India’s education system has long aimed to include environmental topics in school lessons. Modern technology now helps create new ways to teach these ideas, making environmental learning a key part of all school levels. West Bengal’s special location—a mix of the world’s biggest delta, mangrove forests, and busy cities—supports many lives and rich cultures but faces serious threats. Rising seas, cyclones, air and plastic pollution, and unpredictable rain are endangering Sundarbans’ islands, water supplies, and communities.
Teaching students to understand and protect these ecosystems is vital. Ecological literacy—practical knowledge of nature—should be a regular part of school learning. In West Bengal, this means helping kids adapt to climate challenges and rebuild resilient systems for the future.
Artificial Intelligence (AI) can transform environmental education by tailoring lessons to local needs and using interactive tools. A plan to use AI in West Bengal schools could focus on training teachers, creating engaging learning projects, and addressing risks such as gaps in technology access. This approach aims to prepare students for real-world environmental challenges while balancing AI’s strengths and limitations.
Ecological Literacy and Its Significance
As stated by Juanda, Mahmudah and Tuflih (2024), eco-literacy is an understanding that enables us to make appropriate decisions regarding the environment. It also enriches our knowledge of ecosystems, human activities, and systems thinking, helping citizens make informed individual and collective choices. This form of literacy is especially important given the geographical diversity of West Bengal.
The Sundarbans is a UNESCO-protected ecosystem that helps reduce the impact of storms and cyclones. However, it is highly vulnerable to rising sea levels and extreme weather. The conditions of these coastal areas strongly affect the lives of local communities and are important for state planning, as they are endangered and need urgent attention.
A strong, place-based environmental education system in schools can help students understand local issues such as saltwater intrusion, mangrove protection, and waste management. It can also connect these local problems to global challenges like climate change and pollution. This approach encourages students to take part in creating practical solutions that can bring real change (UNESCO World Heritage Centre, 2010).
Both national and state education systems have responded to current needs by including environmental studies in the school curriculum. The latest policies and the National Curriculum Framework (NCF) highlight environmental education as an interdisciplinary, skills-based subject that should be taught across all grades. West Bengal’s State Education Policy 2023 builds on the national policy by promoting innovative, locally relevant teaching methods and technology-supported ecological learning.
These policy changes create an opportunity for schools to rethink how they teach environmental topics. They encourage a continuous, curious, and action-focused approach, helping students understand the environment not just through theory but through real-life experiences and practical activities (Government of West Bengal, 2023).
Artificial Intelligence (AI) and Environmental Education
According to Holzinger et al. (2019), Artificial Intelligence (AI) is a long-standing field of computer science that focuses on creating machines capable of performing tasks that involve thinking, learning, and problem-solving—much like humans do. It uses ideas from both cognitive science and computer science, which is why AI is often described as “machine intelligence,” separate from human intelligence.
Even with these abilities, AI cannot replace the local knowledge that teachers develop through their experience, values, and real-life understanding of nature. However, AI can support teachers by improving the learning process, reducing routine administrative work, and providing useful insights into local ecosystems. This makes education more meaningful while keeping teachers at the centre of learning.
AI Benefits for Ecological literacy
AI-based personalized learning can help students learn at their own level and pace. AI tutors can adjust assignments and content based on a learner’s age, ability, local knowledge, and interests. For example, a Grade 6 student may use AI to collect basic air-quality data from their neighbourhood, while a Grade 10 student may analyse the same data using more advanced statistical tools. This kind of individual support helps avoid abstract, irrelevant, or impersonal environmental learning (Sharma, 2025, p. 6).
AI can also bring together different types of local data and turn them into easy-to-understand visuals. Weather records, satellite images, citizen science sensor data, and waste collection logs can be combined to produce clear classroom visuals. These may include maps showing areas where mangrove forests have been lost, timelines showing monsoon changes, or a school’s carbon and waste footprint. Such visual tools help students make predictions, form hypotheses, and design experiments based on what is happening around them.
Generative AI offers even more possibilities when used with satellite platforms like Google Earth Engine. It can provide rural schools with access to learning opportunities that previously required expensive GIS software and expert training. Students can pair long-term satellite images with AI tools such as Grok, Claude, or Gemini to view 30 years of environmental changes—such as deforestation trends in their own village—in a simple and accessible way.
AI can summarise complex patterns, create clear explanations, and generate interactive visuals from raw datasets. This helps simplify complicated environmental issues so that they can be understood even by school students. In this way, AI becomes a powerful support tool for environmental education, making local problems easier to study and explore (See et al., 2025).
AI simulations can help students see the effects of their decisions, such as land-use changes, school waste management strategies, or mangrove restoration versus neglect. This teaches them systems-thinking and helps them understand long-term consequences (Arno, 2025).
West Bengal classrooms use many languages. AI can create lessons, reading materials, and activities in Bengali, Hindi, Urdu, English, and local dialects. This keeps cultural values intact while teaching scientific knowledge.
AI-based tools can suggest lesson plans, assessments, and classroom activities based on what resources are available locally, whether in rural Sundarbans schools or urban Kolkata schools.
AI can help students collect and organize real data—like photos of plastic pollution, species sightings, or water quality measurements—turning school assignments into real contributions for local environmental monitoring.
AI works best when combined with outdoor learning and community interaction. It should support, not replace, hands-on experience and teamwork (Ryo, 2024, p.6).
