Content uploaded by Englevert Reyes
Author content
All content in this area was uploaded by Englevert Reyes on Mar 14, 2022
Content may be subject to copyright.
Feynman Technique as a Heutagogical Learning Strategy for
Independent and Remote Learning
Englevert P. Reyes1*, Ron Mhel Francis L. Blanco2, Defanee Rose L. Doroon3,
Jay Lord B. Limana4, and Ana Marie A. Torcende5
University of San Jose-Recoletos, Cebu City, Philippines
https://orcid.org/ 0000-0002-8263-2049, https://orcid.org/0000-0001-7633-518X,
https://orcid.org/0000-0001-9834-0860,
4 Immaculate Heart of Mary Academy, Minglanilla, Cebu, Philippines, https://orcid.org/0000-0002-0411-9733
5 ECC Foreign Language of the Philippines Inc., Cebu City, Philippines, https://orcid.org/0000-0003-4721-1123
*Email Correspondence: englevert.reyes@usjr.edu.ph
Abstract
The Feynman Technique is a mental model and learning strategy used to simplify
any complex information. This study endeavors to provide empirical evidence on the
eectiveness of the Feynman Technique as a heutagogy-based learning strategy that ts
the e-learning landscape. Utilizing true experimental research design, grades 4, 7, and 11
students from typical elementary and national high schools were randomly assigned to
experimental and control groups and underwent pre- and posttests. Using two-sample and
paired T-tests, results show that students under the experimental group, which applied the
Feynman Technique, showed higher posttest scores and learning gains than those in the
control group. Hence, this study proves that the Feynman Technique can be an eective
tool to improve K-12 students’ learning, especially now given the new learning delivery
modalities.
Keywords: heutagogy, learning strategy, independent learning, remote learning,
experimental research, new normal in education
1.0 Introduction
Across the world, schools and universities have
closed down to mitigate the catastrophic impact
and unprecedented health threats posed by the
COVID-19 pandemic. Consequently, the education
sector has to embrace an alternative mode of
learning - online education. Both teachers and
students have undergone a steep learning curve
while transitioning from face-to-face instruction to
remote teaching and learning via digital platforms.
Blended and hybrid learning, exible and
modular learning, synchronous and asynchronous
learning, among many other learning setups,
have become the new norm in today's education.
With online learning, learners are given more than
ever the power to exercise autonomy and self-
determination in the learning processes, which
is the core principle of the emerging learning
approach known as heutagogy (Moore, 2020).
In the Philippines, the Department of
Education (DepEd) takes the herculean challenge
to continue learning beyond the accustomed
2December
Recoletos Multidisciplinary Research Journal
setup. As mandated in DepEd Order (DO) 12 s. 2020,
schools and other community learning centers had
to close their physical conduct of classes to ensure
the health, safety, and well-being of learners and
teachers. While DepEd was preparing for the
opening of the school year 2020-2021, DepEd Sec.
Leonor Briones announced that the department
had put all possible learning resources, particularly
the self-learning modules (SLMs), in place so that
each learner will not be burdened and to ensure
access to basic education despite the pandemic
(DepEd, 2020). Adonis (2020) noted that at the
start of classes in public schools, students might
adapt to the new learning delivery modalities, but
absorbing the lessons could be troublesome as
students struggle to understand the contents of
the modules by themselves. Wanting to assist their
children but left with no choice, many parents and
guardians resorted to answering the questions
and activities in the modules themselves.
Although DepEd strategically provides “modular,
television-based, radio-based, blended, and
online” instruction, still several restraining factors
continue to persist (DepEd, 2020, par. 2). Along
with DepEd, the Commission on Higher Education
(CHED) also released its Memorandum Order No.
4, series of 2020 that stipulates the guidelines for
Flexible Learning, a method of learning where
students are given autonomy in how, what, when,
and where they learn (“Flexible Learning Denition
and Meaning,” 2019).
Apart from the similar struggles in both
basic and higher education levels, schools also
incorporate synchronous and asynchronous
learning, alongside other alternatives, to address
the ooded concerns involved in the shift to the
new normal in the Philippine education system.
Synchronous learning happens when the learning
activities and instructor’s guidance are done in
real-time connectivity, such as through video
conferencing. On the other hand, asynchronous
learning emphasizes independent learning, in the
absence of a present, real-time teacher, by utilizing
modules or otherwise known as learning packets
(Villena & Asano, 2020). The Learning Management
System (LMS), now a household term, refers to an
online portal that connects teachers and students
outside the classroom to create an avenue for
instructions and monitoring (Malik et al., 2017). The
implementation of the LMS may be unique for each
teacher and every school or academic institution.
