Language acquisition is a labor of love, but it’s labor-intensive

Mother-baby synchrony shows the start of language acquisition [1]

Language acquisition depends on social contact

Children get their information about language from their caretakers and the adults around them. They tend to pick up on the most frequent nouns, verbs and adjectives first, and then extend their range. They attend to what is in the joint focus of attention for adult and child, to what is physically and conversationally present, and hence to the language directed to them as addressees.[2]

Infant attention… was significantly higher in response to the live person than to either inanimate source… During live exposure, tutors focus their visual gaze on pictures in the books or on the toys they talk about, and infants’ gaze tends to follow the speaker’s gaze… Infants in the live exposure sessions were visibly aroused before the sessions – they watched the door expectantly, and were excited by the tutor’s arrival, whereas infants in the non-social conditions did not.

Exposure to a new language in a live social interaction situation induces remarkable learning in 9-month-old infants, but no learning when the exact same language material is presented to infants by a disembodied source.[3]

Language acquisition is fostered by emotional expression

…infant-directed speech style reflects free vocal expression of emotion to infants, in comparison with more inhibited expression of emotion in typical adult-directed speech. …infant-directed speech is accompanied by exaggerated facial expressions of emotion…[4]

American infants exposed in the laboratory to Mandarin Chinese rapidly learned phonemes and words from the foreign language, but only if exposed to the new language by a live human being during naturalistic play. Infants exposed to the same auditory input at the same age and for the same duration via television or audiotape showed no learning…[5]

…infant-directed prosody itself is not special. What is special is the widespread expression of emotion to infants in comparison with the more inhibited expression of emotion in typical adult interactions.

…infants prefer to listen to infant-directed speech expressing positive (approval) affect over infant-directed speech expressing negative (prohibition) affect…[4]

Infants of nondepressed mothers readily learned that their mothers’ speech signaled a face, whereas infants of depressed mothers failed to learn that their mothers’ speech signaled the face. Infants of depressed mothers did, however, show strong learning in response to speech produced by an unfamiliar nondepressed mother.[6]

Language acquisition takes substantial labor and time

… a mother’s immediate social feedback results both in greater numbers and more mature, adultlike vocalizations from infants…

…infants vocally imitate adult vowel sounds by 5 months but not acoustically matched nonspeech sounds that are not perceived as human speech…

By 10 months… Children raised in Beijing listening to Mandarin babble by using tonelike pitches characteristic of Mandarin, which make them sound distinctly Chinese. Children being raised in Seattle listening to English do not babble by using such tones and sound distinctly American.[5]

Language acquisition labor changes, but the labor continues

Parents frequently check up on what their children mean. They often do this by reformulating with a side sequence or an embedded correction what they think their children said. Since the child’s utterance and the adult reformulation differ while the intended meanings are the same, children infer that adults are offering a correction. Analyses of longitudinal data from five children between 2;0 and 4;0… show that (a) adults reformulate their children’s erroneous utterances and do so significantly more often than they replay or repeat error-free utterances; (b) their rates of reformulation are similar across error-types (phonological, morphological, lexical, and syntactic) in both languages; (c) they reformulate significantly more often to younger children, who make more errors.[7]

At a conservative estimate, the average 5-year-old child will have learned more than 2,000 words… and will learn up to 3,000 more per year in the coming school years…[8]


  1. Melina, Remy. “” LiveScience, 23 Aug. 2011, www.livescience.com/15709-toddlers-understand-complex-grammar.html. Accessed 14 Oct. 2017.
  2. Clark, Eve V. “How language acquisition builds on cognitive development.” Trends in cognitive sciences 8.10 (2004): 472-478.
  3. Kuhl, Patricia K. “Is speech learning ‘gated’ by the social brain?” Developmental science 10.1 (2007): 110-120.
  4. Trainor, Laurel J., Caren M. Austin, and Renée N. Desjardins. “Is infant-directed speech prosody a result of the vocal expression of emotion?” Psychological science 11.3 (2000): 188-195.
  5. Meltzoff, Andrew N., et al. “Foundations for a new science of learning.” Science 325.5938 (2009): 284-288.
  6. Kaplan, Peter S., et al. “Infants of depressed mothers, although competent learners, fail to learn in response to their own mothers’ infant-directed speech.” Psychological Science 13.3 (2002): 268-271.
  7. Chouinard, Michelle M., and Eve V. Clark. “Adult reformulations of child errors as negative evidence.” Journal of child language 30.3 (2003): 637-669.
  8. Baddeley, Alan, Susan Gathercole, and Costanza Papagno. “The phonological loop as a language learning device.” Psychological review 105.1 (1998): 158-173.

Reading skill requires well-trained multilevel networks

Parsing four clauses, and forming connections, illustrating some component networks of reading skill

Parsing four clauses, and forming connections

Working memory keeps new information active for one to two seconds while it carries out the appropriate processes.

Reading skill requires well-trained networks for recognizing words

The most fundamental requirement for fluent reading comprehension is rapid and automatic word recognition… Amazing as it may seem, fluent readers can actually focus on a word and recognise it in less than a tenth of a second… Thus, four to five words per second even allows good readers time for other processing operations. Both rapid processing and automaticity in word recognition (for a large number of words) typically require thousands of hours of practice in reading.

