TODO_AUTHOR, (Marsh and Butler 2013)
- Retrieval or re-experiencing a memory will increase retention.
- Studying should be somewhat difficult; neither too difficult that the subject is unable to overcome the challenge, nor too easy. The difficulty is desirable feature of the process of studying in that the difficulty improves retention.
- One does not need to be aware of the specific benefits of a study method to benefit from them.
- The way you learned a piece of information as well as the cues/environment during retrieval control your ability to remember and utilize information.
- There is no “right” study method, though some are better than others. The study method which will be most effective will depend on the situation in which you will need to recall the information.
Anki seems highly relevant here; it combines spaced repetition and the benefits of the testing effect. However, I think it would be easy to create flashcards which aid in memorizing a fact but not in understanding or application. For instance: I could imagine a card which asks you to recall the abstract steps required to multiply a
IxJ matrix by a
JxK matrix. I think this card, on its own, would not be sufficient to maintain understanding or the ability to perform matrix multiplication. Perhaps you could supplement the card with others which ask:
- What conditions are necessary to multiply two matrices (
- A card, or several, which provide specific examples using numbers rather than generalizations? Perhaps there is a script or addon which allows for this sort of thing.
I worry that Anki wouldn’t be enough to maintain understanding and the ability to apply this knowledge even with these, and more, cards. It would certainly reduce the barrier to re-entry. I used to understand much more calculus than I could prove to you now after letting it fall out of my mind since college. Keeping up with calculus topics, example problems, definitions, etc, through Anki would at least make it easier for me to jump back in should the need arise. I wouldn’t expect to be as “on the ball” as I would if I were actively using and practicing calculus regularly, but I would be at a better place than I am now.
Memory in Educational Settings
Guiding Theoretical Principles
Introducing “Desirable Difficulties” During Learning
Performance during learning is a poor predictor of future performance because it reflects the momentary accessibility of knowledge (i.e., retrieval strength) rather than how well it has been stored in memory (i.e., storage strength)
Storage strength increases when a memory is retrieved or the event is reexperienced.
[I]f knowledge is to be retained over long periods of time, then the goal of learning must be to increase storage strength, not momentary accessibility.
Based on the distinction between retrieval strength and storage strength, R. A. Bjork and colleagues developed the concept of “desirable difficulties” in learning (Bjork, 1994a, 1994b; Christina & Bjork, 1991; Schmidt & Bjork, 1992). The main idea is that introducing difficulties during learning will result in superior long-term retention because the greatest gains in storage strength occur when retrieval strength is low. For example, consider the practice of using flash cards to study vocabulary words. If you study a word and then try to remember it immediately, then the gain in storage strength will be relatively low because it is so easy to retrieve the word right away (retrieval strength is high). However, if you wait 5 minutes before attempting to retrieve the word (when retrieval strength will be lower), then the gain in storage strength will be larger. The implication for educational practice is that instead of arranging the conditions of learning to be easier and faster for the learner, educators should introduce difficulties into the learning process in order to promote long-term retention of knowledge.
Processing Information to Extract Meaning
Critically, directing attention at a lower or “shallow” level of processing (e.g., focusing on the orthography of words while reading) disrupts higher or “deeper” levels of processing (e.g., determining what those words mean). As a result, the type of processing in which one consciously engages determines what information will be encoded into memory and retained. The type of processing is more important than the intent to learn (e.g., Craik & Tulving, 1975); the implication is that a student who deliberately prepares for a test but who does not engage in deep processing will not do as well as the student who processes the material deeply, even if the latter student is not deliberately trying to learn the material.
One helpful distinction involves item- specific processing versus relational processing (Hunt & Einstein, 1981). Item-specific processing involves encoding the various characteristics or properties of a particular piece of information. For example, judging the pleasantness of a word, filling in missing letters in a text, and creating a mental image of each step in a science experiment all focus the learner on a single to-be-remembered item.
In contrast, relational processing refers to the encoding of similarities and differences across pieces of information. For example, sorting words into categories, ordering sentences to create a coherent text, and explaining why each subsequent step in a science experiment follows the preceding step all involve comparing to-be-remembered events to each other. In short, both item-specific and relational processing can involve meaning extraction, but they direct the learner to different aspects of the to-be- remembered events.
