Post on 10-Apr-2016
description
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Shawn Allen
English 102
Professor Burke
29Nov2015
Survey of Learning Methods: A Neuroscience Neophytes Guide to Learning More In Less Time.
It is not without great irony that many people spend at least 13 years in formalized
education, some upwards of 20 years, and most of whom do not think about learning how to
learn effectively – let alone what is on the bleeding edge of learning methods, techniques &
theories. Everybody learns differently. While this familiar adage is true, the rabbit hole of
learning is so much deeper than the proverb credits it. Not only does everybody learn differently,
but everyone learns different types of subject matter differently and across different learning
methodologies – differently. Some methods that would be advantageous to employ learning a
language, for instance, would not be so advantageous for logically figuring out a problem in a
chemistry class. Students often do not know how to study in such a way that will maximize their
study time effectively, and similarly, teachers might not be trained in the appropriate areas to
maximize learning outcomes (Dunlosky et al). It would be truly surprising if any student could
recall their time in formalized education without recalling the techniques of summarization,
highlighting, rereading, or notetaking. It may or may not be surprising to find out these
techniques are not very effective (Dunlosky et al). This of course begs the question: what are the
most effective learning strategies for X use case? In an attempt some of this information
accessible to those of whom are not neuroscience or learning psychology majors, this paper will
look at various research studies that discuss: techniques students report using most often that are
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not successful; classical learning methodologies that have demonstrated the most consistent
effects across a wide range of use cases and learning environments; and finally, a close up look
at the merits of a new fad on the bleeding edge in e-learning – the spaced learning effect.
There a few things to note about interpreting the results of this paper, and many of the
studies reviewed This is especially true of those reviewed by Dunlosky et al, which seemed to
be the seminal work on collecting and correlating a lot of these subjects at the time of this
writing. Most of the studies are aimed at wide implementation and evaluate the subsequent
methods through that lens. The Dunlosky team also looked at most of the subjects with studies
that accounted for intellectual differences, like functional memory, reading ability, and prior
knowledge; as well as learning environment differences, implementation difficulties, and other
such metrics. Many of these types of studies are left out in favor of more interesting and broadly
applicable ones, but is an area left for one to consider for further reading. Some of the more
exotic methods have more narrow use cases, and although promising perhaps, are the least
researched. A lot of the research conflicts. So in light of that fact, many methods herein are
discussed in a simple pro versus con context, while attempting to let one decide which methods
may be appealing, but ultimately staying in line with what seems to be the most reputable
research. So when one evaluates the information herein: do so acknowledging that nothing is
concrete, everything is a spectrum, most everything is likely under-researched in some aspect or
many, and again, everybody learns differently to an extent.
In order to establish a baseline for what most people experience in formalized western
education one could easily argue the most ubiquitous would be the summary. Unlike some of the
other study methods, summaries are in fact well researched. In terms of frequency, as noted
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above, in many students learning experiences summaries have been used quite extensively, but is
that usage justified?
On the positive side of things, “Thiede and Anderson (2003) had students read expository
texts over a variety of topics. In one condition, students were told to make a metacomprehension
judgment for each text while the other condition was asked to generate a summary of the text
prior to completing the judgment. They observed that the students who generated the summaries
had higher judgment accuracy than when they did not” (qtd. in Poulin). In a study from Bretzing
and Kulhavy from 1979 which tested summarizers vs. note takers vs. other methods like
verbatim copying, they found summarizers got scores that about equaled note-takers, receiving
scores of 14 and 15 out of 25 respectively on an immediate test, and 10 and 9 respectively out of
25 on a delayed test (qtd. in Dunlosky et al). Upon reading this one should immediately notice
the lack of retention from the immediate test to the delayed test. Another one of the biggest
takeaways from these results is that summarizing and note-taking were more effective than
verbatim copying. The rationale behind the line of thinking here is that: formulating the subject
matter into ones’ own words, or synthesizing, especially when selecting the most important
information, increases retention due to this synthesis (Dunlosky et al).
Despite this reported upside of increased metacomprehension, and slightly increased
retention over verbatim copying, there is not much more strong evidence to support using
summaries. Poulin, in her master’s thesis, observes that “using summarization to improve
[metacomprehension] accuracy has its limitations”. Poulin also states the primary determinant
factor and implementation issue of summarizing is the student must be trained to summarize
correctly – differentiating between a strong and a weak summary; or put another way, one that
really pulls out the main ideas and only the main ideas of the passages. Poulin goes onto
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conclude: “while summarization might be beneficial to structuring the content during study, it
overlooks the research that has consistently shown that students are highly overconfident in their
future academic success prior to and after reading educational materials.” Overall, Dunlosky and
his team rate it as a “low-utility” activity, which, is a relative score, meaning that among the ten
methods they choose to investigate in that paper, this one was not worth the time it in most use
cases and learning environments relative to the other methods available to the learner.
