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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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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
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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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Weragama, Dinesha; Reye, Jim – International Journal of Artificial Intelligence in Education, 2014
Programming is a subject that many beginning students find difficult. The PHP Intelligent Tutoring System (PHP ITS) has been designed with the aim of making it easier for novices to learn the PHP language in order to develop dynamic web pages. Programming requires practice. This makes it necessary to include practical exercises in any ITS that…
Descriptors: Intelligent Tutoring Systems, Programming, Computer Science Education, Programming Languages
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Steenbergen-Hu, Saiying; Cooper, Harris – Journal of Educational Psychology, 2014
This meta-analysis synthesizes research on the effectiveness of intelligent tutoring systems (ITS) for college students. Thirty-five reports were found containing 39 studies assessing the effectiveness of 22 types of ITS in higher education settings. Most frequently studied were AutoTutor, Assessment and Learning in Knowledge Spaces, eXtended…
Descriptors: Meta Analysis, Intelligent Tutoring Systems, Instructional Effectiveness, College Students
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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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VanLehn, Kurt; Chung, Greg; Grover, Sachin; Madni, Ayesha; Wetzel, Jon – International Journal of Artificial Intelligence in Education, 2016
A common hypothesis is that students will more deeply understand dynamic systems and other complex phenomena if they construct computational models of them. Attempts to demonstrate the advantages of model construction have been stymied by the long time required for students to acquire skill in model construction. In order to make model…
Descriptors: Models, Science Instruction, Intelligent Tutoring Systems, Teaching Methods
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Suleman, Raja M.; Mizoguchi, Riichiro; Ikeda, Mitsuru – International Journal of Artificial Intelligence in Education, 2016
Negotiation mechanism using conversational agents (chatbots) has been used in Open Learner Models (OLM) to enhance learner model accuracy and provide opportunities for learner reflection. Using chatbots that allow for natural language discussions has shown positive learning gains in students. Traditional OLMs assume a learner to be able to manage…
Descriptors: Metacognition, Intelligent Tutoring Systems, Natural Language Processing, Models
Baer, Whitney O.; Cheng, Qinyu; McGlown, Cadarrius; Gong, Yan; Cai, Zhiqiang; Graesser, Arthur C. – Grantee Submission, 2016
The Center for the Study of Adult Literacy (CSAL) seeks to improve our understanding of ways to advance the reading skills of adult learners. Our web-based instructional tutor uses trialogues in the AutoTutor framework to deliver lessons in reading comprehension. We have found a way to manipulate proven comprehension strategies to fit the daily…
Descriptors: Adult Learning, Adult Students, Literacy Education, Adult Literacy
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Jonsdottir, Anna Helga; Bjornsdottir, Audbjorg; Stefansson, Gunnar – Journal of Statistics Education, 2017
A repeated crossover experiment comparing learning among students handing in pen-and-paper homework (PPH) with students handing in web-based homework (WBH) has been conducted. The system used in the experiments, the tutor-web, has been used to deliver homework problems to thousands of students in mathematics and statistics over several years.…
Descriptors: Homework, Web Based Instruction, Conventional Instruction, Comparative Analysis
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