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Running head: COGNITIVE TRAINING 1
ORIGINAL PAPER
Meditation in the Higher Education Classroom: Meditation Training Improves
Student Knowledge Retention during Lectures
Jared T. Ramsburg • Robert J. Youmans
___________________________
J. Ramsburg
Department of Psychology (M/C 285), University of Illinois at Chicago, 1009 Behavioral
Science Building, 1007 West Harrison St., Chicago Illinois, 60607-7137
e-mail: jramsb2@uic.edu
R. Youmans
Department of Psychology, George Mason University, Fairfax, VA
Running head: COGNITIVE TRAINING 2
Abstract
The cognitive skills required for successful knowledge retention may be influenced by
meditation training. The current studies examined the effects of meditation on the
knowledge retention of students. In three experimental studies, participants from three
introductory psychology courses randomly received either brief meditation training or rest,
listened to a class lecture, then took a post-lecture quiz that assessed students’ knowledge
of the lecture material. The results indicated that meditation improved students’ retention
of the information conveyed during the lecture in each of the three experiments. Mood,
relaxation, and class interest were not affected by the meditation training. Limitations and
implications are discussed.
Keywords: learning; meditation; cognitive functioning; higher education; academic
performance
Running head: COGNITIVE TRAINING 3
Introduction
Mindfulness, the ability to maintain one’s attention in the present moment, has long been
theoretically associated with success in higher education. William James (1890) famously wrote
that “the faculty of voluntarily bringing back a wandering attention, over and over again, is the
very root of judgment, character, and will…An education which should improve this faculty
would be the education par excellence (James, 1890, p. 424).” However, when it came to giving
advice about how to achieve mindful control over one’s attention, even the father of psychology
had to admit that it was “easier to define this idea than to give practical directions for bringing it
about.”
One hundred and twenty years later, researchers are now making progress towards
providing the kind of “practical directions” that James was seeking through meditation, a group
of emotional and attentional regulatory strategies leading to the cultivation of well-being and
emotional balance (Lutz et al., 2009). Generally speaking, meditation practices may be divided
into two categories. The first category, open monitoring meditation, involves non-reactive
monitoring of the moment-to-moment content of experience (Lutz, Slagter, Dunne, & Davidson,
2008). Open monitoring meditation is thought to facilitate nonreactive meta-cognitive
monitoring, and an awareness of automatic cognitive and emotional interpretations of sensory
perceptive stimuli. The second category is focused attention meditation, which entails sustaining
attention on a chosen thought or object. Focused attention meditation is thought to facilitate
directing and sustaining attention on a selected object, detecting mind wandering, and reinstating
directed attention (Lutz, Slagter, Dunne, & Davidson, 2008; Travis & Shear, 2010).
A plethora of recent empirical data now suggests that meditation may enhance a variety
of attention-dependent mental tasks. Researchers have demonstrated that focused and open-
Running head: COGNITIVE TRAINING 4
monitoring meditation increases performance on the Stroop task (Chan & Woollacott, 2007),
reduces the variability in attentional processing during dichotic listening tasks (Lutz et al., 2009),
improves performance on the attentional blink task (van Leeuwen, Müller, & Melloni, 2009),
and enhances performance on measures of the efficiency of attentional networks such as Fan et
al.’s (2002) Attention Network Test (Tang et al., 2007). Extensive focused and open monitoring
meditation is also associated with physical alterations to brain areas associated with the
regulation of movements and learning. For example, research has shown that meditation may
lead to increased cortical thickness (Lazar, Kerr, Wasserman, Gray, Greve, et al., 2005), and
greater regional gray matter in the putamen cluster, a structure linked directly to Attention
Deficit Hyperactivity Disorder (Pagnoni & Cekic, 2007; Konrad, Neufang, Hanisch, Fink, &
Herpertz-Dahlmann, 2006). Researchers believe that these, and perhaps other, physical changes
in meditators’ brains facilitate long-term improvements in their self-regulation of sensory,
cognitive, and emotional processing (Pagnoni & Cekic, 2007).
In addition to meditation’s positive effects on our attentional systems and resources,
recent research has also documented other types of cognitive benefits associated with meditation.
Kozhevnikov, Louchakova, Josipovic, and Motes (2009) have demonstrated that a form of
focused attention Buddhist meditation called Deity Yoga improves visuospatial memory, and Ly
and Spezio (2009) have found that open monitoring meditation improves decision-making.
Moore and Malinowski (2009) found that open monitoring meditation enhances cognitive
flexibility via performance on the Stroop task and the d2-concentration endurance test, a timed
test of selective attention. Moore and Malinowski also demonstrated that self-reported levels of
mindfulness were positively related to enhanced cognitive flexibility. Finally, researchers have
demonstrated that meditation training may improve the central-executive functions Baddley
Running head: COGNITIVE TRAINING 5
(2003) argues are necessary for students to solve problems creatively, including the vigilance
necessary to attend to a long lecture (Kramarsko & Mevarech, 2003; Smit, Eling, & Coenen,
2004), and the judgment that students require to make important academic decisions (Butler &
Wine, 1995).