Reading skill requires well-trained networks for parsing syntax

In addition to word recognition, a fluent reader is able to take in and store words together so that basic grammatical information can be extracted… to support clause-level meaning. Syntactic parsing helps to disambiguate the meanings of words that have multiple meanings out of context (e.g. bank, cut, drop).

Reading skill requires well-trained networks for assembling clauses

A third basic process that starts up automatically as we begin any reading task is the process of combining word meanings and structural information into basic clause-level meaning units (semantic proposition formation). Words that are recognised and kept active for one to two seconds, along with grammatical cueing, give the fluent reader time to integrate information in a way that makes sense in relation to what has been read before. As meaning elements are introduced and then connected, they become more active in memory and become central ideas if they are repeated or reactivated multiple times. Each semantic proposition reflects the key elements of the input (word and structure) and also highlights linkages across important units (in this case, verbs), where relevant. Semantic propositions are formed in this way and a propositional network of text meaning is created.

Reading skill requires forming networks connecting text

As clause-level meaning units are formed (drawing on information from syntactic parsing and semantic proposition formation), they are added to a growing network of ideas from the text. The new clauses may be hooked into the network in a number of ways: through the repetition of an idea, event, object or character; by reference to the same thing, but in different words; and through simple inferences that create a way to link a new meaning unit to the appropriate places in the network… As the reader continues processing text information, and new meaning units are added, those ideas that are used repeatedly and that form usable linkages to other information begin to be viewed as the main ideas of the text… they become, and remain, more active in the network. Ideas that do not play any further roles in connecting new information…, or that do not support connecting inferences, lose their activity quickly and fade from the network. In this way, less important ideas tend to get pruned from the network, and only the more useful and important ideas remain active.

Reading skill requires forming networks summarizing ideas

As the reader continues to build an understanding of the text, the set of main ideas that the reader forms is the text model of comprehension. The text model amounts to an internal summary of main ideas… Background knowledge… plays a supporting role and helps the reader anticipate the discourse organisation of the text…

Reading skill requires forming networks modeling narratives

At the same time…, the reader begins to project a likely direction that the reading will take. This reader interpretation (the situation model of reader interpretation) is built on and around the emerging text model. The ability of fluent readers to integrate text and background information appropriately and efficiently is the hallmark of expert reading in a topical domain (e.g. history, biology, psychology).

Reading skill requires controlling attention

…we know that an executive control processor (or monitor) represents the way that we focus selective attention while comprehending, assess our understanding of a text and evaluate our success. Our evaluation of how well we comprehend the text is dependent on an executive control processor.

Reading skill compacts multilevel information into working memory

…the many processes described here all occur in working memory, and they happen very quickly… Roughly, in each and every two seconds of reading, fluent readers:

  1. focus on and access eight to ten word meanings
  2. parse a clause for information and form a meaning unit
  3. figure out how to connect a new meaning unit into the growing text model
  4. check interpretation of the information according to their purposes, feelings, attitudes and background expectations, as needed
  5. monitor their comprehension, make appropriate inferences as needed, shift strategies and repair misunderstanding, as needed
  6. resolve ambiguities, address difficulties and critique text information, as needed [1]

  1. Grabe, William Peter, and Fredricka L. Stoller. Teaching and researching reading. 2nd ed., Routledge, 2011, pp. 13-23.

Industrial basic research brings practical problems to strong networks

Industrial basic research and industrial total R&D was performed in a few sectors by a few companies in the US in 1984

Industrial basic research and industrial total R&D was performed in a few sectors by a few companies in the US in 1984 [1, 2]

Industrial basic research plugs industry networks into universities

Most basic research in the United States is conducted within the university community, but in order to “plug in” to these research centers and to exploit the knowledge that is generated there, a firm must have some in-house capability. The most effective way to remain effectively plugged in to the scientific network is to be a participant in the research process.

When basic research in industry is isolated from the rest of the firm, whether organizationally or geographically, it is likely to become sterile and unproductive.

The history of basic research in industry suggests that it is likely to be most effective when it is highly interactive with the work, or the concerns, of applied scientists and engineers. This is because the high technology industries are continually throwing up problems, difficulties and anomalous observations that are most unlikely to occur outside of a high technology context.

High technology industries provide a unique vantage point for the conduct of basic research, but in order for scientists to exploit the potential of the industrial environment it is necessary to create opportunities and incentives for interaction with other components of the industrial world. …the performance of basic research may be thought of as a ticket of admission to an information network.

Industrial basic research often is the unplanned byproduct of paying talented people to work on great practical problems

…the history of basic research in… industry suggests that a very large part of this research has been unintentional.

…if… Sadi Carnot… had been asked… what he thought he was doing, his answer would have been that he was trying to improve the efficiency of steam engines. As a byproduct of that particular practical interest, he created the modern science of thermodynamics.

If Pasteur had been asked what he thought he was doing back around 1870, he would have replied that he was trying to solve some very practical problems connected with fermentation and putrefaction in the French wine industry. He solved those practical problems – but along the way he invented the modern science of bacteriology.

