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Study

Have benefits of a growth mindset been overstated?

  • A review of growth mind-set research has found the correlation between growth mind-set and academic achievement was very weak, and may be restricted to some groups of students.

In the education world, fixed mind-set is usually contrasted with growth mind-set. In this context, fixed mind-set refers to students holding the idea that their cognitive abilities, including their intelligence, are set at birth, and they just have to accept their limitations. With a growth mind-set, however, the student recognizes that, although it might be difficult, they can grow their abilities.

A growth mind-set has been associated with a much better approach to learning and improved academic achievement, but new research suggests that this difference has been over-stated.

A recent meta-analysis of growth mind-set research found that

  • over half the effect sizes weren't significantly different from zero (157 of 273 effect sizes),
  • a small number (16) actually found a negative association between growth mind-set and academic achievement, and
  • a little over a third (100) were significant and positive.

Overall, the study found the correlation between growth mind-set and academic achievement was very weak.

Perhaps unsurprisingly, one important factor was age — children and teenagers showed significant effects, while adults did not. Interestingly, neither academic risk status nor socioeconomic status was a significant factor, although various studies have suggested that growth mind-set is much more important for at-risk students.

A second, smaller meta-analysis was carried out to investigate whether growth-set interventions made a significant impact on academic achievement. Such interventions are designed to increase students' belief that intelligence (or some other attribute) can be improved with effort.

The study found that

  • 37 of the 43 effect sizes (86%) were not significantly different from zero,
  • one effect size was negative, and
  • five were positive.

Age was not a factor, nor was at-risk status. However, socioeconomic status was important, in that students from low-SES households were significantly impacted by a growth mind-set intervention, while those from higher-SES households were not.

The type of intervention was important: just reading about growth mind-set didn't help; doing something more interactive, such as writing a reflection, did. The number of sessions didn't have an effect. Oddly, the way the intervention was presented made a difference, with materials presented by computer or by a person not being effective, while print materials were. Interventions administered during regular classroom activities were not effective, but interventions that occurred outside regular activities did have a significant effect.

Taken overall, the depressing conclusion is that mind-set interventions are not the revolution some have touted them as. The researchers point out that previous research (Hattie et al 1996) found that the meta-analytic average effect size for a typical educational intervention on academic performance is 0.57, and all the meta-analytic effects of mind-set interventions in this study were smaller than 0.35 (and most were null).

All this is to say, not that mind-set theory is rubbish, but that it is not as straightforward and miraculous as it first appeared. Mind-set itself is more nuanced than has been presented. For example, do we really have a definite fixed mind-set or growth mind-set? Or is it that we have different mind-sets for different spheres? Perhaps we believe that our math ability is fixed, but our musical ability is something that can be developed. That we can develop our problem-solving ability, but our intelligence is set in stone. That our 'natural talents' can be grown, but our 'innate weaknesses' cannot.

Why would low-SES and high-risk students benefit from a growth mind-set intervention, while higher-SES students did not? An obvious answer lies in the beliefs held by such students. For example, it may be that many higher-SES students are challenged by the idea of a growth mind-set, because they're invested in the idea of their own natural abilities. It is their confidence in their own abilities that enables them to do well, just as other students are undermined by their lack of confidence. Given this different starting point, it would not be in any way surprising if such students responded differently to mind-set interventions.

References

Sisk, V. F., Burgoyne, A. P., Sun, J., Butler, J. L., & Macnamara, B. N. (2018). To What Extent and Under Which Circumstances Are Growth Mind-Sets Important to Academic Achievement? Two Meta-Analyses. Psychological Science, 29(4), 549–571. http://doi.org/10.1177/0956797617739704

Hattie, J., Biggs, J., & Purdie, N. (1996). Effects of learning skills interventions on student learning: A meta-analysis. Review of Educational Research, 66, 99–136.

 

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.

 

Self-regulation

Knowing a number of effective strategies for reading and note-taking, practicing and memorizing, is vital, but it's not the whole story. There is also a category of strategies we might term 'support' strategies. These include strategies aimed at setting goals, managing time and effort, and monitoring your performance and progress. In study, these come under the concept of self-regulation, which is related to the more general concept of metamemory.

Self-regulation is crucial to successful study.

Self-regulation isn't simply about 'self-control', although that's one aspect of it. Self-regulation skills include manipulating your environment, your emotions and attitudes, and your social interactions.

Assessing strategy

When you evaluate any specific study strategy the critical questions are:

  • Does it help you understand the information?
  • Does it help you select the important information?

To choose a strategy, you must assess the situation. In this case, this may mean an evaluation of a written text. Let's look at how you might evaluate text.

We can classify text at one of three different levels, according to its structure and density1:

  1. simple (straightforward text with clear connections)
  2. complex (characterized by many changes of topic and more than one level of information)
  3. difficult (dense text with many topic changes, often unclear, inconsistent and/or abstract)

These different types of text require progressively more complex strategies.

Textual strategies can be classified into six broad processes1:

Broad processes

Specific strategies

Re-stating paraphrasing; visualizing; transformational elaboration
Selecting underlining, highlighting, boxes, lists
Abstracting themes headings, summaries
Perceiving structure outlines, graphic organizers
Making sense of information elaborative interrogation, analogies, maps, multimedia summaries, re-structuring, charts & tables, integrating sections of text.
Monitoring comprehension constructing and testing theories about the meaning of the text, seeking additional information

Matching these processes against our classes of text (noting that processes listed beside text levels indicate additional processes required - including processes used at lower levels of difficulty), we get1:

Simple text re-statement
Complex text selecting
abstracting themes
perceiving structure
making sense of information
Difficult text monitoring comprehension

 

 

Successful Learning Simplified

References
  1. Jones, B.F. 1986. Text learning strategy instruction: guidelines from theory and practice. In C.E. Weinstein, E.T. Goetz & P.A. Alexander Learning and study strategies. New York: Academic Press.
  2. 1. Taken from The Memory Key.

