Differences in the note-taking skills of students with high achievement,
average achievement, and learning disabilities
Joseph R. Boyle
, Gina A. Forchelli
Temple University, United States
a b s t r a c t
a r t i c l e i n f o
Article history:
Received 26 March 2013
Received in revised form 19 April 2014
Accepted 16 June 2014
Keywords:
Learning disabilities
Note-taking
Middle-school
Science classes
Cognitive
Metacognitive
Students with learning disabilities (LD) experience problems recording notes from lectures, yet, lectures serve as
one of the major avenues of learning content in secondary classes. Despite the importance of note-taking skills for
students with LD, few if any studies have examined the differences in note-taking between students with LD and
students with high and average achievement. In this study, the note-taking skills of middle school students with
LD were compared to peers with average and high achievement. The results indicate differences in the number
and type of notes recorded between students with LD and their peers and differences in test performance of
lecture content.
© 2014 Elsevier Inc. All rights reserved.
1. Introduction
Note-taking is a critical skill for students in middle and high school,
and eventually becomes the primary means of learning content in post-
secondary settings, such as colleges and universities (
Biemer, Takahashi, & Hearn, 1989
). Approximately one-third to one-
half of the time students spend in general education or inclusive content
classes is spent on teacher-led lectures with note-taking (
Moin, Magiera, & Zigmond, 2009; Putnam, Deshler, & Schumaker, 1993
During lectures, teachers also expect students to discern important from
unimportant information, record notes in sync with the lecture, and use
notes as a method of learning content (
Haggis, 2001; Bakunas & Holley, 2001; Suritsky & Hughes, 1996
). Finally,
because teachers frequently construct tests using information found in
their lectures (
), recording notes allows students mul-
tiple exposures to lecture content through reviewing and elaboration.
Notetaking provides students an opportunity to engage in higher-
order cognitive activities. Students become actively engaged in the
lecture; they need to track the teacher's speech, select important infor-
mation in the lecture, and paraphrase this information into their own
words before recording it in notes (
Steimle, Brdiczka, & Mühlhäuser,
).
noted that this paraphrasing serves as a recon-
struction function; students encode factual information from lecture
content and integrate it into external storage (
). It is as a generative activity (
), whereby students continuously encode and update their existing
knowledge on a topic (
). In addition, according to
, among younger and less skilled students, recording
notes serves as a scaffold to assist them with processing content that
is presented in lectures. In turn, the more ef
ficient processing of lecture
information leads to subsequent gains on recall and comprehension
measures.
These tasks require students to utilize metacognitive and executive
skills, including, but are not limited to: metacognitive and strategy use,
regulation of attention, and memory mechanisms, such as working mem-
ory (
Anderson, 2002; Eslinger, 1996
). From this perspective, executive
processes are primarily responsible for directing and regulating attention
during learning tasks. Once directed, students utilize metacognitive mon-
itoring and regulation to select, monitor, and evaluate strategy use during
note-taking. Students with good metacognitive self-regulatory skills tend
to change their strategies based upon their success or failure on the task.
Studies have indicated that certain aspects of lectures better facili-
tate the use of these skills. Cued lecture points, or pieces of information
that are highlighted through organizational or emphasis verbal cues,
alert students to key lecture content. Emphasis cues have a verbal cue
to stress its importance (e.g.,
“Please write this in your notes: A plasma
engine uses only one tenth of the fuel that a chemical rocket engine
would use.
”). Organizational cues help organize chunks of related infor-
mation (e.g.,
“There are three kinds of plasma engine rockets: ion drive,
Hall thruster, and MPD thruster.
”). Conversely, non-cued lecture points
are pieces of information that did not have a prompt or cue before their
presentation.
and
Learning and Individual Differences 35 (2014) 9
⁎ Corresponding author at: Temple University, 367 Ritter Hall — POLS, 1301 Cecil B.
Moore Ave., Philadelphia, PA 19122, United States.
E-mail address:
(J.R. Boyle).
http://dx.doi.org/10.1016/j.lindif.2014.06.002
1041-6080/© 2014 Elsevier Inc. All rights reserved.
Contents lists available at
Learning and Individual Differences
j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / l i n d i f
revealed that college students who recorded more organizational cued
lecture points in their notes demonstrated superior performance on
comprehension measures. Recorded lecture points also aids later re-
trieval of information.
