NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 6 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Jionghao Lin; Wei Tan; Lan Du; Wray Buntine; David Lang; Dragan Gasevic; Guanliang Chen – IEEE Transactions on Learning Technologies, 2024
Automating the classification of instructional strategies from a large-scale online tutorial dialogue corpus is indispensable to the design of dialogue-based intelligent tutoring systems. Despite many existing studies employing supervised machine learning (ML) models to automate the classification process, they concluded that building a…
Descriptors: Classification, Dialogs (Language), Teaching Methods, Computer Assisted Instruction
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Kwon, Oh-Woog; Kim, Young-Kil; Lee, Yunkeun – Research-publishing.net, 2018
This paper presents a rule-based task-oriented dialogue system for second language learning and a knowledge extraction method which automatically extracts the training data for Natural Language Understanding (NLU) and dialogue rules for dialogue management from a Dialogue Map (DM). The DM consists of turn-by-turn utterances between the system and…
Descriptors: Graphs, Second Language Learning, Second Language Instruction, English (Second Language)
Nye, Benjamin D.; Morrison, Donald M.; Samei, Borhan – International Educational Data Mining Society, 2015
Archived transcripts from tens of millions of online human tutoring sessions potentially contain important knowledge about how online tutors help, or fail to help, students learn. However, without ways of automatically analyzing these large corpora, any knowledge in this data will remain buried. One way to approach this issue is to train an…
Descriptors: Tutoring, Instructional Effectiveness, Tutors, Models
Ababneh, Mohammad – ProQuest LLC, 2014
A dialog system or a conversational agent provides a means for a human to interact with a computer system. Dialog systems use text, voice and other means to carry out conversations with humans in order to achieve some objective. Most dialog systems are created with specific objectives in mind and consist of preprogrammed conversations. The primary…
Descriptors: Item Response Theory, Web 2.0 Technologies, Computer System Design, Intelligent Tutoring Systems
Peer reviewed Peer reviewed
Direct linkDirect link
Forbes-Riley, Kate; Litman, Diane – International Journal of Artificial Intelligence in Education, 2013
In this paper we investigate how student disengagement relates to two performance metrics in a spoken dialog computer tutoring corpus, both when disengagement is measured through manual annotation by a trained human judge, and also when disengagement is measured through automatic annotation by the system based on a machine learning model. First,…
Descriptors: Correlation, Learner Engagement, Oral Language, Computer Assisted Instruction
Peer reviewed Peer reviewed
Rypa, Marikka Elizabeth; Price, Patti – CALICO Journal, 1999
Describes the Voice Interactive Training System (VILTS), a language-training prototype developed to help improve comprehension and speaking skills. The system incorporates two related technologies: speech recognition and pronunciation scoring. Discusses the motivation for the program, the interdisciplinary efforts involved, and the resulting…
Descriptors: Cognitive Style, Communicative Competence (Languages), Computer Assisted Instruction, Computer Software Evaluation