Note-taking

Rules for effective note-taking

  • Select. Omit trivial and redundant details. Omit anything you'll recall anyway!
  • Condense. Replace lists with a category term.
  • Organize. Choose headings and topic sentences.
  • Rephrase. Use your own words.
  • Elaborate. Make connections to existing knowledge.

Effective Notetaking

To use note-taking effectively, you need to understand that its primary value is not in the record you produce, it is in the process itself. The process of taking notes guides the memory codes you make. Note-taking is a strategy for making information meaningful. It is therefore only effective to the extent that you paraphrase, organize and make sense of the information while taking notes.

Note-taking is a strategy for making information meaningful.

What does that mean? What does it mean, to make information meaningful? It means to connect new information to existing knowledge. The more connections you make, the better you will understand the information.

Connection is the heart of what makes information meaningful.

Why is it important to make information meaningful?

Because connection is the key to remembering. The more connections you have, the more entry points you have to the information, therefore the easier it will be to retrieve.

Facts that you already know very well and have no trouble remembering act as anchor points.

The more anchor points you can connect to, the more meaningful the new information becomes, and the more easily you will remember it.

Think about it for a moment. When you are told something new, you only understand it to the extent that you can relate it to something you already know.

Here’s a quote from The complete idiot’s guide to Microsoft Office:

After you select the data source to use, the Mail Merge Helper displays the Label Options dialog box, asking you to specify the type and size of the mailing labels on which you intend to print.

Now if you don’t know anything about computers this will be complete gibberish and there’s no way you’re going to remember it. If you have some experience with Microsoft Office, but have no experience of Mail Merging, then you will sort of understand what’s going on, but not have enough anchor points to really understand it — and you’re not going to remember it either. But if you are already au fait with Mail Merging, and merely want to know how to do the labels, then you will have a well-organized, strong cluster of facts already recorded in memory, and the new fact will slot in easy peasy. You’ll understand it, and you’ll remember it — to the extent that your existing cluster of information about Mail Merging was strong and well-connected.

It’s like learning a new word. Pediment, for example. If you were told this was a triangular part crowning the front of a building in the Grecian style — assuming you don’t already know the word, and assuming you have no particular knowledge of architecture — you’re not likely to remember it without repeatedly coming across it. You might make the connection pedimentimpediment, but since there is no meaningful connection between these words, this won’t help you remember the meaning of pediment. It might help you remember the word itself, mind. But to remember the meaning of the word, you need a meaningful connection. That might be provided by the suggestion that pediment is derived from a corruption of pyramid, which as we all know, is triangular, and is also a building.

The more connections to existing anchor points, the more meaningful the word becomes; the more easily remembered it is.

Connection is the key to remembering.

The more connections you have, the more entry points you have to the information.

Therefore, the more easily it will be found.

Connection is the heart of what makes information meaningful.

How does notetaking help make information meaningful?

Here we came to the nub of the matter. Notetaking doesn’t have to make information meaningful, but it is mainly valuable to the extent that it does.

So this is how you judge your notetaking skills, and how you judge the value of a particular strategy in a particular situation —

Ask yourself: does this help me make connections? Does it help me connect the facts together? Does it help me connect the new information with information I already have? Does it make any connection with facts I already know very well, and am unlikely to forget?

Conditions for effective note-taking

  • Slow or self-determined rate of presentation
  • Well-organized material
  • Material that is not too difficult or complicated
  • Skill at note-taking1
References
  • Baine, D. 986. Memory and instruction. Englewood Cliffs, NJ: Educational Technology Publications.
  • Barnett, J.E., DiVesta, F.J. & Rogozinski, J.T. 1981. What is learned in note-taking. Journal of Educational Psychology, 73, 181-192.
  • Peper, R.J. & Mayer, R.E. 1978. Note-taking as a generative activity. Journal of Educational Psychology, 70, 514-522.
  • Schneider, W. & Pressley, M. 1989. Memory development between Two and Twenty. New York: Springer-Verlag.

1. Adapted from The Memory Key.

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.

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.

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 realized 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 some examples, constructed using cmap, at https://cmap.ihmc.us/cmaps-around-the-world/.

You can also learn more about concept maps at http://cmc.ihmc.us/CMC2004Programa.html (which has a number of conference papers available in pdf format).

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

Effective Notetaking

Using strategies effectively

You can predict how well a student will do from their use of study strategies. Forget intelligence. Forget hours put in. What’s important is the effective use of good study strategies.

To use a strategy effectively, you need to understand why it works, how it works, when it works and when it doesn’t.

For example, all students take notes — not everyone knows how to do it well. Research into the effectiveness of note-taking has found — surprise, surprise — that sometimes note-taking helps you remember information, and sometimes it doesn’t1.

Effective note-taking is more complex than simply knowing some strategies. Every learning situation is different. Every piece of text is different. Every lecture is different. It’s not enough to have a stock way of organizing your notes, and to try and push all the information that comes your way into that format. Sometimes a matrix structure might be best; sometimes a multimedia summary, sometimes a map, sometimes standard old linear notes. It depends on the information and it depends on how it is packaged.

The only way to know which strategy to use when, is to understand how they work.

For example, the primary value of note-taking is to select out the important information and connect it to other pieces of information. If you think the function of note-taking is simply to record what someone has said, or what you've read, then your note-taking will be far less effective.

Successful Learning Simplified

References
  1. Baine, D. 1986. Memory and instruction. Englewood Cliffs, NJ: Educational Technology Publications.