Spoken Versus Typed Human and Computer Dialogue Tutoring

@article{Litman2006SpokenVT,
  title={Spoken Versus Typed Human and Computer Dialogue Tutoring},
  author={Diane J. Litman and Carolyn Penstein Ros{\'e} and Katherine Forbes-Riley and Kurt VanLehn and Dumisizwe Bhembe and Scott Silliman},
  journal={Int. J. Artif. Intell. Educ.},
  year={2006},
  volume={16},
  pages={145-170}
}
While human tutors typically interact with students using spoken dialogue, most computer dialogue tutors are text-based. We have conducted 2 experiments comparing typed and spoken tutoring dialogues, one in a human-human scenario, and another in a human-computer scenario. In both experiments, we compared spoken versus typed tutoring for learning gains and time on task, and also measured the correlations of learning gains with dialogue features. Our main results are that changing the modality… 
View via Publisher
cs.pitt.edu
144 Citations
Highly Influential Citations
18
Background Citations
82
Methods Citations
28
Results Citations
13

144 Citations

Citation Type

Citation Type

Dialogue-Learning Correlations in Spoken Dialogue Tutoring
TLDR
It is shown that the introduction of a new concept into the dialogue by students positively correlates with learning, but student attempts at deeper reasoning do not, and the human tutor's attempts to direct the dialogue negatively correlate with learning.
Recognizing student emotions and attitudes on the basis of utterances in spoken tutoring dialogues with both human and computer tutors
Predicting Student Emotions in Computer-Human Tutoring Dialogues
TLDR
The utility of speech and lexical features for predicting student emotions in computer-human spoken tutoring dialogues is examined and the results of machine learning experiments using these features alone or in combination to predict various categorizations of the annotated student emotions are compared.
Correlations between dialogue acts and learning in spoken tutoring dialogues
TLDR
While the use of dialogue act n-grams is a promising method for examining correlations between dialogue behavior and learning, specific findings can differ in human versus computer tutoring, with the latter better motivating adaptive strategies for implementation.
Speech recognition performance and learning in spoken dialogue tutoring
Speech recognition errors have been shown to negatively correlate with user satisfaction in evaluations of task-oriented spoken dialogue systems. In the domain of tutorial dialogue systems, however,…
Toward Spoken Human–Computer Tutorial Dialogues
TLDR
The results indicated that enhanced content coverage was achieved in the spoken condition; learning gains for both modalities were on par and greater than a no-instruction control; and simulated speech recognition errors had differential impacts on the fidelity of different semantic algorithms.
Turn-Taking Behavior in a Human Tutoring Corpus
TLDR
The experimental results show that female students speak simultaneously longer with the tutor than male students, female activities are less than male activities and also the tutor speaks longer with students who have lower pre-test score.
Expert vs. Non-expert Tutoring: Dialogue Moves, Interaction Patterns and Multi-utterance Turns
TLDR
The differences between an expert and non-expert tutors are explored through the analysis of individual dialogue moves, tutorial interaction patterns and multi-utterance turns to show what behaviors constitute expertise.
Improving the Efficiency of Dialogue in Tutoring.
Running Head : IMPROVING TUTORING EFFICIENCY 1 Improving the Efficiency of Dialogue in Tutoring
TLDR
The results show that dialogue-based intelligent tutoring systems could be designed in a more efficient manner to maximize learning and minimize the cost of time-on-task.
...
...

References

SHOWING 1-10 OF 93 REFERENCES
Dialogue-Learning Correlations in Spoken Dialogue Tutoring
TLDR
It is shown that the introduction of a new concept into the dialogue by students positively correlates with learning, but student attempts at deeper reasoning do not, and the human tutor's attempts to direct the dialogue negatively correlate with learning.
Predicting Student Emotions in Computer-Human Tutoring Dialogues
TLDR
The utility of speech and lexical features for predicting student emotions in computer-human spoken tutoring dialogues is examined and the results of machine learning experiments using these features alone or in combination to predict various categorizations of the annotated student emotions are compared.
Speech recognition performance and learning in spoken dialogue tutoring
Speech recognition errors have been shown to negatively correlate with user satisfaction in evaluations of task-oriented spoken dialogue systems. In the domain of tutorial dialogue systems, however,…
The Role of Why Questions in Effective Human Tutoring
It is undoubtedly true that one prominent component of effective human tutoring is collaborative dialogue between student and tutor [7, 12]. Nevertheless, many important questions remain to be…
The Role of Initiative in Tutorial Dialogue
TLDR
Surprisingly, students had initiative more of the time in the didactic dialogues than in the Socratic dialogues, and interactivity had a positive correlation with learning.
ITSPOKE: An Intelligent Tutoring Spoken Dialogue System
TLDR
ITSPOKE is a spoken dialogue system that uses the Why2-Atlas text-based tutoring system as its "back-end" and generates an empirically-based understanding of the ramifications of adding spoken language capabilities to text- based dialogue tutors.
CIRCSIM-Tutor: An Intelligent Tutoring System Using Natural Language Dialogue
TLDR
CIRCSIM-Tutor version 2, a dialogue-based intelligent tutoring system (ITS), is nearly five years old and can handle a variety of syntactic constructions and lexical items, including sentence fragments and misspelled words.
Learning from a Computer Tutor with Natural Language Capabilities
TLDR
Using a pre-test/post-test paradigm, it is demonstrated that significant learning occurs during a 1 hr interaction with the CIRCSIM-Tutor program.
AutoTutor: A simulation of a human tutor
Learning from human tutoring
...
...