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ERIC Number: ED588058
Record Type: Non-Journal
Publication Date: 2018-Aug-31
Pages: 19
Abstractor: As Provided
ISBN: N/A
ISSN: EISSN-
EISSN: N/A
Exploring an Intelligent Tutoring System as a Conversation-Based Assessment Tool for Reading Comprehension
Shi, Genghu; Lippert, Anne M.; Shubeck, Keith; Fang, Ying; Chen, Su; Pavlik, Philip, Jr.; Greenberg, Daphne; Graesser, Arthur C.
Grantee Submission
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 system (AutoTutor) to assess reading comprehension ability in 52 low-literacy adults who interacted with the system. We analyzed participants' accuracy and time spent answering questions in conversations in lessons that targeted four theoretical components of comprehension: Word, Textbase, Situation Model, and Rhetorical Structure. Accuracy and answer response time were analyzed to track adults' proficiency for comprehension components, and we analyzed whether the four components predicted reading grade level. We discuss the results with respect to the advantages that a conversational intelligent tutoring system assessment may provide over traditional assessment tools and the linking of theory to practice in adult literacy. [This is the online version of an article published in "Behaviormetrika."]
Publication Type: Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: Institute of Education Sciences (ED); National Science Foundation (NSF)
Authoring Institution: N/A
Identifiers - Location: Georgia (Atlanta); Canada (Toronto)
Identifiers - Assessments and Surveys: Woodcock Johnson Tests of Achievement
IES Funded: Yes
Grant or Contract Numbers: R305C120001; ACI1443068