Einstein, Morris, and Smith (1985)
found infor-
mation recorded in notes also aided retrieval of lecture information,
with college students remembering 40% of the lecture points found in
their notes and only 7% of the lecture points that were not in their
notes. Finally, vocabulary knowledge positively in
fluences both lan-
guage and broader academic achievement (
), where it has demonstrated clear links to com-
prehension,
fluency, and achievement (
). Despite
the importance of vocabulary during science lectures (
), there is little evidence about the role that vocabulary plays in
note-taking and lecture comprehension.
Ef
ficiency of notes recorded has been suggested as an indicator of
performance good note-taking skill.
reported that ef
fi-
cient notes have the maximum number of lecture points recorded
using the minimum number of words and found that college students
recorded an average of 32.11 words and 10.88 lecture points per lecture,
resulting in an average lecture point being 3.02 words in length.
Furthermore,
reported that note-taking ef
ficiency was
moderately positively correlated with recall (i.e., .53). Conversely,
demonstrated that among college students, the note-
taking ef
ficiency was inversely related to performance (r = −.38);
students who recorded short, terse notes performed poorly on mea-
sures of lecture comprehension. Of interest in the current study is the
question of whether the length of lecture points varies among middle
school students who perform at different achievement levels.
Recording notes is a cognitively demanding task that requires stu-
dents to recognize and utilize strategies. Students without disabilities
report strategy use with varying effectiveness, where recording main
ideas is more effective than writing every word from a lecture down
(
Sutherland, Badger, & White, 2002
). In fact, when students use typical
note-taking skills, studies have shown that they generally record less
than 45% of the information from a lecture, even among high achieving
college students (
Kiewra, Benton, Kim, Risch, & Christensen, 1995;
). For example,
examined the
difference in ability between successful and less successful college stu-
dents, based on GPA derived from introductory courses to learn and re-
cord notes during a lecture. These researchers reported that successful
students recorded more notes and recalled more information than less
successful college students; however, these successful college students
only recorded between 25 and 33% of the total ideas presented in the
lecture. Notwithstanding, this study did illustrate that successful college
students differ from less successful students in terms of the organization
and structure of lecture information found in their notes. No studies
have examined differences between high achievers and other groups
of students (e.g., students with average achievement or LD) among
the middle school population in terms of notes recorded during lectures
and subsequent test performance on lecture content.
Unfortunately, students with disabilities have dif
ficulties naturally
deploying and using strategies during learning tasks (
).
found that college students with
disabilities have reported numerous problems at recording notes during
lectures; a large percentage of them report problems with note-taking
in secondary (59%) and postsecondary settings (78%). Furthermore,
found that college students with LD had self-reported
dif
ficulties in: writing fast enough to keep up with the pace of the
lecture, paying attention during the lecture, making sense out of their
notes after class (i.e., notes were not legible), and deciding what was
important to record during the lecture.
Many of these note-taking dif
ficulties often result in notes with
either partial or incomplete lecture points. Among college students,
revealed that students with disabilities
recorded fewer total lecture points (36% for students with LD versus
56% for students without LD) and fewer cued lecture points (46% for
students with LD versus 77% for students without disabilities). Likewise,
found that both general education middle school students
recorded fewer notes during lectures (i.e., 25%), with middle school stu-
dents with LD performing much worse, recording only about 13% of the
total lecture points (
). Similarly, this study also reported that
students with LD only recorded 18% of cued lecture points compared to
their peers without disabilities who recorded 42%.
Overall, note-taking has clear advantages to increase students' learn-
ing. Students who can record quality notes demonstrate increased com-
prehension of material and later recall of information. However, it
requires higher cognitive abilities, such as utilizing metacognitive and
executive skill to continually update new information. Students with
disabilities are at a clear disadvantage to utilizing these skills and dem-
onstrate poorer performance. Furthermore, there is limited research on
the note-taking performance of middle school students with LD to peers
without disabilities (
). As such, there are a number of unan-
swered questions about the nature and quality of secondary students'
notes when examined from different achievement levels.
