Operationalizing the C’s of Teamwork in an Intelligent Tutoring System

One of the difficulties in creating a team-focused intelligent tutoring system (ITS) is defining the measures used to assess the team’s performance. While the team research literature offers nine C’s of teamwork to consider, e.g., cooperation, communication, etc., it can also be difficult to implement these in real-world practice. This paper reviews the approach used in three team ITSs in which the C’s were used, offering guidance for future implementation of team tutors.

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Online Pedagogical Tutorial Tactics Optimization Using Genetic-Based Reinforcement Learning

The Scientific World JOURNAL ◽

10.1155/2015/352895 ◽

2015 ◽

Vol 2015 ◽

pp. 1-11 ◽

Cited By ~ 2

Author(s):

Hsuan-Ta Lin ◽

Po-Ming Lee ◽

Tzu-Chien Hsiao

Keyword(s):

Online Learning ◽

Reinforcement Learning ◽

Real World ◽

Intelligent Tutoring ◽

Intelligent Tutoring System ◽

Rule Discovery ◽

Learning Gains ◽

Tutoring System

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.

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The Challenges of Building Intelligent Tutoring Systems for Teams

Proceedings of the Human Factors and Ergonomics Society Annual Meeting ◽

10.1177/1541931213601451 ◽

2016 ◽

Vol 60 (1) ◽

pp. 1981-1985 ◽

Cited By ~ 5

Author(s):

Desmond Bonner ◽

Stephen Gilbert ◽

Michael C. Dorneich ◽

Eliot Winer ◽

Anne M. Sinatra ◽

...

Keyword(s):

Intelligent Tutoring Systems ◽

Intelligent Tutoring ◽

Intelligent Tutoring System ◽

Lessons Learned ◽

Tutoring System ◽

Tutoring Systems ◽

Team Research ◽

Individual Instruction ◽

Individual Task ◽

And Training

Intelligent Tutoring Systems have been useful for individual instruction and training, but have not been widely created for teams, despite the widespread use of team training and learning in groups. This paper reviews two projects that developed team tutors: the Team Multiple Errands Task (TMET) and the Recon Task developed using the Generalized Intelligent Framework for Tutoring (GIFT). Specifically, this paper 1) analyzes why team tasks have significantly more complexity than an individual task, 2) describes the two team-based platforms for team research, and 3) explores the complexities of team tutor authoring. Results include a recommended process for authoring a team intelligent tutoring system based on our lessons learned that highlights the differences between tutors for individuals and team tutors.

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