AI can potentially address some of the biggest challenges in education today. This includes innovating teaching and learning practices and accelerating progress towards SDG 4. The following are five ways AI is transforming the Indian education sector.    

1. AI adoption in the curriculum: Highlighting the importance of AI, Andhra Pradesh CM Y.S. Jagan Mohan Reddy has stressed the need to include it in the curriculum. At a high-level meeting with senior officials of the Education Department and Vice Chancellors of Universities at his camp office at Tadepalli, the CM directed them to take steps to fill the gap between the government's goal and achievements in the field of education in the backdrop of the changes the world was experiencing. AI is now part of the curriculum in government schools in many Indian states. In this context, the Andhra Government came up with this announcement.  Click here to know more.
2. Telangana Public Schools: Last year, several government school complexes in Telangana State are looking forward to deploying artificial intelligence (AI) tools to automate several processes, such as formative assessments, marking attendance, and logging mid-day meal data, among others. These AI tools are also looked at as a medium to teach English and other languages at a later stage.  Click here to know more.
3. Attendance automation: One of the challenges that public schools in Tamil Nadu, India, are struggling to address is student attendance. Manual marking of attendance tends to waste the limited teaching resources of a school, in addition to being prone to errors and manipulation. The initiative aims to help teachers reduce the burden of manual attendance marking and provide an attendance management solution for maintaining and managing attendance records safely and securely. This calls for an unobtrusive and accurate system that does not rely on any manual work by the teachers. TNeGA has developed a cost-effective DL-FRS, a deep learning approach for a facial recognition-based attendance system, which runs on a lightweight edge computing device with an integrated camera. Students can just walk into the school, and the system automatically recognizes each of them face-to-face and marks their attendance. The user-friendly attendance management application helps school management effectively track attendance records.  Click here to know more.
4. Improving teachers' proficiency: Learning Matters' Tara focuses on increasing the teacher's vocabulary, thereby improving communicative skills using grammar constructs. This is achieved by our carefully designed training modules and pedagogical approach to language learning. Tara is a dynamic, two-way interactive, personalized teacher assistant that works on Amazon's Echo Dot, Google Home, and smartphones. Tara uses voice-assisted technology to incorporate the four critical components of language learning - listening, speaking, reading and writing (LSRW). Tara mimics a human teacher by "listening", responding to the learner's utterances, providing feedback and correcting grammatical mistakes, repeating lessons, and conversing with learners tirelessly. This helps learners learn at their pace through repeated practice to gain proficiency in the language. Tara also creates a non-judgmental learning environment where learners can speak confidently without fearing being judged. The lessons are based on real-life situations and everyday conversations. This gives learners the appropriate context to practice speaking in English. Click here to know more. 
5. Identify potential school dropout rate: In December 2015, the Andhra Pradesh Government signed a memorandum of understanding with Microsoft to use AI technology to address the issue of the rise in school dropout rate. By using Microsoft's Azure machine learning platform, an application was developed which helped the state education department in predicting school dropouts. The application processes complex data sets that include details about enrollment, student performance, gender, socio-economic demographics, school infrastructure and teachers' skills to find predictive patterns. The application proactively identified the potential dropouts and analyzed the critical factors responsible for the issue. More than 60 patterns were identified, which helped in tracking dropouts.  Click here to know more.