Use the special issue's design-process questions to shape new SRL scaffolds¶

Strategy · All strategies
Evidence · 6 claims (6 for) · 2 studies (1 review, 1 associational), q2 · 0 of 2 report an effect size · 5 claims rest on one study

Description¶

Rather than concrete guidelines, the introduction offers the contributions as inspiration for the scaffold design process. It poses design considerations for future designers: whether scaffolds are theory-based or data-driven, whether triggering is event- or time-based, whether scaffolds have a single or unique purposes, whether they affect the sequential nature of SRL, and to what extent they should attenuate effects of prior metacognitive abilities. "The papers in this issue can be used to inform the design process of new scaffolds."

Design Implications¶

Context¶

Requirements¶

• Designers must make explicit decisions on theoretical versus data-driven grounding, trigger timing, scaffold purpose, sequencing effects, and prior metacognitive ability

Constraints¶

• The introduction explicitly notes there are different ways to create effective and efficient scaffolds, so no single design recipe is endorsed

Target Learners¶

• university students
• secondary students

Target Learning Goals¶

• self-regulated learning
• metacognition

Affordances¶

• Sma Grid And What When How Scaffold Frameworks

Claims¶

• Pre-structured diagrams improved metacomprehension accuracy while self-assessment cues showed no differences [+W]
• Personalized SRL scaffolds showed higher compliance than no and non-personalized scaffolds, linked to better essay scores [+W]
• Frequent use of reflective prompts related to better strategic problem-solving and conceptual understanding [+W]
• Rule-triggered pedagogical agents increased SRL activities and learning outcomes relative to untriggered agents [+W]
• Metacognitive and strategic scaffold-use subgroups solved more problems correctly than moderate and low-use subgroups [+W]
• Behavioral and environmental regulation knowledge during digital SRL training predicted biology exam performance [+W]

Related Strategies¶

• Provide phase-specific teaching practices and environment features that foster student responsibility for learning in each phase of PBL
• GenAI learning interfaces should actively scaffold monitoring, evaluation, and AI-shaping behaviors adolescents may not bring to the interaction on their own

Examples¶

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Key Sources¶

• Joep van der Graaf, Michelle Taub, Yizhou Fan. (2023). Introduction to special issue on facilitating self-regulated learning with scaffolds: Recent advances and future directions. Metacognition and Learning. https://doi.org/10.1007/s11409-023-09364-9