USING DATA-DRIVEN APPROACHES TO ADDRESS PSYCHOLOGICAL BARRIERS IN INTERDISCIPLINARY EDUCATION: BRIDGING SOCIAL SCIENCES AND TECHNOLOGY FOR EQUITABLE LEARNING

The rapid evolution of job markets needs continuous skill development to ensure that individuals stay relevant and adaptable in the competitive dynamic market. In the era of Artificial Intelligence, transformative fields have significant opportunities for learners from different academic backgrounds. However, non-technical students face psychological barriers which hinders their ability to learn these high demand skills. This study explores these barriers qualitatively, and identifies challenges faced by non-technical learners and the strategies to overcome them. The study conducted through a questionnaire filled out by 58 respondents finds that many students successfully overcome these obstacles by leveraging AI tools and seeking mentorship that simplified complex concepts and boosted their confidence. Upon these insights, this research paper proposes the use of data driven approaches to address psychological barriers in interdisciplinary education. The creation of customized learning programs, and tools designed to help students evaluate potential outcomes and benefits if they transit in this with their current educational background could play a major role in motivating continuous skill development and make the technical field more accessible. By addressing these psychological and practical challenges faced by non-technical learners. This innovative approach will help break the hurdle and will make people work confidently in any dynamic landscape of working professionals.