This study, therefore, seeks to address the following questions: First,
how do middle school students with LD perform on cued lecture points
and total lecture points compared to average and high achieving stu-
dents? Second, how do these students compare on the average length
of total lecture points and cued lecture points that are recorded in
their notes? Third, how do middle school students with LD perform
on the amount of key vocabulary words found in their notes compared
to average and high achieving students? Fourth, what is the relationship
between information (e.g., vocabulary, cued lecture points, total lecture
points, and total words) recorded in notes and performance on a test
without the bene
fit of studying?
2. Method
2.1. Participants
After University level Institutional Review Board (IRB) approval, re-
cruitment of participants was drawn from several science inclusive clas-
ses in an urban middle school of approximately 900 students, located
near a large metropolitan city in the Mid-Atlantic region of the country.
The principal from the target school was contacted and agreed to allow
research to take place in his school. The primary investigator worked
with the school's science curriculum director to solicit interest among
the school's science teachers. Science teachers were then provided
with parental consent and student assent forms that were sent home
with students. After two weeks, only students who returned both
signed forms were permitted to participate in the study.
Figures in
reports a breakdown of various dimensions by
group. Ninety-three middle school students in sixth, seventh, or eighth
grade participated in this study. This sample re
flects the actual student
Table 1
Student demographics.
High ach.
Avg. ach.
LD
(N = 31)
(N = 32)
(N = 30)
Gender:
Male
12
11
17
Female
19
21
13
Ethnicity:
African
–American
21
18
17
Hispanic
–American
2
5
5
European
–American
7
9
8
Asian
–American
1
0
0
Grade:
Sixth
13
13
12
Seventh
11
12
12
Eighth
7
7
6
10
J.R. Boyle, G.A. Forchelli / Learning and Individual Differences 35 (2014) 9
–14
population which is: 61% African American, 26% European American,
10% Hispanic American, and 1% Asian American.
To determine rank (e.g., AA or HA), teachers were asked to examine
students' grades in science and then provide a ranking of HA or AA.
Students who earned an 80% or higher or were in honors science classes
(i.e., where students had to maintain at least an 80% grade average)
were given a rank of HA. Students who earned a C grade or lower
were given a rank of AA. No IQ scores were obtained for HA or AA
groups. Differentiating students by course grade was similar to the
procedure used in past note-taking research among college students
(e.g.,
). In addition, cognitive abilities have been
shown to correlate moderately to high with academic achievement
measures, such as math and science grades (
Fernandes, 2006; Furnham & Monsen, 2009
).
Students with LD were identi
fied through school and state identifi-
cation procedures that used a severe discrepancy method, whereby stu-
dents had to exhibit a severe discrepancy between achievement and
intelligence test scores. When all three groups were examined in
terms of average grades (i.e., scores), students in the HA group had an
average science course grade score of 90.44% (SD = 5.91), students in
the AA group had an average course score of 82.10% (SD = 6.00) and
students with LD had an average course score of 75.05% (SD = 11.11).
These
findings mirror results from other studies. For example,
examined the grades of secondary students with and with-
out disabilities who were in content-area courses and found that 51.3%
of students with disabilities earned D or F grades, while 44% of students
with disabilities earned C grades in their content-area classes. This rep-
resents approximately 95% of students with disabilities in their sample
who earned either C, D, or F grades.
Although the sample chosen to participate in the study was a conve-
nience sample, Pearson's chi-square analyses were conducted between
groups on demographic variables and found no signi
ficant differences
related to gender or grade level. Results indicated no statistical signi
fi-
cant differences between the three groups (i.e., high achievers, average
achievers, and LD) related to gender [
χ2(2, N = 93) = 3.49, p = .18] or
grade level [
χ2(4, N = 93) = .15, p = .99]. Due to low cell sizes, chi-
square analysis of ethnicity among the groups was not possible.
