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Direct linkHollander, John; Sabatini, John; Graesser, Art – Grantee Submission, 2021
Twenty-first century literacy includes a mixture of digital and print literacy skills and strategies. AutoTutor for Adult Reading Comprehension is a web-based intelligent tutoring system that is designed to help adult learners develop effective reading comprehension strategies. Lessons span basic reading skills (vocabulary, word parts),…
Descriptors: Intelligent Tutoring Systems, Adult Literacy, Reading Instruction, Reading Comprehension
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
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
Shi, Genghu; Pavlik, Philip, Jr.; Graesser, Arthur – Grantee Submission, 2017
After developing an intelligent tutoring system (ITS), or any other class of learning environments, one of the first questions that should be asked is whether the system was effective in helping students learn the targeted skills or subject matter. In this study, we employed two educational data mining models (Additive Factor Model, AFM and…
Descriptors: Intelligent Tutoring Systems, Educational Technology, Technology Uses in Education, Program Effectiveness
Nightingale, Elena; Greenberg, Daphne; Branum-Martin, Lee – Grantee Submission, 2016
Selecting assessments for adults who struggle with reading can be difficult because few literacy measures used by reading researchers have been normed on this population, leaving uncertainty regarding the validity of these tests for adult learners. This study focused on the performance of 116 adults reading between the 3rd and 8th grade levels on…
Descriptors: Adult Learning, Adult Literacy, Functional Literacy, 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
