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Kochmar, Ekaterina; Vu, Dung Do; Belfer, Robert; Gupta, Varun; Serban, Iulian Vlad; Pineau, Joelle – International Journal of Artificial Intelligence in Education, 2022
Intelligent tutoring systems (ITS) have been shown to be highly effective at promoting learning as compared to other computer-based instructional approaches. However, many ITS rely heavily on expert design and hand-crafted rules. This makes them difficult to build and transfer across domains and limits their potential efficacy. In this paper, we…
Descriptors: Intelligent Tutoring Systems, Automation, Feedback (Response), Dialogs (Language)
Conrad Borchers; Kexin Yang; Jionghao Lin; Nikol Rummel; Kenneth R. Koedinger; Vincent Aleven – International Educational Data Mining Society, 2024
Peer tutoring can improve learning by prompting learners to reflect. To assess whether peer interactions are conducive to learning and provide peer tutoring support accordingly, what tutorial dialog types relate to student learning most? Advancements in collaborative learning analytics allow for merging machine learning-based dialog act…
Descriptors: Artificial Intelligence, Peer Teaching, Tutoring, Technology Uses in Education
Jionghao Lin; Shaveen Singh; Lela Sha; Wei Tan; David Lang; Dragan Gasevic; Guanliang Chen – Grantee Submission, 2022
To construct dialogue-based Intelligent Tutoring Systems (ITS) with sufficient pedagogical expertise, a trendy research method is to mine large-scale data collected by existing dialogue-based ITS or generated between human tutors and students to discover effective tutoring strategies. However, most of the existing research has mainly focused on…
Descriptors: Intelligent Tutoring Systems, Teaching Methods, Dialogs (Language), Man Machine Systems
Pai, Kai-Chih; Kuo, Bor-Chen; Liao, Chen-Huei; Liu, Yin-Mei – Educational Psychology, 2021
The present study aims to examine the pedagogical effectiveness of a Chinese mathematical dialogue-based intelligent tutoring system used for teaching mathematics. The mathematical unit 'multiplication and division of time expressions' was taught to 134 fifth-grade students in three types of instruction conditions: the intelligent tutoring system…
Descriptors: Dialogs (Language), Intelligent Tutoring Systems, Remedial Mathematics, Multiplication
Linking Dialogue with Student Modelling to Create an Adaptive Tutoring System for Conceptual Physics
Katz, Sandra; Albacete, Patricia; Chounta, Irene-Angelica; Jordan, Pamela; McLaren, Bruce M.; Zapata-Rivera, Diego – International Journal of Artificial Intelligence in Education, 2021
Jim Greer and his colleagues argued that student modelling is essential to provide adaptive instruction in tutoring systems and showed that effective modelling is possible, despite being enormously challenging. Student modelling plays a prominent role in many intelligent tutoring systems (ITSs) that address problem-solving domains. However,…
Descriptors: Physics, Science Instruction, Pretests Posttests, Scores
Wiggins, Joseph B.; Grafsgaard, Joseph F.; Boyer, Kristy Elizabeth; Wiebe, Eric N.; Lester, James C. – International Journal of Artificial Intelligence in Education, 2017
In recent years, significant advances have been made in intelligent tutoring systems, and these advances hold great promise for adaptively supporting computer science (CS) learning. In particular, tutorial dialogue systems that engage students in natural language dialogue can create rich, adaptive interactions. A promising approach to increasing…
Descriptors: Intelligent Tutoring Systems, Self Efficacy, Computer Science Education, Dialogs (Language)
Nye, Benjamin D.; Pavlik, Philip I., Jr.; Windsor, Alistair; Olney, Andrew M.; Hajeer, Mustafa; Hu, Xiangen – International Journal of STEM Education, 2018
Background: This study investigated learning outcomes and user perceptions from interactions with a hybrid intelligent tutoring system created by combining the AutoTutor conversational tutoring system with the Assessment and Learning in Knowledge Spaces (ALEKS) adaptive learning system for mathematics. This hybrid intelligent tutoring system (ITS)…
Descriptors: Intelligent Tutoring Systems, Mathematics Instruction, Outcomes of Education, Mastery Learning
Min, Wookhee; Wiggins, Joseph B.; Pezzullo, Lydia G.; Vail, Alexandria K.; Boyer, Kristy Elizabeth; Mott, Bradford W.; Frankosky, Megan H.; Wiebe, Eric N.; Lester, James C. – International Educational Data Mining Society, 2016
Recent years have seen a growing interest in intelligent game-based learning environments featuring virtual agents. A key challenge posed by incorporating virtual agents in game-based learning environments is dynamically determining the dialogue moves they should make in order to best support students' problem solving. This paper presents a…
Descriptors: Prediction, Models, Intelligent Tutoring Systems, Computer Simulation
Lipschultz, Michael; Litman, Diane; Katz, Sandra; Albacete, Patricia; Jordan, Pamela – Grantee Submission, 2014
Post-problem reflective tutorial dialogues between human tutors and students are examined to predict when the tutor changed the level of abstraction from the student's preceding turn (i.e., used more general terms or more specific terms); such changes correlate with learning. Prior work examined lexical changes in abstraction. In this work, we…
Descriptors: Intelligent Tutoring Systems, Natural Language Processing, Semantics, Abstract Reasoning

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