Revising lecture notes: how revision, pauses,
and partners affect note taking and achievement
•Kenneth A. Kiewra
Received: 29 June 2015 / Accepted: 19 January 2016 / Published online: 25 January 2016
Springer Science+Business Media Dordrecht 2016
Abstract Note taking has been categorized as a two-stage process: the recording of notes
and the review of notes. We contend that note taking might best involve a three-stage
process where the missing stage is revision. This study investigated the beneﬁts of revising
lecture notes and addressed two questions: First, is revision more effective than non-
revision? Second, what revision method is best? Experiment 1 addressed the ﬁrst question
by comparing the performance of participants who revise or recopy lecture notes.
Experiment 2 addressed the second question by investigating whether revision was best
done (a) during pauses throughout the lecture or one equally-timed pause after the lecture,
and (b) with a partner or alone. Dependent measures were original and additional notes and
fact and relationship test scores. Results upheld three effects: (a) a modest revision effect—
revisers recorded more additional notes and achieved somewhat higher scores on rela-
tionship items than re-copiers, (b) a pause effect—those revising during pauses outper-
formed those revising after the lecture on the notes and achievement measures, and (c) a
modest partner effect—those revising with partners recorded more original notes than
those revising alone. Furthermore, the combination of pauses and partners has merit and
holds promise as a means for revision. Overall, ﬁndings suggested that revision is a new
student-centered means to boost lecture note taking and achievement.
Keywords Note taking Note revision Lecture pauses Collaborative learning
Despite recent advancements in instructional technology, lecture remains the dominant
instructional format in most college classrooms (Exley and Dennick 2009; Maydosz and
Department of Educational Psychology, University of Nebraska-Lincoln, Lincoln, NE 68588-0345,
Instr Sci (2016) 44:45–67
Raver 2010; Watts and Becker 2008). Meanwhile, most college students today still record
notes during lectures (Bonner and Holliday 2006; Castello and Monereo 2005) and prefer
to take notes by hand rather than by computer because they believe that hand written notes
allow greater ﬂexibility for signaling important ideas and for creating diagrams and other
graphic organizers (Reimer et al. 2009; Schoen 2012). A recent study conﬁrmed the
beneﬁts of hand written notes. Students who took hand written notes outperformed those
who took laptop notes (Mueller and Oppenheimer 2014).
It is good that students still value note taking because both the process of recording
notes (versus listening only) and the product reviewed (versus no review) raise fact and
relationship learning (e.g., Kiewra 1985a,1989a). The process value of note taking is
attributed to increased attention during the lecture (e.g., Katayama and Crooks 2003;
Kobayashi 2006; Piolat et al. 2005), whereas the product value is attributed to meaningful
processing during review following the lecture (e.g., Armbruster, 2000; Crooks et al.
2007). It is also good that students value note taking because the more paraphrased notes
students record, the higher their achievement (Peverly et al. 2003; Williams and Worth
2002). There is, however, a problem. Students are incomplete note-takers and normally
record just one third of important lecture points (Austin et al. 2004; Titsworth 2004). When
key points are omitted from notes, there is only about a 5 % chance of students recalling
those missing points when tested (Einstein et al. 1985; Howe, 1970). Naturally, researchers
have investigated ways to increase lecture note completeness.
Methods for increasing lecture notes
Four proven methods for increasing note completeness are (a) providing full notes,
(b) providing skeletal notes, (c) providing lecture cues, and (d) re-presenting the lecture.
One obvious means for bolstering notes is for instructors to give students a full set of
notes to review (Grabe 2005; Stefanou et al. 2008). In one representative study (Kiewra
1985b), college students, during the acquisition phase, listened to a lecture, recorded notes
during the lecture, or absented themselves from the lecture. Two days later, during the
review phase, they studied their own notes, a set of full notes provided by the instructor,
both sets of notes, or no notes (depending upon condition). Results showed that groups that
studied full notes achieved most regardless of their acquisition condition. This was because
students’ own notes contained just 35 % of important lecture points compared to 100 % for
A related means for bolstering lecture notes is providing a skeletal outline that presents
the lecture’s main points with spaces below for recording lecture details (Konrad et al.
2009; Raver and Maydosz 2010). In one such study (Kiewra et al. 1995), college students
viewed a lecture on creativity and took notes on blank paper or on a skeletal outline. Those
recording notes on blank paper noted 38 % of lecture points, whereas those using the
skeletal outline noted 56 % of lecture points. A more recent study (Austin et al. 2004) also
found that participants given skeletal notes recorded more lecture information than those
without skeletal notes.
A third instructional strategy for increasing lecture notes is providing organizational
lesson cues (Titsworth 2004). Organizational cues alert students to the organization of the
lecture and to where lecture points ﬁt within that organization. In a study examining
organizational cues (Titsworth and Kiewra 2004), college students listened to one of two
versions of a lecture about communication theories: cued and un-cued. Both versions were
46 L. Luo et al.
well organized and identical with one exception: the cued version signaled the lesson’s
organization by emphasizing one of the four lesson topics (e.g., mass communication) and
one of the ﬁve lesson categories (e.g., description) each time a corresponding lesson point
was presented. Students receiving organizational cues noted more of the lecture’s orga-
nizational points (54 %) and details (80 %) than those not receiving cues (15 and 37 %,
Another method to bolster notes is re-presenting the lecture. In one study (Kiewra et al.
1991), college students recorded notes while watching a brief videotaped lecture presented
one, two, or three times. All three groups noted a high percentage (80 %) of the lecture’s
main ideas but differed in noting lecture details. The one-presentation group recorded
about 35 % of details, whereas the two- and three-presentation groups recorded about 50
and 60 % of details, respectively.
The four proven methods for increasing note taking share a common limitation. All
involve instructor-provided materials or are instructor controlled. Such studies do not
suggest avenues that students might take to improve their note taking. The present study
addressed this limitation by examining a more student-controlled means for increasing note
Revision: the missing link
Note-taking researchers have historically categorized note taking as a two-stage process:
the recording (transcription) of notes and the review (reading or studying) of notes (Di
Vesta and Gray 1972; Kiewra 1985a; Kobayashi 2006). All of the studies reviewed in the
earlier section, for example, helped students record (or simply gave them) a fuller set of
notes to later review. We contend that note taking might best involve a three-stage process
where the missing stage is revision. After notes are recorded, students might beneﬁt from a
brief revision period wherein they make changes to existing notes by adding to them to
make them more complete and understandable. To be clear, revision differs from review in
that the former process strives to add information to existing notes, whereas the latter
process strives to commit noted information to memory. The prospect of revision seems
warranted for two reasons: one based on overcoming lecture processing demands and the
other based on improving information processing. First, in terms of lecturing processing
demands, most college students are not equipped physiologically to record complete lec-
ture notes (Bassili and Joordens 2008; Bui and Myerson 2014; Peverly et al. 2013).
Although adults can listen at a rate of about 210 words per minute (Omoigui et al. 1999), a
level greater than the pace of most lectures—about 100–125 words per minute (Wong
2014), adults can only write at a rate of about 22 words per minute (Brown 1999). College
students, meanwhile, only type lecture ideas at a rate of about 33 words per minute (Karat
et al. 1999). A revision period would partially counteract the processing demands of
lectures by allowing students more time to add to existing notes before reviewing them.
Second, in terms of improved information processing, revision might serve a retrieval
function (Roediger 2000; Thomson and Tulving 1970) wherein notes recorded during
lecture help students retrieve and record additional lecture ideas not originally noted
(Williams and Eggert 2002). For example, suppose a psychology lecturer reports the
following: ‘‘Short-term memory has a limited capacity compared to long-term memory. It
holds about seven items at a time. This might be why zip codes and phone numbers are
seven or fewer digits long.’’ Now suppose that a student wrote this in notes: ‘‘short-term
Revising lecture notes: how revision, pauses, and partners…47
memory holds about seven things.’’ If the student is given a chance to revise, then this
original note might cue the student to retrieve and note related lecture information such as,
‘‘short-term memory is more limited than long-term memory’’ and ‘‘phone numbers and
zip codes are brief to accommodate short-term memory.’’
