Multiple intelligences
27/06/25 02:28
The work of Howard Gardner has influenced my thinking and teaching. Gardner is best known for the theory of multiple intelligences. Before the development of the theory, educators often thought of intelligence as a single general ability. Standardized tests were designed to measure a person’s intelligence and assign a numerical score called the Intelligence Quotient (IQ). The tests were designed to evaluate problem-solving, logical reasoning, memory, and speed of processing information. One of the problems with the tests is that they are based on verbal and linguistic skills. People who excel at reading and writing and learn through reading and writing tend to score higher on standardized intelligence tests.
Gardner proposed that verbal-linguistic intelligence is just one of eight primary intelligences. In addition to the ability to use words effectively and understand language structure, Gardner posited seven additional intelligences: logical-mathematical, spatial, musical, body-kinesthetic, interpersonal, and intrapersonal. When I first studied Gardner’s work, it made sense. I have a brother who was diagnosed as dyslexic. He struggled to learn to read and had to work very hard to earn grades in a traditional educational system. However, he was brilliant at hunting, fishing, and finding his way. His spatial intelligence far exceeded my own. Our daughter struggled with math in her early school years, but could dance to complex rhythms from an early age.
Studying Gardner’s theory taught me to write teaching plans and lessons that appealed to different intelligences. Applying the theory to curriculum design enabled us to produce resources for faith formation that engaged a wide range of learners. Even though I am retired, I occasionally write curriculum pieces for various projects and keep Gardner’s theories in mind when preparing lessons for others.
With the recent attention given to large language models, sometimes called artificial intelligence (AI), I have been thinking about multiple intelligence theory. With AI built into some of the software I use, I want to understand how it works. So far, I have not used AI tools to generate text. I’m writing this journal entry word by word based on my thinking. However, I use a grammar checker that presents me with choices about particular language patterns. I’ve found the program helpful when I write essays, but I do not use it when writing poems and prayers, as I think it is weighted to the patterns of the written word, but it is less helpful when creating oral language.
AI programs are based mainly on linguistic intelligence. Although they use logical-mathematical intelligence to analyze relationships, they function well as calculators but are less helpful in creating formulas for real-world problem solving. Some content creators are experimenting with AI tools for musical composition, but their results have not rivaled human music writing at this point. AI is less helpful for counselors who are focusing on human relationships and effective interactions between people. Human emotions are complex for AI tools at this point.
I have been interested in reading about developers of AI tools developing algorithms based on bee behavior. As a tender of bees, I read articles about bees. AI developers are interested in bee brains partly because they are tiny compared to human brains. A bee brain has a million neurons, compared to a human brain with more than 86 million. However, bees are brilliant and capable, given the size of their brains. They can maintain accurate spatial awareness within seven miles of the hive, traveling back and forth to a single blossom with complete accuracy. They can learn as many as 300 jobs in a lifetime, from nursing brood to dealing with dead bees' bodies, creating cells, foraging, capping cells, caring for the queen, and guarding the hive. They can switch jobs quickly depending on the needs of the colony.
However, there is increasing evidence that bees’ memories don’t work like human memories. DNA evidence shows that bees can change their DNA depending on their jobs. Bees are genetically different when serving as foragers than when capping honey cells in the hive. Evidence shows that they process some information, such as the odors of specific pheromones, without processing the information through their brains. While researchers can develop algorithms for specific bee behaviors and then reverse-engineer silicon computer chips to control robots, they have yet to build the capacity to make robots that can quickly change functions and jobs. Robots also lack bees’ abilities to pass on information. While AI can enable a driverless car to “learn” a route and get from one place to another with accuracy, so far, that same computer cannot deliver a baby if a passenger goes into labor while riding. Bees, however, can switch from navigating to tending and hatching bees as the colony requires.
Bees are not the only creatures whose brains function significantly differently from human brains. Octopuses are considered to be very intelligent animals. They can solve puzzles, open jars, and use tools. Like bees, they can alter their genetics. Octopi can change their genetic material by editing RNA to produce proteins best suited to temperature variations. And, like bees, their brains are not contained only in their heads. Octopus nervous systems extend into the arms, containing thousands of touch and taste sensors through their suction cups. Their brains can process information from these neurons without going through a central brain in their heads. This allows each arm to function independently. It also produces a different understanding of the world than humans perceive.
