When John Sweller wrote his seminal paper on Cognitive Load Theory (CLT) in 1988 (Sweller, 1988) he was primarily interested in the differences in how experts and novices approached problem solving for learning and education. As the community of interest grew, researchers realized that how the information was presented to a learner (problem-solver) could help to guide problem solving and therefore improve learning and retention. This research occurred at a time when the age of digital communications and computer usage was exploding across the globe. During this time Researchers such as Richard Mayer (Mayer & Moreno, 2003) attempted to develop heuristics that would help people optimize the display of digital information for learners. Still others (Lavie, 2010; Lavie, Hirst, de Fockert, & Viding, 2004) started looking at the other side of the equation, i.e., human attention and understanding, to try to understand how that attribute of the human eye-brain system could best be guided to make more efficient use of the displayed information (Figure 1). That research determined that to focus attention on the desired information, the distracting effects of all other information must be reduced or removed. This led to more research in ways to optimize low cognitive load learning and work environments.
It can be seen that the development of cognitive load theory research for the first two decades after Sweller’s paper, was rooted in the belief that cognitive load levels in working memory could only be lowered by reducing the amount or complexity of the information being presented to the learner.
A Major Change in Direction for Cognitive Load Theory
In 2012, an important upgrade to Cognitive Load Theory by Fred Paas and John Sweller changed the direction of CLT research forever. During his research John Sweller had become aware of the work of David Geary of the University of Iowa, in Evolutionary Educational Psychology. Dr. Geary made the convincing case that, because of evolution, humans learned socially-relevant information, which he designated as “biologically-primary’ (Geary, 2002), far easier than culturally-relevant information (i.e., biologically secondary) such as mathematics and some of the sciences. His proof was given by examples of some tasks that babies learn automatically without any instruction at all. These include socially-important skills such as turning the head towards a mother’s breast or learning how to recognize her voice or face. Researchers already knew that presenting information in the context of a survival situation causes learners to learn and retain that information much better. This suggested, for the first time, that all information is not treated equally in working memory. In 2012, Paas and Sweller upgraded CLT to include the idea of biologically primary and secondary information (Paas & Sweller, 2012).
My Research in Cognitive Load Theory
I was working on my Ph.D. dissertation experiment at this time. Dr. Fred Paas, a leading theorist in the international CL community, was my dissertation Committee Content expert. I was looking for ways to improve learning environments and found what I believed was, evidence of both cognitive load reduction in response to added environmental stimuli and gender effects in my data (Figure 2) (Bevilacqua, Paas, & Krigbaum, 2016)..
Over the next five years, I continued to run human experiments and reported my data at several international CLT conferences. Unfortunately, these results were met with a large negative reaction from the Academic community. Not only was I suggesting that it was possible to reduce cognitive load while adding information to working memory, I was suggesting something considered not politically or socially correct in reporting that males and females might process sensory information differently. According to the community, I had to be wrong. I had bypassed tradition by developing my own CL measurement instrument and had not used the traditional subjective rating scales commonly used by other researchers. Therefore, it was suggested that my test methods were flawed.
Despite the consternation that my experimental results generated, I received my Ph.D. and that should have been the end of it, but I was sure my results were correct. In 2018 I wrote a commentary paper in the refereed journal, Educational Psychology Review. In that paper I wrote,
“Recent upgrades to cognitive load theory suggest that evolutionary processes have shaped the way that working memory processes different kinds of information (Paas and Sweller 2012; Sweller 2008; Sweller et al. 2011). …………. If one accepts this new evolutionary interpretation of the cognitive load theory (CLT) framework then by extension one must consider that known evolutionary differences in male and female biology and psychology suggests that some kinds of biologically primary knowledge are gender-specific.”(Bevilacqua, 2017, p.1).
My argument at the time was that, if you were going to adopt the evolutionary view, you had to accept all of it and not just pick and choose the parts that fit your current belief system.
In February of 2019 the CL community responded to my paper by publishing the results of a meta-study that went back and re-examined data sets from previous CL experiments (Castro, et al., 2019). The authors, citing my paper said,
“…..the key finding, supporting Hypothesis 1, is that learning from dynamic or static visualizations was influenced by the gender of the student. This result aligns with the comments by Bevilacqua (2017) that cognitive load theory should investigate the gender effects in cognitive processes.”(Castro-Alonzo, et l., p 19).
Although several of the authors wanted to include my finding that CL can be reduced while adding information to working memory, there was not a consensus so that proof has been left to later in 2020 when current COVID-19 restrictions are lifted and researchers can once again access their laboratories.
These New Discoveries Will Completely Change How Cognitive Load is Managed in Military Systems
As new technology-rich systems for warfighters are being rapidly developed and fielded, military program managers are concerned with the added effects of high cognitive load on warfighter performance. Systems that rely on technologies such as augmented reality / virtual reality, new communications, surveillance and cyber systems all have the possibility that, in spite of the use of advanced technology, these systems could actually decrease overall warfighter performance. Unfortunately, most CL pundits are still recommending outdated CL reduction techniques to their military customers because their knowledge of Cognitive Load comes from books and not personal testing and experimentation. If not stopped, this will result in millions of wasted dollars and overcomplicate already complex systems.
In my next blog article, Part II, I will discuss the implications of the new discoveries discussed here on current and future technological developments in the US military.
Bevilacqua, A., Paas, F., & Krigbaum, G. (2016). Effects of motion in the far peripheral visual field on cognitive test performance and cognitive load. Perceptual and Motor Skills, 122(2), 452-469. http://dx.doi.org/10.1177/0031512516633344
Bevilacqua, A. (2017). Commentary: Should gender differences be included in the evolutionary upgrade to cognitive load theory? Educational Psychology Review, 29(1), 189–194. https://doi.org/10.1007/s10648-016-9362-6.
Castro-Alonso, J., Wong, M., Adesope, O., Ayers, P., & Paas, F., (2019). Gender Imbalance in Instructional Dynamic Versus Static Visualizations: a Meta-analysis. Educational Psychology Review. https://doi.org/10.1007/s10648-019-09469-1
Geary, D. C. (2002). Principles of evolutionary educational psychology. Learning and Individual Differences, 12, 317-345. Retrieved from https://web.missouri.edu/~gearyd/GearyEvoEd.pdf
Lavie, N. (2010). Attention, distraction and cognitive control under load. Current Directions in Psychological Science, 19(3), 143-148.
Lavie, N., Hirst, A., de Fockert, J. W., & Viding, E. (2004). Load theory of selective attention and cognitive control. Journal of Experimental Psychology: General, 133(3), 339-354. http://dx.doi.org/10.1037/0096-34188.8.131.529
Mayer, R. E., & Moreno, R. (2003). Nine ways to reduce cognitive load in multimedia learning. Educational Psychologist, 38(1), 43–52. https://doi.org/10.1207/S15326985EP3801_6
Paas, F., & Sweller, J. (2012). An evolutionary upgrade of cognitive load theory: Using the human motor system and collaboration to support the learning of complex cognitive tasks. Educational Psychology Review, 24, 27-45. http://dx.doi.org/10.1007/s10648-011-9179-2
Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12, 257-285.