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Why good readers might have reading comprehension difficulties and how to deal with them

The limitations of working memory have implications for all of us. The challenges that come from having a low working memory capacity are not only relevant for particular individuals, but also for almost all of us at some points of our lives. Because working memory capacity has a natural cycle — in childhood it grows with age; in old age it begins to shrink. So the problems that come with a low working memory capacity, and strategies for dealing with it, are ones that all of us need to be aware of.

Today, I want to talk a little about the effect of low working memory capacity on reading comprehension.

A recent study involving 400 University of Alberta students found that 5% of them had reading comprehension difficulties. Now the interesting thing about this is that these were not conventionally poor readers. They could read perfectly well. Their problem lay in making sense of what they were reading. Not because they didn’t understand the words or the meaning of the text. Because they had trouble remembering what they had read earlier.

Now these were good students — they had at least managed to get through high school sufficiently well to go to university — and many of them had developed useful strategies for helping them with this task: highlighting, making annotations in the margins of the text, and so on. But it was still very difficult for them to get hold of the big picture — seeing and understanding the text as a whole.

This is more precisely demonstrated in a very recent study that required 62 undergraduates to read a website on the taxonomy of plants. Now this represents a situation that is much more like a real-world study scenario, and one that has, as far as I know, been little studied: namely, drawing together information from multiple documents.

In this experiment, the multiple documents were represented by 24 web pages. Each page discussed a different part of the plant taxonomy. The website as a whole was organized according to a four-level hierarchical tree structure, where the highest level covered the broadest classes of plants (“Plants”), and the lowest, individual species. However — and this is the important point — there was no explicit mention of this organization, and you could navigate only one link up or down the tree, not sideways. Participants entered the site at the top level.

After pretesting, to assess WMC and prior plant knowledge, the students were given 18 search questions. Participants were asked both to read the site and answer the questions. They were given 25 minutes to do so, after which they completed a post-test similar to their pre-test of prior knowledge: (1) placing the eight terms found in the first three levels on the hierarchical tree (tree construction task); (2) selecting the correct two items from a list of five, that were subordinates to a given item (matching task).

Neither WMC nor prior knowledge affected performance on the search task. Neither WMC nor prior knowledge (nor indeed performance on the search task) directly affected performance on the post-test matching task, indicating that learning simple factual knowledge is not affected by your working memory capacity or how much relevant knowledge you have (remember though, that this was a very simple and limited amount of new knowledge).

But, WMC did significantly affect understanding of the hierarchical structure (assessed by the tree construction task). Prior knowledge did not.

These findings don’t only tell us about the importance of WMC for seeing the big picture, they also provide some evidence of what underlies that, or at least what doesn’t. The findings that WMC didn’t affect the other tasks argues against the idea that high WMC individuals may be benefiting from a faster reading speed, or that they are better at making local connections, or that they can cope better at doing multiple tasks. WMC didn’t affect performance on the search questions, and it didn’t affect performance on the matching task, which tested understanding of local connections. No, the only benefit of a high WMC was in seeing global connections that had not been made explicitly.

Let’s go back to the first study for a moment. Many of the students having difficulties apparently did use strategies to help them deal with their problem, but their strategy use obviously wasn’t enough. I suspect part of the problem here, is that they didn’t really realize what their problem was (and you can’t employ the best strategies if you don’t properly understand the situation you’re dealing with!).

This isn’t just an issue for people who lack the cognitive knowledge and the self-knowledge (“metacognition”) to understand their intrinsic problem. It’s also an issue for adults whose working memory capacity has been reduced, either through age or potentially temporary causes such as sleep deprivation or poor health. In these cases, it’s easy to keep on believing that ways of doing things that used to work will continue to be effective, not realizing that something fundamental (WMC) has changed, necessitating new strategies.

So, let’s get to the burning question: how do you read / study effectively when your WMC is low?

The first thing is to be aware of how little you can hold in your mind at one time. This is where paragraphs are so useful, and why readability is affected by length of paragraphs. Theoretically (according to ‘best practice’), there should be no more than one idea per paragraph. The trick to successfully negotiating the hurdle of lengthy texts lies in encapsulation, and like most effective strategies, it becomes easier with practice.

Rule 1: Reduce each paragraph to as concise a label as you can.

Remember: “concise” means not simply brief, but rather, as brief as it can be while still reminding you of all the relevant information that is encompassed in the text. This is about capturing the essence.

Yes, it’s an art, and to do it well takes a lot of practice. But you don’t have to be a master of it to benefit from the strategy.

The next step is to connect your labels. This, of course, is a situation where a mind map-type strategy is very useful.

Rule 2: Connect your labels.

If you are one of those who are intimidated by mind maps, don’t be alarmed. I said, “mind map-type”. All you have to do is write your labels (I call them labels to emphasize the need for brevity, but of course they may be as long as a shortish sentence) on a sheet of paper, preferably in a loose circle so that you can easily draw lines between them. You should also try to write something by these lines, to express your idea of the connection. These labels will also provide a more condensed label for the ideas being connected. You can now make connections between these labels and the others.

The trick is to move in small steps, but not to stay small. Think of the process as a snowball, gathering ideas and facts as it goes, getting (slowly) bigger and bigger. Basically, it’s about condensing and connecting, until you have everything densely connected, and the information getting more and more condensed, until you see the whole picture, and understand the essence of it.

Another advantage of this method is that you will have greatly increased your chances of remembering it in the long-term!

In a situation similar to that of the second study — assorted web pages — you want to end up with a tight cluster of labels for each page, the whole of which is summed up by one single label.

What all this means for teachers, writers of text books, and designers of instructional environments, is that they should put greater effort into making explicit global connections — the ‘big picture’.

A final comment about background knowledge. Notwithstanding the finding of the second study that there was no particular benefit to prior knowledge, the other part of this process is to make connections with knowledge you already have. I’d remind you again that that study was only testing an extremely limited knowledge set, and this greatly limits its implications for real-world learning.

I have spoken before of how long-term memory can effectively increase our limited WMC (regardless of whether your WMC is low or high). Because long-term memory is essentially limitless. But information in it varies in its accessibility. It is only the readily accessible information that can bolster working memory.

So, there are two aspects to this when it comes to reading comprehension. The first is that you want any relevant information you have in LTM to be ‘primed’, i.e. reading and waiting. The second is that you are obviously going to do better if you actually have some relevant information, and the more the better!

This is where the educational movement to ‘dig deep not broad’ falls down. Now, I am certainly not arguing against this approach; I think it has a lot of positive aspects. But let’s not throw out the baby with the bathwater. A certain amount of breadth is necessary, and this of course is where reading truly comes into its own. Reading widely garners the wide background knowledge that we need — and those with WMC problems need in particular — to comprehend text and counteract the limitations of working memory. Because reading widely — if you choose wisely — builds a rich database in LTM.

We say: you are what you eat. Another statement is at least as true: we are what we read.

References

Press release on the first study (pdf, cached by Google)

Second study: Banas, S., & Sanchez, C. a. (2012). Working Memory Capacity and Learning Underlying Conceptual Relationships Across Multiple Documents. Applied Cognitive Psychology, n/a-n/a. doi:10.1002/acp.2834

The changing nature of literacy. Part 4: Models & Literacies

This post is the fourth and last part in a four-part series on how education delivery is changing, and the set of literacies required in today’s world. Part 1 looked at textbooks; Part 2 at direct instruction/lecturing; Part 3 at computer learning.. This post looks at learning models and types of literacy.

 

Literacy. What does it mean?

Literacy is about being able to access information locked up in a code; it's also about being able to use that code. To be literate is to be able to read and write.

There's also another aspect of literacy that goes beyond mere decoding. This is about reading with understanding, with critical awareness.

Argument around the dangers of modern technology tends, in the way of arguments, to simplistically characterize the players: Internet = short, shallow; Social media = frivolous, distracting; Games = frivolous; Textbooks, Lectures = serious, deep, instructive.

But of course this is ridiculous even if we restrict ourselves to the learning context. Even social media have their uses. Even games can teach. And even textbooks and lectures can be shallow, or uninstructive, or inaccurate. (Indeed, way back in my first year of university I experienced a calculus lecturer who, I believe, reduced my understanding of calculus!)

The internet is, as we all recognize, a two-sided tool (but every tool is). Many people worry about the misinformation, the shallowness of much of the information, the superficiality of surfing, the way people might get stuck in a little corner that reinforces their vulnerabilities or prejudices, and so on.

We can say the same about infographics (data visualization, visual communication, call it what you will). It’s fostered as a way of helping us deal with the complexity and quantity of information (and I’m a big fan of it), but some people have criticized it for its potential for misinformation. Of course, text (wherever found) is far from pure in this respect!

But we don’t deal with misinformation by banning it (well, some of us don’t); we deal with it by providing the tools and the education so that people can recognize when something is being dangerously misleading or just plain wrong.

So, one of the important aspects of literacy (once you get beyond the decoding level) is being able to evaluate the information.

Why do we talk about digital literacy? Do we really need a new term (or terms)?