Retrieval, by way of revision, might do more than boost note completeness; it might
enhance learning and boost achievement directly. In one representative study (Karpicke
et al. 2009), students (a) reviewed a text four times, (b) reviewed it three times and then
practiced retrieving text material the ﬁnal time, (c) or reviewed it once and then practiced
retrieving text material three times. The retrieval groups achieved more than the review-
only group. Long-term retention for the review-only group was 15 %, but was 34 % for the
one-retrieval group and 80 % for the repeated retrieval group. According to Karpicke
(2012), retrieval aids learning because each act of retrieval enhances the value of retrieval
cues and improves one’s ability to retrieve knowledge in the future. Karpicke (2012)
concluded that retrieval could be integrated into many learning activities, including
In summary, because recording speed lags well behind lecture speed and because notes
might serve a retrieval function, revision seems to be a useful process for increasing noted
ideas and boosting achievement. Moreover, revision is a more student-controlled note-
improvement strategy than the instructor-controlled strategies like note provision (Grabe
2005) or cuing (Titsworth and Kiewra 2004) that are commonly investigated. To this point,
though, there has been little investigation of revision. No study has investigated revision
systematically by comparing revision with no revision, and a survey of students’ study
strategies yielded no evidence of revising lecture notes (Jairam and Kiewra 2010). Instead,
students commonly recopy notes between lectures and review (Aharony 2006; Jairam and
The most basic way for students to revise lecture notes is to do so after the lecture and on
their own. But, that is not the only way. Revision might take place during lecture pauses
(instead of after the lecture) and with a partner (instead of alone). Although no previous
research has investigated these factors during the revision process, research indicates that
pauses and partners aid the note-taking and review processes and might aid the revision
process as well.
With respect to pauses, inserting them in lectures for purposes of taking or reviewing
notes is advantageous (see Boyle, 2007). With respect to inserting pauses for taking notes,
Aiken et al. (1975) had students take notes during lecture segments or during pauses
between lecture segments. Although the two note-taking groups recorded comparable
notes, the notes-during-pauses group scored higher on a delayed memory test and recalled
a higher percentage of noted ideas than did the notes-during-lecture-segments group. With
respect to inserting pauses for reviewing notes, Di Vesta and Gray (1973) had students
either take notes during lecture segments and then review them during lecture pauses or
take no notes during lecture segments and then review mentally during lecture pauses.
Those who took notes during lecture segments and reviewed them during lecture pauses
From a theoretical perspective, lecture pauses might be effective because they promote
distributed learning, which involves breaking a massed learning episode into smaller parts.
48 L. Luo et al.
The investigation of distributed versus massed learning originated with Ebbinghaus (1885/
1964) and Thorndike (1912) and is still active today. Recent reviews and investigations
(e.g., Cepeda et al. 2006; Stringfellow and Miller 2005) conﬁrm that distributed learning
produces higher achievement than massed learning probably because distributed learning
relative to massed learning aids (a) attention—attention is better maintained across brief
segments versus longer ones, (b) encoding—more associative links are made, and
(c) consolidation—more time is available for information to consolidate (take hold) in
With respect to partners, lecture-learning research stems from collaborative learning
theory rooted in the social learning ideas of Vygotsky (1962). Collaborative learning is a
situation in which two or more people attempt to learn something together while capi-
talizing on one another’s resources and skills (Bruffee 1999). Collaborative learning
generally works (Mitnik et al. 2009) because there is social responsibility to perform
(Gillies 2004; Johnson and Johnson 1999) and because meaningful processing is more
likely when individuals confer with partners (Delgado-Tellez and Raposo 2011).
According to Chi’s Interactive-Constructive-Active–Passive (ICAP) model (Chi and Wylie
2014), however, collaboration only enhances learning when partners truly interact and
jointly construct meaning. Without meaningful collaboration, there is often no advantage
for collaboration over individual learning (Barron 2003; Yetter et al. 2006).
Research on collaborative learning in note taking is mixed. With respect to the encoding
function of note taking, some research showed that recording lecture notes with a partner
led to more note taking than recoding notes alone and to improved learning (e.g., Kam
et al. 2005), but other research did not ﬁnd note-taking collaboration helpful (e.g., Aitken
and Hatt 2012). With respect to the storage function, reviewing lecture notes with a partner
was more advantageous than reviewing alone in one study (O’Donnell and Dansereau
1993) but no more advantageous than reviewing alone in another study (Lambiotte et al.
When it comes to revising notes, there might be two types of collaborative learning:
simple note sharing (e.g., ‘‘I didn’t have that point in notes, let me write it down’’), and
collaborative retrieval (e.g., ‘‘Okay, we both noted the deﬁnition, but wasn’t there an
example? Let’s try to recall that and add it to notes.’’). According to the ICAP model (Chi
and Wylie 2014), simple note sharing might boost the quantity of recorded notes, but
collaborative retrieval might directly improve learning because it is interactive and
Research questions, purpose, and predictions
Two primary research questions guided the present investigation: First, is revision more
effective than non-revision? Second, what revision method is best? To date, no study we
are aware of has examined the revision process of note taking exclusively and systemat-
ically. The ﬁrst question was addressed in Experiment 1. During a period between note
taking and review, participants either revised their original lecture notes or recopied them.
Recopying notes is a common practice for lecture note-taking students left to their own
devices (Jairam and Kiewra 2010; Karpicke et al. 2009). The second question was
addressed in Experiment 2. To determine the effect of pauses on revision, participants
either revised lecture notes during pauses interspersed throughout the lecture or revised
them during one equally timed pause at the end. To determine the effect of partners on
Revising lecture notes: how revision, pauses, and partners…49
revision, participants either revised notes alone or with a partner. This two-factor design
produced four revision groups: pause/partner, pause/no partner, no pause/partner, and no
pause/no partner. Dependent measures for both experiments included (a) notes that were
examined for ideas noted originally and during revision and (b) achievement test scores
measuring fact and relationship learning.
Three theoretical accounts guided our predictions. First, because revision might serve a
retrieval function wherein originally noted ideas spur the recall of previously non-noted
ideas, we predicted that the revision group would record more notes and achieve more than
the recopy comparison group (revision effect). Second, because lecture pauses distribute
learning, we predicted that groups with revision pauses interspersed throughout the lecture
would record more notes and achieve more than those with one equally timed revision
opportunity following the lecture (pause effect). Third, because working with a partner
allows for note sharing and collaborative retrieval, we predicted that those revising with a
partner would record more notes and achieve more than those revising alone (partner
Experiment 1 addressed the ﬁrst research question, is revision effective, by comparing the
performance of a revision group and non-revision (recopy) group.
Participants and design
Participants were 59 undergraduate education majors enrolled in an educational psychol-
ogy course at a large Midwestern university who participated in order to receive research
participation credit. Fifty-four percent were female, most were juniors and seniors (85 %),
and 88 % held grade-point averages (GPAs) of 3.0 or higher. Participants were assigned
randomly to either the revision group (n=29) or to the recopy (non-revision comparison)
Materials included a demographic survey, a lecture, blank paper and pens for note taking
and revision/recopy activities, a vocabulary ﬁller task, and an achievement test. The
demographic survey asked students to declare their gender (a. Male, b. Female), class
standing (a. Freshman, b. Sophomore, c. Junior, d. Senior), approximate overall GPA (a.
3.5–4.0, b. 3.0–3.4, c. 2.5–2.9, d. 2.0–2.4, e., below 2.0), and prior knowledge about
reinforcement schedules (a. Yes, b. No), which was the lecture topic. These demographics
were collected because they are sometimes related to academic achievement and students’
use of study strategies (e.g., DeBerard et al. 2004; Kiewra 1989b).
The 14-min, 1902-word lecture covered the topic of reinforcement schedules. This topic
and amount of coverage were standard for the course in which participants were enrolled.
Participants covered this topic later in the course weeks after the present study was con-
ducted. The lecture was audio-recorded (for standardization between groups) and presented
at a rate of 136 words per minute. An audio-recorded presentation mode was chosen (over
50 L. Luo et al.
video-recorded) because the lecture was exclusively verbal (spoken words with no written
or graphic supplements), making any visual display unnecessary. The lecture introduced
four types of schedules and then covered each in turn: ﬁxed ratio, variable ratio, ﬁxed
interval, and variable interval. For each schedule, information was provided with regard to
deﬁnition, example, behavior rate, and behavior pattern. The last lecture section covered
extinction for ﬁxed and variable schedules.