Given the extraordinary circumstances
wherein learning in an online or virtual
environment is not an option anymore but a
necessity, the current educational system shows a
heavy leaning towards a learner-directed approach
(Moore, 2020). As learning opportunities center on
the use of technology, heutagogy, as an emerging
net-centric learning approach, gains today's
attention of educational experts across the globe.
The ultimate goal of heutagogy is for learners to
exhibit high autonomy and self-determination
so that they become “well-prepared for the
complexities of today’s workplace” (Blaschke &
Hase, 2016). Tumapon (2020) asserted that
teachers must provide learners with means that
develop learners’ self-ecacy – a trait essential to
improving the learner’s performance with lesser
monitoring by the teacher. Teachers should expose
students to other helpful learning methods and
enable students to nd opportunities to create
their strategies (Ramos, 2015). Hence, this paper
introduces a self-determined study model or
technique, known as the Feynman Technique
which was developed by the 1965 Nobel-prize-
winning physicist Richard Feynman. The very goal
of this study model is to simplify substantive and
complex concepts. Richard Feynman, himself,
was dubbed as “the Great Explainer” since he was
known to explain exceptionally the most complex
ideas in the simplest terms (Goodstein et al., 1996).
Having diculty adapting to remote learning,
learners are redirected to nd relevant solutions
and wise options such that they can learn on their
3
2021
own. This phenomenon explains the need to take
a heutagogical approach in teaching and learning.
In building self-ecacy among learners, educators
should strive to enable learners to explore their
problems profoundly and nd solutions without
the teacher's constant coaching (Blaschke & Hase,
2016). Despite the strong potential of heutagogy
to become the standard approach to learning in
this new era, the challenge is the lack of empirically-
studied strategies, methods, and systems that
support heutagogy due to its relative newness
(Moore, 2020).
In this study, the Feynman Technique is viewed
as a promising learning strategy that adheres to the
principles of heutagogy. Within the process of this
study model, students exhibit a signicant level of
independence as they ensure that their grasp on
the subject contents and lessons are profound and
accurate. Nevertheless, the eectiveness of the
Feynman Technique as a learning strategy is still
unexplored. Most of the existing studies are focused
on the specic mathematical and scientic models
that Richard Feynman developed and contributed
in his elds of expertise (Arlego & Fanaro, 2017;
Battaglia et al., 2017; De Luca, 2012; Kontokostas
& Kalkanis, 2013; Seltzer-Kelly, 2013; Wong et al.,
2014). None has attempted to examine, apply,
and test empirically the eectiveness of Feynman
Technique as a learning strategy.
Thus, this study endeavors to provide empirical
evidence of the eectiveness of the Feynman
Technique as a heutagogy-based learning strategy
that ts the e-learning landscape.
Conceptual Framework
This study is anchored on the Constructivist
Theory by Catherine Twomey Fosnot (1989). In
her theory, she posited four major concepts: (1)
learning relies on what people already know; (2)
new ideas arise as people adjust and change the
old ones; (3) learning includes inventing ideas
rather than gathering a set of facts mechanically;
and (4) substantive learning occurs by rethinking
old ideas and arriving at new perspectives or
paradigms after new ideas clash with old ones.
Another school of learning that supports this
study is autodidacticism, also referred to as self-
education or self-directed learning. According to
Brockett and Hiemstra (1991), the learner should
learn to regulate his learning and direct himself
to formulate schemes in realizing his goal. With
numerous technological resources available,
learners are now more enabled to self-directed
learning that comprises the freedom to choose the
methods of inquiry, self-regulation, and reection.
Hase and Kenyon (2013) also proposed an
approach suited for a 21st-century education,
the heutagogy or self-determined learning.
Heutagogy delves into the learner's adaptability to
various learning challenges previously neglected
under the constructivist approach. Blaschke and
Hase (2016) asserted that self-reection and
metacognition inuence the learner’s motivation
to arrive at a solution based on his derived
process (also known as double-loop learning).
Heutagogy has become a new trend in education
due to the disruptions caused by the pandemic
(Moore, 2020). As an approach, it emphasizes how
learning can be processed using online technology
and other strategies that could help learners
think more deeply about their assumptions and
beliefs – clarifying and simplifying their learning
experiences.