It comes down to skills. Because that is what literacy is: it's a skill (with all that that implies). And the new literacies do, undeniably, require new skills.

As far as the decoding aspect is concerned, well, text is still text. And textbooks have always included illustrations, so you could say that that is not new either. But that would be a mistake. The problem with visualizations is that it is not obvious that there's a skill to reading them — they're not as transparent as most believe (hence the misinformation claim). Humans have always used pictures to communicate; it is only recently that these have become sufficiently sophisticated to warrant the term 'language'.

So one of the modern literacies must be visual language, which like verbal language (and math and music), comes in different flavors. We wouldn’t use the same strategies to interpret and analyze a novel as we would a chemistry text, or a poem. We need to develop the same understanding of the taxonomy of visual language.

So I think we should include visual literacy in our new literacy set.

But of course, the new information delivery systems have requirements that go beyond content. Being able to use the code goes beyond reading text and pictures. It involves being able to navigate the delivery system. With a book, you just have to turn the pages. But with hyperspace, learning spaces, video-books, and so on, 'reading' is more complicated.

This is the important thing, the qualitative shift: the shift from linearity. Having a space, be it the whole of the internet or a confined learning space, in which you can go in many directions, in which there is no one path, may be empowering and richly layered, but it is not a place you can throw anyone into without training. Not if they are going to truly benefit from it. Like the need for visual literacy, this is another under-recognized need.

The complexity of these spaces and their navigation has, however, led to a number of useful distinctions being made — between digital literacy and computer literacy, information literacy, and media literacy (among others). Basically, these point to the need to distinguish between an ability to use technology (know the language of software — What’s a window? What’s the difference between a browser and a search engine? Do you hashtag your tweets? Do you use folders?) from the ability to find, filter, and evaluate information, and from the ability to actively participate in the information flow across media (Do you change your verbal style appropriately when you move from a tweet to a YouTube script to a written report to a comment on someone’s blog? Do you use different modes of analysis and evaluation when viewing different media?)

Given that we want students to become adept at all of these, how should we teach them?

In an interview, Will Richardson, a teacher whose experiences with interactive Web tools in the classroom led him to write Blogs, Wikis, Podcasts, and Other Powerful Web Tools for Classrooms talks about the need for teachers to have a visible presence on the Web, to participate in learning networks, and about how this openness is a huge culture shift for the closed shop of teachers. About network literacy as a key skill: “students should be able to create, navigate, and grow their own personal learning networks in safe, effective, and ethical ways. It’s really about the ability to engage with people around the world in these online networks, to take advantage of learning opportunities that are not restricted to a particular place and time, and to be conversant with the techniques and methodologies involved in doing this.” About how kids may be more technologically savvy, but they need help sorting out which information, and which people, to trust.

My favorite bit: he talks about Rethinking Education in the Age of Technology: The Digital Revolution and Schooling in America (Amazon affiliate link), which apparently discusses how historically we used to have an apprenticeship model of education, which moved to the factory model, where it’s all about training everyone the same way, and now we’re moving back to a more individualized, self-directed and flexible lifelong-learning model. Put in those terms, it seems clear that we can’t just keep tweaking; the changes are more fundamental than that.

He also asks why no one is consciously teaching kids how to read and write in linked environments — which relates back to my point about learning to traverse non-linear spaces.

But the onus shouldn't (and can't) be all on the teacher. They need a structure that supports them.

But as with learning networks and digital tools (Facebook, Twitter, blogs, RSS, Scribd, Flickr, TumblrMashable, ...), the structures too keep changing under their feet. Blackboard, Moodle, Udemy, Instructure (to pick out some old and some new).

It's perhaps easier when the structure is purely online. (In the U.S., the Keeping Pace with K-12 online learning 2010 report tells us that state virtual schools or state-led online learning initiatives now exist in 39 states, and 27 states plus Washington DC have at least one full-time online school operating statewide.) But mostly online learning occurs side-by-side with face-to-face learning. (The report estimates that about 50% of all districts are operating or planning online and blended learning programs.)

A report profiling 40 schools that have blended-learning programs has found six basic models of blending learning:

  • Face-to-face-driver: face-to-face teachers deliver most of the curricula. The physical teacher deploys online learning on a case-by-case basis to supplement or remediate, often in the back of the classroom or in a technology lab.
  • Rotation: within a given course, students rotate on a fixed schedule between learning online in a one-to-one, self-paced environment and sitting in a classroom with a traditional face-to-face teacher. The face-to-face teacher usually oversees the online work
  • Flex: uses an online platform to deliver most of the curricula. Teachers provide on-site support on a flexible and adaptive as-needed basis through in-person tutoring sessions and small group sessions.
  • Online-lab: relies on an online platform to deliver the entire course but in a lab environment. Usually these programs provide online teachers. Paraprofessionals supervise, but offer little content expertise.
  • Self-blend: encompassing any time students choose to take one or more courses online to supplement their traditional school’s catalog. The online learning is always remote.

As we can see (and as was also discussed in the Keeping Pace report), online learning is not about making the teacher redundant! No surprise when you consider that a major aspect of online learning (and its attraction for many students) is that it personalizes learning.

This is also echoed at university level. A spokesman for the Pearson Foundation, discussing a survey of over 1,200 college students, said: "There seems to be this belief among students that tablets are going to fundamentally change the way they learn and the way they access what they are learning. Students see these devices as a way to personalize learning." Students don't see tablets as means of accessing digital textbooks as much as a means to access e-mail, manage assignments and schedules, and read non-textbook materials such as study aids, reports, and articles. (You might also like to read about one university's experience introducing iPad's into the classroom)).

In the same way, a study involving students in China and Hong Kong found that Facebook was being used to let them connect with faculty and other students, provide comments to peers/share knowledge, share feelings with peers, join Groups established for subjects, share course schedules and project management calendars, and (via educational applications) organize learning activities.

So one aspect of online learning is management and collaboration.

Of course online learning is not only about personalizing learning. It's also about broadening access to quality educational resources. The open course movement is perhaps more advanced at university level (exemplified by MIT's OpenCourseWare (updated: now Open Education Global), Yale's Open Courses, the Open University's Learning Space), but in Iowa, schools will soon have access to wide variety of digital materials from a central repository using Pearson Education's Equella. Certainly the internet is rife with educational materials aimed at K-12, but there are great benefits from the more formal structure of such a repository.

But this wonderful cornucopia is also the biggest problem. So many resources. And so many structures, programs, digital tools. It takes a lot of time and effort to master each one, and who wants to put in that effort unless they’re sure it’s really important and going to last?

There's no good answer to that, I'm afraid. We are living in a time of transition, and this is the price of that.

But we can try and develop our own 'rules of engagement'. Something to filter out the deluge of new tools and new systems and new resources.

When doing so, we need to consider the two principal, and different, issues involved in this revolution in information delivery systems, which should be kept quite distinct when thinking about them (however muddled together they will be in application). One concerns their use in learning — do textbooks need 'bells and whistles' to be more effective means of learning? what is the best way to frame this information so that students (at their grade level) can understand and remember it? This is the how question. For this we need to work out the different strategies that each delivery system needs to be an effective learning tool, and the different contexts in which each one is effective.

The other issue concerns the world for which the education system is supposedly training students. How is information delivered today? How do people work with information? This is the what question; the issue of content — though not in the 'core knowledge' sense.

Although, part of the issue does concern this question of core content. Because the fact is, however we may pine for the days when we all knew the same things, read the same books, could recite the same poems (no, we never really had those days; we just had smaller groups), there is too much information in the world for that to be possible. And society needs the diversity of many people knowing different things, because there's too much for us all to know the same thing. So what we need from our education system — and I know it's a truism but there you go, doesn't make it less true — is for our students to learn how to learn. Which means they need to know the best strategies for learning from the various information delivery systems they're going to be trying to learn from.

And there's something else, that stems from this point that there's too much for us all to know the same thing. We have this emphasis on doing well as an individual — individuals graduate, become famous, get Nobel Prizes, get remembered in the history books. But science and scholarship, and politics and community development, have always benefited from the stimulation of different minds. The complexity of the world today means that we need that more than ever. The complexity of science today means that most discoveries are the results of a team rather than a single person. Even in mathematics, the archetypal home of the solitary genius.

For example, the Polymath Project began with one mathematical genius who decided to take one of the complex mathematical problems he had struggled to solve to his blog. He threw it out there. And readers threw ideas back. Since then, several papers have been published in journals under the collective name DHJ Polymath.

An example of the open science movement (see the Open Knowledge Foundation and the Open Science Summit), raising the question — is the ‘traditional’ way of doing science really the best way? Let’s bear in mind that the ‘traditional’ way is not in fact all that traditional. It’s a product of its times (and rather recent times at that). We shouldn’t confuse the process of scientific thinking with the institutionalization of science. Proponents of Open Science argue that the advent of the internet can break right through the inertia of the institutions, can allow collaboration and the processing of huge data-sets in ways that are far quicker and more efficient.

This is the world we need to educate for. Educate ourselves and our children. And the heart of it is collaboration. Which is one of the reasons we shouldn't be keeping social media out of the classroom. We just have to use it in the right way.

