Amid teacher shortages and low literacy, AI-powered adaptive learning offers a path to personalised, multilingual education, aligning with NEP 2020 to overcome geographical and social barriers in J&K
By Muhsin Ameen Malik
In a freezing Kashmiri meadow classroom, an AI whisperer deciphers a student’s reluctant Kashmiri song about algebra and transforms it into a virtual tapestry of apple orchards that employ adaptive algorithms to predict how much fruit will be produced, healing the wounds of school closures due to unrest. Education, which forms the foundation of human development, has constantly undergone transformations in tandem with technological advancements. Since the invention of the blackboard, every new instrument has brought about a revolution in the way teachers instruct their students. One of the most disruptive factors transforming the way schools operate worldwide in the twenty-first century is artificial intelligence (AI), which has become one of the most prominent examples of this shift.
Artificial intelligence (AI) is more than simply a new technology; it represents a shift in educational philosophy away from an instructor-centred approach towards one that is student-centred. By enabling data-driven decisions, providing tailored feedback, and teaching in ways that suit each learner best, AI has addressed the longstanding issue of variability in learning. Lessons in a typical classroom are often delivered uniformly, with the assumption that all students will understand the material at the same pace. However, this “one-size-fits-all” approach frequently fails to account for different learning styles, cognitive capacities, and socioeconomic backgrounds.
AI-enabled classrooms, on the other hand, have the ability to personalise the educational experience for each individual student, ensuring they receive an education tailored to their specific needs, abilities, and pace. For example, by utilising AI techniques such as machine learning algorithms, natural language processing (NLP), and predictive analytics, these classrooms can provide teachers with real-time information on their pupils’ performance. Consequently, teachers can communicate with their students in a proactive and strategic manner.
Artificial intelligence has transformed global learning environments, making education more versatile and adaptive. AI-powered learning environments are being used to personalise instruction for millions of students in the USA, China, Finland, and other countries. These systems adjust the delivery of content based on data derived from student behaviour, including response accuracy, time spent on activities, and learning preferences. Through adaptive feedback loops, platforms like China’s Squirrel AI Learning and the US’s Knewton have made significant progress in maintaining student engagement and interest.
These advancements demonstrate how AI can assist teachers who may lack expertise in certain areas, as well as students with diverse needs. The use of “micro-learning pathways” that can be replicated by AI systems has the potential to improve individual learning outcomes, ensuring no student falls behind. Moreover, AI employs affective computing to identify patterns of disengagement or discontent, helping students develop not only academically but also emotionally and socially. This technology can assess facial expressions and behavioural cues to determine emotional states.
The Indian education system, one of the largest in the world, is beginning to implement AI in its classrooms. The National Education Policy (NEP) 2020 explicitly states that emerging technologies such as AI, machine learning, and robotics should be utilised to aid students in critical thinking and innovation. Projects like AI for All, a collaboration between the Ministry of Education and Intel India, and DIKSHA (Digital Infrastructure for Knowledge Sharing) have laid the groundwork for a significant digital transformation across the country.
However, the integration of AI in Indian classrooms remains uneven. Rural and remote areas continue to face substantial challenges, despite urban regions benefiting from improved digital infrastructure and qualified teachers. These disparities highlight the importance of employing context-specific approaches, especially in regions like Jammu and Kashmir (J&K), which are characterised by political and social instability.
Although Jammu and Kashmir boasts breathtaking landscapes, the region is beset by significant educational challenges. According to ASER 2024, only about 32 per cent of children in Class 8 can perform simple division. Factors such as ongoing conflict, lack of infrastructure, and low literacy levels contribute to this situation.
AI-enabled classrooms serve as beacons of personalised and flexible learning, tailored to each student’s pace, cultural background, and trauma history. Schools in J&K struggle to find adequate teachers (with a ratio of 1:45) and often rely on rote methods that do not accommodate the region’s linguistic diversity, including languages such as Pahari and Gojri. Despite the Right to Education Act of 2009, which guarantees access to education for all, schools in J&K continue to face difficulties.
AI creates personalised learning pathways through intelligent tutoring systems (ITS) and predictive analytics. These align with global trends such as UNESCO’s 2023 AI Education Framework, which praises adaptive technology for its ability to improve learning outcomes by up to 25 per cent in resource-constrained regions.
The unique geographical and geopolitical circumstances of Jammu and Kashmir have historically posed barriers to education, including mountainous terrain, unreliable internet connectivity, and civil unrest, leading to disparities between urban and rural populations. The NEP 2020 aims to transform this landscape through principles of equity, inclusivity, and technological integration. It prioritises AI-driven adaptive systems that can personalise instruction and expand learning opportunities.
By leveraging AI, education can shift from rote, instructor-centred methods to learner-centred, data-driven experiences. Intelligent tutoring systems can assess student progress, adjust content difficulty, and offer immediate feedback. In J&K, where multiple languages are spoken and teacher shortages are acute, AI can support differentiated instruction and ensure continuity of learning despite infrastructural challenges.
However, adoption remains unequal. Despite initiatives like Samagra Shiksha Abhiyan’s computer literacy programmes, rural areas often lack stable power supplies and suitable facilities, as noted by NCERT (2023) and UNESCO (2021). To effectively implement AI in these contexts, tools must be capable of understanding diverse languages (Urdu, Kashmiri, Dogri) and functioning well in regions with limited bandwidth.
Personalised and Adaptive Learning
“Personalised learning” refers to teaching strategies tailored to meet the needs of diverse groups of pupils. AI achieves this by creating learner profiles through analysing data such as performance metrics, behaviour patterns, and learning preferences. Adaptive learning then dynamically adjusts lesson plans based on individual performance, ensuring students are challenged appropriately.
In Jammu and Kashmir, where students vary greatly in linguistic background, resource access, and prior knowledge, AI-powered applications can support multilingual learning—for example, by providing additional exercises for struggling students or accelerating content delivery for advanced learners. These systems can operate independently of school hours, allowing students in remote or conflict-affected areas to continue learning.
AI’s ability to identify learning gaps and process vast amounts of data makes it especially valuable in regions like J&K, where student-teacher ratios can reach 1:60. Intelligent tutoring systems can offer customised support, enabling teachers to focus on complex explanations and emotional support. Furthermore, AI can inform data-driven policymaking: natural language processing can analyse student feedback to improve curricula, while predictive analytics can identify students at risk of dropping out, guiding resource allocation.
The adoption of AI aligns with national and international policy goals. The NEP 2020 advocates for technological integration to overcome geographical and social barriers, supporting the United Nations Sustainable Development Goal 4 (SDG 4) — ensuring inclusive and equitable quality education and promoting lifelong learning opportunities. The Jammu and Kashmir government has launched various online education initiatives under the Samagra Shiksha Abhiyan and NDEAR frameworks. Integrating AI into these programmes could transform them into comprehensive, evidence-based learning ecosystems.
The writer is a teacher
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