Until recently, most empirical studies on meditation relied on research designs that
examined how meditation altered cognition over longer periods of time, that is, over the course
of several weeks, months, or even years. Research of this type has demonstrated that meditation
is a viable method for improving mood, levels of relaxation, cognition functioning, and self-
regulation over the long-term (Basak, Boot, Voss, & Kramer, 2008; Grossman, Niemann,
Schmidt, & Walach, 2004; Pagnoni & Cekic, 2007). For example, Zylowska et al. (2007) have
utilized meditation routines to treat children who had been diagnosed with Attention Deficit
Hyperactivity Disorder, and Innes, Selfe, Brown, Rose, & Thompson-Heisterman (2012) have
employed meditation routines to treat those suffering from Alzheimer’s disease. While these
studies have demonstrated practical long-term benefits for meditation, a smaller number of
studies have also demonstrated potential cognitive benefits of meditation in the shorter term,
either immediately following a meditation session, or after only a small number of meditation
sessions. For example, Srinivasan and Baijal (2007) demonstrated that focused attention
mediators detect changes in the environment better following meditation, and Ramsburg and
Youmans (2012) demonstrated that focused attention meditation may positively influence
participants’ decision-making and motivation while completing a complex problem-solving task.
Given that meditation benefits a wide variety of cognitive processes in both the short and
long term, educators worldwide have begun to utilize meditation as a learning tool for students
across a wide variety of age and education levels (Kirk, Downar, & Read Montague, 2011; So &
Running head: COGNITIVE TRAINING 6
Orme-Johnson, 2001; Zeidan, Johnson, Diamond, David, & Goolkasian, 2010). Fiebert and
Mead (1981) examined whether focused meditation before studying and examinations would
promote better knowledge retention compared to students meditating at different times. Baseline
measures taken over the course of three weeks revealed no differences between groups, but
meditation before examinations and study sessions resulted in better scores on examinations
during the nine-week experimental period compared to participants that meditated at other times.
Manger, Eikenland, and Asbjornsen (2002) designed a 9-month social-cognitive training
program that included meditation-like training tasks that was able to improve the social-cognitive
functioning of female schoolchildren. Beauchemin, Hutchins, and Patterson (2008) provided
students suffering from learning disabilities with a five-week meditation course that included
both focused attention and open monitoring styles of meditation. The program reduced student
anxiety, increased social functioning, and improved academic achievement.
Unfortunately, because of the variability in the methods utilized among published studies
on the academic benefits of meditation, many questions remain about what length, scope, and
duration of meditation training is optimal to achieve positive academic results. For example,
while research suggests that meditation may affect processes likely associated with knowledge
retention and learning (Butler & Wine, 1995; Zimmerman, 1990, 2000; Zimmerman & Schunk,
2001), variations in types of meditation that are employed by researchers can make it difficult to
know which forms of meditation are optimal, or for how long a form of meditation would need
to be practiced before students might expect to see benefits. Some researchers have also pointed
out that relatively few studies have investigated the role that meditation might play in academic
achievement using externally valid, experimental procedures necessary to establish causation
between meditation and improved student learning (Meiklejohn, et al., 2012; Napora, 2011,
Running head: COGNITIVE TRAINING 7
Shapiro, Brown, & Astin, 2011). In short, variations in how meditation has been studied and
administered by researchers raises reasonable questions in the minds of skeptical educators
regarding whether meditation would translate well into an educational setting.
Shapiro, Brown, and Astin (2011) echo these concerns in their comprehensive review of
meditation in the context of higher education. Shapiro et al. call for rigorous empirical studies
necessary to demonstrate how and to what degree meditation may enhance higher education. The
present series of experiments were designed to test a series of hypotheses regarding the potential
benefits of meditation training in higher-education classrooms. Experiment 1 tested the
hypothesis that brief meditation training before a lecture would improve students’ learning as
measured by a short quiz following that lecture. Experiment 2 tested whether hypothetical
improvements in student learning might occur due to increased student interest in lectures versus
some other cognitive mechanism. Experiment 3 tested whether hypothetical improvements in
student learning as a result of meditation would replicate on a different lecture topic that was
presented in a different presentation format. Finally, because all three experiments utilized a
novel method of administering meditation experimentally, the three experiments together
represented a chance to test whether meditation could be experimentally administered before a
higher education classroom lecture without disrupting the learning environment.
Experiment 1
In Experiment 1, we administered a form of brief meditation training before an actual
higher education classroom lecture to test whether the meditation would improve students’
performance on a short quiz about that lecture. Based upon prior research demonstrating that
meditation may improve those cognitive functions necessary for learning (see Butler & Wine,
1995; Tang, et al., 2007), we hypothesized that the students who meditated would learn more
Running head: COGNITIVE TRAINING 8
from the lecture than students who had not meditated. Because enhancements in mood and levels
of relaxation have been reported following meditation training (see Arias, Steinberg, Banga, &
Trestman, 2006), we also measured students’ self-reports of mood and level of relaxation.