I began this series with Denmark allowing internet access during exams. So let's finish by returning to this issue.

As with the wider question of education, we need to ask ourselves what testing is for. First of all there's the point that, like note-taking, testing has an obvious purpose and a less obvious one. The obvious one is that it provides a measurement of how well a student knows something (we’ll get to the squirrelly ‘knows’ in a minute); the less obvious is that testing helps students learn. (For note-taking, the obvious purpose is that it provides a record; the less obvious is the same as for testing: it helps you learn.) Many tests may be (or perhaps should be) primarily for learning.

Final exams, on the other hand, are usually solely about assessment. But then we must ask, assessment of what? What do we mean by 'know'? There are topics within subjects which are 'core' — crucial details and understandings without which the subject cannot be understood — cell division in biology; atomic structure in chemistry. But there are many other details that you don't need to have in your head — but you do need to 'know' them enough so that you can find them readily, and fit them into their place readily.

Anyone who can write well and develop an argument in depth on a specialist topic in a three-hour exam period from the internet deserves to pass (I'm assuming, of course, that there are adequate guards against plagiarism!). As with course-work, access to the internet simply raises the standard.

 

These posts have all been rather a grab-bag. This is such a wide topic, with so many issues and everything is such a state of flux. To write coherently on this would require a book. Here I have simply tried to raise some issues, and point to a random diversity of articles and tools that might be of interest. Do add any others (issues, articles, tools) in the comments.

The changing nature of literacy. Part 3: Computers

This post is the third part in a four-part series on how education delivery is changing, and the set of literacies required in today’s world. Part 1 looked at the changing world of textbooks; Part 2 looked at direct instruction/lecturing. This post looks at computer learning.

The use of computers in schools and for children at home is another of those issues that has generated a lot of controversy. But like e-readers, they’re not going back in the box. Indeed, there’s apparently been a surge of iPads into preschool and kindergarten classrooms. There are clear dangers with this — and equally clear potential benefits. As always, it all depends how you do it.

But the types of guidance and restrictions needed are different at different ages. Kindergarten is different from elementary is different from middle grade is different from high school, although media reports (and even researchers) rarely emphasize this.

Media reports last year cited two research studies as evidence that home computers have a negative effect on student achievement, particularly for students from low-income households. One involved 5th to 8th students in North Carolina ; the other Romanian students aged 7 to 22.

The Romanian study concerned low-income families who won government vouchers for the purchase of a personal computer. The study found that, although there was an increase in computer skills and fluency and even an apparent increase in general cognitive ability, academic performance (in math, English, and Romanian) was negatively affected. Use of the computers was mostly focused on games, at the expense of doing homework and reading for pleasure (and watching TV).

Interestingly, children with parents who imposed rules on computer use were significantly less skilled and fluent on the computer, but no better on homework or academic achievement. On the other hand, those who had parents who imposed rules on homework retained the benefits in terms of computer skills, and the negative impact on academic achievement was significantly reduced.

Additionally, there was some evidence that younger children showed the biggest gains in general cognitive ability.

Similarly, the North Carolina study (pdf) found that students who gained access to a home computer between 5th and 8th grade tended to show a persistent decline in reading and math test scores. But these results are very specific and shouldn’t be generalized. Those who already had computers prior to the 5th grade scored significantly above average, and showed improvement over time.

An Italian study also found positive benefits of computer ownership - PISA achievement significantly correlated with 15-year-olds' use of computers at home as an educational tool. However, there seemed to be an optimal level, with the effect becoming smaller the more often they used the computer and even becoming negative if they used school computers almost every day.

The North Carolina and Romanian studies indicate that the problem appears to be when computer use knocks out more beneficial activities such as doing homework and reading for pleasure. It's unsurprising that this might be more likely to occur among children and adolescents who gain ready access to a computer after many years of "deprivation".

In Britain the e-Learning Foundation has recently come out claiming that over a million children will perform significantly worse on exams (an average grade lower) because they don’t have internet access at home. This idea is based on research showing that students who use revision materials on the internet to help them revise have an advantage over those students who don’t have access to such materials. Surely no surprise there! And no contradiction to the previous research. There is undoubtedly a lot of very good educational material on the internet, and even if you have a good teacher, getting a different take on things can help you understand more fully. If you have a poor teacher, this is even more true!

So it all comes down to how computers are being used (and what their use is knocking out, for there is only so much time in the day). Bearing on this point, two programs in the U.S. have with some apparent success introduced computers into disadvantaged homes in such a way that they support a more effective home-learning environment and thus improve academic achievement.

There’s also an argument that laptops have shown little benefit in general because the schools in which they’re used have, by and large, good teachers and good students. But the true value of laptops is for those without access to good teachers. For ten years, computers have been placed into brick walls in public places in hundreds of villages and slums in India, Cambodia and Africa, with apparently very successful results.

An extension of the project has involved British grandparents, many of them retired teachers, volunteering their time to talk, using Skype, to children in the slums and villages of India. From this has developed the model of a Self-organized learning environment (Sole), where children work in self-organized groups of four or five, exploring ideas using computers, the exploration triggered (but not constrained) by questions set by teachers.

I must admit, while I applaud this sort of thing, I have to shake my head at the surprise that this sort of activity is effective, and the comment that the students “maintain their own order”. My children had a Montessori education in their early years — in Montessori schools children habitually “self-organize” and teach themselves (with of course the teachers’ guidance, and the use of the resources provided).

But of course, it helps to have the right resources. Five years gathering data from math-tutoring programs has revealed how 10th and 11th grade students use a help button, which offers progressively more in-depth hints and eventually gives the answer to the question. Basically, most students (70-75%) strenuously resist seeking help, even after several errors. When they do eventually give in and ask for a hint, they do so only because they have given up trying to solve the problem and are aiming to cheat — 82% of those using the hint tool didn’t stop to read it, just clicked through all the hints to get to the answer.

Most recently, then, the researchers changed a geometry tutoring program so that the help tool would encourage students to reflect on their problem-solving strategies — for example, by opening a help window if a student seems to be guessing, or doesn’t seem to reading the hints. In pilot studies, the new help tutor significantly improved students’ help-seeking behavior.

But perhaps these children wouldn’t so misunderstand the use of the help button if they’d been taught in a learning environment that encouraged peer-tutoring. As any teacher knows, the best way to learn something is to teach it!

Teachable Agents software allows students to customize a virtual agent and teach it mathematics or science concepts. The agent questions, misunderstands, and otherwise learns realistically. Pilot studies of these programs have included kindergarten through to college.

Additionally, the virtual agent always explains how it came to an answer, and this seems to transfer to the student-teachers, helping them learn how to reason.

But I'd like to note (because it sounds a wonderful program) that you don’t need fancy software to harness the power of peer-tutoring. The Learning Community Project (English translation) operates in nearly 600 rural schools in Mexico and is planned to go into nearly 7000 rural and urban schools. In this model, students choose a learning project and explore it, guided by adult tutors. They then formally present the results of their inquiry to fellow students, tutors, and parents. When they have developed mastery in an area, they tutor other students who are exploring that area. The learning of students and the training of tutors builds a fund of common knowledge that is available in the community of neighboring schools.

But anyway, the message seems clear, if rather obvious: computers and the internet can be a very positive tool for learning, but, as with books and lectures, there are right ways and wrong ways of implementing these delivery systems.

In the next and lash post in this series, I'll discuss what literacy means in today's world, and the new  learning models that are being developed.

[Update: Note that some links have been removed as the linked article is no longer available]

The changing nature of literacy. Part 1: Textbooks

As we all know, we are living in a time of great changes in education and (in its broadest sense) information technology. In order to swim in these new seas, we and our children need to master new forms of literacy. In this and the next three posts, I want to explore some of the concepts, applications, and experiments that bear on this.

Apparently a Danish university is going to allow students access to the internet during exams. As you can imagine, this step arouses a certain amount of excitement from observers on both sides of the argument. But really it comes down, as always, to goals. What are students supposed to be demonstrating? Their knowledge of facts? Their understanding of principles? Their capacity to draw inferences, make connections, apply them to real-world problems?

I’m not second-guessing the answers here. It seems obvious to me that different topics and situations will have different answers. There shouldn’t be a single answer. But it’s a reminder that testing, like learning, needs to be flexible. And education could do with a lot more clear articulation of its goals.

For example, I came across an intriguing new web app called Topicmarks, that enables you to upload a text and receive an automated précis in return. On the one hand, this appalls me. How will students learn how to gather the information they need from a text if they use such tools? How can a summary constructed automatically possibly elicit the specific information you’re interested in? (Updated: this no longer appears to exist, but you can see an example at the end of this post, where I’ve appended the summary produced of a Scientific American article.)

Even if we assume it actually does a good job, it is worrying. And yet … There is too much information in the world for anyone to keep up with — even in their own discipline. There’s a reason for the spate in recent years of articles and books on how the invention of printing brought about a technological revolution — a need for new tools, such as indices, the idea of using the alphabet to order them, meaningful titles and headings, tables of contents. Because the flood of information, as we all know, requires new tools. This one (which will assuredly get better, as translation software apparently has) may have its place. Before we get all excited about the terrible consequences of automated summaries, and internet-access during exams, we should think about the world as it is today, and not the world for which the education system was designed.

