India’s PM eVidya aim to provide digital resources to underserved communities.

THE CONCLUSION:

The future of AI in education holds immense promise but requires careful navigation through its unpredictable growth trajectory. To this end, we must foster continuous learning among educators, redesign curricula to include AI literacy, implement robust policy frameworks, and maintain a balance between technology and human-centered pedagogy.

UPSC PAST YEAR QUESTIONS:

Q.1 Education is not an injunction but an effective and pervasive tool for the all-round development of an individual and social transformation”. Examine the New Education Policy,2020(NEP,2020)in light of the above statement. 2020

Q.2 Artificial Intelligence’s application as a dependable input source for administrative rational decision-making is a debatable issue. Critically examine the statement from an ethical point of view. 2024

MAINS PRACTICE QUESTION:

Q.1 Artificial Intelligence (AI) is increasingly integrated into educational systems worldwide, offering transformative potential and significant challenges. Discuss the advantages and concerns associated with AI in education.

SOURCE:

https://www.deccanherald.com/opinion/ai-led-education-a-new-normal-3317059