Method
Participants
Participants in this study were 35 undergraduate psychology students who were enrolled
in an Introduction to Psychology course at a California state university. Access to the student
population was gained by consent from the course instructor. Of the 35 participants, 27 were
males, 8 were females, and the mean age was 18.09. Participants identified themselves as
Caucasian (26.10%), Asian or Pacific Islander (4.30%), more than one race/other (2.20%),
Black/African-American (4.30%), Middle Eastern (6.50%), Latino/Hispanic (32.60%), declined
to state (23.90%). Thirty-three students were freshman, one was a sophomore, and one was a
senior.
Meditation Style
Although there are many different types of meditation (e.g., Vipassana, Zen,
Transcendental, Yogic, Mantra, Jain, and many others), participants in this experiment were
given the first type of meditation taught to novices within the Zen Buddhist meditation tradition
for over eight centuries, the counting method. In this method, the practitioner sits with a straight
back and counts his or her own breaths, usually from ‘one’ to ‘ten’ and back to ‘one,’
repetitively. If at any time the practitioner loses count, he or she is instructed to return to ‘one’
and continue the breath-counting cycle. The main purpose of this form of meditation training is
to improve the practitioner’s joriki, which is a special type of concentration thought to develop as
people practice meditation (Kapleau, 1980). The counting supports the focus on meditators’
Running head: COGNITIVE TRAINING 9
breath, which helps to diminish wandering thoughts. The counting method and other focused
attention forms of meditation have been used extensively in past research in conjunction with
open monitoring meditation (for a review see Lutz et al., 2008; see also Ramsburg & Youmans,
2012; Tang et al., 2007). The present study offered the opportunity to study exclusively whether
focused attention meditation may produce measurable gains in knowledge retention. The
counting method of meditation was chosen by one of the researchers who at the time of the study
had a meditation experience of more than 10 years, which included teaching meditation to
novices at various meditation centers.
Materials and Measurement
Demographic data. A brief demographic questionnaire was used to assess age, sex, year
in college, and major field of study.
Brief mood introspection scale (BMIS). The BMIS was used to examine mood effects
(Mayer & Gaschke, 1988). The BMIS is a scale where participants rate how they feel on a 4-
point Likert scale from ‘definitely do not feel’ to ‘definitely feel’ for 14 mood adjectives. The
scale is empirically grounded and well anchored allowing for internal and external validity (see
Mayer & Gaschke, 1988).
Positive affect negative affect scale (PANAS). The PANAS was used to examine mood
effects (Watson, Clark, & Tellegen, 1988). The PANAS is a scale consisting of words that
describe different feelings and emotions. Participants indicate to what extent they are
experiencing the adjectives on a 5-point Likert scale from ‘Not at All’ to ‘Extremely’ for 20
mood adjectives. The scale is empirically grounded and well anchored allowing offering internal
and external validity (see Watson, Clark, & Tellegen, 1988).
Behavioral relaxation scale (BRS). This scale was to assess the participants’ current
Running head: COGNITIVE TRAINING 10
level of relaxation (Poppen, 1988). Participants needed to choose from one of the following 7
options: 1) I feel more deeply and completely relaxed than I ever have. 2) I feel completely
relaxed throughout my entire body. 3) I feel more relaxed than usual. 4) I feel relaxed as in my
normal resting state. 5) I feel some tension in some parts of my body. 6) I feel generally tense
throughout my body. 7) I feel extremely tense and upset throughout my body. The scale is
empirically grounded and well anchored allowing internal and external validity (see Norton,
Holm, & McSherry, 1997).
Quiz. A quiz was designed to test knowledge retained from the lecture. The quiz
contained seven total questions, three multiple-choice questions, and four fill-in-the-blank
questions. The quiz was developed with the instructor based on the content from the lecture that
was to be given that same day. Students were made aware at the beginning of the lecture that a
quiz would be administered at the conclusion of the lecture. An example of one of the multiple-
choice quiz questions is: “Which of the following will most likely lead to stress? A. exercise, B.
apathy, C. negative emotion, D. reciprocity.” An example of one of the fill-in-the-blank quiz
questions is: “Being able to adapt to stressful situations is called ____________?”
Design and Procedure
Experiment 1 utilized a between-participants experimental design. Participants were
greeted at the start of an otherwise normal Introduction to Psychology course and asked to
participate in a short activity that would be related to that day’s lecture on health and
psychology. Participants received informed consent forms, and were then randomly provided
with one of two versions of a paper packet with writing on it that had been folded over and
stapled. The randomization process consisted of randomizing the information packets and then
handing them out to students. From the students’ perspective, both versions of the packets were
Running head: COGNITIVE TRAINING 11
identical. The BMIS mood questionnaire was printed on front of the packet, and participants
began the experiment by answering those brief questions about their mood.
Next, participants were instructed to flip the packet over and follow the directions printed
on the back of the packet. One version of the packet, the meditation version, contained directions
for what was described as a self-test of focused relaxation, with simple instructions for
attempting the counting method of meditation training. The students were asked to close their
eyes, remain silent, and attend to their breathing. The second, non-meditative version of the
packet contained directions for resting, where participants were asked to close their eyes and rest
for six minutes. Rest is commonly used as a comparison activity in meditation studies (e.g., Cahn
& Polich, 2006; Kozhevnokov et al., 2009). However, there are cognitive benefits associated
with resting. Therefore, while our hypothesis was that the meditation condition would
outperform the rest condition, it may be more appropriate to consider the rest condition as a
comparison group. Because participants were all quietly seated next to one another with their
eyes closed, there was no reason for the students to suspect that they were not all performing the
same mental task (i.e., either meditating or resting), which was important for isolating the effects
of the cognitive training from other nuisance variables. From the students’ perspective, they were
all participating in the same class exercise, but in reality half of the class was meditating and half
were not.