The three theories/approaches, though they
hold some distinct features, become integrated
into this study since they reinforce the attributes of
the Feynman Technique as a student-centered and
self-determined learning strategy that emphasizes
ideas of processing and critical thinking. Moreover,
with particular attention to heutagogy, the
Feynman Technique enables a learner to discover
independently a concept and choose his own best
way to arrive at the desired outcome. The goal of
Feynman Technique is for a learner to explain a
Reyes, Blanco, Doroon, Limana, & Torcende
4
Figure 1. Conceptual Framework
complex concept in its simplest manner which
allows even a child to understand. Under this
technique, Feynman proposed these four basic
steps: (1) writing down everything about the
chosen or focused topic/concept based on prior
knowledge or after receiving input, (2) explaining
the topic in simple terms as if teaching a child,
(3) reviewing and identifying gaps or problem
areas of one’s understanding or explanation, and
(4) simplifying the language further or creating
analogies to understand better. It can be noted that
steps 2-4 are expected to be iterative or constitute
a looping process. Probing further about a topic
may include the use of online resources. When
this rigorous process of alterations and revisions
reaches exhaustion, the learner: (a) learns a new
idea, (b) understands an existing idea better, (c)
remembers an idea, and (d) goes beyond learning
the concept through reconstruction. The Feynman
Technique allows the learner to assess which
aspect of his knowledge or understanding is solid
and which aspect is weak. This learning procedure
concretizes Albert Einstein’s wisdom, “If you can’t
explain it simply, you don’t understand it well enough."
Figure 1 shows the conceptual framework
of this study – highlighting the theories being
anchored on, the research participants, the
research design, and the outcome to be measured
to establish the eectiveness of the Feynman
Technique.
2.0 Research Design and Methods
This study utilized true experimental research,
specically, pretest-posttest equivalent groups
design. This design is also regarded as the only
research procedure that can adequately establish
the cause-and-eect relationship (Campbell
& Stanley, 2015). In this setup, learners were
randomly assigned to two groups - experimental
and control groups. During the class session, the
experimental group received the treatment or
the Feynman Technique while the control group
experienced the standard lesson procedures
indicated in DepEd’s prototype daily lesson plan.
Both groups were taught by the same teacher,
December
Recoletos Multidisciplinary Research Journal
5
at the same time and the same venue through
breakout sessions. Based on the pretest results,
both groups were found to be equivalent in
terms of intellectual level. All these measures
were done to prevent the extraneous variables
from potentially inuencing the outcomes of the
experiment, thereby strengthening the internal
validity of this research. The stages of the pretest
and posttest design follow the experimental model
of Campbell and Stanley (2015) as shown below:
R O X O
R O O
Referring to the model above, the R stands for
randomized selection and assignment of individual
participants, O for pretest, O for posttest, and X
for the intervention, which was the application of
the Feynman Technique.
The participants were Grades 4, 7, and 11 from
a local public elementary school and a national
high school. These grade levels were selected as
these are the beginning levels (as stated in the K-12
curriculum of DepEd) in elementary (intermediate),
junior high, and senior high school levels.
Although getting all the grade levels would be
ideal, the researchers’ limited time and resources
impeded them from doing so. Furthermore, since
all participants came from the same school, their
experiences in terms of school culture, practices,
norms, and standards would be the same; hence,
the participants were comparable. The total
participants from Grade 4 were 34 with 19 females
and 15 males, aged 8-11 years old. The Grade 7
level had the highest number of participants with a
classroom population of 37 with 26 females and 12
males, aged 12-13. The last participants were from
Grade 11, taking up Bread and Pastry Production
under the TVL (Technical-Vocational-Livelihood)
strand, aged 16-17, all females. Grade 11 had
the least number of participants based on the
attendance followed within the entire time frame
of the actual testing.
After identifying the sample size, multi-stage
sampling was done. Samples were taken in stages
using smaller sampling units at each chapter.
These chapters include stratied random sampling
and simple random sampling. During the rst
phase, stratied random sampling was employed
to identify students from one section. They were
then grouped into strata and categorized as high
and low procient English learners (based on
the English Prociency Test of the Department
of Education). During the second phase, simple
random sampling was used. Students from each
stratum were divided equally and chosen randomly
to complete both the control and the experimental
groups.
The lesson topics were determined by referring
to the competencies stipulated in DepEd K-12
English Curriculum Guide.
