Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 5 |
Since 2016 (last 10 years) | 10 |
Since 2006 (last 20 years) | 12 |
Descriptor
Author
Graesser, Arthur C. | 12 |
Chen, Su | 6 |
Fang, Ying | 6 |
Greenberg, Daphne | 5 |
Shi, Genghu | 5 |
Cai, Zhiqiang | 4 |
Lippert, Anne | 4 |
Frijters, Jan C. | 2 |
Shubeck, Keith | 2 |
Baer, Whitney O. | 1 |
Betrancourt, Mirelle | 1 |
More ▼ |
Publication Type
Reports - Research | 7 |
Speeches/Meeting Papers | 6 |
Reports - Descriptive | 4 |
Journal Articles | 3 |
Reports - Evaluative | 1 |
Education Level
Adult Education | 8 |
Adult Basic Education | 1 |
Elementary Education | 1 |
Audience
Practitioners | 1 |
Laws, Policies, & Programs
Assessments and Surveys
Woodcock Johnson Tests of… | 3 |
What Works Clearinghouse Rating
Greenberg, Daphne; Miller, Christine; Graesser, Arthur C. – Adult Literacy Education, 2023
This article is written by two researchers and a teacher involved with the development and implementation of a web-based intelligent tutoring system for adults reading at elementary levels. A description of the tool is provided, followed by some of the challenges faced in designing, developing, and using the tool in adult literacy classrooms.
Descriptors: Intelligent Tutoring Systems, Adult Students, Adult Basic Education, Reading Comprehension
Shi, Genghu; Wang, Lijia; Zhang, Liang; Shubeck, Keith; Peng, Shun; Hu, Xiangen; Graesser, Arthur C. – Grantee Submission, 2021
Adult learners with low literacy skills compose a highly heterogeneous population in terms of demographic variables, educational backgrounds, knowledge and skills in reading, self-efficacy, motivation etc. They also face various difficulties in consistently attending offline literacy programs, such as unstable worktime, transportation…
Descriptors: Intelligent Tutoring Systems, Adult Literacy, Adult Students, Reading Comprehension
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
Chen, Su; Fang, Ying; Shi, Genghu; Sabatini, John; Greenberg, Daphne; Frijters, Jan; Graesser, Arthur C. – Grantee Submission, 2021
This paper describes a new automated disengagement tracking system (DTS) that detects learners' maladaptive behaviors, e.g. mind-wandering and impetuous responding, in an intelligent tutoring system (ITS), called AutoTutor. AutoTutor is a conversation-based intelligent tutoring system designed to help adult literacy learners improve their reading…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Attention, Adult Literacy
Chen, Su; Lippert, Anne; Shi, Genghu; Fang, Ying; Graesser, Arthur C. – Grantee Submission, 2018
This paper describes a novel automated disengagement tracing system (DTS) that detects mind wandering in students using AutoTutor, an Intelligent Tutoring System (ITS) with conversational agents. DTS is based on an unsupervised learning method and thus does not rely on any self-reports of disengagement. We analyzed the reading time and response…
Descriptors: Learner Engagement, Intelligent Tutoring Systems, Reading Comprehension, Adult Literacy
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
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
Shi, Genghu; Lippert, Anne M.; Shubeck, Keith; Fang, Ying; Chen, Su; Pavlik, Philip, Jr.; Greenberg, Daphne; Graesser, Arthur C. – Grantee Submission, 2018
Reading comprehension is often assessed by having students read passages and administering a test that assesses their understanding of the text. Shorter assessments may fail to give a full picture of comprehension ability while more thorough ones can be time consuming and costly. This study used data from a conversational intelligent tutoring…
Descriptors: Reading Comprehension, Intelligent Tutoring Systems, Adults, Accuracy
Diagnosing Reading Deficiencies of Adults with Low Literacy Skills in an Intelligent Tutoring System
Shi, Genghu; Hampton, Andrew J.; Chen, Su; Fang, Ying; Graesser, Arthur C. – Grantee Submission, 2018
We developed a version of AutoTutor that helps struggling adult learners improve their comprehension strategies through conversational agents. We hypothesized that the accuracy and time to answer questions during the conversation could be diagnostic of their mastery of different reading comprehension components: words, textbase, situation model,…
Descriptors: Intelligent Tutoring Systems, Educational Technology, Technology Uses in Education, Reading Difficulties
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
Feng, Shi; Stewart, Janay; Clewley, Danielle; Graesser, Arthur C. – Grantee Submission, 2015
We manipulated three types of short feedback (emotional, epistemic, and neutral) in an intelligent tutoring system designed to help struggling adult readers improve reading comprehension strategies. We conducted our research on college students to eventually compare with the targeted adult population. We also recorded their facial emotions.…
Descriptors: Intelligent Tutoring Systems, Educational Technology, Technology Uses in Education, Feedback (Response)
Rouet, Jean-Francois; Betrancourt, Mirelle; Britt, M. Anne; Bromme, Rainer; Graesser, Arthur C.; Kulikowich, Jonna M.; Leu, Donald J.; Ueno, Naoki; van Oostendorp, Herre – OECD Publishing (NJ1), 2009
Governments and other stakeholders have become increasingly interested in assessing the skills of their adult populations for the purposes of monitoring how well prepared they are for the challenges of the new information world. The current paper provides an overview of the conceptual framework developed for the assessment of problem solving in…
Descriptors: Problem Solving, Information Technology, Foreign Countries, Educational Technology