Put It In the Vault: Permastore

If you took a foreign language in high school or college, do you remember the translation of the following words? 

• Three
• Mother
• Water
• Street
• House

How many of these words did you remember? Also, how long ago was it that you studied a foreign language? Was it between 0 - 6 years ago, 6 - 25 years ago, or more than 25 years ago? The reason I ask is because it's possible that forgetting occurs at different rates, depending on how long ago the initial learning occurred.

Fifty years of data collection

It's every educator's dream that her students will retain the information from her class for the rest of their lives. The reality is that some amount of forgetting will occur after the class ends. But how much information is retained over an entire lifetime? Has anyone ever attempted to collect data that would reveal how much people forget over the course of their lives?

At least one brave soul has tried. A cognitive scientist, who we shall refer to as Harry, decided to measure the amount of knowledge retained over a lifespan for students who took Spanish in high school and/or college [1]. Before tackling the Herculean task of collecting his data, Harry had to make a methodological decision. One method to track memory over a lifetime would be to measure the knowledge of a large sample of high school or college students, and then test their knowledge every year for fifty years. This is called a longitudinal study. The advantage of a longitudinal design is that Harry would have fairly good control over extraneous factors that are not relevant to his experiment. The obvious disadvantage is that it would take precisely 50 years to collect all of his data. To overcome this disadvantage, Harry decided to conduct a cross-sectional study instead. That is, rather than following the same individuals over time, he recruited a large number of people who studied Spanish between 1 and 50 years ago, and compared current memory of the language for people who learned it at different time points.

What were the results from Harry's study? Do students forget everything after leaving class? If not, how much do they retain 50 years later? Before we dig into the results, let's set the stage by looking at the historical context in which Harry conducted his study.

Whee! Sliding down the forgetting curve

One of the earliest controlled experiments on human memory was conducted by a German psychologist named Hermann Ebbinghaus [2]. To accurately measure the effects of learning and forgetting, he dedicated himself to studying lists of "words" (although they weren't really words). He constructed trigrams, which were composed of a consonant, followed by a vowel, and concluded with a consonant. LEK is an example of a trigram. 

The reason Hermann made lists of trigrams instead of real words is that he was attempting to control for the pre-existing associations that words have in long-term memory. Also, testing memory of made-up words would prevent Harry from using any of the memorization tricks we have talked about in previous posts. Thus, he was attempting to measure rates of learning and forgetting in a "pure" environment. To accurately measure the time course of forgetting, Hermann attempted to recall his lists of words across several time spans. The shortest time span was 20 minutes, and the longest span was one month (i.e., 744 hours).

How did he do? Ebbinghaus's results are plotted in Fig. 1 [3]. You will notice that even after 20 minutes, there was a little bit of forgetting. But after a month, he remembered only about a fifth (21.1%) of the original list of trigrams.

Figure 1: The amount of forgetting over several intervals of time.

How does this stack up to the forgetting curves from the Spanish study? If you squint, they look surprisingly similar! In Fig. 2, you can see that there was an extremely steep drop-off in terms of the correctly recalled vocabulary words between the ending of the class and six years afterwards. But after six years, Harry's participants remembered around 70% of the items that he tested. These items lasted for a very long time. If these vocabulary items made it past six years, then they were highly likely to be recalled 25 years later. The discontinuous nature of forgetting in this graph suggests that there might be a very long-term memory, which Harry called permastore. If memories make it to permastore, they will likely remain with us until the end of our lives.

Figure 2: Amount of forgetting of vocabulary terms over 50 years.

The STEM Connection

Plants grow at the apical meristem and Trypanosoma causes African sleeping sickness are two declarative chunks of information that I learned in 10th grade Biology. That was over 20 years ago. At my current rate of forgetting, I will probably take these facts to my grave. (My Biology teacher would be so proud!) Unfortunately, there are hundreds of other facts from that same class that I will never be able to recall. (My Biology teacher would probably be less than thrilled to hear that.) So should we think of this as good news or bad news? 

