Development of an Interactive Narrative for Adult Literacy Learners

This chapter describes development efforts that build upon the Interactive Strategy Trainer for Active Reading and Thinking-2 (iSTART-2), an intelligent tutoring system that provides self-explanation strategy instruction to improve reading comprehension. The chapter reflects on considerations of the unique needs of adult literacy learners, and outlines the specific guidelines followed to adapt the system to these learners. Several modifications have been made to adapt iSTART to adult learners, including the following: 1) two additional strategy instructional modules for summarization and deep question asking, 2) a text library with life-relevant texts for adult learners, and 3) an interactive narrative which allows instantiated practice of reading strategies using life-relevant artifacts. The authors also describe results from two attitudinal studies examining learners' perceptions of the interactive narrative.

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Development of an Interactive Narrative for Adult Literacy Learners

End-User Considerations in Educational Technology Design - Advances in Educational Technologies and Instructional Design ◽

10.4018/978-1-5225-2639-1.ch012 ◽

2018 ◽

pp. 238-262

Author(s):

Amy M. Johnson ◽

Elizabeth L. Tighe ◽

Matthew E. Jacovina ◽

G. Tanner Jackson ◽

Danielle S. McNamara

Keyword(s):

Reading Comprehension ◽

Adult Learners ◽

Adult Literacy ◽

Intelligent Tutoring ◽

Intelligent Tutoring System ◽

Strategy Instruction ◽

Interactive Narrative ◽

Tutoring System ◽

Active Reading ◽

Literacy Learners

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Automated Disengagement Tracking Within an Intelligent Tutoring System

Frontiers in Artificial Intelligence ◽

10.3389/frai.2020.595627 ◽

2021 ◽

Vol 3 ◽

Author(s):

Su Chen ◽

Ying Fang ◽

Genghu Shi ◽

John Sabatini ◽

Daphne Greenberg ◽

...

Keyword(s):

Reading Comprehension ◽

Sentence Processing ◽

Adult Literacy ◽

Digital Literacy ◽

Text Comprehension ◽

Intelligent Tutoring ◽

Tracking System ◽

Intelligent Tutoring System ◽

Tutoring System ◽

Literacy Learners

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 comprehension skills. Learners interact with two computer agents in natural language in 30 lessons focusing on word knowledge, sentence processing, text comprehension, and digital literacy. Each lesson has one to three dozen questions to assess and enhance learning. DTS automatically retrieves and aggregates a learner's response accuracies and time on the first three to five questions in a lesson, as a baseline performance for the lesson when they are presumably engaged, and then detects disengagement by observing if the learner's following performance significantly deviates from the baseline. DTS is computed with an unsupervised learning method and thus does not rely on any self-reports of disengagement. We analyzed the response time and accuracy of 252 adult literacy learners who completed lessons in AutoTutor. Our results show that items that the detector identified as the learner being disengaged had a performance accuracy of 18.5%, in contrast to 71.8% for engaged items. Moreover, the three post-test reading comprehension scores from Woodcock Johnson III, RISE, and RAPID had a significant association with the accuracy of engaged items, but not disengaged items.

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THE DESIGN AND DEVELOPMENT OF AN INTELLIGENT TUTORING SYSTEM FOR ADULT LITERACY STUDENTS

Computer Assisted Language Learning ◽

10.1080/0958822900020106 ◽

1990 ◽

Vol 2 (1) ◽

pp. 69-81

Author(s):

Jane Horton ◽

David Ellis ◽

Philip Black

Keyword(s):

Adult Literacy ◽

Intelligent Tutoring ◽

Intelligent Tutoring System ◽

Tutoring System ◽

Design And Development

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Evidence of an Intelligent Tutoring System as a Mindtool to Promote Strategic Memory of Expository Texts and Comprehension With Children in Grades 4 and 5

Journal of Educational Computing Research ◽

10.1177/0735633117696909 ◽

2017 ◽

Vol 55 (7) ◽

pp. 1022-1048 ◽

Cited By ~ 1

Author(s):

Kausalai (Kay) Wijekumar ◽

Bonnie J. F. Meyer ◽

Puiwa Lei ◽

Weiyi Cheng ◽

Xuejun Ji ◽

...

Keyword(s):

Reading Comprehension ◽

Prior Knowledge ◽

Large Scale ◽

Intelligent Tutoring ◽

Intelligent Tutoring System ◽

Text Structure ◽

Tutoring System ◽

Randomized Controlled Studies ◽

Strategic Memory ◽

Memory Structures

Reading and comprehending content area texts require learners to effectively select and encode with hierarchically strategic memory structures in order to combine new information with prior knowledge. Unfortunately, evidence from state and national tests shows that children fail to successfully navigate the reading comprehension challenges they face. Schools have struggled to find approaches that can help children succeed in this important task. Typical instruction in classrooms across the country has focused on procedural application of strategies or content-focused approaches that encourage rich discussions. Both approaches have achieved success but have limitations-related transparency and specificity of scaffolds and guidance for the teacher and learner in today’s diverse and complex classroom settings. The text structure strategy combines content and strategy to provide pragmatic, transparent, and scaffolded instruction addressing these challenges. A web-based intelligent tutoring system for the text structure strategy, named ITSS, was designed and developed to provide consistent and high-quality instruction to learners in Grades 4 and 5 about how to read, select main ideas, encode strategic memory structures, make inferences, and monitor comprehension during reading. In this article, we synthesize results from two recent large-scale randomized controlled studies to showcase how the ITSS supports selection and encoding of students’ strategic memory structures and how prior knowledge affects the memory structures. We provide greater depth of information about such processing than examined and reported in extant literature about overall increases in reading comprehension resulting from students using ITSS.

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