Despite the capacity of computers to process large amounts of information and their capacity to process language with increasing accuracy, actual intelligence is more complex than an algorithm. Furthermore, human intelligence is not the only intelligence operating in our universe. While AI can expand human productivity in some arenas, I don’t expect it to replace human thinking. Regular readers of my journal know how quirky my brain is when it comes to selecting a subject for an entry. I don’t expect my computer to be able to learn to make journal entries without me.
Gardner proposed that verbal-linguistic intelligence is just one of eight primary intelligences. In addition to the ability to use words effectively and understand language structure, Gardner posited seven additional intelligences: logical-mathematical, spatial, musical, body-kinesthetic, interpersonal, and intrapersonal. When I first studied Gardner’s work, it made sense. I have a brother who was diagnosed as dyslexic. He struggled to learn to read and had to work very hard to earn grades in a traditional educational system. However, he was brilliant at hunting, fishing, and finding his way. His spatial intelligence far exceeded my own. Our daughter struggled with math in her early school years, but could dance to complex rhythms from an early age.
Studying Gardner’s theory taught me to write teaching plans and lessons that appealed to different intelligences. Applying the theory to curriculum design enabled us to produce resources for faith formation that engaged a wide range of learners. Even though I am retired, I occasionally write curriculum pieces for various projects and keep Gardner’s theories in mind when preparing lessons for others.
With the recent attention given to large language models, sometimes called artificial intelligence (AI), I have been thinking about multiple intelligence theory. With AI built into some of the software I use, I want to understand how it works. So far, I have not used AI tools to generate text. I’m writing this journal entry word by word based on my thinking. However, I use a grammar checker that presents me with choices about particular language patterns. I’ve found the program helpful when I write essays, but I do not use it when writing poems and prayers, as I think it is weighted to the patterns of the written word, but it is less helpful when creating oral language.
AI programs are based mainly on linguistic intelligence. Although they use logical-mathematical intelligence to analyze relationships, they function well as calculators but are less helpful in creating formulas for real-world problem solving. Some content creators are experimenting with AI tools for musical composition, but their results have not rivaled human music writing at this point. AI is less helpful for counselors who are focusing on human relationships and effective interactions between people. Human emotions are complex for AI tools at this point.
I have been interested in reading about developers of AI tools developing algorithms based on bee behavior. As a tender of bees, I read articles about bees. AI developers are interested in bee brains partly because they are tiny compared to human brains. A bee brain has a million neurons, compared to a human brain with more than 86 million. However, bees are brilliant and capable, given the size of their brains. They can maintain accurate spatial awareness within seven miles of the hive, traveling back and forth to a single blossom with complete accuracy. They can learn as many as 300 jobs in a lifetime, from nursing brood to dealing with dead bees' bodies, creating cells, foraging, capping cells, caring for the queen, and guarding the hive. They can switch jobs quickly depending on the needs of the colony.
However, there is increasing evidence that bees’ memories don’t work like human memories. DNA evidence shows that bees can change their DNA depending on their jobs. Bees are genetically different when serving as foragers than when capping honey cells in the hive. Evidence shows that they process some information, such as the odors of specific pheromones, without processing the information through their brains. While researchers can develop algorithms for specific bee behaviors and then reverse-engineer silicon computer chips to control robots, they have yet to build the capacity to make robots that can quickly change functions and jobs. Robots also lack bees’ abilities to pass on information. While AI can enable a driverless car to “learn” a route and get from one place to another with accuracy, so far, that same computer cannot deliver a baby if a passenger goes into labor while riding. Bees, however, can switch from navigating to tending and hatching bees as the colony requires.
Bees are not the only creatures whose brains function significantly differently from human brains. Octopuses are considered to be very intelligent animals. They can solve puzzles, open jars, and use tools. Like bees, they can alter their genetics. Octopi can change their genetic material by editing RNA to produce proteins best suited to temperature variations. And, like bees, their brains are not contained only in their heads. Octopus nervous systems extend into the arms, containing thousands of touch and taste sensors through their suction cups. Their brains can process information from these neurons without going through a central brain in their heads. This allows each arm to function independently. It also produces a different understanding of the world than humans perceive.
Despite the capacity of computers to process large amounts of information and their capacity to process language with increasing accuracy, actual intelligence is more complex than an algorithm. Furthermore, human intelligence is not the only intelligence operating in our universe. While AI can expand human productivity in some arenas, I don’t expect it to replace human thinking. Regular readers of my journal know how quirky my brain is when it comes to selecting a subject for an entry. I don’t expect my computer to be able to learn to make journal entries without me.
