Swanand K. Navandar

Work place: Dr. Babasaheb Ambedkar Technological University, Lonere, Raigad, 402103, India

E-mail: swanandnavandar@gmail.com

Website: http://orcid.org/0000-0003-2986-3427

Research Interests: Human-Computer Interaction, Computer systems and computational processes, Artificial Intelligence, Computational Learning Theory, Data Mining, Data Structures and Algorithms, Analysis of Algorithms

Biography

Swanand K. Navandar received his Bachelor of Engineering degree in Information Technology from Savitribai Phule Pune University and Master of Technology degree in Computer Engineering from Dr. Babasaheb Ambedkar Technological University. He is pursuing his Ph.D. degree from Dr. Babasaheb Ambedkar Technological University, lonere, India. His area of interest includes Cognitive Science, Artificial Intelligence, Data mining, Machine learning, Algorithms, Internet of Things and Human-computer Interaction, etc

Author Articles
A Performance Analysis of the Impact of Prior-Knowledge on Computational Thinking

By Swanand K. Navandar Arvind W. Kiwelekar Manjushree D. Laddha

DOI: https://doi.org/10.5815/ijmecs.2023.02.05, Pub. Date: 8 Apr. 2023

Previously acquired knowledge plays a significant role to learn new knowledge and skills.  Previously acquired knowledge consists of Short-term memory and Long-term memory.  Though it is a well-accepted learning phenomenon, it is challenging to empirically analyse the impact of prior knowledge on learning. In this paper, we use two systems models for human thinking proposed by Nobel Laureate Prof. Daniel Kahneman. This is a  model for human cognition which uses two systems of thinking—the first being quick and intuitively known as fast thinking and the second being slow and tedious known as slow thinking. While slow thinking uses long-term memory, fast thinking uses short-term memory.  The impact of prior knowledge of programming language is analyzed to learn a new programming language. We assigned a learning task to two different groups with one having learnt a programming language i.e. senior students and the second group without any prior knowledge of programming language i.e. freshers. The impact of prior knowledge is measured and compared against the time taken to answer quizzes.

[...] Read more.
Other Articles