After six minutes had passed, the experimenter asked the participants to stop, open their
stapled packets, and fill out the enclosed questionnaire containing additional mood (BMIS) and
relaxation questions (the behavioral relaxation scale; BRS; Poppen, 1988). The experimenter
collected the forms, thanked the participants, and left the class. The entire procedure took
approximately 15 minutes. The students then proceeded with the normal 50-minute lecture on the
Running head: COGNITIVE TRAINING 12
topic of health and psychology from their regular instructor. The instructor announced to the
students that a quiz would be administered at the end of class on the material being presented,
and as indicated, students took that quiz at the conclusion of the lecture. After students turned in
their quizzes, they completed a short demographics questionnaire, and finally the students were
debriefed.
Results and Discussion
Random distribution of the paper instruction packets yielded 18 students who meditated,
and 17 that rested. Our analysis of Experiment 1 focused on participants’ self-report ratings and
quiz performance. Specifically, we examined which condition led to better quiz performance and
whether mood and behavioral relaxation were affected by the meditation. Prior to the meditation
or rest manipulation, mood surveys detected no differences in the student’s moods with respect
to positive or negative affect via an analysis of variance (ANOVA), F(2, 31) = .50, p = .613, nor
did moods differ following the training, F(2, 32) = .48, p = .621 (see Table 1). While some
studies have shown that mood is affected by meditation in the long term, we had not expected
strong changes in mood as a result of meditation given the brevity of the meditation utilized here.
However, those students who had been randomly assigned to the meditation condition reported
higher levels of behavioral relaxation following the meditation training, t(33) = 2.84, p = .008.
Finally, our results indicated that students who were randomly assigned to the meditation
condition performed better on the post-lecture quiz than students in the rest condition using a
two-tailed t-test, t(33) = 1.84, p = .043; d = .64. Correct answers on the quiz ranged from three to
seven, and the effect size for quiz performance was found to be a medium effect according to
Cohen’s (1988) convention for a medium effect (see Table 1 for Ms and SDs). Due to the
relatively small sample size, more complex analyses were not conducted as they might have
Running head: COGNITIVE TRAINING 13
resulted in type 2 error. Nonetheless, in the interest of fully describing the data, we have included
an analysis of covariance (ANCOVA), which found that behavioral relaxation did not influence
scores on the quiz, F(1, 32) = .13, p = .717.
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Insert Table 1 about here
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Experiment 1 demonstrated the feasibility of utilizing the counting method of meditation
training in an ordinary higher-education classroom. One qualitative measure of the success was
that the instructor who had allowed us to conduct the study in her classroom reported that she
thought that the meditation had created a better learning environment, and volunteered that she
would be happy to use her class again if we conducted any future studies of meditation. Data
analysis subsequently revealed that students who had meditated performed better on a post-
lecture quiz, suggesting that meditation training may be an effective method for improving
academic performance.
However, after only one experiment, very little could be said about why meditators’ quiz
scores had improved. Following Experiment 1, we concluded that something about the
meditation had improved quiz performance, but what was the mechanism underlying the
improvement? Because the improvements in meditators’ quiz scores did not appear to be
mediated by mood or relaxation effects, we wondered at the conclusion of Experiment 1 whether
the improved quiz scores might have arisen from increased interest on the part of the students
who had completed the meditation on the topic of that day’s lecture, which was about health and
psychology. The meditation could have increased students’ interest in the lecture topic itself,
which might explain their improved quiz performance.
Running head: COGNITIVE TRAINING 14
Experiment 2
Experiment 2 was designed to test the hypothesis that meditators’ quiz scores had
improved in Experiment 1 as a result of their increased interest in the lecture topic. We also
conducted Experiment 2 in order to replicate the techniques and primary findings of Experiment
1 to protect against a possible Type 1 error (i.e., that we had found improved quiz scores in the
meditation condition due to coincidence). Therefore, Experiment 2 was identical to Experiment
1 in design, except that we asked the participants at the end of the class lecture to rate how
interesting they thought the class lecture had been that day. We hypothesized that a replicated
increase in quiz performance that was accompanied by an increase in students’ levels of interest
would provide evidence that student interest in the lecture topic was the mechanism responsible
for their improved quiz performance.
Method
Participants
Participants in this study were 55 undergraduate psychology students and one graduate
student enrolled in an Introduction to Psychology course at a California state university.
