The human brain has an unlimited capacity for evolving knowledge. In instructional design, learners must be the center of all stages of a specific module via research, development, design, or implementation. How humans understand and process information through brain-based behavior can help deliver knowledge in ways that learners can receive, process, and store information adequately for later retrieval. While there is no direct link between neuroscience and how the brain processes information, there is excellent scientific evidence that the link has yet to be discovered (Jensen, 2008). Therefore, as facilitators of learning, it is crucial to understand how the brain, as an organ, functions (neuroscience) concerning education.
Inside the Cortex is where information processed is categorized into somatosensory (Parental lobes), visual (Occipital lobes), complex auditory (Temporal lobes), and lastly, “human” activities ( frontal lobes) (Ormrod, Schunk, & Gredler, 2009). After the Cortex’s lobes receive the information, knowledge remains in working memory until it is organized and stored for another similar stimulus. In summary, all knowledge is processed through the brain. How the brain uses perception, and relatability to organize and retrieve information can be classified as cognitive psychology backed by neuroscience. There is no direct relation between the two; however, one can’t exist without the other.
As outlined, the Cortex inside the brain is responsible for triggering responses to presented by stimuli, which can be presented in various fashions to the sensory receptors. Instructional designers can use neuroscience and how the brain interprets information through the effective use of sensory. Designing training plans should not over stimulate the sensory receptors in the CNS. Overwhelming the brain with the stimulus is no different than overworking your liver by consuming alcohol. Knowledge can be received and used while given a specific task, but with the more stimulus responses triggered, the less is committed organized long term memory.
Cerbin defines working memory as the mental space where we do conscious, progressive thinking; however, that space has limited capacity (Cerbin, n.d.). This temporary storage allows cognitive information processing to manipulate storage later (Gutierrez, 2014). Think of working memory as a bucket; when full, the information is tossed or spilled. Even though the plastic material the bucket, made of is thin plastic, the design indentations of the bucket still lower the storage capacity. The working memory, “bucket,” uses part of the storage with tasks processed in an automatic method. When working memory is full, and the learner is challenged with many things to organize, overload sets in often resulting in a disengaged learner, but more importantly, the inability to recall responses.
Karla Gutierrez, SH!FT Disruptive eLearning contributor outlines how to design eLearning using working memory strategies, activities, and resources that will enhance cognitive processing skills using brain-function while not overstimulating. Working memory strategies help achieve a schema, receiving parts of the objective in smaller pieces (Ormrod, Schunk, & Gredler, 2009). To manage the information at each level of the pedagogy, activities, and resources help learners store information in an organization to easily retrieve under relatable circumstances.
All learning starts with the neuroscience of the brain. These discoveries have helped us understand how the brain receives processes and stores information. Where the brain stores, the data is contengient on the amount of working memory in use. To ensure learning is as simplistic for learners to process, instructional designers can use SH!FT’s suggested working memory strategies, activities, and resources.
Cerbin, B. (n.d.). Working Memory as a Bottleneck in Learning – Exploring How Students Learn. Retrieved May 19, 2020, from https://sites.google.com/a/uwlax.edu/exploring-how-students-learn/working-memory-as-a-bottleneck-in-learning
Gutierrez, K. (2014, July 22). Designing eLearning to Maximize the Working Memory. Retrieved May 19, 2020, from https://www.shiftelearning.com/blog/bid/351491/Designing-eLearning-to-Maximize-the-Working-Memory
Jensen, Eric P. (2008). A Fresh Look at Brain-Based Education. Phi Delta Kappan, 89(6), 408–410. Retrieved from https://www.teachers.net/gazette/OCT08/jensen/
Ormrod, J., Schunk, D., & Gredler, M. (2009). Learning theories and instruction (Laureate custom edition). New York, NY: Pearson.