Industrial basic research at Bell Labs, for example, started with practical problems and ended up producing scientific advances

Back at the end of the 1920s when transatlantic radiotelephone service was first established, the service was poor because there was lots of static. Bell Labs asked a young man, Karl Jansky, to determine the source of the noise so that it could be reduced or eliminated. He was given a rotatable antenna to work with. Jansky published a paper in 1932 in which he reported three sources of noise: Local thunderstorms, more distant thunderstorms, and a third source. which he identified as “a steady hiss static, the origin of which is not known”. It was this “star noise”, as he labelled it, which marked the birth of radio astronomy…

…Bell Labs decided to support basic research in astrophysics because of its relationship to the whole field of problems and possibilities in microwave transmission, and especially the use of communication satellites for such purposes. It turned out that, at very high frequencies, rain and other atmospheric conditions became major sources of interference in transmission. This source of signal loss was a continuing concern in the development of satellite communications. It was out of such practical concerns that Bell Labs decided to employ Arno Penzias and Robert Wilson. Penzias and Wilson… first observed the cosmic background radiation, which is now taken as confirmation of the “big bang” theory of the formation of the universe, while they were attempting to identify and measure the various sources of noise in their antenna and in the atmosphere. Although Penzias and Wilson did not know it at the time, the character of the background radiation that they discovered was just what had been postulated earlier by cosmologists favoring the “big bang” theory. Penzias and Wilson appropriately shared a Nobel Prize for this finding.

Industrial basic research at Bell Labs also started with practical problems and ended up producing practical advances

…basic research can provide valuable guidance to the directions in which there is a high probability of payoffs to more applied research. In this sense, William Shockley’s education in solid state physics during the 1930s may have been critical to the decision at Bell Labs to look for a substitute for the vacuum tube in the realm of semiconductor materials – a search that led directly to the invention of the transistor.[2]


  1. National Science Foundation. National Patterns of Science and Technology Resources 1986. NSF 86-309. 1986, pp. 59, 56.
  2. Rosenberg, Nathan. “Why Do Firms Do Basic Research (with Their Own Money)?” Research Policy 19.2: 165-174.

IT-enabled process improvements increase productivity 7 ways

Cost breakdown of initial projects to implement new information technology in large manufacturing firms, the start of developing IT-enabled process improvements.

Cost breakdown of initial projects to implement new information technology in large manufacturing firms. The IT investment is just a part, and the total project is just a part, of developing IT-enabled process improvements.

IT-enabled process improvements show that IT is a general-purpose technology

…criteria for a general-purpose technology…

  • wide scope for improvement and elaboration
  • applicability across a broad range of uses
  • potential for use in a wide variety of products and processes
  • strong complementarities with existing or potential technologies.

…David… described the invention of the dynamo and its effect on the organization of the factory. …decades passed before factories reorganized themselves internally and made truly significant productivity gains possible.

Bresnahan and Trajtenberg… developed a model of the use of semiconductors as a general-purpose technology, characterized by “pervasiveness, inherent potential for technical improvements, and ‘innovational complementarities’”… On one level, computing invention-possibility can make existing processes run faster.

…a more exciting use of computing would be to push out the frontier. Computing can change the way business is done. …we believe that there are decades’ worth of potential innovations to be made by creatively combining inventions that we already have in creative ways.

IT-enabled process improvements use hard-to-value capabilities to generate, in part, hard-to-value results

…the literature agrees on one basic point: the size of the total stock of intangible capital in the United States is very large—as much as several trillion dollars. Often this capital does not show up in balance sheets or economic figures, either in government accounts or as an item in firm-level balance sheets.

If we used consumer surplus data to examine the effects of technological innovation over the decades, we would find hundreds of billions, perhaps trillions of dollars of unmeasured benefits in the economy.

Although decreasing communications costs have been affecting incentives for innovation for centuries, free and perfect copies that are easy to distribute were never possible until recently. But the Internet, so far, has not killed innovation. Rather, it has created an entire generation of individual innovators. If history is any guide, the Internet will encourage vast amounts of innovation.

IT-enabled process improvements led by the United States are increasing productivity

…IT is playing an important role in the US productivity resurgence since 1995, and… something unique is occurring in the United States.

The further productivity acceleration since 2001 in the absence of substantial investments in IT remains a subject of debate in the literature. …our hypothesis is that firms benefited from the organizational capital that they built at the end of the 1990s. That is, there may be a lag of approximately 3 or 4 years before the process improvements to IT appear in the productivity statistics.

Major empirical and case studies from the period 1995– 2008 point to business-process reorganization as a major factor in explaining productivity differences across plants or firms.

IT-enabled process improvements have come from seven practices

…the firms that simultaneously invested in IT and in the practices did disproportionately better than firms that did only one or the other. In other words, the practices are complementary to IT investment.

  1. Move from analog to digital processes
    Moving an increasing number of processes into the paperless, digital realm…
  2. Open information access
    Digital organizations… encourage the use of dispersed internal and external information sources.
  3. Empower the employees
    Digital organizations decentralize authority—pushing decision rights to those with access to information.
  4. Use performance-based incentives
    Meritocratic pay structures, incentive pay for individuals and groups, and stock options are common at digital organizations.
  5. Invest in corporate culture
    Part of making productive use of IT is to define and promote a cohesive set of high-level goals and norms that pervade the company.
  6. Recruit the right people
    The fact that technology gives employees more information and authority implies that such employees need to be more capable…
  7. Invest in human capital
    …digital organizations provide more training… Many of the changes… call for increased levels of thinking and ingenuity on the part of employees.[1]

  1. Brynjolfsson, Erik, and Adam Saunders. Wired for innovation: how information technology is reshaping the economy. MIT Press, 2009.