Highlighting is yet another familiar memory of formalized education. Similar in many
aspects to notetaking and summarizing, but primarily, one is asking the reader to take only the
best ideas from the subject matter and highlight or underline them. It is such common a practice
that indeed it could be said that “any educator who has examined students’ course materials is
familiar with the sight of a marked-up, multicolored textbook.” (Dunlosky et al). (Dunlosky goes
on to mention there are various studies confirming its popularity.) So it is because of the
popularity that highlighting seems to enjoy that the topic is mentioned here – mostly as a
warning. The best thing about highlighting is it takes relatively little effort, unfortunately, the
long-term educational benefit is fairly low as well. In the studies Dunlosky et al looked at, there
was relatively nothing substantially positive about the effects of highlighting, and again was only
when it was implemented correctly. Specifically, highlighting only the main ideas and nothing
else. Again, Dunlosky and team rate this activity as “Low Utility”, partly due to implementation
difficulties (i.e. doing it quickly and correctly), and partly due to it not having an empirically
proven educational benefit.
Rereading is a bit more of a controversial topic, so ones’ own mileage may vary here. At
a quick glance, rereading does seem to have at least some retention benefits in various studies.
Moreover, in a study conducted by Peter Verkoeijen and his team, the observation was made that
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there might be a correlation between rereading and the timing of that rereading session for
maximum long term retention benefits.
This next study on rereading gets a bit into spaced learning, which will be discussed in
more depth in the next section, but the basic tenet that one needs to understand is that you have a
space in between learning sessions, and furthermore, that you carefully considering the timing or
spaces between these sessions depending on one’s desired learning outcome. In the study, which
used about 60 psychology undergrads, “participants read the text twice, either in immediate
succession (massed repetition), with a 4-day interstudy interval (spaced short), or with a 3.5-
weeks interstudy interval (spaced long). Two days after the second study trial, all participants
were tested” (Verkoeijen et al). The results of this test are quite curious indeed – finding that the
participants of the first group and the third group scored about the same. The group in the
middle, the group that had the 4 day interval between study sessions: had apparently found the
rereading goldilocks zone, with their scores significantly outmatching the other two groups with
a mean of about 42 versus 60 (Verkoeijen et al). Ultimately, the most important takeaway is that
you can actually hurt retention by rereading too soon.
Another study on rereading conducted by Rothkoph in 1968 found that there is seemingly
no difference between rereading the subject matter 3 and 4 times, but it did show there was a
mean difference of about 8 percentage points in favor of those who read twice as opposed to
those who read once (qtd. in Dunlosky et al). Dunlosky and team conclude rereading can create
durable memories they qualify that by saying “most effects have been shown with recall-based
memory measures, whereas the benefit for comprehension is less clear.”This earns the activity a
Dunlosky chart: “Low Utility”. Although it has been demonstrated that rereading has some
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merit in durable learning, they deem it this way relative to the other methods available to the
learner.
The techniques reviewed thus far have represented some of the common experiences that
students self-report using the most often, but it is a wonder why they do. As one can see from the
studies reviewed so far, none of these techniques are especially effective, yet they keep being
employed by students and educators again and again. Luckily, and apparently contrary to popular
belief, these are not the only tools available. The focus will now shift on the most proactive ways
a prospective student can spend their study time. Some of these ideas are not exactly new, but, as
per usual, the devil lies in the details of implementation.
Elaborative interrogation is a term perhaps not many are familiar with, but it basically
boils down to asking: Why? There are various situations in which one might be engaged with
elaborative interrogation, it may in response to a prompt from a professor, or a prompt on a
screen from a computer. Perhaps the most common form of elaborative interrogation is self-
explanation (Dulosky et al). (Although Dunlosky differentiates the two concepts slightly.) The
next study is one of the earliest studies of elaborative interrogation:
Pressley, McDaniel, Turnure, Wood, and Ahmad (1987) presented undergraduate
students with a list of sentences, each describing the action of a particular man
(e.g., “The hungry man got into the car”). In the elaborative-interrogation group,
for each sentence, participants were prompted to explain “Why did that particular
man do that?” Another group of participants was instead provided with an
explanation for each sentence (e.g., “The hungry man got into the car to go to the
restaurant”), and a third group simply read each sentence. On a final test in which
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participants were cued to recall which man performed each action (e.g., “Who got
in the car?”), the elaborative-interrogation group substantially outperformed the
other two groups (collapsing across experiments, accuracy in this group was
approximately 72%, compared with approximately 37% in each of the other two
groups). From this and similar studies, Seifert (1993) reported average effect sizes
ranging from 0.85 to 2.57 (qtd. in Dunlosky et al).