Blank paper was provided for participants to record lecture notes and to revise or recopy
notes following the lecture. Participants were given black pens for recording lecture notes
and given red pens for revising or recopying notes. Different colored pens were used so
that original notes could be distinguished from revised or recopied notes for analysis.
The ﬁller task was 10 vocabulary multiple-choice questions taken from sample
Scholastic Aptitude Test items. For example: The revolution in art has not lost its steam, it
____________ on as ﬁercely as ever (a. trudges, b. meanders, c. edges, d. ambles, e. rages).
This ﬁller task was also used to determine if groups differed in verbal ability.
The 20-item multiple-choice achievement test measured fact and relationship learning.
The 10-item fact portion was a measure of lower-level, rote learning. Each fact item
covered one lecture fact. For example: (1) Which schedule yields a scallop response
pattern (a. ﬁxed interval, b. variable interval, c. ﬁxed ratio, d. variable ratio)? (2) Which
best deﬁnes how extinction occurs (a. reinforcement is no longer delivered, b. punishment
is delivered rather than reinforcement, c. reinforcement is delivered in gradually smaller
and smaller amounts, d. a person has to respond more and more to earn reinforcement)?
The 10-item relationship portion was a measure of higher-level, associative learning. Each
relationship item covered an implicit (unstated) relationship between two schedules. For
example: (1) Which schedules involve slow responding (a. ﬁxed, b. variable, c. ratio, d.
interval)? (2) Which schedules involve rapid extinction (a. ﬁxed, b. variable, c. ratio, d.
interval)? A content expert reviewed the achievement test and conﬁrmed content validity;
each portion sampled the lecture content adequately and representatively (Haynes et al.
1995). Internal consistency, as measured by Cronbach’s alpha, was .310 for the fact items
and .718 for the relationship items. The low internal consistency coefﬁcient for the fact
items perhaps occurred because each item targeted a unique fact; the items, by nature, were
not supposed to correlate with one another. In addition, low internal consistency could also
be an artifact of the short test length (Onwuegbuzie and Daniel 2002). The internal con-
sistency for the relationship items was acceptable (Frisbie 1988).
Participants gathered in a single classroom and were assigned randomly to the revision or
recopy group. Participants received a folder that contained common materials, general
instructions, and group speciﬁc instructions. General instructions informed participants that
they would record notes in their own style using a provided black ink pen while listening to
a 14-min lecture and then study those notes for 10 min before completing an unrelated
vocabulary task (5 min) and a lecture-related fact and relationship test (10 min). Group-
speciﬁc instructions for the revision group informed them that they would have 15 min to
revise lecture notes immediately following the lecture in order to make them more com-
plete for review. They were told to use the provided red ink pen to add to their original
notes anything that might have been missed during the lecture and anything else that could
help them learn the material. Group speciﬁc instructions for the recopy group informed
them to recopy their notes for 15 min following the lecture. After instructions were read,
Revising lecture notes: how revision, pauses, and partners…51
all participants completed the demographic survey and then proceeded through the lecture,
revision/recopy, review, and testing phases as directed.
Tests were multiple-choice and were, therefore, scored objectively based on scoring keys.
All notes were scored for completeness using a scoring sheet that included all of the 95
lecture idea units derived from the lecture transcript. According to Kintsch’s (1988) model
of text comprehension, an idea unit (or proposition) is a conceptual unit composed of an
argument and its relations. A sample idea unit in the present study was: a variable ratio
schedule (argument) involves rapid responding (relation). One point was awarded for each
idea unit recorded. Thus, the maximum score was 95 points. Two scores were derived:
original notes, based on what was written in black ink during the lecture; and additional
notes, based on what was recorded in red ink during the revision period. The ﬁrst author
scored all notes. A reliability check was conducted by having another trained rater inde-
pendently score about one third of the notes. Peason’s rinter-rater correlation coefﬁcient
was .89 for original notes and .73 for additional notes. These indices exceeded the
threshold of good inter-rater reliability (Cohen 1988).
Preliminary analyses were conducted on demographic variables (gender, class standing,
GPA, and prior knowledge) and on verbal ability (vocabulary score) to ensure that the
groups were comparable. Table 1presents group statistics. Chi square tests assessed group
Table 1 Experiment 1 group
statistics for demographic
Revision (n=29) Recopy (n=30)
Male 14 48 13 43
Female 15 52 17 57
Freshman 0 0 1 3
Sophomore 4 14 4 13
Junior 1 3 5 17
Senior 24 83 20 67
3.5–4.0 14 48 12 40
3.0–3.4 13 45 13 43
2.5–2.9 2 7 5 17
2.0–2.4 0 0 0 0
Below 2.0 0 0 0 0
Yes 8 28 9 30
No 21 72 21 70
Verbal ability 29 54 30 62
52 L. Luo et al.
differences for categorical demographic variables (i.e., gender, class standing, GPA, and
prior knowledge), whereas an independent ttest assessed group difference for the con-
tinuous verbal ability variable. Results conﬁrmed that the revision and recopy groups were
comparable in terms of gender (v
(1, N=59) =.15, p=.70), class standing (v
N=59) =4.02, p=.26), GPA (v
(2, N=59) =1.42, p=.49), prior knowledge (v
(1, N=59) =.042, p=.84), and verbal ability (t(57) =1.71, p=.09).
Primary analyses pertained to the ﬁrst research question: Is revision more effective than
non-revision with respect to notes (original ideas and additional ideas) and achievement (fact
and relationship test scores)? To answer this research question, independent t-tests
employed to test differences between the revision and recopy groups on note measures and
achievement measures. Independent t-tests were chosen over MANOVAs because t-test is
the statistic of choice for two independent samples with small sample sizes (Larson and
Farber 2011). Moreover, MANOVA increases the complexity and ambiguity of results and
should, therefore, be avoided if possible (Tabachnick and Fidell 2007). When conducting t-
tests, Bonferroni correction was used to control the family-wise error rate due to multiple
comparisons (Rosenthal and Rubin 1984); therefore, the critical value for each individual test
was .05/4 =.0125. In addition, Hedges’ gwas provided as a measure of effect size for each
mean comparison (Lakens, 2013). According to Cohen (1992), effect sizes around .20 are
considered small, around .50 are considered moderate, and around .80 are considered large.
Table 2provided the means, standard deviations, and other important test statistics.
Finally, correlational analyses were conducted to determine relationships between notes
and achievement. If notes, and particularly additional notes, were related to achievement,
then that would supply further evidence for the value of revision.
The ﬁrst two rows of Table 2contain group note-taking statistics. With respect to original
notes, revision and recopy groups recorded comparable amounts during the lecture,
p=.82. Incidentally, each group recorded about 38 % of lecture ideas, which is consistent
with note completeness indices reported in previous studies (e.g., Kiewra 1985b; Titsworth
Table 2 Experiment 1 results summary of note and achievement measures by group
Variable Revision (n=29) Recopy (n=30) 95 % CI Hedges’ g
MSDMSDt(57) pLL UL
Idea units in notes
Original 38.6 10.5 38.0 9.2 .23 .82 -2.46 2.58 .06
Additional 3.2 2.3 0.0 0.0 7.57 .001 1.55 2.37 1.96
Fact 45.9 18.6 43.3 15.8 .56 .58 -4.25 4.55 .15
Relationship 45.9 27.8 33.0 19.7 2.06 .04 -5.60 6.66 .53
Mean and standard deviation values are percentages
CI conﬁdence interval, LL lower limit, UL upper limit
The assumption of normality was checked for each dependent variable. Most had a normal distribution.
Only one variable, additional notes, had a non-normal distribution. Therefore, both ttest and Mann–Whitney
U test were employed. The result of the Mann–Whitney U test mirrored the t-test result, so only t-test results
were reported in line with other analyses.
Revising lecture notes: how revision, pauses, and partners…53
2004). With respect to additional notes, revisers naturally added more lecture ideas during
the revision/recopy period than did re-copiers, p\.001.
Group achievement statistics appear in the bottom section of Table 2. With respect to fact
items, revisers and re-copiers performed comparably, p=.58. With respect to relationship
items, there was a modest revision effect, p=.04. The effect was not statistically sig-
niﬁcant because the pvalue, .04, was greater than the adjusted alpha level, .0125. Group
differences, however, are of practical importance given the mean differences (M=46 %
for revisers and M=33 % for re-copiers) and moderate effect size.
