A framework for self‐regulated digital learning (SRDL)
Abstract
This article develops a framework for self‐regulated digital learning, which supports for self‐regulated learning (SRL) in e‐learning systems. The framework emphasizes 8 features: learning plan, records/e‐portfolio and sharing, evaluation, human feedback, machine feedback, visualization of goals/procedures/concepts, scaffolding, and agents. Each feature facilitates or supports one or more SRL skills, including planning, monitoring and evaluating learning, applying appropriate cognitive strategies, and setting standards of products or performance. The implementation in domain‐general and ‐specific systems as illustrated by web‐based inquiry and problem‐solving are discussed. Examples and learning effects are elicited from the literature to demonstrate various designs. Approaches for designing SRL systems, educational implications, and new directions for future research incorporating SRL into digital learning are presented.
Lay Description
What is already known about this topic:
- An increasing amount of information and learning materials is delivered in a digital format, which requires self‐regulation for effective learning.
- Individual efforts have been made to facilitate self‐regulated learning in domain‐general/specific learning systems.
What this paper adds:
- A synthesized framework is developed to support self‐regulation in e‐learning.
Implications for practice and/or policy:
- Online learning via MOOCS or open courses would be enhanced by integrating the SRDL framework into the systems.