The world for which the education system was designed was a simpler one, in terms of information. You gained information from people you knew, or from a book. Literacy was about being able to access the information in books.

But that’s no longer the case. Now we have the internet. We have hyperlinked texts and powerpoint slides, multimedia and social media. Literacy is no longer simply about reading words in a linear, unchanging text. Literacy is about being able to access information from all these new sources (and the ones that will be here tomorrow!).

Even our books are changing.

The simplest ‘modernized’ variant of the traditional textbook is the traditional textbook on a digital device. But e-readers are not well designed for textbook reading, which is quite different from novel reading.

A study involving 39 first-year graduate students in Computer Science & Engineering (7 women and 32 men; aged 21-53) who participated in a pilot study of the Kindle DX, found that, seven months into the study, less than 40% of the students were regularly doing their academic reading on the e-reader. Apart from the obvious – students wanted better support for taking notes, checking references and viewing figures – the really interesting thing was the insight it gave into how students use academic texts.

In particular, students constantly switch between reading techniques, such as skimming illustrations or references before reading the text. They also use physical cues to help them remember where certain information was, or even to remember the information itself (this is something classic and medieval scholars relied on heavily; I have spoken of this in the context of the art of memory). Both of these are problematic with the Kindle.

Consequently, in a survey of 655 college students, 75% said that, if the choice was entirely theirs, they would select a print textbook. (The article also lists some of the digital textbook providers, and some open-access educational resources, if you’re interested).

But e-readers are the future. (Don’t panic! This is not an either/or situation. There will still be a place for physical books — but that place is likely to become more selective.) The survey found a surge in the number of students who have a dedicated e-reader (39% vs 19% just five months earlier). Another, more general survey of over 1,500 end users in the US, the UK, Japan, India, Italy, and China, found that the amount of time spent reading digital texts now nearly equals time spent reading printed materials.

Nearly everyone (94%) who used tablets (such as iPads) either preferred reading digital texts (52%) or found them as readable as print (42%). In contrast, 47% of laptop users found digital text harder to read than print. While 40% of respondents had no experience of e-readers, this varied markedly by country. Surprisingly, the country with the highest use of e-readers was China. Rates in the US and the UK were comparable (57% and 56% had no experience of e-readers).

The age-group unhappiest about reading on screen were 40- to 54-year-olds. Falling into that age-group myself, I speculate that this has something to do with the way our eyesight is beginning to fail! We’re not at the point of needing large font (or at least of accepting that we need it), but we find increasing difficulty in comfortably reading in conditions that are less than optimal.

So, we have a mismatch between e-readers and the way textbooks are read. There’s also the issue of the ‘textbook model’. Many think it’s broken. Because of their cost, because some subjects move so fast (and publishing moves so slowly) that they’re out of date before they come out, even because of their weight. And then there’s the question of whether students actually learn from textbooks, and how relevant they are to student learning today.

This is reflected in various attempts to revolutionize the textbook, from providing interactive animations (see, for example, a new intro biology textbook) to the ‘learning space’ being developed (again in biology — is this just happenstance, or is biology leading the way in this?). Here information is organized into interconnected learning nodes that contain all of the baseline information a textbook would include, plus supplemental material and self-assessments. So there are videos, embedded quizzes, information flow between students and the teacher.

One aspect of this I find particularly interesting: both students and teachers can write new nodes. So for example, in a pilot of this biology program, 19 students wrote 130 new nodes in one semester — clearly demonstrating their engagement in the course, and hopefully their much greater learning.

Another attempt at providing more user-control is that of “flexbooks”. Flexbooks for K-12 classes enables teachers to easily select specific chapters from the content on the website, and put them together into a digital textbook in three formats (pdf, openreader, and html — this format is interactive, with animations and videos). You can also change the content itself.

Multimedia is of course all the rage. But, as I discuss in my book on effective note-taking, it’s not enough to simply provide illustrations or animations — it has to be done in the right way. Not only that, but the reader needs to know how to use them. Navigating a ‘learning space’ or multimedia environment is not the same as reading a book, and it’s not something our book-literacy skills directly transfer to.

And it’s not only a matter of textbooks. Textbooks have their own particular rules, but any expositional text has the potential to be recreated as a multimedia experience.

Here, for example, is a “video-book”: Learning From YouTube , is "large-scale online writing that depends upon video, text, design, and architecture for its meaning making." The author, Alexandra Juhasz, talks about how “common terms of scholarly writing and publishing must be reworked, modified, or scare-quoted to most effectively describe and traverse the "limits of scholarship" of the digital sphere.”

She talks about how scholars should ask which book medium is best suited for their study (rather than simply assuming it must be a traditional book). Reading and writing practices are changing on the internet — rather than deploring or embracing the new habits, we should ask ourselves which practices are most appropriate for the specific material.

She also talks about the need to educate readers in new ways of doing things. We don’t want to simply equate internet use with surfing, with hyperactive jumping and skimming. That has a place, but the internet is also home to material (like her video-book) that requires lengthy and deep study.

And of course there’s an obligation on the net to actually provide the deeper information (at least in the form of links) that in print books we can fob off with references and recommended reading lists.

Note this point: scholars should ask which book medium is best suited for their study. It applies to textbooks too. Books are not being transformed into something different; they are blossoming. There is still room for straight texts. Nor should it — it most certainly should not — be assumed that throwing a bunch of animated videos into the mix is enough to turn a book into an exciting new learning experience. As with books, some are going to be created that are effectively presented, and some are not.

I’ve said we should think of this as a blossoming of the book concept. But are these new, blossoming variants, still books? Where are we going to draw the lines? Video-books and learning spaces are more like courses than books. Indeed, the well-known textbook publisher Pearson has recently partnered with the lecture capture provider Panopto — another sign of the movement from traditional textbooks to cloud-based “educational ecosystems”.

Perhaps it’s premature to try and draw any lines. Let’s consider the oral equivalent of textbooks: lecturing, or as it’s known at K-12 level, direct instruction. My post tomorrow will look at that.

 


Topicmarks summary (Scientific American article)

In humans, brain size correlates, albeit somewhat weakly, with intelligence, at least when researchers control for a person's sex (male brains are bigger) and age (older brains are smaller). Many modern studies have linked a larger brain, as measured by magnetic resonance imaging, to higher intellect, with total brain volume accounting for about 16 percent of the variance in IQ. But, as Einstein's brain illustrates, the size of some brain areas may matter for intelligence much more than that of others does. Studying the brains of 47 adults, Haier's team found an association between the amount of gray matter (tissue containing the cell bodies of neurons) and higher IQ in 10 discrete regions, including three in the frontal lobe and two in the parietal lobe just behind it. In its survey of 146 children ages five to 18 with a range of IQs, the Cincinnati group discovered a strong connection between IQ and gray matter volume in the cingulate but not in any other brain structure the researchers examined.

In a 2006 study child psychiatrist Philip Shaw of the National Institute of Mental Health and his colleagues scanned the brains of 307 children of varying intelligence multiple times to determine the thickness of their cerebral cortex, the brain's exterior part. Over the years brain scientists have garnered evidence supporting the idea that high intelligence stems from faster information processing in the brain. Underlying such speed, some psychologists argue, is unusually efficient neural circuitry in the brains of gifted individuals. The researchers used electroencephalography (EEG), a technique that detects electrical brain activity at precise time points using an array of electrodes affixed to the scalp, to monitor the brains of 27 individuals while they took two reasoning tests, one of them given before test-related training and the other after it. The results suggest that gifted kids' brains use relatively little energy while idle and in this respect resemble more developmentally advanced human brains.

Some researchers speculate that greater energy efficiency in the brains of gifted individuals could arise from increased gray matter, which might provide more resources for data processing, lessening the strain on the brain. In a 2003 trial psychologist Jeremy Gray, then at Washington University in St. Louis, and his colleagues scanned the brains of 48 individuals using functional MRI, which detects neural activity by tracking the flow of oxygenated blood in brain tissue, while the subjects completed hard tasks that taxed working memory. The researchers saw higher levels of activity in prefrontal and parietal brain regions in the participants who had received high scores on an intelligence test, as compared with low scorers. Lee and his co-workers measured brain activity in 18 gifted adolescents and 18 less intelligent young people while they performed difficult reasoning tasks. These tasks, once again, excited activity in areas of the frontal and parietal lobes, including the anterior cingulate, and this neural commotion was significantly more intense in the gifted individuals' brains.

Reading for Study

Reading is a deceptive skill, for it is not a single process, but a number of processes. Thus, while you might be a fluent reader, in that you can swiftly and easily decode the letter-markings, and quickly access the meaning of the words, that doesn't mean you're a skilled reader of informational texts.

Reading effectively for information or instruction, unlike reading a story, needs to be a very active process, for comprehension is far more difficult than it is in the familiar format of a story. That's why so-called 'speed reading' can be so problematic.

