An Integrated System for Real-Time Student Assessment and Career Guidance Using Neural Networks in Computing Disciplines
Researchers have developed an AI-driven system to help undergraduate students in computer science and software engineering identify suitable career paths. The system integrates a Career Guidance Expert (CGE) with a Web-Based Student Assessment (WBSA) platform. The CGE uses a Multilayer Perceptron (MLP) model, achieving 94.71% validation accuracy in predicting career paths, while the WBSA platform facilitates student-faculty interaction through assessments and mentorship. AI
IMPACT This system could improve student outcomes by providing personalized career recommendations, potentially reducing graduate unemployment in the IT sector.