Journal of Advanced Research in Operating System Development and Evolution

An AI-Powered Career Guidance and Skill Gap Analysis System for Students

2026-09-17T07:27:04+00:00

The fast development of technology and changing industry demands have made career selection challenging for students. Several students face difficulty in recognizing relevant career options and understanding the gap between their current abilities and industry demands. Common career counselling techniques generally offer general suggestions and do not have customized guidance. This paper proposes an AI-Powered Career Guidance and Skill Gap Analysis System for Students. The system allows a student to select a target career role and enter existing and additional skills; it then compares the student's skill profile with the competency requirements of the selected role, computes a skill match score, identifies missing and partially covered skills, and generates AI-assisted, individualized guidance for closing the identified gaps. A preliminary evaluation using five manually constructed test profiles shows that the prototype can distinguish between profiles with different levels of alignment to a selected career role, with skill match scores ranging from 7% to 55% and a corresponding career-readiness indicator ranging from 5% to 39%. The developed application combines AI-powered skill-gap analysis and personalized guidance into a single structure to help students make knowledgeable career choices and increase student employability.

AI-BASED PERSONALIZED LEARNING AND STUDENT PERFORMANCE PREDICTION SYSTEM

2026-09-17T10:36:49+00:00

Artificial Intelligence (AI) is becoming increasingly useful in the field of education. Different students have different learning abilities, strengths, and weaknesses, but traditional education systems often provide the same learning materials and support to all students. This can make it difficult for teachers to identify students who need additional academic support. This paper proposes an AI-driven personalized learning system for student performance prediction and early academic intervention. The proposed system uses student information such as marks, attendance, assignment scores, quiz scores, study hours, and learning activities to analyze academic performance. Machine learning techniques are used to predict future student performance and identify students who may be at risk of poor academic results. Based on the student's performance and weak areas, the system provides personalized learning recommendations such as study materials, practice questions, videos, and quizzes. The system also helps teachers monitor student progress and identify students who need additional support at an early stage. Different machine learning algorithms can be compared to determine a suitable model for student performance prediction. The proposed framework connects prediction, learning-gap identification, personalized recommendation, and early intervention in a single workflow. The approach can support data-driven educational decisions while keeping teachers involved in the final interpretation and intervention process.

The Changing Landscape Of Employment In India Due To AI And Automation

2026-09-17T07:22:14+00:00

AI and automation are changing the way people work around the world. While they can improve productivity and create new job opportunities, they may also replace some routine jobs and increase inequality. This study examines how AI and automation are affecting job loss, job creation, and changes in existing jobs. It highlights the growing need for new skills, better education, and workforce training.

Overall, AI and automation are not simply eliminating jobs; they are changing the nature of work and creating a need for workers and governments to adapt to the future.