4.1: Intelligence

Introduction to Intelligence, Neuroscience, and the Brain

Introduction
Intelligence is a concept that has been studied and debated for centuries, with different scholars emphasizing different aspects of what it means to be intelligent. Most definitions include the ability to learn from experience, adapt to new situations, and solve problems effectively. Psychologists often describe intelligence as a set of cognitive skills, including reasoning, memory, attention, and verbal ability. These skills are important because they determine how well a person can process information and respond to challenges. Neuroscientists expand on this idea by studying how neural networks in the brain support these skills. For example, when you solve a complex math problem, multiple areas of your brain work together, including regions responsible for logic, working memory, and attention. Understanding intelligence in this way helps explain why some people excel in certain tasks while others struggle. It also highlights that intelligence is not a single trait but a combination of many abilities. Charles Spearman argued that there is a single underlying factor, called general intelligence or “g,” that influences all cognitive tasks. Others, like Howard Gardner, suggest that there are multiple intelligences, such as linguistic, logical-mathematical, spatial, musical, bodily-kinesthetic, interpersonal, intrapersonal, and naturalistic abilities. These different views show how complex the concept of intelligence is and why it continues to be studied. Robert Sternberg proposed the Triarchic Theory of Intelligence, which includes analytical, creative, and practical components. Analytical intelligence involves problem solving and logical reasoning. Creative intelligence involves generating new ideas and thinking outside the box. Practical intelligence involves applying knowledge to real-world situations. These theories illustrate that intelligence is not just about doing well on a test but also about how we navigate everyday life. They also show that intelligence is influenced by both biology and environment. By understanding these theories, we gain a broader perspective on human potential. This understanding also helps educators develop teaching methods that cater to different types of intelligence. In neuroscience, these theories guide research into how specific brain regions support different kinds of thinking. Overall, defining intelligence is a dynamic process that reflects advances in both psychology and neuroscience.

Understanding intelligence requires exploring not only psychological concepts but also the biological foundations within the brain, which form the physical structures that make learning, memory, and reasoning possible. Neuroscience, which is the study of the nervous system, offers powerful insights into how brain structures and functions contribute to cognitive abilities. These cognitive abilities include problem solving, logical reasoning, the ability to store and recall memories, and the speed with which information can be processed. By looking at intelligence through the lens of neuroscience, we begin to see that intelligence is not just an abstract concept, but something that is closely tied to physical mechanisms in the brain. This intersection is important because it allows scientists and educators to understand why people learn differently and how various conditions might affect learning and reasoning. Neuroscience has grown rapidly over the past century, providing new tools like functional imaging and computational modeling to study intelligence. When we examine intelligence scientifically, we also begin to understand how factors such as environment, genetics, and experience interact to shape mental abilities. For instance, research shows that enriched environments can lead to stronger neural connections, which may contribute to higher cognitive performance. This connection between biology and behavior has real-world implications, from designing educational programs to creating therapies for brain injuries. It also shows that intelligence is dynamic rather than fixed, changing with development, experience, and health. Researchers today explore how specific brain regions like the prefrontal cortex work together to solve complex problems. They also investigate how communication between regions influences performance on intelligence tests. This chapter introduces key ideas from both psychology and neuroscience to explain how intelligence emerges. It also provides a foundation for understanding how brain research can inform our everyday lives. Throughout the chapter, you will encounter examples of how basic neural processes relate to higher-level reasoning. These examples help bridge the gap between abstract concepts and biological mechanisms. By exploring intelligence from this integrated perspective, we can develop more effective learning strategies and interventions. This perspective also helps us appreciate the remarkable adaptability of the human brain. The study of intelligence through neuroscience enriches our understanding of both fields. It opens up new possibilities for research, education, and clinical practice. As you read further, keep in mind how interconnected these concepts are and how this knowledge can be applied in multiple areas of life.

