title: Online Pedagogical Tutorial Tactics Optimization Using Genetic-Based Reinforcement Learning.
abstract: Tutorial tactics are policies for an Intelligent Tutoring System (ITS) to decide the next action when there are multiple actions available. Recent research has demonstrated that when the learning contents were controlled so as to be the same, different tutorial tactics would make difference in students' learning gains. However, the Reinforcement Learning (RL) techniques that were used in previous studies to induce tutorial tactics are insufficient when encountering large problems and hence were used in offline manners. Therefore, we introduced a Genetic-Based Reinforcement Learning (GBML) approach to induce tutorial tactics in an online-learning manner without basing on any preexisting dataset. The introduced method can learn a set of rules from the environment in a manner similar to RL. It includes a genetic-based optimizer for rule discovery task by generating new rules from the old ones. This increases the scalability of a RL learner for larger problems. The results support our hypothesis about the capability of the GBML method to induce tutorial tactics. This suggests that the GBML method should be favorable in developing real-world ITS applications in the domain of tutorial tactics induction.
authors.affiliation: Institute of Biomedical Engineering, National Chiao Tung University, 1001 University Road, Hsinchu, Taiwan.
authors.forename: Hsuan-Ta
authors.initials: HT
authors.lastname: Lin
authors.affiliation: Institute of Computer Science and Engineering, National Chiao Tung University, 1001 University Road, Hsinchu, Taiwan.
authors.forename: Po-Ming
authors.initials: PM
authors.lastname: Lee
authors.affiliation: Institute of Biomedical Engineering, National Chiao Tung University, 1001 University Road, Hsinchu, Taiwan ; Department of Computer Science, National Chiao Tung University, 1001 University Road, Hsinchu, Taiwan ; Biomedical Electronics Translational Research Center and Biomimetic Systems Research Center, National Chiao Tung University, 1001 University Road, Hsinchu, Taiwan.
authors.forename: Tzu-Chien
authors.initials: TC
authors.lastname: Hsiao
mesh_terms: D000293:Adolescent; D000328:Adult; D000465:Algorithms; D005260:Female; D006801:Humans; D020407:Internet; D007858:Learning; D008297:Male; D009862:Online Systems; D012054:Reinforcement, Psychology; D055815:Young Adult