Reading "actively" involves:

  • thinking about what you’re reading
  • asking yourself questions about it
  • trying to relate it to information you already know.

How well you do this depends in part on your understanding of the topic. Thus, you may be a skilled reader of philosophy texts, but be completely at a loss when confronted by a physics text.

Nor is it only a matter of content knowledge. How you go about your active reading also depends in part on the subject you're reading in. Reading scientific texts, for example, is very different from reading a history text; both require a different approach — different skills — compared to reading an economics text. And reading in a foreign language is, of course, different again.

Reading for study is difficult to separate from note-taking, for the active processing you need to do is helped considerably by note-taking strategies. The two go hand in hand, and more so the more difficult the text is.

Improving your reading skills, then, involves not simply improving reading skills themselves, but also:

  • recognizing the different processes involved in reading, so that you can accurately pinpoint the source of your comprehension difficulties (for example, it may be simply a jargon issue - unfamiliarity with the specialist vocabulary used)
  • increasing your knowledge and understanding of the topic
  • improving your note-taking skills, so that you know the best way to approach different types of text, to organize the information for better understanding.

 

Working memory, expertise & retrieval structures

In a 1987 experiment (1), readers were presented with a text that included one or other of these sentences:

or

Both texts went on to say:

After reading the text, readers were asked if the word sweatshirt had appeared in the story. Now here is the fascinating and highly significant result: those who read that John had put on a sweatshirt responded “yes” more quickly than those who had read that he had taken off his sweatshirt.

Why is this so significant? Because it tells us something important about the reading process, at least in the minds of skilled readers. They construct mental models. If it was just a matter of the mechanical lower-order processing of letters and words, why would there be a difference in responses? Neither text was odd — John could as well have put on a sweatshirt before going out for a jog as taken it off — so there shouldn’t be a surprise effect. So what is it? Why is the word sweatshirt not as tightly / strongly linked in the second case as it is in the first? If they were purely textbase links (links generated by the textbase itself), the links should be equivalent. The difference in responses implies that the readers are making links with something outside the textbase, with a mental model.

Mental models, or as they are sometimes called in this context, situation models, are sometimes represented as lists of propositions, but in most cases it seems likely that they are actually analogue in nature. Thus the real world should be better represented by the situation model than by the text. Moreover, a spatial situation model will be similar in many ways to an image, with all the advantages that that entails.

All of this has relevance to two very important concepts: working memory and expertise.

Now, I’m always talking about working memory. This time I want to discuss not so much the limited attentional capacity that is what we chiefly mean by working memory, but another, more theoretical concept: the idea of long-term working memory.

Think about reading. To make sense of the text you need to remember what’s gone before — this is why working memory is so important for the reading process. But we know how limited working memory is; it can only hold a very small amount — is it really possible to hold all the information we need to make sense of what we’re reading? Shouldn’t there be constant delays as we access needed information from long-term memory? But there aren’t.

It’s suggested that the answer lies in the use of long-term working memory, a retrieval structure that keeps a network of linked propositions readily available.

Think about when you are studying / reading a difficult text in a subject you know well. Compare this to studying a difficult text in a subject you don’t know well. In the latter case, you may have to painfully backtrack, checking earlier statements, trying to remember what was said before, trying to relate what you are reading to things you already know. In the former case, you seem to have a vastly expanded amount of readily accessible relevant information, from the text itself and from your long-term memory.

The connection between long-term working memory and expertise is obvious. And expertise has already been conceptualised in terms of retrieval structures (see for example my article on expertise). In other words, you can increase your working memory in a particular domain by developing expertise, and the shortest route to developing expertise is to concentrate on building effective retrieval structures.

One of the areas where this is particularly crucial is that of reading scientific texts. Now we all know that scientific texts are much harder to process than, for example, stories. And there are several reasons for that. One is the issue of language: any science has its own technical vocabulary and you won't get far without knowing it. But another reason, far less obvious to the untutored, concerns the differences in structure — what may be termed differences of genre.

Now it might seem self-evident that stories are far simpler than science, than any non-fiction texts, and indeed a major distinction is usually made between narrative texts and expository texts, but it’s rather like the issue of faces and other objects. Are we specially good at faces because we're 'designed' to be (i.e., we have special 'expert' modules for processing faces)? Or is it simply that we have an awful lot of practice at it, because we are programmed to focus on human faces almost as soon as we are born?

In the same way, we are programmed for stories: right from infancy, we are told stories, we pay attention to stories, we enjoy stories. Stories have a particular structure (and within the broad structure, a set of sub-structures), and we have a lot of practice in that structure. Expository texts, on the other hand, don't get nearly the same level of practice, to the extent that many college students do not know how to handle them — and more importantly, don't even realize that that is what they're missing: a retrieval structure for the type of text they're studying.

References

Glenberg, A.M., Meyer, M. & Lindem, K. 1987. Mental models contribute to foregrounding during text comprehension. Journal of Memory and Language, 26, 69-83.

Reading

  • Poor readers may be divided into two groups: those whose problems stem primarily from an innate disruption in their neural systems, and those whose problems stem from deprivation.
  • In both cases, early intervention is very important.
  • In both cases, training specifically aimed at activating or strengthening specific neural circuitry is required.
  • Although individuals will have different impairments requiring instructional programs focusing on different skill components, an effective reading program will need to involve phonemic awareness training.
  • Encouragingly, there are now a number of training programs that have had positive results with retraining the brains of dyslexics.
  • Reading problems are more common in boys, and it appears that the genders develop different neural connections at different times. It may be that current reading programs favor the pattern of development in girls (I'm speculating here).

Types of reading disability

A longitudinal study that used imaging to compare brain activation patterns has identified two types of reading disability:

  • a primarily inherent type with higher cognitive ability (poor readers who compensate for disability), and
  • a more environmentally influenced type with lower cognitive skills and attendance at more disadvantaged schools (persistently poor readers).

It seems, compensated poor readers are able to overcome some of the disability, improving their ability to read words accurately and to understand what they read, while persistently poor readers continue to experience difficulties.Brain activation patterns showed a disruption in the neural systems for reading in compensated readers (specifically, a relative underactivation in posterior neural systems for reading located in left parietotemporal and occipitotemporal regions), while persistently poor readers had the neural circuitry for reading real words, but it had not been properly activated.These results point to the importance of providing early interventions aimed at stimulating both the ability to sound out words and to understand word meanings for children at risk for reading difficulties associated with disadvantage.

The importance of childhood environment is also emphasized by a study of older adults that found that the larger a person's head in adulthood, the less likely their cognitive abilities are to decline in later years. Head size in adulthood is determined in infancy: during the first year of life, babies' brains double in size, and by the time they are six, their brain weight has tripled. These, it appears, are the crucial years for laying down brain cells and neural connections — pointing to the importance of providing both proper nourishment and intellectual stimulation in these early years.

Impaired reading skills are found in some 20% of children - in boys, more than girls. Dyslexia - a disability which is found across all socioeconomic classes and all ethnicities - may be thought of as the low end of a continuum of reading ability. Training that helps dyslexics can also help those whose problems with reading are of lesser magnitude.

Gender differences

It has been suggested that the reason reading disabilities are more common among boys is that teachers simply tend to recognize the problem in boys more often, but it does now seem clear that boys really do have more reading difficulties than girls. Analysis of four large-scale studies of reading in children, involving some 9,800 children, found about 20% of the boys had reading disabilities compared with about 11% of the girls.

An EEG study of gender differences in the emerging connectivity of neural networks associated with phonological processing, verbal fluency, higher-level thinking and word retrieval (skills needed for beginning reading) in preschoolers confirms different patterns of growth in building connections between boys and girls. These differences point to the different advantages each gender brings to learning to read, and suggests the need for different emphases in teaching boys and girls to read. Boys favor vocabulary sub-skills needed for comprehension while girls favor fluency and phonic sub-skills needed for the mechanics of reading.

Reading programs

No educational system in the world has mastered the problem of literacy; every existing system produces an unacceptably high level of failures. So, we cannot point to a particular program of instruction and say, this is the answer. Indeed, I am certain that such an aim would be foredoomed to failure - given the differences between individuals, how can anyone believe that there is some magic bullet that will work on everyone?

Having said that, we have a far greater idea now of the requirements of an effective literacy program. One of the reasons for that is the work of the National Reading Panel in the United States, which spent some three years analyzing a huge number of studies into various aspects of reading instruction. I have summarized their findings here.

Direct instruction in specific components of reading skills is clearly only part, albeit a major part, of improving literacy. There is also the role of providing a stimulating environment, most particularly in the very early years. Little is known about the precise nature of the stimulation that would be most productive for providing the foundation for later literacy, but we may speculate that, apart form the obvious (being read to, etc), music may also be beneficial. Although I am not aware of any studies specifically looking at the possible benefits of music training for developing reading skills in children, recent research does provide evidence that giving children music instruction benefits their verbal memory.

