Syllabus: GS2/ Education
Context
- India AI’s mission envisages the opening of the AI Centres for Excellence (CoE) in education.
| IndiaAI Mission – A key focus of this mission is the development of a high-end common computing facility equipped with 18,693 Graphics Processing Units (GPUs), making it one of the most extensive AI compute infrastructures globally. – This capacity is nearly nine times that of the open-source AI model DeepSeek and about two-thirds of what ChatGPT operates on. |
India’s AI Integration in Education
- Increase in Number of Schools having Computer Access: One of the most notable improvements is the increase in the number of schools with computer access, rising from 57.2% in 2023–24 to 64.7% this year.
- Increase in Number of Schools having Internet Access: The percentage of schools with internet connectivity increased from 53.9% in the previous year to 63.5% in 2024–25.
- Teacher training & digital literacy: Fewer than 50% of secondary/higher secondary teachers are trained in computer use.
- Student access, gender, and digital divides: Male students tend to have higher digital literacy than female peers; rural and disadvantaged students have lower access.
AI in Curriculum & Policy
- National Strategy for AI (2018): Education was identified as a core sector in India’s National Strategy for Artificial Intelligence. The strategy suggests:
- Curriculum reforms to integrate AI and digital skill education.
- Adaptive learning tools, intelligent tutoring systems, and predictive analytics (for student dropout risk, etc.).
- Digitization of records (teacher performance, student data) as prerequisites.
- National Education Policy (NEP) 2020: NEP 2020 sees AI as a transformative force and calls for adaptation of the education ecosystem to leverage it. It envisions:
- AI-based software for holistic progress tracking using learning data and interactive questionnaires.
- Use of adaptive assessment systems and AI-driven feedback to personalize learning and support diverse learners.
- AI Subject / Curriculum in Schools: CBSE has introduced Artificial Intelligence as an optional subject from Class VIII (12-hour module), and as a skill subject in Classes IX–XII.
- CBSE released an AI Curriculum Handbook and AI Integration Manual to support teachers.
- Topics include three domains: data, computer vision, and natural language processing, in an age-appropriate manner.
- India has several national building blocks intended to reduce the readiness gap:
- DIKSHA (a national digital infrastructure for learning resources), PM e-VIDYA (multimode access to digital education), the National Digital Education Architecture (NDEAR) blueprint, and Samagra Shiksha (which finances ICT components in schools and teacher training).
- These platforms and schemes provide a backbone for scaling digital content and teacher development.
Significance of AI adoption in Schools
- Personalized / adaptive learning: AI can dynamically adjust difficulty, pace, content type based on individual student performance, providing remedial or extension support.
- Multilingual & language support: AI can help students access content in multiple languages, support translation, and assist learners in linguistically diverse backgrounds.
- Support for learners with disabilities: AI can enable assistive technologies (text-to-speech, alternate input modalities, personalized interfaces) to enhance accessibility.
- Automating administrative tasks: Grading, report generation, lesson planning, attendance, etc., can be partially automated to free up teacher time for higher value tasks.
- Enhanced assessment design & feedback: AI can help design assessments that go beyond rote recall and standardize grading to some extent.
- Predictive analytics for at-risk students: By analyzing attendance, performance, etc., AI systems can flag students likely to drop out or underperform and prompt interventions.
Challenges/Concerns
- Bias, fairness & trust: If models are trained on non-diverse or skewed data, they may perpetuate or amplify biases (gender, socio-economic, language).
- Data privacy & security: Schools hold sensitive student and teacher data. Ensuring secure storage, limiting usage, obtaining consent, and preventing misuse is complex.
- AI misinformation: Generative models may produce incorrect or misleading content. In education, such hallucinations can mislead students.
- Lack of localized datasets and language support: Many AI tools are built in English or dominant languages; regionally relevant datasets or models in Indian languages are scarce.
- Digital divide & equity: Students in remote, poor, or underprivileged areas may lack devices, connectivity, or support, leading to exclusion.
- Preservation of foundational thinking skills: Overreliance on AI tools can weaken students’ capacity for independent thinking, reasoning, and self-regulated learning.
Suggestions
- Transparency & explainability: Systems should disclose how they arrive at recommendations or judgments, in user-understandable ways.
- Privacy & consent: Child data must be collected with verifiable parental consent, stored securely, used only for intended purposes, and retention limited (In line with India’s DPDP Act 2023) .
- Expand internet connectivity and digital access, especially in rural and government schools, to close the infrastructure gap.
- Invest in school-level computing hardware, maintenance, and IT support systems (e.g., regional support centers).
- Scale up teacher training and professional development focusing not just on technical skills but pedagogy, AI literacy, ethics, and implementation support.
- Establish clear policy and regulatory guardrails, including guidelines for data use, audit, liability, redress, and transparency.
Source: TH