Neuroscience Foundations
At the heart of intelligence is the neuron, a specialized cell that transmits information throughout the nervous system. Neurons communicate using electrical impulses and chemical signals, which travel across small gaps called synapses. When you learn something new, neurons form new connections or strengthen existing ones, creating pathways that store information. These networks of neurons, known as neural circuits, are responsible for all our thoughts, memories, and actions. Neuroscientists use tools like functional MRI (fMRI) to see which parts of the brain are active during certain tasks. Electroencephalography (EEG) records electrical activity in the brain and helps track how information flows in real time. By using these methods, researchers can observe how different regions of the brain work together during problem solving. For example, the prefrontal cortex often works with the parietal lobes to manage complex reasoning tasks. The temporal lobes play a key role in understanding language and storing memories. The hippocampus is essential for forming new memories and linking them to existing knowledge. When these areas communicate efficiently, cognitive performance improves. If there are disruptions in these networks, it can affect learning and memory. Research has shown that both genetic factors and environmental influences shape how these neural systems develop. For instance, children who grow up in stimulating environments often show greater synaptic density, which supports better learning. On the other hand, damage to certain brain regions can lead to difficulties in specific cognitive skills. These findings emphasize that intelligence is not just about having a certain brain size or shape but about how well different parts of the brain coordinate their activity. Neuroscience also shows that the brain is plastic, meaning it can change throughout life in response to experience. This adaptability explains why practice and training can improve performance in many areas. As we study these foundations, we see that intelligence emerges from complex interactions within the nervous system. This knowledge not only deepens our understanding of the brain but also guides interventions that can enhance learning and recovery after injury. The study of neurons and neural networks is therefore central to understanding intelligence. It provides a biological framework that complements psychological theories. By combining these perspectives, we can develop more effective educational tools and therapeutic approaches.

Neuroscience Research on Intelligence

Brain Size and Intelligence
For many years, scientists speculated about whether the overall size of the brain was directly related to intelligence. Early research often relied on crude measures, such as weighing brains after death, but these methods offered little insight into how brain structure related to function. Modern imaging techniques like MRI have allowed researchers to measure brain volume in living individuals with far greater accuracy. Studies have found a modest correlation between brain size and IQ, suggesting that larger brains may support more complex processing. However, researchers emphasize that size alone is not a reliable predictor of intelligence. What matters more is the organization and connectivity of neural circuits within the brain. A smaller brain with efficient connections and highly developed regions can perform just as well, or even better, than a larger brain with less efficient organization. Different regions contribute to different types of intelligence, so localized differences in volume or density can be more important than overall size. For instance, greater gray matter density in the prefrontal and parietal regions often correlates with better reasoning and problem-solving skills. These findings highlight that intelligence is multifaceted and cannot be reduced to a single physical measurement. Cultural and environmental factors also play a significant role in shaping cognitive abilities, independent of brain size. Researchers continue to investigate how genetics influence brain development and how experiences like education and training affect brain structure. Brain size might reflect certain developmental processes, but it does not determine destiny. Intelligence emerges from a dynamic interplay between biology, environment, and experience. This understanding counters earlier simplistic ideas about intelligence being innate and fixed. It also underscores the need to consider multiple factors when evaluating human cognitive potential. Modern neuroscience provides a more nuanced picture, showing that intelligence is shaped by both inherited traits and life experiences. This knowledge encourages educators and clinicians to look beyond superficial measures and focus on underlying processes. By integrating brain size data with functional imaging, researchers can better understand how structure supports performance. As research advances, scientists aim to identify patterns of connectivity that are more predictive of learning and reasoning than size alone. This ongoing work reflects the complexity of human intelligence and the power of neuroscience to illuminate it.

White Matter and Connectivity
White matter is composed of myelinated axons, the long fibers that carry signals between different regions of the brain. These axons are covered by a fatty substance called myelin, which speeds up the transmission of electrical impulses. When white matter pathways are well-developed and intact, information flows more quickly and efficiently. Studies using diffusion tensor imaging (DTI) have revealed that individuals with higher intelligence often have more organized white matter tracts. This organization allows for faster communication between regions involved in complex thinking. For example, efficient connectivity between the frontal and parietal lobes supports better problem-solving and reasoning skills. White matter integrity also contributes to working memory, which is critical for learning new information. Disruptions in white matter can slow processing speed and affect performance on cognitive tasks. Researchers have found that training and practice can strengthen white matter pathways, a phenomenon that demonstrates the brain’s adaptability. Learning to play a musical instrument or mastering a new language often increases white matter density in relevant areas. This suggests that intelligence is not only influenced by innate traits but also shaped by experience and effort. It also highlights the importance of lifelong learning in maintaining cognitive abilities. White matter research provides evidence that neural efficiency, rather than sheer processing power, underlies many aspects of intelligence. The speed at which information travels affects how quickly we can solve problems or adapt to new challenges. Furthermore, white matter development is influenced by factors such as nutrition, physical activity, and mental stimulation. Studies on aging show that maintaining white matter integrity can protect against cognitive decline. This research has practical applications in designing interventions to preserve brain health throughout life. It also informs educational strategies that emphasize active engagement and practice. By understanding white matter, we gain insight into the biological basis of learning and intelligence. This knowledge bridges the gap between neuroscience research and real-world applications, from classrooms to clinical settings.

