Intelligent Tutoring Systems in Smart Learning Environments for Higher Education: A Systematic Literature Review

E-learning integrates information and communication technologies on technological platforms to facilitate access to learning, as well as make it interactive and personalized. Within e-learning, intelligent tutoring systems (ITS) use artificial intelligence to adapt content and activities to the needs of each student, perform academic monitoring and facilitate interaction with virtual learning objectives, allowing for interaction between teachers, students, and intelligent tutors. Smart learning environments (SLE) integrate ITS to create innovative, motivating, and effective learning experiences, based on educational theories and models for the teaching-learning process under the online modality. This article presents a systematic literature review (SLR) on these topics, with the objective of identifying the trends, challenges, and research opportunities in this field. Educational theories that support e-learning and promote student interaction with virtual platforms are analyzed. Student-centered ITS models focused on learning styles, and the integration of data mining and learning analytics, as well as strategies for the implementation and validation of intelligent systems in SLEs. The design of a self-adaptive architecture in the Moodle platform is proposed, for the academic monitoring of students in the online modality with the use of autonomous agents. Finally, it is concluded that the research should be geared towards adaptive learning, to perform academic monitoring focused on the student and their learning styles within the SLE.