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- Vol 7 RE: App B
- Vol 7 RE: Chapters 7, 11, App D
intelligent tutoring systemslearning outcomesadaptive instructionstep-based guidanceinstructional feedbackdomain modelsprocedural knowledgemeta-analysisJournal article Evidence summaryAt a glance
This meta-analysis evaluates intelligent tutoring systems (ITS)—programs that model learners and adapt instruction—against several alternative learning conditions. The authors synthesised 107 effect sizes from studies spanning school, university, and workplace settings and many subject areas.
Key ideas
Overall, students using an ITS achieved better learning outcomes than those receiving large-group instruction, textbook or workbook study, and other computer-based instruction. Effects were smaller when ITS were compared with individualised human tutoring or small-group instruction, showing that the relevant comparison matters. The analysis also examined system type, procedural versus declarative knowledge, assessment type, and design features as potential moderators. Results support the value of step-based guidance, feedback, and adaptation but reveal substantial variation among systems and studies.
Why it matters
For educators, the paper does not imply that any software labelled intelligent will work; benefits depend on sound domain models, close alignment between tutoring and assessment, and thoughtful integration with teaching.
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Edition abbreviations
- TE
- Teacher Edition
- PE
- Practice Edition
- RE
- Research Edition
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