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Adopting AI in higher education

Adopting AI in higher education As the cost of computing decreases as time passes as computing costs decrease, the integration of AI applications in higher education will become a necessity. In the article below we’ll examine the three areas in which the use of AI/ML will provide instant advantages. The three areas include:

  • Automatization of repetitive tasks
  • Student registration prediction and retention
  • Individualized education

Automating repetitive tasks: In all the major institutions, faculty members tend to spend a lot of their time working on back-end tasks like graded assignments, checking for plagiarism, responding to questions in forums, and making assessments. These tasks can be automated with AI systems. This helps faculty by allowing them enough time to engage directly with the students. It is the AI chatbot “Jill”, used for responding to questions on forums on behalf of Georgia University with a success rate of 97%, and Turnitin (plagiarism screening software) are just two instances of success that have demonstrated the benefits of automating routine tasks.

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Retention and prediction of student registration The main challenge facing many universities is to complete the enrollment of students across every department. The efficiency of registration and student enrolment can be predicted with the creation of deep learning models that analyze the previous data and provide the list of students most likely to complete the course. The model can also provide an overview of those who require preparation for employment. These precise reports assist institutions to gain an assessment of the qualifications of their students. They also help them make the right decisions and enhance their overall effectiveness.

The effectiveness of learning is enhanced by ensuring that individual attention is provided to all students. The majority of universities face numerous issues, including students who are disengaged as well as high dropout rates as well as the lack of effectiveness of a conventional “one-size-fits-all” approach to education. With the assistance of the academic staff, AI systems can provide students with the opportunity to develop their educational path, as well as provide constant monitoring. The AI systems continuously adapt themselves to make learning easier and more enjoyable for the user at their own pace of learning and reduce the rate of dropping out. Digital technology has enabled the collection of an enormous amount of data. As a result learning personalization could be an important application in the coming years.

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In a nutshell, AI promises to be an integral component of the learning and teaching procedure in universities. Collaboration between academics, researchers as well as government and industry will bring about the next generation of paradigm shifts in education that will result in a greater increase the size of education, making it more personal and improving the learning outcomes.

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