Experiment 2 took place in the academic semester following Experiment 1, and access to the
student population was gained by consent from the same course instructor who had volunteered
to participate in Experiment 1 previously. None of the students in Experiment 2 had participated
in Experiment 1. Of the 56 participants, 23 were males, 32 were females, and the mean age was
18.52 (one participant did not fill out the demographics form). Participants identified themselves
as Caucasian (22.80%), Asian or Pacific Islander (8.80%), Asian Indian (1.80%), Black/African-
American (24.60%), Middle Eastern (3.50%), and Latino/Hispanic (35.10%), Native American
(1.80%), and declined to state (1.80%). Forty-five students were freshmen, eight were
Running head: COGNITIVE TRAINING 15
sophomores, two were juniors, and one was a graduate student.
Design and Procedure
The same procedure as in Experiment 1 was used in Experiment 2. Students listened to
the same class lecture on Health and Psychology as the students had in the previous semester
during Experiment 1, and the same instructor gave the lecture. The quiz that was administered
following the lecture was also the same as the quiz that was used in Experiment 1, with the
addition of one question at the end asking ‘how interesting was the class lecture for the day’ on a
five-point Likert scale (1 = Not at all interesting, 5 = Very interesting).
Results and Discussion
Random distribution of the paper instruction packets yielded 30 students who meditated,
and 26 that rested. Our analysis of Experiment 2 indicated that those in the meditation condition
did not significantly differ in pre-meditation mood, F(2, 52) = 1.10, p = .339, and there were no
differences between conditions on post-meditation mood, t(53) = 1.26, p = .214. Additionally, no
statistical differences were found for behavioral relaxation, t(55) = 0.04, p = .901. Importantly,
we detected no difference between either conditions’ interest in the class lecture, t(53) = .32, p
= .749. Admittedly, as with any self-reported measure, there is a possibility of biases from
students when asked to rate the class.
However, just as we had found in Experiment 1, students who had been randomly
assigned to the meditation condition performed better on the quiz following the lecture than
those students randomly assigned to the rest condition as indicated using a directional t-test, t(54)
= 2.12, p = .038; d = .58. Correct answers on the quiz ranged from two to seven. The effect size
for quiz performance was found to be a medium effect, replicating the main finding from
Experiment 1 (see Table 2 for Ms and SDs). Additionally, an ANCOVA revealed that post mood,
Running head: COGNITIVE TRAINING 16
F(1, 48) = 1.01, p = .320, relaxation, F(1, 48) = .01, p = .755, and class interest, F(1, 48) = .48, p
= .490, did not influence quiz performance, which was improved with meditation training, F(1,
48) = 4.81, p = .033. The results of Experiment 2 indicated that meditating prior to a classroom
lecture improved students’ quiz performance, regardless of their level of interest for the class
lecture, and irrespective of their mood and relaxation level.
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Insert Table 2 about here
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Experiment 3
At the conclusion of Experiment 2, we were much more confident that meditation had
improved students’ knowledge retention of the lecture. The meditation training had been
randomly assigned to students who were unaware of the manipulation, and the quiz score
benefits that the meditating students had received had been replicated. Additionally, quiz scores
were shown to be independent of students’ self-reported interest in the class. However, after two
experiments, we still did not know why meditators’ quiz scores had improved. Improvements in
meditators’ quiz scores did not appear to be mediated by mood or relaxation effects, or by
increases in interest in the topic of that day’s lecture. Therefore, we wondered whether the
effects of meditation training on quiz performance might be due to the close association between
meditation and the lecture topic itself, i.e., health and psychology. Therefore, we conducted
Experiment 3 in order to determine whether the key findings of Experiments 1 and 2 would
replicate on a different lecture topic and presentation format.
To do so, we identified an Introduction to Psychology course where students were
scheduled to watch a video recording of a lecture by Philip Zimbardo, a well-known
Running head: COGNITIVE TRAINING 17
psychologist in the United States, on the topic of Testing and Intelligence from the Discovering
Psychology video series. The particular lecture was chosen because we could think of no strong
overlap between the presentation topic and the topics of meditation or applied cognitive training.
Additionally, Experiment 3 also provided a means to test whether the learning improvements that
meditation had brought about in Experiments 1 and 2 would replicate when students were
watching a recording of a lecture, a lecture format that is becoming more common as universities
adopt so-called ‘online’ or ‘distance’ higher education programs.
Method
Participants
Participants in this study were 93 undergraduate psychology students and one graduate
student enrolled in an Introduction to Psychology course at a California state university. Access
to the student population was gained by consent from the course instructor. None of the students
in Experiment 3 had participated in Experiments 1 or 2. Of the 94 participants, 30 were males, 62
were females, and the mean age was 19.03 (two participants chose not to fill out a demographics
form so their data is excluded). Participants identified themselves as Caucasian (19.40%), Asian
or Pacific Islander (12.90%), more than one race (3.20%), Asian Indian (1.10%), Black/African-
American (15.10%), Middle Eastern (8.60%), Latino/Hispanic (37.60%) and declined to state
(2.20%). Forty-seven participants were freshmen, 33 were sophomores, nine were juniors, two
were seniors, one was a graduate student, and one participant did not indicate class standing.
Quiz
The quiz used in Experiment 3 was different from that which had been administered in
Experiments 1 and 2 because the topic of the video lecture was different. There were seven total
questions, four multiple-choice questions, two short-answer questions, and one true-or-false
Running head: COGNITIVE TRAINING 18
question. An example of one of the multiple-choice questions used is: “Who developed the first
well-known test of intelligence? A. Claude Steele, B. Stanford Binet, C. Lewis Truman, or D.
