comprehension

Working memory, expertise & retrieval structures

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

After doing a few warm-up exercises, John put on his sweatshirt and began jogging.

or

After doing a few warm-up exercises, John took off his sweatshirt and began jogging.

Both texts went on to say: John jogged halfway around the lake.

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.

tags memworks: 

tags study: 

tags strategies: 

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.

References: 

Press release on the first study: http://www.physorg.com/news/2012-01-high-school-whiz-kids-comprehension.html; see also http://rrl.educ.ualberta.ca/research.html

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

tags memworks: 

tags study: 

tags problems: 

tags strategies: 

Finding the right strategy through perception and physical movement

I talk a lot about how working memory constrains what we can process and remember, but there’s another side to this — long-term memory acts on working memory. That is, indeed, the best way of ‘improving’ your working memory — by organizing and strengthening your long-term memory codes in such a way that large networks of relevant material are readily accessible.

Oddly enough, one of the best ways of watching the effect of long-term memory on working memory is through perception.

tags memworks: 

tags study: 

tags strategies: 

Should learning facts by rote be central to education?

Michael Gove is reported as saying that ‘Learning facts by rote should be a central part of the school experience’, a philosophy which apparently underpins his shakeup of school exams. Arguing that "memorisation is a necessary precondition of understanding", he believes that exams that require students to memorize quantities of material ‘promote motivation, solidify knowledge, and guarantee standards’.

tags study: 

tags strategies: 

Concept maps

Broadly speaking, a concept map is a graphic display that attempts to show how concepts are connected to each other. A concept map is a diagram in which labeled nodes represent concepts, and lines connecting them show the relationships between concepts.

There is one type of concept map you’re probably all aware of — mind maps. Mind maps are a specialized form of concept map popularized very successfully by Tony Buzan.

A mind map has four essential characteristics:

  • the subject is crystallized in a central image
  • main themes radiate from it as branches
  • the branches comprise a key image or key word
  • the branches form a connected nodal structure

The essential difference between a mind map and the more general concept map is that in a mind map the main themes are connected only to this single central image — not to each other. In a concept map, there are no restrictions on the links between concepts.

Also, the connections between concepts in a concept map are labeled — they have meaning; they’re a particular kind of connection. In a mind map, connections are simply links; they could mean anything.

Mind maps are also supposed to be very pictorial. In Buzan’s own words:

“The full power of the Mind Map is realised by having a central image instead of a central word, and by using images wherever appropriate rather than words.”

Concepts in a concept map, on the other hand, can be (and usually are) entirely verbal. But the degree to which you use words or pictures is entirely up to the user.

In fact, this insistence on images is one of the things I don’t like about mind maps (I hasten to add that there are many things I do like about mind maps). While images are certainly powerful memory aids, they are not for everyone, nor for all circumstances.

Mind maps and concept maps are really aimed at different purposes, and perhaps, different personalities.

The chief usefulness of mind mapping, I believe, is when you’re still trying to come to grips with an idea. Mindmapping is good for brainstorming, for outlining a problem or topic, for helping you sort out the main ideas.

Concept maps, on the other hand, are particularly useful further down the track, when you’re ready to work out the details, to help you work out or demonstrate all the multitudinous ways in which different concepts (and a “concept” can be anything) are connected.

Concept maps are more formal than mind maps, and are better suited to situations where the concept is to be shared with others. Mind maps are considerably more personal, and are often not readily understood by others.

Both mind maps and concept maps are good at clarifying your thoughts, but because of the greater formality of the concept map — the need to be more precise in your connections — concept maps are better at showing you exactly what you don’t understand properly.

Which is why concept maps take a while to get right!

This is a very important point that I should emphasize — hardly anyone ever gets their map (mind or concept) right the first time. In fact, if you did, you probably didn’t need to construct it! It’s the redesigning that is important.

But concept maps can come in different flavors — from the more formal, to a visual display which simply use the basic idea of nodes and links. You can see a whole bunch of proper concept maps, constructed using cmap, at http://cmex.ihmc.us/cmex/table.html . And if you’re interested in becoming a cmapper yourself, check out http://cmap.ihmc.us/ .

And here’s a couple more links to help you learn more about concept maps:
http://www.fed.cuhk.edu.hk/~johnson/misconceptions/concept_map/concept_maps.html
http://cmc.ihmc.us/CMC2004Programa.html (this one has a number of conference papers available in pdf format).