I think the concept of permastore should be perceived as good news, and here is why: we are partially in control of how much information makes it into permastore. The line in Fig. 2 glosses over an important variable in the original Spanish study. Harry categorized the individuals in his study into groups who learned the material really, really well and into groups of student who did not learn the material as well. The line shows the forgetting rate averaged over multiple levels of initial learning. It turns out that the lines were different based on how well people learned the material originally. Specifically, those who mastered their Spanish vocabulary demonstrated less forgetting than the students who did not learn their vocabulary words to the same depth (i.e., the lines for each group were completely parallel). Thus, if we study hard, and learn the material really well, then it is likely that more items will enter permastore. That, I think, is very good news indeed.


Share and Enjoy!

Dr. Bob

For More Information

[1] Bahrick, H. P. (1984). Semantic memory content in permastore: fifty years of memory for Spanish learned in school. Journal of Experimental Psychology: General, 113(1), 1.

[2] Ebbinghaus, Hermann (1964/1885) Memory: A contribution to experimental psychology. Oxford, England: Dover.

[3] I'm doing some handwaving here. Ebbinghaus's methodology was to memorize a list so that he could reproduce it perfectly. Then he would wait some interval of time. Then he would try to remember it. If he failed, he would study the list again until he could reproduce it without any errors. The amount that he didn't have to study, he called "Savings." For example, when the time interval was short, he didn't have to study as much to get back to 100%. For seriously long intervals (i.e., a month), he had to study a lot to get back to 100%. For the sake of the current discussion, though, we can just talk about this in terms of how much he forgot. 

Smile For the Camera!: Flashbulb Memories

Take a moment to answer the following questions:

• Where were you exactly 1 month ago at 10am? 
• Who were you with? 
• What you were doing?
• What was the weather like that day?

Now take a moment to answer these questions:

• Where were you on September 11th, 2001? 
• Who were you with? 
• What were you doing at the time you found out that the first airplane had crashed into the World Trade Center?
• What was the weather like that day?

If you are old enough, then maybe you can answer these questions as well:

• Where were you, who were you with, and what were you doing when you learned that the space shuttle Challenger exploded? 
• Where were you, who were you with, and what were you doing when you found out that President Kennedy had been assassinated?

The "Now Print!" Mechanism

It is probably too obvious to say, but I will say it anyway: some memories are more vivid than others. We might have a vague sense about what we did on this day exactly one month ago, but it's unlikely that we will be able to recall, in detail, who we were with, what we were doing, where we were, and how we felt. It's even more unlikely that we will be able to recall seemingly trivial details (e.g., What was the weather like?). However, for certain events, even those that happened several years ago, our memories are much more vivid. A flashbulb memory is a memory of a highly significant event that seems to capture many details that are usually not present in other, regular memories. As the name implies, one's memory creates a snapshot in time that captures even the smallest of details. When one thinks back to that moment, it is almost like they are reliving the event.

What, then, is the hallmark of an event that will give rise to a flashbulb memory? Obviously, each person is different, but the unifying theme seems to be that events likely to result in flashbulb memories must be extremely unexpected and highly emotional. Given these two components, the event doesn't have to be one that gains national media attention. Instead, highly personal events can also result in flashbulb memories. 

Are flashbulb memories accurate?

If you have ever experienced a highly charged, extremely unexpected life event, then you can probably attest to the reality of a flashbulb memory. It feels different when you recall it than when you recall other, more mundane memories. The experience (or phenomenology) is different for flashbulb memories in that they feel extremely accurate and detailed. However, in a recent post about memory being an active, reconstructive process, which suggested that our memory can be shaped by our current situation. Therefore, we might be inclined to ask: Are flashbulb memories accurate? The phenomenological component makes it tempting to believe that flashbulb memories are both real and accurate. But can we really trust them as true any more than other memories? 

To determine the veracity of flashbulb memories, scientists have to be ready to spring at a moment's notice. After all, highly unexpected and emotional events are the precursor for flashbulb memories. When an event reaches a threshold for "extremely unexpected," scientists sometimes round up a bunch of participants and ask them to report how they found out, who they were with, how they felt, and any other detail they think is important. Then the scientists wait for a significant amount of time to pass before they ask the individuals to report on the exact same set of questions. 

If flashbulb memories are indeed highly detailed and accurate, then the answers to the questions should be the same, regardless of the delay. If flashbulb memories use the exact same memory mechanisms, and are subject to the same limitations and errors, then we would expect to see some deviation between the initial recall and the later retelling of the event. What do you predict scientists would find?

