Saturday, June 27, 2015

Mental practice & Mental rehearsal

Mental practice

In 1972, Corbin defined mental practice as the repetition of a task, without observable movement with the specific intent of learning’. It is to enhance performance in the absence of a physical activity.

There is some agreement that mental practice frequently has a beneficial effect on other the learning of a new skill or the betterment of performance of an existing skill.

Mental practice has been found to improve both cognitive and psychomotor performance.

The use of mental visualization in sports, mental practice was used in the context of sports psychology as a possible means for improving performance on a wide range of sport related task.

The mental practice most helpful to improve riding skills, is the mental practice of those skills in the midst of being improved or attempted for the first time.

Mental practice is most famous for the gains achieved in terms of muscle memory and the mental organization of sub-skills needed to successfully achieve a new skill.

Mental rehearsal

Mental rehearsal is one aspect of imaginary. It means the mental practice of performing a skill as oppose to actual practice. This is sometimes called mental practice and is a strategy adopted by many sportsmen and women.

It is a strategy for practicing something in mind before actually performing the task.

By mentally rehearsing it form mental image of the skill or event that the people are going to perform. No physical movements are involved in mental rehearsal. Some performers find mental rehearsal easier than other but the ability can be improved with practice. Mental rehearsal appears to be particularly useful in therapy settings with patients who are unable to engage in large amounts of physical practice because they lack endurance.

Mental rehearsal is used either to learn a new skill or to improve existing skills. There are a number of ways in which metal rehearsal is used including skills practice and rehearsal, practicing for events, competition practice, practicing ‘What if….?’, scenarios, replaying performance and performance routines.

How does the brain work?

We have no idea. We are still in the very beginning stages of understanding most of the basics. From a researcher's perspective, it's a very exciting time to be a scientist, because you get to rummage around on the ground floor. But from an overall perspective, most of it is spooky.  

Let me give you some examples of how little we know about how the brain works. We know that you use the left-side of your brain for speech. Under normal circumstances, if you get a stroke on the left side of your brain, your speech can be greatly affected. Depending upon where you got the stroke, it could affect your ability to speak language or your ability to understand language.

There is a little six year old who suffered from something Sturge-Weber syndrome, a catastrophic brain disease. Because he had this disorder, the little guy had to have his entire left hemisphere removed. No left hemisphere, no language. That should have completely destroyed his language ability. Right?

Wrong!

Within two years, the little guy had regained his language abilities entirely. The right side of his brain seemed to have noticed there was a deficit and simply rewired itself to take over talking. Do we understand this?

We do not.

We do not understand how you learn a language of any kind. We don't know how you know how to walk. We don't know how you know how to read. You have a complete map of your body in your head. Actually, you have several maps of your body in your head. Some of them tell you where you are, some of them tell you how to move. One even tells you how to see. We don't know how they coordinate their information. We don't know how it knows its you - and what, if anything, YOU are. Consciousness remains a slippery fish as ever.

So you ask me how the brain works. I am happy to repeat my answer. We have no idea.

Visit brainrules.net to learn about the 12 things we know about how the brain works. These are the Brain Rules

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Optimal Spacing for Study, What's this?

We have all been told by teachers that learning occurs best when we spread it out over time, rather than trying to cram everything into our memory banks at one time. But what is the optimal spacing? There is no general consensus.
However we do know that immediately after a learning experience the memory of the event is extremely volatile and easily lost. It's like looking up a number in the phone book: if you think about something else at the same time you may have to look the number up again before you can dial it. School settings commonly create this problem. One learning object may be immediately followed by another, and the succession of such new information tends to erase the memory of the preceding ones.
Memory researchers have known for a long time that repeated retrieval enhances long-term retention. This happens because each time we retrieve a memory, it has to be reconsolidated and each such reconsolidation strengthens the memory. Though optimal spacing intervals have not been identified, research confirms the importance of spaced retrieval. No doubt, the nature of the information, the effectiveness of initial encoding, competing experiences, and individual variability affect the optimal interval for spaced learning.
One study revealed that repeated retrieval of learned information (100 Swahili–English word pairs) with long intervals produced a 200% improvement in long-term retention relative to repeated retrieval with no spacing between tests. Investigators compared different-length intervals of 15, 30, or 90 minute spacing that expanded (for example, 15-30-45 min), stayed the same (30-30-30 min) or contracted (45-30-15 min) revealed that no one relative spacing interval pattern was superior to any other.
Another study has revealed that the optimally efficient gap between study sessions depends on when the information will be tested in the future. A very comprehensive study of this matter in 1,350 individuals involved teaching them a set of facts and then testing them for long-term retention after 3.5 months. A final test was given at a further delay of up to one year. At any test delay, increasing the inter-study gap between the first learning and a study of that material at first increased and then gradually reduced final test performance. Expressed as a ratio, the optimal gap equaled 10-20% of the test delay. That is, for example, a one-day gap was best for a test to be given seven days later, while a 21-day gap was best for a test 70 days later. Few of any teachers or students know this, and their study times are rarely scheduled in any systematic way, typically being driven by test schedules for other subjects, convenience, or even the teacher's whim.
The bottom line: the optimal time to review a newly learned experience is just before you are about to forget it. Obviously, we usually don't know when this occurs, but in general the vast bulk of forgetting occurs within the first day after learning. As a rule of thumb, you can suspect that a few repetitions early on should be helpful in fully encoding the information and initiating a robust consolidation process. So, for example, after each class a student should quickly remind herself what was just learned—then that evening do another quick review. Before the next class on that subject, the student should review again. Teachers help this process by linking the next lesson to the preceding one.
Certain practices will reduce the amount of time needed for study and the degree of long-term memory formation. These include:

• Don't procrastinate. Do it now!
• Organize the information in ways that make sense (outlines, concept maps)
• Identify what needs to be memorized and what does not.
• Focus. Do not multi-task. No music, cell phones, TV or radio, or distractions of any kind.
• Association the new with things you already know.
• Associate words with mental images and link images to locations, or in story chains
• Think hard about the information, in different contexts
• Study small chunks of material, in short intervals. Then take a mental break.
• Say out loud what you are trying to remember.
• Practice soon after learning and frequently thereafter at spaced intervals.
• Explain what you are learning to somebody else. Work with study groups later.
• Self-test. Don't just "look over" the material. Truly engage with it.
• Never, never, ever CRAM!

Sleep in Your bad attitude, avoid!!

Generally speaking, you cannot learn from sounds of new information while you sleep, though this was a fad several decades ago. But in an earlier post, I discussed a new line of research where sleep learning can occur. The key is to play sound cues that were associated with learning that occurred during the previous wakefulness period. The explanation I posted was that cue-dependent sleep learning can work because a normal function of sleep is to strengthen memories of new information and that presenting relevant cues during sleep increases the retrieval of these memories and makes them accessible for rehearsal and strengthening.
The latest experiment by a different group shows that this cuing during sleep can modify bad attitudes and habits. The test involved counter stereotype-training of certain biased attitudes during wakefulness, and investigators reactivated that counter-training during sleep by playing a sound cue that had been associated with the wakefulness training.
In the experiment, before a 90-minute nap 40 white males and females were trained to counter their existing gender and racial biases by counter-training. A formal surveyed allowed quantification of each person's level of gender or racial bias before and after counter-training. For example, one bias was that females are not good at math. Subjects were conditioned to have a more favorable attitude about women and math with counter-training that repeatedly associated female faces with science-related words. Similarly, racial bias toward blacks was countered by associating black faces with highly positive words. In each training situation, whenever the subject saw a pairing that was incompatible with their existing bias they pressed a "correct" button, which yielded a confirmatory sound tone that was unique for each bias condition. Subjects were immediately tested for their learning by showing a face (female or black) and the counter-training cue, whereupon they were to drag the appropriate bias-free face on to a screen with the positive word. For example, if the first test screen was that of a woman, accompanied by the sound cue, the subject dragged a woman's face onto a second screen that said "good at math." Results revealed that this conditioning worked: both kinds of bias were reduced immediately after counter-conditioning.
Then during the nap, as soon as EEG signs indicated the presence of deep sleep, the appropriate sound cue was played repeatedly to reactivate the prior learning. When subjects re-took the bias survey a week later, the social bias was reduced in the sound-cued group, but not in the control group that was trained without sound cues.
Experimenters noted that the long-term improvement of bias was associated with rapid-eye-movement (REM) (dream) sleep which often followed the deep sleep during early stages of the nap. That is, the beneficial effect was proportional to the amount of nap time spent in both slow-wave sleep and REM sleep, not either alone. It may be that memories are reactivated by cuing during deep (slow-wave) sleep, but that the actual cell-level storage of memory is provided by REM sleep.
Implications of this approach to enhancing learning and memory show a great deal of promise. Can it be used for enhancing learning in school? Can it be used in rehabilitation of addicts or criminals? But there is a dark side. Now might be a good time to re-read Huxley'sBrave New World wherein he actually described conditioning values in young children while they slept. Sleep is a state where people are mentally vulnerable and without conscious control over their thoughts. Malevolent people could impose this kind of conditioning and memory enhancement on others for nefarious purposes.  These techniques may have valid social engineering applications, but they must be guided by ethical considerations.