This article first appeared in the Memory Key Newsletter for October 2006

tags study: 

tags strategies: 

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.

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.

tags strategies: 

tags study: 

Understanding scientific text

In the last part I talked about retrieval structures and their role in understanding what you’re reading. As promised, this month I’m going to focus on understanding scientific text in particular, and how it differs from narrative text.

First of all, a reminder about situation models. A situation, or mental, model is a retrieval structure you construct from a text, integrating the information in the text with your existing knowledge. Your understanding of a text depends on its coherence; it’s generally agreed that for a text to be coherent it must be possible for a single situation model to be constructed from it (which is not to say a text that is coherent is necessarily coherent for you —that will depend on whether or not you can construct a single mental model from it).

There are important differences in the situation models constructed for narrative and expository text. A situation model for a narrative is likely to refer to the characters in it and their emotional states, the setting, the action and sequence of events. A situation model for a scientific text, on the other hand, is likely to concentrate on the components of a system and their relationships, the events and processes that occur during the working of the system, and the uses of the system.

Moreover, scientific discourse is rooted in an understanding of cause-and-effect that differs from our everyday understanding. Our everyday understanding, which is reflected in narrative text, sees cause-and-effect in terms of goal structures. This is indeed the root of our superstitious behavior — we (not necessarily consciously) attribute purposefulness to almost everything! But this approach is something we have to learn not to apply to scientific problems (and it requires a lot of learning!).

This is worth emphasizing: science texts assume a different way of explaining events from the way we are accustomed to use — a way that must be learned.

In general, then, narrative text (and ‘ordinary’ thinking) is associated with goal structures, and scientific text with logical structures. However, it’s not quite as clear-cut a distinction as all that. While the physical sciences certainly focus on logical structure, both the biological sciences and technology often use goal structures to frame their discussions. Nevertheless, as a generalization we may say that logical thinking informs experts in these areas, while goal structures are what novices focus on.

This is consistent with another intriguing finding. In a comparison of two types of text —ones discussing human technology, and ones discussing forces of nature — it was found that technological texts were more easily processed and remembered. Indications were that different situation models were constructed — a goal-oriented representation for the technological text, and a causal chain representation for the force of nature text. The evidence also suggested that people found it much easier to make inferences (whether about agents or objects) when human agents were involved. Having objects as the grammatical subject was clearly more difficult to process.

Construction of the situation model is thus not solely determined by comprehension difficulty (which was the same for both types of text), but is also affected by genre and surface characteristics of the text.

There are several reasons why goal-oriented, human-focused discourse might be more easily processed (understood; remembered) than texts describing inanimate objects linked in a cause-effect chain, and they come down to the degree of similarity to narrative. As a rule of thumb, we may say that to the degree that scientific text resembles a story, the more easily it will be processed.

Whether that is solely a function of familiarity, or reflects something deeper, is still a matter of debate.

Inference making is crucial to comprehension and the construction of a situation, because a text never explains every single word and detail, every logical or causal connection. In the same way that narrative and expository text have different situation models, they also involve a different pattern of inference making. For example, narratives involve a lot of predictive inferences; expository texts typically involve a lot of backward inferences. The number of inferences required may also vary.

One study found that readers made nine times as many inferences in stories as they did in expository texts. This may be because there are more inferences required in narratives — narratives involve the richly complex world of human beings, as opposed to some rigidly specified aspect of it, described according to a strict protocol. But it may also reflect the fact that readers don’t make all (or indeed, anywhere near) the inferences needed in expository text. And indeed, the evidence indicates that students are poor at noticing coherence gaps (which require inferences).

In particular, readers frequently don’t notice that something they’re reading is inconsistent with something they already believe. Moreover, because of the limitations of working memory, only some of the text can be evaluated for coherence at one time (clearly, the greater the expertise in the topic, the more information that can be evaluated at one time — see the previous newsletter’s discussion of long-term working memory). Less skilled (and younger) readers in particular have trouble noticing inconsistencies within the text if they’re not very close to each other.

Let’s return for a moment to this idea of coherence gaps. Such gaps, it’s been theorized, stimulate readers to seek out the necessary connections and inferences. But clearly there’s a particular level that is effective for readers, if they often miss them. This relates to a counter-intuitive finding — that it’s not necessarily always good for the reader if the text is highly coherent. It appears that when the student has high knowledge, and when the task involves deep comprehension, then low coherence is actually better. It seems likely that knowledgeable students reading a highly coherent text will have an “illusion of competence” that keeps them from processing the text properly. This implies that there will be an optimal level of coherence gaps in a text, and this will vary depending on the skills and knowledge base of the reader.

