AI-Driven Recommender Systems for Personalized Entrepreneurial Learning in Startup Education

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Authors: Ravikumar Natarajan, Aarthi Selvakumar, Umid Otajanov, Makhmudov Asliddin
Cited by: 1
References: 44

Abstract

The concept of Artificial Intelligence is changing the nature of entrepreneurial education because it allows personalized and adaptable learning based on recommender systems. This chapter will discuss the way AI-based recommendation models are developed and implemented to analyze the profile of learners, their behaviors, and data of the ecosystem to provide specific learning pathways. Through a combination of methods like collaborative filtering, content-based approaches, and deep learning, the systems increase engagement, skills improvement, and start up preparedness. The chapter discusses also online platform and incubator case studies, where the learning outcomes were improved in reality. The issues associated with privacy, bias, and assessment are addressed, as well as how AI-driven entrepreneurial learning systems can be scaled and ethically sound in the future.

Fields of Study & Subjects

Entrepreneurship Studies and Influences E-Learning and Knowledge Management AI in Service Interactions

Publication details

Journal / source
Advances in computational intelligence and robotics book series
Publisher
IGI Global Scientific Publishing
Pages
117–158
Publication date
30 April 2026
Document type
Book chapter