Friday, June 19, 2015

Excuse-making by School Children

My last column on "Blaming the Victim" was a departure from my usual emphasis on improving learning and memory. But it did set the stage for this current post on the crippling effect of allowing children to make excuses for underperformance in school.
Most of us know how common it is for kids to make excuses ("the dog ate my homework" syndrome). When we adults were young, we also probably made excuses, blaming the textbook, the teacher, the school, and whatever else could serve to avoid facing the real causes of the problems.
Why do kids do that? The main reason is their fragile egos. Confronting personal weakness is especially hard for kids when they are embedded in an adult culture that inevitably reminds them that they are relatively powerless kids.
I remember a recent dinner-table conversation with my competitive 6th grade granddaughter, who was complaining about a test in which some of the questions were not aligned well with the instruction, which itself was deemed confusing. I said, "I understand that others did do better than you on the test. Wasn't everybody facing the same handicap?" No answer. Then I added, "It doesn't matter who the teacher is or what instruction you get. If you are not first in the class, it is your fault." Again, no response.
One approach that parents and teachers use is to bolster children's egos by praising them richly and often. Too much of a good thing is a bad thing. Too much praise makes kids narcissistic. Anybody who is not aware of the raging narcissism in today's youngsters must not be around young people very much. The most obvious sign is the compulsive checking of e-mail and texting, all in an effort by a child to be at the center of attention.
I and other professors notice narcissism in college students. In a selective college, most students think they are "A" students, and because of low standards in secondary school and grade inflation they are actually told they are A students. If they don't make As in college, it is somebody else's fault (usually the professor).
Scholars are beginning to address this growing narcissism. Eddie Brummelman at the University of Amsterdam in the Netherlands and his colleagues studied 565 children between the ages of 7 to 12. They picked this age group because most other such studies have been in adults, and they believed that early adolescence is when children develop narcissistic traits such as selfishness, self-centeredness and vanity.
Over 18 months, the children and their parents were given several detailed questionnaires that were designed to measure narcissistic traits and parental behavior. There was a small but significant link at each stage between how much parents praised their children and how narcissistic the children were six months later. Because the effect was only small, it suggests that other things also make people selfish and self-centered. I suspect the effect is larger in the U.S.
Maybe school culture is part of the problem. As in Lake Woebegon, "all kids are above average." For brighter students, the instructional rigor is so low that these kids get a false sense of how smart they are and how easy it is to be an "A" student.
I suspect that another factor is that students are not taught enough about how to be realistically self-aware. They may not even know when they are making excuses unless adults call them on it. Too often, parents side with the student in criticizing a teacher when the real problem is with the child.
Some of the blame shifting comes from biology. It is in human nature to claim ownership of things we do that turn out well, but disown actions that yield negative consequences. Experiments support this conclusion. The most recent experiments had a primary focus on our sense of time in association with voluntary actions. The experimental design was based on prior evidence that the perceived estimate of time lag between when we do something and when we think we did it is an implicit index of our sense of ownership. Investigators asked people to press a key, which was followed a quarter of a second later by negative sounds of fear or disgust, positive sounds of achievement or amusement, or neutral sounds. The subjects were then asked to estimate when they had made the action and when they heard the sound. Timing estimation errors were easily measured by computer. Subjects sensed a longer time lag between their actions and the consequences when the outcome (the sound) was negative than when it was positive.