Moreover, the comprehension strategy generally used with simple narratives focuses on referential and causal coherence, but lengthy scientific texts are likely to demand more elaborate strategies. Such strategies are often a problem for novices because they require more knowledge than can be contained in their working memory. Making notes (perhaps in the form of a concept map) while reading can help with this.

Next month I’ll continue this discussion, with more about the difficulties novices have with scientific texts and what they or their teachers can do about it, and the problems with introductory textbooks. In the meantime, the take-home message from this is:

Understanding scientific text is a skill that must be learned;

Scientific text is easier to understand the more closely it resembles narrative text, with a focus on goals and human agents;

How well the text is understood depends on the amount and extent of the coherence gaps in the text relative to the skills and domain knowledge of the reader.

References: 

Otero, J., León, J.A. & Graesser, A.C. (eds). 2002. The psychology of science text comprehension.

tags strategies: 

tags study: 

Speed Reading

  • Speed-reading courses generally make extravagant claims that no independent research has justified.
  • However, speed-reading courses can improve your reading skills.
  • Speed-reading courses principally improve reading by teaching you how to efficiently skim.

Speed-reading techniques

Like many memory improvement courses, speed-reading programs tend to make inflated claims. Also like memory programs, most speed-reading programs proffer the same advice. In essence, speed-reading techniques involve the following components:

  • learning to see more in a single eye fixation
  • eliminating subvocalization ("saying" the words in your head as you read them)
  • using your index finger as a visual guide down the page
  • active reading

How reading works

The first thing you need to understand about reading is that it proceeds in jerks. Though we might think our eyes are traveling smoothly along the lines, this is an illusion. What happens is that the eyes gaze steadily for around 240 milliseconds (for a college student; less practiced readers take longer) and then jerk along (during which nothing is registered), then stop again. We "read" during the eye fixations.

Now the duration of these fixations is not hugely different between readers of different abilities - a first-grade child takes about 330 ms, which is not a vast difference when you consider the chasm between a first-grade reader and an educated adult. What does change significantly is the number of fixations. Thus, to read a 100-word passage, our first-grade reader takes some 183 fixations, while our college reader takes only 75. From this, it is calculated that the first-grade reader is taking in 0.55 of a word in each fixation (100/183), while the college reader is grasping 1.33 words in each fixation (100/75). And from this, the reading rate is calculated. [These figures are of course only indicative - different types of reading matter will obviously produce different figures; the degree to which comprehension is emphasized also makes a difference].

This is not, of course, the whole story. We also can pick up some information about letters on either side of the fixation point - about 10 to 11 letter positions right of the fixation point (or left, if you're reading in a script that goes from right to left) for specific letter information, and about 15 positions for information about word length.

It is these facts that set bounds on how fast a person can read. It has been calculated that, even being very generous with the figures (reducing the duration of fixation to 200 ms; using the upper limit of how many letters we can see at one time), the upper limit for reading speed would be about 900 wpm.

How speed-reading works

This, then, is one of the things speed-reading programs aim to tackle - to increase the span of letters you can see in one fixation, and to alter the number of fixations. It is not, however, clear that (a) you can in fact train people to increase this span, or (b) it would be useful to do so.

What research does show, is that speed readers, while they don't change the length of their fixations, do significantly differ from normal readers in the pattern of their jumps. One researcher concluded from the pattern of eye movements, that speed-readers are in fact skimming.

Now there is certainly nothing wrong with skimming. Indeed, it is an extremely valuable skill, and if you wish to improve your skill at skimming, then it may well be worthwhile for you to use a speed-reading program to do so. On the other hand, there is no particular evidence that such programs do anything more than modestly improve your skimming skills.

Testing speed-reading skills

One study compared expert speed-readers against other groups of superior readers. While the speed-readers were fastest (444 words per minute - a respectable speed (250 wpm is average) but nowhere near the claims made by many of these programs), their comprehension was relatively low (71%). [1]

Interestingly, the speed-readers' speed was about twice that when they knew their speed was being tested but their comprehension would not be. In other words, like the rest of us, they slowed down markedly when they wanted to understand what they were reading (and what otherwise is the point of reading something?)

Well, actually, there is one circumstance when you read and do not look to understand or retain what you read - which brings us back to skimming.