In an influential study on flashbulb memories, scientists asked people to recall details about when they found out about the Challenger explosion [2]. They administered a questionnaire within three days of it happening and again nine months later. Between the two interviews, they found that some forgetting did occur during the nine-month interval. On the second questionnaire, 15.4% said that they didn't remember the answer to one of the questions. More interestingly, the scientists also coded if the answers didn't match. For those responses, 8.5% of the responses were inconsistent between the two recall events. Even though flashbulb memories feel like they are vivid, and we have a very high confidence in their validity [3], it is possible that a small percentage of our memories are inaccurate. 

The STEM Connection

What is the connection between flashbulb memories and STEM education? The connection is tenuous because, by definition, flashbulb memories are rare. One possible connection that I see is one of empathy. In other words, there is a remote (albeit real) possibility that an "extremely unexpected" event could happen in your classroom. If something happens, make sure you give yourself and your students the time and space that all of you need to process the event. Flashbulbs are probably going to be going off all over the place. 

The other connection that I can envision is this idea of one-trial learning. In most cases, the memory system requires repeated exposure to the same information before the information makes it to long-term memory. Repetition forms the basis for learning. Flashbulb memories indicate that there may be a mechanism that can instantly encode massive amounts of information. Maybe someday we will learn how to exploit that mechanism for other, less traumatic learning opportunities.

Flashbulb memories are extremely interesting for a variety of reasons. They seem so real, but evidence suggests that they might be prone to errors (just like any other memory). They also hint at a couple of interesting memory mechanisms, including single-trial learning (or the "Now Print!" mechanism) and a class of memories that are permanently stored in long-term memory.


Share and Enjoy!

Dr. Bob

For More Information

[1] Brown, R., & Kulik, J. (1977). Flashbulb memories. Cognition, 5(1), 73-99.

[2] McCloskey, M., Wible, C. G., & Cohen, N. J. (1988). Is there a special flashbulb-memory mechanism?. Journal of Experimental Psychology: General, 117(2), 171. Here is the questionnaire that they asked volunteers to answer:

1. Where were you when you first learned of the explosion?
2. What were you doing when you first learned of the explosion?
3. Did you see the event at the time it was actually happening, or did you learn about it later? If later, how did you learn about it?
4. What were your first thoughts upon hearing the news?

[3] Despite his high level of confidence, it seems that even former President Bush is not immune to inaccurate flashbulb memories: Greenberg, D. L. (2004). President Bush's false [flashbulb] memory of 9/11/01. Applied Cognitive Psychology, 18(3), 363-370.

Crash Into Me(mory): Memory Is an Active, Reconstructive Process

Pull out a piece of paper and jot down how much money you made this year. Now, write how much money you made two years ago. All set? Now here's the fun part. Go find your W-2 tax forms. How accurate were you? I'm going to guess that you were fairly accurate in estimating both numbers. However, if you were off, even by a little bit, then it was probably in a reliable direction. If you made more money this year than you did two years ago, then I bet your estimate of your income two years ago was a little bit on the high side. If you make less than you did two years ago, then I'm willing to bet that your estimate was a little low. 

Not having access to your IRS files, why would I bet that you were off? And how could I know what direction your error was in? As it turns out, memory errors are somewhat predictable [1]. You might be thinking to yourself: Is memory fallible? (Short Answer: Yes, it is.) Are errors in memory reliable and/or predictable? (Short Answer: Yes, they are.) Our goal in this post is to figure out how and why.

Do people change?

Most people have a theory about how individuals change as they mature and grow older. A person's theory of change can be one of stability. For example, some might assume that their political beliefs are relatively stable over time and do not change from one election year to the next. Theory of change can also be dynamic in the sense that people believe they are essentially different people from when they were young. As a kid, for instance, you might have believed that the sun revolved around the earth, but then you learned in science class that the earth actually revolves around the sun.

What does one's theory of change have to do with memory? Above I made the claim that memory is predictably fallible [2]. In fact, memory is an active, reconstructive process where the individual uses her current situation to help unpack and understand past events (i.e., episodic memories). The implication is that memory is not a stable entity like a video recording. Instead, it is full of inferences based on two things: what's going on in the present moment and one's theory of change. 