Dyslexia

Dyslexics who are identified at a very early age (1st grade or earlier) have significantly fewer problems in learning to read than those who are not diagnosed until later. About 74%of the children with dyslexia who are poor readers in 3rd grade remain poor readers in the 9th grade, and often can’t read well as adults either. The earlier dyslexia is recognized and proper instruction given the better. Dyslexia tends to run in families.

Other research also points to the importance of early intervention.The brains of children with learning problems not only appear to develop more slowly than those of their unaffected counterparts but also actually may stop developing around the time of puberty's onset. In the study, children with impairments started out about three years behind, but their rate of improvement was very similar to that of the children without impairments — until around 10 years, when further development in the children with learning problems stopped.

What causes dyslexia?

We always want simple answers, but, as so often, it seems likely that there is no single, simple answer to the problem of dyslexia. Imaging studies have revealed that different phonological skills relate to activity in different parts of the brain when children read.There are probably several neurobiological profiles that correspond to different subtypes of dyslexia, each associated with varying deficits in different phonological skills.

For example, a key predictor of reading problems is lack of a skill called "rapid naming" - basically, being able to quickly retrieve the names of very familiar letters and numbers. It's been suggested that inability to rapidly name, and inability to differentiate between sounds, may be separate causes of dyslexia.

Interestingly, confirming a very old theory of dyslexia, it seems that normally developing readers learn to suppress the visual images reported by the right hemisphere of the brain - these images potentially interfere with input from the left. Dyslexic readers also appear to process auditory and visual sensory cues differently than do normal readers. During an auditory matching task, dyslexic readers showed increased activity in the visual pathway of the brain, while that same region deactivated in normal readers.

The tendency for dyslexia to run in families points to a genetic aspect. It has been found that brain images of people with a family history of dyslexia show significant reduction of gray matter in centers associated with language processing.

How to help dyslexics

A number of educational tools have been developed to teach people with dyslexia to read. Remembering that dyslexia is a label for a variety of different skill deficits, it is not surprising that an effective training program is not the same for everyone. The dyslexic person’s individual strengths and weaknesses must be assessed to find the program that will help best.

What is exciting is the converging evidence in recent years that it is indeed possible to re-train dyslexic brains. Clearly, the earlier the better, but one encouraging recent study found clear evidence for the benefits of a comprehensive reading program for dyslexic children aged 11-12 years. The study mapped the brain activation patterns of dyslexic children and good readers of the same age during two types of reading tests: phoneme mapping (which tests the ability to make correct associations between letters or letter combinations and sounds in nonsense words - e.g., if oa in ploat stands for the same sound as ow in crow) and morpheme mapping (having to decide if one word comes from another word - e.g., builder and build (yes); corner and corn (no)).

Both groups of children were found to use the same specific parts of their brains to perform the reading tasks, however, the activation of these regions was much weaker in the dyslexic children. The children with dyslexia then received a three-week training program based on principles outlined by the National Reading Panel Research findings of the NRP). After this program the levels of brain activation were found to be essentially the same in the two groups.The improvement in activation in the dyslexics was mirrored in improved reading scores.

Another recent study used an interactive computer game called MovingToRead (MTR) to significantly improve reading skills in poor second-grade readers within three months by practicing left-right movement discrimination for 5 to 10 minutes once or twice a week. It has been suggested that immature motion pathways — the circuit of neurons that helps readers determine the location of letters of a word and words on a page — may be related to reading problems in children. The therapy appears to be most effective with second-graders (age 7).

Other studies, such as Fast ForWord, and the Lindamood Phoneme Sequencing program (LiPS), also appear to have had good results. The point is not so much that any one specific program is the answer. Remember that different dyslexics will have different impairments, and accordingly, different programs will be effective for different individuals. Having said that, there are some common aspects to these programs. In particular, any such program should emphasize phoneme awareness.

Research from the National Reading Panel

  • A meta-analysis of the research on phonemic awareness training showed quite clearly the benefits of this technique, as a component of a successful reading program.
  • Similarly, the detailed analysis of many studies involving phonics instruction revealed that systematic phonics instruction produces significant benefits for students in kindergarten through 6th grade and for children having difficulty learning to read.
  • However, systematic phonics instruction requires phonemic awareness training to be effective, and, like phonemic awareness, must be only one component of a reading program — it is not sufficient in itself.
  • A review of the research also found that guided repeated oral reading procedures had a significant and positive impact on word recognition, fluency, and comprehension across a range of grade levels.
  • There is still insufficient research evidence obtained from studies of high methodological quality to support the idea that having students engage in independent silent reading with minimal guidance or feedback improves reading achievement, including fluency.
  • The available data do suggest that independent silent reading is not an effective practice when used as the only type of reading instruction to develop fluency and other reading skills, particularly with students who have not yet developed critical alphabetic and word reading skills.
  • The research done in vocabulary instruction and text comprehension was insufficient to enable the Panel to carry out the type of meta-analysis done for phonemic awareness and phonics instruction. The Panel did however make various recommendations regarding specific strategies on the basis of their analysis of the research.

Introduction

In 1997, the U.S. Congress asked the Director of the National Institute of Child Health and Human Development (NICHD) at the National Institutes of Health, in consultation with the Secretary of Education, to convene a national panel to assess the effectiveness of different approaches used to teach children to read. For over two years, the National Reading Panel reviewed research-based knowledge on reading instruction and held open panel meetings in Washington, DC, and regional meetings across the United States. On April 13, 2000, the NRP concluded its work and submitted "The Report of the National Reading Panel: Teaching Children to Read."

Below are edited excerpts from the report, regarding their findings on a variety of reading instruction strategies.

Phonemic Awareness

Phonemes are the smallest units composing spoken language. For example, the words “go” and “she” each consist of two sounds or phonemes. Instruction in phonemic awareness (PA) involves teaching children to focus on and manipulate phonemes in spoken syllables and words. PA instruction should not be confused with phonics instruction (see below), or with auditory discrimination, which refers to the ability to recognize whether two spoken words are the same or different.

An extensive and rigorous analysis of studies involving PA training found that teaching children to manipulate phonemes in words was highly effective under a variety of teaching conditions with a variety of learners across a range of grade and age levels and that teaching phonemic awareness to children significantly improves their reading more than instruction that lacks any attention to PA.

The evidence seems very clear that PA training caused improvement in students’ phonemic awareness, reading, and spelling. PA instruction also helped normally achieving children learn to spell, but was not effective for improving spelling in disabled readers.

The characteristics of PA training found to be most effective in enhancing PA, reading, and spelling skills included:

  • explicitly and systematically teaching children to manipulate phonemes with letters,
  • focusing the instruction on one or two types of phoneme manipulations rather than multiple types,
  • teaching children in small groups.

It is important to note that PA instruction is a component of a successful reading program, not a complete reading program.

It is also important to note that there are many ways to teach PA effectively, and that the motivation of both students and their teachers is a critical ingredient of success.

Phonics instruction

Phonics instruction is a way of teaching reading that stresses the acquisition of letter-sound correspondences and their use in reading and spelling. The primary focus of phonics instruction is to help beginning readers understand how letters are linked to sounds (phonemes) to form letter-sound correspondences and spelling patterns and to help them learn how to apply this knowledge in their reading. Phonics instruction may be provided systematically or incidentally. A variety of systematic approaches are listed below. In incidental phonics instruction, the teacher simply highlights particular elements opportunistically when they appear in text.

The detailed analysis of studies involving phonics instruction revealed that systematic phonics instruction produces significant benefits for students in kindergarten through 6th grade and for children having difficulty learning to read.

The ability to read and spell words was enhanced in kindergartners who received systematic beginning phonics instruction. First graders who were taught phonics systematically were better able to decode and spell, and they showed significant improvement in their ability to comprehend text. Older children receiving phonics instruction were better able to decode and spell words and to read text orally, but their comprehension of text was not significantly improved.

Systematic synthetic phonics instruction also had a positive and significant effect on disabled readers’ reading skills. Additionally, systematic synthetic phonics instruction was significantly more effective in improving low socioeconomic status children’s alphabetic knowledge and word reading skills than instructional approaches that were less focused on these initial reading skills.

Across all grade levels, systematic phonics instruction improved the ability of good readers to spell. The impact was strongest for kindergartners and decreased in later grades. For poor readers, the impact of phonics instruction on spelling was small.

Although conventional wisdom has suggested that kindergarten students might not be ready for phonics instruction, this assumption was not supported by the data. The effects of systematic early phonics instruction were significant and substantial in kindergarten and the 1st grade, indicating that systematic phonics programs should be implemented at those age and grade levels.

While the findings provide converging evidence that explicit, systematic phonics instruction is a valuable and essential part of a successful classroom reading program, there is a need to be cautious in giving a blanket endorsement of all kinds of phonics instruction. In particular, to be able to make use of letter-sound information, children need phonemic awareness. Programs that focus too much on the teaching of letter-sound relations and not enough on putting them to use are unlikely to be very effective. Systematic phonics instruction is only one component—albeit a necessary component—of a total reading program; systematic phonics instruction should be integrated with other reading instruction in phonemic awareness, fluency, and comprehension strategies to create a complete reading program. Unfortunately, there is as yet insufficient research to tell us exactly how phonics instruction can be most effectively incorporated into a successful reading program.

