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Learning is often considered complete when a student can produce the correct answer to a question. In our research, students in one condition learned foreign language vocabulary words in the standard paradigm of repeated study-test trials. In three other conditions, once a student had correctly produced the vocabulary item, it was repeatedly studied but dropped from further testing, repeatedly tested but dropped from further study, or dropped from both study and test. Repeated studying after learning had no effect on delayed recall, but repeated testing produced a large positive effect. In addition, students' predictions of their performance were uncorrelated with actual performance. The results demonstrate the critical role of retrieval practice in consolidating learning and show that even university students seem unaware of this fact.
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DOI: 10.1126/science.1152408
, 966 (2008);319 Science
Jeffrey D. Karpicke and Henry L. Roediger III
The Critical Importance of Retrieval for Learning
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The Critical Importance
of Retrieval for Learning
Jeffrey D. Karpicke
*and Henry L. Roediger III
Learning is often considered complete when a student can produce the correct answer to a
question. In our research, students in one condition learned foreign language vocabulary words in
the standard paradigm of repeated study-test trials. In three other conditions, once a student had
correctly produced the vocabulary item, it was repeatedly studied but dropped from further testing,
repeatedly tested but dropped from further study, or dropped from both study and test. Repeated
studying after learning had no effect on delayed recall, but repeated testing produced a large
positive effect. In addition, studentspredictions of their performance were uncorrelated with
actual performance. The results demonstrate the critical role of retrieval practice in consolidating
learning and show that even university students seem unaware of this fact.
Ever since the pioneering work of Ebbinghaus
(1), scientists have generally studied hu-
man learning and memory by presenting
people with information to be learned in a study
period and testing them on it in a test period to
see what they retained. When this procedure oc-
curs over many trials, an exponential learning
curve is produced. The standard assumption in
nearly all research is that learning occurs while
people study and encode material. Therefore, ad-
ditional study should increase learning. Retriev-
ing information on a test, however, is sometimes
considered a relatively neutral event that mea-
sures the learning that occurred during study but
does not by itself produce learning. Over the
years, researchers have occasionally argued that
learning can occur during testing (26). However,
the assumptions that repeated studying promotes
learning and that testing represents a neutral event
that merely measures learning still permeate con-
temporary memory research as well as contem-
porary educational practice, where tests are also
considered purely as assessments of knowledge.
Our goal in the present research was to ex-
amine these long-standing assumptions regard-
ing the effects of repeated studying and repeated
testing on learning. Specifically, once informa-
tion can be recalled from memory, what are the
effects of repeated encoding (during study trials)
or repeated retrieval (during test trials) on learn-
ing and long-term retention, assessed after a
week delay? A second purpose of this research
was to examine studentsassessments of their
own learning. After learning a set of materials
under repeated study or repeated test conditions,
we asked students to predict their future recall
on the week-delayed final test. Our question
was, would students show any insight into their
own learning?
A final purpose of the experiment was to
address another venerable issue in learning and
memory, concerning the relation between the
speed with which something is learned and the
rate at which it is forgotten. Is speed of learning
correlated with long-term retention, and if so, is
the correlation positive (processes that promote
fast learning also slow forgetting and promote
good retention) or negative (quick learning may
be superficial and produce rapid forgetting)? Early
research led to the conclusion that quick learn-
ing reduced the rate of forgetting and improved
long-term retention (7), but later critics argued
that, when forgetting is assessed more properly
than in the early studies, no differences exist be-
tween forgetting rates for fast and slow learning
conditions (8,9). By any account, conditions that
exhibit equivalent learning curves should produce
equivalent retention after a delay (9).
Using foreign language vocabulary word pairs,
we examined the contributions of repeated study
and repeated testing to learning by comparing a
standard learning condition to three dropout condi-
tions. The standard method of measuring learning,
used since Ebbinghauss research (1), involves
presenting subjects with information in a study
period, then testing them on it in a test period,
then presenting it again, testing on it again, and so
on. The dropout learning conditions of the present
experiment differed from the standard learning
condition in that, once an item was successfully
recalled once on a test, it was either (i) dropped
from study periods but still tested in one con-
dition, (ii) dropped from test periods but still re-
peatedly studied in a second condition, or (iii)
dropped altogether from both study and test pe-
riods in a third condition (Table 1).