Remembering how much money you made two years ago is a perfect example. When trying to recall the exact figure, you first anchored your estimate on your current situation (e.g., How much do I currently make?). Then you invoked your theory of how your income changed (e.g., Did I get a raise or take a pay-cut?). Based on these two data points, you can then "recall" (or reconstruct) how much money you made. In other words, the memory of the exact figure is highly influenced by your current situation and your theory of change with regard to your income.

"I'd like to voir dire this witness..." -V. Gambini

One of the best demonstrations of the inferential nature of memory can be found in the literature on eyewitness testimony. When a crime is committed, and there is no photographic evidence, we must rely on eyewitnesses to testify as to what they saw. Unfortunately, memory does not act like a video recording where the memory replays exactly the same every time. Instead, how we remember something can change based on our current situation.

Given the flexibility of the English language, lawyers can influence how an eyewitness remembers something by framing their questions in different ways:

   Framing 1: "About how fast were the cars going when they hit each other?"

   Framing 2: "About how fast were the cars going when they smashed into each other?"

If memory acted like a video recording, then it shouldn't matter how the lawyer asks her question. The eyewitness should provide similar estimates of the car's speed. However, if memory is an active, reconstructive process, then the estimates should change depending on the way the question is framed. 

To find out if the question framing had an effect on memory, a pair of scientists invited a group of participants to watch a video of a car crash [3]. After a delay, participants were then asked to estimate the speed of the car. Based on the two framings above, what do you suppose they found? Participants who heard the question framed using the word "hit" estimated that the car was traveling 34.0 mph. However, participants who heard the question framed in terms of "smashed into" estimated that the car was traveling 40.5 mph. Even though both groups of participants saw the exact same video, their memory of the event was highly influenced by the wording of the question.

The STEM Connection

Why is this important for education? First of all, I believe that it is important for students to have an accurate understanding about the way their memory works. If they believe the misconception that memory is like a video recording, then that belief will guide their behavior. For instance, they will be more likely to believe their own memories of past events and may also trust the memories other people share with them to be hard facts. But if they understood how memory can be biased by the current situation and an individual's theory of change, then they might be more skeptical of the recalled information. They might also study differently if they understand that memories are error prone. 

Second, it seems reasonable to assume that students might develop better metacognitive skills if they have an accurate understanding about the way memory works. In other words, if they understand that memory is fallible, then they might try various technique to reduce the possibility of introducing errors into their episodic memories. They might not rely on memory at all! Instead, they may elect to store episodic memories externally (e.g., in pictures or in a journal). 

To summarize, remember that memory is fallible, and that it is not like a video or audio recording. The present is typically used as an anchor and inferences about the past need to be made. Also, the next time you're called for jury duty, pay attention to the way lawyers ask their questions. It could make serving jury duty a smashing good time.


Share and Enjoy!

Dr. Bob

For More Information

[1] Ross, M. (1989). Relation of implicit theories to the construction of personal histories. Psychological Review, 96(2), 341.

[2] Methodologically speaking, the claim that memory is predictably fallible is difficult to verify scientifically. To test this claim, you would need to follow someone around and record their beliefs, and then wait for an extended period of time and ask them to recall what you had recorded. Then you would have an accurate measure of the truth and any deviations in memory when recalling the event. That typically isn't practical, so researchers need to be creative in collecting autobiographical data and testing the accuracy of those individual's memories. One way to get around this methodological hurdle is to ask people to keep a journal. Assuming the person faithfully keeps track of the events in his or her life, then memories can be compared against the journal entries.

[3] Here is a replication of the video used in the experiment, and here is the paper where they report the results: Loftus, E. F., & Palmer, J. C. (1974). Reconstruction of automobile destruction: An example of the interaction between language and memory. Journal of verbal learning and verbal behavior, 13(5), 585-589.

You Got Some Explaining To Do!: Self-explaining

Here's a fun question for you: How detailed is your mental model of a toilet? If I had to guess, I would say you generally know how a toilet works, but haven't written a thesis on the topic. To test yourself, read the following passage and try to assemble a mental model of the modern flushable toilet.

