Abstract
Nowadays in digitized modern world, the growth and adoption of latest technology is rapid and widely used in almost all fields like education, medicine, business etc. When compared to the 90’s generation, the 2K’s generation can easily adapt the latest technologies. According to the WHO’s report, the health and mental status of 2K’s is poor when compared to 90’s generation. Therefore, it is necessary to improve and continuously monitor the health and socio-cognitive skills among young and future generations to adapt those technologies. Hence, the objective of this paper is to predict the behaviors of two different generations on two different aspects such as social and cognitive skills in order to measure the changes between those two generations. First, data is collected based on questionnaire form and data preprocessing is performed. Next, Naïve Bayes (NB) technique is used to classify the parameters and chi-square test is used to identify the correlation between parameters by analyzing the skills. Finally, the experimental results have been proved that the algorithm accurately predicted the skills of those generations and served as a best prediction tool for measurement of socio-cognitive skills.
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Anitha, N., Devi Priya, R., Baskar, C., Devi Surya, V. (2021). Analysis of Socio-cognitive Skills Among 90’s and 2k’s Generations Using Machine Learning Techniques. In: Abraham, A., Sasaki, H., Rios, R., Gandhi, N., Singh, U., Ma, K. (eds) Innovations in Bio-Inspired Computing and Applications. IBICA 2020. Advances in Intelligent Systems and Computing, vol 1372. Springer, Cham. https://doi.org/10.1007/978-3-030-73603-3_21
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