Surprisingly, standard learning conditions
and dropout conditions have seldom been com-
pared in memory research, despite their critical
importance to theories of learning and their prac-
tical importance to students (in using flash cards
and other study methods). Dropout conditions
were originally developed to remedy methodo-
logical problems that arise from repeated practice
in the standard learning condition (10), but they
can also be used to examine the effect of re-
peated practice in its own right, as we did in the
present experiment. If learning happens exclu-
sively during study periods and if tests are neutral
assessments, then additional study trials should
have a strong positive effect on learning, whereas
additional test trials should produce no effect.
Further, if repeated study or test practice after an
item has been learned does indeed benefit long-
term retention, this would contradict the conven-
tional wisdom that students should drop material
that they have learned from further practice in
order to focus their effort on material they have
not yet learned. Dropping learned facts may create
the same long-term retention as occurs in stan-
dard conditions but in a shorter amount of time,
or it may improve learning by allowing stu-
dents to focus on items they have not yet recalled.
This strategy is implicitly endorsed by contem-
porary theories of study-time allocation (11,12)
and is explicitly encouraged in many popular
study guides (13).
Department of Psychological Sciences, Purdue University,
West Lafayette, IN 47907, USA.
Department of Psychol-
ogy, Washington University in St. Louis, St. Louis, MO
63130, USA.
*To whom correspondence should be addressed. E-mail:
Table 1. Conditions used in the experiment, average number of trials within each study or test
period, and total number of trials in the learning phase in each condition. S
indicates that only
vocabulary pairs not recalled in the previous test period were studied in the current study period. T
indicates that only pairs not recalled in the previous test period were tested in the current test
period. Students in all conditions performed a 30-s distracter task that involved verifying multi-
plication problems after each study period.
Study (S) or test (T) period and number of trials per period Total
of trials
12 3 4 5 6 7 8
40 40 40 40 40 40 40 40 320
40 40 26.8 40 8.0 40 2.0 40 236.8
40 40 40 27.9 40 11.8 40 3.3 243.0
40 40 27.1 27.1 8.8 8.8 1.5 1.5 154.8
15 FEBRUARY 2008 VOL 319 SCIENCE www.sciencemag.org966
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In the experiment, we had college students
learn a list of foreign language vocabulary word
pairs and manipulated whether pairs remained in
the list (and were repeatedly practiced) or were
dropped after the first time they were recalled,
as shown in Table 1. All students began by study-
ing a list of 40 Swahili-English word pairs (e.g.,
mashua-boat) in a study period and then testing
over the entire list in a test period (e.g., mashua-?).
All conditions were treated the same in the ini-
tial study and test periods. Once a word pair was
recalled correctly, it was treated differently in the
four conditions. In the standard condition, sub-
jects studied and were tested over the entire list in
each study and test period (denoted ST). In a
second condition, once a pair was recalled, it was
dropped from further study but tested in each sub-
T, wh e re S
cates that only nonrecalled pairs were restudied).
In a third condition, recalled pairs were dropped
from further testing but studied in each subsequent
study period (denoted ST
that only nonrecalled pairs were kept in the list
during test periods). In a fourth condition, recalled
pairs were dropped entirely from both study and
test periods (S
). The final condition repre-
sents what conventional wisdom and many edu-
cators instruct students to do: Study something
until it is learned (i.e., can be recalled) and then
drop it from further practice.
At the end of the learning phase, students in
all four conditions were asked to predict how
many of the 40 pairs they would recall on a final
test in 1 week. They were then dismissed and
returned for the final test a week later. Of key
importance were the effects of the four learning
conditions on the speed with which the vocabulary
words were learned, on studentspredictions of
their future performance, and on long-term reten-
tion assessed after a week delay (14).
Figure 1 shows the cumulative proportion of
word pairs recalled during the learning phase,
which gives credit the first time a student recalled
a pair. We also analyzed traditional learning
curves (the proportion of the total list recalled
in each test period) for the two conditions that
required recall of the entire list (ST and S
and the results by the two measurement meth-
ods were identical. Thus, we restrict our dis-
cussion to the cumulative learning curves on
which all four conditions can be compared.
Figure 1 shows that performance was virtually
perfect by the end of learning (i.e., all 40 English
target words were recalled by nearly all sub-
jects). More importantly, there were no differences
in the learning curves of the four conditions.
