On a scale of 1 to 10, how much do you think Pearson publishing cares about the efficacy of their products?
Now now, I asked for a numerical rating, not invective or expletives.
My own rating might be a three or a four. I'm guessing that the folks at Pearson care about effectiveness to some
extent because it affects how much things sell.
But the bottom line is that what matters is the bottom line. The success and failure of particular marketing strategies are followed closely, I'm guessing, as are sales of particular products. Learning outcomes from the product? Well, the customer can track them if they are interested.
So what are we to make of it when Pearson says
"We are putting the pursuit of efficacy and learning outcomes at the centre of our new global education strategy."
Educators have every right to be cynical. It's not just that Pearson has shown little inclination in this direction in the past, but also that it's a publicly traded company that shareholders ought to expect will put profits first.
Ironically, the path
Pearson plans to effect this change is mostly about inputs: hiring people who care about efficacy, developing a global research network to gather evidence, that sort of thing.
But crucially they also promise to track outcomes, namely "to report audited learning outcomes, measures, and targets alongside its financial accounts, covering its whole business by 2018."
That's an enormous commitment and if they really follow through, it gives me some confidence that this is not merely a marketing ploy. Or if it is, the marketing team has concluded that to make this ploy appear not to be a ploy, they need to put some teeth in the plan.
A significant aspect of the success of this step turns on that small adjective "audited." It's not that hard to cook the learning outcome books. For this new effort to be persuasive, Pearson will need to have disinterested parties weigh in on the efficacy measures used, and their interpretation.
A person knowledgeable about testing, yet wholly disinterested? Does Pearson have Diogenes on staff?
There's another aspect of this plan that I find even more interesting, and potentially useful. Pearson has published a do-it-yourself efficacy review tool. It's a series of questions you are to consider to help you think about the effectiveness of a product you are currently using, or are contemplating using. There's an online version as well as a downloadable pdf.
The tool encourages you to consider four factors (listed here in my own phrasing):
- What am I trying to achieve?
- What evidence is there that this product will help with my goal?
- What's my plan to use this tool?
- Do I have what I need to make my plan work?
These simple, sensible questions are elaborated in the framework, but working through the details should still take less than an hour. The tool includes sample ratings to help the user think through the rating scheme.
I think this tool is great, and not just because it aligns well with a similar tool I offered in When Can You Trust the Experts?
I think it offers Pearson a way to gain credibility as the company that cares about efficacy. If I were to hear that Pearson's sales force made a habit of encouraging district decision-makers to apply this efficacy framework to the educational products of Pearson (and others) that would be a huge step forward.
I would be even more impressed if Pearson warned users about the difficulty of overcoming the confirmation bias, and making these judgments objectively.
Still, this is a start. There might be some satisfaction in greeting this move with cynicism, but I think it's better to start with skepticism--skepticism that will prompt action and help to encourage educators to think effectively about efficacy.
Is there a critical period of brain plasticity for literacy? We know that brain development progresses with age. If a child does not learn to read at the right age, has the brain lost its plasticity such that learning to read will be more difficult?
For at least one aspect of brain plasticity, we now have data indicating that the answer is “no.”
That aspect of plasticity that bears on reading is the loss of mirror invariance in visual perception.
Mirror invariance means recognizing a mirror image as the same object. It makes good sense for visual recognition to be set up this way. If I recognize a dog facing to my left, I ought to recognize the same dog facing to my right as the same object.
But mirror invariance is a problem when children are learning to read, because for that task one must NOT treat mirror-reversed objects as identical: b and d must be treated differently. Anyone who has observed children learning to read and write cannot help but notice that they initially make a lot of mirror reversal errors. The errors disappear with practice.
In a recent study Felipe Pegado and colleagues (2013) set out to investigate whether literacy changes mirror invariance not just for letters of the alphabet, but for other visual stimuli as well. Does the process of learning to read actually change this aspect of vision?
The researchers simply showed subjects pairs of stimuli, to which they were to respond “same” or “different” via button press. Mirror images were to be judged “same.”
The experimenters used three different types of stimuli: pictures, letter strings, and false fonts (that is, letter-like stimuli that were not actually letters.
