Review of Educational Research · 2016 · 316 citations · 105 references
EducationAdult EducationEducational AssessmentCurriculum DesignMeta-analysisStem EducationProblem-solving StrategiesProblem-solving SupportStem AssessmentStem Conceptual UnderstandingTechnology IntegrationAssessment LevelsCurricular ScaffoldingExperimental StudiesHigher-order Thinking SkillsPedagogical ScaffoldingProblem-centered CurriculumProblem-centered LearningScaffolded Learning Environments
Computer-based scaffolding assists students as they generate solutions to complex problems, goals, or tasks, helping increase and integrate their higher order skills in the process. However, despite decades of research on scaffolding in STEM (science, technology, engineering, and mathematics) education, no existing comprehensive meta-analysis has synthesized the results of these studies. This review addresses that need by synthesizing the results of 144 experimental studies (333 outcomes) on the effects of computer-based scaffolding designed to assist the full range of STEM learners (primary through adult education) as they navigated ill-structured, problem-centered curricula. Results of our random effect meta-analysis (a) indicate that computer-based scaffolding showed a consistently positive (ḡ = 0.46) effect on cognitive outcomes across various contexts of use, scaffolding characteristics, and levels of assessment and (b) shed light on many scaffolding debates, including the roles of customization (i.e., fading and adding) and context-specific support. Specifically, scaffolding's influence on cognitive outcomes did not vary on the basis of context-specificity, presence or absence of scaffolding change, and logic by which scaffolding change is implemented. Scaffolding's influence was greatest when measured at the principles level and among adult learners. Still scaffolding's effect was substantial and significantly greater than zero across all age groups and assessment levels. These results suggest that scaffolding is a highly effective intervention across levels of different characteristics and can largely be designed in many different ways while still being highly effective.
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Statistical Power Analysis for the Behavioral Sciences
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Bias in meta-analysis detected by a simple, graphical test
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