So, how did our speed-readers compare on skimming skills? Two tasks were used to assess these:

  • to pick the best title to passages presented at rates of 7500, 1500 and 300 wpm
  • to write summaries of 6000-word passages presented at 24000, 6000, 1500 and 375 wpm

The speed readers were in fact no better than the other groups at picking titles, and though they were best at writing summaries when the passages were presented at 1500 wpm, they were no better than the others at the other rates of presentation. In an extra test of recall of important details, the speed readers in fact did worst.

Reading for understanding

Please don't mistake me, I am not condemning speed-reading - merely their often extravagant claims. Learning to skim (if you have not developed this skill on your own, and many have) is clearly worthwhile. Learning not to subvocalize - yes, I think there's value in that too. I cannot speak to any research, but I know from my own experience that when I am reading slowly, either because the material demands the effort or because I wish to make the book last longer, I make myself 'hear' the words in my head. Subvocalization does slow you down - if you wish to read faster that you can speak, you need to discard the habit.

And lastly, active reading. Well, that deserves a whole chapter of its own. So for now, for those who don't know what it means, I shall simply define it. Active reading is about thinking when you read. It is about asking yourself (and the book) questions. It is about anticipating what is going to be said, and relating what you read to what you already know, and making inferences about what you've read. Active reading is about understanding, and thus it is an essential part of reading to remember.

So that too, is a very useful skill.

This article originally appeared in the July 2002 newsletter.

References: 

  • Underwood, G. & Batt, V. 1996. Reading and understanding. Oxford: Blackwell.
  • Crowder, R.G. & Wagner, R.K. 1992. The Psychology of Reading. 2nd ed. Oxford University Press.
  1. Carver, R.P. 1985. How good are some of the world's best readers? Reading Research Quarterly, 20, 389-419.

tags study: 

Context & the conditionalization of knowledge

Context is absolutely critical to successful communication. Think of the common experience of being a stranger at a family gathering or a meeting of close friends. Even familiar words and phrases may take on a different or additional meaning, among people who have a shared history. Many jokes and comments will be completely unintelligible, though you all speak the same language.

American anthropologist Edward Hall makes a useful distinction between ‘High context’ and ‘Low context’ communications. Your family gathering would be an example of a high context situation. In this setting, much of the meaning is carried in the speakers, their relationships, their knowledge of each other. In a low context situation, on the other hand, most of the meaning is carried in the actual words.

Part of the problem with email, as we all recognize, is that the context is so lacking, and the burden lies so heavily on the words themselves.

The importance of context for comprehension has, of course, profound implications for learning and memory.

I was reminded of this just the other day. I’m a fan of a TV program called NCIS. I only discovered it, however, at the beginning of the third season. After I’d watched it for some weeks, I purchased the DVDs of the earlier seasons. Most recently, I bought the DVD of season 3, which I had, of course, seen on TV. Watching the first episode of that season, which was the first episode of NCIS I ever saw, I was surprised to hear a line which I had no memory of, that was freighted with significance and led me to a much deeper understanding of the relationship between two of the characters — but which had meant absolutely nothing to me when I originally saw it, ignorant as I was of any of the characters and the back story.

The revelation meant nothing to me as a novice to the program, and so I didn’t remember it, but it meant everything to me as (dare I say it?) an expert.

Context is such a slippery word; so hard to define and pin down. But I think it’s fair to say that the difference between the novice and the expert rests on this concept. When an expert is confronted with a piece of information from her area of expertise, she knows what it means and where it belongs — even if the information is new to her. Because of this, she can acquire new information much more easily than a novice. But this advantage applies only in the expert’s area of expertise.

To take another example from the frivolous world of popular culture, a British study of fans of the long-running radio soap opera The Archers were given one of two imaginary scripts to read. One story was representative of the normal events in The Archers (a visit to a livestock market); the other was atypical (a visit to a boat show). These experts were able to remember many more details of the typical, market story than a group of subjects who knew little about the soap opera, but were no better at remembering details for the atypical story. Most importantly, this occurred even though the two stories shared many parallel features and most of the questions (and answers) used to assess their memory were the same. This indicates the specificity of expert knowledge.

Part of the advantage experts have is thought to rest on the ‘conditionalization’ of knowledge. That is, experts’ knowledge includes a specification of the contexts in which it is relevant.

