Using latent transition analysis to identify effects of an intelligent tutoring system on reading comprehension of seventh-grade students
Latent transition analysis (LTA) was conducted on data from a recent cluster randomized controlled study of 1808 seventh-grade students’ use of a web-based intelligent tutoring system (ITSS). This analysis goes beyond traditional variable-centered methods to focus on profiles of learners and changes...
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Published in | Reading & writing Vol. 31; no. 9; pp. 2095 - 2113 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
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Springer Netherlands
01.11.2018
Springer Springer Nature B.V |
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Abstract | Latent transition analysis (LTA) was conducted on data from a recent cluster randomized controlled study of 1808 seventh-grade students’ use of a web-based intelligent tutoring system (ITSS). This analysis goes beyond traditional variable-centered methods to focus on profiles of learners and changes in reading class membership between pre- and post-tests for students with and without receiving ITSS intervention. A four-class model was obtained, consisting of poor readers (class 1), delayed readers (class 2), proficient readers (class 3), and readers with specific deficits in problem and solution (class 4). Analysis showed that students receiving the ITSS intervention were more likely than students without the intervention to transition into the proficient class regardless of their initial reading performance profiles. However, the odds ratio of transitioning into the proficient class (as opposed to staying in the same class) in the ITSS condition, compared to the control, was the highest (4.29) for initial readers with deficits in problem and solution, followed by initial poor readers (1.66) and initial delayed readers (1.50). Findings indicated that students in the ITSS condition had larger reading improvement than students in the control condition, particularly for readers with initial deficits in problem and solution. |
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AbstractList | Latent transition analysis (LTA) was conducted on data from a recent cluster randomized controlled study of 1808 seventh-grade students’ use of a web-based intelligent tutoring system (ITSS). This analysis goes beyond traditional variable-centered methods to focus on profiles of learners and changes in reading class membership between pre- and post-tests for students with and without receiving ITSS intervention. A four-class model was obtained, consisting of poor readers (class 1), delayed readers (class 2), proficient readers (class 3), and readers with specific deficits in problem and solution (class 4). Analysis showed that students receiving the ITSS intervention were more likely than students without the intervention to transition into the proficient class regardless of their initial reading performance profiles. However, the odds ratio of transitioning into the proficient class (as opposed to staying in the same class) in the ITSS condition, compared to the control, was the highest (4.29) for initial readers with deficits in problem and solution, followed by initial poor readers (1.66) and initial delayed readers (1.50). Findings indicated that students in the ITSS condition had larger reading improvement than students in the control condition, particularly for readers with initial deficits in problem and solution. |
Audience | Grade 7 |
Author | Beerwinkle, Andrea Malatesha Joshi, R. Zhang, Shuai Ji, Xuejun Ryan Lei, Puiwa Wijekumar, Kausalai (Kay) |
Author_xml | – sequence: 1 givenname: Xuejun Ryan surname: Ji fullname: Ji, Xuejun Ryan email: x.ryan.ji@ubc.ca organization: The University of British Columbia – sequence: 2 givenname: Andrea surname: Beerwinkle fullname: Beerwinkle, Andrea organization: Texas A&M University – sequence: 3 givenname: Kausalai (Kay) surname: Wijekumar fullname: Wijekumar, Kausalai (Kay) organization: Texas A&M University – sequence: 4 givenname: Puiwa surname: Lei fullname: Lei, Puiwa organization: The Pennsylvania State University – sequence: 5 givenname: R. surname: Malatesha Joshi fullname: Malatesha Joshi, R. organization: Texas A&M University – sequence: 6 givenname: Shuai surname: Zhang fullname: Zhang, Shuai organization: Texas A&M University |
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Cites_doi | 10.1080/10705511.2014.935751 10.1037/edu0000168 10.1037/a0021606 10.1177/0731948714550204 10.3102/00346543061002239 10.1080/10705510902751010 10.1037/0022-0663.93.1.141 10.3102/0002831206298171 10.1598/RRQ.45.1.4 10.1007/s11423-012-9263-4 10.2307/747349 10.1037/edu0000082 10.1037/0022-0663.94.3.486 10.1080/19345747.2013.853333 |
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Copyright | Springer Nature B.V. 2018 Reading and Writing is a copyright of Springer, (2018). All Rights Reserved. |
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SubjectTerms | CAI Computer assisted instruction Education Educational Technology Grade 7 Intelligent Tutoring Systems Intervention Language and Literature Linguistics Literacy Middle school students Neurology Program Effectiveness Psycholinguistics Reading comprehension Reading Difficulties Reading Improvement Reading Instruction Reading Skills Social Sciences Student Characteristics Technology Uses in Education Tutoring |
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Title | Using latent transition analysis to identify effects of an intelligent tutoring system on reading comprehension of seventh-grade students |
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