Human Intelligence Analysis through Perception of AI in Teaching and Learning.

Journal: Computational intelligence and neuroscience
Published Date:

Abstract

Instructional practices have undergone a drastic change as a result of the development of new educational technology. Artificial intelligence (AI) as a teaching and learning technology will be examined in this theoretical review study. To enhance the quality of teaching and learning, the use of artificial intelligence approaches is being studied. Artificial intelligence integration in educational institutions has been addressed, though. Students' assistance, teaching, learning, and administration are also addressed in the discussion of students' adoption of artificial intelligence. Artificial intelligence has the potential to revolutionize our social interactions and generate new teaching and learning methods that may be evaluated in a variety of contexts. New educational technology can help students and teachers better accomplish and manage their educational objectives. Artificial intelligence algorithms are used in a hybrid teaching mode in this work to examine students' attributes and introduce predictions of future learning success. The teaching process may be carried out in a more efficient manner using the hybrid mode. Educators and scientists alike will benefit from artificial intelligence algorithms that may be used to extract useful information from the vast amounts of data collected on human behavior.

Authors

  • Pravin R Kshirsagar
    Department of Artificial Intelligence, G. H. Raisoni College of Engineering, Nagpur, India.
  • D B V Jagannadham
    Department of Electronics and Communication Engineering, Gayatri Vidya Parishad College of Engineering (A), Madhurawada, Visakhapatnam 530041, India.
  • Hamed Alqahtani
    King Khalid University, College of Computer Science, Center of Artificial Intelligence, Unit of Cybersecurity, Abha, Saudi Arabia.
  • Quadri Noorulhasan Naveed
    College of Computer Science, King Khalid University, Abha 61413, Saudi Arabia.
  • Saiful Islam
    Civil Engineering Department, College of Engineering, King Khalid University, Abha 61421, Asir, Saudi Arabia.
  • M Thangamani
    Department of Computer Science Engineering, Kongu Engineering College, Perundurai, India.
  • Minilu Dejene
    Department of Biotechnology, College of Biological and Chemical Engineering, Addis Ababa Science and Technology University, Addis Ababa, Ethiopia.