Counselling Guidance Using Big Data Analytics

Authors

  • Jinka Thirunarayana  M.Tech (CS), Department of CSE, JNTUCEA, Anantapur, Andhra Pradesh, India

Keywords:

CSIR, Big Data, Analysis Of Historical Counseling Data, NAAC

Abstract

Owing to the increasing career paths with the diversified opportunities, choosing a suitable career has become the most important and crucial decision among students and obviously it has turned out as quite difficult decision in students. The Council of Scientific and Industrial Research (CSIR) stated that 40% of immediate graduates are in perplexing state towards their career option. This scenario is an unfortunate and leading the students to choose an inappropriate career path, sometimes the field of work may be irrelevant to their field of study or interest. Therefore, this unfavorable scenario may cause damage to the quality of human resource and productivity of organization as well. Hence, there is a need for counselling guidance to all graduating student community in order to guide them regarding career option at right direction. This proposed analytics would definitely help the students to select an institution and program or course in accordance to their field of interest, personality, trait, mental ability. This proposed analytics would definitely help the students to select an institution and program or course in accordance to their field of interest, personality, trait, mental ability. This module is also much helpful to colleges, managements, and universities to review the historical data pertaining to counselling records and college details.

References

  1. A Roshani, PR Deshmukh, An incremental ensemble of classifiers as a technique for prediction of student's career choice. IEEE Networks & Soft Computing (ICNSC) on 25 September 2015.
  2. A Mustafer, Predicting Instructor performance using data mining technique in higher education. IEEE 2016; 4:2379-2387.
  3. C Ling, R Dymitr, et al. Big Data: Opportunities for Big Data Analytics. IEEE Digital Signal Processing (DSP) on 10 September 2015.
  4. UD Beth, HE Janet, Using Learning Analytics to Predict (and Improve) Student Success: A Faculty Perspective. Journal of Interactive Online Learning 2013; 12:17-26.
  5. KS Lokesh, RS Bhakti, et al. Novel Professional career prediction and recommendation method for individual through analytics on personal traits using C4.5 algorithm. IEEE Communication Technology (GCCT) on 3 December 2015.
  6. M Yannick, X Jie, et al. Predicting Grades. IEEE transactions on signal processing on 15 February 2016
  7. M Jiri, S Jan, AdaBoost. Centre for Machine Perception, Czech Technical University, Prague

Downloads

Published

2018-04-30

Issue

Section

Research Articles

How to Cite

[1]
Jinka Thirunarayana, " Counselling Guidance Using Big Data Analytics, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 3, pp.1645-1649, March-April-2018.