2.2. Materials
A videotaped lecture was used in this study and has been used in
several other studies (
Einstein et al., 1985; Hughes & Suritsky, 1994;
Ward-Lonergan, Lilies, & Anderson, 1998, 1999
), proving advantageous
in the ability to present the same content to multiple groups of students
while controlling for extraneous variables (e.g., pauses, feedback) that
might have occurred. The topic was drawn from a Scienti
fic American
article titled:
“New Dawn for Electric Rockets” and resulted in a
videotaped lecture that was 19 min in length and was presented at an
average rate of 109 words per minute (WPM). This WPM rate falls with-
in the range of WPM rates that have been used in past research, with 75
WPM (
Bretzing, Kulhavy, & Caterino, 1987
) and 122 WPM (
). In all, the lecture contained a total of 78 total lecture points,
with 13 cued lecture points and 65 non-cued lecture points (i.e., details
without a verbal cue). Finally, 19 key vocabulary words (e.g., asteroids,
delta-v) were identi
fied as being essential to understanding the lecture
content.
2.3. Procedures
Prior to the experimental session, students were asked to complete a
three-minute writing task to assess any writing
fluency differences be-
tween the three groups. It is similar to tasks used in other studies (
& Weishaar, 2001; Gansle, Noell, VanDerHeyden, Naquin, & Slider,
2002; Hughes & Suritsky, 1994
). Writing
fluency was chosen due to
claims that
fluent handwriting, writing speed is a key determinant of ef-
ficient note-taking (
). During this three-minute writing
task, students were asked to write their
first name continuously until
told to stop. Student's performance was assessed by counting the num-
ber of letters written per minute. An analysis of variance (ANOVA) re-
vealed no signi
ficant differences between the three groups (i.e., HA,
AA, LD).
During the 40
–45 minute experimental session, students watched
the videotaped lecture while recording notes, and then took a 10-
point quiz. In each classroom at the start of the session, students were
asked to watch and listen carefully to a 19-minute videotaped lecture
entitled Electric Plasma Rockets and Vesta and Ceres and record as
many notes as they could throughout the lecture. All students were
supplied with three sheets of lined paper and were asked to write
their name and date on each page. Immediately following the lecture,
students' notes were collected and asked to take a 10-question test.
The test was distributed to students and when they completed it, they
were asked to remain quiet until the session ended. The test was then
collected and scored.
2.4. Measures
In this study, undergraduate and graduate level students scored stu-
dents' notes across
five variables: cued lecture points (CLP), total lecture
points (TLP), total words (TW), vocabulary (VOC) and test score (TS).
Using previous studies (
Brown, 2005; Hughes & Suritsky, 1994; Risch
), a lecture point found in students' notes was de
fined
as a complete idea or block of information, such as a sentence, sentence
clause, or phrase from the lecture. TLP represented the raw overall
lecture (both cued and non-cued) points that were recorded by the
student. CLP represented the number of cued lecture points verbalized
during the lecture (e.g.,
“This is important to remember,” “There are
three types of plasma engines
”) that the student recorded; Non-cued
lecture points (NCLPs) were the score of details that were not preceded
by a cue. VOC represents the raw number of instances the student wrote
down one of the vocabulary words within the lecture.
An answer key highlighting CLP in yellow was provided to facilitate
the scoring of these types of lecture points. Along with this, the total
number of words used for all CLP was counted to determine the average
number of words of each CLP. VOC was calculated by number of 19 vo-
cabulary word instances that were found in the lecture. Students were
awarded one point per vocabulary word; no additional points were pro-
vided for repetitions. Students' notes were also counted for the total
number of words (TW). This
final count determined the average length
of each lecture point written in notes. Finally, 10-point multiple-choice
test score assesses student comprehension. The test was developed
from the content from the lecture,
“Electric Plasma Rockets and Vesta
and Ceres
” and has been used in other studies (
).
Students' TS was used to assess how performance would vary between
the groups and to see which factors (i.e., CLP, VOC, TLP and TW) were
correlated the test. Furthermore, test scores (TS) were used to assess
the mediating effects of note-taking on immediate learning without
having other variables (i.e., studying or reviewing notes) contributing
to student performance on the test. It is interesting to note that stu-
dents' TS were found to be signi
ficantly, positively correlated (r = .71,
p
b .01) with student rank (e.g., AA, HA, & LD).
2.5. Interobserver agreement
An independent rater scored all notes and the test. All of the stu-
dents' notes were also rescored by a second graduate-level student
rater in the same manner as the
first rater. Inter-rater reliability was cal-
culated to be .98 for TW, .97 for CLP, .95 for TLP, .97 for VOC, and .99 for
TS. Finally, the content of the quiz was con
firmed by the second rater
when this rater located and found the content pertaining to all of the
questions and correct answers (i.e., 100%) in the lecture notes of the
presenter from the script of the videotaped lecture.