Table 1. Competencies measured for pre-and posttest
GRADE
LEVEL
TOPIC COMPETENCY
Grade 4 Denotation and
Connotation EN4V-IId-20.1: Denotation
EN4V-IId-20.2: Connotation
Grade 7 Hyponyms EN7V-III-d-13: Determine words or expressions with
hyponymous relations in a selection
Grade 11 Patterns of
Developmental
Writing
EN11/12RWS-IIIbf3: Distinguishes between and
among patterns of development in writing across
disciplines.
2021 Reyes, Blanco, Doroon, Limana, & Torcende
6
The research tool used was a thirty-ve-
item multiple-choice test questionnaire, which
underwent a dry run testing to dierent students
but from similar schools. The test items were
then statistically treated using Cronbach Alpha
Statistical Measure. The results yielded 0.79
and higher Cronbach alphas, which indicate
good reliability. The tests diered accordingly
based on the competencies (see table 1 for the
competencies). Separate consent letters had been
sent to the schools for dry run testing and schools
for actual testing and experimentation before the
approval was granted.
The three-week study was broken down
into three phases as seen in Figure 2: (a)
Pretesng, (b) Intervenon, and (c) Posesng.
During the Pretesng phase, English Prociency
Test and Pretest were conducted in the rst
week to actualize the sampling mechanisms
and establish groups' equivalency. In the
second phase, the intervenon or treatment
was implemented. The control group received
the convenonal teaching method while
the experimental group was taught using
the Feynman Technique. The process of the
Feynman Technique involved the following
steps: (1) a een-minute reading of the
given material/handout and taking notes of
the concept, (2) a ten-minute self-discussion
or explanaon, (3) a ve-minute review
acvity from the constructed knowledge with
scaolding, and (4) a ve-minute vericaon of
one’s understanding of the concept aimed at
simplifying its meaning. Researchers collected
learners’ actual wrien composions as
evidence of the treatment process. The last
phase was the Posesng, wherein both groups
took a test similar to the pretest.
As a measure against validity threats, the
researchers became experimenters of the study
since they possessed a full grasp of the Feynman
Technique and its processes. Weeks before the
conduct of the experiment, the experimenters
had built a rapport with the parcipants as the
former served as student teachers or teacher
assistants. This, in eect, brought in the
naturalness of behaviors among all the student
parcipants. During the study, there were also
setbacks caused by factors beyond the control
of the researchers. These limitaons included
student aendance, teacher support, and me
constraints.
The data gathered from the pretest and
posest were stascally treated using paired
t-test and two-sample t-test. The paired
t-test is a type of parametric procedure used
to compare two quantave measurements
taken from the same individuals whereas the
two-sample t-test was used to compare two
independent groups. Both can tell if there is
a signicant dierence between the means of
two groups or measures.
Figure 2. Time frame for the implementation of the study
December
Recoletos Multidisciplinary Research Journal
7
3.0 Results and Discussion
Data on the various variables taken during
the study period underwent statistical analyses to
determine the eectiveness of Feynman Technique.
One prerequisite of a parametric test like a
t-test is testing the raw data for normality. All pre-
and post-test data results of both experimental and
control groups passed the normality test. Hence,
t-tests (paired and two-sample) could be applied.
The distribution of scores gives us an overview
that (a) during the pretest, the majority of the
participants' scores fell under 'fairly satisfactory'
and 'satisfactory’ and (b) during posttest, a
signicant number improved, placing the bulk of
participants under 'approaching prociency' and
a few under 'procient' and 'satisfactory.' It can be
further noted that the most apparent leaps were
coming from the experimental groups.
Scores
Grade 4 Grade 7 Grade 11
InterpretationExperimental Control Experimental Control Experimental Control
Pre Post Pre Post Pre Post Pre Post Pre Post Pre Post
28 - 35 0 2 0 0 0 4 0 0 0 1 0 0 Procient
21 - 27 3 8 1 5 8 15 8 12 3 8 3 3 Approaching
Prociency
15 - 20 8 6 9 10 9 0 8 7 5 1 5 7 Satisfactory
7 – 14 6 1 7 2 2 0 3 0 2 0 2 0 Fairly Satisfactory
1 – 6 0 0 0 0 0 0 0 0 0 0 0 0 Poor
Table 2. Distribution of participants’ scores during the pre-and posttesting
The participants were assumed to have
no background about the topics or concepts
introduced to them during the pretesting. Therefore,
a two-sample t-test had to be applied to establish
the comparability or equivalency of both groups
(experimental and control) in each grade level.
