Increase Readability, Reduce Cognitive Load
Freeing Working Memory for Processing Meaning
Meaghan Crowley-Sullivan, M.Ed., M.A.
How does Readability Affect Cognitive Load, Fluency, and Comprehension?
Research studies have shown a direct connection between reading fluency and comprehension. Individuals who process and recognize words quickly can determine the meaning and engage in critical thinking skills faster and more effectively than their peers who take longer to do so. While scientific discovery continues, many researchers see an explanation in the Cognitive Load Theory.
John Sweller developed the Cognitive Load Theory based on a three-part understanding of how humans process information. Bombarded daily, the brain analyzes information through our sensory, then working (short-term), and finally, long-term memories. Cognitive load theory looks at the amount of intrinsic and extraneous load that the working memory can process simultaneously. Since each individual has a limited capacity of working memory (5 to 9 chunks of information at once), any additional cognitive load placed on information processing can impede an individual’s ability to progress through the three stages fully.
Although seeming like a relatively simple task to many adults, reading to understand is a complex skill that requires the use of several cognitive processes simultaneously. Taking the components of word recognition, decoding, and language comprehension, into consideration, individuals manage multiple strands and skills within their working memory. When the intrinsic load is great, requiring significant working memory to process the text or the extraneous load of the individual’s context becomes too much, it can significantly impact the individual’s ability to make meaning from their reading. When the presentation of the text is in a format that is too overwhelming, this extraneous load takes too much processing, leaving less working memory space to understand it.
Therefore, since both intrinsic and extraneous loads affect cognitive processing, making adjustments to lessen the load on an individual’s working memory can positively impact the ability to process more effectively. As an individual reads, these adjustments can increase fluency, accuracy, and, ultimately, comprehension.
Why Measure Fluency?
Fluency is often an early indicator alerting teachers to underlying issues that impact comprehension. Defined as accurate and automatic word recognition at an appropriate rate of speed and expression, fluency difficulties point to a lack of automation in the processing of text, patterns, and phonological letter/sound relations. Studies have likewise shown a direct connection between student fluency and the likelihood of effective understanding.
In other words, the cognitive load expected of a non-fluent reader trying to decode is taking up too much space in the working memory to be able to focus on rate, prose, expression, and understanding. Comprehension ultimately becomes blocked or limited because the reader’s cognitive abilities are consumed with decoding. Lack of fluency is an indicator of stress on the cognitive load of an individual’s working memory.
“When text-specific processes, particularly decoding, are not fluent and automatic, reading comprehension is weakened. This is because weak decoding skills act as a bottleneck, increasing cognitive load and leaving fewer cognitive resources available for reading comprehension.”
Connor, et al.
What Effect Does Text Readability Have?
Sweller argued that instructional design could reduce cognitive load in learners. Cognitive Load Theory suggests that any reduction to required processing frees up working memory. Making changes to a text format (font, size, character width or spacing, weight, and line spacing) to improve readability for an individual reader may reduce the extraneous load on the reader’s cognitive processing. The result is freeing up more space in the working memory for the decoding or word recognition components of reading.
For individuals learning to read, reducing extraneous load allows their working memory to devote more time to the decoding process. This allows the reader to practice the decoding component more carefully, enhance its automation, and begin to think more about the meaning of the content. Likewise, for readers who have already mastered decoding, cutting down on the extraneous load can free up working memory for other reading tasks. The individual can better identify vocabulary, link content to their background knowledge, and focus more on higher-level aspects of reading like critical thinking and analysis.
In summary, personalized text formats can reduce cognitive load, freeing up working memory for other components of the reading process. Making the connection between text presentation, cognitive load, reading fluency, and comprehension creates an opportunity to support an individual’s overall success and growth as a reader.
About Meaghan Crowley-Sullivan Meaghan Crowley-Sullivan, M.Ed., M.A., is the Curriculum and Professional Learning Developer for the iDEAL Institute at Loyola Marymount University. She completed undergraduate and graduate degrees from the University of Notre Dame, where she graduated with a Bachelor of Arts in American Studies, a minor in Education, Schooling and Society, a Master of Education in Elementary Education, and a Master of Arts in Educational Leadership. Working as an expeditionary learning and blended learning teacher both in California and Colorado, her experience as a lower and upper elementary teacher has been shaped by her passion for forward-thinking instructional models, her commitment to encouraging teacher collaboration, and the desire to utilize technology to meet the needs of all students, while promoting creativity, collaboration, critical thinking, and communication.
Connor, Carol McDonald et al. “Building Word Knowledge, Learning Strategies, and Metacognition with the Word-Knowledge E-Book.” Computers & education vol. 128 (2019): 284-311. doi:10.1016/j.compedu.2018.09.016
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Sweller, J (June 1988). “Cognitive load during problem solving: Effects on learning” (PDF). Cognitive Science. 12 (2): 257–285. doi:10.1207/s15516709cog1202_4.