A Bayesian Network Meta-Analysis to Synthesize the Influence of Contexts of Scaffolding Use on Cognitive Outcomes in STEM Education

• Published in: Review of educational research Vol. 87; no. 6; pp. 1042 - 1081
• Main Authors: Belland, Brian R., Walker, Andrew E., Kim, Nam Ju
• Format: Journal Article
• Language: English
• Published: Los Angeles, CA SAGE Publications 01.12.2017; American Educational Research Association
• Subjects: Active Learning; Adult Education; Argumentation; Bayesian analysis; Bayesian Statistics; Coding; Computer Assisted Instruction; Disabilities; Educational attainment; Educational Technology; Effect Size; Elementary Secondary Education; English Language Learners; Higher Education; Inquiry; Instructional scaffolding; Intelligent Tutoring Systems; Learning disabilities; Markov Processes; Mathematics; Meta Analysis; Monte Carlo Methods; Problem Based Learning; Problem solving; Scaffolding; Scaffolding (Teaching Technique); Secondary Education; STEM Education; Systematic review; Teaching Methods; cognitive tutor; scaffold; intelligent tutoring systems; Bayesian network meta-analysis; problem-centered instruction; STEM
• ISSN: 0034-6543; 1935-1046
• DOI: 10.3102/0034654317723009

Computer-based scaffolding provides temporary support that enables students to participate in and become more proficient at complex skills like problem solving, argumentation, and evaluation. While meta-analyses have addressed between-subject differences on cognitive outcomes resulting from scaffolding, none has addressed within-subject gains. This leaves much quantitative scaffolding literature not covered by existing meta-analyses. To address this gap, this study used Bayesian network meta-analysis to synthesize within-subjects (pre-post) differences resulting from scaffolding in 56 studies. We generated the posterior distribution using 20,000 Markov Chain Monte Carlo samples. Scaffolding has a consistently strong effect across student populations, STEM (science, technology, engineering, and mathematics) disciplines, and assessment levels, and a strong effect when used with most problem-centered instructional models (exception: inquiry-based learning and modeling visualization) and educational levels (exception: secondary education). Results also indicate some promising areas for future scaffolding research, including scaffolding among students with learning disabilities, for whom the effect size was particularly large (ḡ = 3.13).