Notes and achievement
Table 3displays correlations between note-taking indices (original and additional) and
achievement measures (fact and relationship). As can be seen, most correlations are sta-
tistically signiﬁcant, and the largest correlations for fact and relationship achievement are
with additional notes. These ﬁndings conﬁrm previous research—that note taking is pos-
itively related to achievement (Peverly et al. 2003)—and offer new evidence that notes
made during revision are especially related to achievement.
The revision effect was upheld to some degree. Not surprisingly, the revision group, which
was instructed to add additional notes following the lecture, did, in fact, add more notes than
the non-revision comparison group, which was instructed to recopy their existing notes. With
respect to achievement, the revision group scored higher on the relationship test than the non-
revision group (although not statistically signiﬁcant when a Bonferroni correction was used).
In addition, notes made during revision were positively correlated with both fact and rela-
tionship achievement. We acknowledge, though, that revision had somewhat meager effects
on note taking and achievement. Therefore, we followed up with Experiment 2 to seek ways
to enhance revision through the use of lecture pauses and revision partners.
Experiment 2 addressed the second research question, what method of revision is best, by
investigating whether revision is best carried out (a) during lecture pauses or after the
lecture and (b) with a partner or alone.
Table 3 Experiment 1 correlations between note-taking indices and achievement measures
Original notes Additional notes Fact items Relationship items
Original notes – .146 .204 .309*
Additional notes – .310* .494**
Fact items – .382*
Relationship items –
*p\.05, ** p\.01
54 L. Luo et al.
Participants and design
Participants were 72 undergraduate education majors drawn from the same research pool
as those in Experiment 1. Participants in this sample did not participate in Experiment 1.
Seventy percent were female, most were juniors and seniors (90 %), and most (82 %) held
GPAs of 3.0 or higher.
Participants were assigned randomly to one cell of a 2 92 factorial design that spec-
iﬁed when and with whom lecture notes were revised. The ﬁrst factor was when notes were
revised: either during three 5-minute pauses spaced throughout the lecture or for 15 min
following the lecture. The second factor was with whom notes were revised: either with a
partner or alone. This research design resulted in a total of four groups: pause/partner
(n=18), pause/no partner (n=20), no pause/partner (n=14), and no pause/no partner
Materials were identical to those used in Experiment 1, except that there were two versions
of the lecture. One ran from start to ﬁnish without interruption for the no-pause groups. The
other version was divided into three roughly time-equivalent segments for the pause
groups. Pauses came during natural breaks in the content. The ﬁrst lecture pause came at
about ﬁve minutes, the second at about ten minutes, and the last at the end of the 14-minute
Internal consistency, as measured by Cronbach’s alpha, was .304 for the fact items on
the achievement test and .620 for the relationship items. As with Experiment1, the rela-
tively low internal consistency coefﬁcient for the fact items perhaps occurred because each
item targeted a unique fact; the items, by nature, were not supposed to correlate with one
another. In addition, the short test length might have contributed to the low internal
consistency coefﬁcient. The internal consistency for the relationship items was acceptable.
The four groups participated in the same classroom, with the same experimenter, but at
different times. In this way, each group participated in a classroom-like setting with all its
participants completing the same activities. Although this convenience sampling technique
is a threat to internal validity, the experimenter reduced the threat by strictly following a
script that ensured that all groups were treated equally except for their group-speciﬁc
instructions and activities.
All participants completed the demographic survey and then received and followed
experimental instructions. They were told that they would record notes in their own style
using a provided black ink pen while listening to a 14-min lecture and then study those
notes for 10 min before completing an unrelated vocabulary task (5 min) and a lecture-
related fact and relationship test (10 min). All groups were also told they would have
15 min to revise lecture notes in order to make them more complete for review. Speciﬁ-
cally, pause groups were told to revise during three 5-minute pauses spaced throughout the
lecture. No-pause groups were told to revise one time for 15 min immediately following
the lecture. Partner groups were told to revise with a partner (students numbered off before
Revising lecture notes: how revision, pauses, and partners…55
the lecture to determine partners). No-partner groups were told to revise alone. All groups
were told to use the provided red ink pen to add to their original notes anything that might
have been missed during the lecture and anything else that could help them learn the
The scoring process for notes and test items was identical to that described in Experiment
1. With regard to notes, a reliability check was conducted by having another trained rater
score independently about one third of the notes. Peason’s rinter-rater correlation coef-
ﬁcient was .85 for original notes and .90 for additional notes. These indices exceeded the
threshold of good inter-rater reliability (Cohen 1988).
In addition to these quantitative scoring procedures, notes made during revision were
also examined qualitatively to investigate the nature of revised notes more fully. The
original scoring method used in Experiment 1 simply determined how many new idea units
were added to notes (note additions). This qualitative examination also assessed note
extensions (additional information that makes an idea unit more complete) and note
elaborations (additional information linking the noted idea to information outside the
lecture) that were ignored in the original scoring method. For example, a student might
have recorded this statement in original notes and been credited with one idea unit:
‘‘Extinction is difﬁcult—slot machine.’’ During revision, the student might have extended
that note this way (‘‘Extinction is difﬁcult, for example, it would take a long time to
ﬁgure out that a slot machine is not paying off’’) and/or added this elaboration (‘‘Another
example is ignoring a baby’s crying during night’’) but not have received credit for adding
Preliminary analyses were conducted on demographic variables (gender, class standing,
GPA, and prior knowledge) and on verbal ability (vocabulary score) to ensure that the groups
were comparable. Table 4presents group statistics. Chi square tests assessed group differ-
ences for categorical demographic variables, and a one-way ANOVA assessed group dif-
ferences for the continuous verbal ability variable. Results conﬁrmed that the four groups
were comparable in terms of gender (v
(3, N=72) =2.65, p=.45), class standing (v
N=72) =4.62, p=.59), GPA (v
(9, N=72) =8.15, p=.52), prior knowledge (v
N=72) =2.39, p=.50), and verbal ability (F(3, 68) =1.15, p=.34).
Primary analyses pertained to the second research question: What manner of revision is
best with respect to notes and achievement? Two sets of dependent variables, notes
achievement, were analyzed separately using 2-way MANOVAs,
with pause and partner
as independent variables. Both multivariate tests had statistically signiﬁcant results. With
respect to the two types of notes, there were a signiﬁcant multivariate interaction effect of
pause and partner, Wilks’ lambda =.86, p=.008, and a main effect for pause, Wilks’
The sample size for notes analyses was less than that for achievement because two sets of notes were
misplaced and could not be scored.
The assumption of normality was checked for each dependent variable. Most had a normal distribution,
except additional notes. Therefore, in addition to the overall MANOVA test, a log transformation was
performed on the additional-notes measure and a one-way ANOVA followed. The signiﬁcant interaction
effect between pause and partner was conﬁrmed using the log transformation, just as in MANOVA.
Therefore, only MANOVA results were reported.
56 L. Luo et al.
lambda =.688, p\.001; but the main effect for partner was not signiﬁcant, p=.088.
