Computer Minds
ATD Blog

What Do You Know: Do Our Minds Work Like Computers?

Wednesday, June 14, 2017

When people discuss how the human mind works, they often use computer terminology. In cognitive psychology, we see the terms working memory for actively processing information, and long-term memory for storing information. Sounds a lot like RAM and hard drive storage. 

This way of looking at the human mind perceives human thinking as information processing, much like how computers process information. I was recently asked if this was an accurate way of looking at how we process information. Before I present my reply here, try answering the following question about whether you think our minds are like computers. 

QUESTION: Do Our Minds Work Like Computers? Select the Best Answer. 

A. Yes. That’s why we often use computer analogies to describe how the mind works. 

B. Somewhat. We use computer analogies to describe how the mind works, but it doesn’t work exactly like a computer. 

C. We’re not all that sure how the mind works. Computer analogies are useful, but our minds don’t work like one. 

Cognitive psychology offers helpful insights for the design of learning, including how to: 

  • Help people see what is important and not overload their working memory. 
  • Support memory. 
  • Build accurate schema in long-term memory. 

It offers metacognitive strategies that research shows help people plan, monitor, and assess their learning so they can be more self-sufficient learners. 

What Do We Know and How Do We Know It? 

One of the most researched areas of cognition is memory. Researchers and scientists express different ideas about how the brain processes, codes, and uses information. But we know that the mind does not actually process information like a computer does. We know that memory is not a tape recorder of our experiences. But there is much debate about exactly how information is processed and stored. Although we use computer terms to describe how the mind works, the words are metaphors. They aren’t meant to imply that our mind operates like a computer does. 

Recent research has led to interesting insights about memory neurons, which are thought to store and retrieve memories. Memory scientists think that memory changes happen due to perceived connections between memories, the value of the memories, and how often memories are retrieved. Meaning is critical to what is retained and what each item is connected to. The way that memory works is under intense research; the data we have are still preliminary information. So, when people say neuro[subject] or brain-based [topic], what they are really talking about is cognitive [topic], because our understanding of how the brain works is still in its infancy. Understanding how we think and learn (cognition) is farther along. 


Individual Cognition. Enough? 

This brings up an important question about what is important to study. What are we really interested in: how individuals learn, or the environment in which they learn and the reasons for learning? Donald Norman, a well-known cognitive and usability scientist and the author of The Design of Everyday Things (a book everyone in our field should read), describes issues with the traditional information processing view of cognition. He explains that thinking is far more than the biological acts of perception, encoding, memory retrieval, and so on. Norman says we are not purely biological beings, so cognition isn’t purely biological either. Humans are social and cultural beings as well as biological. 

For example, when we learn how to use a new system on the job, we don’t learn it simply to encode and store it. We learn it so we can do our job, not get fired, get a promotion, and become even better at something we are proud we can do.  

We do not process information like a computer does. We think, consider, share, ask questions, and get feedback from others. We misconstrue and misunderstand. And there’s plenty of research to show that, unlike computers, our thinking is not all that rational (look up confirmation bias). Learning isn’t only an individual act; it can and does affect others. What a group of people knows can have a very large impact for good or not-so-good. A view of learning that only focuses on individual cognition, then, is missing essential elements.  

Cognitive psychology typically looks at cognition from an individual’s perspective, but many skills are learned for performance in a social context. We typically learn a great deal from others on the job: how to fit in, job tasks, social norms, who to go to for answers, and more. An information-processing view of learning is helpful for understanding many elements of individual learning and designing good instruction. 


But we are not computers. Far from it. We work with people, and much of what we learn will be from and with others. Not seeing and supporting the interdependence between individual learning and organizational learning reduces both individual and organizational effectiveness. The answer to the question at the beginning of this blog post is C: Computer analogies are useful, but don’t provide the complete picture. 

The point here is that an information-processing view is valuable, and instruction built with insights from this point of view will be far better than simply trying to deliver content to people without any context about how they learn. But because we aren’t computers, the computer-brain analogy only a beginning source of information about how to design instruction. As such, it can tell us how to make instruction easier to learn, apply, and remember. And that’s important. 


But we must design according to how people use what they learn. A lot of how people use what they learn is social. So, we also need to understand the social implications of learning. An information-processing view of learning is necessary, but insufficient at capturing the social aspect of the learning process. Some people have said you must take an individual view of learning or a social view of learning. Because both types of learning occur, there’s no reason to not use the best insights from each. 

Further Reading 

Kandarakis, A. G. & Poulos , M.S. (2008). Teaching implications of information processing theory and evaluation approach of learning strategies using lvq neural network. WSEAS Transactions on Advances in Engineering Education, 3(5) 111-119. 

Lutz, S., & Huitt, W. (2003). Information processing and memory: Theory and applications. Educational Psychology Interactive. Valdosta, GA: Valdosta State University. 

McLeod, S. A. (2008). Information Processing. 

Norman, N. (1980). Twelve issues for cognitive science. Cognitive Science, A Multidisciplinary Journal. 4(1), 1-32. 

Oxenham, S. (July 18. 2016). Thousands of fMRI brain studies in doubt due to software flaws. New Scientist.  

Palinscar, A. S. (1998). Social constructivist perspectives on teaching and learning. Annual Review of Psychology, 49, 345-375. 

Piccinini, G. & Scarantino, A. (2011). Information processing, computation, and cognition. Journal of Biological Physics. 37(1), 1–38. 

Templeton, G. (December 2, 2015). The more we learn about memory, the weirder it gets.

About the Author

Patti Shank, PhD, CPT, is a learning designer and analyst at Learning Peaks, an internationally recognized consulting firm that provides learning and performance consulting. She is an often-requested speaker at training and instructional technology conferences, is quoted frequently in training publications, and is the co-author of Making Sense of Online Learning, editor of TheOnline Learning Idea Book, co-editor of The E-Learning Handbook, and co-author of Essential Articulate Studio ’09.

Patti was the research director for the eLearning Guild, an award-winning contributing editor forOnline Learning Magazine, and her articles are found in eLearning Guild publications, Adobe’s Resource Center, Magna Publication’s Online Classroom, and elsewhere.

Patti completed her PhD at the University of Colorado, Denver, and her interests include interaction design, tools and technologies for interaction, the pragmatics of real world instructional design, and instructional authoring. Her research on new online learners won an EDMEDIA (2002) best research paper award. She is passionate and outspoken about the results needed from instructional design and instruction and engaged in improving instructional design practices and instructional outcomes.

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