Phonics Instructional Approaches

Analogy Phonics —Teaching students unfamiliar words by analogy to known words (e.g., recognizing that the rime segment of an unfamiliar word is identical to that of a familiar word, and then blending the known rime with the new word onset, such as reading brick by recognizing that -ick is contained in the known word kick, or reading stump by analogy to jump).

Analytic Phonics—Teaching students to analyze letter-sound relations in previously learned words to avoid pronouncing sounds in isolation.

Embedded Phonics—Teaching students phonics skills by embedding phonics instruction in text reading, a more implicit approach that relies to some extent on incidental learning.

Phonics through Spelling—Teaching students to segment words into phonemes and to select letters for those phonemes (i.e., teaching students to spell words phonemically).

Synthetic Phonics —Teaching students explicitly to convert letters into sounds (phonemes) and then blend the sounds to form recognizable words.

Fluency

Fluency is one of several critical factors necessary for reading comprehension. Despite its importance as a component of skilled reading, fluency is often neglected in the classroom. Reading practice is generally recognized as an important contributor to fluency. Two instructional approaches, each of which has several variations, have typically been used to teach reading fluency:

  • guided repeated oral reading - encourages students to read passages orally with systematic and explicit guidance and feedback from the teacher
  • independent silent reading - encourages students to read silently on their own, inside and outside the classroom, with minimal guidance or feedback

On the basis of a detailed analysis of the available research that met NRP methodological criteria, the Panel concluded that guided repeated oral reading procedures that included guidance from teachers, peers, or parents had a significant and positive impact on word recognition, fluency, and comprehension across a range of grade levels. These studies were conducted in a variety of classrooms in both regular and special education settings with teachers using widely available instructional materials.

These results apply to all students—good readers as well as those experiencing reading difficulties. Nevertheless, there were important gaps in the research. In particular, the Panel could find no multiyear studies providing information on the relationship between guided oral reading and the emergence of fluency.

Independent Silent Reading

There has been widespread agreement that encouraging students to engage in wide, independent, silent reading increases reading achievement. Literally hundreds of correlational studies find that the best readers read the most and that poor readers read the least. These correlational studies suggest that the more that children read, the better their fluency, vocabulary, and comprehension. However, these findings are correlational in nature, and correlation does not imply causation.

Unfortunately only 14 of the studies that examined the effect of independent silent reading on reading achievement could meet the NRP research review methodology criteria, and these studies varied widely in their methodological quality and the reading outcome variables measured. Thus, a meta-analysis could not be conducted. Rather, the 14 studies were examined individually and in detail to identify converging trends and findings in the data.

With regard to the efficacy of having students engage in independent silent reading with minimal guidance or feedback, the Panel was unable to find a positive relationship between programs and instruction that encourage large amounts of independent reading and improvements in reading achievement, including fluency.

In other words, even though encouraging students to read more is intuitively appealing, there is still not sufficient research evidence obtained from studies of high methodological quality to support the idea that such efforts reliably increase how much students read or that such programs result in improved reading skills.

The available data do suggest that independent silent reading is not an effective practice when used as the only type of reading instruction to develop fluency and other reading skills, particularly with students who have not yet developed critical alphabetic and word reading skills.

Comprehension

Vocabulary Instruction

The importance of vocabulary knowledge has long been recognized in the development of reading skills. For various reasons, a formal meta-analysis could not be conducted. Instead the vocabulary instruction database was reviewed for trends across studies. Fifty studies dating from 1979 to the present were reviewed in detail. There were 21 different methods represented in these studies.

The studies reviewed suggest that vocabulary instruction does lead to gains in comprehension, but that methods must be appropriate to the age and ability of the reader.

The following approaches appeared to be helpful:

  • learning words before reading a text
  • techniques such as task restructuring and repeated exposure (including having the student encounter words in various contexts)
  • substituting easy words for more difficult words can assist low-achieving students.
  • use of computers in vocabulary instruction was found to be more effective than some traditional methods in a few studies
  • vocabulary also can be learned incidentally in the context of storybook reading or in listening to others

The Panel concluded that:

  • vocabulary should be taught both directly and indirectly
  • repetition and multiple exposures to vocabulary items are important
  • learning in rich contexts, incidental learning, and use of computer technology all enhance the acquisition of vocabulary
  • direct instruction should include task restructuring as necessary and should actively engage the student
  • dependence on a single vocabulary instruction method will not result in optimal learning.

They also concluded that, while much is known about the importance of vocabulary to success in reading, there is little research on the best methods or combinations of methods of vocabulary instruction and the measurement of vocabulary growth and its relation to instruction methods.

Text Comprehension Instruction

Comprehension is defined as “intentional thinking during which meaning is constructed through interactions between text and reader” (Harris & Hodges, 1995). Thus, readers derive meaning from text when they engage in intentional, problem solving thinking processes. The data suggest that text comprehension is enhanced when readers actively relate the ideas represented in print to their own knowledge and experiences and construct mental representations in memory.

In its review, the Panel identified 16 categories of text comprehension instruction of which 7 appear to have a solid scientific basis for concluding that these types of instruction improve comprehension in non-impaired readers. Some of these types of instruction are helpful when used alone, but many are more effective when used as part of a multiple-strategy method. The types of instruction are:

  • Comprehension monitoring, where readers learn how to be aware of their understanding of the material;
  • Cooperative learning, where students learn reading strategies together;
  • Use of graphic and semantic organizers (including story maps), where readers make graphic representations of the material to assist comprehension;
  • Question answering, where readers answer questions posed by the teacher and receive immediate feedback;
  • Question generation, where readers ask themselves questions about various aspects of the story;
  • Story structure, where students are taught to use the structure of the story as a means of helping them recall story content in order to answer questions about what they have read; and
  • Summarization, where readers are taught to integrate ideas and generalize from the text information.

In general, the evidence suggests that teaching a combination of reading comprehension techniques is the most effective. When students use them appropriately, they assist in recall, question answering, question generation, and summarization of texts. When used in combination, these techniques can improve results in standardized comprehension tests.

Nevertheless, some questions remain unanswered. More information is needed on ways to teach teachers how to use such proven comprehension strategies. The literature also suggests that teaching comprehension in the context of specific academic areas—for example, social studies—can be effective. If this is true of other subject areas, then it might be efficient to teach comprehension as a skill in content areas.

Questions remain as to which strategies are most effective for which age groups. More research is necessary to determine whether the techniques apply to all types of text genres, including narrative and expository texts, and whether the level of difficulty of the texts has an impact on the effectiveness of the strategies. Finally, it is critically important to know what teacher characteristics influence successful instruction of reading comprehension.

References

National Institute of Child Health and Human Development. (2000). Report of the National Reading Panel. Teaching children to read: an evidence-based assessment of the scientific research literature on reading and its implications for reading instruction. Retrieved September 2, 2004 from http://www.nichd.nih.gov/publications/nrp/smallbook.htm

Novices' problems with scientific text

This is the last part in my series on understanding scientific text. In this part, as promised, I am going to talk about the difficulties novices have with scientific texts; what they or their teachers can do about it; and the problems with introductory textbooks.

The big problem for novices is of course that their lack of knowledge doesn’t allow them to make the inferences they need to repair the coherence gaps typically found in such texts. This obviously makes it difficult to construct an adequate situation model. Remember, too, that to achieve integration of two bits of information, you need to have both bits active in working memory at the same time. This, clearly, is more difficult for those for whom all the information is unfamiliar (remember what I said about long-term working memory last month).

But it’s not only a matter a matter of having knowledge of the topic itself. A good reader can compensate for their lack of relevant topic knowledge using their knowledge about the structure of the text genre. For this, the reader needs not only to have knowledge of the various kinds of expository structures, but also of the cues in the text that indicate what type of structure it is. (see my article on Reading scientific text for more on this).

One of the most effective ways of bringing different bits of information together is through the asking of appropriate questions. Searching a text in order to answer questions, for example, is an effective means of improving learning. Answering questions is also an effective means of improving comprehension monitoring (remember that one of the big problems with reading scientific texts is that students tend to be poor at judging how well they have understood what was said).

One of the reasons why children typically have pronounced deficits in their comprehension monitoring skills when dealing with expository texts, is that they have little awareness that expository texts require different explanations than narrative texts. However, these are trainable skills. One study, for example, found that children aged 10-12 could be successfully taught to use “memory questions” and “thinking questions” while studying expository texts (Elshout-Mohr & van Daalen-Kapteijns, 2002).

Moreover, the 1994 study found that when the students were trained to ask questions intended to access prior knowledge/experience and promote connections between the lesson and that knowledge, as well as questions designed to promote connections among the ideas in the lesson, their learning and understanding was better than if they were trained only in questions aimed at promoting connections between the lesson ideas only (or if they weren’t trained in asking questions at all!). In other words, making explicit connections to existing knowledge is really important! You shouldn’t just be content to consider a topic in isolation; it needs to be fitted into your existing framework.