With respect to the two types of achievement, the multivariate interaction effect was not
signiﬁcant, p=.717, but there was a signiﬁcant main effect for pause, Wilks’
lambda =.821, p=.001. The main effect for partner was not signiﬁcant, p=.313. All
signiﬁcant MANOVAs were followed up with univariate analyses for each dependent
variable and then with tests of simple effects and main effects when appropriate. Effect
sizes (i.e., eta squares) were also provided. According to Cohen (1992), effect sizes around
.02 are small, around .13 are moderate, and around .26 are large. Table 5presents inter-
action level results involving the individual groups (pause/no partner, pause/partner, no
Table 4 Experiment 2 group statistics for demographic variables
No pause/no partner
n M(%) n M(%) n M(%) n M(%)
Male 6 30 3 17 6 30 6 43
Female 14 70 15 83 14 70 8 57
Freshman 0 0 0 0 0 0 0 0
Sophomore 4 20 1 5 1 5 1 7
Junior 7 35 7 39 11 55 6 43
Senior 9 45 10 56 8 40 7 50
3.5–4.0 13 65 9 50 7 35 6 43
3.0–3.4 4 20 5 28 10 50 5 36
2.5–2.9 3 15 3 17 3 15 3 21
2.0–2.4 0 0 1 5 0 0 0 0
Below 2.0 0 0 0 0 0 0 0 0
Yes 9 45 5 28 7 35 3 21
No 11 55 13 72 13 65 11 79
Verbal ability 20 57 18 59 20 50 14 52
Table 5 Experiment 2 mean percentages (and standard deviations) among groups for idea units in notes
and achievement items
Groups Idea units in notes Achievement items
Original Additional Fact Relationship
M(SD) M(SD) M(SD) M(SD)
Pause/no partner (n=20) 49.3 (8.8) 4.7 (2.3) 50.5 (18.2) 55.5 (19.6)
Pause/partner (n=18) 56.7 (10.4) 7.4 (4.4) 55.6 (17.9) 51.1 (19.1)
No pause/no partner (n=20) 44.5 (9.1) 3.9 (2.9) 44.5 (15.7) 38.0 (23.5)
No pause/partner (n=14) 46.8 (9.4) 2.2 (1.6) 42.9 (18.2) 31.4 (18.3)
The sample size for idea units in notes of no pause/partner group is 12: two sets of notes were misplaced and
could not be scored
Revising lecture notes: how revision, pauses, and partners…57
pause/no partner, no pause/partner), and Table 6presents main effect level results
involving the combined groups (pause, no pause, partner, no partner). In each table, note-
taking results appear on the left side, and achievement results appear on the right side.
With respect to original notes, there was no interaction effect, F(1, 66) =1.24, p=.27,
=.002. However, there were main effects for pause, F(1, 66) =10.20, p=.002,
Table 6 Experiment 2 mean percentages (and standard deviations) among combined groups for idea units
in notes and achievement items
Groups Idea units in notes Achievement items
Original Additional Fact Relationship
M(SD) M(SD) M(SD) M(SD)
Pause (n=38) 52.8 (10.2) 6.0 (3.7) 52.9 (18.0) 53.4 (19.2)
No pause (n=34) 45.4 (9.1) 3.3 (2.6) 43.8 (16.5) 35.3 (21.5)
Partner (n=32) 52.7 (11.0) 5.3 (4.4) 50.0 (18.8) 42.5 (21.0)
No partner (n=40) 46.9 (9.2) 4.3 (2.6) 47.5 (17.1) 46.7 (23.1)
Total (n=72) 49.4 (10.3) 4.7 (3.5) 48.6 (17.8) 44.9 (22.1)
For original notes and additional notes, the sample size of no pause groups was 32, the sample size of partner
groups was 30, and the total sample size for note measures was 70
Fig. 1 Experiment 2 interaction effect of pause and partner on additional notes
58 L. Luo et al.
=.13, and for partner, F(1, 66) =4.33, p=.04, g
=.06. As shown in Table 6,
pause groups (M=52.8 %) recorded more original notes than no-pause groups
(M=45.4 %), and partner groups (M=52.7 %) recorded more original notes than no-
partner groups (M=46.9 %).
With respect to additional notes, there was an interaction for pause and partner, F(1,
66) =8.63, p=.005, g
=.12. Interaction results appear in Table 5and are depicted in
Fig. 1. The interaction can be interpreted two ways. First, we examine the simple effect of
the pause variable at each level of the partner variable: When participants revised with
partners, pause groups (M=7.4 %) added about 5 % more notes than no-pause groups
(M=2.2 %), p\.001, 95 % CI [3 %, 7.5 %]; when participants revised alone, pause
groups (M=4.7 %) and no-pause groups (M=3.9 %) added comparable amounts of
notes, p=.21, 95 % CI [-1.1 %, 2.8 %]. Second, we examine the simple effect of the
partner variable at each level of the pause variable: When there were lecture pauses,
revising with a partner (M=7.4 %) yielded 2.7 % more additional notes than revising
alone (M=4.7 %), p=.001, 95 % CI [0.7 %, 4.7 %]; when there were no lecture pauses,
revising with a partner (M=2.2 %) or alone (M=3.9 %) resulted in comparable addi-
tions to notes, p=.10, 95 % CI [-0.5 %, 3.9 %].
With respect to the qualitative analysis of additional notes, ﬁndings are presented in
Table 7. Inspection of Table 7yields the following revision observations: (a) note
extensions occurred about as often as note additions, (b) note extensions were somewhat
more common among students revising alone than with a partner, and (c) note elaborations
With respect to fact items, there was no pause-by-partner interaction effect, F(1,
68) =.65, p=.42, g
=.01. However, there was a main effect for pause, F(1,
68) =5.1, p=.03, g
=.07. As shown in Table 6, pause groups (M=52.9 %) scored
9 % higher on fact items than no-pause groups (M=43.8 %). There was no main effect
for partner, F(1, 68) =.17, p=.68, g
=.002. Although the pause-by-partner interac-
tion was not statistically signiﬁcant, there is a pattern in the Table 5data of practical
importance. It appears that the combination of pause and partners worked best for learning
facts. Notice that partners scored about 12 % higher under pause conditions (M=55.6 %)
compared to no-pause conditions (M=42.9 %). Such differences were not as evident for
those revising alone. They scored just 6 % higher when working under pause conditions
(M=50.5 %) compared to no-pause conditions (M=44.5 %).
With respect to relationship items, there was no interaction effect of pause and partner,
F(1, 68) =.05, p=.82, g
=.001. However, there was a main effect for pause, F(1,
Table 7 Frequencies for each
category of revised notes Note
Group Additions Extensions Elaborations
Pause/no partner 51 54 7
Pause/partner 76 34 11
No pause/no partner 40 66 9
No pause/partner 16 7 1
Total 183 161 28
Revising lecture notes: how revision, pauses, and partners…59
68) =14.6, p\.001, g
=.18. As shown in Table 6, pause groups (M=53.4 %) scored
18 % higher on relationship items than no-pause groups (M=35.3 %). The main effect of
partner, F(1, 68) =.13, p=.26, g
=.002, was not statistically signiﬁcant.
First, revising notes during lecture pauses uniformly aided note taking and achievement.
Revising notes on three occasions during lecture pauses, versus once following the lecture,
resulted in more original and additional notes, and in higher fact and relationship
achievement. Second, revising notes with a partner, versus alone, aided note taking but not
achievement. Revising with a partner resulted in more original notes but not in more
additional notes or in higher achievement scores. Third, the interaction pattern for addi-
tional notes revealed that revision is best carried out during pauses and with partners.
Revision during pauses with a partner produced more additional notes than revision
without pauses and partners. The combined superiority of pauses and partners for notes,
however, was not statistically signiﬁcant for fact or relationship achievement (although
partners scored 12 % higher under pause conditions than under no-pause conditions for
fact items). Finally, the qualitative examination of additional notes during the revision
period showed that revision was more than the addition of new ideas. It also involved
substantial note extensions that helped bolster or clarify previously noted ideas. In some
instances, revision also entailed elaboration, although such revision was relatively rare.
The present study investigated revision, the missing link between note taking and the
review of notes. We proposed that a note revision period after notes are recorded might
yield more complete notes to review as students use noted ideas as retrieval cues to recall
and note additional ideas absent from their original notes. We also proposed that revision
might best be carried out during lecture pauses, instead of after the lecture, and with a
partner, instead of alone, because lecture pauses might distribute learning and because
partners might share and retrieve lecture ideas not previously noted by one partner or the
other. Based on these beliefs, two primary research questions were posed and addressed.
First, is revision more effective than non-revision? Second, what revision method is best?
Is revision effective?
The ﬁrst primary research question was answered in Experiment 1 by comparing note-
taking and achievement results of those who revised notes following a lecture with those
who recopied notes. Results suggested a modest revision effect—revision is superior to no
revision. In terms of notes, revisers naturally added more notes than non-revisers during the
revision process, but just 3 % more. In terms of achievement, revisers outperformed non-
revisers on relationship items, which were an index of associative learning—the ability to
relate ideas that were presented independently. Revision might boost relationship perfor-
mance for two reasons. First, revision increased the number of additional notes; it is well
established that having more notes is associated with higher achievement (Peverly et al.