11
J.R. Boyle, G.A. Forchelli / Learning and Individual Differences 35 (2014) 9
–14
2.6. Experimental design and data analysis
Multivariate analysis of variance (MANOVA) was used for the analy-
ses and probability values were set with
α at .05, unless otherwise
noted. Further, when a signi
ficant overall pairwise MANOVA result is
found, Tukey procedures were used to determine which individual var-
iables are contributing to each pairwise signi
ficant result. Using these
procedures, students in each group were compared to one another in
this analysis using CLP, TLP, TW, VOC, and TS, with a second MANOVA
conducted using: words per lecture point (WPLP), words per cued
lecture point (WPCLP), and vocabulary per lecture point (VPLP). Finally,
five variables (CLP, TLP, TW, VOC, and rank) were compared to the test
score (TS) to examine the correlation between the variables. Rank
(e.g., HA, AA, & LD) was also used to examine the relationship between
the test and teachers' ranking by grades using Pearson r.
3. Results
Using the variables TS, TLP, VOC, CLP, and TW in the analysis yielded
statistical signi
ficance with Wilks' Λ = .37, F(10, 172) = 11.00, p b .001,
η
p
2
= .39. Subsequent pairwise univariate tests indicated that there were
signi
ficant effects between the three groups on all of the variables: TS,
F(2, 90) = 53.23, p
b .001, η
p
2
= .54; TLP, F(2, 90) = 23.17, p
b .001,
η
p
2
= .34; VOC, F(2, 90) = 21.34, p
b .001, η
p
2
= .32; CLP, F(2, 90) =
25.66, p
b .001, η
p
2
= .36; and TW, F(2, 90) = 21.53, p
b .001, η
p
2
=
.32. See
for mean scores per group. Tukey HSD tests indicated
signi
ficant differences (p b .05) between all of the groups on the TS,
with students with HA performing better on the test than students
with AA and LD. Likewise, students with AA outperformed students
with LD on TS. Tukey HSD tests also found signi
ficant differences
(p
b .05) between all of the groups on the TLP, with students with HA
recording more TLP in notes than students with AA and students with
LD. Similarly, students with AA outperformed students with LD on
TLP. Tukey HSD tests also indicated signi
ficant differences (p b .05) be-
tween all of the groups on the VOC, with students with HA recording
more vocabulary in notes than students with AA and students with
LD. In a similar vein, students with AA outperformed students with LD
on VOC. Tukey HSD tests also indicated signi
ficant differences (p b .05)
between all of the groups on the TW, with students with HA recording
more words in notes than students with AA and students with LD.
Also, students with AA outperformed students with LD on the number
of words recorded in notes. Finally, Tukey HSD tests also indicated signif-
icant differences (p
b .05) between students with HA recording more CLP
in notes than students with AA and students with LD; however, there
was no signi
ficant difference between students with AA and student
with LD on the number of CLP recorded in notes.
Using the variables words per lecture points (WPLP), words per cued
lecture point (WPCLP), and vocabulary per lecture point (VPLP) in
the analysis, yielded signi
ficant differences Λ = .86, F(6, 176) = 2.37,
p
b .05, η
p
2
= .08. However, pairwise univariate tests revealed no signif-
icant differences on the three variables between the different groups of
students.
Correlations were computed to examine the relationships between
students' notes and test scores. All of the variables were signi
ficant at
the .01 level. As shown in
, all four variables had a positive mod-
erate correlation with students' test scores, with vocabulary exhibiting
the strongest correlation.
4. Discussion
The current study extends note-taking research among both general
education and special education populations in several important ways.
First, it demonstrated that middle school students demonstrate signi
fi-
cant differences between the number of TLP recorded and CLP recorded
according to achievement level; that is, high achieving middle school
students recorded more important lecture points than other middle
school students. This
finding extends
study of dif-
fering achievement level among college students relation to lecture
points to the middle school population.