Given the similarity of acquisition perform-
ance, it is not too surprising that students in the
four conditions did not differ in their aggregate
judgments of learning (their predictions of their
future performance). On average, the students in
all conditions predicted they would recall about
50% of the pairs in 1 week. The mean number of
words predicted to be recalled in each condition
were as follows: ST = 20.8, S
22.0, and S
= 20.3. An analysis of variance did
not reveal significant differences among the
conditions (F<1).
Although studentscumulative learning per-
formance was equivalent in the four conditions
and predicted final recall was also equivalent,
actual recall on the final delayed test differed
widely across conditions, as shown in Fig. 2.
The results show that testing (and not studying)
is the critical factor for promoting long-term re-
call. In fact, repeated study after one successful
recall did not produce any measurable learning
a week later. In the learning conditions that re-
quired repeated retrieval practice (ST and S
students correctly recalled about 80% of the
pairs on the final test. In the other conditions in
which items were dropped from repeated test-
ing (ST
and S
), students recalled just
36% and 33% of the pairs. It is worth em-
phasizing that, despite the fact that students
repeatedly studied all of the word pairs in every
study period in the ST
condition, their long-
term recall was much worse than students who
were repeatedly tested on the entire list. Com-
bining the two conditions that involved repeated
testing (ST and S
T) and combining the two
conditions that involved dropping items from
testing after they were recalled once (ST
), repeated retrieval increased final recall
by 4 standard deviations (d= 4.03). The distri-
butions of scores in these two groups did not
overlap: Final recall in the drop-from-testing
conditions ranged from 10% to 60%, whereas
final recall in the repeated test conditions ranged
from 63% to 95%. Whether students repeatedly
studied the entire set or whether they restudied
only pairs they had not yet recalled produced
virtually no effect on long-term retention. The
dramatic difference shown in Fig. 2 was caused
by whether or not the pairs were repeatedly tested.
Even though cumulative learning perform-
ance was identical in the four conditions, the
total number of trials (study or test) in each con-
dition varied greatly. Table 1 shows the mean
number of trials in each study and test period
and the total number of trials in each condition.
The standard condition (ST) involved the most
trials (320) because all 40 items were presented
in each study and test period. The S
tion involved the fewest trials (154.8, on aver-
age) because the number of trials in each period
grew smaller as items were recalled and dropped
from further practice. The other two conditions
) involved about the same number
of trials (236.8 and 243.0, respectively) but be-
cause they differed in terms of whether items
were dropped from study or test periods, they
produced dramatically different effects on long-
term retention. In other words, about 80 more
study trials occurred in the ST
condition than
in the S
condition, but this produced prac-
tically no gain in retention. Likewise, about 80
more study trials occurred in the ST condition
than in the S
T condition, and this produced no
gain whatsoever in retention. However, when
about 80 more test trials occurred in the learning
phase (in the ST condition versus the ST
dition, and in the S
T condition versus the S
condition), repeated retrieval practice led to greater
than 150% improvements in long-term retention.
The present research shows the powerful ef-
fect of testing on learning: Repeated retrieval
practice enhanced long-term retention, whereas
repeated studying produced essentially no ben-
efit. Although educators and psychologists often
consider testing a neutral process that merely
assesses the contents of memory, practicing re-
trieval during tests produces more learning than
additional encoding or study once an item has
been recalled (1517). Dropout methods such as
the ones used in the present experiment have
seldom been used to investigate effects of re-
peated practice in their own right, but compar-
ison of the dropout conditions to the repeated
practice conditions revealed dramatic effects of
retrieval practice on learning.
Fig. 1. Cumulative performance during the learn-
ing phase.
Fig. 2. Proportion recalled on the final test 1 week
after learning. Error bars represent standard errors
of the mean. SCIENCE VOL 319 15 FEBRUARY 2008 967
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The experiment also shows a striking ab-
sence of any benefit of repeated studying once
an item could be recalled from memory. A basic
tenet of human learning and memory research is
that repetition of material improves its retention.
This is often true in standard learning situations,
yet our research demonstrates a situation that
stands in stark contrast to this principle. The
benefits of repetition for learning and long-term
retention clearly depend on the processes learners
engage in during repetition. Once information
can be recalled, repeated encoding in study trials
produced no benefit, whereas repeated retrieval
in test trials generated large benefits for long-
term retention. Further research is necessary to
generalize these findings to other materials. How-
ever, the basic effects of testing on retention have
been shown with many kinds of materials (16),
so we have confidence that the present results
will generalize, too.
