The Alliance for Excellent Education has issued a 77-page meta-analysis of experimental and quasi-experimental research, the Writing Next Report (via Anne Davis), and have come up with the following recommendations for writing instruction:

Eleven Elements of Effective Adolescent Writing Instruction

1. Writing Strategies, which involves teaching students strategies for planning, revising, and editing their compositions
2. Summarization, which involves explicitly and systematically teaching students how to summarize texts
3. Collaborative Writing, which uses instructional arrangements in which adolescents work together to plan, draft, revise, and edit their compositions
4. Specific Product Goals, which assigns students specific, reachable goals for the writing they are to complete
5. Word Processing, which uses computers and word processors as instructional supports for writing assignments
6. Sentence Combining, which involves teaching students to construct more complex, sophisticated sentences
7. Prewriting, which engages students in activities designed to help them generate or organize ideas for their composition
8. Inquiry Activities, which engages students in analyzing immediate, concrete data to help them develop ideas and content for a particular writing task
9. Process Writing Approach, which interweaves a number of writing instructional activities in a workshop environment that stresses extended writing opportunities, writing for authentic audiences, personalized instruction, and cycles of writing
10. Study of Models, which provides students with opportunities to read, analyze, and emulate models of good writing
11. Writing for Content Learning, which uses writing as a tool for learning content material

The report notes that these 11 elements are,

effective for helping adolescent students learn to write well and to use writing as a tool for learning. [However] ... even when used together, they do not constitute a full writing curriculum.

The report adds this qualifer because, as they note, there may be effective strategies that have not yet been studied.

Grammar Instruction
The controversial topic of grammar instruction is also touched upon:

Grammar instruction in the studies reviewed involved the explicit and systematic teaching of the parts of speech and structure of sentences.The meta-analysis found an effect for this type of instruction for students across the full range of ability, but surprisingly, this effect was negative.This negative effect was small, but it was statistically significant, indicating that traditional grammar instruction is unlikely to help improve the quality of students’ writing. Studies specifically examining the impact of grammar instruction with low-achieving writers also yielded negative results ... However, other instructional methods, such as sentence combining, provide an effective alternative to traditional grammar instruction, as this approach improves students’ writing quality while at the same time enhancing syntactic skills. In addition, a recent study (Fearn & Farnan, 2005) found that teaching students to focus on the function and practical application of grammar within the context of writing (versus teaching grammar as an independent activity) produced strong and positive effects on students’ writing. Overall, the findings on grammar instruction suggest that, although teaching grammar is important, alternative procedures, such as sentence combining, are more effective than traditional approaches for improving the quality of students’ writing.

Most of the studies analyzed in this report looked at L1 students. However, decontextualized grammar instruction without frequent feedback is also unlikely to have a positive effect for L2 students. A while back, I noted that on the related topic of error feedback (see links below) to acquire competence in any field, extensive practice accompanied by appropriate feedback was necessary. It seems unlikely that grammar should be the lone exception.

Alternative Methods of Grammar Instruction
Perhaps grammar instruction/practice/feedback could become more effective if we were to design it along the lines of those 11 elements. For a beginning point, suppose we reorient some of those 11 elements toward grammar:

1. Writing Strategies that teach students strategies for editing their grammar
2. Summarization, which involves explicitly and systematically teaching students how to explain and summarize grammar's rhetorical effects
3. Collaborative Writing, which uses instructional arrangements in which adolescents work together to plan grammatical choices and edit their compositions
4. Specific Product Goals, which assigns students specific, reachable goals for the grammar they need to acquire
5. Word Processing, which uses computers and word processors as instructional supports for checking spelling and grammar
6. Study of Models, which provides students with opportunities to read, analyze, and emulate models of good grammar

One implementation of these elements can be found in the grammar logs recommended in Error Feedback: Practice. Grammar logs have specific grammar goals and models of the grammar points to be learned.

Theoretical Understanding of Grammar Instruction
Simply using these 11 elements, as even the report stated, is insufficient to design a "full writing curriculum." LIkewise, it's not enough to use them innovatively for grammar instruction without a theoretical understanding of why and how these 11 elements work. Along the lines of ACT-R Theory (see also Error Feedback: Theory), key elements of learning include:

1. time on task
2. the use of examples accompanied by explanation and understanding,
3. accurate diagnosis of the learning task and performance, and
4. feedback

It's easy to see from these elements why traditional grammar instruction doesn't work. Although it may use examples and explanations, students are not spending time on tasks integrating grammar into their writing (outside of fill-in-the-blank sentences) nor necessarily receiving appropriate feedback. In contrast, Writing Strategies, Summarization, Inquiry Activities, and Models of Study easily fit into these key elements of learning. Collaborative writing, however, is not always effective for learning. To be done appropriately, it needs to integrate accurate diagnosis and understanding of the task, along with feedback. Otherwise, collaborators can just as easily reinforce misunderstandings of grammar and writing. Word processing, because it can underline grammar and spelling questions, focuses students' attention on recurring errors, thus allowing for more diagnosis of the problem and encouraging more time on task.

The Writing Next Report is worth reading, and having a theoretical understanding of learning elements is important for integrating its recommendations effectively, whether for grammar instruction or other writing goals.