Second, this study con
firms results from the
study that
found signi
ficant differences between students with and without LD. In-
terestingly, there were signi
ficant differences between the CLP of stu-
dents with HA and the other two groups (students with AA and LD)
but no signi
ficant differences between students with AA and LD. In
terms of the percentage of CLP recorded in notes, students with HA re-
corded an average of 52% of the total CLP, and students with AA record-
ed an average of 27% of CLP in notes, and students with LD recorded only
15% of CLP in notes. From a statistical point of view, this data indicates
that both groups (i.e., students with AA and LD) had a dif
ficult time dis-
cerning important from less important lecture content or recording the
important information in their notes. This is supported by past research
indicating that selecting important from less important lecture content
is a problematic area for college students with LD (
).
Third, the current study extends previous note-taking research by
being the
first to examine the role of vocabulary in note-taking. While
research demonstrates vocabulary's importance in other areas (e.g.,
Pearson, Hiebert, & Kamil, 2007
), no research studies have examined
the impact of vocabulary in students' lecture notes. In this study, stu-
dents with HA recorded on average 71% of the 19 key vocabulary
words from the lecture, while students with AA recorded an average
46% and students with LD recorded an average 28% of key vocabulary
in notes. Furthermore, the results show that vocabulary had the highest
correlation (e.g., .62) with test scores.
Fourth, the results of the current study provides support for the
note-taking dif
ficulties experienced by students with LD. Students
with LD recorded fewer words and TLPs than HA students. The lack of
signi
ficant difference between groups on the three-minute writing
task suggests that note-taking ef
ficiency is less closely related to writing
fluency, alone, and may be more related to higher cognitive skills, such
as listening and cognitive processing skills. These
findings support
hypothesis that students with LD reported having dif-
ficulty writing fast enough when recording notes during lectures because
when combined with higher cognitive processing of information, low
level writing
fluency task transforms into a higher cognitive load task.
Table 2
Number of lecture points (cued and total), vocabulary, and total words in notes.
High ach.
Avg. ach.
LD
Groups
(N = 31)
(N = 32)
(N = 30)
Measure
M
SD
M
SD
M
SD
Test score
75.48
(15.02)
45.94
(11.60)
36.33
(19.21)
Cued lecture points
6.77
(3.14)
3.53
1
(2.68)
1.97
(2.11)
Total lecture points
21.52
(9.80)
13.03
(7.67)
7.93
(5.54)
Vocabulary
13.48
(6.31)
8.75
(4.66)
5.27
(3.34)
Total words
130.48
(54.48)
85.75
(60.40)
44.97
(32.82)
a
Signi
ficant at .05 level.
b
No signi
ficant difference between groups.
Table 3
Correlation between lecture points, vocabulary, total words, and
test score.
Test
Dependent variables
Pearson's r
CLP & TS
.56
TLP & TS
.52
VOC & TS
.62
TW & TS
.50
a
Signi
ficant at .05 level.
12
J.R. Boyle, G.A. Forchelli / Learning and Individual Differences 35 (2014) 9
–14
Fifth, among the three groups, this study found no signi
ficant differ-
ences in the average number of words per lecture point, the average
number of words per cued lecture point, or the average number of
vocabulary words per lecture point. At
first, this finding was surprising
because it was anticipated that there would be differences between
groups in terms of the number of words recorded per lecture point.
However, upon further examination, the average number of words per
lecture point may not be a reliable measure because even though
some students record few lecture points (e.g., 6 TLP) and few words
(e.g., 30 TW), other students may record more lecture points (e.g., 20
TLP) and more words (e.g., 100 TW), yielding the same result (e.g., 5
words per lecture point). In this study, the results of students in differ-
ent groups were similar. This may suggest that other processes, such
as semantic clustering of information, in
fluence note-taking efficiency
during learning of verbal information (
).
That is, the number of words recorded is not as important as the seman-
tic relationships between those words.
In summary, there are considerable differences between the notes of
students with different ability levels. While the present study found no
differences between the average number of words per lecture point,
there were distinct differences in the total number of lecture points,
cued lecture points, and vocabulary recorded by students. These differ-
ences support the notion that the more notes that students can record,
particularly cued lecture points and vocabulary words, the better they
should perform on comprehension measures of the lecture. Moreover,
the present study supplements prior studies on the note-taking of
students with disabilities and provides support for the fact that note-
taking is a challenging cognitive task for students with LD, as evidenced
by differences in notes produced.