Learn easier by planning better, and thinking harder

Think about the same problem repeatedly and you learn less. Think about different problems in-between and you learn easier. To learn easier, think harder.

Think about the same problem repeatedly and you learn less.
Think about different problems in-between and you learn easier.

To learn easier, think harder.

Learn easier by knowing your capabilities better

One reason to make things difficult while studying is that making things too easy leads to overconfidence, which in turn leads students to stop studying too soon. Students should actively avoid overconfidence, especially students who have a pattern of doing worse on exams than they expected:

  1. Test yourself.
  2. Consider what could go wrong on a test.
  3. Think about what you don’t know.

Ironically, students also tend to be underconfident in their ability to learn and improve, and so if you are a student who is discouraged by how difficult the material is, you might benefit if you:

  1. Remember if you are prone to underestimating your capacity for learning.

Learn easier by planning better

There are also ways to overcome another huge problem for studiers, the planning fallacy:

  1. Break the task down into elements and consider how long each subtask will take.
  2. Consciously estimate that everything will take twice as long as you think it will take.

Procrastination is a huge hurdle to effective studying. Advice that one should avoid procrastination is easy to find (e.g., Benjamin Franklin: “Don’t put off until tomorrow what you can do today,”) but advice on how to do so is difficult to come by. Research suggests that there are ways of decreasing procrastination:

  1. Increase expectancy of success.
  2. Set appropriate and achievable subgoals.
  3. Form predictable work habits that essentially make the decision that it is time to work for you.

Learn easier by learning to think harder

With respect to how to study, our most general advice is this:

  1. Struggle while thinking.
    Easy studying is often ineffective.
  2. Do not try to take shortcuts on the path to knowledge.
  3. Make it as easy as possible to think hard.
    Avoid pitfalls such as trying to study in a situation that leads to too much distraction.

We have already alluded to multiple productive ways to make things difficult.

  1. Summarize notes during a lecture.
    Don’t transcribe notes during a lecture.
  2. Ask yourself questions while studying.
  3. Simulate test conditions by quizzing yourself and see if you really know the answers.
    Don’t go over the answers and decide that you know them—which is easy when they are right in front of you.
  4. Space repeated study sessions apart in time to allow forgetting.
  5. Return to restudy information that seemed well-learned at one point but might have been forgotten.

These strategies have dual benefits: They enhance learning, and they make self-monitoring more accurate.

Learn easier by learning longer

Studying more is not effective unless one is smart about how to study. We have tried to explain how students can become smarter studiers. Making bad choices about how to study can be akin to pedaling a stationary bike: You put in effort but you go nowhere. Making bad choices about what and when to study can be like riding in the wrong direction (what) or starting a race at the wrong time (when). Our goal in this chapter is to point studiers in the right direction and give them a faster bike.

There is one last piece of advice, and it is the most obvious of all: The more time you spend riding, the farther you get—and the same is true of studying:

  1. Learn to study efficiently.
  2. Study a lot.

Distance = rate × time, and learning = efficiency × time.

If you end up accomplishing your goals and have free time afterward:

  1. Study some more.

Learn easier

learning = efficiency × time

  1. Test yourself.
  2. Consider what could go wrong on a test.
  3. Think about what you don’t know.
  4. Remember if you are prone to underestimating your capacity for learning.
  5. Break the task down into elements and consider how long each subtask will take.
  6. Consciously estimate that everything will take twice as long as you think it will take.
  7. Increase expectancy of success.
  8. Set appropriate and achievable subgoals.
  9. Form predictable work habits that essentially make the decision that it is time to work for you.
  10. Struggle while thinking.
    Easy studying is often ineffective.
  11. Do not try to take shortcuts on the path to knowledge.
  12. Make it as easy as possible to think hard.
    Avoid pitfalls such as trying to study in a situation that leads to too much distraction.
  13. Summarize notes during a lecture.
    Don’t transcribe notes during a lecture.
  14. Ask yourself questions while studying.
  15. Simulate test conditions by quizzing yourself and see if you really know the answers.
    Don’t go over the answers and decide that you know them—which is easy when they are right in front of you.
  16. Space repeated study sessions apart in time to allow forgetting.
  17. Return to restudy information that seemed well-learned at one point but might have been forgotten.
  18. Learn to study efficiently.
  19. Study a lot.
  20. Study some more.[1]

  1. Kornell, Nate, and Bridgid Finn. “Self-regulated learning: An overview of theory and data.” The Oxford Handbook of Metamemory, edited by John Dunlosky and Sarah (Uma) K. Tauber, Oxford University Press, 2016, pp. 325-340.

