Anu Parthiban | September 23, 2025 | 07:53 PM IST | 1 min read
More than 900 academics, including Padma and Bhatnagar Prize winners have signed a petition against the draft curriculum, citing 'grave defects' in the UGC LOCF curriculum.
Kerala will not accept the Learning Outcomes-based Curriculum Framework (LOCF) published by the University Grants Commission (UGC), the state minister of higher education and social justice, R Bindu said.
The decision to reject the proposed UGC curriculum was taken based on the findings of the expert committee appointed by the Kerala government to examine the framework. The minister had previously informed Union education minister Dharmendra Pradhan and acting chairperson of UGC Vineet Joshi about the state government’s rejection of the framework.
In her letters to the Centre, the minister stated that the UGC draft curriculum violated the autonomy of universities, the manoramaonline.com reported.
“Prescribing syllabi, course structures, and reading lists exceeds the constitutional responsibilities of the UGC,” the TOI quoted from the letter.
The statement comes amid opposition from subject experts, educators, student groups, and researchers, who flagged ‘grave defect’ only only in mathematics, but related fields like sciences, economics, and engineering. More than 900 academics, including Padma and Bhatnagar Prize winners have signed a petition against the draft curriculum.
The UGC draft LOCF mathematics curriculum 2025 drew sharp criticism from experts due to insufficient coverage of core topics like real analysis, algebra, and applied mathematics, while retaining outdated courses like analytical geometry and mechanics.
The draft curriculum says the Mathematics in Music course needs only Class 10 maths, but the experts highlighted that the course includes advanced topics like Fourier analysis and Markov chains, which cannot be taught at that level.
Similarly, they also pointed out that the Mathematics for Machine Learning course includes basic concepts like sets, functions, and vector spaces, leaving just 15 hours for machine learning concepts.
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