Table 3 indicates that the p values (p = 0.528, p =
0.942, p = 0.630 for grades 4, 7, and 11, respectively)
were all greater than .05, which implies that there is
no signicant dierence between the experimental
and control groups. The result conrms that the
participants coming from the two dierent groups
were deemed comparable or equivalent and are
on an equal footing at the start of the experiment.
Furthermore, the results strengthened the internal
validity of the experiment.
Tables 4 and 5 measure the changes that
occurred before and after the treatment in both
control and experimental groups, respectively,
across all levels. All grade levels in both groups
demonstrated a signicant increase in pre- and
posttest scores, except for the Grade 11 participants
under the control group, with t(9) = 0.000, p =
1.000. Based on actual observation, probable
factors behind this lack of improvement were the
lack of interest and tardiness in reporting to class.
Nevertheless, the results generally imply that
when students were taught about the lesson in
whatever forms, ways, or strategies, learners were
expected to improve. Control groups proved to
gain some learning growth still despite receiving
only traditional teaching methods. It is also equally
2021 Reyes, Blanco, Doroon, Limana, & Torcende
8
important to pinpoint how the Feynman Technique
could still signicantly improve learning even if
the learner was as young as eight years old. As a
self-determined learning strategy, the Feynman
Technique is assumed to work only for learners with
high autonomy, reection, and maturity, in which
age becomes a determining factor (Piaget, 1964;
Kuhn, 2000). The results proved otherwise – that the
Feynman Technique showed potential applicability
and benets, not only to high school and college
students but even to children at the elementary
level.
Table 3. Two-sample t-test results on pretest between groups in all levels
Grade Level Mean SD T-Value P-Value Df Decision Interpretation
G4PretestExperimental 15.82 4.10 0.64 0.528 30 Accept No Signicant Dierence
G4PretestControl 15.00 3.39
G7PretestExperimental 19.16 4.52 0.07 0.942 35 Accept No Signicant Dierence
G7PretestControl 19.05 4.26
G11PretestExperimental 17.40 5.76 -0.49 0.630 16 Accept No Signicant Dierence
G11PretestControl 18.50 4.12
Table 4. Paired t-test results on pre- and posttests of the control group in all levels
Table 5. Paired t-test results on pre- and posttests of the experimental group in all levels
Grade Level Mean SD T-Value P-Value Df Decision Interpretation
G4Pretest 15.82 4.10 -5.96 0.000 16 Reject Signicant Dierence
G4Posttest 23.18 4.94
G7Pretest 19.16 4.52 -6.77 0.000 18 Reject Signicant Dierence
G7Posttest 26.16 1.68
G11Pretest 17.40 5.76 -3.97 0.003 9 Reject Signicant Dierence
G11Posttest 24.00 3.74
Grade Level Mean SD T-Value P-Value Df Decision Interpretation
G4Pretest 15.00 3.39 -3.24 0.005 16 Reject Signicant Dierence
G4Posttest 18.47 4.27
G7Pretest 19.053 4.262 -2.29 0.034 18 Reject Signicant Dierence
G7Posttest 21.474 3.339
G11Pretest 18.50 4.12 0.000 1.000 9 Accept No Signicant Dierence
G11Posttest 18.50 3.84
December
Recoletos Multidisciplinary Research Journal
9
In any true experiment study, the control
group mainly functions as a baseline or
comparison group. The control group provides a
point of reference when measuring the eect of
the Feynman Technique on the students' learning.
Hence, Tables 6 and 7 indicate results that compare
the posttest performances and the learning gains
between the experimental and the control groups.
A learning gain score was obtained by subtracting
an individual's pretest score from his/her posttest
score (LG = Posttest – Pretest). Using a two-sample
t-test in comparing the posttest and the learning
gain scores of both experimental and control groups
could determine if the two groups have varying
leaps of improvement and whether the dierence
between the two is statistically signicant or not.
Furthermore, the groups' dierence helps conrm
or validate the eectiveness of the Feynman
Technique as a heutagogical learning strategy.