People grow alike naturally, as the people with less power change

A little girl looks at her mom, showing one big way that people grow alike naturally

A little girl looks at her mom, showing one big way that people grow alike naturally [1]

People grow alike temporarily while they’re together

…people in close relationships become more similar to each other over time. For example, relationship partners converge in their values and attitudes, verbal and social skills, cognitive complexity and mental abilities, eating and drinking habits, and perceptions of others.

People express emotion through facial, vocal, and postural behavior, and quickly and automatically detect and interpret the emotional expressions of others.

Moreover, people are quite susceptible to the social transmission of emotion. Research on emotional contagion has shown that people automatically mimic facial expressions, vocalizations, and postures when they interact with another person, which leads both individuals to experience similar emotions. Studies of empathy find that people take the perspective of others and vicariously feel the emotions that the other person feels.

People grow alike over time emotionally

In the present study, we ask: Do relationship partners also converge emotionally over time?

The development of emotional similarity would benefit relationships in at least three ways. First, because emotions are modes of relating to the environment, emotional similarity would coordinate relationship partners’ thoughts and behaviors and help them respond to potential opportunities or threats. Second, when two people feel similar emotions, they more accurately perceive each other’s intentions and motivations. Third, emotional similarity would be reinforcing to relationship partners; when two people feel similar emotions, their own feelings and appraisals are validated.

…our three studies offer strong evidence that emotional convergence does occur…

…the current research shows how emotions help individuals build and maintain long-term, intimate relationships. Our research shows that close relationships shape emotional responses in fundamental ways. We become emotionally similar, both in experience and display, to those people with whom we are intertwined.

People grow alike in ways that help the relationship

…we hypothesized that emotional similarity would benefit close relationships. The evidence for this hypothesis was strong and consistent across studies.

…this similarity would help coordinate the thoughts and behaviors of the relationship partners, increase their mutual understanding, and foster their social cohesion.

…relationships whose partners were more emotionally similar were more cohesive and less likely to dissolve.

People grow alike regardless of whether the changes help them personally or hurt them personally

…our findings shed light on processes by which relationship partners “transmit” emotional disorders such as depression or anxiety. For example, children of depressed parents are often themselves depressed, and individuals who live with a depressed person can become depressed. The social transmission of emotion may not be limited to clinical levels of emotionality, or even limited to negative emotion. The transmission of emotional disorders can now be understood as a special case of a much broader and inherently normal emotion process in close relationships.

…emotional convergence may be due to a convergence in appraisal styles. Ways of appraising events lead to specific emotions, just as specific emotional dispositions lead to ways of appraising social events. For example, people who view an event as uncontrollable and dangerous tend to experience fear in response to that event. When individuals become close, they might converge in appraisal styles, which in turn leads to greater similarity in emotional responses. Consistent with this idea, close friends are similar in the cognitive dimensions they use to describe themselves and others.

The people with less power change the most

…relationship partners with less power made more of the change necessary for convergence to occur.

These findings paint a striking picture of the emotional lives of powerful and powerless people. The emotional lives of low-power individuals… seem more variable, changing across relationship contexts.[2]


  1. “Child & Parent Place (CAPP).” www.lutherwood.ca/mentalhealth/capp. Accessed 29 May 2017.
  2. Anderson, Cameron, Dacher Keltner, and Oliver P. John. “Emotional Convergence Between People Over Time.” Journal of Personality and Social Psychology 84.5 (2003): 1054-1068.

Efficient peer teaching, starting in India, brought literacy to the modern world

A child who’s a little older teaches two other children, demonstrating efficient peer teaching[1]

A child who’s a little older teaches two other children, demonstrating efficient peer teaching

Efficient peer teaching was described in India in 1623

Peter Della Valle in 1623… “entertained himself in the porch of the Temple, beholding little boys learning arithmetic after a strange manner.” The method used a combination of four children gathered together “singing musically” to help them remember their lessons, and writing number bonds in the sand, “not to spend paper in vain . . . the pavement being for that purpose strewed all over with fine sand.” In the same way, they were taught reading and writing.

Peter Della Valle asked them, “If they happen to forget or be mistaken in any part of the lesson, who corrected them and taught them?” They said they all taught each other, “without the assistance of any Master.” For, “it was not possible for all four to forget or mistake in the same part, and that they thus exercised together, to the end, that if one happened to be out, the other might correct him.” It was, wrote the explorer, “indeed a pretty, easy and secure way of learning.”

…the “conditions under which teaching took place in the Indian schools were less dingy and more natural” than in Britain.

“When the whole are assembled, the scholars according to their numbers and attainments, are divided into several classes. The lower ones of which are placed partly under the care of monitors, whilst the higher ones are more immediately under the superintendence of the Master, who at the same time has his eye upon the whole schools. The number of classes is generally four; and a scholar rises from one to the other, according to his capacity and progress.”

Efficient peer teaching was learned in India by British Rev. Dr. Andrew Bell around 1787

Rev. Dr. Andrew Bell… arrived in India in 1787… to teach the abandoned progeny of British soldiers and native women. He found that the (expatriate) teachers in the asylum “had no knowledge of their duties, and no very great love for them.”

