Bridging the Career Guidance Gap in India: A Tech-Driven Approach with CareerNeeti
Aditya Tiwari, Abhishek Tiwari, Hariom Upadhyay
Department of Computer Science & Engineering, R.D. Engineering College, Ghaziabad, India.
Abstract
The primary purpose of this study is to improve students' career decision-making through the provision of data-driven and student-centric recommendations using artificial intelligence. We used a mixed-method research methodology featuring surveys, user interviews, and real-world platform testing to gain insights into user needs and evaluate system effectiveness. Based on a representative sample of higher secondary and undergraduate students, the platform's recommendation engine powered by AI was tested.
We do this in a world where career decisions have become more complex than ever before for students and there is a need for better and more tailored career counselling platforms. Conventional systems tend to offer one-size-fits-all solutions, unable to cater to the nuanced and multi-faceted goals of students. To address this gap, this research presents Careerneeti, an AI-driven career guidance platform that provides tailored career recommendations, expert consultations, curated learning resources, and features with a focus on accessibility.
Early results show that students who know their power match also improve common sense accuracy and confidence in career decisions compared to peer (swipe left, swipe right)-based recommendations. Moreover, the study substantiates that students appreciate connection to experts and the availability of customized resources when it comes to their career exploration.
Our research adds to the existing body of knowledge by proposing a solution that is both scalable and easily accessible for building future career guidance systems. It also highlights the increasing use of AI in shaping the education and career decisions of individuals, paving the way for more personalized and accessible career guidance solutions. The results prove that career decisions made based on AI recommendations are much more accurate compared to those without, aligning with prior studies showing the transformational impact AI can have on educational decision-making [1].
Keywords: career guidance, AI-driven recommendation, personalized learning, student decision-making.