Neuroplasticity
Neuroplasticity refers to the brain’s remarkable ability to reorganize itself by forming new neural connections throughout life. This concept has transformed our understanding of intelligence, showing that cognitive abilities are not fixed but can be improved through experience and learning. When we engage in challenging mental activities, our brains adapt by strengthening existing connections and creating new ones. For example, practicing mathematics or learning a new language can lead to measurable changes in brain structure. These changes are often seen in regions associated with memory, attention, and reasoning. Neuroplasticity also explains how people recover functions after brain injuries, as other regions take over tasks once managed by damaged areas. Research demonstrates that neuroplasticity is most active during childhood, but it continues throughout adulthood. This means that adults can still improve their cognitive abilities with the right training and experiences. Activities that promote neuroplasticity include reading, solving puzzles, playing musical instruments, and engaging in regular physical exercise. These activities increase blood flow to the brain, stimulate growth factors, and support the formation of new synapses. The adaptability of the brain provides hope for interventions in neurodegenerative diseases, as therapies can encourage the brain to compensate for lost functions. Neuroplasticity also underscores the importance of education and lifelong learning in maintaining intelligence. It challenges the outdated view that intelligence is determined solely by genetics. Instead, it suggests that effort, environment, and experience play crucial roles. This concept is empowering because it means we can actively influence our cognitive development. Teachers and clinicians use this knowledge to design programs that harness neuroplasticity for better outcomes. For example, cognitive rehabilitation therapy for stroke patients often relies on principles of neuroplasticity. In education, strategies like spaced repetition and active engagement take advantage of the brain’s ability to strengthen connections over time. Neuroscientists continue to study the molecular mechanisms behind neuroplasticity to develop new ways to enhance learning and recovery. This ongoing research reinforces the idea that intelligence is dynamic and adaptable. It shows that our brains are not static organs but living systems that grow and change throughout life.

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Intelligence Across the Lifespan

Development in Childhood and Adolescence
The human brain undergoes profound changes during childhood and adolescence, shaping the foundation for intelligence and learning. In early childhood, the brain produces an abundance of synapses, which are later pruned to increase efficiency. This synaptic pruning allows neural circuits to become more specialized and refined. Myelination, the process of coating axons with myelin, accelerates signal transmission, enhancing processing speed and cognitive performance. These biological processes align with improvements in attention, memory, and reasoning skills observed as children grow. Educational experiences play a critical role in guiding which connections are strengthened and which are pruned. Children exposed to stimulating environments often develop stronger neural networks, supporting better academic outcomes. Conversely, lack of stimulation or exposure to stress can negatively affect brain development. Adolescence brings further changes, particularly in the prefrontal cortex, which governs executive functions like planning and impulse control. During this period, teenagers may exhibit uneven cognitive development, excelling in some areas while struggling in others. Social interactions also influence brain development, as peer relationships contribute to emotional and cognitive growth. Hormonal changes during puberty interact with brain development, affecting motivation and decision making. The adolescent brain is highly plastic, making it both a period of opportunity and vulnerability. Educational interventions during this time can have lasting impacts on intelligence and learning strategies. Neuroscience research highlights the importance of sleep, nutrition, and physical activity in supporting brain development. Chronic sleep deprivation in teenagers, for example, can impair memory consolidation and attention. Programs that promote healthy lifestyles during adolescence can therefore enhance cognitive outcomes. Understanding these developmental processes helps educators design age-appropriate curricula. It also helps parents create supportive environments that foster learning and curiosity. Research continues to explore how individual differences, such as genetic factors, interact with these developmental milestones. By studying childhood and adolescent brain development, scientists can better understand how to maximize learning potential. This knowledge underscores the importance of early intervention for developmental disorders. Overall, the dynamic changes during these years lay the groundwork for lifelong intelligence. They demonstrate that intelligence is shaped by a complex interplay of biology, experience, and environment.