Error feedback posts

• Error Feedback in L2 Writing
• Error Feedback in L2 Writing: Scant Evidence
• Error Feedback: Theory
• Error Feedback: Skill Acquisition Theory
• Error Feedback: Motivation
• Error Feedback: Practice

Keith Burnett responded to my response on his preference for being a Guide on the Side as opposed to Sage on the Stage:

I’m both in different parts of the lesson. I think that many people assume that PowerPoint use implies Sage role, and I was trying to provide counterexamples.

That Burnett did well, and it's also clear that he plays both roles, choosing the role appropriate to a student's stage in the learning process.

Unlike Burnett, however, not everyone seems to understand that both roles are appropriate. If you google the words "sage stage guide side", you'll find more than a few links to titles saying "Guide on the side, not Sage on the stage." Here's a typical example from the Internet Time Group:

an instructor’s energy should be channeled to become the medium whereby the discovery of learning is facilitated in a student-centered environment. No longer a "sage on the stage, " the online instructor becomes a "guide on the side," helping others to discover and synthesize the learning material.

Discovery learning is simply re-inventing the wheel. The time spent in "discovering" could be better spent using the wheels that have already been designed.

Here's another one, an excerpt from an article in College English by Alison King:

In most college classrooms, the professor lectures and the students listen and take notes. The professor is the central figure, the "sage on the stage," the one who has the knowledge and transmits that knowledge to the students, who simply memorize the information and later reproduce it on an exam-often without even thinking about it. This model of the teaching- learning process, called the transmittal model, assumes that the student's brain is like an empty container into which the professor pours knowledge. In this view of teaching and learning, students are passive learners rather than active ones. Such a view is outdated and will not be effective for the twenty-first century, when individuals will be expected to think for themselves, pose and solve complex problems, and generally produce knowledge rather than reproduce it.

There's some truth in this perspective. We've all had classes in which we took notes, crammed for an exam, and regurgitated information on the exam. The problem, however, is that this is a caricature of lecturing. Not all lecturers assume that students are empty containers, and not all use lecture as their only mode of teaching. Interestingly, the same people who promote this perspective are often the same ones who give presentations in lecture mode at a conference.

Again from the excerpt:

According to the current constructivist theory of learning, knowledge does not come package in books, or journal, or computer disks (or professors' and students' heads) to be transmitted intact from one to another. Those vessels contain information, not knowledge. Rather, knowledge is a state of understanding and can only exist in the mind of the individual knower; as such, knowledge must be constructed--or re-constructed--by each individual knower through the process of trying to make sense of new information in terms of what that individual already knows. In this constructivist view of learning, students use their own existing knowledge and prior experience to help them understand the new material; in particular, they generate relationships between and among the new ideas and between the new material and information already in memory (see also Brown, Bransford, Ferrara, and Campione 1983; Wittrock 1990).

And again, we can say, yes, students construct their understanding and in terms of previous experience. However, this does not mean that they cannot "generate relationships" from the information in lectures to their own experiences. If lectures are "bad," so are books and any other "containers" of information.

When students are engaged in actively processing information by reconstructing that information in such new and personally meaningful ways, they are far more likely to remember it and apply it in new situations. This approach to learning is consistent with information-processing theories (e.g., Mayer 1984), which argue that reformulating given information or generating new information based on what is provided helps one build extensive cognitive structures that connect the new ideas and link them to what is already known. According to this view, creating such elaborated memory structures aids understanding of the new material and makes it easier to remember.

It's not clear that one way of engaging with new information is more likely to be remembered than another. This is an interpretation. Anderson and Schunn in their article "The implications of the ACT-R learning theory: no magic bullets" (pdf) note that it is much more likely that any better remembering is due to more "time on task" rather than the notion of self-constructing as opposed to learning from provided examples, and they write:

There are no magical properties conveyed upon a knowledge structure just because it was self-generated. If all things were equal it would be preferable to have children learn by generating the knowledge (due to the redundant encoding). However, because of difficulties of generation and dangers of misgeneration, things are not always equal and it can be preferable to tell the knowledge.

None of this is to oppose the "guide on the side" perspective. Rather, there is a time and place for being a sage and for being a guide. Repeating mantras is no more than educational indoctrination.

Jason, reporting about Mike O'Connell's article in the Chronicle of Higher Education, has a post worth reading on this issue and ends nicely on this note:

In short, I think we need to get beyond the “sage” and “guide” dichotomy, and use both for truly effective teaching. One cannot just impose a set teaching style when it doesn’t work. It behooves teachers at all levels to consider what really works (or what might really work), drawing upon the makeup of individual classes and individual students to make the course truly memorable and meaningful. Otherwise, we’re just playing with techniques, and using unwitting students as guinea pigs.

For the convenience of one location, here are my posts on error feedback, along with my sources and links if available.

My posts:

• Error Feedback in L2 Writing
• Error Feedback in L2 Writing: Scant Evidence
• Error Feedback: Theory
• Error Feedback: Skill Acquisition Theory
• Error Feedback: Motivation
• Error Feedback: Practice

Sources:

Anderson, J. R., Fincham, J. M., & Douglass, S. (1997). The role of examples and rules in the acquisition of a cognitive skill (pdf). Journal of Experimental Psychology, 23, 932-945.

Anderson, J. R., & Schunn, C. D. (2000). Implications of the ACT-R learning theory: No magic bullets (pdf). In R. Glaser (ed.), Advances in instructional psychology: Educational design and cognitive science (pp. 1-33). Mahwah, NJ: Lawrence Erlbaum (LE).

