This study aims to systematically review the development and implementation of Intelligent Tutoring Systems (ITS) in education using a Systematic Literature Review (SLR). Literature searching was conducted through Publish or Perish using Google Scholar and Scopus databases with four ITS-related keyword combinations. Following the PRISMA flow, 864 studies were identified, screened through title-abstract evaluation, and filtered through full-text eligibility, resulting in 20 final articles published between 2018 and 2024. Data extraction covered educational fields, ITS tools, system purposes, user interfaces, evaluation methods, and reported impacts. The findings show that ITS is widely applied in general education, computer science, and mathematics. Most ITS implementations employ web-based platforms and various customized tools. ITS is predominantly used to support adaptive learning, automated assessment, feedback generation, and cognitive skill development. University students and school learners are the primary target users. Evaluation methods commonly include technical assessments, questionnaires, observations, and pre-test/post-test approaches. Overall, the review concludes that ITS continues to evolve as an AI-supported learning environment that enhances personalization, learning effectiveness, and student engagement.
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