The Self-Regulation-View in Writing-to-Learn: Using Journal Writing to Optimize Cognitive Load in Self-Regulated Learning
By Matthias Nückles, Julian Roelle, Inga Glogger-Frey, Julia Waldeyer, Alexander Renkl. Educational Psychology Review, 2020
187 citations recorded by the source corpus.
We propose the self-regulation view in writing-to-learn as a promising theoretical perspective that draws on models of self-regulated learning theory and cognitive load theory. According to this theoretical perspective, writing has the potential to scaffold self-regulated learning due to the cognitive offloading written text generally offers as an external representation and memory aid, and due to the offloading, that specifically results from the genre-free principle in journal writing. However, to enable learners to optimally exploit this learning opportunity, the journal writing needs to be instructionally supported. Accordingly, we have set up a research program—the Freiburg Self-Regulated-Journal-Writing Approach—in which we developed and tested different instructional support methods to foster learning outcomes by optimizing cognitive load during self-regulated learning by journal writing. We will highlight the main insights of our research program which are synthesized from 16 experimental and 4 correlative studies published in 16 original papers. Accordingly, we present results on (1) the effects of prompting germane processing in journal writing, (2) the effects of providing worked examples and metacognitive information to support students in effectively exploiting prompted journal writing for self-regulated learning, (3) the effects of adapting and fading guidance in line with learners’ expertise in self-regulated learning, and (4) the effects of journal writing on learning motivation and motivation to write. The article closes with a discussion of several avenues of how the Freiburg Self-Regulated-Journal-Writing Approach can be developed further to advance research that integrates self-regulated learning with cognitive load theory.
Subfields: Developmental and Educational Psychology, Experimental and Cognitive Psychology
View Paper: https://www.semanticscholar.org/paper/30c1ad6e56c3101aadd1e471d15975b3b8a1706c
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In Developmental and Educational Psychology
Citations in the corpus
- The Metacognitive Demands and Opportunities of Generative AI (2023, background): “…perspective of metacognition, when considered with the unique features of GenAI—model flexibility, generality, and originality—presents an opportunity to realize what Alan Kay proposed as a “grand collaboration” with “agents: computer processes that act as guide, as coach, and as amanuensis” [88].”