It is surprising to many, this idea that it is not necessarily a lack of knowledge that is the problem — that people often have relevant knowledge and don’t apply it. In reading, for example, readers often don’t make inferences that they are perfectly capable of making, on the knowledge they have, unless the inferences are absolutely demanded to make sense of the text.

Another example comes from the making of analogies. I discuss this in my workbook on taking notes. Here’s a brief extract:

------------------------------------------

Rutherford’s comparison of the atom to the solar system gave us a means to understand the atom. The story goes that Newton ‘discovered’ gravity when an apple fell on his head — because of the comparison he made, realizing that the motion of an apple falling from a tree was in some sense like the motion of the planets. These are comparisons called analogies, and analogy has been shown to be a powerful tool for learning.

But the problem with analogies is that we have trouble coming up with them.

Generally, when we make analogies, we use an example we know well to help us understand something we don’t understand very well. This means that we need to retrieve from memory an appropriate example. But this is clearly a difficult task; people frequently fail to make appropriate connections — even, surprisingly, when an appropriate connection has recently come their way. In a study where people were given a problem to solve after reading a story in which an analogous problem was solved, 80% didn’t think of using the story to solve the problem until the analogy was pointed out to them.

It’s thought that retrieving an appropriate analogy is so difficult because of the way we file information in memory. Certainly similarity is an important attribute in our filed memories, but it’s not the same sort of similarity that governs analogies. The similarity that helps us retrieve memories is a surface similarity — a similarity of features and context. But analogies run on a deeper similarity — a similarity of structure, of relations between objects. This will only be encoded if you have multiple examples (at least more than one) and make an explicit effort to note such relations.

----------------------------------------------

The conditionalization of knowledge is of course related to the problem of transfer. Transfer refers to the ability to extend (transfer) learning from one situation to another (read more about it here) . Transfer is frequently used as a measure of successful learning. It’s all very well to know that 399-(399*0.1) = 359.1, but how far can you be said to understand it — how much use is it — if you can’t work out how much a $3.99 item will cost you if you have a 10% discount? (In fact, the asymmetry generally works the other way: many people are skilled at working out such purchase calculations, but fall apart when the problem is transferred to a purely numerical problem).

Transfer is affected by the context in which the information was originally acquired — obviously transfer is particularly problematic if you learn the material in a single context — and this is partly where the experts achieve their conditionalization: because, spending so much time with their subject they are more likely to come across the same information in a variety of contexts. But the more important source is probably the level of abstraction at which experts can operate (see my article on transfer for examples of how transfer is facilitated if the information is framed at a higher level of abstraction).

In those with existing expertise, an abstract framework is already in place. When an expert is confronted by new information, they automatically try and fit it into their existing framework. Whether it is consistent or inconsistent with what is already known doesn’t really matter — either way it will be more memorable than information that makes no deep or important connections to familiar material.

Let’s return to this idea of high and low context. Hall was talking about communications, in the context of different cultures (interestingly, he found cultures varied in the degree to which they were context-bound), but the basic concept is a useful one in other contexts. It is helpful to consider, when approaching a topic, either as student or teacher, the degree to which understanding requires implicit knowledge. A high context topic might be thought of as one that assumes a lot of prior knowledge, that assumes a knowledge of deeper structure, that is difficult to explain in words alone. A low context topic might be thought of as one that can be clearly and simply expressed, that can largely stand alone. Learning the basics of a language — how to conjugate a verb; some simple words and phrases — might be thought of as a low context topic, although clearly mastery of a language requires the complex and diverse building up of experiences that signifies a high context topic (and also clearly, some languages will be more ‘high context’ than others).

There is nothing particularly profound about this distinction, but an awareness of the ‘contextual degree’ of a topic or situation, is helpful for students, teachers, and anyone involved in trying to communicate with another human being (or indeed, computer!). It’s also helpful to be aware that high context situations require much more expertise than low context ones.

This article first appeared as "Context, communication & learning" in the Memory Key Newsletter for April 2007

References: 

Reeve, D.K. & Aggleton, J.P. 1998. On the specificity of expert knowledge about a soap opera: an everyday story of farming folk. Applied Cognitive Psychology, 12 (1), 35-42.

tags memworks: 

tags study: 

tags strategies: 

Asking better questions

Questions — especially why questions — help us make connections to existing anchor points — facts we know well. But some questions are better than others.

To decide whether a question is effective, ask:

  • does it make the information more meaningful?
  • does it make the information more comprehensible?
  • does it increase the number of meaningful connections?