But then he had his moment of insight: “One morning, in the course of his early ride along the surf-beaten shore of Madras, he happened to pass a… school, which, as usual with Indian schools, was held in the open air. He saw the little children writing with their fingers on sand, which, after the fashion of such schools, had been strewn before them for that purpose.” He also saw them peer teaching, children learning from one another rather than from their masters. “He turned his horse, galloped home, shouting, ‘Heureka! Heureka!’ and now believed that he… saw his way straight before him.”

Bell first tried an experiment. He got one of the older boys who knew his alphabet to teach one of the classes that “the master had pronounced impossible” to teach. But this boy managed to teach the class “with ease.” Bell appointed him the class’s teacher. “The success exceeded expectation. This class, which had been before worse, was now better taught, than any other in the school.” He tried it in other classes, and it worked again. So Bell sacked all his teachers, and the school “was entirely taught by the boys” under his supervision.

Efficient peer teaching, popularized by Dr. Bell in London in 1797, rapidly boosted literacy in Britain

Bell returned to London in 1797 and published the description of his “Madras Method.” Following that, he was in great demand to introduce the system in British schools. First was St. Botolph’s, Aldgate in East London, followed swiftly by schools in the north of England.

…Joseph Lancaster, who created the famed Lancastrian schools across Britain—and with whom Bell was to have a furious dispute about who really invented the system— introduced peer learning in his first London school, in Borough Road, in 1801.

[Bell’s] method was adopted by the new National Society for the Education of the Poor in 1811.

…James Mill, father of John Stuart Mill, wrote in the October 1813 Edinburgh Review: “From observation and inquiry… we can ourselves speak decidedly as to the rapid progress which the love of education is making among the lower orders in England. Even around London, in a circle of fifty miles radius, which is far from the most instructed and virtuous part of the kingdom, there is hardly a village that has not something of a school; and not many children of either sex who are not taught more or less, reading and writing.”

How were such schools funded? Predominantly, it turns out, through school fees. These were very much private schools for the poor, in Victorian England. Mill noted: “We have met with families in which, for weeks together, not an article of sustenance but potatoes had been used; yet for every child the hard-earned sum was provided to send them to school.”

By 1821, 300,000 children were being educated under Bell’s principles.

Efficient peer teaching, described further by Dr. Bell in 1823, rapidly spread across the world

As it became widely emulated, Bell was asked to write an extended outline of the system, which he published in 1823. His ideas were adopted around Europe, and as far away as the West Indies and Bogotá, Colombia; the educational reformer Pestalozzi was apparently even using the Madras Method.

The system transformed education in the Western world and was arguably the basis by which mass literacy in Britain was achieved. But in its fundamental, “economical” principles, it…was based precisely on what the Rev. Dr. Andrew Bell had observed in India.

For England and Wales… “When the government made its debut in education in 1833 mainly in the role of subsidiser it was as if it jumped into the saddle of a horse that was already galloping.”


  1. “Peer teaching at the Marlboro Montessori Academy.” 30 Sept. 2014, marlboromontessori.blogspot.com/2014/09/peer-teaching-at-marlboro-montessori.html. Accessed 30 Apr. 2017.
  2. Tooley, James. The Beautiful Tree: A Personal Journey Into how the World’s Poorest People are Educating Themselves. Cato Institute, 2009, Scribd pp. 330-348.

 

 

English-language expertise and peak skill take decades

Age at best publication vs. age at first publication shows that English-language expertise and peak use take decades

Age at peak skill vs. age at initial expertise for writers. Expert-to-peak averaged 11-13 years, and took up to 45 years.[1]

English-language expertise starts with years to proficiency

… even in two California districts that are considered the most successful in teaching English to limited-English-proficient students, oral proficiency takes 3 to 5 years to develop, and academic English proficiency can take 4 to 7 years.

This paper follows on precedent-setting research… estimates of up to 10 years before students are fully proficient in English, i.e., are fully competitive in the academic uses of English with their age-equivalent, native English-speaking peers.[2]

English-language expertise is not necessarily automatic

…the ‘compressed’ discourse style of academic writing is much less explicit in meaning than alternative styles employing elaborated structures. These styles are efficient for expert readers, who can quickly extract large amounts of information from relatively short, condensed texts. However, they pose difficulties for novice readers, who must learn to infer unspecified meaning relations among grammatical constituents.[3]

This article presents a case study of a nonnative-English-speaking scholar from Hong Kong and his experience in publishing a scholarly article in an international refereed journal on his return from doctoral study in the United States.

…Oliver had considerable exposure to English throughout his life. His first contact with the language was at kindergarten, when he was 3–4 years old. Following kindergarten, he went to an English-medium elementary school. After that he moved to an English-medium secondary school that was staffed primarily by Irish Jesuit priests. His undergraduate education was at a Hong Kong university that has a bilingual policy of teaching in Chinese or English. On graduation, he worked for a time. Later, for his MA and PhD, he moved to a major research university in the United States, where he had very little contact with non-English speakers either inside the university or outside, where he had friends in the local community, living for 2 years with an American family. Oliver said that he considered both Chinese and English as his mother tongue.