Teaching Kids to Deal with Failure


There is a common denominator to most self-limiting styles of living. It is a fear of failure. Children express this fear by making excuses, which has the unintended effect of blocking the path to success. Excuses may provide immediate relief of anxiety, but it creates a self-limiting learning style that assures continued underachievement.
Whatever one’s station in life, one axiom is paramount: for things to get better for you, you have to get better. This point is well illustrated in an inspiring rags-to-riches success book by A. J. Williams. He points out that a main reason that people do not make the changes they need to is that they are afraid of failure. But, paradoxically, learning from failure is how many people turn their lives around and become happier. Children, I have noticed, are highly resistant to personal change, maybe more so than adults. I am dismayed at how often I show children how to memorize more effectively and they just can't bring themselves to study in a different way. It is as if they don't believe me enough to even try new approaches. Or maybe they have convinced themselves they are mediocre and need the shield of excuses to keep others from detecting their weaknesses.
Louis Armstrong, the famous trumpeter, told an instructive story about fear when he was a boy. One day when his mother asked him to go down to the levee to fetch a pail of drinking water, he came back home with an empty pail. Upon noticing the empty pail, his mother said, “I told you to bring back a pail of water for us to drink. How come your pail is empty?” Louis replied, “There’s an alligator there, and I was scared to death.” His mother then said, “You shouldn’t be afraid. That gator is as afraid of you as you are of him.” To which Louis answered, “If that’s the case, then that water ain’t fit to drink.”
If there is an alligator keeping you away from what you need to do, have faith you will prevail over your demons. But as long as a child lets fear get in the way, her pail will stay empty.
Other kinds of fear are also self-limiting. Many children fear commitment to learning. Commitment exacts an emotional price requiring dedication, passion, and self-discipline. Children fear confusion and difficulty. They fear disapproval.
Kids need to put their under-performance in perspective. Failure and under-achievement are not permanent. They are not pervasive reflections of inadequacy. Children can acquire learning skills that lead to success. Unfortunately, schools don't teach much about learning skills, being focused on teaching to high-stakes tests.
Kids need to recognize their weakness and strive to fix them. But to bolster their motivation and general attitude about school, they need to recognize what they have done well and strive to do even more of that. Dwelling on under-performance is counter-productive.

The Most Important Thing Kids Need to Learn


Excuse-making prevents a child from developing the attitude that will best serve them throughout life: a sense of personal efficacy, a state of perceived control over one's life. I explain this more thoroughly in my book, "Blame Game, How to Win It." But a summary here will have to suffice.
How children perceive their personal power determines how much effort they will expend to control their lives. If they lack a genuine sense of power, excuse-making applies salve to their wounded egos. Self-efficacy is not the same as self-esteem. Psychologist, Albert Bandura, puts it this way: “Perceived self-efficacy is concerned with judgments of personal capability, whereas self-esteem is concerned with judgments of self-worth.” Both are important for happiness, but it is perceived self-efficacy that drives academic achievement. One practical application where this distinction is apparently not recognized is with school teachers who think the cure for low achievement in school is to foster self-esteem. Teachers should emphasize self-efficacy. Children learn self-efficacy from teachers and parents who enable them to master their environment. Students who are filled with self-doubt do not put much effort into school work. They make excuses. As kids are progressively given the skills to achieve, they develop a sense of confidence in their ability to succeed, which will motivate them to strive for more achievement. When I was a kid, I only became a good student when I discovered, more or less by accident, that I could make good grades. Discovering that I could make good grades if I tried motivated me to do just that. This sense has to be earned. It does not come from excuses.

Physical exercise to improve memory

A great way to improve memory is a physical exercise. It is an exceptional way to increase memory.  Exercises can reverse changes in the brain that cause cognitive decline.

Exercise increases blood flow and oxygen to the brain and stimulates nervous system. This releases endorphins onto the blood stream that creates that overall feeling of well-being.

Exercise can help us to get back our memory where it should be. We can take a walk and free ourself from any frustration that we may be experiencing.

By increasing the supply of oxygen to the brain, exercise helps reducing risk for disease and disorders that eventually lead to memory loss.

According to studies, high levels of physical activity could be more protective against cognitive decline than lower levels (Scarmeas, Luchsinger & Schupf, 2009; Taaffe 2008; Weuve, 2004).

When we’re not exercising, our brain is not receiving much blood. Blood needs to flow to the brain so we can think straight.  We have to move around and not be stagnant. Researchers from the Netherlands’ found that physical fitness could improve memory by boosting blood flow to the rain and increasing brain volume.
Physical exercise to improve memory

Saturday, May 30, 2015

Decision making :one of multiple category options

In the previous post, Decision-making learning from one’s mistakes., I provided evidence that selective attention to items that were retrieved into working memory were a major factor in making good decisions. This has generally unrecognized educational significance. Rarely is instructional material packaged with foreknowledge of how it can be optimized in terms of reducing the working memory cognitive load. New research from a cognitive neuroscience group in the U.K. is demonstrating the particular importance this has for learning how to correctly categorize new learning material. They show that learning is more effective when the instruction is optimized ("idealized" in their terminology).

Decisions often require categorizing novel stimuli, such as normal/abnormal, friend/foe, helpful/harmful, right/wrong or even assignment to one of multiple category options. Teaching students how to make correct category assignments is typically based on showing them examples for each category. Categorization issues routinely arise when learning is tested. For example, the common multiple-choice testing in schools requires that a decision be made on each potential answer as right or wrong.

