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Torres-Jimenez, Jose; Lescano, Germán; Lara-Alvarez, Carlos; Mitre-Hernandez, Hugo – Education and Information Technologies, 2023
Conflicts play an important role to improve group learning effectiveness; they can be decreased, increased, or ignored. Given the sequence of messages of a collaborative group, we are interested in recognizing conflicts (detecting whether a conflict exists or not). This is not an easy task because of different types of natural language…
Descriptors: Conflict, Identification, Computer Assisted Instruction, Cooperative Learning
Jaeho Jeon; Seongyong Lee – Education and Information Technologies, 2024
Research has demonstrated the promising potential of chatbots in education. Moreover, technological advancements, such as ChatGPT, prompted us to reexamine distinctions between pedagogical roles that humans and chatbots assume. In this context, a systematic review of 11 experimental studies on human-chatbot comparisons in language education was…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Computer Assisted Instruction
Prapasiri Klayklung; Piyawatjana Chocksathaporn; Pongsakorn Limna; Tanpat Kraiwanit; Kris Jangjarat – Online Submission, 2023
The development of conversational artificial intelligence (AI) has brought about new opportunities for improving the learning experience in education. ChatGPT, a large language model trained on a vast corpus of text, has the potential to revolutionize education by enhancing learning through personalized and interactive conversations. This paper…
Descriptors: Artificial Intelligence, Interaction, Foreign Countries, Technology Integration
Lämsä, Joni; Uribe, Pablo; Jiménez, Abelino; Caballero, Daniela; Hämäläinen, Raija; Araya, Roberto – Journal of Learning Analytics, 2021
Scholars have applied automatic content analysis to study computer-mediated communication in computer-supported collaborative learning (CSCL). Since CSCL also takes place in face-to-face interactions, we studied the automatic coding accuracy of manually transcribed face-to-face communication. We conducted our study in an authentic higher-education…
Descriptors: Cooperative Learning, Computer Assisted Instruction, Synchronous Communication, Learning Analytics
D'Mello, Sidney K.; Dowell, Nia; Graesser, Arthur – Journal of Experimental Psychology: Applied, 2011
There is the question of whether learning differs when students speak versus type their responses when interacting with intelligent tutoring systems with natural language dialogues. Theoretical bases exist for three contrasting hypotheses. The "speech facilitation" hypothesis predicts that spoken input will "increase" learning,…
Descriptors: Intelligent Tutoring Systems, Prior Learning, Natural Language Processing, Tutoring
Pérez-Marín, Diana; Pascual-Nieto, Ismael – Behaviour & Information Technology, 2013
A pedagogic conversational agent (PCA) can be defined as a computer system that interacts with the student in natural language assuming the role of the instructor, a student or a companion. It can have a personality and can generate different sentences according to the agent or the student mood. Empathy with the students' feelings seems to…
Descriptors: Natural Language Processing, Conversational Language Courses, Computer Assisted Instruction, Questionnaires
Matthews, Danielle E.; VanLehn, Kurt; Graesser, Arthur C.; Jackson, G. Tanner; Jordan, Pamela; Olney, Andrew; Rosa, Andrew Carolyn P. – Cognitive Science, 2007
It is often assumed that engaging in a one-on-one dialogue with a tutor is more effective than listening to a lecture or reading a text. Although earlier experiments have not always supported this hypothesis, this may be due in part to allowing the tutors to cover different content than the noninteractive instruction. In 7 experiments, we tested…
Descriptors: Tutoring, Natural Language Processing, Physics, Computer Assisted Instruction
Jones, Greg; Squires, Todd; Hicks, Jeramie – Journal of Educational Technology Systems, 2008
This article will describe research done at the National Institute of Multimedia in Education, Japan and the University of North Texas on the creation of a distributed Internet-based spoken language learning system that would provide more interactive and motivating learning than current multimedia and audiotape-based systems. The project combined…
Descriptors: Feedback (Response), Speech, Oral Language, Online Courses

Moore, Johanna D. – Journal of Artificial Intelligence in Education, 1996
Describes those features that distinguish human tutorial explanations from those produced by computer-based instructional systems utilizing natural language interfaces. This is illustrated through a study conducted on an intelligent instruction system, drawing comparisons between student interaction with a human tutor and the system feedback.…
Descriptors: Artificial Intelligence, Comparative Analysis, Computer Assisted Instruction, Discourse Analysis
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers