Reinforcement learning of pedagogical policies in adaptive and intelligent educational systems

Abstract

Adaptive and intelligent educational systems Distance learning Artificial intelligence applied to intelligent tutoring systems a b s t r a c tIn an adaptive and intelligent educational system (AIES), the process of learning pedagogical policies according the students needs fits as a Reinforcement Learning (RL) problem. Previous works have dem onstrated that a great amount of experience is needed in order for the system to learn to teach properly, so applying RL to the AIES from scratch is unfeasible. Other works have previously demonstrated in a the oretical way that seeding the AIES with an initial value function learned with simulated students reduce the experience required to learn an accurate pedagogical policy. In this paper we present empirical results demonstrating that a value function learned with simulated students can provide the AIES with a very accurate initial pedagogical policy. The evaluation is based on the interaction of more than 70 Computer Science undergraduate students, and demonstrates that an efficient and useful guide through the contents of the educational system is obtained.

Systematic review of research on artificial intelligence applications in higher education – where are the educators?

“…Teaching course content The disciplines that are taught through adaptive systems are diverse, including environmental education (Huang, 2018), animation design (Yuanyuan & Yajuan, 2014), language learning (Jia, 2009;Vlugter et al, 2009), Computer Science (Iglesias, Martinez, Aler, & Fernandez, 2009) and Biology (Chaudhri et al, 2013). Walsh, Tamjidul, and Williams (2017), however, present an adaptive system based on machine learning-human machine learning symbiosis from a descriptive perspective, without specifying any discipline.…”

Artificial Intelligence in Education (AIEd): a high-level academic and industry note 2021

“…These algorithms have achieved breakthrough performance in multiple domains including games [ 66 ], healthcare [ 14 ] and robotics [ 34 ]. This presents a great opportunity for AI’s applications in education for further enhancing students’ learning outcomes, reducing teachers’ workloads [ 30 ] and making learning personalized [ 64 ], interactive and fun [ 50 , 53 ] for teachers and students.…”

La llegada de la inteligencia artificial a la educación

“…Aprendizaje de refuerzo de las políticas pedagógicas de adaptación y Sistemas educativos inteligentes de Ana Iglesias, Paloma Martínez, Ricardo Aler, Fernando Fernández del Departamento de Informática, de la Universidad Carlos III de Madrid [14], en la cual: "Presentamos resultados empíricos que demuestran que una función de valor aprendida con estudiantes simulados puede proporcionar al AIES una política pedagógica inicial muy precisa… permitiendo que el sistema educativo se adapte tutoría a las necesidades de los alumnos. "…”