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Huang, Jin-Xia; Lee, Kyung-Soon; Kwon, Oh-Woog; Kim, Young-Kil – Research-publishing.net, 2016
This paper presents an automatic dialogue scoring approach for a Dialogue-Based Computer-Assisted Language Learning (DB-CALL) system, which helps users learn language via interactive conversations. The system produces overall feedback according to dialogue scoring to help the learner know which parts should be more focused on. The scoring measures…
Descriptors: Second Language Learning, Second Language Instruction, Computer Assisted Instruction, Dialogs (Language)
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Klingler, Severin; Käser, Tanja; Solenthaler, Barbara; Gross, Markus – International Educational Data Mining Society, 2016
The extraction of student behavior is an important task in educational data mining. A common approach to detect similar behavior patterns is to cluster sequential data. Standard approaches identify clusters at each time step separately and typically show low performance for data that inherently suffer from noise, resulting in temporally…
Descriptors: Student Behavior, Data Analysis, Behavior Patterns, Multivariate Analysis
Allen, Laura K.; Likens, Aaron D.; McNamara, Danielle S. – Grantee Submission, 2018
The assessment of argumentative writing generally includes analyses of the specific linguistic and rhetorical features contained in the individual essays produced by students. However, researchers have recently proposed that an individual's ability to flexibly adapt the linguistic properties of their writing may more accurately capture their…
Descriptors: Writing (Composition), Persuasive Discourse, Essays, Language Usage
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Easterday, Matthew W.; Aleven, Vincent; Scheines, Richard; Carver, Sharon M. – Journal of the Learning Sciences, 2017
How might we balance assistance and penalties to intelligent tutors and educational games that increase learning and interest? We created two versions of an educational game for learning policy argumentation called Policy World. The game (only) version provided minimal feedback and penalized students for errors whereas the game+tutor version…
Descriptors: Educational Games, Intelligent Tutoring Systems, Policy, Persuasive Discourse
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McCarthy, Kathryn S.; Jacovina, Matthew E.; Snow, Erica L.; Guerrero, Tricia A.; McNamara, Danielle S. – Grantee Submission, 2017
iSTART is an intelligent tutoring system designed to provide self-explanation instruction and practice to improve students' comprehension of complex, challenging text. This study examined the effects of extended game-based practice within the system as well as the effects of two metacognitive supports implemented within this practice. High school…
Descriptors: Reading Comprehension, Reading Instruction, Intelligent Tutoring Systems, Reading Strategies
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Price, Thomas; Zhi, Rui; Barnes, Tiffany – International Educational Data Mining Society, 2017
In this paper we present a novel, data-driven algorithm for generating feedback for students on open-ended programming problems. The feedback goes beyond next-step hints, annotating a student's whole program with suggested edits, including code that should be moved or reordered. We also build on existing work to design a methodology for evaluating…
Descriptors: Feedback (Response), Computer Software, Data Analysis, Programming
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Zayyad, Muhammad, Ed.; Unsal, Atilla Ayaz, Ed. – Online Submission, 2020
"Education Research Highlights in Mathematics, Science and Technology" is published annually from the selected papers invited by the editors. This edition includes 3 sections and 11 papers from the field of Educational Technology, Mathematics Education and Science Education, all submissions are reviewed by at least two international…
Descriptors: Educational Research, Mathematics Education, Science Education, Technology Education
Kelly, Kim; Heffernan, Neil – International Educational Data Mining Society, 2015
Intelligent tutoring systems have been developed to help students learn independently. However, students who are poor self-regulated learners often struggle to use these systems because they lack the skills necessary to learn independently. The field of psychology has extensively studied self-regulated learning and can provide strategies to…
Descriptors: Intelligent Tutoring Systems, Active Learning, Self Management, Independent Study
Eagle, Michael; Barnes, Tiffany – International Educational Data Mining Society, 2015
Interactive problem solving environments, such as intelligent tutoring systems and educational video games, produce large amounts of transactional data which make it a challenge for both researchers and educators to understand how students work within the environment. Researchers have modeled the student-tutor interactions using complex network…
Descriptors: Interaction, Teacher Student Relationship, Intelligent Tutoring Systems, Data
Tang, Steven; Gogel, Hannah; McBride, Elizabeth; Pardos, Zachary A. – International Educational Data Mining Society, 2015
Online adaptive tutoring systems are increasingly being used in classrooms as a way to provide guided learning for students. Such tutors have the potential to provide tailored feedback based on specific student needs and misunderstandings. Bayesian knowledge tracing (BKT) is used to model student knowledge when knowledge is assumed to be changing…
Descriptors: Intelligent Tutoring Systems, Difficulty Level, Bayesian Statistics, Models
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Liu, Gi-Zen; Lu, Hui-Ching; Lin, Vivien; Hsu, Wei-Chen – Journal of Computer Assisted Learning, 2018
With the increased use of digital materials, undergraduate writers in English as a foreign language (EFL) contexts have become more susceptible to plagiarism. In this study, the researchers designed a blended English writing course with an online writing tutorial system entitled "DWright." The study examined the effectiveness of the…
Descriptors: Undergraduate Students, Plagiarism, Prevention, Intelligent Tutoring Systems
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Nakamura, Christopher M.; Murphy, Sytil K.; Christel, Michael G.; Stevens, Scott M.; Zollman, Dean A. – Physical Review Physics Education Research, 2016
Computer-automated assessment of students' text responses to short-answer questions represents an important enabling technology for online learning environments. We have investigated the use of machine learning to train computer models capable of automatically classifying short-answer responses and assessed the results. Our investigations are part…
Descriptors: Physics, Introductory Courses, Science Instruction, Intelligent Tutoring Systems
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Rummel, Nikol; Walker, Erin; Aleven, Vincent – International Journal of Artificial Intelligence in Education, 2016
In this position paper we contrast a Dystopian view of the future of adaptive collaborative learning support (ACLS) with a Utopian scenario that--due to better-designed technology, grounded in research--avoids the pitfalls of the Dystopian version and paints a positive picture of the practice of computer-supported collaborative learning 25 years…
Descriptors: Artificial Intelligence, Cooperative Learning, Futures (of Society), Electronic Learning
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Chou, Chih-Yueh; Chan, Tak-Wai – International Journal of Artificial Intelligence in Education, 2016
"Reciprocal tutoring," as reported in "Exploring the design of computer supports for reciprocal tutoring" (Chan and Chou 1997), has extended the meaning and scope of "intelligent tutoring" originally implemented in stand alone computers. This research is a follow-up to our studies on a "learning companion…
Descriptors: Peer Teaching, Tutoring, Cognitive Processes, Difficulty Level
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Hoppe, H. Ulrich – International Journal of Artificial Intelligence in Education, 2016
The 1998 paper by Martin Mühlenbrock, Frank Tewissen, and myself introduced a multi-agent architecture and a component engineering approach for building open distributed learning environments to support group learning in different types of classroom settings. It took up prior work on "multiple student modeling" as a method to configure…
Descriptors: Guidelines, Intelligent Tutoring Systems, Cooperative Learning, Modeling (Psychology)
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