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Direct linkCai, Zhiqiang; Hu, Xiangen; Graesser, Arthur C. – Grantee Submission, 2019
Conversational Intelligent Tutoring Systems (ITSs) are expensive to develop. While simple online courseware could be easily authored by teachers, the authoring of conversational ITSs usually involves a team of experts with different expertise, including domain experts, linguists, instruction designers, programmers, artists, computer scientists,…
Descriptors: Programming, Intelligent Tutoring Systems, Courseware, Educational Technology
Fang, Ying; Lippert, Anne; Cai, Zhiqiang; Chen, Su; Frijters, Jan C.; Greenberg, Daphne; Graesser, Arthur C. – International Journal of Artificial Intelligence in Education, 2022
A common goal of Intelligent Tutoring Systems (ITS) is to provide learning environments that adapt to the varying abilities and characteristics of users. This type of adaptivity is possible only if the ITS has information that characterizes the learning behaviors of its users and can adjust its pedagogy accordingly. This study investigated an…
Descriptors: Intelligent Tutoring Systems, Classification, Reading Comprehension, Accuracy
Graesser, Arthur C.; Hu, Xiangen; Nye, Benjamin D.; VanLehn, Kurt; Kumar, Rohit; Heffernan, Cristina; Heffernan, Neil; Woolf, Beverly; Olney, Andrew M.; Rus, Vasile; Andrasik, Frank; Pavlik, Philip; Cai, Zhiqiang; Wetzel, Jon; Morgan, Brent; Hampton, Andrew J.; Lippert, Anne M.; Wang, Lijia; Cheng, Qinyu; Vinson, Joseph E.; Kelly, Craig N.; McGlown, Cadarrius; Majmudar, Charvi A.; Morshed, Bashir; Baer, Whitney – International Journal of STEM Education, 2018
Background: The Office of Naval Research (ONR) organized a STEM Challenge initiative to explore how intelligent tutoring systems (ITSs) can be developed in a reasonable amount of time to help students learn STEM topics. This competitive initiative sponsored four teams that separately developed systems that covered topics in mathematics,…
Descriptors: Intelligent Tutoring Systems, STEM Education, Electronics, Integrated Curriculum
Hu, Xiangen; Cai, Zhiqiang; Hampton, Andrew J.; Cockroft, Jody L.; Graesser, Arthur C.; Copland, Cameron; Folsom-Kovarik, Jeremiah T. – Grantee Submission, 2019
In this paper, we consider a minimalistic and behavioristic view of AIS to enable a standardizable mapping of both the behavior of the system and of the learner. In this model, the "learners" interact with the learning "resources" in a given learning "environment" following preset steps of learning…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Metadata, Behavior Patterns
Lippert, Anne; Gatewood, Jessica; Cai, Zhiqiang; Graesser, Arthur C. – Grantee Submission, 2019
One out of six adults in the United States possesses low literacy skills. Many advocates believe that technology can pave the way for these adults to gain the skills that they desire. This article describes an adaptive intelligent tutoring system called AutoTutor that is designed to teach adults comprehension strategies across different levels of…
Descriptors: Intelligent Tutoring Systems, Educational Technology, Adult Literacy, Skill Development
Cai, Zhiqiang; Gong, Yan; Qiu, Qizhi; Hu, Xiangen; Graesser, Art – Grantee Submission, 2016
AutoTutor uses conversational intelligent agents in learning environments. One of the major challenges in developing AutoTutor applications is to assess students' natural language answers to AutoTutor questions. We investigated an AutoTutor dataset with 3358 student answers to 49 AutoTutor questions. In comparisons with human ratings, we found…
Descriptors: Intelligent Tutoring Systems, Natural Language Processing, Dialogs (Language), Programming
Fang, Ying; Lippert, Anne; Cai, Zhiqiang; Chen, Su; Frijters, Jan C.; Greenberg, Daphne; Graesser, Arthur C. – Grantee Submission, 2021
A common goal of Intelligent Tutoring Systems (ITS) is to provide learning environments that adapt to the varying abilities and characteristics of users. This type of adaptivity is possible only if the ITS has information that characterizes the learning behaviors of its users and can adjust its pedagogy accordingly. This study investigated an…