Bitchener, J., Young, S., & Cameron, D. (2005). The effect of different types of feedback on student ESL writing. Journal of Second Language Writing, 14, 191-205.

Blackwell, L. S., Trzesniewski, K. H., & Dweck, C. S. (2007). Implicit theories of intelligence predict achievement across an adolescent transition: A longitudinal study and an intervention. Child Development, 78, 246-263. (See here, here, and here for synopses of this work and others by Dweck.)

Chandler, J. (2003). The effects of various kinds of error feedback for improvement in the accuracy and fluency of L2 student writing. Journal of Second Language Writing, 267-296.

Csikszentmihalyi, M. (1990). Flow: The psychology of optimal experience. New York: Harper & Row, Publishers.

Deci, E. L., & Ryan, R. M. (2000). The "what" and "why" of goal pursuits: human needs and the self-determination of behavior (pdf). Psychological Inquiry, 11, 227-268. (See homepage for more on self-determination theory.)

DeKeyser, R. (2007). Skill acquisition theory. In B. VanPatten & J. Wiliams (eds.), Theories in Second Language Acquisition. Mahwah, NJ: LE.

Dörnyei, Z. (2001). Teaching and research motivation. Harlow, England: Pearson Education.

Ericsson, K.A., & Charness, N. (1994). Expert Performance: Its structure and acquisition. American Psychologist, 49, 725-747.

Ferris, D. (2004). The "grammar correction" debate in L2 writing: Where are we, and where do we go from here? (and what do we do in the meantime...?) (pdf). Journal of Second Language Writing, 13, 49-62.

---- (2003). Response to student writing: Implications for second language students. Mahwah, NJ: LE.

---- (2002). Treatment of error in second language student writing. Ann Arbor: University of Michigan Press.

---- (1999). The case for grammar correction in L2 writing classes: A response to Truscott (1996). Journal of Second Language Writing, 8, 1-11.

Ferris, D., & Hedgcock, J. (2005). Teaching ESL composition: Purpose, process, and practice (2nd ed.). Mahway, NJ: LE.

Hinkel, E. (2004). Teaching academic ESL writing: Practical techniques in vocabulary and grammar. Mahwah, NJ: LE.

Hinkel, E., & Fotos, S. (eds.) (2002). New perspectives on grammar teaching in second language classrooms. Mahwah, NJ: LE.

MIles, J. (2002). Second language writing and research: The writing process and error analysis in student texts. TESL-EJ 6.

Ross, P. (2006). The expert mind. Scientific American, 295(2), 64-71.

Truscott, J. (2004). Evidence and conjective on the effects of correction: A response to Chandler (pdf). Journal of Second Language Writing, 13, 337-343.

---- (1999). The case for "The case against grammar correction in L2 writing classes. A response to Ferris (pdf). JJournal of Second Language Writing, 8, 111-122.

---- (1996). The case against error correction in L2 writing courses (pdf). Language Learning 46, 327-369.

Yates, R., & Kenkel, J. (2002). Responding to sentence-level errors in student writing. Journal of Second Language Writing, 11, 29-47.

Below are bibliography pages with downloadable articles related to the above sources (and some repetition, of course):

ACT-R Theory
Self-determination theory

From the previous posts on learning theory (here and here), two crucial points were:

1. Acquiring expertise in any field, including language, requires extensive practice.
2. Effective time on task is the most important factor in learning.

You have to be motivated to practice extensively. Videogamers are and do. They can spend 50-100 hours on a game. Imagine a student spending 50-100 hours writing an essay! In an article on Wired, James Gee comments:

The secret of a videogame as a teaching machine ... [is] its underlying architecture. Each level dances around the outer limits of the player's abilities, seeking at every point to be hard enough to be just doable. In cognitive science, this is referred to as the regime of competence principle, which results in a feeling of simultaneous pleasure and frustration - a sensation as familiar to gamers as sore thumbs. Cognitive scientist Andy diSessa has argued that the best instruction hovers at the boundary of a student's competence. ... Also, good videogames incorporate the principle of expertise. They tend to encourage players to achieve total mastery of one level, only to challenge and undo that mastery in the next, forcing kids to adapt and evolve.

These principles of expertise and competence are also seen in two theories of motivation: self-determination theory and flow.

In self-determiantion theory, motivation is driven by three needs:

1. autonomy,
2. social relatedness, and
3. competence, including informational (not evaluative) feedback on competence, that is, feedback that supports autonomy in learning as opposed to controlling it.

Flow is a state in which one is fully engaged in the task at hand (see this review of Csikszentmihaly's book Finding Flow). Another post noted that flow occurs under certain conditions, three of which are:

1. clear goals
2. immediate feedback
3. tasks that challenge (without unduly frustrating) one's skills

These needs and conditions are an integral part of video games. But have they been in providing error feedback?

Probably not as directly as in other arenas. Just look at the condition of "immediate feedback." In my own first-year composition classes, error feedback is given mostly on essay drafts, which I receive every 2-3 weeks and return in 2-7 days. Can you imagine a basketball coach giving feedback only every few weeks and then a few days after the practice in question?

Although it's not as easy to incorporate these motivation principles into error feedback, I have a few ideas I'll discuss in the next post.

All Error Feedback Posts in this series:
Error Feedback in L2 Writing
Error Feedback in L2 Writing: Scant Evidence
Error Feedback: Theory
Error Feedback: Skill Acquisition Theory
Error Feedback: Motivation
Error Feedback: Practice
Error Feedback: Bibliography

As noted in the previous post on theory in error feedback, the research on expertise and ACT-R Theory suggest that learning a language is similar to learning other activities like chess, music, and math. In this post, we'll look at Skill Acquisition Theory (SAT), which is based upon the work in ACT-R.