2003; Williams and Worth 2002). Second, revision perhaps had underlying cognitive
beneﬁts beyond simple note additions. The process of using original notes to retrieve
60 L. Luo et al.
additional lecture points might somehow encourage revisers to relate lecture ideas to one
another. For example, revisers reading the noted idea, ‘‘variable schedules involve rapid
responding,’’ might have related this idea to ‘‘ﬁxed schedules involve slow responding.’’ In
fact, there was modest evidence for elaborative revision in Experiment 2. This associative
linking of ideas might occur because revision is an active process requiring learners to
think about lecture ideas in meaningful ways. Meanwhile, we discount the possibility that
revision helped simply because of additional exposure to lecture notes. The comparison
group in Experiment 1 spent the same amount of time as revisers recopying their lecture
notes, but such rote exposure did not boost notes or achievement.
What revision method is best?
The second primary research question was answered in Experiment 2 by examining the
main and interaction effects of pauses and partners with respect to note taking and
The pause effect (revision pauses interspersed throughout the lecture are superior to one
equally timed revision opportunity following the lecture) was upheld. Revision pauses led
to increased original and additional notes and to higher fact and relationship achievement
than revision without pauses. Pauses might be instrumental because they divide lectures
into smaller units that make learning distributed rather than massed. Distributed learning,
in turn, aids attention, encoding, and consolidation (Cepeda et al. 2006).
Pauses might aid attention because pauses break lectures into parts so that attention is
better maintained throughout the lecture. Previous research has shown that with un-paused
lectures, attention wanes and note taking decreases in latter stages (Scerbo et al. 1992).
Pauses might also aid encoding because learners tend to relate information stemming
from multiple but similar contexts. This recent explanation for encoding advantages in
distributed learning is called reminding theory (Benjamin and Tullis 2010). In the present
study, the similarity among pause contexts (both in nature and in content) might have
reminded learners to associate and encode lecture ideas across pauses. For example, Pause
2 material about variable ratio schedules might have reminded learners about Pause 1
material about ﬁxed ratio schedules and prompted the joint encoding of the two concepts.
Again, there was modest evidence in Experiment 2 that note revisions sometimes involved
such elaboration. The encoding beneﬁt of pauses might particularly explain why pauses
had their largest effect on relationship learning, which depended on relating information
spaced throughout the lecture.
Pauses might also aid memory consolidation—the stabilization of memory traces after
initial acquisition (Wickelgren 1972). Distributed learning enhances memory consolidation
in general and relational memory in particular because repeated exposure to information
creates stronger and better organized synaptic connections among memory traces in the
brain (Dash et al. 2004; Karpicke 2012). In the present study, improved consolidation, as
the result of pauses, might have solidiﬁed memories but also given learners a progressively
better framework for assimilating lecture ideas in notes from one lecture segment to the
Revising lecture notes: how revision, pauses, and partners…61
The partner effect (revising with a partner is superior to revising alone) was upheld to some
degree. Although those revising with partners and those revising alone did not differ in
terms of fact or relationship achievement, there were note-taking differences between
groups. Those with partners recorded more original notes, but not more additional notes. In
terms of additional notes, the qualitative analysis in Experiment 2 revealed that those
revising alone were actually somewhat more likely to extend originally noted ideas than
were those revising with partners. In terms of original notes, it might seem surprising that
those with partners recorded more, but perhaps students who knew they would be partnered
were motivated to record complete notes to hold up their end of the note-revision part-
nership. Such social responsibility, or absence of social loaﬁng (Brickner et al. 1986), is
consistent with ﬁndings from social psychology (Gillies 2004) and from cooperative
learning studies (Delgado-Tellez and Raposo 2011).
We thought that revising with a partner would especially produce more additional notes
and higher achievement because revisers would not only get the beneﬁt of their own notes
acting as retrieval cues, they would also get access to their partner’s original notes and their
partner’s retrieved notes. Such was not the case. According to the ICAP model (Chi and
Wylie 2014), true interactive and constructive collaborations take place only if each
partner ‘‘generates some knowledge beyond what was presented in the original learning
materials’’ (p. 223). The qualitative examination of participants’ added notes in Experi-
ment 2, however, showed that the majority of additional notes were ideas from the lecture
(note additions and note extensions), rather than new ideas (note elaborations). This new
idea deﬁcit might explain why the partner effect was not stronger. Moreover, working with
a partner under experimental conditions might not be effective because (a) partnership
skills take time to develop (Johnson and Johnson 1999), and (b) participants lacked
motivation to engage in meaningful collaborations. Aitken and Hatt (2012) found that
when students participated in collaborative note taking, it was beneﬁcial when students had
strong motivation to collaborate.
It seems that the potential partner effect was only observed to some degree when
partners and pauses were combined. As shown in Table 5, the pause/partner group, relative
to the no pause/partner group, recorded about 10 % more original notes, 5 % more
additional notes, scored 13 % higher on fact items, and 20 % higher on relationship items.
Moreover, the pause effect for fact learning was more than twice as large for partners than
for no partners as seen in Table 5. Partners scored 5 % higher than those revising alone
under pause conditions but scored less than 2 % higher under no-pause conditions. The
combination of pauses and partners was perhaps somewhat effective because those in the
pause/partner group were doubly aided. They reaped the beneﬁts of both pauses (dis-
tributed learning) and partners (note sharing and collaborative retrieval). In summary,
present results indicate that collaboration is not always effective. In a lecture setting, it
works somewhat better for revising notes on multiple occasions throughout the lecture than
just one time following the lecture.
Conclusions, limitations, and implications
In conclusion, the present study made new inroads into the scientiﬁc study of note taking.
First, it conceptualized note taking as a three-step process of note taking, revision, and
review. Second, it examined the independent effects of revision and found that revision is
62 L. Luo et al.
superior to no revision. Third, it examined how best to revise and found that revision is best
when carried out during pauses and that the combination of pauses and partners has merit
and holds promise. Fourth, it added revision as a new student-centered means to boost
lecture note taking because students can, on their own, revise their notes before reviewing
them. Revision can also be added to other instructor-centered means (presenting full notes,
presenting skeletal notes, presenting cues, and re-presenting the lecture) for increasing note
One limitation of the study was in how prior knowledge was assessed. A single self-
report item measured participants’ prior knowledge of the lesson topic. This self-report
measure was crude because it did not directly assess prior knowledge but only participants’
estimations. Future studies could use assessments that directly measure prior knowledge,
such as a free recall test that asks participants to write down what they know about the
topic (Dochy et al. 1999).
Another limitation was the low internal consistency of the fact achievement items.
Although the low internal consistency coefﬁcient was perhaps an artifact of short test
length, it brought uncertainty to the reliability of the fact learning measure. Therefore,
results for fact learning should be interpreted with caution.
Some educational implications follow from this study. First, students should revise
lecture notes. Second, instructors should provide occasional lecture pauses for revision and
possibly advocate that students work with partners during these pauses to make notes more
complete. Third, instructors should warn students not to recopy notes because such rote
rehearsal activity does not increase notes or boost achievement.
In terms of research implications, researchers might replicate the present study under
more contemporary conditions involving computer-assisted instruction, computer note
taking, or on-line partner consultation, especially in light of recent research comparing
taking notes longhand versus taking them via computer (Bui et al. 2013; Mueller and
Oppenheimer 2014). Perhaps revision, pause, and partner variables can aid note taking and
achievement for computer-aided learning environments too. Existing programs are already
in use for partnered note taking (e.g., Microsoft Ofﬁce OneNote), but such programs are
untested for revision. Researchers might also unpack the pause effect to determine if the
distributed learning advantage of pauses is due to timeliness (revision occurs close in time
to note taking) or amount (there is less information to process at one time). This issue
might be investigated, as was done in the present study, by comparing the performance of
those who revise during pauses spaced throughout the lecture with those who revise
following the lecture, with one exception: Those revising after the lecture would also
revise lecture notes in three ﬁve-minute intervals, with each interval focused on lecture
notes corresponding to one of the three lecture segments. Researchers might also inves-
tigate whether partner familiarity or partner training aids partner interaction and improves
revision, especially for partners working together one time following a lecture. Finally,
researchers might seek ways to improve revision—perhaps through training—both in note
quantity and elaborative quality.
Aharony, N. (2006). The use of deep and surface learning strategies among students learning English as a
foreign language in an Internet environment. British Journal of Educational Psychology, 76, 851–866.
