A Breakthrough in the Regulation of Human Cognitive Load: Decoding the Language of the Brain

Many of us grew up thinking about the senses (eyes, ears, nose, skin, and mouth) as the information/signal gatherers, the brain as the control center and the nervous system as the pathways that attach the brain to the muscles and internal organs. Although we now know that this simplistic view of how information is shared within the body is not exactly correct, for the sake of this discussion, we will use this classis paradigm as the basis of our discussion (Figure 1).

Figure 1: Classic View of the Pathway for Human Sensory Information

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PART II: The Impact of Important New Upgrades to Cognitive Load Theory on The Performance of Warriors Using Hi-Tech Systems

Introduction

In part I of this blog I laid the foundation for my claim that the Military needs to fully understand the recent upgrades to cognitive load theory (CLT) or risk wasting money, time and the performance improvements promised by new military technology. We followed the development of the theory from its genesis by John Sweller (1988) through 2012 when upgrades, based on research in the field of evolutionary educational psychology (Geary, 2008; Paas & Sweller, 2012) suggested that different kinds of information (social and cultural) are handled differently in working memory. Finally, we introduced new research that found that cognitive load could be actively controlled through the addition of specific visual stimuli that takes advantage of the brain’s bias towards socially-relevant information (Bevilacqua, Paas & Krigbaum, 2016: Bevilacqua 2017). It was also found that this bias works differently for males and females (Bevilacqua, 2017; Castro-Alonzo, et al., 2019). Continue reading “PART II: The Impact of Important New Upgrades to Cognitive Load Theory on The Performance of Warriors Using Hi-Tech Systems”

PART I: The Impact of Important New Upgrades to Cognitive Load Theory on The Performance of Warriors Using Hi-Tech Systems

Background

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. Continue reading “PART I: The Impact of Important New Upgrades to Cognitive Load Theory on The Performance of Warriors Using Hi-Tech Systems”

Artificial Intelligence and Machine Learning: Part 5: Complexity

In this series I am writing several blog articles about Artificial Intelligence. This week’s article, the last in the series, introduces the CORE toolset that can be used by the Government under an existing license to meet most of its AI/ML needs. Continue reading “Artificial Intelligence and Machine Learning: Part 5: Complexity”

Artificial Intelligence and Machine Learning: Part 1: Defining Artificial Intelligence

In this series, I am writing several blog articles about Artificial Intelligence. We finally have enough processing power and memory to accomplish great things. However, after 40 years of working in this field I am amazed at what some companies are trying to sell as Artificial Intelligence and Machine Learning. The purpose of these articles is to help the reader sift through the hype and discriminate real AI/ML from useless marketing that lacks real substance. This week’s articles concentrate on a simple but important aspect of the AI/ML problem….What is the REAL definition of AI and ML? Continue reading “Artificial Intelligence and Machine Learning: Part 1: Defining Artificial Intelligence”