Robert DeKeyser (2007) has a good overview of Skill Acquisition Theory. (See Theories in Second Language Acquistion.) As he notes, development has three stages: declarative, procedural, and automatic (from ACT-R Theory). Declarative knowledge refers to explicit knowledge about a topic, as in "knowing" and talking about grammar rules. Procedural knowledge is implicit knowledge that refers to behavior, such as speaking or writing a language. Of course, there are different levels of proficiency in using a language, and thus automaticity is not an "all-or-nothing affair". Automaticity occurs toward the endpoint of extensive practice, toward the point at which one has become completely fluent in a language. From the perspective of SAT, the sequence of these stages is crucial, as is the appropriate "combination of abstract rules and concrete examples" at the declarative stage.

According to DeKeyser, Skill Acquisition Theory does not explain all of language learning and apparently is most effective at beginner levels. He states that SAT works best with

1. high-aptitutde adult learners engaged in
2. the learning of simple structures at
3. fairly early stages of learning
4. in instructional contexts

It seems obvious that young children will not respond as well as adults to the use of declarative knowledge as their ability to understand rules and explanations is more limited. Conversely, as rules become more complex, they may become too difficult to understand in the form of declarative knowledge. Thus, it's possible that learning (or acquiriing) complex rules may rely more upon implicit processes. Anderson and Schunn (pdf) say something similar:

As knowledge domains become more advanced, their underlying cognitive structure tends to become more obscure. Thus, while it may remain easy to provide feedback on what the final answer is, it becomes difficult to provide feedback on the individual mental steps that lead to the final answer. Teachers often are unaware, at an explicit level, of what this knowledge is and do not know how to teach it to children.

Anderson and Schunn are pointing to the need to diagnose a task and break it down into its components in order to provide effective feedback. When we can't componentialize a task, then feedback becomes considerably less effective. Basically, we can only say then, "No, that's not right" or "Yes, that's it."

Thus, with respect to error correction, we need

• rules that are not obscure,
• examples of the rules, and
• understandable explanations of those rules.

The ability to use declarative knowledge in the learning process does not accelerate acquisition. Rather, it eliminates wasted time and effort.

Before turning to practical suggestions for error correction, I'll look at motivation in my next post.

All Error Feedback Posts in this series:
Error Feedback in L2 Writing
Error Feedback in L2 Writing: Scant Evidence
Error Feedback: Theory
Error Feedback: Skill Acquisition Theory
Error Feedback: Motivation
Error Feedback: Practice
Error Feedback: Bibliography

When the evidence for error feedback is "scant", mostly what we have to go on is theory. Those who oppose error correction would likely assume a nativist framework that includes:

1. Language acquisition (whether first or second language) differs from general learning processes.
2. Language acquisition and general learning processes do not interact.
3. The process of language acquisition cannot be accelerated.

Without reviewing the research, let me say that there are those, even in L1 studies, that assert that language acquistion results from general learning processes (e.g., Christiansen and Chater's working paper, "Language as Shaped by the Brain"). And alternative theories also exist in second language acqusition, such as Skill Acquistion Theory and Associate-Cognitive CREED (Construction-based, Rational, Exemplar-driven, Emergent, and Dialectic). (See Theories in Second Language Acquistion.) So, why would anyone want to take a nativist position? There are more than a few reasons. The main one seems to be the poverty of the stimulus, but in part, one reason seems to be that language acquisition is seen as inexplicably complex while other learning endeavors seem simple in comparison. I would like to suggest that the comparisons being made are simple, but not the objects, or processes, being compared.

I've mentioned Philip Ross's article "The Expert Mind" (in Scientific American, see also my post) on more than one occasion, but it's worthwhile to return to it often. It states,

The preponderance of evidence is that experts are made, not born.

Although not innate, expertise takes time to develop. In general, it takes "takes approximately a decade of heavy labor to master any field." Thus, although it doesn't take much to learn how to move the pieces in chess, becoming a grandmaster of strategy, however, takes at least a decade of intense practice. Similarly, although it doesn't take much to learn a few basic grammar rules and a small vocabulary, becoming fluent in another language--that is, acquiring the "grandmaster status" of a native speaker--takes at least 10 years of intense practice, too.

If the amount of time to acquire expertise is similar between chess, music, art, math, and language, that suggests for learning a language,

1. the crucial element is practice rather than some language module
2. the process cannot be accelerated.

Because the process cannot be accelerated, it may matter little whether one takes an nativist or general learning process approach to language acquistion. Note, however, that all practice is not equal. From the article,

Ericsson argues that what matters is not experience per se but "effortful study," which entails continually tackling challenges that lie just beyond one's competence. That is why it is possible for enthusiasts to spend tens of thousands of hours playing chess or golf or a musical instrument without ever advancing beyond the amateur level and why a properly trained student can overtake them in a relatively short time. It is interesting to note that time spent playing chess, even in tournaments, appears to contribute less than such study to a player's progress; the main training value of such games is to point up weaknesses for future study.

The case of enthusiasts practicing without advancing is reminiscent of fossilization, and the "effortful study" reminds me of Krashen's i+1 principle for input. One difference is "point[ing] up weakenesses for future study," a "monitor" approach that Krashen would say does not contribute to language acquisition.