Revising lecture notes: how revision, pauses, and partners…63
Aiken, E. G., Thomas, G. S., & Shennum, W. A. (1975). Memory for a lecture: Effects of notes, lecture rate,
and informational density. Journal of Educational Psychology, 67, 439–444. doi:10.1037/h0076613.
Aitken, A., & Hatt, G. (2012). Students taking notes and creating summaries together (or not). In A.
Herrington, J. Schrape, & K. Singh (Eds.), Engaging students with learning technologies (pp.
147–165). Perth: Curtin University.
Armbruster, B. B. (2000). Taking notes from lectures. In R. F. Flippo & D. C. Caverly (Eds.), Handbook of
college reading and study strategy research (pp. 175–200). Mahwah, NJ: Lawrence Erlbaum
Austin, J. L., Lee, M., & Carr, J. P. (2004). The effects of guided notes on undergraduate students’ recording
of lecture content. Journal of Instructional Psychology, 31, 314–320. Retrieved from: http://www.
Barron, B. (2003). When smart groups fail. Journal of the Learning Sciences, 12, 307–359. doi:10.1207/
Bassili, J. N., & Joordens, S. (2008) Media player tool use, satisfaction with online lectures and examination
performance. International Journal of E-Learning & Distance Education, 22, 93–108. Retrieved from:
Benjamin, A. S., & Tullis, J. (2010). What makes distributed practice effective? Cognitive Psychology, 61,
Bonner, J. M., & Holliday, W. G. (2006). How college science students engage in note-taking strategies.
Journal of Research in Science Teaching, 43, 786–818. doi:10.1002/tea.20115.
Boyle, J. R. (2007). The process of note taking: Implications for students with mid disabilities. The Clearing
House: A Journal of Educational Strategies, Issues and Ideas, 80, 227–232. doi:10.3200/TCHS.80.5.
Brickner, M. A., Harkins, S. G., & Ostrom, T. M. (1986). Personal involvement: Thought provoking
implications for social loaﬁng. Journal of Personality and Social Psychology, 51, 763–769. doi:10.
Brown, C. M. (1999). Human-computer interface design guidelines. Exeter: Intellect Books.
Bruffee, K. A. (1999). Collaborative learning: Higher education, independence, and the authority of
knowledge (2nd ed.). Baltimore, MD: Johns Hopkins University Press.
Bui, D. C., & Myerson, J. (2014). The role of working memory abilities in lecture note-taking. Learning and
Individual Differences, 33, 12–22. doi:10.1016/j.lindif.2014.05.002.
Bui, D. C., Myerson, J., & Hale, S. (2013). Note-taking with computers: Exploring alternative strategies for
improved recall. Journal of Educational Psychology, 105, 299–309. doi:10.1037/a0030367.
Castello, M., & Monereo, C. (2005). Students’ note-taking as a knowledge-construction tool. Educational
Studies in Language and Literature, 5, 265–285. doi:10.1007/s10674-005-8557-4.
Cepeda, N. J., Pashler, H., Vul, E., Wixted, J. T., & Rohrer, D. (2006). Distributed practice in verbal recall
tasks: A review and quantitative synthesis. Psychological Bulletin, 132, 354–380. doi:10.1037/0033-
Chi, M. T. H., & Wylie, R. (2014). The ICAP framework: Linking cognitive engagement to active learning
outcomes. Educational Psychologist, 49, 219–243. doi:10.1080/00461520.2014.965823.
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Mahwah, NJ: Lawrence
Cohen, J. (1992). A power primer. Psychological Bulletin, 112, 155–159. doi:10.1037/0033-2909.112.1.155.
Crooks, S. M., White, D. R., & Barnard, L. (2007). Factors inﬂuencing the effectiveness of note taking on
computer-based graphic organizers. Journal of Educational Computing Research, 37, 369–391. doi:10.
Dash, P. K., Hebert, A. E., & Runyan, J. D. (2004). A uniﬁed theory for systems and cellular memory
consolidation. Brain Research Reviews, 45, 30–37. doi:10.1016/j.brainresrev.2004.02.001.
DeBerard, M. S., Spielmans, G. I., & Julka, D. C. (2004). Predictors of academic achievement and retention
among college freshmen: A longitudinal study. College Student Journal, 38, 66–80.
Delgado-Tellez, M., & Raposo, A. P. (2011, November). Motivating creativity and cooperation in class-
room. In Proceedings of the 4th international conference of education, research and innovation,
Madrid, Spain (pp. 1699–1703). Retrieved from http://library.iated.org/publications/ICERI2011.
Di Vesta, F. J., & Gray, S. G. (1972). Listening and note taking. Journal of Educational Psychology, 63,
Di Vesta, F. J., & Gray, S. G. (1973). Listening and note taking: II. Immediate and delayed recall as
functions of variations in thematic continuity, note taking, and length of listening-review intervals.
Journal of Educational Psychology, 64, 278–287. doi:10.1037/h0032243.
64 L. Luo et al.
Dochy, F., Segers, M., & Buehl, M. M. (1999). The relation between assessment practices and outcomes of
studies: The case of research on prior knowledge. Review of Educational Research, 69, 145–186.
Ebbinghaus, H. (1964). Memory: A contribution to experimental psychology (H. A. Ruger, C. E. Bussenius,
& E. R. Hilgard, Trans.). Mineola, NY: Dover Publications. (Original work published 1885).
Einstein, G. O., Morris, J., & Smith, S. (1985). Notetaking, individual differences, and memory for lecture
information. Journal of Educational Psychology, 77, 522–532. doi:10.1037/0022-0622.214.171.1242.
Exley, K., & Dennick, R. (2009). Giving a lecture: From presenting to teaching (2nd ed.). London:
Frisbie, D. A. (1988). Reliability of scores from teacher-made tests. Educational Measurement: Issues and
Practice, 7, 25–35. doi:10.1111/j.1745-3992.1988.tb00422.x.
Gillies, R. M. (2004). The effects of cooperative learning on junior high school students during small group
learning. Learning and Instruction, 14, 197–213. doi:10.1016/S0959-4752(03)00068-9.
Grabe, M. (2005). Voluntary use of online lecture notes: Correlates of note use and note use as an alternative
to class attendance. Computers & Education, 44, 409–421. doi:10.1016/j.compedu.2004.04.005.
Haynes, S. N., Richard, D. C. S., & Kubany, E. S. (1995). Content validity in psychological assessment: A
functional approach to concepts and methods. Psychological Assessment, 7, 238–247. doi:10.1037/
Howe, M. J. A. (1970). Using students’ notes to examine the role of the individual learner in acquiring
meaningful subject matter. Journal of Educational Research, 64, 61–63. doi:10.1080/00220671.1970.
Jairam, D., & Kiewra, K. A. (2010). Helping students soar to success on computers: An investigation of the
SOAR study method for computer-based learning. Journal of Educational Psychology, 102, 601–614.
Johnson, D. W., & Johnson, R. T. (1999). Making cooperative learning work. Theory into Practice, 38,
Kam, M., Wang, J., Iles, A., Tse, E., Chiu, J., Glaser, D. et al. (2005). Livenotes: A system for cooperative
and augmented note-taking in lectures. In Proceedings of the SIGCHI conference on Human factors in
computing systems (pp. 531–540). New York: ACM. doi:10.1145/1054972.1055046.
Karat, C. M., Halverson, C., Horn, D., & Karat, J. (1999). Patterns of entry and correction in large
vocabulary continuous speech recognition systems. In Proceedings of the SIGCHI conference on
human factors in computing systems (pp. 568–575). New York: ACM. doi:10.1145/302979.303160.
Karpicke, J. D. (2012). Retrieval-based learning: Active retrieval promotes meaningful learning. Current
Directions in Psychological Science, 21, 157–163. doi:10.1177/0963721412443552.
Karpicke, J. D., Butler, A. C., & Roediger, H. L. (2009). Metacognitive strategies in student learning: Do
students practice retrieval when they study on their own? Memory, 17, 471–479. doi:10.1080/
Katayama, A. D., & Crooks, S. M. (2003). Online notes: Differential effects of studying complete or partial
graphically organized notes. Journal of Experimental Education, 71, 293–312. doi:10.1080/
Kiewra, K. A. (1985a). Investigating notetaking and review: A depth of processing alternative. Educational
Psychologist, 20, 23–32. doi:10.1207/s15326985ep2001_4.