The toilet has several working components. The tank (or cistern) holds clean water, and it is located above the toilet bowl, which holds the flushable content. Connected to the tank is a handle that, when pressed, releases the water from the tank. Gravity drains the water into the bowl through a small cistern tube. The water then exits the bowl at the bottom through the S-trap. 

Inside the tank are several additional components that control the flow of water into and out of the tank. At the bottom of the tank is a flapper valve, which is connected to the handle by a chain. When the handle is pressed, the chain raises the flapper valve to let the water out. As the water level decreases, the float ball, which is connected to the float rod, drops and opens the inlet valve. When the inlet valve opens, clean water rushes in to fill the tank. When the water reaches the top of the tank, the float ball closes the inlet valve. 

There's a lot of information crammed into those paragraphs [1]; however, it is also the case that a lot of information is missing. For example, how does the float ball and rod open and close the inlet valve? To make sense of the description as currently written, you still have to do some work. First, you have to spatially assemble all of the components in your mind's eye as you learn about them. Second, you need to supply any information that may be missing. Finally, you might have to resolve contradictions that arise between the information you are learning and the mental model you are building as you engage in the first two activities [2].

What do good students do when learning something new? 

When students read a text about an unfamiliar topic, their first priority is to make sense of each and every word. Once they decode the words, their next task is to assemble them into larger chunks of meaningful information. For example, you probably know what the words handle, chain, and tube mean. But you need to connect all three concepts together to form a working model of the flush mechanism in a toilet. The mental process of hooking these concepts together is what we will call self-explaining, or the generation of inferences that are required to construct an accurate mental model.


Evidence for self-explaining was first observed by asking students to read a passage about a branch of physics called statics [3]. In statics problems, balanced forces are acting on a body, which means there is no acceleration (see Fig. 1 for an example). Statics problems can become quite complex, as you can probably imagine. Researchers noticed that students who best understood statics were the ones who explained to themselves how to solve these types of problems. In other words, the best students naturally engaged in self-explaining. They also generated several self-explanation inferences to fill in the missing pieces of information that are not stated explicitly in the text. These missing pieces are necessary to fully understand the problem's solution.

Fig 1. An example statics problem.

Can you motivate students to self-explain? 

It's really interesting to read transcripts of students as they attempt to make sense of a complex topic. They might not understand it at first. But as they explain it to themselves, they are then able to see how to correct their current understanding with the model presented in the text. Good students naturally self-explain, but can we get all students to engage in self-explaining? The answer, as it turns out, is a qualified "yes." 

In one of the first studies to demonstrate that self-explaining can be prompted, researchers asked eighth grade students to read a passage about the human circulatory system [4]. Before students read the passage, the researchers asked them several questions about their understanding of the circulatory system. Because they were so young, it was no surprise that students generally had an impoverished understanding of the circulatory system. Most knew that the heart beats, but they didn't know why or what purpose the heart served. Some of the better students knew that the heart circulates blood, but they didn't understand pulmonary circulation. That is, they didn't realize that the heart has a special circuit of blood that goes to the lungs for oxygenation (and back).

After the pretest phase of the experiment, the students were asked to read a text passage that described, in detail, all of the steps of circulation. The student was verbally prompted by the experimenter to self-explain after reading each sentence of the text. After a while, merely turning the page was a prompt to self-explain. In other words, the researchers trained the students to self-explain, and then they reminded them over and over to self-explain. It was a pretty heavy-handed approach, but it worked. It paid off because the students who were prompted to self-explain demonstrated a more robust mental model of the circulatory system on the post-test than students in control condition who were only prompted to think about or reread the sentences.

Why was prompting students to self-explain a qualified success? Like most educational interventions, there were individual differences in the amount and effectiveness of the prompting. Some students generated several self-explanation inferences, whereas others generated only a few. Since the original study, researchers have designed new ways to help students become better self-explainers. For example, one study gave students an incorrect solution and asked students to debug the fictitious student's reasoning process [5]. This helped take the pressure off the student so that they could focus their attention on reconciling the differences between the correct and incorrect solution paths.