Alfred Binet.” An example of one of the short answer questions used is: “What is stereotype
threat?”
Design and Procedure
With the exception of the video presentation, the same general procedure was utilized in
Experiment 3 as was used in Experiments 1 and 2. A small change was made to the type of mood
survey that was being used. We utilized only the PANAS for pre and post mood measures
because it offered six additional mood adjectives not offered in the BMIS, but otherwise
participants completed the identical manipulation used in the previous experiments, and then
watched the 35-minute video lecture.
Results and Discussion
Random distribution of the paper instruction packets yielded 46 students who meditated,
and 48 that rested. Our analysis of Experiment 3 indicated that those in the meditation condition
did not significantly differ in pre mood, F(2, 88) = 0.27, p = .762, nor post mood, F(2, 88) =
0.78, p = .356. Likewise, behavioral relaxation, t(91) = 0.001, p = .888, and class interest, t(80)
= .80, p = .424, were unaffected by meditation. Correct answers on the quiz ranged from one half
to seven, and the meditation condition again performed better on the quiz than the rest condition
evidenced by a one-tailed t-test, t(92) = 1.80, p = .038; d = .38, replicating Experiments 1 and 2.
The effect size for quiz performance was found to be a small to medium effect according to
Cohen’s (1988) convention for a small effect (see Table 3 for Ms and SDs).
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Insert Table 3 about here
Running head: COGNITIVE TRAINING 19
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Experiment 3 demonstrated that meditation training before a video lecture on a topic
unrelated to meditation improved performance on a quiz about the lecture. Although both the
presentation style (i.e., a recorded lecture) and the lecture topic (i.e., testing and intelligence) did
lower the baseline student quiz performance, the topic and lecture format did not influence the
relative improvement in performance that meditating students demonstrated.
However, after three experiments, the authors admit that we do not fully understand the
underlying mechanisms by which meditation was able to improve knowledge retention of the
students in each of these three studies. After ruling out mood, relaxation, interest, and
interactions with the style or content of the lecture, we now speculate that the salutary benefits
we detected may have been due to increases in the meditating students’ self-regulatory
functioning, specifically their ability to delay gratification or avoid impulsive behaviors (see
Muraven & Baumeister, 2000; Muraven, Shmueli, & Burkley, 2006; Schmeichel, Vohs, &
Baumeister, 2003). We also know that students who are less able to self-regulate are less likely
to perform well in school (Butler & Winne, 1995; Zimmerman, 2000; Zimmerman, Bandura, &
Martinez-Pons, 1992), and that the ability to self-regulate may be diminished during long tasks
that require consistent self-regulation like attending to a course lecture (Muraven & Baumeister,
2000; Muraven, Tice, & Baumeister, 1998; Vohs, Baumeister, Schmeichel, Twenge, Nelson, &
Tice, 2008). Given that self-regulation is a mental resource that is susceptible to depletion
(Muraven & Baumeister, 2000), we now believe that a plausible explanation for the
improvements we detected in meditating students’ knowledge retention could be that the
meditation somehow boosted students’ ability to self-regulate in the short term, allowing
students who meditated to concentrate longer on the lecture material.
Running head: COGNITIVE TRAINING 20
Unfortunately, Experiments 1-3 utilized no direct measures self-regulation, a fact that
makes testing the boost hypothesis difficult. However, because we had collected demographic
information, we were able to perform one additional analysis on our data to indirectly test
whether the meditation we administered might have been of greater benefit to students with low
self-regulatory functioning. To do so, we reasoned that students who are better able to self-
regulate are more likely to perform well in school (Butler & Winne, 1995; Zimmerman, 2000;
Zimmerman, Bandura, & Martinez-Pons, 1992), and, therefore, that students with higher self-
regulatory functioning in higher education were more likely to continue their education (see
Flowers, 2002; Kitsantas, Winsler, & Huie, 2008; Nota, Soresi, & Zimmerman, 2004). As a
consequence, we reasoned that the number of students with low self-regulation would be greatest
among freshman, and we tested whether the meditation training we had provided had produced a
greater benefit to freshmen by comparing the percentage of freshman in each of our samples to
the effect size of the meditation on quiz performance. Table 4 demonstrates the observation that,
as the percentage of freshmen in the three classes we studied declined, so too did the effect size
of the meditation training we provided. While this analysis was conducted post-hoc, the data is
consistent with the idea that the students who were most likely to be low in self-regulatory
functioning (i.e., the freshmen) also received the greatest benefits to their knowledge retention as
a result of the brief meditation session.
-----------------------------------
Insert Table 4 about Here
-----------------------------------
General Discussion
A series of three experiments were conducted in three different higher education
Running head: COGNITIVE TRAINING 21
classrooms to test whether a brief form of meditation that was administered on paper prior to a
college lecture would improve the knowledge retention of students. The results of the three
experiments repeatedly demonstrated that students who meditated before a lecture performed
better on a post-lecture assessment than students who rested. These experiments also showed that
the improvements in students’ knowledge retention were not due to changes in the meditating
students’ mood, their levels of relaxation, conscious increases in students’ interest in the lecture,
or because of some unconscious priming between meditation and the lecture topic. Based on our
results, we now believe that it is reasonable to conclude that brief periods of meditation via the
Zen counting method are an effective method of improving students’ retention of information in
introductory college courses.