Implementation of AI in Educational Institutions
Using AI in West Bengal’s education system must follow principles that prevent inequality and avoid solutions that are too technology-heavy or extractive.
- Equity first: Schools in rural or low-internet areas should have access to simple tools like SMS, voice assistants, and offline apps. AI systems should work on basic smartphones and low-cost tablets commonly used in schools.
- Pedagogical fit: AI tools must support active, inquiry-based learning. They should help create tasks that involve field visits, discussions, and community activities—not passive learning.
- Transparency and teacher control: Teachers must be able to check, edit, or reject AI suggestions. AI systems should clearly explain why they recommend a certain activity or assessment.
- Local relevance and data protection: Local ecological data, community knowledge, and student work must be treated as local assets. Any central AI system must respect privacy, consent, and data ownership.
- Evaluation and continuous improvement: Pilot projects must include strong impact assessment—looking at students’ ecological understanding, behaviour change, and community impact—as well as an ethical review.
Integrating AI into environmental education in West Bengal can make learning more effective and meaningful. It helps teachers plan lessons, supports hands-on activities, and connects students with real local environmental issues. Students can use AI to monitor air quality, track mangroves, or document plastic pollution, contributing data that guides community decisions and policies. Participating in citizen-science and community projects allows students to see the real impact of their work, building responsibility and civic awareness. This approach turns classrooms into active learning spaces, inspires environmental action, and empowers students to protect their communities while promoting sustainability and resilience for the future.
Roadmap for AI in Environmental Education
A practical, step-by-step plan is needed for schools, educational bodies, and civil society in West Bengal to use AI for ecological literacy.
- Policy alignment and partnerships: Follow State Education Policy and NCF guidance to form an “Ecological Literacy + AI” group including the Education Department, SCERT, universities, NGOs, teacher unions, and environmental agencies. This group will set learning goals, data rules, and pilot criteria (Banglar Shiksha, 2023).
- Context mapping: Review current environmental programs like Urja Chetana, local hotspots such as Sundarbans and rivers, and schools’ readiness in terms of devices, connectivity, and teacher training. Successful existing programs can speed up implementation (Centre for Environment Education).
- Toolkit design: Create open-source AI toolkits for schools, with offline content in local languages, lightweight apps, data collection tools, and visualizations to blend local data with lessons, even in low-bandwidth areas.
- Diverse pilots: Run pilot projects in 30–50 schools across different areas—Sundarbans, semi-urban areas, Kolkata, and agricultural districts. Each pilot includes teacher guidance, AI-supported lessons, student projects, and community action labs like composting or mangrove nurseries. Existing initiatives like Diksha, Urja Chetana, Paribesh Bandhu, and WWF-India programs can be included.
- Integrating ecological concerns: Projects should focus on local issues. In Sundarbans: mangrove restoration, saltwater intrusion, livelihood activities. In urban areas: air quality, plastic waste, green schoolyards. Local relevance increases engagement and links learning to real-life action.
- Mixed methods monitoring: Measure outcomes like understanding of ecological concepts, systems thinking, behaviour changes (waste segregation, less plastic use), and community impact (clean-ups, tree planting). Use classroom assessments, interviews, and citizen-science data.
- Teacher networks and micro-credentialing: Build teacher networks for sharing materials and training peers. Introduce micro-credentials for teachers who master ecological education and AI tools.
- Regular eco-practices in schools: Make eco-activities routine with weekly data collection, eco-committees, and student projects using AI to analyse local data.
- Resource centres and mobile labs: Set up district eco-learning centres and mobile labs with sensors and demo kits for rural schools.
- Sustainability funding and partnerships: Finance devices, training, and monitoring through public-private partnerships, CSR funding, community co-investment, and central schemes like the Environment Education Programme.
AI and Sustainable Career Skills
AI skills, combined with ecological knowledge, prepare students for future green jobs and climate-focused careers. By learning to use AI for environmental problem-solving, students gain practical, real-world skills while understanding local ecosystems. This connection between classroom learning and future opportunities empowers learners to contribute to sustainable development and build careers that support a healthier planet.
Ethical Use of AI
AI must be used responsibly, ethically, and without bias in schools. This includes protecting students’ data, respecting privacy, and ensuring fairness in learning tools. Ethical AI builds trust, supports safe and inclusive classrooms, and encourages responsible use of technology. By following these principles, AI can enhance environmental education while respecting students, teachers, and communities.
Way Forward
With the right support and careful planning, West Bengal can lead the way in AI-based environmental education. Schools, teachers, and students can work together to learn about local ecosystems, take meaningful actions, and solve real environmental problems. This approach will not only build ecological knowledge but also inspire communities to protect nature and create a sustainable future.
Conclusion
In West Bengal, where rich ecosystems face growing climate threats, using AI in environmental education can greatly improve learning. AI tools and simulations make difficult ideas easy to understand and help students see real local issues like mangrove loss in the Sundarbans or pollution in the Hooghly River. Classrooms become active learning spaces where theory connects with real-life solutions. AI also supports teachers by personalizing lessons, creating hands-on tasks, and reducing planning time. This approach builds climate awareness and encourages students to take action. When used in local contexts, AI-based education inspires learners to protect West Bengal’s environment and the planet.
Written By:
- Md.Imran Wahab, IPS &
- Dr. Romana Ali, Assistant Professor