Anderson and Schunn in their article "The implications of the ACT-R learning theory: no magic bullets" (pdf) make similar assertions:

For competences to be displayed over a lifetime, time on task is by far and away the most significant factor.

However, they qualify that to mean "effective time on task." Once again, not all practice is equal. In the case of ACT-R Theory, "effective time on task" is promoted through

• the use of examples accompanied by explanation and understanding,
• accurate diagnosis of the learning task and performance, and
• feedback

It seems that research on expertise and ACT-R Theory would support some form of error correction. Because Skill Acquistion Theory, which draws upon ACT-R and similar theories, focuses on SLA, in my next post, I'll look at it in a little more detail.

All Error Feedback Posts in this series:
Error Feedback in L2 Writing
Error Feedback in L2 Writing: Scant Evidence
Error Feedback: Theory
Error Feedback: Skill Acquisition Theory
Error Feedback: Motivation
Error Feedback: Practice
Error Feedback: Bibliography

Engagement is a term heard everywhere in educational circles. But how do we measure it? Is engagement always relevant to learning? Artichoke asks these questions and others:

“Engagement” is an interesting notion, as is “rich and authentic”. When I hear schools advocating the use of student inquiry and authentic contexts over other pedagogical approaches on the grounds that it engages (and thus apparently motivates) students, I always want to ask

• How do you assess engagement?
• How different are these measures when students are learning through inquiry activities than when they are learning through other pedagogical approaches? And
• What difference do you find in student learning outcomes that can be causally attributed to your measures of engagement?

And when I think about “rich and authentic” I want to ask, authentic to whom? I want to know why “rich and authentic” is a more popular descriptor of the quantity and quality of the learning experience than “educationally relevant”

Perhaps the emperor has no clothes. Engagement is a fuzzy and anecdotal term. Still, I suppose when I use that term, I'm really referring to time on task and self-determination. In terms of self-determination theory, acting autonomously promotes intrinisic motivation, which in turn leads to more time on task. And it's clear that the more "effective time on task" there is (see Implications of ACT-R Theory: No Magic Bullets (pdf)), the more learning can take place.

So, yes, we need to be careful in our bandying about the terms "engagement" and "rich and authentic." Having said that, "effective time on task" and "self-determination" are important pillars of the learning process.

Jay Mathews, in "New teacher jolts KIPP", writes about Lisa Suben, a new teacher in the KIPP schools, who had her math students jump from the 16th to the 77th percentile in a single year. That's an unbelievably huge jump! How'd she do it? Theoretically, she says:

"My primary goal as a teacher is to help my students understand the reasoning behind math rules and procedures. I have several core beliefs about this: (1) Understanding is constructed by the learner, not passively received from the teacher. (2) Understanding is built by making connections between as many strands of knowledge as possible. (3) Understanding is galvanized through communication. (4) Understanding is only valuable when you reflect on it and question it."

Items (2) and (3) are related. That is, communication can (but need not) present more strands of knowledge to enter the picture that allows more connections to be made. It's not the connections per se that build understanding but rather the contradictions among them. Contradictions are the driving force of learning. On item (4), reflecting and questioning can improve one's understanding, of course, but most understanding is unconscious. That doesn't make it unvaluable.

Suben translated her theory into the following practice:

The core of her method is the workbook she produced last year on the fly. It "lets students build their own notes and create their own examples. It is incredibly active learning," she said. They were encouraged to write down the meaning of important terms and strategies they used that worked with certain kinds of problems.

Suben, I imagine, is differentiating between a traditional lecture form of teaching and Deweyan "learning by doing". It's not clear that one type of learning is more active than another. All learning is active. Of course, I can also imagine that students focus more on something they are "doing" as opposed to "receiving," and thus they spend more "effective time on task," the crucial element in learning. Thus, Suben's having her students create their own notes, examples, and meaning is an excellent way to (1) focus them more effectively on the tasks at hand and (2) bring them into contradictions between their declarative and procedural knowledge (see ACT-R Theory) and so improve their understanding.

Related posts on the five-paragraph essay:
Forget IQ. Just Work Hard!
The Expert Mind
Learning: A State of Disatisfaction
Learning with Examples

Philip Ross wrote a good review on The Expert Mind (Scientific American via elearningpost via elearnspace via Stephen's Edu_RSS). Some excepts:

The one thing that all expertise theorists agree on is that it takes enormous effort to build these structures in the mind. Simon coined a psychological law of his own, the 10-year rule, which states that it takes approximately a decade of heavy labor to master any field.

Ericsson argues that what matters is not experience per se but "effortful study," which entails continually tackling challenges that lie just beyond one's competence.

Thus, motivation appears to be a more important factor than innate ability in the development of expertise.

The preponderance of psychological evidence indicates that experts are made, not born. What is more, the demonstrated ability to turn a child quickly into an expert--in chess, music and a host of other subjects--sets a clear challenge before the schools. Can educators find ways to encourage students to engage in the kind of effortful study that will improve their reading and math skills?

"Effortful study" is related to ACT-R theory and in some ways just seems to be common sense. What seems to be missing in this article is the recognition that the 10-year rule when applied to reading and math equals 20 years, unless we double the total amount of "effortful study" in each and every day. Although we might argue that reading (especially reading) and math have greater application to more subjects, it would still mean that students would need to focus on a career subject at an early age in order to become an expert.

