Improving the efficiency of dialogue in tutoring |
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| Authors: | Kristopher J. Kopp M. Anne Britt Keith Millis Arthur C. Graesser |
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| Affiliation: | 1. Department of Psychology, Northern Illinois University, Dekalb, IL 60115, USA;2. Department of Psychology, University of Memphis, Memphis, TN 38152, USA;1. College of Communications Engineering, PLA University of Science and Technology, Nanjing 210007, China;2. Huawei Technologies Canada Co., LTD., Markham, Ontario L3R 5A4, Canada;1. Universidad Politécnica de Madrid, Departamento de Ingeniería Civil: Transportes. C/Profesor Aranguren s/n 28040 Madrid – Spain;2. Universidad Politécnica de Madrid, Departamento de Ingeniería Civil: Hidraúlica y Energética. C/Profesor Aranguren s/n 28040 Madrid – Spain;1. Pediatric Surgery Division, Department of Surgery, Faculty of Medicine, Universitas Gadjah Mada/Dr. Sardjito Hospital, Yogyakarta, Indonesia;2. Department of Child Health, Faculty of Medicine, Universitas Gadjah Mada/UGM Hospital, Yogyakarta, Indonesia;1. Yale University, 230 South Frontage Road, New Haven, CT 06520, USA;2. Max Planck Institute for Human Cognitive and Brain Sciences, P.O. Box 500355, 04303 Leipzig, Germany |
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| Abstract: | The current studies investigated the efficient use of dialogue in intelligent tutoring systems that use natural language interaction. Such dialogues can be relatively time-consuming. This work addresses the question of how much dialogue is needed to produce significant learning gains. In Experiment 1, a full dialogue condition and a read-only control condition were compared with a mixed dialogue condition in which students engaged in full dialogue for half the problems followed by problems requiring only a limited engagement. We found that the mixed dialogue condition produced results as impressive as the full dialogue condition and took less time. Experiment 2 replicated these findings and further examined issues of time engaged in learning, quality of instruction, and learning gains. Overall, these 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. |
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