The National e-governance division (NeGD) of the Ministry of Electronics and Information Technology (MeitY) is set to integrate personalised Adaptative learning (PAL) into its  digital infrastructure for knowledge sharing (DIKSHA) Platform.

expected to allow each student to have individualised learning experience over the course of the curriculum based on their needs and Abilities.

E-Content: Diksha comes under Education ministry, provides e-content for school by an online portal and a mobile application.

Visual Learners: It has embedded assistive technologies for learners with visual of hearing challenges.

Digitisation: DIKSHA features digitise NCERT textbooks used by national and state boards.

AI learning system: THE NCERT has sought expertise in facilitating the PAL’s integration into DIKSHA.

Example: If a student of class 9 is learning the Pythagoras theorem and makes a calculation mistake, the AI AI learning system flags it and loops the student flags it and loops the student back to a basic video of how to make the calculations.

Massive Exercise: Building the PAL is a massive exercise. Content from across subjects will have to be categorised and different chunks will have to be tagged.

E-learning and AI (Artificial Intelligence) are two closely intertwined fields that have been significantly impacting education and training in recent years. AI technologies have the potential to revolutionize the way we learn and teach by providing personalized, adaptive, and efficient educational experiences. Here are some key aspects of the relationship between e-learning and AI:

Personalization:

AI can analyze a learner's strengths, weaknesses, and learning preferences to provide personalized content and recommendations. This personalization enhances engagement and helps students learn more effectively.

Adaptive Learning:

• Adaptive learning systems use AI algorithms to adjust the difficulty and pace of content based on a student's progress. This ensures that learners are challenged but not overwhelmed, optimizing their learning outcomes.

Intelligent Content Creation:

• AI-powered tools can assist educators in creating high-quality educational content. For example, AI can generate practice questions, quizzes, and even educational videos, reducing the time and effort required to develop materials.

Automated Assessment:

• AI can automate the assessment process, grading assignments, quizzes, and exams more efficiently. It can also provide detailed feedback to students, helping them understand their mistakes and improve.

Natural Language Processing (NLP):

• NLP algorithms enable AI to understand and respond to natural language. This technology can be used in chatbots, virtual tutors, and automated essay scoring systems, enhancing communication and support in e-learning environments.

Data Analytics:

• AI can analyze vast amounts of data generated in e-learning platforms, identifying trends, learning patterns, and areas where students might struggle. Educators can use these insights to make data-driven decisions and improve course design.

Accessibility:

• AI-powered tools can make e-learning materials more accessible to individuals with disabilities. For example, speech recognition and text-to-speech technologies can assist those with visual or hearing impairments.

Language Learning:

• AI-driven language learning platforms can provide real-time feedback on pronunciation, grammar, and vocabulary, making language learning more interactive and effective.

Predictive Analytics:

• By analyzing student data, AI can predict which students may be at risk of falling behind or dropping out. Educators can then intervene with targeted support to help these students succeed.

Virtual Reality (VR) and Augmented Reality (AR):

• AI can enhance the immersive experiences offered by VR and AR in e-learning, creating realistic simulations and interactive environments for subjects like science, history, or medical training.

Continuous Improvement:

• AI can assist educational institutions in continuous improvement efforts by analyzing feedback and performance data from students and educators, enabling institutions to refine their programs and teaching methods.

It is essential to consider ethical and privacy concerns when implementing AI in e-learning. Issues like data security, algorithmic bias, and the responsible use of AI should be carefully addressed to ensure the benefits of AI in education are maximized while minimizing potential risks.

In summary, the integration of AI into e-learning has the potential to revolutionize education by providing personalized, adaptive, and efficient learning experiences for students and more effective teaching tools for educators.