Our experiment also speaks to an old debate
in the science of memory, concerning the rela-
tion between speed of learning and rate of for-
getting (79). Our study shows that the forgetting
rate for information is not necessarily deter-
mined by speed of learning but, instead, is greatly
determined by the type of practice involved.
Even though the four conditions in the experi-
ment produced equivalent learning curves, re-
peated recall slowed forgetting relative to
recalling each word pair just one time.
Importantly, students exhibited no awareness
of the mnemonic effects of retrieval practice, as
evidenced by the fact that they did not predict
they would recall more if they had repeatedly
recalled the list of vocabulary words than if they
only recalled each word one time. Indeed, ques-
tionnaires asking students to report on the strat-
egies they use to study for exams in education
also indicate that practicing recall (or self-testing)
is a seldom-used strategy (18). If students do test
themselves while studying, they likely do it to
assess what they have or have not learned (19),
rather than to enhance their long-term retention
by practicing retrieval. In fact, the conventional
wisdom shared among students and educators is
that if information can be recalled from mem-
ory, it has been learned and can be dropped
from further practice, so students can focus their
effort on other material. Research on students
use of self-testing as a learning strategy shows
that students do tend to drop facts from further
practice once they can recall them (20). However,
the present research shows that the conventional
wisdom existing in education and expressed in
many study guides is wrong. Even after items
can be recalled from memory, eliminating those
items from repeated retrieval practice greatly re-
duces long-term retention. Repeated retrieval in-
duced through testing (and not repeated encoding
during additional study) produces large positive
effects on long-term retention.
References and Notes
1. H. Ebbinghaus, Memory: A Contribution to Experimental
Psychology, H. A. Ruger, C. E. Bussenius, Transls. (Dover,
New York, 1964).
2. R. A. Bjork, in Information Processing and Cognition:
The Loyola Symposium, R. L. Solso, Ed. (Erlbaum,
Hillsdale, NJ, 1975), pp. 123144.
3. M. Carrier, H. Pashler, Mem. Cognit. 20, 633 (1992).
4. A. I. Gates, Arch. Psychol. 6, 1 (1917).
5. C. Izawa, J. Math. Psychol. 8, 200 (1971).
6. E. Tulving, J. Verb. Learn. Verb. Behav. 6, 175 (1967).
7. J. A. McGeoch, The Psychology of Human Learning
(Longmans, Green, New York, 1942).
8. N. J. Slamecka, B. McElree, J. Exp. Psychol. Learn. Mem.
Cogn. 9, 384 (1983).
9. B. J. Underwood, J. Verb. Learn. Verb. Behav. 3, 112
10. W. F. Battig, Psychon. Sci. Monogr. 1(suppl.), 1 (1965).
11. J. Metcalfe, N. Kornell, J. Exp. Psychol. Gen. 132, 530
12. K. W. Thiede, J. Dunlosky, J. Exp. Psychol. Learn. Mem.
Cognit. 25, 1024 (1999).
13. S. Frank, The Everything Study Book (Adams, Avon, MA,
14. Materials and methods are available as supporting
material on Science Online.
15. J. D. Karpicke, H. L. Roediger, J. Mem. Lang. 57, 151
16. H. L. Roediger, J. D. Karpicke, Perspect. Psychol. Sci. 1,
181 (2006).
17. H. L. Roediger, J. D. Karpicke, Psychol. Sci. 17, 249
18. N. Kornell, R. A. Bjork, Psychon. Bull. Rev. 14, 219 (2007).
19. J. Dunlosky, K. Rawson, S. McDonald, in Applied
Metacognition, T. Perfect, B. Schwartz, Eds. (Cambridge
Univ. Press, Cambridge, 2002), pp. 6892.
20. J. D. Karpicke, thesis, Washington University, St. Louis,
MO (2007).
21. We thank J. S. Nairne for helpful comments on the
manuscript. This research was supported by a
Collaborative Activity Grant of the James S. McDonnell
Foundation to the second author.
Supporting Online Material
Materials and Methods
Table S1
31 October 2007; accepted 12 December 2007
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... Another strategy is elaboration which involves relating new information to existing knowledge. At the same time, rehearsal refers to the repeated practice of encoding and retrieving information, both of which can strengthen memory and facilitate information integration into the argumentative writing process (Craik and Lockhart, 1972;Karpicke and Roediger, 2008). ...
