India has always cherished the ideal of the classroom as a great equalizer. However, this equality often falters when it comes to the language of instruction. Historically, crowded classrooms, inflexible curricula, and English-centric learning materials have inadvertently broadened educational disparities rather than bridging them. A profound, yet subtle, shift is now underway: the rise of adaptive learning platforms offered in India’s native languages. These powerful tools personalize learning journeys, adapting to each child’s individual pace and style, and critically, speaking to them in the language they inherently understand. This isn’t merely flashy educational technology; it’s a fundamental commitment to equity, delivering tailored learning, one student, one step, and one mother-tongue interface at a time.
This AI-generated image illustrates how adaptive learning platforms, leveraging Indian languages, are working to close the nation’s educational equity gap.
The Stubborn Equity Gap
The existing educational disparities are far from abstract; they are starkly quantified. The comprehensive ASER 2024 survey, which encompassed nearly 18,000 villages and over six lakh children, revealed a concerning trend: only 23.4% of Standard III students in rural India were proficient enough to read a Standard II level text in 2024, marking an improvement from 16.3% in 2022. However, significant challenges persist. Similarly, in arithmetic, 33.7% of Standard III students could solve a basic subtraction problem in 2024, an increase from 25.9% in 2022, while Standard V students’ division proficiency stood at merely 30.7%. Despite an impressive near-universal enrollment rate—with 98.1% of children aged 6–14 attending school in 2024—the persistent gap in actual learning outcomes stands as a critical indicator of the country’s educational reality.
The Scale That Needs to Be Served
The sheer magnitude of India’s education system is highlighted by the government’s UDISE+ 2023–24 data, which reports nearly 250 million students enrolled in schools, with more than two-thirds attending government institutions. A crucial detail is that the majority of these students receive instruction in regional languages such as Marathi, Telugu, Bengali, Tamil, or Hindi, rather than English. The National Education Policy 2020 acknowledged this reality by advocating for mother-tongue instruction during the foundational years. This policy formalizes a truth long understood by parents: true comprehension and effective learning begin in a child’s native language, not solely in a language often associated with future aspirations.
What Makes an Adaptive Learning Platform Different?
An adaptive learning platform transcends the capabilities of a mere video library with improved navigation. Instead, it functions as a dynamic feedback system that continuously adjusts the difficulty level, content sequence, and pedagogical support based on a child’s real-time performance. For instance, a student struggling with fractions would be presented with simpler problems, alternative visual explanations, or fresh instructions delivered in their native language. Conversely, a student who quickly grasps a concept can seamlessly advance. This represents a highly calibrated approach to education, and its effectiveness is supported by concrete evidence, not just anecdotes. Randomized evaluations of Mindspark, an adaptive system implemented in Delhi and Jaipur, demonstrated learning gains equivalent to three to four months of extra schooling within a single academic year. Notably, the most significant improvements were observed among students who were initially struggling the most, underscoring its role in achieving educational equity.
Language Support and State Deployments
A cornerstone of personalized learning in India is its inherent multilingual capability. DIKSHA, the Ministry of Education’s digital infrastructure, now offers curriculum-aligned resources in 36 Indian languages. While DIKSHA itself isn’t an adaptive platform, it serves as a crucial hub, enabling states to integrate adaptive learning systems featuring vernacular content and QR-linked textbooks. Andhra Pradesh, for example, has successfully launched a Personalised Adaptive Learning (PAL) program in Telugu and English, utilizing tablets and WhatsApp chatbots, with independent evaluations confirming substantial learning improvements. Karnataka has entered a five-year partnership with Khan Academy to deliver adaptive math and science practice to approximately 1.9 million students, offering support in Kannada and other regional languages. Maharashtra has a similar Memorandum of Understanding (MoU) that integrates with its Balbharati content portal. Earlier initiatives in Rajasthan, using Mindspark in Hindi-medium government schools, demonstrated the power of computer-adaptive engines to boost performance even where resources were thin.
The ASER 2024 report highlights a significant recovery trend: government school students showed faster improvement in learning outcomes compared to their private school counterparts between 2022 and 2024. Reading proficiency, for instance, saw an increase of approximately seven percentage points in government schools versus about two points in private schools. It is reasonable to conclude that focused remediation efforts and the growing adoption of adaptive, mother-tongue learning tools played a vital role in this positive development.
Engines and Enablers: Clear Roles
To better understand the ecosystem, it’s useful to distinguish between classroom ‘engines’ and system ‘enablers.’ Platforms like Balbharati/e-Balbharati, which serve as state content portals, enhance access to textbooks and educational resources in Marathi and other languages, but they do not offer personalized learning. Similarly, Andhra Pradesh’s Nadu-Nedu program focuses on upgrading school infrastructure, including classrooms, electricity, and internet connectivity. While these improvements are essential for technology integration, they don’t inherently provide a pedagogical approach. Furthermore, Vidya Samiksha Kendra (data dashboard centers) collect attendance and assessment data to inform planning and targeted interventions. These centers facilitate adaptive strategies but are not direct student-facing learning platforms. In essence, the ‘engines’ are the systems that deliver the personalized, adaptive learning experience, while the ‘enablers’ create the necessary conditions and infrastructure for these engines to operate effectively at scale and reach specific student populations.
Access, Costs, and Implementation
Indicators related to access are showing promising improvements. The ASER 2024 report reveals that an impressive 90% of rural youth aged 14–16 reside in households with a smartphone, and approximately 82% are capable of using one. While challenges such as device-sharing and gender disparities in usage persist, the development of low-bandwidth solutions, like Andhra Pradesh’s WhatsApp-based PAL program or DIKSHA’s QR-linked textbooks, are effectively lowering barriers to access. Moreover, the economic viability of these solutions is noteworthy. Evaluations of computer-adaptive instruction, such as Mindspark, position it among India’s most cost-effective educational interventions. It delivers significant learning gains at a comparatively low per-pupil cost when measured against the expense of additional teacher hours. Ultimately, the success of adaptive learning platforms hinges on the quality of their implementation, which includes crucial factors like robust teacher training, thoughtful time-tabling, and effective integration of data into lesson planning.
Measuring Success
Considering the vast scale outlined by UDISE+ 2023–24 and the foundational learning data from ASER 2024, the effectiveness of these initiatives can be tracked using several key metrics. These include the percentage of government school students utilizing adaptive learning platforms in their native languages, observed improvements in foundational reading and arithmetic scores on both state assessments and the National Achievement Survey, the level of classroom integration as evidenced by teachers’ adoption of platform dashboards for student grouping and remediation, and disparities in access based on gender and device availability. These crucial indicators will ultimately reveal whether multilingual, adaptive learning strategies are successfully delivering lasting educational benefits to the populations most in need.