Oliver was lucky in that… the single reviewer of his submission had the skill to see a publishable article in a manuscript that two nonspecialists (the research assistant/local editor and I) were unable to envision and that had what the reviewer described as “second language mistakes that interfere with clarity and obscure meaning”… The in-house editor did an aggressive job, cutting the paper from 43 pages to 29. Entire paragraphs were removed, and virtually every sentence was rewritten.[4]

English-language expertise and peak skill take decades

Most children these days are being taught grammar and are given creative writing assignments as early as Elementary school… …in our sample… it is certainly plausible that they started writing creatively at age 10. The average age in which any writer in our sample produced their first work is 32.8 years. The average age at which any writer in our sample produced their “best” work is 43.4.[1]

‘It took me fifteen years to discover I had no talent for writing, but I couldn’t give it up because by that time I was too famous.’—Robert Benchley [5]

In our sample of writers, it took an average of 10.6 or 12.8 years (depending on whether you exclude those whose best work was also their first work) to produce a “masterpiece” of fiction once they had started publishing. Since our sample included contemporary writers, mostly still living, there is still a good chance that the writer’s “best” work has yet to been produced, which would only increase our overall mean. According to Simonton (1997), the average peak year for novelists is 27.1 years into their career…

…many of the skills required to become an expert in literature (i.e., constructing a problem representation, goal setting, planning, etc.) are also required of any task in which people are trying to extend themselves or to achieve a novel or superior result.[1]

In many fields, English-language expertise and peak skill are only just a start

The most frequently reported outside ability for scientists is that of verbal ability… When disabilities are mentioned, however, disabilities in language are named for scientists…[6]

…it is quite possible that writers might require less time for expertise acquisition than other domains. It has been suggested… that the greater the knowledge base of a domain, the more formal knowledge is required for truly innovative work within it.[1]


  1. Kaufman, Scott Barry, and James C. Kaufman. “Ten years to expertise, many more to greatness: An investigation of modern writers.” The Journal of Creative Behavior 41.2 (2007): 114-124.
  2. Hakuta, Kenji, Yuko Goto Butler, and Daria Witt. “How Long Does It Take English Learners to Attain Proficiency?” The University of California Linguistic Minority Research Institute Policy Report 2000-1 (2000).
  3. Biber, Douglas, and Bethany Gray. “Challenging stereotypes about academic writing: Complexity, elaboration, explicitness.” Journal of English for Academic Purposes 9.1 (2010): 2-20.
  4. Flowerdew, John. “Discourse community, legitimate peripheral participation, and the nonnative-English-speaking scholar.” TESOL quarterly 34.1 (2000): 127-150.
  5. Kaufman, James C., and Claudia A. Gentile. “The will, the wit, the judgement: The importance of an early start in productive and successful creative writing.” High Ability Studies 13.2 (2002): 115-123.
  6. Raskin, Evelyn. “Comparison of scientific and literary ability: a biographical study of eminent scientists and men of letters of the nineteenth century.” The Journal of Abnormal and Social Psychology 31.1 (1936): 20-35.

Nonfiction narratives help us see how new information fits together

A storyteller’s hands grasp an unseen object, illustrating nonfiction narratives, which are complex and embedded
[1]

Nonfiction narratives give us the stories we crave

…when I read the best analytic writing… it often feels like a story to me. The writing unfolds. I enjoy the playing out of ideas and positions, the ways they conflict, the ways questions are raised and explored—the way they are narrated. All of these writers are masters of the embedded story that grounds any point in live experience, which gives it what rhetoricians call presence.

So here is my modest proposition—that narrative is the deep structure of all good writing. All good writing. “Narrative imagining—story—is the fundamental instrument of thought. Rational capacities depend on it. It is our chief means of looking into the future, of predicting, of planning, of explaining”…even research reports must tell a story.

We never really read for raw information. We can’t.

So-called “informational texts” work only when the writer has been able to establish a set of expectations to drive the reading. This frame stabilizes the reading, gives it purpose, provides a pattern to place the “information” in.

Nonfiction narratives are journeys we take with the writers

Reading, as I am describing it, is not a treasure hunt for the main idea; it is a journey we take with a writer.

Extended informational writing is mediated by a teller; someone is guiding us through facts, theories, or perspectives. We can sense his or her cognitive energy, the fascination with the topic, the delight in the odd and unexpected fact, the sense of irony or humor that leavens even writing on the most serious topics. There is a relationship, a trust even.

When, in the name of pure objectivity, these traits are withheld (usually the case with textbooks), we have difficulty reading; the writing is called academic, synonymous, in the public mind at least, with dullness. Or to use a term from the field of reading, these texts are inconsiderate.

Nonfiction narratives aren’t like textbooks

Whenever I raise the question of comprehending nonfiction, someone asks, How will your ideas help students read textbooks? The short answer is, they won’t.

Textbooks are not read—that is, they do not require sustained attention to the development of an idea, the kind of reading that it might take to read an essay in The Atlantic or a professional research article.

Take, for example, a standard high school text like Biology (Biggs, Glencoe/McGraw-Hill, & National Geographic Society, 2007), which weighs in at a hefty 6.2 pounds. For all its bulk, students are rarely asked to read more than three paragraphs before a text break or a new topic occurs. The writing itself seems geared for presenting terminology (all bolded) rather than for engaging a reader. Two or three terms are introduced per page, for a total of approximately 1,500 terms for the entire book. The pages are extraordinarily busy, with sidebars, photos, and diagrams, all distracting in a People Magazine sort of way. So what we have is essentially a dictionary with elaborated definitions.