Of most interest, they tested three groups of subjects: illiterate adults (“il” in the graph below), ex-illiterates (i.e, those who learned to read as adults; “ex” in the graph below) and literate adults (that is, those who learned to read at a typical age; “li” in the graph below).
The solid line shows reaction times to mirror reversed images, and the dashed line is reaction time to the non-reversed images. Look first at the data for the illiterate subjects for the pictures, strings, and false fonts: they respond equally quickly for mirror reversed and same stimuli.
But the ex-illiterate (ex) and the literate (li) subjects have trouble with the mirror reversed images. They have BIG trouble with the letter strings, but they are slower even with the pictures.
What does this result mean?
A straightforward interpretation is that lots of practice with visual stimuli that are not mirror-reversible—that is, learning to read—changes the visual system. The natural state of the visual system is that mirror-reversed objects are treated as equivalent. Literate people can treat them as equivalent, but it takes a little extra time.
I find two aspects of these findings interesting: that that visual system changes in this way and that the “ex-illiterate” subjects show the same phenomenon. Thus (at least for this process) it’s not that case that, once brain development is finished the visual system is no longer open to change.
This visual process is not the only one that is changed by learning to read, but this one at least is not subject to a critical period of development.
Pegado, F., Nakamura, K., Braga, L. W., Ventura, P., Filho, G. N., Pallier, C., Jobert, A., Morais, J., Cohen, L., Kolinsky, R., & Dehaene, S. (2013, June 17). Literacy Breaks Mirror Invariance for Visual Stimuli: A Behavioral Study With Adult Illiterates. Journal of Experimental Psychology: General. doi: 10.1037/a0033198
"Stereotype threat" refers to a phenomenon in which people perform worse on tasks (especially mental tasks) in line with stereotypes, if they are are reminded of this stereotype.
Hence, the stereotype for women (in American culture) is that they are not as good at math as men; for older people, that they are more forgetful than the young; and for African-Americans, that they are less proficient at academic tasks. Members of each group do indeed perform worse at that type of task if the stereotype is made salient just before they undertake it (e.g. Appel & Kronberger, 2012).
Why does it happen? Most researchers have thought that the mechanism is via working memory. When the stereotype becomes active, people are concerned that they will verify the stereotype. These fears occupy working memory, thereby reducing task performance (e.g., Hutchison, Smith & Ferris, 2013).
But a new experiment offers an alternative account. Sarah Barber & Mara Mather (2013) suggests that stereotype threat might operate through a mechanism called regulatory fit. That's a theory of how people pursue goals. If the way you conceive of task goals matches the goal structure of the task, you're more likely to do well than if it's a poor fit.
Stereotype threat makes you focus on prevention; you don't want to make mistakes (and thus confirm the stereotype). But, Barber & Mather argue, most experiments emphasize doing well, not avoiding mistakes. Thus, you'd be better off with a promotion focus, not a prevention one.
To test this idea, Barber & Mather tested fifty-six older (around age 70) subjects on a combined memory/working memory task. Subjects read sentences, some of which made sense, others which were nonsensical either syntactically or semantically.
Subjects indicated with a button press whether the sentence made sense or not. In addition, they were told to remember the last word of the sentence for as many of the sentences as they could. Task performance was measured by a combined score: how many sentences were correctly identified (sensible/nonsensical) and how many final words were remembered.
Next, subjects read one of two fictitious news articles. The one meant to invoke stereotype threat described the loss of memory due to aging. The control article described preservation of memory with aging.
Then, subjects performed the sentence task again. We would expect that stereotype threat would lead to worse performance.
BUT the experimenters also varied the reward structure of the task. Some subjects were told they would get a monetary reward for good performance. Others were told they were starting with a set amount of money, and that each memory error would incur a penalty.
The instructions made a big difference in the outcome. As shown in the graph, framing in terms of costs for errors didn't just remove stereotype threat; it actually lead to an improvement.
This outcome makes sense, according to the regulatory fit hypothesis. Subjects were worried about errors, and the task rewarded them for avoiding errors.
These data are the first to test this new hypothesis as to the mechanism of stereotype threat, and should not be seen as definitive.
But if this new explanation holds up (and if it applies to other groups) it should have significant implications for how threat can be avoided.
Appel, M., & Kronberger, N. (2012). Stereotypes and the achievement gap: Stereotype threat prior to test taking. Educational Psychology Review, 24(4), 609-635.