4.1. Educational implications
This study suggests that note-taking ef
ficiency is more accessible to
higher achieving students than average students or students with
disabilities. This may indicate a need to explicitly teach these latter
two groups of students note-taking strategy or provide students with
compensatory supports to scaffold this activity. Past studies have dem-
onstrated that explicit teaching of note-taking skills has improved the
quality and quantity of notes (
). Therefore, teachers
should consider embedding note-taking skills within the curriculum
(
Evans, Pelham, & Grudberg, 1995
). For example, when teachers pres-
ent cued lecture points, they should also tell students to highlight or
star that content, and since it is deemed important by the teacher,
they should also explain why that particular lecture content is impor-
tant. In this way, students can begin to learn that certain lecture points
are more important than others and can begin to understand why cer-
tain lecture content is essential to record in notes and learn. Moreover,
teachers themselves should have a set of model notes that students
could compare to their own notes in order to see the differences
between expert notes versus their own notes. In this way, students
can begin to learn what good notes look like.
For students with that have more dif
ficulty engaging in higher cog-
nitive tasks (i.e., students with LD), concrete tools should be provided
to students to facilitate note-taking. In one study by
, a note-taking mnemonic (CUES+) and note-taking paper were
provided to students with disabilities. In addition, students with
motor or writing dif
ficulties may still benefit from remaining active dur-
ing note-taking activity with the support of a scribe to record class notes
or a set of teacher's notes.
4.2. Limitations of the research and future directions
There were several limitations to this study. First, this study exam-
ined students from one urban school. The results may have been differ-
ent had the sample been derived from several schools or a different
school. Second, the sampling method used in this study represents a
convenience sample (
) and caution should be exercised
when generalizing the sample to larger populations. Third, the lack of
a clear de
finition or breakdown of the LD group (e.g., reading disability,
math disability) does not allow a consideration for heterogeneity of pre-
sentation of LD. Further, it is hard to ascertain if poor note-taking in this
sample is due to a students' learning disability or other possible emo-
tional factors, such as motivation. Since both the LD and AA groups
both improved after the implementation of the intervention, it may be
an overall lack of motivation and not a processing dif
ficulty. This should
be investigated in future studies. Fourth, another limitation was the use
of only one lecture. It is possible that a different lecture would have led
to different results. Fifth, the use of a videotaped lecture itself may have
been a limitation. Although videotaped and audiotaped lectures have
been used in past research (
Hughes & Suritsky, 1994; Titsworth &
), it is possible that live lectures may have led to different
results due to it being more interactive for students.
Future research should examine the relationship between immediate
and delayed effects of note-taking, similar to work by
Additionally, future studies should seek to discern listening skills from
note-taking skills. First, since most students are assessed a few days or
weeks after notes were taken in a typical classroom, a more realistic as-
sessment of the effects of note-taking would be to assess students using
a delayed test. It would be interesting to examine the effects on note-
taking among students with and without disabilities to see how the
delay affects these different groups of students. This measure might also
be used to assess the broader effects of the process of note-taking/studying,
since students often record notes to not only learn during lectures, but
also use the same notes to prepare to tests and quizzes. Second, re-
searchers should examine the effects of note-taking over multiple lec-
tures, again to assess the effects of notes in more realistic situations and
to examine the cumulative effect of notes over time. Another area that
should be examined is the effects of student note-taking with different
content-area lectures, particularly in content areas that are often
overlooked in note-taking research, such as math. Future research should
examine the effects of listening skills compared to note-taking skills of
students with and without disabilities to better understand the role
that these skills play in student learning during note-taking. Furthermore,
the impact of technology on note-taking skills should be investigated.
In conclusion, as students move from elementary grades to second-
ary grades, classroom lectures with note-taking become more common
and teachers rely upon students to have good note-taking skills to learn
content (
). Furthermore, these skills become neces-
sary as students transition to post-secondary settings, such as colleges
and universities. Because of the importance of developing these skills
in students, particularly for students with disabilities, content area
teachers should examine students' notes for missing components and
then teach note-taking skills through their lectures, helping students
to understand the purpose and usefulness of note-taking skills for learn-
ing content.
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