These studies are profound not only because of the results, but because of the multitude
of studies present confirming them. Elaborative interrogation has proven not only to be effective
with these “Man does X, for Y reason” questions, but also for more classical material (Dunlosky
et al). Overall, it is rated by Dunlosky and team as an activity with “moderate utility”. Dunlosky
and team came to this conclusion because of this methods relatively proven track record with
fact based material, however, they feel that it does not have the same track record with more
complex and lengthy material, and that it also requires more study about retention time,
otherwise, they might have rated it as “high utility”.
Another method that has been proven to work fairly evenly across all the different
learning metrics and environments is practice testing. Distinct from actual testing, in the sense
that it is a ‘low stakes’ type of test where the focus for the student really becomes about
metacomprehension. There is a wide definition as well, Dunlosky et al defines its’ scope as
“practicing recall of target information via the use of actual or virtual flashcards, completing
practice problems or questions included at the end of textbook chapters, or completing practice
tests included in the electronic supplemental materials that increasingly accompany textbooks.”
There is quite a bit of connective tissue between how spaced learning and practice testing are
studied, and a lot of studies that focus on the “testing effect”, (similar phrasing and concept as
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spacing effect), are dealing with the time spaced between these practice testing sessions and the
immediacy of feedback.
In a follow up to a call for more study from Dunlosky and Rawson a newer study on the
subject of practice testing from 2014, which paid special attention to accounting for working
memory capacity, the importance of immediate and correct feedback, as well as various other
factors that were considered due to prior research done on the subject. The setup for the study
conducted by Wiklund-Hörnqvist et al repeated a Rawson & Dunlosky 2011 experiment:
Following these common learning phases (lecture and familiarization), the two
groups were assigned to different experimental procedures namely, either
rereading the facts (restudy group; SS) or taking a test with feedback (test group;
STfb) six consecutive times. For the SS-group, a key-concept was presented (15
sec.), and the instruction only required subjects to study For the STfb-group, a
key-concept leaving out the keyword was presented (15 sec.) and subjects were
requested to type in the correct answer at a blank screen (10 sec). This was
followed by feedback in the form of the correct answer (5 sec) (Wiklund-
Hörnqvist et al).
The mean proportion of correct responses for the STtb and SS group for three time points
respectively were: ~83 vs ~70 on an immediate test, ~58 vs ~45 on a 18-day delay test – with no
significant difference from then till the 5-week delay test (Wiklund-Hörnqvis et al). The results
of this particular study are fairly striking with the obvious gap between the two groups, some in
the practice group even scored nearly 100% on the exam. One of the interesting inferences from
this data set is that the retention of the information is encoded into long term memory at a
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significantly higher rate as well. Dunlosky et al rated it as having “High Utility”, concluding it
had low implementation difficulties, and high rewards relative to other methods.
Spaced learning or otherwise known as the retrieval spacing effect, has become
reasonably popular with those learning foreign languages and other fact based study online in the
form of a software which are known as: spaced repetition systems. This is a general category of
software comprised of: a media-rich flashcard system; the ability to get immediate correct
answer feedback, and the ability to have one be able to report metacomprehension by labeling
the cards easy, difficult or somewhere between, which in turn sets the spacing of the card to a
user defined long or short time-period for review. It seems it is not just our homo-sapien brains
that are structured in a fashion that makes correlations upon spaced retrieval cues in memory as:
“recently a robust model of LTM [Long-Term Memory] formation has emerged through studies
of late Long-Term Potentiation (LTP) and LTM in many different contexts and species” (qtd. in
Kelly & Whatson).
Demonstrating this effect with the unlikely candidate of honeybees Menzel et al., 2001
reported: “using spaces between stimuli of 30 sec, 3 min, and 10 min, memory retention was
tested after 30 min, one day, and 3 days. Honeybees trained with 30 sec spaces showed the best
learning after 30 min with over 80% retention, but this rapidly decreased, falling to 20% on the
third day, a demonstration only STM had been created. In contrast, honeybees trained with 10
min spaces between learning trials showed less than 80% retention after 30 min but subsequently
consolidated these memories, reaching almost 100% on the third day, demonstrating [LTM] had
been created” (qtd. in Kelly and Whatson). One of the problems with the research so far had
been the lack of studies focused on high stakes examination outcomes. In the study conducted by
Kelly and Whatson they looked at exactly this, using a method they “derived directly from the
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research demonstrating LTM mechanisms of DNA synthesis at an intracellular level can be
triggered using three stimuli spaced by two 10 min periods without stimulation” they went on to
craft a way to apply these constraints in a learning environment:
A Technique was developed based on this pattern to test weather encoding
complex information into LTM in students was possible using the pattern within a
very short time scale. In an educational context, stimuli were periods of highly
compressed instruction, and spaces were created through 10 min distractor
activities. Spaced Learning in this form was used only as the means of instruction
for a national curriculum of biology courses. Remarkably, learning at a greatly
increased speed and in a pattern that included deliberate distraction produced
significantly highly scores than random answers (p < 0.00001) and scores were
not significantly different for experimental groups (one hour spaced learning) and
control groups (four months teaching). Thus learning per hour of instruction, as
measured by the test, was significantly for the spaced learning groups (p <
0.00001). In a third condition, spaced learning was used to replace the end of
course review for one of two examinations. Results showed significantly higher
outcomes for the course using spaced learning (p < 0.0005) (Kelly and Whatson).
