The Experts below are selected from a list of 12852 Experts worldwide ranked by ideXlab platform

Scott Silliman - One of the best experts on this subject based on the ideXlab platform.

  • spoken versus typed human and Computer Dialogue tutoring
    Artificial Intelligence in Education, 2006
    Co-Authors: Diane J Litman, Kurt Vanlehn, Carolyn Penstein Rose, Kate Forbesriley, Dumisizwe Bhembe, Scott Silliman
    Abstract:

    While human tutors typically interact with students using spoken Dialogue, most Computer Dialogue tutors are text-based. We have conducted two 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 from text to speech caused changes in the learning gains, time and superficial Dialogue characteristics of human tutoring, but for Computer tutoring it made less difference.

  • spoken versus typed human and Computer Dialogue tutoring
    Lecture Notes in Computer Science, 2004
    Co-Authors: Diane J Litman, Kurt Vanlehn, Carolyn Penstein Rose, Kate Forbesriley, Dumisizwe Bhembe, Scott Silliman
    Abstract:

    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 from text to speech caused large differences in the learning gains, time and superficial Dialogue characteristics of human tutoring, but for Computer tutoring it made less difference.

Jiyou Jia - One of the best experts on this subject based on the ideXlab platform.

  • the generation of textual entailment with nlml in an intelligent Dialogue system for language learning csiec
    International conference natural language processing, 2008
    Co-Authors: Jiyou Jia
    Abstract:

    This paper introduces the generation of textual entailment within the project CSIEC (Computer simulation in educational communication), an interactive Web-based human-Computer Dialogue system with natural language for English instruction. The generation of textual entailment (GTE) is critical to the further improvement of CSIEC project and other natural language generation program. Up to now we have found few literatures on the general algorithm for GTE. Simulating the process that a human being learns English as a foreign language, we explore our naive approach to tackle the GTE problem and its algorithm within the framework of CSIEC, i.e. rule annotation in NLML, pattern recognition and entailment transformation. The time and space complexity of our algorithm is tested with some entailment examples. An interactive command line textual entailment editor is created to generalize an entailment rule from a case pair of text and entailment. The test version of this innovative GTE approach can be accessed in the CSIEC website. Further works include the rules annotation based on the English textbooks and a GUI interface for normal users to edit the entailment rules.

  • the generation of textual entailment with nlml in an intelligent Dialogue system for language learning csiec
    arXiv: Computation and Language, 2008
    Co-Authors: Jiyou Jia
    Abstract:

    This research report introduces the generation of textual entailment within the project CSIEC (Computer Simulation in Educational Communication), an interactive web-based human-Computer Dialogue system with natural language for English instruction. The generation of textual entailment (GTE) is critical to the further improvement of CSIEC project. Up to now we have found few literatures related with GTE. Simulating the process that a human being learns English as a foreign language we explore our naive approach to tackle the GTE problem and its algorithm within the framework of CSIEC, i.e. rule annotation in NLML, pattern recognition (matching), and entailment transformation. The time and space complexity of our algorithm is tested with some entailment examples. Further works include the rules annotation based on the English textbooks and a GUI interface for normal users to edit the entailment rules.

Diane J Litman - One of the best experts on this subject based on the ideXlab platform.

  • spoken versus typed human and Computer Dialogue tutoring
    Artificial Intelligence in Education, 2006
    Co-Authors: Diane J Litman, Kurt Vanlehn, Carolyn Penstein Rose, Kate Forbesriley, Dumisizwe Bhembe, Scott Silliman
    Abstract:

    While human tutors typically interact with students using spoken Dialogue, most Computer Dialogue tutors are text-based. We have conducted two 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 from text to speech caused changes in the learning gains, time and superficial Dialogue characteristics of human tutoring, but for Computer tutoring it made less difference.

  • spoken versus typed human and Computer Dialogue tutoring
    Lecture Notes in Computer Science, 2004
    Co-Authors: Diane J Litman, Kurt Vanlehn, Carolyn Penstein Rose, Kate Forbesriley, Dumisizwe Bhembe, Scott Silliman
    Abstract:

    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 from text to speech caused large differences in the learning gains, time and superficial Dialogue characteristics of human tutoring, but for Computer tutoring it made less difference.

Dumisizwe Bhembe - One of the best experts on this subject based on the ideXlab platform.

  • spoken versus typed human and Computer Dialogue tutoring
    Artificial Intelligence in Education, 2006
    Co-Authors: Diane J Litman, Kurt Vanlehn, Carolyn Penstein Rose, Kate Forbesriley, Dumisizwe Bhembe, Scott Silliman
    Abstract:

    While human tutors typically interact with students using spoken Dialogue, most Computer Dialogue tutors are text-based. We have conducted two 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 from text to speech caused changes in the learning gains, time and superficial Dialogue characteristics of human tutoring, but for Computer tutoring it made less difference.

  • spoken versus typed human and Computer Dialogue tutoring
    Lecture Notes in Computer Science, 2004
    Co-Authors: Diane J Litman, Kurt Vanlehn, Carolyn Penstein Rose, Kate Forbesriley, Dumisizwe Bhembe, Scott Silliman
    Abstract:

    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 from text to speech caused large differences in the learning gains, time and superficial Dialogue characteristics of human tutoring, but for Computer tutoring it made less difference.

Carolyn Penstein Rose - One of the best experts on this subject based on the ideXlab platform.

  • spoken versus typed human and Computer Dialogue tutoring
    Artificial Intelligence in Education, 2006
    Co-Authors: Diane J Litman, Kurt Vanlehn, Carolyn Penstein Rose, Kate Forbesriley, Dumisizwe Bhembe, Scott Silliman
    Abstract:

    While human tutors typically interact with students using spoken Dialogue, most Computer Dialogue tutors are text-based. We have conducted two 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 from text to speech caused changes in the learning gains, time and superficial Dialogue characteristics of human tutoring, but for Computer tutoring it made less difference.

  • spoken versus typed human and Computer Dialogue tutoring
    Lecture Notes in Computer Science, 2004
    Co-Authors: Diane J Litman, Kurt Vanlehn, Carolyn Penstein Rose, Kate Forbesriley, Dumisizwe Bhembe, Scott Silliman
    Abstract:

    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 from text to speech caused large differences in the learning gains, time and superficial Dialogue characteristics of human tutoring, but for Computer tutoring it made less difference.