An Interest-Driven Adaptive Learning Platform for Career Growth

Digital learning tools have grown fast, opening fresh chances to build abilities and move work lives forward. Still, without clear direction or tailored routes, people frequently feel lost, waste time, learn poorly, then lose drive. Many current setups hand out one-size-fits-all material, ignoring what users care about, aim for, or how well they’re doing - slowing real advancement. What follows introduces a system shaped by personal interests: an adaptive platform meant to guide career-focused learning in ways that fit varied starting points. Picking what you care about shapes how the journey begins. From there, tasks show up tailored just right - tests pop in now and then, exercises follow each week, steps line up ahead. Watched closely, every try shifts what comes next - harder bits appear when ready, easier ones return if needed. Notes come back after each move, pointing out where things click and where they stall. Learning sticks better this way - not forced, but shaped around real effort and pace. Growth keeps going because the space bends to fit who's using it, building ability without pause.

Keywords: Adaptive Learning, Personalized Learning, Interest-Based Learning, Career Growth, Skill Development, Learning Path Generation, Performance Analysis, Recommendation System, E-Learning Platform, Artificial Intelligence

Brundha S, Ashwini C, Nagamma M (2026). An Interest-Driven Adaptive Learning Platform for Career Growth. International Journal of Innovative Research in Multidisciplinary Education & Technology (IJIRMET), 11(3).