Career guidance tool using deep learning

Abstract

The selection of a suitable career is a significant societal concern, with career counselling playing a vital role in addressing this issue. Students pursuing their undergraduate studies encounter the challenge of selecting a career path. Embarking on a career path not aligned with a students’ preferences can result in diminished job satisfaction, a deficit in skills, and mental strain. This study introduces innovative approaches involving deep learning techniques that has the potential to benefit students. Within the field of education, a substantial volume of data exists, although its utility for students is limited. This research aims to assess student data and provide guidance on the most suitable career for their sustained success. The study employed machine learning algorithms to provide career options for students with emphasis being placed on students pursuing or have graduated in Information Technology (IT) in institutions of higher learning. The research used agile software development methodology as the preferred software development methodology. The model was developed using MLP classifier a class of deep learning algorithms. The developed model achieved an accuracy of 99.93% surpassing the accuracy of all prediction models in career guidance domain. The developed tool will exert a significant influence on both the institutions and society at large.

Keywords: Career Guidance, Data Mining, Deep Learning, Information Technology, Machine Learning, Undergraduates.