It is truly amazing that the experimental group nearly matched the 4-month classical
education group and that the spaced review group reported significantly increased scores over
the classical review group (Kelly and Whatson). Drawing conclusions from these two points:
perhaps some of the highest utility might be in a hybridization of classical education and the
tenets of spaced learning. This particular method does not get a mention in Dunlosky’s chart,
however, Dunlosky and Rawson have done some research on the effect in other papers, which is
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definitely an area suggested for further reading. In rating this methods utility and staying
consistent with the rest of the previous analysis, one may look to the components this method is
essentially comprised of: spaced sessions of practice testing with immediate feedback and focus
on metacomprehension. After looking at it from such a vantage, it is relatively reasonable to
conclude that such systems are of high-utility, and in fact, hybridize most of the strong points of
all the methodologies discussed so far.
Yes, everyone does learn a bit differently, but, as has been demonstrated, there is much
commonality to learning as well, even to very distantly related species, like honeybees. Spaced
Learning, like many of these methods discussed herein, is not a very new idea. However, despite
the copious amount of research documenting the existence of the effect, the overall impact into
formalized education has been minimal at best (Kelly and Whatson). Techniques like
highlighting, summarizing, and note-taking still describe the majority of student experiences.
One could easily say that awareness is actually the primary implementation problem for the high-
utility methods, and also the reason why lower-utility methods are not more readily abandoned.
In all likelihood, it will take an entirely new generation of teachers to really shift the paradigm of
twenty-first education into a direction that is backed by neurologists, until then, one can always
benefit from analyzing the ways in which one learns best individually, and supplement one’s
own curriculum with some of methods that were discussed here. It is an exciting time for
neuroscience, the science how we learn is still in its infancy with much room for improvement
and further research. Suggestions for further reading include: anything written by John Dunlosky
and Katherine Rawson, as well as the work from Kelly and Whatson listed in the works cited.
.
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Works Cited
Dunlosky, J., K. A. Rawson, E. J. Marsh, M. J. Nathan, and D. T. Willingham.
"Improving Students' Learning with Effective Learning Techniques: Promising
Directions from Cognitive and Educational Psychology." Psychological Science
in the Public Interest 14.1 (2013): 4-58. Indiana University, 2013. Web. 29 Nov.
2015.
Kelly, Paul, and Terry Whatson. "Making Long-term Memories in Minutes: A Spaced
Learning Pattern from Memory Research in Education." Frontiers. Frontiers in
Human Neuroscience, 25 Sept. 2013. Web. 29 Nov. 2015.
<http://dx.doi.org/10.3389/fnhum.2013.00589>.
Poulin, Christina Marie. "Do Rubrics Improve Students’ Metacomprehension Accuracy?"
Thesis. Kent State, 2013. Https://etd.ohiolink.edu/!etd.send_file?
accession=kent1374595640&disposition=inline. Kent State. Web.
<https://etd.ohiolink.edu/!etd.send_file?
accession=kent1374595640&disposition=inline>.
Rawson, Katherine A., John Dunlosky, and Sharon M. Sciartelli. "The Power of
Successive Relearning: Improving Performance on Course Exams and Long-Term
Retention." Educational Psychology Review Educ Psychol Rev 25.4 (2013): 523-
48. Web.
Verkoeijen, Peter P. J. L., Remy M. J. P. Rikers, and Binnur Özsoy. "Distributed
Rereading Can Hurt the Spacing Effect in Text Memory." Applied Cognitive
Psychology Appl. Cognit. Psychol. 22.5 (2008): 685-95. Web.
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Wiklund-Hörnqvist, Carola, Bert Jonsson, and Lars Nyberg. "Strengthening Concept
Learning by Repeated Testing." Scandinavian Journal of Psychology Scand J
Psychol 55.1 (2013): 10-16. Web.