Barber, S. J., & Mather, M. (2013). Stereotype Threat Can Both Enhance and Impair Older Adults’ Memory. Psychological science, published online Oct. 22, 2013. DOI: 10.1177/0956797613497023.
Hutchison, K. A., Smith, J. L., & Ferris, A. (2013). Goals Can Be Threatened to Extinction Using the Stroop Task to Clarify Working Memory Depletion Under Stereotype Threat. Social Psychological and Personality Science, 4(1), 74-81.
I finally got around to reading Paul Tough's How Children Succeed. If you haven't read it yet, I recommend that you do.
You probably know by now the main message: what really counts for academic success is conscientiousness (or its close cousins, grit, or character or non-cognitive skills).
Tough intersperses explanations of the science behind these concepts with stories of students that he's met and followed. The stories add texture and clarity, and Tough is among a very small number of reporters who gets complex science right consistently. He takes you through attachment theory, the HPA axis, and executive control functions, all without losing his footing nor prompting glazing in the reader's eyes.
Tough also devotes considerable space to a fascinating inside look at how charter school mavens have thought about self-control, how their thinking has changed over time, and how their views square with the science.
The only flaws I see in the book concern a couple of big-picture conclusions that Tough draws.
First, there's what Tough calls the cognitive hypothesis--that academic success is driven primarily (perhaps even solely) by cognitive skills. The book suggests that this premise may be in error. What really counts is self-control.
But of course, you do need cognitive skills for academic success. In fact, Tough describes in detail the story of a boy who is very gritty indeed when it comes to chess, and who scales great heights in that world. But he's not doing all that well in school, and a teacher who tries to tutor him is appalled by what he does not know.
Self-control predicts academic success because it makes you more likely to do the work to develop cognitive skills. I'm sure Tough understands this point, but a reader could easily miss it.
Second, Tough closes the book with some thoughts on education reform. This section, though brief, struck me as unnecessary and in fact ill-advised. The whole book is about individual children and what makes them tick. Jumping to another level of analysis--policy--can only make this speculation seem hasty.
But these two minor problems are mere quibbles. If you have heard about "non-cognitive skill," or "self-control" or "grit" and wonder whether there's anything to it, you'd be hard put to find a better summary than How Children Succeed.
My colleague, Tim Wilson, has long advocated that the psychology department at the University of Virginia stop interviewing potential graduate students or job applicants.
We conduct unstructured interviews, as most departments do, meaning the candidate meets with an individual for twenty or thirty minutes and chats.
You do end feeling as though you have a richer impression of the person than that gleaned from the stark facts on a resume. But there's no evidence that interviews prompt better decisions (e.g., Huffcutt & Arthur, 1994).
A new study (Dana, Dawes, & Peterson, 2013) gives us some understanding of why.
The information on a resume is limited but mostly valuable: it reliably predicts future job performance. The information in an interview is abundant--too abundant actually. Some of it will have to be ignored. So the question is whether people ignore irrelevant information and pick out the useful. The hypothesis that they don't is called dilution. The useful information is diluted by noise.
Dana and colleagues also examined a second possible mechanism. Given people's general propensity for sense-making, they thought that interviewers might have a tendency to try to weave all information into a coherent story, rather than to discard what was quirky or incoherent.
Three experiments supported both hypothesized mechanisms.
The general method was this. 76 students at Carnegie Mellon University served as interviewers. They were shown the academic record of a fellow student who they would then interview. (The same five students served as interviewees throughout the experiment.)
The interviewers were to try to gain information through the interview to help them predict the grade point average of the interviewee in the next semester. The actual GPA was available so the dependent measure in the experiment was the accuracy of interviewers' predictions.
The interviewers were constrained to asking yes-or-no questions. The interviewee either answered accurately or randomly. (There was an algorithm to produce random "yeses" or "nos" on the fly.) Would interviewers do a better job with valid information than random information?
It's possible that limiting the interview to yes or no questions made the interview artificial so a third condition without that constraint was added, for comparison. This was called the natural condition.
The results? There was evidence for both dilution and for sense-making.
Dilution because interviewers were worse at predicting GPA than they would have been if they had used previous GPA alone. So the added information from the interview diluted the useful statistical information.