The ten-year rule also puts into better perspective why people take so long to acquire a second language. Language fluency requires expertise in the language. Add to that expertise in writing in a second language means adding even more time.

The article also notes that experts do not exist in abundance:

Without a demonstrably immense superiority in skill over the novice, there can be no true experts, only laypeople with imposing credentials. Such, alas, are all too common. Rigorous studies in the past two decades have shown that professional stock pickers invest no more successfully than amateurs, that noted connoisseurs distinguish wines hardly better than yokels, and that highly credentialed psychiatric therapists help patients no more than colleagues with less advanced degrees.

Some questions: Is this a problem for education? In general? That is, should people in general strive for expertise in their fields? Or simply to be competent? With respect to second language learning, how should the 10-year rule affect our approach to language teaching and our expectations about language learning?

Kerry Hempenstall. senior lecturer in psychology at RMIT University, argues for a phonics approach to L1 reading in "Practice Makes Permanent":

We now understand that the brain responds to multiple similar experiences. These stimulate activity in particular areas, building connections in and between those active brain regions. That is how practice makes permanent. Practising productive strategies forms and strengthens the optimal connections that stimulate subsequent reading development.

In the same way, routinely engaging in ineffective strategies also builds circuits in the brain, but circuits that are second-rate for reading. These routines are not easy to break when students grow older, perhaps because between ages five and 10, there's a pruning process that erases under-used neural cells. ...

Among those struggling readers, there are teaching strategies that can alter the inefficient pattern of brain activation. Studies have indicated that about 60 hours of careful daily phonics teaching alters the way the brain responds to print. Inefficient right-hemisphere activity diminishes, and left-hemisphere activity increases. New MRI images now look much more like those of good readers. The measured reading outcomes include increased fluency and comprehension.

The brain imaging studies have also shown how difficult and exhausting is the task of reading for struggling students. They use up to five times as much energy when reading as do fluent readers. It is not surprising that they prefer not to read.

With adult learners of a second language, these studies suggest a few areas for consideration. Take, for example, fossilization. Why is it so hard to overcome? It may because circuits for undesired forms have been constructed that are not easy to break. Although research would be needed, if correct, such a perspective would support not so much correction as practice on desired forms--not drill and kill, but use and learn in context.

Relatedly, the post "Forget IQ. Just Work Hard" cites John Anderson's assertion that there are no magic bullets to speed up learning. Rather,

the ACT-R theory makes it clear that there is no magic bullet that allows some way out of these enormous differences in time on task [between 9th grade students in Pittsburgh and in Japan]. For competences to be displayed over a lifetime, time on task is by far and away the most significant factor.

Thus, gimmicks like mnemonics are simply that: gimmicks for vocabulary regurgitation at the expense of language proficiency. What's crucial in language learning is time, practice, and examples. As "Learning with Examples" notes, however, without appropriate examples, time and practice cannot only be wasted but also used to construct, as seems to be the case with some L1 readers, incorrect language circuits.

As you may have noticed, I've been working on the design of this blog: mostly color changes but also a fluid design for the content side. At first, I started trying to wrap the posts around at the bottom of the sidebar. I did my research, read the tutorials, but couldn't figure it out. I emailed Mark Bernstein, the designer of Tinderbox, this weblog's software application, suggesting that the feature be incorporated into later versions. He responded (Mark's generosity with his time is unbelievable!), offered to do it for me, and, one hour later, sent me my weblog file re-coded with the fluid design (a switch from the earlier wrapping style). And I continued with changing the colors, which is not a straightforward process for someone who is colorblind. (I use the Color Generator and patient friends.)

What's this got to do with learning with examples? Well, I've learned by observing what Mark did. Previously, I would duplicate an entire file to have a practice file; Mark simply added a new CSS note. Previously, I would export an entire document to see how it looked in html. While in Boston, I noticed that Mark just used the Preview button. And from the code he sent, I began to understand the difference between "float" and "absolute". In trying to re-design this blog,I spent two full days acquiring quite a bit of frustration but little understanding, as opposed to taking a few minutes to look at Mark's re-coding to learn where I had gone wrong.

Such incidental learning via examples underscores John Anderson's ACT-R learning theory. Anderson, a professor of psychology and computer science at Carnegie Mellon University, is the one who first posited two types of knowledge: declarative and procedural. I've posted on Anderson before (see "Lies teachers tell?" and "Forget IQ. Just Work Hard!".

Anderson and Schunn in their article "The implications of the ACT-R learning theory: no magic bullets" (pdf) write:

There are no magical properties conveyed upon a knowledge structure just because it was self-generated. If all things were equal it would be preferable to have children learn by generating the knowledge (due to the redundant encoding). However, because of difficulties of generation and dangers of misgeneration, things are not always equal and it can be preferable to tell the knowledge.

...

Thus, ACT-R's theory of procedural learning claims that procedural skills are acquired by making references to past problem solutions while actively trying to solve new problems. Thus, it is both a theory of learning by doing and a theory of learning by example.

Simply providing the learner with examples is not sufficient to guarantee learning in the ACT-R theory. The sufficiency of the production rules acquired depends on the understanding of the example.

Anderson and Schunn add, "For competences to be displayed over a lifetime, time on task is by far and away the most significant factor." That is, learners must practice a lot. The problem is one can practice the wrong skills, in which case "practice makes imperfect." In other words, learners need feedback and explicit guidance, often in the form of examples, to make their practice effective.