The STEM Connection

The connection between self-explanation and STEM education is extremely straightforward. Students should be trained on the definition of what self-explaining is. Then they should be prompted, periodically, to engage in self-explaining. To help them get started, here is a list of prompts that were used in the original study [4]: 

1. What new information does each line provide for you?
2. How does it relate to what you’ve already read?
3. Does it give you a new insight into your understanding of how ______ works?
4. Does it raise a question in your mind?

Also, students should be shown evidence of the utility of self-explaining. Students will probably be more likely to self-explain if they understand what it will eventually buy them. Moreover, students should be given an opportunity to develop the skill [6]. In fact, there is an intelligent tutoring system that was developed to do precisely that. The iSTART system gives students the opportunity to self-explain while reading complex textual passages [7]. Because self-explaining can be mentally taxing, the iSTART system was even outfitted with a bunch of mini-games to help build fluency in self-explaining [8].

Self-explaining is a powerful learning mechanism. It can be time-consuming and mentally exhausting, but the end result is definitely worth the effort. Like other concepts covered in this blog, self-explaining is a skill, which means it can become automatized over time. Thus, we need to get students started with self-explaining as early as possible because when they get to college, they will thank us for giving them the tools to make sense of tough concepts like organic chemistry (and flushable toilets). 


Share and Enjoy!

Dr. Bob

For More Information

[1] Here is the resource I consulted to write this description. To further enhance reading comprehension, it's typically to include a diagram. I intentionally omitted the diagram because I wanted you to attempt to assemble a mental model without a visual aid. 

[2] Chi, M. T. H. (2000). Self-explaining expository texts: The dual processes of generating inferences and repairing mental models. In R. Glaser (Ed.), Advances in Instructional Psychology, Hillsdale, NJ: Lawrence Erlbaum Associates. 161-238.

[3] Chi, M. T. H., Bassok, M., Lewis, M., Reimann, P., & Glaser, R. (1989). Self-explanations: How students study and use examples in learning to solve problems. Cognitive Science, 13: 145-182.

[4] Chi, M. T. H., de Leeuw, N., Chiu, M. H., & LaVancher, C. (1994). Eliciting self-explanations improves understanding. Cognitive Science, 18: 439-477.

[5] Booth, J. L., Lange, K. E., Koedinger, K. R., & Newton, K. J. (2013). Using example problems to improve student learning in algebra: Differentiating between correct and incorrect examples. Learning and Instruction, 25, 24-34.

[6] Hausmann, R.G.M., & Chi, M.T. H. (2002). Can a computer interface support self-explaining? Cognitive Technology, 7(1), 4-14.

[7] McNamara, D. S., Levinstein, I. B., & Boonthum, C. (2004). iSTART: Interactive strategy training for active reading and thinking. Behavior Research Methods, Instruments, & Computers, 36(2), 222-233.

[8] Jackson, G. T., & McNamara, D. S. (2013). Motivation and performance in a game-based intelligent tutoring system. Journal of Educational Psychology, 105(4), 1036.

The Sandpaper Theory of Success: Grit

We all know the importance of IQ on academic success, but the problem is that it takes so long to measure. To get around that problem, psychometricians have boiled the traditional IQ test down to three questions. Take a few minutes and answer the World's Shortest IQ Test [1]:

1. A bat and a ball cost $1.10 in total. The bat costs $1.00 more than the ball. How much does the ball cost? _____ cents
2. If it takes 5 machines 5 minutes to make 5 widgets, how long would it take 100 machines to make 100 widgets? _____ minutes
3. In a lake, there is a patch of lily pads. Every day, the patch doubles in size. If it takes 48 days for the patch to cover the entire lake, how long would it take for the patch to cover half of the lake? _____ days

The Right Stuff

The history of IQ testing is extremely interesting [2]. The purpose of testing someone's IQ is to predict how well that person will perform on some important (future) task. For instance, a Harvard admission officer would like to admit only the students who are most likely to graduate. The officer needs information today that will help her reliably place her bet. Moreover, she doesn't want to be fooled by any surface features that may seem to be related to graduation rate (e.g., the applicant's family name). In other words, the admission officer needs a measure today that will highly correlate with the outcome of graduation, which will most likely take place in four to five years. If she has 37,000 applications for only 2,000 slots, how will she choose? What information is the most reliable? 