... In addition, rehearsal is the process of repeatedly encoding and retrieving information to strengthen memory and facilitate information integration (Karpicke and Roediger, 2008). In argumentative writing, students can practice rehearsal by frequently reviewing their notes, summarizing key arguments and evidence, and engaging in discussions or debates on the topic. ...
... Both techniques have been shown to improve students' recall of new vocabulary and concepts. Karpicke and Roediger (2008) examined the importance of retrieval practice, a memory strategy that involves actively recalling information rather than passively rereading or reviewing the material. Their study found that students who engaged in retrieval practice demonstrated better long-term retention compared to those who only reviewed their notes or material. ...
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... So that it allows students to better remember the material being studied because it brings out the information stored in memory. This is in line with the opinion of Karpicke et al. (2008) that learning outcomes can be seen from how students remember the answers to a question regarding previously studied material. ...
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... Many studies provide empirical evidence that addressing questions in tests and exams can improve memory recall and the retention of information (Butler & Roediger, 2007;Deng et al., 2015;Karpicke & Roediger, 2008;McDaniel et al., 2007;Roediger & Karpicke, 2006). These studies, in the field cognitive psychology, define this phenomenon as 'the testing effect' or 'test-enhanced learning,' and show that testing produces greater retention than studying. ...
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High-stakes examinations enjoy widespread use as summative assessments in higher education. We review the arguments for and against their use, across seven common themes: memory recall and knowledge retention; student motivation and learning; authenticity and real-world relevance; validity and reliability; academic misconduct and contract cheating; stress, anxiety and wellbeing; and fairness and equity. For each theme, we evaluate empirical evidence for the perceived pedagogical benefits and pedagogical drawbacks of high-stakes examinations. We find that relatively few of the perceived academic benefits of high-stakes examinations have a strong evidence base. Support for their use is largely rooted in opinion and pragmatism, rather than being justified by scientific evidence or pedagogical merit. By contrast, there is substantial evidence for pedagogical drawbacks of high-stakes summative examinations. We conclude that the current heavy reliance on high-stakes final examinations in many university subjects is poorly justified by the balance of empirical evidence.
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... This makes it more likely that the information will be successfully retrieved again in the future. Enlarging the associative retrieval network will facilitate transfer of what is learned (Karpicke & Roediger, 2008;Roediger & Butler, 2011), which in our case may also affect valenced autobiographical memories. ...
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... One common assessment of episodic memory involves presenting pairs of items and later probing retention of the associations. Although one-shot learning of paired associates is possible, many paradigms have participants with re-engage with the material through retrieval practice or restudying, and there is a well-established benefit of the former, known as the testing effect [22][23][24][25][26][27][28] . There is debate as to whether the "desirable difficulty" 29,30 or effortfulness 31 of searching for and retrieving a target association is what strengthens memory or whether testing is advantageous because the episodic experience of retrieval practice is more contextually similar to the final test 32 . ...
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Background Flipped classroom, blended with online and offline learning, was regarded as an effective learning approach in pharmacy education. This meta-analysis was to comprehensively compare the effectiveness of flipped classroom and traditional lecture-based approaches, attempting to generate a unified and firm conclusion of the effectiveness of flipped classroom in pharmacy education. Methods Data were collected from 7 databases, involving Cochrane Library, PubMed, Embase, ScienceDirect, Web of Science, China National Knowledge Infrastructure (CNKI), and Chinese Biomedical Literature Service System (SinoMed). The studies were included if they included objective evaluation of students’ performance between groups of flipped classroom and traditional approaches. The standardized mean difference (SMD) with a corresponding 95% confidence interval (95% CI) was used as the outcomes for data pooling. Results A total of 22 studies (28 comparing groups) with 4379 participants were included in the meta-analysis. The risk of bias was relatively high. Results of the analysis revealed that flipped classroom presented significant advantages over traditional approaches in student performance improvement, with no evidence of publication bias. Through subgroup analysis, it showed better outcomes for flipped classrooms over traditional lectures for the other subgroups, including different performance, degree programs. Conclusions Current evidence reveals that the flipped classroom approach in pharmacy education yields a statistical improvement in student learning compared with traditional methods. In the future, instructors should introduce more online technology into classroom and construct an interactive learning environment.