Though the previous tables (tables 4 and 5) indicate
that all the participating students signicantly
improved during the posttest regardless of
the type of intervention, Table 6 gives a more
profound nding by revealing that the posttest
performances of the two groups per grade level
were signicantly dierent. In all grade levels, the
experimental group consistently obtained better
or higher posttest scores compared to the control
group with t(31) = 2.97, p = 0.006; t(26) = 5.46, p =
0.000; t(17) = 3.25, p = 0.005, for grades 4, 7, and
11, respectively. In the same manner, Table 7 shows
a signicant dierence between the two groups
in terms of their learning gains. The experimental
groups had greater learning leaps as compared to
the control groups with t(31) = 2.38, p = 0.024; t(35)
= 3.10, p = 0.004; t(13) = 3.49, p = 0.004, for grades
4, 7, and 11, respectively.
The main advantage of employing a true
experimental design is its eectiveness and
adequacy to establish a cause-and-eect
relationship (Campbell & Stanley, 2015). This
experiment has provided conclusive evidence on
the eectiveness of the Feynman Technique. The
consistent and better test results of students from
the experimental groups were attributed to the use
of Feynman Technique in this study. Participants
revealed that most often, learning for them was
simply regurgitating facts and information (Lord &
Baviskar, 2007). The Feynman Technique, however,
seeks to dispel this low-level thinking practice by
encouraging deeper learning processes, which
include synthesis (putting complex ideas into simple
terms), analysis (identifying gaps of knowledge),
evaluation (testing one’s understanding), creativity
(using analogies to explain better or remember the
concept), and metacognition (thinking about one’s
own thinking) (Bloom, 1956; Piaget, 1964; Kuhn
2000). If the learner can explain an idea in simple
language, then he/she has deeply understood
it (Einstein, n.d.). With the Feynman Technique,
learners are also encouraged to use digital tools
and resources to further their understanding of the
concept (Moreillon, 2015; Genova, 2019). Feynman
Technique is a learning strategy that allows the
learner to exercise high autonomy and self-
regulation. These requisites make the Feynman
Technique an eective and superior learning
method, especially for 21st-century learning
(Kuhlthau et al., 2015; Kereluik et al., 2013) and
education in the new normal (Dziuban et al., 2018;
Triyason et al., 2020). The Feynman Technique
shows great potential as the primary learning
strategy amid the widespread demand for online
or remote learning.
2021 Reyes, Blanco, Doroon, Limana, & Torcende
10
Table 6. Two-sample t-test results on posttest between groups in all levels
Grade Level Mean SD T-Value P-Value Df Decision Interpretation
G4PosttestExperimental 23.18 4.94 2.97 0.006 31 Reject Signicant Dierence
G4PosttestControl 18.47 4.27
G7PosttestExperimental 26.16 1.68 5.46 0.000 26 Reject Signicant Dierence
G7PosttestControl 21.47 3.34
G11PosttestExperimental 24.00 3.74 3.25 0.005 17 Reject Signicant Dierence
G11PosttestControl 18.00 3.84
Table 7. Two-sample t-test results of learning gains for all groups in all levels
Grade Level Mean SD T-Value P-Value Df Decision Interpretation
G4Experimental 7.35 5.09 2.38 0.024 31 Reject Signicant Dierence
G4Control 3.37 4.42
G7Experimental 7.00 4.51 3.10 0.004 35 Reject Signicant Dierence
G7Control 2.42 4.60
G11Experimental 6.60 5.25 3.49 0.004 13 Reject Signicant Dierence
G11Control 0.00 2.87
4. 0 Conclusion and Recommendation
This study has proven the eectiveness of
the Feynman Technique as a heutagogy-based
learning strategy after utilizing a true experimental
research design. Students (experimental group)
who were exposed to the Feynman Technique
exceeded their counterparts in the control group
in terms of the posttest and learning gain scores.
The positive results can be attributed to its
constructivist, autodidactic, and heutagogical
approach. Deep understanding of the concepts
and demonstration of high-level autonomy and
self-regulation enable the learners to learn their
lesson more eectively and eciently, especially
now given the new learning delivery modalities.
The Feynman Technique as a pedagogical practice
reemphasizes that independent learning plays a
crucial role in students’ authentic learning. Using
the Feynman Technique as a teaching strategy can
help learners improve their academic performance
and develop the necessary 21st-century skills.
Adopting a pedagogy that allows complex
information to be digested into simpler concepts,
teachers and school administrators may be able
to nd an answer to the diculty of the students
to learn in a remote or modular learning setup.
