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Hollander, John; Sabatini, John; Graesser, Art – COABE Journal: The Resource for Adult Education, 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
Hollander, 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
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
Zhihong Xu; Kausalai Wijekumar; Qing Wang; Robin Irey; Hua Liang – Language Teaching Research, 2024
Underdeveloped reading comprehension skills can limit academic success; a particular challenge for English language learners (ELLs). The current study investigated whether a web-based text structure strategy, delivered via the Intelligent Tutoring of Structure Strategy (ITSS) program to adult Chinese ELLs, improved students' use of reading…
Descriptors: Reading Strategies, Reading Comprehension, Intervention, Reading Instruction
Graesser, Arthur C.; Greenberg, Daphne; Frijters, Jan C.; Talwar, Amani – Grantee Submission, 2021
A large percentage of adults throughout the world have low reading skills. Computer technologies can potentially help these adults improve their literacy in addition to instructors at literacy centers. AutoTutor was designed to teach comprehension strategies by implementing conversational "trialogues" in which two computer agents (tutor…
Descriptors: Reading Achievement, Learner Engagement, Reading Comprehension, Intervention
Justin L. Mathews – ProQuest LLC, 2021
Pedagogical agents, virtual avatars that are often included in online training or educational modules, have been studied in a variety of disciplines to determine the extent to which their inclusion in online or multimedia learning environments may influence both cognitive and affective outcomes in learners. The present study examined the effect of…
Descriptors: Adult Students, Electronic Learning, Self Efficacy, Performance
Wesley Morris; Scott Crossley; Langdon Holmes; Chaohua Ou; Danielle McNamara; Mihai Dascalu – Grantee Submission, 2023
As intelligent textbooks become more ubiquitous in classrooms and educational settings, the need arises to automatically provide formative feedback to written responses provided by students in response to readings. This study develops models to automatically provide feedback to student summaries written at the end of intelligent textbook sections.…
Descriptors: Textbooks, Electronic Publishing, Feedback (Response), Formative Evaluation
John Hollander; John Sabatini; Art Graesser; Daphne Greenberg; Tenaha O'Reilly; Jan Frijters – Grantee Submission, 2023
Adult literacy learners are characterized by their diversity, both in terms of educational histories and cognitive skill sets. Accounting for the specific strengths and weaknesses of each learner is vital to the assessment of literacy gains and optimization of educational systems. We examined pre- and post-difference scores on a component reading…
Descriptors: Adult Literacy, Adult Education, Adult Students, Student Characteristics
John Hollander; John Sabatini; Art Graesser; Daphne Greenberg; Tenaha O'Reilly; Jan Frijters – Discourse Processes: A Multidisciplinary Journal, 2023
Adult literacy learners are characterized by their diversity, both in terms of educational histories and cognitive skill sets. Accounting for the specific strengths and weaknesses of each learner is vital to the assessment of literacy gains and optimization of educational systems. We examined pre- and post-difference scores on a component reading…
Descriptors: Adult Literacy, Adult Education, Adult Students, Student Characteristics
Viktor Wang, Editor – IGI Global, 2025
Artificial Intelligence (AI) integration in andragogical education offers significant enhancements to the learning experience for adult learners. By utilizing AI-powered platforms, instructors can provide personalized learning paths that adapt to the unique needs, interests, and goals of each individual. These systems can analyze performance data…
Descriptors: Andragogy, Artificial Intelligence, Computer Software, Technology Integration
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
Yuan, Chia-Ching; Li, Cheng-Hsuan; Peng, Chin-Cheng – Interactive Learning Environments, 2023
Fighter jets are a critical national asset. Because of the high cost of their manufacture and that of their related equipment, both pilots and maintenance personnel must complete intensive training before coming into contact with a jet. Due to gradual military downsizing, one-on-one training is often impracticable, and the level of familiarization…
Descriptors: Artificial Intelligence, Man Machine Systems, Technology Uses in Education, Educational Technology