But how can examples be so effective? Perhaps because human beings learn mostly through imitating. Vilayanur Ramachandran, Director of the Center for Brain and Cognition, posits that imitation via mirror neurons is the driving force of human evolution:

With knowledge of these neurons, you have the basis for understanding a host of very enigmatic aspects of the human mind: "mind reading" empathy, imitation learning, and even the evolution of language. Anytime you watch someone else doing something (or even starting to do something), the corresponding mirror neuron might fire in your brain, thereby allowing you to "read" and understand another's intentions, and thus to develop a sophisticated "theory of other minds."

An earlier post "Be Happy, and Learn!", commented on Kathy Sierra's post "Angry/negative people can be bad for your brain" on the effect of mirror neurons on one's emotional state:

There is now strong evidence to suggest that humans have the same type of "mirror neurons" found in monkeys. It's what these neurons do that's amazing--they activate in the same way when you're watching someone else do something as they do when you're doing it yourself! This mirroring process/capability is thought to be behind our ability to empathize, but you can imagine the role these neurons have played in keeping us alive as a species. We learn from watching others. We learn from imitating (mirroring) others. The potential problem, though, is that these neurons go happily about their business of imitating others without our conscious intention.

Note, however, that this imitation is an unconscious process. I'm not quite sure of the relationship between consciously understanding and using examples and imitating those examples. Perhaps understanding comes through imitation + practice.

Although we wouldn't want to limit ourselves to learning by imitation, the fact that imitation is such a strong component of learning should give us pause when we read statements that denigrate imitation and position it in opposition to creativity.

Paul Butler argues for re-introducing imitation into composition in his article "Imitation as Freedom: (Re)Forming Student Writing":

For many years now, the use of imitation in the composition classroom has been waning. As Connors points out, articles on imitation, sentence combining, and generative rhetoric have steadily declined and have been almost nonexistent since 1995. Yet in composition classrooms all over the country, as we adopt various process techniques, we still hold our students accountable for the fundamental elements of good writing: organization, coherence, unity, and clarity, among others. Lisa Delpit has pointed out that our expectations are sometimes “hidden,” that they remain invisible to students as we encourage them to explore their ideas and work within the process model of teaching. Delpit’s argument, though intended to address the situation of minority students, also applies to students in composition classes around the country. Indeed, it seems the height of hypocrisy to use strictly process techniques when we expect high quality “products” from our students’ writing.

Along these lines of using examples and imitation, I commented previously on They say/I say : the moves that matter in academic writing, a book by Gerald Graff and Cathy Birkenstein that uses templates to help students see and be able to make the rhetorical moves of academia.

I think that most of us forget how often we use and appreciate examples when we enter new territory. For instance, when writing my first book review, I looked at dozens of other book reviews to understand this genre's requirements. I imagine if someday I write a grant proposal, I'll do the same, too. And, I imagine that most writers follow suit. If we learn this way, then why wouldn't our students do so, too? Why do we expect them to start from scratch when we don't? And with respect to EFL/ESL students who don't have a strong L2 cultural foundation for learning L2 writing by "osmosis," the case for making explicit the implicit is even more essential.

None of this is an argument for rote memorization of models. Rather, it's an acknowledgement that if we are wired for imitation, for learning with examples, then why not take advantage of our "wiring" when designing class activities?

I mentioned this back in December, but it's worth repeating. Dave Munger ("High IQ: Not as good for you as you thought", Cognitive Daily) reported on some research by Angela Duckworth and Martin Seligman that investigates the question,

Could a more robust measure of self-discipline demonstrate that it's more relevant to academic performance than IQ?

To address this question, Duckworth and Seligman conducted a two-year study of eighth graders, combining several measures of self-discipline for a more reliable measure, and also assessing IQ, achievement test scores, grades, and several other measures of academic performance. Using this better measure of self-discipline, they found that self-discipline was a significantly better predictor of academic performance 7 months later than IQ.

As Munger comments, "Most impressive was the whopping .67 correlation between self-discipline and final GPA, compared to a .32 correlation for IQ." That's certainly impressive.

Self-discipline, of course, means that students spend more time on task. From this perspective, John R. Anderson's ACT-R model of learning supports the stance that self-discipline is important. ACT-R is a theory of how people think and learn.

The original ACT (Atomic Components of Thought) model was the one that posited the different types of knowledge, declarative and procedural. Anderson and Schunn's article "Implications of the ACT-R learning theory: No magic bullets", as the title suggests, asserts:

the ACT-R theory makes it clear that there is no magic bullet that allows some way out of these enormous differences in time on task [between 9th grade students in Pittsburgh and in Japan]. For competences to be displayed over a lifetime, time on task is by far and away the most significant factor.

This perspective is a crucial one for language learning. Many try to speed up language acquisition through various strategies such as mnemonics. As the article states:

There has been a long-standing strand of research in human memory looking at the advantage of mnemonics and various memory-enhancing strategies in terms of learning material. Such mnemonics strategies have been recommended for domains as far ranging as foreign vocabulary learning and learning of chemical formulas. However, the important thing to recognize is that these techniques speed the initial acquisition of the knowledge. Speed of the first steps on the learning curve becomes insignificant if ones goal is long-term possession of the knowledge. Such mnemonics drop out with practice and the critical factor becomes, not saving a relatively small amount of time in initial acquisition, but rather investing substantial amounts of time in subsequent practice. It is not clear that there is anything to be saved in subsequent practice by use of mnemonics.