A central part of singing includes learning new pieces of vocal music. Learning a new song is a complex task that involves several functions and modalities, such as memory functions, language and motor skills, and auditory and visual perception. Memory functions are a well-studied area, but it is unknown how memory theories apply to a multimodal activity such as singing. In this study, an attempt is made to translate the theories to the applied field of singing. This study aims to investigate the effectiveness of three types of learning formats for learning new song lyrics: auditory learning with image support (AI), auditory learning with text support (AT), and auditory learning only (A). Ninety-five participants were randomly assigned to one of the three experimental conditions. A univariate analysis of variance revealed a significant effect of condition on the lyric recall score and post-hoc tests showed that participants performed significantly better in the AI condition in comparison to both the AT and the A condition. No significant difference was found between AT and A. This study sheds light on how memory processes might work in learning song lyrics. Practical implications for practitioners such as music educators, conductors, and choir singers are discussed.
A daily quiz on Newtonian biomechanics has previously been shown to improve student self-confidence, enthusiasm, and test results in biomechanics courses. This study investigated whether such a quiz could also improve retention of knowledge over a longer term. Our study found that students who participated very actively in daily quizzes scored significantly better on a retention test compared to those who participated less actively or not at all. From these results, we can conclude that very active participation in a daily quiz resulted in a slight gain in the long-term retention of biomechanics knowledge.
Student-study behaviors and metacognition are predictors of student-academic success. However, student metacognitive evaluation of their own study habit behavior use has been largely unexplored. To address this gap, we gave students enrolled in three different Biology courses (n = 1140) a survey that asked them to identify the study behaviors used to prepare for their first and third exams and to appraise the effectiveness of each behavior. We observed that, across all courses, students used different counts of active- and passive-study behaviors. However, there were no differences in performance across courses, and the use of effective (i.e., active) study behaviors resulted in improved exam performance for all students, regardless of course, while the use of ineffective (i.e., passive) study behaviors had no significant impact on exam performance. Finally, our qualitative analysis revealed that students across all courses demonstrated similar ability in identifying effective-study behaviors, but students could not explain why those behaviors were effective. Taken together, our study demonstrates that students use various study behaviors to prepare for exams without understanding their effectiveness. We encourage instructors to structure their courses to promote the development of metacognitive evaluation and effective-study behaviors.
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A powerful way of improving one's memory for material is to be tested on that material. Tests enhance later retention more than additional study of the material, even when tests are given without feedback. This surpris- ing phenomenon is called the testing effect, and although it has been studied by cognitive psychologists sporadically over the years, today there is a renewed effort to learn why testing is effective and to apply testing in educational settings. In this article, we selectively review laboratory studies that reveal the power of testing in improving re- tention and then turn to studies that demonstrate the basic effects in educational settings. We also consider the related concepts of dynamic testing and formative assess- ment as other means of using tests to improve learning. Finally, we consider some negative consequences of testing that may occur in certain circumstances, though these negative effects are often small and do not cancel out the large positive effects of testing. Frequent testing in the classroom may boost educational achievement at all levels of education. In contemporary educational circles, the concept of testing has a dubious reputation, and many educators believe that testing is overemphasized in today's schools. By ''testing,'' most com- mentators mean using standardized tests to assess students. During the 20th century, the educational testing movement produced numerous assessment devices used throughout edu- cation systems in most countries, from prekindergarten through graduate school. However, in this review, we discuss primarily the kind of testing that occurs in classrooms or that students engage in while studying (self-testing). Some educators argue
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People of all ages are more likely to choose to restudy items (or allocate more study time to items) that are perceived as more difficult to learn than as less difficult to learn. Existing models of self-regulated study adequately account for this inverse relation between perceived difficulty of learning and these 2 measures of self-regulated study (item selection and self-paced study). However, these models cannot account for positive relations between perceived difficulty of learning and item selection, which are demonstrated in the present investigation. Namely, in Experiments 1 and 2, the authors described conditions in which people more often selected to study items judged as less difficult than as more difficult to learn. This positive relation was not demonstrated for self-paced study, which was always negatively correlated with judged difficulty to learn. In Experiments 3 through 6, the authors explored explanations for this dissociation between item selection and self-paced study. Discussion focuses on a general model of self-regulated study that includes planning, discrepancy reduction, and working-memory constraints. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
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Three experiments, with 276 undergraduates, examined how degree of learning affects normal forgetting. Exp I varied learning of categorized lists and tested retention at 3 intervals (immediately and 1 or 5 days after presentation). Across all measures, study trials affected intercepts but not slopes of forgetting functions. Exp II varied learning of paired-associate lists and tested retention at the same 3 intervals. Across all measures, trials influenced intercepts but not forgetting slopes. Exp III varied learning of sentence lists and tested verbatim and gist memory at the same intervals. Again, trials affected intercepts but not slopes. Results suggest that the forgetting of verbal lists is independent of their degree of learning. No current theories of memory predict these outcomes, but neither does the pattern of results disconfirm any theory. It is argued that present memory theorizing neglects almost entirely the central problem of normal forgetting. (36 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
There is a growing theoretical and practical interest in the topic of metacognition; how we monitor and control our mental processes. Applied Metacognition provides a coherent and up-to-date overview of the relation between theories in metacognition and their application in real-world situations. As well as a theoretical overview, there are substantive chapters covering metacognition in three areas of application: metacognition in education, metacognition in everyday life memory and metacognition in different populations. A diverse range of topics are covered such as how we judge our own learning, why we create false beliefs about our past, how children learn to monitor and control their memory, how well eyewitnesses can judge the accuracy of their own memories and how memory judgements change across the lifespan. The book has contributions from many of the leading researchers in metacognition from around the world.