Sense-making because ratings made after the interview showed that interviewers generally agreed with the statement "From the interview, I got information that was valuable in making a GPA prediction."
There were no differences among the accurate, random, and natural conditions on these measures.
It's possible that the effect is due, at least in part, to the fact that interviewers themselves pose the questions. That makes them feel that answers confirm their theories about the interviewee.
So in a second experiment researchers had subjects watch a video of one the interviews conducted for the first experiment, and use that as the basis of their GPA prediction. All of the results replicated.
Keep in mind, what's new in this experiment is not the finding that unstructured interviews are not valid. That's been long known. What's new is some evidence as to the mechanisms: dilution and sense-making.
And sense-making in particular gives us insight into why my colleagues in the psychology department have never taken Tim Wilson's suggestion seriously.
Dana, J., Dawes, R., & Peterson, N. (2013) Belief in the unstructured interview: The persistence of an illusion. Judgement and Decision Making, 8, 512-520.
Huffcutt, A. I. & Arthur, W. Jr. (1994). Hunter and Hunter (1984) revisited: Interview validity for entry-level jobs. Journal of Applied Psychology, 79, 184-190.
The results of this experiment probably won't surprise you. What surprised me was the fact that we didn't already have data like this in hand.
The researchers (Sadler et al., 2013) tested 181 7th and 8th grade science teachers for their knowledge of physical science in fall, mid-year, and years end. They also tested their students (about 9,500) with the exact same instrument.
Each was a twenty-item multiple choice test. For 12 of the items, the wrong answers tapped a common misconception that previous research showed middle-schoolers often hold. For example, one common misconception is that burning produces no invisible gases. This question tapped that idea:
But the researchers didn't just ask the teachers to pick the right answer. They also asked teachers to pick the answer that they thought their students would pick.
What makes this study interesting is that it tests teacher subject-matter knowledge directly (instead of using a proxy like courses taken, or degrees) and that it directly measures one aspect of pedagogical content knowledge, namely, student misconceptions. The dependent measure of interest is student gain scores in content knowledge over the course of the year.
Teachers content knowledge was good, but not perfect. They got about 84% of the questions right.
Their knowledge of student misconceptions was not as good. Teachers correctly identified just 43% of those. (And their students had, as in previous studies, selected those incorrect items in high numbers.)
And what type of teacher knowledge matters to student learning? It turns out to interact with past student achievement, as measured by standard math and reading tests.
The graph shows gains in student knowledge, separated by items for which teachers have (or lack) various types of knowledge. Filled circles are for students who scored well on a math and reading test (high achievers), and open circles are students who scored poorly (low achievers)
Look first at learning for concepts without a common misconception. If teachers have subject matter knowledge (SMK in the graph) students learn the concept better. In fact, low-achieving students learned nothing about a concept if teachers didn't know the concept themselves. High-achieving students did. The researchers speculate they may have learned the content from a textbook or other source.
For the strong misconception items, the low-achieving students learned very little, whatever the teacher knowledge. For high-achieving students, knowledge mattered, and they were most likely to learn when their teacher had both subject-matter knowledge and knew the misconceptions their students likely held (KoSM in the graph).
So the overall message is not that surprising. Students learn more when their teachers know the content, and when they can anticipate student misconceptions.
Somewhat more surprising (and saddening), low-achieving students are especially vulnerable when teachers lack knowledge. High-achieving students are more resilient.
There are limitations to this study, the most notable being that the sample is far from random (teachers were volunteers), and that the test was zero-stakes for all.
The strength was the direct measure of both types of knowledge, and that the researchers could examine the relationship of knowledge to performance at the level of individual items. One hopes we'll see more studies using this type of design.
Sadler, P. M., Sonnert, G., Coyle, H.P., Cook-Smith, N., & Miller, J.L. (2013) Student learning in middle school science classrooms. American Educational Research Journal, 50, 1020-1049.
We all know that most Americans don't read much. A recent poll
showed that a common reason they don't read is "lack of time." Fifty-one percent suggested that was a major factor that kept them from reading more books.It's tempting to
quote Sir John Lubbock: "In truth, people can generally make time for what they choose to do; it is not really the time but the will that is lacking.