Descriptors: Intelligent Tutoring Systems, Educational Technology, Technology Uses in Education, Reading Comprehension
Fang, Ying; Shubeck, Keith; Lippert, Anne; Chen, Qinyu; Shi, Genghu; Feng, Shi; Gatewood, Jessica; Chen, Su; Cai, Zhiqiang; Pavlik, Philip; Frijters, Jan; Greenberg, Daphne; Graesser, Arthur – Grantee Submission, 2018
A common goal of Intelligent Tutoring Systems (ITS) is to provide learning environments that adapt to the varying abilities and characteristics of users. To do this, researchers must identify the learning patterns exhibited by those interacting with the system. In the present work, we use clustering analysis to capture learning patterns in over…
Descriptors: Intelligent Tutoring Systems, Educational Technology, Technology Uses in Education, Adult Literacy
Cai, Zhiqiang; Graesser, Arthur C.; Windsor, Leah C.; Cheng, Qinyu; Shaffer, David W.; Hu, Xiangen – International Educational Data Mining Society, 2018
Latent Semantic Analysis (LSA) plays an important role in analyzing text data from education settings. LSA represents meaning of words and sets of words by vectors from a k-dimensional space generated from a selected corpus. While the impact of the value of k has been investigated by many researchers, the impact of the selection of documents and…
Descriptors: Semantics, Discourse Analysis, Computational Linguistics, Intelligent Tutoring Systems
Fang, Ying; Shubeck, Keith; Lippert, Anne; Cheng, Qinyu; Shi, Genghu; Feng, Shi; Gatewood, Jessica; Chen, Su; Cai, Zhiqiang; Pavlik, Philip; Frijters, Jan; Greenberg, Daphne; Graesser, Arthur – International Educational Data Mining Society, 2018
A common goal of Intelligent Tutoring Systems (ITS) is to provide learning environments that adapt to the varying abilities and characteristics of users. To do this, researchers must identify the learning patterns exhibited by those interacting with the system. In the present work, we use clustering analysis to capture learning patterns in over…
Descriptors: Intelligent Tutoring Systems, Educational Technology, Technology Uses in Education, Adult Literacy
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
Forsyth, Carol; Pavlik, Philip, Jr.; Graesser, Arthur C.; Cai, Zhiqiang; Germany, Mae-lynn; Millis, Keith; Dolan, Robert P.; Butler, Heather; Halpern, Diane – International Educational Data Mining Society, 2012
"OperationARIES!" is an Intelligent Tutoring System that teaches scientific inquiry skills in a game-like atmosphere. Students complete three different training modules, each with natural language conversations, in order to acquire deep-level knowledge of 21 core concepts of research methodology (e.g., correlation does not mean…
Descriptors: Learning, Cognitive Processes, Logical Thinking, Scientific Methodology
Forsyth, Carol M.; Graesser, Arthur C.; Pavlik, Philip, Jr.; Cai, Zhiqiang; Butler, Heather; Halpern, Diane; Millis, Keith – Journal of Educational Data Mining, 2013
Operation ARIES! is an Intelligent Tutoring System that is designed to teach scientific methodology in a game-like atmosphere. A fundamental goal of this serious game is to engage students during learning through natural language tutorial conversations. A tight integration of cognition, discourse, motivation, and affect is desired to meet this…
Descriptors: Intelligent Tutoring Systems, Scientific Methodology, Science Instruction, Educational Games
Halpern, Diane F.; Millis, Keith; Graesser, Arthur C.; Butler, Heather; Forsyth, Carol; Cai, Zhiqiang – Thinking Skills and Creativity, 2012
Operation ARA (Acquiring Research Acumen) is a computerized learning game that teaches critical thinking and scientific reasoning. It is a valuable learning tool that utilizes principles from the science of learning and serious computer games. Students learn the skills of scientific reasoning by engaging in interactive dialogs with avatars. They…
Descriptors: Critical Thinking, Tutoring, Thinking Skills, Educational Games
