AI in higher education

AI in higher education

The application of Artificial Intelligence (AI) in higher education has the potential to revolutionise teaching and learning by creating personalised, adaptive, and engaging learning experiences for students, and by improving efficiency, productivity, and decision-making for educators and institutions. It enables institutions and educators to transcend multiple barriers, and has far-reaching uses, particularly in the context of the National Education Policy (NEP) 2020.

Universal education: The NEP 2020 emphasises equitable and inclusive education, allowing students from all backgrounds access to education in the same way. With AI-empowered education, students with different abilities can benefit from natural language processing tools that convert written text into audio or other accessible formats. Further, courses can be delivered in local languages, thus allowing institutions to cater to students from across the country.

Customised learning: AI-powered adaptive learning platforms use algorithms to tailor course content and assignments to the needs and abilities of individual. Thus, it helps identify areas where a student may be struggling, and adjust the material to suit their learning style.

Real-time assessment: AI-powered systems can enable faculty to get real-time feedback about student behaviour, participation and engagement, and even help develop lesson plans by taking into account gaps in understanding. This can empower faculty to create or modify their approach within the approved framework.

Admission support: Many universities now use AI-powered chatbots to provide 24/7 support by answering questions about admissions, financial aid, and course registration. This allows staff to focus on more complex issues and reduces wait time for students.

Performance assessment: AI-powered predictive analytics can help universities identify students who may be at the risk of dropping out based on data about attendance, grades, and so on. This information can then be used to provide targeted support to help them stay on track.

Doctoral research: The use of AI tools in doctoral research or completing assignments is a matter of debate in the academic community. Doctoral research is meant to be original and using AI tools can lead to academic dishonesty and plagiarism. The same issue arises when it comes to college assignments that are designed to test students’ understanding and critical thinking skills. AI tools may not be able to capture the nuances and complexities of certain subjects. In such cases, it may be necessary to rely on traditional research methods to ensure the validity and reliability of the research findings. Another problem with AI-generated responses is the inherent bias or incompleteness of the source information, which can affect the accuracy and usefulness of the final submission.