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The effectiveness of intelligent tutoring systems on K‐12 students' reading comprehension: A meta‐analysis
Author(s) -
Xu Zhihong,
Wijekumar Kausalai Kay,
Ramirez Gilbert,
Hu Xueyan,
Irey Robin
Publication year - 2019
Publication title -
british journal of educational technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.79
H-Index - 95
eISSN - 1467-8535
pISSN - 0007-1013
DOI - 10.1111/bjet.12758
Subject(s) - reading comprehension , computer science , strictly standardized mean difference , reading (process) , comprehension , meta analysis , multimedia , variance (accounting) , mathematics education , confidence interval , statistics , psychology , mathematics , medicine , accounting , political science , law , business , programming language
Abstract This meta‐analysis examined the effectiveness of improving reading comprehension for students in K‐12 classrooms using intelligent tutoring systems (ITSs), a computer‐based learning environment that provides customizable and immediate feedback to the learner. Nineteen studies from 13 publications incorporating approximately 10 000 students were included in the final analysis; using robust variance estimation to account for statistical dependencies, the 19 studies yielded 88 effect size estimates. The meta‐analysis indicated that the overall random effect size of ITSs on reading comprehension was 0.60 (using a mix of standardized and researcher‐designed measures) with a 95% confidence interval 0.36 to 0.85 ( p < 0.001). This review confirms previous studies comparing ITSs to human tutoring: ITSs produced a small effect size when compared to human tutoring (0.20, 0.02–0.38, p = 0.036, n = 21). All comparisons to human tutoring used standardized measures. This review also found that ITSs produced a larger effect size on reading comprehension when compared to traditional instruction (0.86) for mixed measures and (0.26) for standardized measures. These findings may be of interest to practitioners and policy makers seeking to improve reading comprehension using consistent and accessible ITSs. Recommendations for researchers include conducting studies to understand the difference between traditional and updated versions of ITSs and employing valid and reliable standardized tests and researcher‐designed measures.