Context & Policy Concerns
- NEP 2020 enforces a three–language policy, but India’s school system struggles with even two languages.
- Evidence-based policymaking should guide decisions, yet data on third-language learning outcomes is absent.
- Instead of strengthening math, science, and emerging fields like AI, resources are being diverted to an unproven linguistic policy.
Relevance : GS 2(Education)
Surveys & Learning Outcomes
- PISA 2009: India ranked 73/74, withdrew from the test afterward.
- NAS 2017 & 2021:
- Class 8 (2017): Only 48% could read, 47% could write, 42% grasped grammar.
- Class 8 (2021): 56% could read, 49% could write, 44% had grammar skills (marginal improvement).
- ASER 2018 & 2022:
- 2018: 27% of Class 8 students couldn’t read a Class 2-level text.
- 2022: This worsened to 30.4%.
- English Proficiency (2016 vs. 2022):
- 2016: 73.8% of Class 8 students couldn’t read simple English sentences.
- 2022: Still 53.3% struggled with basic English.
Schools are failing to ensure proficiency in two languages, making a third language redundant.
Cognitive & Pedagogical Challenges
- Cognitive Load Theory: Learning an L3 strains cognitive capacity, reducing efficiency in L1 & L2.
- Language Similarity Impact:
- Indo-Aryan languages (Marathi, Punjabi, Odia) → Facilitative learning of Hindi.
- Dravidian & Sino-Tibetan languages (Tamil, Santali, Mizo) → Difficult, asymmetric learning burden.
NEP 2020 ignores linguistic diversity and cognitive limitations.
Implementation Challenges
- Teacher Shortages & Resource Allocation:
- Rural schools lack teachers for core subjects, let alone three languages.
- Budget constraints make it impractical for States to fund additional language teachers.
- Illusory Choice:
- The policy states students can choose any three languages, but in practice, schools will default to Hindi or Sanskrit due to teacher availability.
- This creates an indirect push for Hindi, especially in non-Hindi-speaking States.
AI & Language Learning
- NEP 2020 overlooks AI-driven language tools like real-time translation, voice-to-text conversion.
- Instead of classroom instruction, students could use AI for additional language learning at their own pace.
A flexible AI-based approach would be more cost-effective and inclusive.
Lessons from Singapore
- Bilingual Policy: English (neutral global language) + mother tongue (Mandarin, Malay, or Tamil).
- Results:
- PISA 2015 & 2022: Singapore ranked 1st in the world.
- Social harmony & economic success due to English proficiency.
India should prioritize English and regional languages, not force a third language.
Why Hindi Can’t Be a National Unifier
- 2011 Census: 43.63% Indians are classified as Hindi speakers, but this includes 53 other languages as “Hindi dialects.”
- Actual Hindi speakers: ~25% of the population.
- Migration patterns:
- 95.28% of Indians never migrate outside their home States → They do not require Hindi for survival.
- Forcing Hindi ignores India’s linguistic diversity and federal structure.
Conclusion: Evidence Over Ideology
- India struggles with basic literacy in two languages, enforcing a third is impractical and unnecessary.
- NEP 2020 prioritizes ideology over data-driven policymaking.
- Investments should focus on STEM education, AI, and real-world skills instead of an unproven trilingual model.
