Geeta N.

Work place: Department of Computer Science & Engg, KLE Dr. M.S.Sheshagiri CET, Udyambag, Belgaum-590008, India

E-mail: geeta_malgi@yahoo.co.in

Website:

Research Interests: Computer systems and computational processes, Computer Networks, Parallel Computing, Data Structures and Algorithms

Biography

Prof Geeta N. has graduated in Electronics and Communication Engineering from GIT, Belgaum and completed Post-graduation in Computer Networking from VTU Belgaum. Currently she is working as Assoc. Prof in Computer Science and Engineering at KLE Dr. M.S. Sheshagiri College of Engineering and Technology, Belgaum, Karnataka. Her areas of interest include cognitive computing, brain-computer interface, computer networks and parallel processing.

Author Articles
Enhanced Learning with Abacus and its Analysis Using BCI Technology

By Geeta N. Rahul Dasharath Gavas

DOI: https://doi.org/10.5815/ijmecs.2014.09.04, Pub. Date: 8 Sep. 2014

Although technology is successfully being used these days as a tool to improve education at all levels, its improper usage is curbing the imagination of the student community, leading to a diminution in their thinking capacity and ability to focus and concentrate. As attention is a vital cognitive feature of any learning process, students these days are not coping well with this process. This study attempts to analyse the focusing capacity of students from two different backgrounds; students who have undergone training in mental arithmetic and usage of the abacus and students without any formal mental arithmetic training. The analysis is done through a simple Electroencephalogram (EEG) based gaming software, which measures the time needed for the players to focus and reach a specific attention level. An EEG device measures brain invoked potentials. Due to the availability of low cost commercial grade EEG devices, usage of these devices today, is not confined only to research and clinical purposes, but is being used beyond these applications. This study is an attempt to apply Brain Computer Interface (BCI) Technology to assess cognition. The performance of the first category was found to be better than the second set of students.

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