One contribution of the present study is that we have examined meditation and
knowledge retention using an experimental method that Shapiro et al. (2011) and others have
argued is necessary to establish causal links between meditation and salutary effects. Random
assignment does not always result in the ability to infer causation, but because the students in our
experiments were randomly assigned to either a meditation or control conditions, the two groups
were likely to be statistically equivalent in every other way but the meditation manipulation (see
Youmans, 2012). The chance that the effects were caused by some other variable are further
reduced by virtue of the replication of the effect across three different experiments. As such, we
have provided strong evidence for causality between the meditation manipulation and the
increases we detected in quiz performance, and we view our results as yet further evidence for
the salutary benefits of meditation that have already been documented via nonexperimental
methods (e.g., Cahn & Polich, 2006; Chan & Woollacott, 2007; van Leeuwen, Müller, &
Melloni, 2009).
Running head: COGNITIVE TRAINING 22
Other contributions of our study stem from the brevity of our meditation manipulation
that was sufficient to produce measurable gains in knowledge retention after only one session
lasting six minutes. Creating a brief meditation condition was important because one of our goals
had been to find some method of meditation that could be realistically administered before a
higher education classroom lecture without disrupting the learning environment. In our case, not
only did the meditation lead to better knowledge retention, but the instructors who volunteered
their classes for testing both anecdotally agreed that the meditation had been easy to administer,
and even had seemed to have a calming effect on their class. While we view these outcomes as
modest reasons for instructors who are interested in incorporating meditation to consider using
our methods, we note that researchers have also demonstrated the effectiveness of computer-
based cognitive intervention programs (e.g., Basak, Boot, Voss, & Kramer, 2008; Manger,
Eikenland, & Asbjornsen, 2002; Smith et al., 2009; Willis et al., 2006). Theoretically, these types
of manipulations might show the same, or greater, knowledge retention effects, and may be
easier for instructors to administer in classes where computers are present or during online
instruction. Finally, we note that the majority of participants in our study were Latino. To the
authors’ knowledge, there is no research that directly examines the effects of meditation on a
Latino population’s knowledge retention. The present findings therefore support the use of
meditation as a potential means to help minority student populations with knowledge retention.
All studies have limitations, and here many were the result of tradeoffs between the
control afforded by a laboratory study and the ecological validity of a study that collects data in
the actual setting of interest. By conducting our research in real higher education classroom with
students who were attending an actual class lecture for course credit, we were forced to make
many concessions that future laboratory studies may wish to address. One example was our
Running head: COGNITIVE TRAINING 23
utilization of a quiz that needed to be fair to the students and cover the lecture material, which
prevented us from using a more established measure of learning. Additionally, the time
differences between training and test differed because of differences between the durations of
time that the classes met, from 50 minutes for Experiments 1 and 2, to only 35 minutes for
Experiment 3. These differences might have produced some unintended temporal effects. We
also could not employ any direct measures of self-regulation or attentional processing given the
classroom setting. A third example was that no manipulation check on student engagement was
conducted due to requests to keep our manipulation as short as possible, and also because we
worried about how we would maintain the illusion that the experimental and control conditions
were completing the same task. But with no measure of how engaged the meditators were in the
meditation task, one cannot predict how our effect might hold across other settings and
populations where levels of engagement might be different. These realities qualify what readers
should conclude about the degree to which using the Zen counting method may affect student
learning. On the one hand, the effects of meditation might be the same, or even higher, if
engagement in the meditation is strong. However, the effects of meditation on classroom
learning might quickly diminish if engagement wans, for example, as the novelty of engaging in
meditation for the first time diminishes. Future researchers with interests in applying meditation
in academic settings are encouraged to address these issues using established measures of
learning and engagement.
Finally, an additional limitation of the studies reported here was our failure to uncover
more evidence about what underlying mechanisms might be mediating the effects of meditation
on knowledge retention. We found no evidence that the effect was due to changes in students’
mood, relaxation, or interest with the material, and only limited post-hoc evidence for mediation
Running head: COGNITIVE TRAINING 24
via self-regulation. Previous research has demonstrated that meditation is a viable method for
improving mood, levels of relaxation, cognition functioning, and self-regulation over the long-
term (Basak, Boot, Voss, & Kramer, 2008; Grossman, Niemann, Schmidt, & Walach, 2004;
Pagnoni & Cekic, 2007), leaving the cause of our findings rather mysterious, and threatening the
internal validity of the study. The authors are left to speculate that self-regulation is a
cognitively demanding task that can be aided by meditation creating additional cognitive
capacity useful for learning. This post-hoc speculation was supported by differences in the effect
sizes of the meditation on the basis of the ratio of first year to more senior students in the class
(see Table 4), but these proportions were also confounded with materials and test procedures
making it difficult to draw any definitive conclusions about the effect of year in college. On the
basis of these and other findings implicating self-regulation with learning enhancements, we
encourage future researchers to directly measure self-regulation as a mediator between
meditation and learning enhancement.