In other words, practice makes perfect--not learning gimmicks.

So, for Munger the question becomes, How (if we can) teach self-discipline? For me, the question becomes, How can we foster an environment in which self-discipline is the norm?

Tim Frederick (via Bud and Nancy) are discussing the "lies" teachers tell their students, one of which seems to be saying "this is an important book." They make some good points, which I'll come back to, but first I want to look at some of the assumptions being made.

According to Tim, this is called a lie because: "How did we become so arrogant as to think we had the right to say which books were important to read and which aren't? "

I'm not sure we should consider arrogance as a form of lying, and I'm not sure that it's rights that are the issue. Shouldn't it be responsibility? That is, teachers have the responsibility (and are accountable to parents and society) for selecting those books that will best enable students to learn. Actually, depending on the grade level and subject, school administrators often do the choosing of books for the school's curricula, books that must meet a state's criteria, as determined by state departments of education.

Tim adds:

What disturbs me most is that when we say this, we take a little power away from students AND hurt their critical thinking. Shouldn't they decide what's important and why? That can be empowering, as well as exercise the critical thinking muscle of evaluating. They would have to be able to justify their reasons for thinking a book is important and we can share how other people define "important". Students can further evaluate others' criteria for "importance". How many perfectly good lessons surrounding this are thrown away when we decide what's important?

Part of this argument is a value judgment of "empowering" students, of appealing to egalitarian values. In the classroom, however, such an appeal should be secondary to principles of learning. No research on learning is cited in these claims, nor is any evidence given to support that "empowering" students will help them learn better. To be fair, Bud just wrote a few paragraphs, not an academic essay. However, with such strong claims, I'd like to see a little evidence.

Another assumption without evidence is that saying "This is an important book" somehow "hurt[s] their crtical thinking." Actually, this assumption is a shift from the perspective of teachers wanting students to read "good" books to a position on the value of "critical thinking," as if these positions were exclusive. Of course, I can imagine teachers who pontificate without inviting students into the discussion, but that's not at issue here.

There is no getting away from the teacher's responsibility. Consider Bud's last sentence, "How many perfectly good lessons surrounding this are thrown away when we decide what's important?" Who decides what are "perfectly good lessons"? If we carry this perspective to its conclusion, then we should have the children evaluating the criteria for "perfectly good lessons" and the criteria for good teaching. In fact, we should listen to the commplace saying that one learns best by teaching, and we should just have the children do the teaching, too. Then what would the teachers do?

Now looking at the positives of Bud's argument, It does make sense that students need to learn and evaluate "how other people define 'important'" and also develop critical thinking. The issue is how to do this. Perhaps we can draw from ACT-R learning theory. Anderson and Schunn (2000) write,

There are no magical properties conveyed upon a knowledge structure just because it was self-generated. If all things were equal it would be preferable to have children learn by generating the knowledge (due to the redundant encoding). However, because of difficulties of generation and dangers of misgeneration, things are not always equal and it can be preferable to tell the knowledge.

...

Thus, ACT-R's theory of procedural learning claims that procedural skills are acquired by making references to past problem solutions while actively trying to solve new problems. Thus, it is both a theory of learning by doing and a theory of learning by example.

Simply providing the learner with examples is not sufficient to guarantee learning in the ACT-R theory. The sufficiency of the production rules acquired depends on the understanding of the example.

Anderson and Schunn add, "For competences to be displayed over a lifetime, time on task is by far and away the most significant factor." That is, learners must practice a lot, whether critical thinking or other skills. The problem is one can practice the wrong skills, in which case "practice makes imperfect." In other words, learners need feedback and at times explicit guidance to make their practice effective. Of course, they can get that when they choose their own books. And now we're back where we started: How does the teacher choosing a book hurt students?

Reference:

Anderson, John R., & Schunn, Christian D. (2000). The implications of the ACT-R learning theory: no magic bullets. In R. Glaser (Ed.), Advances in instructional psychology (Vol. 5). Mahwah, NJ: Erlbaum.

Carl Zimmer of the New York Times reported in an article "Children learn by monkey see, monkey do. Chimps don't" on psychological studies concluding that human beings are hard-wired to learn via imitation.

Mr. Lyons sees his results as evidence that humans are hard-wired to learn by imitation, even when that is clearly not the best way to learn. If he is right, this represents a big evolutionary change from our ape ancestors. Other primates are bad at imitation. When they watch another primate doing something, they seem to focus on what its goals are and ignore its actions.

As human ancestors began to make complicated tools, figuring out goals might not have been good enough anymore. Hominids needed a way to register automatically what other hominids did, even if they didn't understand the intentions behind them. They needed to imitate.

Not long ago, many psychologists thought that imitation was a simple, primitive action compared with figuring out the intentions of others. But that is changing. "Maybe imitation is a lot more sophisticated than people thought," Mr. Lyons said.

Much of learning theory posits that reflection is a deeper form of learning while imitation is a lower form of learning (e.g., Engeström). Yet, there is also an understanding that examples and models facilitate learning. John Anderson of ACT-R learning theory (i.e., declarative and procedural knwoledge) states that there is no real difference between self-generated learning and passive reception of knowledge (unless the former "produces multiple ways to retrieve the material"). Extrapolating to the difference between imitation and reflection, I wonder when reflection is worth the time invested and how much of a difference it really makes.