In reviewing the literature on optimizing training, these investigators found reports that one approach that works is to present training in a specific order. For example, in teaching students how to classify by category, people perform better when a number of examples from one category are presented together followed by a number of contrasting examples from the other category. Other ordering manipulations are learned better if simple, unambiguous cases in either category are presented together early in training, while the harder, more confusing cases are presented afterwards. Such training strengthens the contrast between the two categories.

The British group has focused on the role of working memory in learning. Their idea is that ambiguity during learning is a problem. In real-world situations that require correct category identification, naturally occurring ambiguities make correct decisions difficult. Think of these ambiguities as cognitive "noise" that interferes with the training that is recalled into working memory. This noise clutters the encoding during learning and clutters the thinking process and impairs the rigorous thought processes that may be needed to make a correct distinction. In the real world of youngsters in school, other major cognitive noise sources are the task-irrelevant stimuli that come from multi-tasking habits so common in today's students.

The theory is that when performing a learned task, the student recalls what has been taught into working memory. Working memory has very limited capacity, so any "noise" associated with the initial learning may be incompletely encoded and the remembered noise may also complicate the thinking required to perform correctly. Thus, simplifying learning material should reduce remembered ambiguities, lower the working memory load, and enable better reasoning and test performance.


One example of optimizing learning is the study by Hornsby and Love (2014) who applied the concept to training people with no prior medical training to decide whether a given mammogram was normal or cancerous. They hypothesized that learning would be more efficient if students were trained on mammograms that were easily identified as normal or cancerous, and did not include examples where the distinction was not so obvious. The underlying premise is that decision-making involves recalling past remembered examples into working memory and accumulating the evidence for the appropriate category.  If the remembered items are noisy (i.e. ambiguous) the noise also accumulates and makes the decision more difficult. Thus, learners will have more difficulty if they are trained on examples across the whole range of possibilities from clearly evident to obscure than if they were separately trained on examples that were clearly evident as belong into one category or another.

Initially a group of learners was trained on a full-range mixture of mammograms so the images could be classified by diagnostic difficulty as easy or hard or in between. On each trial, three mammograms were shown: the left image was normal, the right was cancerous, and the middle was the test item requiring a diagnosis of whether it was normal or cancerous.

In the actual experiment, one student group was trained to classify a representative set of easy, medium, and hard images, while the other group was trained only on easy samples. During training trials, learners looked at the three mammograms, stated their diagnosis for the middle image, and were then given feedback as to whether they were right or wrong. After completing all 324 training trials, participants completed 18 test trials, which consisted of three previously unseen easy, medium and hard items from each category displayed in a random order. Test trials followed the same procedure as training trials.

When both groups were tested on samples across the range in both conditions, the optimized group was better able to distinguish normal from cancerous mammograms in both the easy and medium images. Note that the optimized group was not trained on medium images. However, no advantage was found in the case of hard test items; both groups made many errors on the hard cases, and optimized training yielded poorer results than regular training. 

We need to explain why this strategy does not seem to work on hard cases. I suspect that in easy and medium cases, not much understanding is required. It is just a matter of pattern recognition, made easier because the training was more straightforward and less ambiguous. The learner is just making casual visual associations. For hard cases, a learner must know and understand the criteria needed to make distinctions. The subtle differences go unrealized if diagnostic criteria are not made explicit in the training. In actual medical practice, many mammograms actually cannot be distinguished by visual inspection—they really are hard. Other diagnostic tests are needed.

The basic premise of such research is that learning objects or task should be pared down to the basics, eliminating extraneous and ambiguous information, which constitute “noise” that confounds the ability to make correct categorizations.

In common learning situations, a major source of noise is extraneous information, such as marginally relevant detail. Reducing this noise is achieved by focus on the underlying principle. Actually I stumbled on this basic premise of simplification over 50 years ago when I was a student trying to optimize my own learning. What I realized was the importance of homing in on the basic principle of what I was trying to learn from instructional material. If I understood a principle, I could use that understanding to think through to many of the implications and applications.

In other words, the principle is: "don't memorize any more than you have to." Use the principles as a way to figure out what was not memorized. Once core principles are understood, much of the basic information can be deduced or easily learned. This is akin to the standard practice of moving from the general to the specific. Even so, general ideas should emphasize principles.

Textbooks are sometimes quite poor in this regard. Too many texts have so much ancillary information in them that they should be thought of as reference books. That is why I have found a good market for my college-level neuroscience electronic textbook, “Core Ideas in Neuroscience,” in which each 2-3 page chapter is based entirely on each of the 75 core principles that cover the broad span of membrane biochemistry to human cognition.. A typical neuroscience textbook by other authors can run up to 1,500 pages.