High-profile colleges and universities turned to intelligence testing in an effort to become more egalitarian. The name and content of those intelligence tests may have changed over the years, but the intent behind them has always been the same: Find a scientifically valid measure that correlates with academic success. Once that has been established, then decision makers will have an easier time allocating their scarce resources (e.g., admission to Harvard).

While the goal may be clear, its implementation is far from it. First of all, there isn't universal agreement on what counts as "academic success." Is it merely graduating? Or does the student have to earn all "A's"? Does the student have to obtain a high-paying job straight out of school to be considered a success? Because of this ambiguity, there may be some behavioral measures that correlate better with certain definitions of success than others. So now what? Where does that leave IQ testing?  

"Get a hold of yourself!"  

For the sake of moving the conversation forward, let's assume that academic success is rigorously defined as the student's final GPA. The association between IQ and final GPA, unfortunately, is modest (r = .32). That means that only about 10% of the variance is explained by differences in IQ. Said a different way, 10% of the differences in the outcome measure (i.e., final GPA) can be explained by differences in IQ. A third way to think about it is if we consider all of the students with the exact same IQ; their final GPAs are going to be fairly different from each other. How might we explain the differences in GPA for kids who all have roughly the same IQ? 

Because IQ is an imperfect predictor, scientists decided to expand their search and consider various other factors. What other traits can we measure to predict success? Angela Duckworth and the collaborators in her lab decided to focus on two very important personality traits: grit and self-control [3]. Grit can be thought of as persistence in the face of adversity and self-control as the ability to delay gratification in the service of long-term goals. How well do grit and self-control stack up against IQ? 

According to one of their studies [4], the correlation between IQ and final GPA was r = .32, whereas the correlation between final GPA and their measure of self-control was r = .67. A perfect correlation (r = 1.00) means that you can predict the outcome of an event every single time. Thus, the measure of self-control was twice as good at predicting academic success as IQ. That's pretty interesting given our infatuation with "IQ."

The STEM Connection

Given that grit and self-control are more strongly associated with academic success than IQ, what does that mean for education? 

First, I think the time is ripe to banish the word "smart" from our vocabulary. Why? Because it does not motivate people toward higher levels of academic achievement. For example, suppose I told you that you are smart. Now what? Are you going to seek out challenging assignments that stretch you in a new direction? Or are you going to play it safe and only accept assignments that are within your comfort zone? That way you can continue to collect confirmatory evidence that you are smart. Alternatively, what if I labeled you as gritty. How might that affect your behavior? You might take pride in the fact that you tackled a highly challenging task, faced obstacles head on, and stuck it out until you experienced a breakthrough. Being called "gritty" moves you toward learning opportunities in a way that being labeled "smart" does not.

Second, these findings suggest that students should be given long-term assignments that are extremely difficult. In so doing, however, we should ensure that failure is an acceptable step along the way. For example, when I write a computer program, I am grateful when I fail quickly because then I can correct my mistakes and improve the overall quality of the program [5]. 

Finally, we should strongly consider adding character strengths as part of our standard curriculum. Like the growth mindset, these qualities are malleable and can be taught. Some charter schools go so far as to weave character development into the very fabric of their school [6]. When students see the implications of their behavior (i.e., by quitting or not) on their classmates, the lesson comes to life and is thereby encoded as an episodic memory. 

For each of us, grit and self-control appear in various quantities. They may fluctuate from time-to-time, and they may largely depend on the task at hand. But the main take-away from this nascent literature is that, while IQ is important for life-long success, there are other factors that strongly shape the course of one's life in school (and beyond).


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Dr. Bob

For More Information

[1] Frederick, S. (2005). Cognitive reflection and decision making. Journal of Economic perspectives, 19(4) 25-42.

[2] Gould, S. J. (1996). The mismeasure of man (Rev. ed.). New York: W.l. Norton.

[3] Watch Angela Duckworth's TED talk.

[4] Duckworth, A. L. & Seligman, M. E. P. (2005). Self-discipline outdoes IQ predicting academic performance in adolescents. Psychological Science, 16, 939-944.

[5] Fail Fast has become a mantra in Silicon Valley. 

[6] Read about the KIPP Academy in Tough, P. (2013). How children succeed. Random House (cf. Chapter 2).