" That's the line of thinking taken in this Atlantic blog,
noting that many of us spend plenty of time watching television. This line of argument is true enough, but probably won't help much. So without scolding, here are some ideas on how to think about reading and time differently.1) Don't assume that that you have to have a long block of time to read. Bit and pieces add up. If you think "I need at least thirty minutes of uninterrupted time to get into the book," well, try fitting reading into the bits and pieces of time in your day. You're ready to go out and your spouse isn't? There's five minutes. Long line in the grocery store? There's five minutes.
2) Be prepared
. To make use of these times, keep books in places where you find yourself with a few minutes. Bathroom. (Let's not deny it.) Kitchen (if you eat alone). Car (also useful when you're not driving, but at your destination. B. F. Skinner noted he read Thoreau's Walden
, which he kept in his glove box, in snippets when waiting for late-comers.) Get audio books for your commute.
3) The best preparation is on your phone
. It's not my favorite way to read, but you always have your phone with you. Get Kindle for your iPhone
. Reading emergencies--e.g., my kid was supposed to play but isn't and now I'm stuck watching other people's kids play pee-wee soccer--reading emergencies happen.
3) Don't assume that you can only read one book at a time
. If you've got books distributed in different spots, won't you get mixed up? Probably not. But if you are really worried about that, start with books that have lots of short stuff: Uncle John's bathroom reader
in the car, Chekhov short stories
in your purse, etc.
4) You don't you have to finish what you start.
For a long time I assumed that if I started a book I was in some way obligated to finish it. Or maybe that if I didn't, I had wasted my time in starting it. This attitude makes no sense. Don't fail to start a book because you're afraid it might turn out too challenging or emotionally hard, or whatever. If you don't like the book, abandon it.
5) No, seriously, I'm too busy.
When was the last time you were bored? If you really can't remember, then okay, you're too busy. If you can name a time, then you could have been reading instead of being bored.
In Why Don't Students Like School?
I pointed out that cognitive challenge is engaging if it's at the right level of difficulty, but boring if it's too easy or too hard. It sounds, then, like it would make sense to organize students into different classes based on their prior achievement. It might make sense cognitively, but the literature shows that
such a practice leads to bad outcomes for the kids in lower tracks. Those classes tend to have less demanding curricula and and lower expectations for achievement (e.g., Brunello & Checchi, 2007). Further, assignment to tracks is often biased by race or social class (e.g.,
Maaz et al., 2007).
What tracking does to students self-perceptions has been less clear. A new international study (Chmielewski et al., 2013) examined data from the 2003 PISA data set to examine the association of different types of tracking and student self-perceptions of mathematics self-concept. The authors compared
- Between school streaming: in which students with different levels of achievement are sent to different schools.
- Within school streaming: in which students with different levels of achievement are put in different sequences of courses for all subjects.
- Course-by-course tracking: in which students are assigned to more or less advanced courses within a school, depending on their achievement within a particular subject.
Controlling for individual achievement and the average achievement of the track or stream, the researchers found that course tracking
is associated with worse
self-perceptions among low-achieving students, but streaming
is associated with better
self-perceptions.This figure shows the difference between the self perceptions of higher and lower
achieving students in individual countries, sorted by the type of tracking system.
The data suggest that when students are tracked for some but not all of their courses, they compare their achievement to other, more advanced students, perhaps because they see these students more often. Students who are streamed within or between schools, in contrast, compare their abilities to their fellow stream-mates.
But why is there self-concept higher than higher-achieving students? This effect may be comparable to a more general phenomenon that people are poorer judges of their competence for tasks that they perform poorly. If you're not very good, you're not good enough to realize what you lack.
The authors do not suggest that between school steaming is the way to go (since it's associated with higher confidence). They note that the association is just the reverse of that seen in achievement: kids who stream between schools seem to take the biggest hit to achievement.
Brunello, G., & Checchi, D. (2007). Does school tracking affect equality of opportunity? New international evidence. Economic Policy, 22, 781–861.
Chmielewski, A. K., Dumont, H. Trautwein, U. (2013). Tracking effects depend on tracking type: An international comparison of students' mathematics self-concept. American Educatioal Research Journal, 50, 925-957.
Maaz, K., Trautwein, U., Ludtke, O., & Baumert, J. (2008). Educational transitions and differential learning environments: How explicit between-school tracking contributes to social inequality in educational outcomes. Child Developmental Perspectives, 2, 99–106.