Aging and Intelligence
As individuals age, their brains continue to change in ways that affect intelligence and cognitive abilities. Some functions, such as processing speed and working memory, often show gradual decline beginning in midlife. However, other aspects of intelligence, such as vocabulary, accumulated knowledge, and emotional regulation, remain stable or even improve. Neuroscience research has revealed that aging brains maintain a surprising degree of plasticity, allowing older adults to learn new skills and adapt to new challenges. Structural changes, such as reduced volume in certain regions, are offset by functional reorganization in others. For example, older adults often recruit additional brain areas to compensate for declining regions when performing cognitive tasks. Lifestyle factors, including regular physical exercise and mental stimulation, have been shown to slow cognitive decline. Engaging in activities like reading, playing chess, or learning a new hobby can enhance neural connections and preserve cognitive abilities. Social engagement also plays a vital role, as maintaining strong relationships supports mental health and cognitive function. Studies suggest that a positive attitude toward aging can itself contribute to better cognitive outcomes. Nutrition and sleep continue to be important, as deficiencies can exacerbate cognitive decline. Research into neurodegenerative diseases like Alzheimer’s and Parkinson’s has provided insight into the mechanisms of cognitive aging. Early detection and interventions can slow progression and improve quality of life. Scientists are exploring how factors like inflammation and oxidative stress contribute to age-related changes in the brain. Cognitive training programs designed for older adults show promise in enhancing memory and attention. Brain imaging studies reveal that lifelong learning promotes greater connectivity and resilience. This reinforces the message that intelligence is not fixed at any stage of life. Educators and health professionals are developing strategies to support cognitive health in aging populations. Public health initiatives encourage older adults to stay mentally and physically active. Interdisciplinary research is shedding light on how genetics, lifestyle, and environment interact in the aging brain. Understanding these processes helps society prepare for an aging population with unique cognitive needs. It also offers hope that intelligence, in many forms, can flourish well into later life. The study of aging and intelligence ultimately reminds us that the human brain is adaptable throughout the lifespan.

Implications and Future Directions

Integrating Intelligence Research and Neuroscience
The growing integration between intelligence research and neuroscience offers exciting opportunities for education, clinical practice, and technology. By studying how the brain supports various cognitive functions, researchers can design more effective teaching methods tailored to individual strengths. For example, knowing how working memory functions in the brain allows educators to structure lessons that build on prior knowledge and reduce overload. This can lead to classrooms that feel more supportive and responsive to diverse learning needs. Neuroscience research has also shed light on learning disabilities, such as dyslexia and attention-deficit disorders, enabling earlier diagnosis and intervention. With this knowledge, schools can implement targeted programs that give students with these challenges the tools they need to succeed. Beyond education, clinical settings benefit as well. Neuropsychologists use findings about memory networks and brain plasticity to design rehabilitation programs for people recovering from brain injuries. Advances in imaging allow doctors to track recovery and adjust treatments accordingly. Technology plays a role, too, as brain-computer interfaces are developed to help people with severe motor impairments communicate and interact with their environments. These devices rely on understanding how brain signals can be translated into actions. Cognitive training programs, often delivered through apps or games, use principles of neuroplasticity to strengthen specific mental skills. However, applying neuroscience findings comes with ethical considerations. For instance, while brain scans can reveal differences in connectivity, these should never be used to unfairly label or limit someone’s potential. Instead, this information should be used to empower individuals with strategies to enhance learning and development. There is also the question of data privacy when dealing with sensitive neurological information. Researchers must work carefully to ensure that technological tools do not reinforce social inequalities or stereotypes. Another implication is the growing need for interdisciplinary collaboration. Psychologists, educators, neuroscientists, and engineers must work together to translate findings into real-world applications. This collaboration ensures that interventions are both scientifically sound and culturally sensitive. Understanding the neural basis of intelligence also opens up questions about how to foster creativity, emotional intelligence, and practical skills. Each of these areas may have distinct neural underpinnings that can be studied and supported. Overall, the future of intelligence research looks bright, but it requires a careful balance between innovation and ethics. As we learn more, the goal is to use this knowledge to improve lives, not limit them. This integration represents a new frontier in understanding the mind and optimizing human potential.