College students, too, demonstrate limited comprehension monitoring, with little of their self-questioning going deeply into the material. So it may be helpful to note Baker’s 7 comprehension aspects that require monitoring:

  1. Your understanding of the individual words
  2. Your understanding of the syntax of groups of words
  3. External consistency — how well the information in the text agrees with the knowledge you already have
  4. Internal consistency — how well the information in the text agrees with the other information in the text
  5. Propositional cohesiveness — making the connections between adjacent propositions
  6. Structural cohesiveness —integrating all the propositions pertaining to the main theme
  7. Information completeness — how clear and complete the information in the text is

Think of this as a checklist, for analyzing your (or your students’) understanding of the text.

But questions are not always the answer. The problem for undergraduates is that although introductory texts are presumably designed for novices, the students often have to deal not only with unfamiliar content, but also an approach that is unfamiliar. Such a situation may not be the best context for effective familiar strategies such as self-explanation.

It may be that self-explanation is best for texts that in the middle-range for the reader — neither having too little relevant knowledge, or too much.

Introductory texts also are likely to provide only partial explanations of concepts, a problem made worse by the fact that the novice student is unlikely to realize the extent of the incompleteness. Introductory texts also suffer from diffuse goals, an uneasy mix of establishing a basic grounding for more advanced study, and providing the material necessary to pass immediate exams.

A study of scientific text processing by university students in a natural situation found that the students didn’t show any deep processing, but rather two kinds of shallow processing, produced by either using their (limited knowledge of) expository structures, or by representing the information in the text more precisely.

So should beginning students be told to study texts more deeply? The researchers of this study didn’t think so. Because introductory texts suffer from these problems I’ve mentioned, in particular that of incomplete explanations, they don’t lend themselves to deep processing. The researchers suggest that what introductory texts are good for is in providing the extensive practice needed for building up knowledge of expository structures (and hopefully some necessary background knowledge of the topic! Especially technical language).

To that end, they suggest students should be advised to perform a variety of activities on the text that will help them develop their awareness of the balance between schema and textbase, with the aim of developing a large repertory of general and domain-specific schemata. Such activities / strategies include taking notes, rereading, using advance organizers, and generating study questions. This will all help with their later construction of good mental models, which are so crucial for proper understanding.

References
  • Baker, L. 1985. Differences in the standards used by college students to evaluate their comprehension of expository prose. Reading Research Quarterly, 20 (3), 297-313.
  • Elshout-Mohr, M. & van Daalen-Kapteijns, M. 2002. Situated regulation of scientific text processing. In Otero, J., León, J.A. & Graesser, A.C. (eds). The psychology of science text comprehension. Pp 223-252. Mahwah, NJ: LEA.
  • King, A. 1994. Guiding Knowledge Construction in the Classroom: Effects of Teaching Children How to Question and How to Explain. American Educational Research Journal, 31 (2), 338-368.

Reading Scientific Text

There are many memory strategies that can be effective in improving your recall of text. However, recent research shows that it is simplistic to think that you can improve your remembering by applying any of these strategies to any text. Different strategies are effective with different types of text.

One basic classification of text structure would distinguish between narrative text and expository text. We are all familiar with narrative text (story-telling), and are skilled in using this type of structure. Perhaps for this reason, narrative text tends to be much easier for us to understand and remember. Most study texts, however, are expository texts.

Unfortunately, many students (perhaps most) tend to be blind to the more subtle distinctions between different types of expository structure, and tend to treat all expository text as a list of facts. Building an effective mental model of the text (and thus improving your understanding and recall) is easier, however, if you understand the type of structure you're dealing with, and what strategy is best suited to deal with it.

Identifying structure

Five common types of structure used in scientific texts are:

  • Generalization: the extension or clarification of main ideas through explanations or examples
  • Enumeration: listing of facts
  • Sequence: a connecting series of events or steps
  • Classification: grouping items into classes
  • Comparison / contrast: examining the relationships between two or more things

Let's look at these in a little more detail.

Generalization

In generalization, a paragraph always has a main idea. Other sentences in the paragraph either clarify the main idea by giving examples or illustrations, or extend the main idea by explaining it in more detail. Here's an example:

Enumeration

Enumeration passages may be a bulleted or numbered list, or a list of items in paragraph form, for example:

Sequence

A sequence describes a series of steps in a process. For example:

Classification

In classification, items are grouped into categories. For example:

Comparison / contrast

This type of text looks at relationships between items. In comparison, both similarities and differences are studied. In contrast, only the differences are noted. For example:

[examples taken from Cook & Mayer 1988]

A study [1] involving undergraduate students inexperienced in reading science texts (although skilled readers otherwise) found that even a small amount of training substantially improved the students' ability to classify the type of structure and use it appropriately.

Let's look briefly at the training procedures used:

Training for generalization

This involved the following steps:

  • identify the main idea
  • list and define the key words
  • restate the main idea in your own words
  • look for evidence to support the main idea
    • what kind of support is there for the main idea?
    • are there examples, illustrations?
    • do they extend or clarify the main idea?

Training for enumeration

This involved the following steps:

  • name the topic
  • identify the subtopics
  • organize and list the details within each subtopic, in your own words

Training for sequence

This involved the following steps:

  • identify the topic
  • name each step and outline the details within each
  • briefly discuss what's different from one step to another

[Only these three structures were covered in training]

Most effective text structures

Obviously, the type of structure is constrained by the material covered. We can, however, make the general statement that text that encourages the student to make connections is most helpful in terms of both understanding and memory.

In light of this, compare/contrast would seem to be the most helpful type of text. Another text structure that is clearly of a similar type has also been found to be particularly effective: refutational text. In a refutational text, a common misconception is directly addressed (and refuted). Obviously, this is only effective when there is a common misconception that stands in the way of the reader's understanding -- but it's surprising how often this is the case! Incompatible knowledge is at least as bad as a lack of knowledge in hindering the learning of new information, and it really does need to be directly addressed.

Refutational text is however, not usually enough on its own. While helpful, it is more effective if combined with other, supportive, strategies. One such strategy is elaborative interrogation, which involves (basically) the student asking herself why such a fact is true.

Unfortunately, however, text structures that encourage connection building are not the most common type of structure in scientific texts. Indeed, it has been argued that "the presentation of information in science textbooks is more likely to resemble that of a series of facts [and thus] presents an additional challenge that may thwart readers' efforts to organize text ideas relative to each other".

Most effective strategies

The fundamental rule (that memory and understanding are facilitated by any making of connections) also points to the strategies that are most effective.

As a general rule, strategies that involve elaborating the connections between concepts in a text are the most effective, but it is also true that the specifics of such strategies vary according to the text structure (and other variables, such as the level of difficulty).

Let's look at how such a linking strategy might be expressed in the context of our five structures.

Generalization

Restatement in your own words -- paraphrasing -- is a useful strategy not simply because it requires you to actively engage with the material, but also because it encourages you to connect the information to be learned with the information you already have in your head. We can, however, take this further in the last stage, when we look for the evidence supporting the main idea, if we don't simply restrict ourselves to the material before us, but actively search our minds for our own supporting evidence.

Enumeration

This text structure is probably the hardest to engage with. You may be able to find a connective thread running through the listed items, or be able to group the listed items in some manner, but this structure is the one most likely to require mnemonic assistance (see verbal mnemonics and list-learning mnemonics).

Sequence

With this text structure, items are listed, but there is a connecting thread — a very powerful one. Causal connections are ones we are particularly disposed to pay attention to and remember; they are the backbone of narrative text. So, sequence has a strong factor going for it.

Illustrations particularly lend themselves to this type of structure, and research has shown that memory and comprehension is greatly helped when pictures portraying a series of steps, in a cause-and-effect chain, are closely integrated with explanatory text. The closeness is vital — a study that used computerized instruction found dramatic improvement in memory when the narration was synchronous with the animation, for example, but there was no improvement when the narration was presented either before or after the text. If you are presented with an illustration that is provided with companion text, but is not closely integrated with it, you will probably find it helpful to integrate it with the text yourself.

Classification

Classification is frequently as simple as grouping items. However, while this is in itself a useful strategy that helps memory, it will be more effective if the connections between and within groups are strong and clear. Connections within groups generally emphasize similarities, while connections between groups emphasize both similarities (between closely connected groups) and differences. Ordering groups in a hierarchical system is probably the type of arrangement most familiar to students, but don't restrict yourself to it. Remember, the important thing is that the arrangement has meaning for you, and that the connections emphasize the similarities and differences.

Compare / contrast

This type of structure lends itself, of course, to making connections. Your main strategy is probably therefore to simply organize the material in such a way as to make those connections clear and explicit.

References
  1. Cook, L.K. & Mayer, R.E. 1988. Teaching readers about the structure of scientific text. Journal of Educational Psychology, 80, 448-54.
  2. Castaneda, S., Lopez, M. & Romero, M. 1987. The role of five induced learning strategies in scientific text comprehension. The Journal of Experimental Education, 55(3), 125–131.
  3. Diakidoy, I.N., Kendeou, P. & Ioannides, C. 2002. Reading about energy: The effects of text structure in science learning and conceptual change.