James (1890) believed that an education could improve attentional faculties would be the
education "par excellence" (p. 424), but we humbly recommend that educators who may be
considering whether to adopt meditation in the classroom do so only after weighing the potential
pros and cons. While the enhancements in quiz performance in the introductory courses we
tested were reliable, we note that they were also somewhat modest. Meditation increased quiz
scores between only 7-8% above those students who rested, and we did not test whether the
effects would persist, for example, if meditation were used in the classroom often or if
instruction was given verbally in a guided meditation. It is possible that there could be
differences in meditation presented either textually or verbally and that verbal guided meditation
in the classroom might improve engagement in the practice. We were also unable to test whether
Running head: COGNITIVE TRAINING 25
meditation would improve knowledge retention in situations where there were delays between
lectures and evaluations. For example, we do not know whether meditation would affect
students’ performance on a cumulative final exam. Of course, educators should also consider that
the present study was able to demonstrate measurable change in student performance with only 6
minutes of meditation training, with other research demonstrating that the positive effects may
last months (Fiebert & Mead, 1981) and may persist even after training is discontinued (Basak et
al., 2008). Introducing meditation in the classroom also produces other student benefits beyond
grade increases, including greater student interest in topics related to meditation, mindfulness,
and self-regulation, and greater understanding and appreciation of the differences between
eastern and western psychology (Hull, 2001; Michaelson, 2006). Providing different points of
view about lecture topics has also been shown to improve students’ problem solving (Griggs,
2003) and creativity (Leung, Maddux, Galinsky, & Chiu, 2008). Finally, numerous studies have
shown enhancements in cognitive, physiological, and neurological functioning with meditation
training (Brown et al., 2007; Cahn & Polich, 2006); these improvements are likely to be of
benefit, and of interest, to a variety of student populations.
Running head: COGNITIVE TRAINING 26
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Table 1
The Means and Standard Deviations for Mood, Relaxation, and Quiz Performance.
Mood
Pre Post
PA
(PANAS
)
NA
(PANAS
)
PA
(BMIS)
NA
(BMIS)
Relaxation
Quiz
Score
Meditation
M26.24 15.41 21.00 16.06 4.72* 6.33*
S
D
6.46 4.61 4.07 4.45 1.18 0.69
Rest
M23.76 16.53 19.35 16.12 3.65* 5.70*
S
D
9.50 6.63 6.50 4.86 1.06 1.05
Notes. PA = positive affect. NA = negative affect. PANAS = positive affect negative affect scale.
BMIS = brief mood introspection scale. PANAS scores were summed scores for 10 NA and 10
PA measures each scaled from 1(very slightly or not at all) to 5 (extremely). BMIS were also
summed score, eight NA and eight PA measures each scaled from 1(definitely do not feel) to 4
(definitely feel). Relaxation scores were measured from 1 (I felt extremely tense and upset
throughout my body) to 7 (I felt more deeply and completely relaxed than I ever have). Quiz
scores were a maximum of 7 points. *p < .05.
Running head: COGNITIVE TRAINING 36
Table 2
The Means and Standard Deviations for Mood, Relaxation, Quiz Performance, and Class
Interest.
Mood
Pre Post
PA
(PANAS
)
NA
(PANAS
)
SA
(BMIS)
Relaxation
Quiz
Score
Class
Interest
Meditation
M27.00 14.77 45.50 4.30 5.73* 4.24
S
D
8.45 3.82 5.91 1.06
1.17
0.74
Rest
M30.36 15.48 47.60 4.24 4.92* 4.31
S
D
8.74 5.72 6.46 1.27
1.67
0.79
Notes. PA = positive affect. NA = negative affect. SA= summed affect. PANAS = positive affect
negative affect scale. BMIS = brief mood introspection scale. Summed affect scores were
computed by adding positive affect scores to reverse scores of negative affect. Quiz scores were
a maximum of 7 points. * p < .05.
Running head: COGNITIVE TRAINING 37
Table 3
The Means and Standard Deviations for Mood, Relaxation, Quiz Performance, and Class
Interest.
Mood
Pre Post
PA
(PANAS)
NA
(PANAS
)
PA
(PANAS
)
NA
(PANAS
)
Relaxation
Quiz
Score
Class
Interest
Meditation
M28.06 15.46 23.33 13.09 3.89 3.90* 2.73
S
D
7.60 5.99 10.90 5.51 1.17 1.57 1.00
Rest
M28.06 16.38 26.36 13.34 3.89 3.33* 2.93
S
D
8.42 6.57 9.15 3.81 0.67 1.50 1.19
Notes. PA = positive affect. NA = negative affect. PANAS = positive affect negative affect scale.
Quiz scores were a maximum of 7 points. * p < .05.
Running head: COGNITIVE TRAINING 38
Table 4
Are the Effects of Cognitive Training Mediated by Individual Differences in the Ability to Self-
Regulate?
Experiment # Percentage of Freshmen Enrolled Cohen’s D
1 94.29% 0.64
2 80.36% 0.58
3 50.54% 0.38
