Link to the University of Pittsburgh Homepage
Link to the University Library System Homepage Link to the Contact Us Form

Empirically evaluating the application of reinforcement learning to the induction of effective and adaptive pedagogical strategies

Chi, M and Vanlehn, K and Litman, D and Jordan, P (2011) Empirically evaluating the application of reinforcement learning to the induction of effective and adaptive pedagogical strategies. User Modeling and User-Adapted Interaction, 21 (1-2). 137 - 180. ISSN 0924-1868

[img] Plain Text (licence)
Available under License : See the attached license file.

Download (1kB)


For many forms of e-learning environments, the system's behavior can be viewed as a sequential decision process wherein, at each discrete step, the system is responsible for selecting the next action to take. Pedagogical strategies are policies to decide the next system action when there are multiple ones available. In this project we present a Reinforcement Learning (RL) approach for inducing effective pedagogical strategies and empirical evaluations of the induced strategies. This paper addresses the technical challenges in applying RL to Cordillera, a Natural Language Tutoring System teaching students introductory college physics. The algorithm chosen for this project is a model-based RL approach, Policy Iteration, and the training corpus for the RL approach is an exploratory corpus, which was collected by letting the system make random decisions when interacting with real students. Overall, our results show that by using a rather small training corpus, the RL-induced strategies indeed measurably improved the effectiveness of Cordillera in that the RL-induced policies improved students' learning gains significantly. © 2011 Springer Science+Business Media B.V.


Social Networking:
Share |


Item Type: Article
Status: Published
CreatorsEmailPitt UsernameORCID
Chi, M
Vanlehn, K
Litman, Ddlitman@pitt.eduDLITMAN
Jordan, P
Centers: Other Centers, Institutes, Offices, or Units > Learning Research & Development Center
Date: 1 April 2011
Date Type: Publication
Journal or Publication Title: User Modeling and User-Adapted Interaction
Volume: 21
Number: 1-2
Page Range: 137 - 180
DOI or Unique Handle: 10.1007/s11257-010-9093-1
Schools and Programs: Dietrich School of Arts and Sciences > Computer Science
Dietrich School of Arts and Sciences > Intelligent Systems
Refereed: Yes
ISSN: 0924-1868
Date Deposited: 30 Jul 2014 20:34
Last Modified: 02 Feb 2019 15:59


Monthly Views for the past 3 years

Plum Analytics

Actions (login required)

View Item View Item