Computers as Cognitive Tools
Fearnot!: an experiment in emergent narrative
Lecture Notes in Computer Science
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
THESPIAN: An Architecture for Interactive Pedagogical Drama
Proceedings of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology
Serious Use of a Serious Game for Language Learning
Proceedings of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work
Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
Toward Scenario Adaptation for Learning
Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
A framework for narrative adaptation in interactive story-based learning environments
Proceedings of the Intelligent Narrative Technologies III Workshop
BiLAT: A Game-Based Environment for Practicing Negotiation in a Cultural Context
International Journal of Artificial Intelligence in Education
Integrating learning and engagement in narrative-centered learning environments
ITS'10 Proceedings of the 10th international conference on Intelligent Tutoring Systems - Volume Part II
Director agent intervention strategies for interactive narrative environments
ICIDS'11 Proceedings of the 4th international conference on Interactive Digital Storytelling
Predicting student self-regulation strategies in game-based learning environments
ITS'12 Proceedings of the 11th international conference on Intelligent Tutoring Systems
User Modeling and User-Adapted Interaction
| Hi-index | 0.01 |
Narrative-centered learning environments introduce novel opportunities for supporting student problem solving and learning. By incorporating cognitive tools into plots and character roles, narrative-centered learning environments can promote self-regulated learning in a manner that is transparent to students. In order to adapt narrative plots to explicitly support effective cognitive tool-use, narrative-centered learning environments need to be able to make early predictions about how effectively students will utilize learning resources. This paper presents results from an investigation into machine-learned models for making early predictions about students' use of a specific cognitive tool in the Crystal Island learning environment. Multiple classification models are compared and discussed. Findings suggest that support vector machine and naïve Bayes models offer considerable promise for generating useful predictive models of cognitive tool use in narrative-centered learning environments.