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The History of Intelligence Testing

Early Foundations of Intelligence Testing
The story of intelligence testing begins with early efforts to measure human differences, long before modern psychology existed. Ancient philosophers like Plato and Aristotle speculated about why some people seemed wiser or more capable than others, but they lacked systematic methods. It was not until the 19th century that these questions began to be approached scientifically. Sir Francis Galton, an English polymath and cousin of Charles Darwin, pioneered studies on individual differences. In his book Hereditary Genius (1869), Galton argued that intelligence was inherited and attempted to measure mental acuity through sensory and reaction-time tasks. Although his tests were often unreliable, they introduced the idea that intelligence could be quantified. Galton’s work laid the foundation for the field of differential psychology, which seeks to understand how and why individuals differ. Building on this, James McKeen Cattell, an American psychologist, coined the term “mental tests” in 1890. He developed assessments that measured reaction times, memory spans, and other basic processes, hoping they would predict academic success. While these early tests did not directly measure intelligence as we understand it today, they represented a shift toward objective evaluation. This period also reflected a growing interest in applying scientific methods to education and policy. However, these tests were limited by the tools and theories available at the time. Many researchers focused on sensory abilities without linking them to higher-order thinking. Despite these limitations, the idea that intelligence could be studied systematically inspired others to refine and expand testing methods. The late 19th century thus set the stage for more practical and valid assessments in the early 20th century. These foundations are important because they show how scientific curiosity, even when imperfect, can lead to significant advancements. They also reveal how concepts of intelligence were shaped by cultural and historical contexts. Understanding this history reminds us that testing tools are not neutral; they reflect the values and knowledge of their time. It is crucial to view early tests as stepping stones rather than final answers. They demonstrate the evolution of thought in psychology and highlight the need for continual revision and improvement. From these beginnings, the field of intelligence testing would grow into a major influence on education and public policy worldwide.

The Birth of the Modern Intelligence Test
A major breakthrough came in 1905 when French psychologist Alfred Binet, working with Theodore Simon, developed the first practical intelligence test. Commissioned by the French Ministry of Education, their goal was to identify children who needed extra help in school. The Binet-Simon Scale included tasks measuring reasoning, comprehension, and problem-solving, which were more directly linked to academic success than previous sensory tests. This test introduced the concept of “mental age,” comparing a child’s performance to typical age norms. For example, a child who could solve problems typical of older children would be considered advanced. This innovation allowed teachers and psychologists to tailor instruction more effectively. Binet and Simon emphasized that their test was not a fixed measure of ability but a tool to guide education. Their work inspired further developments worldwide. In the United States, Lewis Terman of Stanford University revised and standardized the Binet-Simon Scale, creating the Stanford-Binet Intelligence Scale in 1916. Terman introduced the Intelligence Quotient (IQ), calculated by dividing mental age by chronological age and multiplying by 100. This provided a single number that could be compared across individuals. The Stanford-Binet quickly became widely used in schools, military settings, and clinical contexts. It shaped educational policies and influenced how intelligence was understood for decades. However, even as the test gained popularity, debates continued about what exactly it measured. Critics argued that cultural and language biases could affect scores. Despite these concerns, the Stanford-Binet laid the groundwork for modern intelligence assessments. It demonstrated that intelligence could be measured in a way that informed practical decisions. This period marked a shift from experimental curiosity to widespread application. The success of these tests spurred further research into refining items and reducing bias. It also sparked interest in exploring multiple types of intelligence beyond a single score. The legacy of Binet, Simon, and Terman continues in contemporary testing practices. Their work reminds us that intelligence testing is both a scientific endeavor and a social tool. Its history is a story of innovation, application, and ongoing revision. Understanding this background helps us appreciate the strengths and limitations of current assessments.