Importance of Match Between Processing at Encoding and Retrieval
Rather, memory performance is the joint product of the way in which the memory was encoded (i.e., the memory trace that is stored) and the way in which it is retrieved (i.e., the cues provided) (e.g., Tulving & Pearlstone, 1966; Tulving & Osler, 1968). This idea is codified in the theory of transfer-appropriate processing, which states that memory performance will be enhanced to the extent that the processes engaged during initial learning match the processes required for the criterial task
In short, there is not always a single right answer about which study strategy will be best. Rather, as reflected in ideas about transfer-appropriate processing, the ideal study strategy depends upon what the student will need to do later.
We have presented three general cognitive principles that are critical for determining memory performance in educational settings:
- introducing desirable difficulties during learning
- engaging in processes that emphasize meaning extraction
- and matching learning processes to the processes needed to excel on the final criterial task (i.e., transfer-appropriate processing).
Learning Strategies for Studying Material
Receiving Advance Organizers
Highlighting and Underlining
Although note taking yields memorial benefits, the type of notes naturally taken may not be the most powerful mnemonic possible. One issue involves how much note taking involves going beyond the to-be-remembered information (versus simply copying; see Marsh & Sink, 2010), including paraphrasing the to-be-remembered information and connecting it to stored knowledge. Returning to the levels of processing framework, the key issue is the depth of processing note taking naturally affords. We have just reviewed evidence that note taking encourages relational processing that affords transfer. Nevertheless, additional benefit may come from techniques that encourage the reader or listener to process the material even more deeply. For example, King (1992) trained students to summarize material, specifically how to identify and encapsulate the main idea. This group of students was compared to another group who took notes naturally, and who later had a chance to review those notes. Students who summarized the lecture performed better on both immediate and delayed comprehension tests than students who took notes (see Bretzing & Kulhavy, 1979, for similar results). Similarly, the note-taking group did not do as well as a group of students trained to ask themselves (and answer) questions about the material. Students might benefit from incorporating some of these deep processing techniques into their notes; in other words, training might help students to take notes that include more of the generative processing thought to be key for transfer (e.g., Peper & Mayer, 1978).
Learning Strategies for Poststudy
… memory research has shown that retrieving information from memory actually changes memory (e.g., Bjork, 1975), improving long-term retention of the material
The finding that retrieval practice produces superior long-term retention has been termed the testing effect
When testing is used as a learning tool in educational settings, there are several ways in which its efficacy can be enhanced.
- Tests that require students to produce a response, such as short-answer and essay tests, generally lead to better retention than tests that simply require the selection of the correct response, such as multiple-choice tests and true/false tests.
- Taking multiple tests results in better retention than taking a single test, so it is beneficial to repeat questions on quizzes and give cumulative exams.
- Successful retrieval is the key to learning from tests, so providing feedback after the test is essential, especially if test-takers do not retrieve many correct responses
Processing Feedback to Correct Errors
The most consistent result is that providing learners with the correct answer in the feedback message produces better subsequent performance than simply indicating whether an answer is correct or incorrect (e.g., Pashler et al., 2005; for a meta-analysis, see Bangert-Drowns, Kulik, Kulik, & Morgan, 1991). This finding makes sense because informing the learner that a given response is incorrect will not help the learner to correct the error if the learner does not have any recourse to learn the correct answer.
Spacing Out Practice Over Time
… [I]t seems that the optimal interval depends on how long the knowledge needs to be retained after the last practice (i.e., the retention interval). Cepeda and colleagues (2006; see also Cepeda, Vul, Rohrer, Wixted, & Pashler, 2008) performed a meta-analysis that included 317 experiments from 184 articles on the spacing effect. They found that the optimal spacing interval is approximately 10%–20% of the retention interval. Thus, if the goal is to retain the material for 5 days, then practice should be spaced over intervals between 12 and 24 hours
Applying the Guiding Principles and Learning Strategies in Educational Settings
Learning Beyond Facts
… [I]n the classroom, educators have many different goals for their students, and these goals vary as a function of the level of education, the type of course, and the time frame given for learning, among many other factors. One way of categorizing these goals is through Bloom’s (1956) taxonomy of educational objectives, which conceptualizes learning as a hierarchy in which the various levels must be mastered in sequential order. The cognitive domain is comprised of six levels (from lowest to highest):
- knowledge (e.g., learning facts, concepts, etc.)
- comprehension (e.g., understanding the relationship between ideas)
- application (e.g., using knowledge to solve new problems)
- analysis (e.g., finding evidence to support a hypothesis)
- synthesis (e.g., combining different accounts of an event to understand what occurred)
- evaluation (e.g., assessing the validity of an idea according to certain criteria)