Kiewra, K. A. (1985b). Learning from a lecture: An investigation of notetaking, review, and attendance at a
lecture. Human Learning, 4, 73–77.
Kiewra, K. A. (1989a). A review of note-taking: The encoding-storage paradigm and beyond. Educational
Psychology Review, 1, 147–172. doi:10.1007/BF01326640.
Kiewra, K. A. (1989b). Cognitive aspects of autonomous note taking: Control processes, learning strategies,
and prior knowledge. Educational Psychologist, 23, 39–56. doi:10.1207/s15326985ep2301_3.
Kiewra, K. A., Benton, S. L., Kim, S., Risch, N., & Christensen, M. (1995). Effects of note taking format
and study technique on recall and relational performance. Contemporary Educational Psychology, 20,
Kiewra, K. A., Mayer, R. E., Christensen, M., Kim, S. I., & Risch, N. (1991). Effects of repetition on recall
and note-taking: Strategies for learning from lectures. Journal of Educational Psychology, 83,
Kintsch, W. (1988). The role of knowledge in discourse comprehension: A construction–integration model.
Psychological Review, 95, 163–182. doi:10.1037/0033-295X.95.2.163.
Kobayashi, K. (2006). Combined effects of note-taking/reviewing on learning and the enhancement through
interventions: A meta-analytic review. Educational Psychology, 26, 459–477. doi:10.1080/
Revising lecture notes: how revision, pauses, and partners…65
Konrad, M., Joseph, L. M., & Eveleigh, E. (2009). A meta-analytic review of guided notes. Education and
Treatment of Children, 32, 421–444. doi:10.1353/etc.0.0066.
Lakens, D. (2013). Calculating and reporting effect sizes to facilitate cumulative science: a practical primer
for t-tests and ANOVAs. Frontiers in Psychology, 4, 1–12. doi:10.3389/fpsyg.2013.00863.
Lambiotte, J. G., Skaggs, L. P., & Dansereau, D. F. (1993). Learning from lecture: Effects of knowledge
maps and cooperative review strategies. Applied Cognitive Psychology, 7, 483–497. doi:10.1002/acp.
Larson, R., & Farber, E. (2011). Elementary statistics: Picturing the world (5th ed.). Upper Saddle River,
NJ: Prentice Hall.
Maydosz, A., & Raver, S. A. (2010). Note taking and university students with learning difﬁculties: What
supports are needed? Journal of Diversity in Higher Education, 3, 177–186. doi:10.1037/a0020297.
Mitnik, R., Recabarren, M., Nussbaum, M., & Soto, A. (2009). Collaborative robotic instruction: A graph
teaching experience. Computers & Education, 53, 330–342. doi:10.1016/j/compedu.2009.02.010.
Mueller, P. A., & Oppenheimer, D. M. (2014). The pen is mightier than the keyboard: Advantages of
longhand over laptop note taking. Psychological Science,. doi:10.1177/0956797614524581.
O’Donnell, A., & Dansereau, D. F. (1993). Learning from lectures: Effects of cooperative review. Journal of
Experimental Education, 61, 116–125. doi:10.1080/00220973.1993.9943856.
Omoigui, N., He L., Gupta, A., Grudin, J., & Sanocki, E. (1999). Time-compression: Systems concerns,
usage, and beneﬁts. In Proceedings of the SIGCHI conference on human factors in computing systems
(pp. 136–143). New York: ACM. doi:10.1145/302979.303017.
Onwuegbuzie, A. J., & Daniel, L. G. (2002). A framework for reporting and interpreting internal consistency
reliability estimates. Measurement and Evaluation in Counseling and Development, 35, 89–103.
Retrieved from Academic Search Premier Database.
Peverly, S. T., Brobst, K. E., Graham, M., & Shaw, R. (2003). College adults are not good at self-regulation:
A study on the relationship of self-regulation, note taking, and test taking. Journal of Educational
Psychology, 95, 335–346. doi:10.1037/0022-06126.96.36.1995.
Peverly, S. T., Vekaria, P. C., Reddington, L. A., Sumowski, J. F., Johnson, K. R., & Ramsay, C. M. (2013).
The relationship of handwriting speed, working memory, language comprehension and outlines to
lecture note-taking and test-taking among college students. Applied Cognitive Psychology, 27,
Piolat, A., Olive, T., & Kellogg, R. T. (2005). Cognitive effort during note taking. Applied Cognitive
Psychology, 19, 291–312. doi:10.1002/acp.1086.
Raver, S. A., & Maydosz, A. S. (2010). Impact of the provision and timing of instructor-provided notes on
university students’ learning. Active Learning in Higher Education, 11, 189–200. doi:10.1177/
Reimer, Y. J., Brimhall, E., Cao, C., & O’Reilly, K. (2009). Empirical user studies inform the design of an
e-notetaking and information assimilation system for students in higher education. Computers &
Education, 52, 893–913. doi:10.1016/j.compedu.2008.12.013.
Roediger, H. L. (2000). Why retrieval is the key process in understanding human memory. In E. Tulving
(Ed.), Memory, consciousness, and the brain: The Tallinn conference (pp. 52–75). Philadelphia, PA:
Rosenthal, R., & Rubin, D. B. (1984). Multiple contrasts and ordered Bonferroni procedures. Journal of
Educational Psychology, 76, 1028–1034. doi:10.1037/0022-06188.8.131.528.
Scerbo, M. W., Warm, J. S., Dember, W. N., & Grasha, A. F. (1992). The role of time and cuing in a college
lecture. Contemporary Educational Psychology, 17, 312–328. doi:10.1016/0361-476X(92)90070-F.
Schoen, I. (2012). Effects of method and context of note-taking on memory: Handwriting versus typing in
lecture and textbook-reading contexts. Pitzer Senior Theses. Paper 20. Retrieved from http://
Stefanou, C., Hoffman, L., & Vielee, N. (2008). Note-taking in the college classroom as evidence of
generative learning. Learning Environment Resources, 11, 1–17. doi:10.1007/s10984-007-9033-0.
Stringfellow, J. L., & Miller, S. P. (2005). Enhancing student performance in secondary classrooms while
providing access to the general education curriculum using lecture formats. Teaching Exceptional
Children Plus, 1, 1–16.
Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics (5th ed.). Boston, MA: Pearson.
Thomson, D. M., & Tulving, E. (1970). Associative encoding and retrieval: Weak and strong cues. Journal
of Experimental Psychology, 86, 255–262. doi:10.1037/h0029997.
Thorndike, E. L. (1912). The curve of work. Psychological Review, 19, 165–194. doi:10.1037/h0073541.
Titsworth, B. S. (2004). Students’ note taking: The effects of teacher immediacy and clarity. Communication
Education, 53, 305–320. doi:10.1080/0363452032000305922.
66 L. Luo et al.
Titsworth, B. S., & Kiewra, K. A. (2004). Spoken organizational lecture cues and student notetaking as
facilitators of student learning. Contemporary Educational Psychology, 29, 447–461. doi:10.1016/j.
Vygotsky, L. S. (1962). Thought and language. Cambridge, MA: MIT Press. (Original work published in
Watts, M., & Becker, W. E. (2008). A little more than chalk and talk: Results from a third national survey of
teaching methods in undergraduate economics courses. The Journal of Economic Education, 39,
Wickelgren, W. A. (1972). Trace resistance and the decay of long-term memory. Journal of Mathematical
Psychology, 9, 418–455. doi:10.1016/0022-2496(72)90015-6.
Williams, R. L., & Eggert, A. C. (2002). Notetaking in college classes: Student patterns and instructional
strategies. Journal of General Education, 51, 173–199. doi:10.1353/jge.2003.0006.
Williams, R. L., & Worth, S. L. (2002). Thinking skills and work habits: Contributors to course perfor-
mance. Journal of General Education, 51, 200–227. doi:10.1353/jge.2003.0007.
Wong, L. (2014). Essential study skills (8th ed.). Stamford, CT: Cengage Learning.
Yetter, G., Gutkin, T., Saunders, A., Galloway, A., Sobansky, R., & Song, S. (2006). Individual practice for
complex problem solving: A cautionary tale. Journal of Experimental Education, 74, 137–159. doi:10.
Revising lecture notes: how revision, pauses, and partners…67