This paper was directed toward problems involved in the measurement of forgetting uncontaminated by differences in degree of learning. More particularly, it was concerned with these measurements when some variable, such as a characteristic of the task, is being manipulated and when such a variable produces differences in rate of learning. If we are to assess properly the influences of these variables on retention, degree of learning must be equated, since degree of learning and retention are directly related. The two basic situations considered were those in which a constant number of learning trials was given and those in which learning was carried to a specified criterion of performance. The single-entry technique is appropriate only when a constant number of learning trials is used. When a criterion of performance is set for learning another procedure (multiple-entry projection) may be used. Although the mean predictions are fairly accurate by this method, predictions for individual Ss are not. In most studies of retention it seems most efficient to use a constant-trials procedure for learning. Finally, it was pointed out that some studies of short-term retention of single items have probably confounded effects of degree of learning on retention with the effects of variables producing differences in rate of learning the items.
A theory is proposed to account for the functions of unreinforced test (T) trials in paired-associate learning: the forgetting-prevention effects as contrasted to blank (B) trials and the potentiating effects upon the subsequent reinforcement (R) trials. Both empirical effects were confirmed, through six experiments with a total of 384 valid subjects, under the three basic repetitive programming of R-T-B sequences of RT1 … Tm (Case 1), RB1 … Bm−1T (Case 2), and RTB1 … Bm−1 (Case 3), in which m was varied from 1 to 5. To solve the fifficulties encountered in extant learning theories, the new model postulates active retrieval processes as unique theoretical functions of T trials. The processes did not change empirical response probabilities significantly over the m successive Ts within a replication, but resulted in increasing the effectiveness on the subsequent Rs. Consistently satisfactory quantitative analyses with respect to both empirical effects of Ts provided decisive grounds for support for the proposed test trial potentiating model.
From a much larger number 1200 titles have been selected covering the period from the work of Ebbinghaus to and including the year 1930. Selection is on the basis of significance for learning as such, representativeness, and availability. Under Learning, the titles are grouped under fifty topics, and under Retention they are grouped under thirty-two. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
A comprehensive survey of the literature on human learning for advanced students and research workers in this area. Although certain organizational changes are made in the revision, the author has attempted to maintain Dr. McGeoch's (see 16: 4303) systematic position with regard to the increased factual knowledge and new emphasis in the field. Extensive chapter bibliographies. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Tests not only measure the contents of memory, they can also enhance learning and long-term retention. We report two experiments inspired by Tulving’s (1967) pioneering work on the effects of testing on multitrial free recall. Subjects learned lists of words across multiple study and test trials and took a final recall test 1 week after learning. In Experiment 1, repeated testing during learning enhanced retention relative to repeated studying, although alternating study and test trials produced the best retention. In Experiment 2, recalled items were dropped from further studying or further testing to investigate how different types of practice affect retention. Repeated study of previously recalled items did not benefit retention relative to dropping those items from further study. However, repeated recall of previously recalled items enhanced retention by more than 100% relative to dropping those items from further testing. Repeated retrieval of information is the key to long-term retention.