Behrooz Mostafavi

Exploring the Effect of Autoencoder Based Feature Learning for a Deep Reinforcement Learning Policy for Providing Proactive Help

ARTIFICIAL INTELLIGENCE IN EDUCATION. POSTERS AND LATE BREAKING RESULTS, WORKSHOPS AND TUTORIALS, INDUSTRY AND INNOVATION TRACKS, PRACTITIONERS, DOCTORAL CONSORTIUM AND BLUE SKY, AIED 2023, Vol. 1831, pp. 278–283.

Impact of Learning a Subgoal-Directed Problem-Solving Strategy Within an Intelligent Logic Tutor

ARTIFICIAL INTELLIGENCE IN EDUCATION, AIED 2023, Vol. 13916, pp. 389–400.

Investigating the Impact of Backward Strategy Learning in a Logic Tutor: Aiding Subgoal Learning Towards Improved Problem Solving

International Journal of Artificial Intelligence in Education, 8.

Improving Learning & Reducing Time: A Constrained Action-Based Reinforcement Learning Approach

Improving Learning & Reducing Time: A Constrained Action-Based Reinforcement Learning Approach. PROCEEDINGS OF THE 26TH CONFERENCE ON USER MODELING, ADAPTATION AND PERSONALIZATION (UMAP'18), pp. 43–51.

An analysis of feature selection and reward function for model-based reinforcement learning

Intelligent tutoring systems, its 2016, 0684, 504–505.

Combining Worked Examples and Problem Solving in a Data-Driven Logic Tutor

INTELLIGENT TUTORING SYSTEMS, ITS 2016, Vol. 9684, pp. 347–353.

Data-driven Proficiency Profiling - Proof of Concept

LAK '16 CONFERENCE PROCEEDINGS: THE SIXTH INTERNATIONAL LEARNING ANALYTICS & KNOWLEDGE CONFERENCE, pp. 324–328.

Evolution of an Intelligent Deductive Logic Tutor Using Data-Driven Elements

INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE IN EDUCATION, 27(1), 5–36.

Data-driven worked examples improve retention and completion in a logic tutor

Artificial intelligence in education, aied 2015, 9112, 726–729.