Artificial intelligence and tutoring systems: computational and cognitive approaches to the communication of knowledge
Making computer tutors more like humans
Journal of Artificial Intelligence in Education
Andes: A Coached Problem Solving Environment for Physics
ITS '00 Proceedings of the 5th International Conference on Intelligent Tutoring Systems
A Virtual Environment for Learning to Pilot Remotely Operated Vehicles
VSMM '97 Proceedings of the 1997 International Conference on Virtual Systems and MultiMedia
The cognitive skill of coaching collaboration
CSCL '99 Proceedings of the 1999 conference on Computer support for collaborative learning
Correlations between dialogue acts and learning in spoken tutoring dialogues
Natural Language Engineering
The Andes Physics Tutoring System: Lessons Learned
International Journal of Artificial Intelligence in Education
Spoken Versus Typed Human and Computer Dialogue Tutoring
International Journal of Artificial Intelligence in Education
Responding to Student Uncertainty in Spoken Tutorial Dialogue Systems
International Journal of Artificial Intelligence in Education
The Behavior of Tutoring Systems
International Journal of Artificial Intelligence in Education
Dialogue-Learning Correlations in Spoken Dialogue Tutoring
Proceedings of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology
What Level of Tutor Interaction is Best?
Proceedings of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work
Comparing Linguistic Features for Modeling Learning in Computer Tutoring
Proceedings of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work
The Influence of Learner Characteristics on Task-Oriented Tutorial Dialogue
Proceedings of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work
Out of the Lab and into the Classroom: An Evaluation of Reflective Dialogue in Andes
Proceedings of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work
Learner characteristics and feedback in tutorial dialogue
EANL '08 Proceedings of the Third Workshop on Innovative Use of NLP for Building Educational Applications
Using Natural Language Processing to Analyze Tutorial Dialogue Corpora Across Domains Modalities
Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
To Elicit Or To Tell: Does It Matter?
Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
Discourse structure and performance analysis: beyond the correlation
SIGDIAL '09 Proceedings of the SIGDIAL 2009 Conference: The 10th Annual Meeting of the Special Interest Group on Discourse and Dialogue
BiLAT: A Game-Based Environment for Practicing Negotiation in a Cultural Context
International Journal of Artificial Intelligence in Education
Towards Systems That Care: A Conceptual Framework based on Motivation, Metacognition and Affect
International Journal of Artificial Intelligence in Education
Characterizing the effectiveness of tutorial dialogue with hidden markov models
ITS'10 Proceedings of the 10th international conference on Intelligent Tutoring Systems - Volume Part I
Reflective tutoring for immersive simulation
ITS'06 Proceedings of the 8th international conference on Intelligent Tutoring Systems
International Journal of Artificial Intelligence in Education - Special issue on Best of ITS 2010
Reformulating student contributions in tutorial dialogue
INLG '12 Proceedings of the Seventh International Natural Language Generation Conference
Using reflective text to improve qualitative physics tutoring
International Journal of Learning Technology
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Two studies investigated the role and effectiveness of post-solution, reflective dialogues in physics tutorials. The first study investigated the instructional roles of post-solution discussions, their relationship to problem-solving discussions, and features that predict learning. Seven tutors individually guided 15 students as they worked on problems in the Andes physics tutoring system. Tutors adapted the post-solution discussions to students? ability levels and their performance on the current problem. Qualitative analysis of the transcripts revealed several roles of the post-solution dialogues - most prominently, explaining conceptual knowledge and integrating this knowledge with strategic, problem-solving knowledge. The number of post-solution discussions students had with their tutor, the number of discussions that abstracted from the current problem, and the number of tutor-initiated discussions predicted transfer, as measured by pre-test to post-test gain score on problems similar to those solved in Andes. Several tutorial strategies that are distributed between problem solving and post-solution reflection were identified. A framework for describing distributed plans for reflection is proposed based on these analyses. The second study investigated whether reflection questions such as those asked by the tutors in the first study lead to better conceptual understanding and problem-solving ability, as measured by overall gain scores and gain scores on conceptual and quantitative questions. It also examined whether human tutor-provided feedback on students?responses - with its often multi-exchange, dialectic character - is more effective than a single, canned explanation. Forty-six students solved problems in Andes in one of three conditions: with no reflection questions after problem solving, with reflection questions discussed with human tutors, or with the same reflection questions followed by canned feedback (without a human tutor). Students learned more with reflection questions and feedback than without, but the canned feedback and human tutored conditions did not differ significantly. Hence, overall, these studies support the practice of implementing post-solution reflective activities in intelligent tutoring systems, but call into question the need for natural-language processing techniques to support these activities.