Intelligence Testing in the Early 20th Century and Beyond
The early 20th century saw intelligence testing expand rapidly, particularly during World War I. The U.S. Army needed a way to classify large numbers of recruits, leading to the development of the Army Alpha and Beta tests. The Alpha was a verbal test, while the Beta was nonverbal, designed for recruits with limited English proficiency or literacy. These tests were administered to over 1.75 million soldiers, demonstrating the feasibility of large-scale assessment. Results helped place soldiers in roles suited to their abilities, showing practical benefits. However, these tests also fueled public fascination with measuring intelligence. Policymakers began considering how such tools could guide immigration policies, education, and employment. Unfortunately, some misused test results to support eugenic ideas, arguing for restrictive immigration laws and segregation. This misuse serves as an important reminder of the ethical responsibilities involved in testing. Despite these controversies, intelligence testing continued to evolve. In 1939, David Wechsler developed the Wechsler-Bellevue Intelligence Scale, later known as the Wechsler Adult Intelligence Scale (WAIS). Unlike the Stanford-Binet, the WAIS provided separate scores for verbal and performance abilities, offering a more nuanced profile. Wechsler also created versions for children (WISC) and preschoolers (WPPSI), making intelligence testing applicable across the lifespan. During the mid-20th century, factor-analytic approaches advanced theoretical understanding. Charles Spearman’s “g factor” suggested a general intelligence underlying all cognitive tasks, while Louis Thurstone proposed multiple primary mental abilities. These debates enriched the field and informed test design. Today, intelligence tests are used in clinical psychology to diagnose learning disabilities and guide interventions. They are also used in research to study cognition and development. Modern tests strive to be culturally fair and minimize biases that plagued earlier versions. Critics remind us that intelligence is multifaceted, encompassing creativity, emotional understanding, and practical problem-solving. This ongoing dialogue has inspired alternative assessments that go beyond traditional IQ measures. The history of intelligence testing, therefore, is not just about the tests themselves but about how society uses them. It shows the potential for these tools to help or harm, depending on the context and intent. By studying this history, we learn to apply tests responsibly, with cultural sensitivity and awareness of their limitations. Understanding this evolution helps future educators and psychologists make informed choices. It encourages continued innovation in creating assessments that reflect the diversity and complexity of human intelligence.

Primary Open-Source References
(All resources are available in the public domain or through open educational repositories.)

• Bear, M. F., Connors, B. W., & Paradiso, M. A. (2020). Neuroscience: Exploring the Brain (4th ed.). Wolters Kluwer.
  Portions and summaries available through many educational repositories and course websites.

• Binet, A., & Simon, T. (1905). Méthodes nouvelles pour le diagnostic du niveau intellectuel des anormaux. L’Année Psychologique, 11, 191–244.
  Public domain. Access via Internet Archive or Project Gutenberg.

• Cattell, J. M. (1890). Mental Tests and Measurements. Mind, 15(59), 373–381.
  Public domain. Available at Internet Archive.

• Dehaene, S. (2020). How We Learn: Why Brains Learn Better Than Any Machine…for Now. Penguin.
  Summaries and related materials available through academic OER portals.

• Galton, F. (1869). Hereditary Genius. London: Macmillan.
  Public domain. Access via Project Gutenberg.

• Gardner, H. (1983). Frames of Mind: The Theory of Multiple Intelligences. New York: Basic Books.
  OER summaries and study guides available through OER Commons.

• Gould, S. J. (1981). The Mismeasure of Man. New York: W. W. Norton.
  Selected summaries and open-access discussions available via educational resources and Internet Archive.

• Jung, R. E., & Haier, R. J. (2007). The Parieto-Frontal Integration Theory (P-FIT) of Intelligence: Converging Neuroimaging Evidence. Behavioral and Brain Sciences, 30(2), 135–154.
  Portions accessible through institutional repositories and open academic archives.

• Kolb, B., & Whishaw, I. Q. (2015). An Introduction to Brain and Behavior. Worth Publishers.
  Open educational slides and summaries available via OER resources.

• Park, D. C., & Reuter-Lorenz, P. (2009). The Adaptive Brain: Aging and Neurocognitive Scaffolding. Annual Review of Psychology, 60, 173–196.
  Open-access summaries available through educational sites and NIH resources.

• Spearman, C. (1904). “General Intelligence,” Objectively Determined and Measured. The American Journal of Psychology, 15(2), 201–292.
  Public domain. Access via Project Gutenberg or Internet Archive.

• Sternberg, R. J. (1985). Beyond IQ: A Triarchic Theory of Human Intelligence. Cambridge University Press.
  Open educational summaries available via OER Commons.

• Terman, L. M. (1916). The Measurement of Intelligence. Boston: Houghton Mifflin.
  Public domain. Full text available at Internet Archive.

• Wechsler, D. (1944). The Measurement of Adult Intelligence (3rd ed.). Baltimore: Williams & Wilkins.
  Public domain editions available at Internet Archive.

• Yerkes, R. M. (1921). Psychological Examining in the United States Army. Memoirs of the National Academy of Sciences, 15, 1–889.
  Public domain. Available through Internet Archive.

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General Open Educational Resources

• OpenStax Psychology
  https://openstax.org/books/psychology/pages/1-introduction

• OER Commons
  https://www.oercommons.org

• NIH Neuroscience Resources
  https://www.ninds.nih.gov

• Project Gutenberg
  https://www.gutenberg.org

• Internet Archive
  https://archive.org