If you follow education matters you know that the home environment in very early years are vital. One aspect of that home environment is the language infants and toddlers hear at home.
The groundbreaking work of Hart & Risley (1995; replicated by others, e.g. Huttenlocher et al, 2010) showed that socio-economic status of the parents is correlated with vast differences in the amount and complexity of language that children hear at home.
But what aspect of this speech is important? Does speech need to be directed to children? Perhaps all that’s needed is for children to be in the presence of this more complex language. After all, we know that children do not learn language via instruction; they learn it by observation.
Three studies published in the last couple of years build a convincing case that parents should, indeed, talk to their children. Talking in the presence of their children (but to others) does not confer the same vocabulary benefit.
In the most recent study (Weisleder & Fernald, 2013), experimenters tested 29 Spanish-learning infants at age 19 months. The children wore a small device that made an audio recording of all speech to which the child was exposed. The audio recordings were analyzed by software meant to differentiate speech directed toward the child versus speech audible to the child, but directed to others. A subset of recordings was coded by human observers to ensure the accuracy of the software.
Recordings of a full day’s speech were analyzed and the results showed a huge range in child-directed speech; caregivers in one family spoke over 12,000 words to the child whereas in another family that figure was just 670 words. The amount of child-directed speech as not significantly correlated (r = .17) with the amount of overheard speech.
At 24 months the productive vocabulary of the children was measured by asking the parents to judge words that they believed their child understood and words that their child used.
Of greatest interest, the amount of child-directed speech at 19 months was correlated (r = .57) with vocabulary at 24 months. The amount of overheard speech at 19 months was not (r = .25).
The sample size in this study is limited and there were some quirky features. (E.g., the software sorting “child-directed” vs. overherd speech is good, but not perfect.) But my confidence in the conclusion is bolstered by reports of the same finding from another lab, investigating speakers of other languages: English (Schneidman et al, 2013) and Yucatec (Schneidman & Goldin-Meadow, 2012).
Why must speech be directed to the child?
Weisleder & Fernald administered another task at 19 months meant to measure word processing efficiency. They speculated that the effect of child-directed speech on vocabulary was mediated through efficiency—something like, for example, the speed and accuracy with which the particular phonemes of the child’s language are processed.
This doesn’t fully explain the difference between child-directed and overheard speech. The obvious hypothesis is that other cues (e.g. eye gaze direction) prompt greater attention to speech that is child-directed, and that attention is necessary to build efficiency.
More details will have to await further research. For now, we can say with greater confidence “talk to your children” not just “talk in the presence of your children.”
Hart, B. M., & Risley, T. R. (1995). Meaningful differences in the everyday experience of young American children. Baltimore, MD: Brookes.
Huttenlocher, J., Waterfall, H., Vasilyeva, M., Vevea, J., & Hedges, L. V. (2010). Sources of variability in children’s language growth. Cognitive Psychology, 61, 343–365.
Shneidman, L. A., Arroyo, M. E., Levine, S., & Goldin-Meadow, S. (2013). What counts as effective input for word learning? Journal of Child Language, 40, 672–686.
Shneidman, L. A., & Goldin-Meadow, S. (2012). Language input and acquisition in a Mayan village: How important is directed speech? Developmental Science, 15, 659–673.
Weisleder, A. & Fernald, A. (2013). Talking to children matters: Early language experience strengthens processing and builds vocabulary. Psychological Science, DOI: 10.1177/0956797613488145
Ten people you may not have known were teachers.
1) John Adams
was not the only U.S. President to have taught school, but he was the first to have done so. After his graduation from Harvard, he became the master of the grammar school in Worcester, Massachusetts. Adams did not enjoy the post. He described his students as “little runtlings, just capable of lisping A, B, C, and troubling the master.”
2) Alexander Graham Bell
is best known to us as the inventor of the telephone, of course, but he had broad interests in sound, elocution, and speech. His mother and his wife were deaf, a significant factor in his experimentation with devices to improve hearing, culminating in the telephone. Bell taught at Susanna E. Hull’s private school for the deaf in London, working on his experiments in his spare time.