Consider our facts about blood:

  • arteries are thick and elastic and carry blood that is rich in oxygen from the heart.
  • veins are thinner, less elastic, and carry blood rich in carbon dioxide back to the heart.

We could, as is often advised, simply turn these into why questions. And we can answer these on the basis of the connections we’ve already made:

Why are arteries elastic?

Because they need to accommodate changes in pressure

Why are arteries thick?

Because they need to accommodate high pressure

Why do arteries carry blood away from the heart?

Because blood coming from the heart comes out at high pressure and in spurts of variable pressure

Why do arteries carry blood that is rich in oxygen?

Because the blood coming from the heart is rich in oxygen

Why are veins less elastic?

Because the blood flows continuously and evenly

Why are veins less thick?

Because the blood flows at a lower pressure

Why do veins carry blood to the heart?

Because blood going to the heart flows continuously and evenly

Why do veins carry blood that is rich in CO2?

Because the blood going to the heart is rich in CO2

What’s missing? Connections between these facts. The facts have become more meaningful, but to be really understood you need to make the connections between the facts explicit.

Look again at our original questions. See how they relate the facts to each other? They don’t ask: why are arteries elastic? They ask: Why do arteries need to be more elastic than veins? They don’t ask: why do arteries carry blood that is rich in oxygen? They ask: why do vessels carrying blood from the heart need to be rich in oxygen?

By answering these questions, we have built up an understanding of the facts that ties them together in a multi-connected cluster:

pictorial representation of this information

For simplicity, I’ve just focused on the arteries. See how the four facts about arteries are connected together. Meaningfully connected. In a perfect world we’d be able to close the circle with a direct connection between the facts “Arteries carry blood rich in oxygen” and “Arteries are thick”, but as far as I know, the only connection between them is indirect, through the fact that “Arteries carry blood from the heart”.

So … the world isn’t perfect, and information doesn’t come in neatly wrapped bundles where every fact connects directly to every other fact. But the more connections you can make between related facts — the stronger a cluster you can make — the more deeply you will understand the information, and the more accessible it will be. That is, you will remember it more easily and for longer.

If it’s well enough connected

If it’s connected to strong anchor points

You will simply 'know' it.

You’re never going to forget that you breathe in oxygen and that your heart pumps out blood. These are strong anchor points. If the facts about arteries are strongly connected to these anchor points, you will never forget them either.

Asking questions is one of the best ways of making connections,

but

Bad questions can be worse than no questions at all.

Rote questions that direct your attention to unimportant details are better not asked.

Effective questions prepare you to pay attention to the important details in the text.

The best questions not only direct your attention appropriately, but also require you to integrate the details in the text. Ask yourself:

  • Is this helping me to select the important information?
  • Is it helping me make connections?

When the subject is new to you

When you don’t have enough prior knowledge about a subject to ask effective questions, you are better off forming connections using mnemonics — either through verbal elaboration, as in our sentence about “Art (ery) being thick around the middle so he wore trousers with an elastic waistband” or by creating interactive images.

However, mnemonics such as these — while perfectly effective — are only good for rote learning. Sometimes that’s all you want, of course. But if you’re going to be learning more information that relates to these facts, then you’re making a rod for your own back.

When you learn something by rote, it never gets easier. When you learn by building connections, every new fact is acquired more easily. And it’s progressive. An expert on a subject can hear a new fact in her area of expertise, and it’s there. Remembered. Without effort. Because she’s an expert. And what makes her an expert? Simply the fact that she’s built up a network of information that is so tightly connected, and that has so many strong anchor points, that the information is always retrievable.

Why questions, like any questions, are only effective to the extent that they direct attention to appropriate information.

Research confirms that it is better to search for consistent relations than inconsistent ones. In many cases your background knowledge may include information that is consistent with the new information, and information that is inconsistent.

By asking “Why is this true?” you focus on the consistent information.

 

References: 

  • Woloshyn, V.E., Willoughby, T., Wood, E., & Pressley, M. 1990. Elaborative interrogation facilitates adult learning of factual paragraphs. Journal of Educational Psychology, 82, 513-524.
  • Pressley, M. & El-Dinary, P.B. 1992. Memory strategy instruction that promotes good information processing. In D. Herrmann, H. Weingartner, A. Searleman & C. McEvoy (eds.) Memory Improvement: Implications for Memory Theory. New York: Springer-Verlag.

tags study: 

tags strategies: 

Pages

Subscribe to comprehension