Nonfiction narratives embed tensions and resolutions that embed information

In the classification schemes of the most respected literacy educators… informational reading is “efferent” and functional, a carrying away, in this case, of information.

Take, for example, Siddhartha Mukherjee’s The Emperor of All Maladies: A Biography of Cancer… What I got was the experience of being with the author as he led me through the cycles of hope and defeat, the carnage of so many patients in such grueling trials, and the hesitant but steady progress of researchers. I retain the sensation of cancer itself becoming the main character of the book—evasive, adaptive, persistent, multiple, an adversary of extraordinary wiliness and devastation. I retain these narrative contours—and the information I retain adheres to them.

…to be taken into a book like The Emperor of All Maladies is to move outside ourselves and to be present as a first-rate mind explains the science and human drama of cancer research.

These writers never leave narrative far behind. Instead, they use narrative in more complex and embedded ways.[2]


  1. “stories. for grownups.” PatSpalding.com. Accessed 11 Mar. 2017.
  2. Newkirk, Thomas. “How We Really Comprehend Nonfiction.” Educational Leadership 69.6 (Mar. 2012): 29-32.

Serving customers best requires radical innovation

Paths from market orientation to new product success illustrate that serving customers best requires radical innovationThree market orientation–learning style–innovation–new product success paths.

Market orientation is expected to be positively related to generative learning (1)
and negatively related to gleaning (3)
but is not expected to be related to adaptive learning (2)…

Serving customers best still takes incremental innovation

…market orientation may be characterized as ‘‘ pervasive commitment to a set of processes, beliefs, and values reflecting the philosophy that all decisions start with the customer and are guided by a deep and shared understanding of customers’ needs and behavior, and competitors’ capabilities and intentions, for the purpose of realizing superior performance by satisfying customers better than competitors’’…

Although market-oriented firms are expected to be adept at adaptive learning inspired incremental innovation,… it is expected that this will also be true of most firms regardless of their market orientation.

Typically, innovation takes the form of brand or line extensions, modifications to existing products, or repositionings. There is a comfort to the learning and innovation that takes place in this mode because organizational members are not questioning the successes of the past. They are merely improving on them.

Although the results show that this type of innovation is the most common and least variable in the sample of firms, they also show that it is not related to market orientation. Incremental innovation was the most common form of innovation in firms. The priority firms place on it, however, was not related to new product success.

Serving customers best requires more radical innovation, and less imitation

In general, radical innovations have greater value to firms than incremental innovations, particularly when radical innovators have deep pockets and strong market power… New product concepts have greater value than line extensions… and technological breakthroughs are more profitable than incremental improvements… [Researchers] reported… product advantage and product innovativeness—two correlates of radical innovation—to be strongly related to new product success. Radical innovation priority was positively related to new product success; imitation priority was negatively related to new product success.

Market orientation had a direct positive relationship with new product success. Market orientation also had a positive indirect influence on new product success through generative-learning-inspired radical innovation and a negative indirect influence on new product success through gleaning-inspired imitation. Market orientation had no influence on firms’ adaptive learning priority or incremental innovation priority.

Overall, the results suggest that market orientation shifts the weight of a firms innovation programs away from imitation toward a balance between incremental and radical innovation.

Relative priorities of firms by market orientation, showing that serving customers best requires radical innovation

Serving customers best requires new learning and experimenting

Maximal long-term success requires a two-pronged innovation strategy.

In the short run, firms must remain competitive and alluring by engaging in incremental improvements that appeal to their customer base. These types of innovations can be discovered and prioritized by talking to customers and by monitoring competitors through traditional marketing research and intelligence activities.

In the long run, however, the most successful firms accompany adaptive modifications to the marketing mix with framebreaking initiatives. …long-term market leaders must innovate relentlessly and must be willing to cannibalize their own products to maintain their leadership position. These initiatives must be proactive and planned and must encourage employees to be selectively destructive (e.g., to identify and undo the obsolete). Although short-run incremental innovation programs can be linked explicitly to deadlines, budgets and outcome measures (e.g., ROI), longer-run destructive programs are not likely to produce results in a linear manner. As a result, they may best be pursued offline.

…a strong market orientation appears to be a key to the ability of firms to balance incremental and radical innovation programs. Prior research has also identified learning orientation as a key element of this process.

Managers should strive to improve their market and learning orientations by diagnosing their performance on each and benchmarking progress relative to exemplar firms.

In addition, long-run radical innovation requires firms to foster the motivation, opportunity, and ability to implement change…; in other word culture is key…

  • Motivation can be instilled by a reward system that makes experimentation and failure psychologically safe and the maintenance of the status quo psychologically unsafe.
  • Opportunity requires that employees be given the money, time, and voice to engage in change related behaviors.
  • Ability requires firms to hire the right type of people: ‘‘Individuals with low needs for uncertainty avoidance, high tolerance for ambiguity and the lust to experiment should be recruited for decision-makers’’…

  1. Baker, William E., and James M. Sinkula. “Does market orientation facilitate balanced innovation programs? An organizational learning perspective.” Journal of product innovation management 24.4 (2007): 316-334.