3) Gail Borden
was an inventor and businessman. In 1853 he applied for a patent for a method of removing 75% of the water from milk and adding sugar to what remained, a process that led to a stable shelf-life. Borden soon established a food company to sell his evaporated milk. It would become Borden foods with its recognizable mascot, Elsie the Cow. (The company went under in 2001, but many of it more popular products were bought out by other manufacturers). As a young man, Borden taught school for seven years in Amite County, Mississippi.
4) Levi Coffin
was an anti-slavery activist and is often referred to as the “President” of the underground railroad, which he supported financially and by using his home
in Fountain City, Indiana as a safe house for escaped slaves. As a young man, Coffin taught in a school for whites for several years in New Garden, North Carolina
. In 1821 he tried to open a school for black pupils, but local slave-holders forced its closure. He moved to Indiana three years later.
5) Robert Frost
may be the most beloved American poet, known for his depictions of New England rural life. After making a marginal living as a farmer, Frost taught English at the Pinkerton Academy
in Derry, NH
for five years. Doubtless from this experience, Frost offered many quotable thoughts on education, such as “There are two kinds of teachers: the kind that fill you with so much quail shot that you can’t move, and the kind that just gives you a little prod behind and you jump to the skies.”
6) Andy Griffith
is best known for his television roles on the Andy Griffith Show
, but he first made his name in 1953 with a big-selling comedic monologue, What it was, was football
. Before that first success Griffith was a high school music teacher in Goldsboro, North Carolina
. Curiously, other cast members from the Andy Griffith Show had similar pasts: George Lindsey
(“Goober”) was a high school history teacher in Huntsville Alabama
, and both Don Knotts
(“Barney Fife”) and Frances Bavier
(“Aunt Bee”) had intended to become teachers before being persuaded to give acting a try.
(7) Lyndon B. Johnson
is viewed, on the one hand, as a man of real compassion. Architect of “The Great Society,” he championed legislative programs for Civil Rights, for government-supported health care for the poor and elderly, increased support for education, and the “War on Poverty.” On the other hand, Johnson is also well known for a larger-than-life personality, and for being very tough when seeking support for his legislative goals. Both personality characteristics might have come in handy in his life as a teacher. Johnson taught at a segregated elementary school for children of Mexican descent in Cotulla Texas
in the late 1920s. He later taught public speaking at a high school in Houston
. Many of his biographers say that Johnson’s experience as a teacher had a profound impact on him. In a speech
given in 1965, Johnson said “I shall never forget the faces of the boys and the girls in that little Welhausen Mexican School, and I remember even yet the pain of realizing and knowing then that college was closed to practically every one of those children because they were too poor. And I think it was then that I made up my mind that this Nation could never rest while the door to knowledge remained closed to any American.”
(8) The reception of D. H. Lawrence’s
poems and novels was uneven during his lifetime, but most today view him as one of the great voices of modernism in the early 20th century, and certainly at the vanguard in the treatment of sexuality in the English novel. At the age of 23, Lawrence taught
at the Davidson Road elementary school in South London. A still undiscovered writer, he got much support from his fellow teachers, who loaned him books, read his work, and encouraged him. Some are thought to appear as characters in his novels.
(9) It is hard to believe that Gene Simmons
could have been a teacher. He is known best as the frontman for the 1970′s rock band Kiss
(right), known for outrageous shows during which Simmons would spit blood, breath fire, and taunt the audience. But Simmons did teach sixth grade
in Spanish Harlem. Simmons was reportedly fired for, among other things, replacing the Shakespearean play in the curriculum with Spiderman comics.
10. Carter G. Woodson
is commonly called the Father of Black History. Woodson graduated from Berea College
in 1900 and in 1912 was the first African-American of slave parentage to earn a PhD from Harvard University. Woodson believed that the history of Black America had been misrepresented and had not been the subject of serious study. To address the problem, in 1915 he co-founded the Association for the Study of Negro Life and History (later renamed the Association for the Study of African-American Life and History
). Woodson was an essential figure in bringing Black history academic credibility as well as popularity–he was also one of the founders of Black History Month. Woodson taught high school in Fayette county
while he attended Berea and was named Principal in his last year there. From 1903-1906 Woodson taught in the Philippines
while it was a U.S. protectorate, and taught High School again in Washington, D.C.
while working on his PhD dissertation in the Library of Congress.This blog was originally published at Britannica.com