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This review describes a meta-analysis of findings from 50 controlled evaluations of intelligent computer tutoring systems. The median effect of intelligent tutoring in the 50 evaluations was to raise test scores 0.66 standard deviations over conventional levels, or from the 50th to the 75th percentile. However, the amount of improvement found in an evaluation depended to a great extent on whether improvement was measured on locally developed or standardized tests, suggesting that alignment...
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Dynamic geometry software (DGS) aims to enhance mathematics education. This systematic review and meta-analysis evaluated the quasi-experimental studies on the effectiveness of DGS-based instruction in improving students’ mathematical achievement. Research articles published between 1990 and 2013 were identified from major databases according to a prespecified search strategy and selection criteria. A meta-analysis was conducted based on the random-effects model to evaluate the effectiveness...
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In this study, we meta-analyzed empirical research of the effectiveness of intelligent tutoring systems (ITS) on K–12 students’ mathematical learning. A total of 26 reports containing 34 independent samples met study inclusion criteria. The reports appeared between 1997 and 2010. The majority of included studies compared the effectiveness of ITS with that of regular classroom instruction. A few studies compared ITS with human tutoring or homework practices. Among the major findings are (a)...
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This study examines the impact of computer technology (CT) on mathematics education in K-12 classrooms through a systematic review of existing literature. A metaanalysis of 85 independent effect sizes extracted from 46 primary studies involving a total of 36,793 learners indicated statistically significant positive effects of CT on mathematics achievement. In addition, several characteristics of primary studies were identified as having effects. For example, CT showed advantage in promoting...
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Outcome measure
Instructional domain (subject)
Education Level and Type
- K-12 (5)
- Primary 7-10 (2)
- Tertiary (1)
Groups of students
- At-risk (1)
- Learning difficulties (1)
- Low-performing (2)
- Low socio-economic status (2)
- SEND (1)
School or home
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- Home (1)
- Mixture (1)
- School (4)
Moderating variables
- Assessments (1)
- Attainment level of students (2)
- Design-type/ testing instruments (2)
- Length of time (3)
- Novelty Effect (1)
- Peer involvement/group learning (1)
- Student characteristics (1)
- Subject (1)
- Teacher involvement (1)
- Teacher pedagogy/implementation (1)
- Type of knowledge or task (exposing, procedural, active, etc (1)
Tech Hardware
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- Internet (1)
- Laptops (1)
- Multimedia (1 or more) (1)
Tech Software
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- Computer-Assisted Instruction (CAI) (2)
- Computer-Based Teaching (CBT) (1)
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- Dynamic Geometry Software (1)
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- Intelligent Tutoring (2)
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- Virtual manipulatives (1)
Tech mechanism
Learning Approach
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- Blended learning (1)
- Classroom learning (3)
- Remote learning (1)
Teacher Pedagogy
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- Collaboration (2)
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- Project-based learning (1)
Research methods
Effect size/ heterogeneity
HIC/LMIC
- HIC (high income) (3)
- Mixture or unknown (4)
Quality of research
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- Medium: 4 or above (4)
Geography if specific
- USA (2)