With the recognition of the limitations of this
study, further research is recommended, which
may include: [1] looking for similar strategies to
elevate student performance during online and
oine learning; [2] introducing the technique to
learners in an actual remote learning setup; and [3]
applying this method in other academic subjects,
elds, and disciplines, or even in the workplace.
December
Recoletos Multidisciplinary Research Journal
11
References
Adonis, M. (2020). DepEd Modules Stump Even
Adults. Inquirer October 08, 2020 issue.
https://bit.ly/3mZe3ow
Arlego, M., & Fanaro, M.D. (2017). Light and matter
diraction from the unied viewpoint of
Feynman's Sum of all Paths. European Journal
of Physics Education, 8, 16-26. https://doi.
org/10.20308/ejpe.v8i2.164
Battaglia, O. R., Di Paola, B., & Fazio, C. (2017).
K-means Clustering to Study How Student
Reasoning Lines Can Be Modied by a
Learning Activity Based on Feynman’s
Unifying Approach. Eurasia Journal of
Mathematics, Science and Technology
Education, 13(6), 2005-2038. https://doi.
org/10.12973/eurasia.2017.01211a
Blaschke, L. M., & Hase, S. (2016). Heutagogy:
A holistic framework for creating twenty-
rst-century self-determined learners. In
The future of ubiquitous learning (pp. 25-40).
Springer, Berlin, Heidelberg. https://doi.
org/10.1007/978-3-662-47724-3
Bloom, B. S. (1956). Taxonomy of educational
objectives. Vol. 1: Cognitive domain. New
York: McKay, 20(24), 1. https://bit.ly/3F24zT3
Brockett, R. G., and Hiemstra, R. (1991) A
Conceptual Framework for Understanding
Self-Direction in Adult Learning. Self-
Direction in Adult Learning: Perspectives on
Theory, Research, and Practice. https://doi.
org/10.4324/9780429457319
Campbell, D. T., & Stanley, J. C. (2015). Experimental
and Quasi-Experimental Designs for Research.
https://doi.org/10.1016/j.amj.2006.09.001
De Luca, R. (2012). Feynman's and Ohta's
Models of a Josephson Junction. European
Journal of Physics, 33(6), 1547. https://doi.
org/10.1088/0143-0807/33/6/1547
DepEd (2020). DepEd prepares Self-Learning
Modules for Education's New Normal. https://
bit.ly/2U3Jd1x
Dziuban, C., Graham, C. R., Moskal, P. D., Norberg,
A., & Sicilia, N. (2018). Blended learning: the
new normal and emerging technologies.
International journal of educational technology
in Higher education, 15(1), 1-16. https://doi.
org/10.1186/s41239-017-0087-5
Einstein, A. (n.d.) Albert Einstein Quotes.
BrainyQuote. https://www.brainyquote.com/
quotes/albert_einstein_383803
Flexible Learning Denition and Meaning. (2019,
September 16). Retrieved from https://
tophat.com/glossary/f/exible-learning/
Fosnot, C. T. (1989). Enquiring Teachers, Enquiring
Learners: A Constructivist Approach to
Teaching.
Genova, M. M. (2019). 21st century language
classroom with digital tools and resources.
Industry 4.0, 4(3), 142-145. https://
stumejournals.com/journals/i4/2019/3/142
Goodstein, D. L., Feynman, R. P., & Goodstein, J.
R. (1996). Feynman's lost lecture: the motion
of planets around the sun. WW Norton &
Company.
Hase, S., & Kenyon, C. (Eds.). (2013). Self-determined
Learning: Heutagogy in Action. Bloomsbury
2021 Reyes, Blanco, Doroon, Limana, & Torcende
12
Academic Collections (3-6). https://doi.
org/10.5040/9781472553232.ch-001
Kereluik, K., Mishra, P., Fahnoe, C., & Terry, L. (2013).
What knowledge is of most worth: Teacher
knowledge for 21st century learning. Journal
of digital learning in teacher education, 29(4),
127-140. https://doi.org/10.1080/21532974.2
013.10784716
Kontokostas, G., & Kalkanis, G. (2013). Teaching
Electron-Positron-Photon Interactions
with Hands-on Feynman Diagrams. The
Physics Teacher, 51(4), 232-233. http://doi.
org/10.1119/1.4795369
Kuhn, D. (2000). Metacognitive development.
Current directions in psychological science,
9(5), 178-181. http://www.jstor.org/
stable/20182660
Kuhlthau, C. C., Maniotes, L. K., & Caspari, A. K.
(2015). Guided inquiry: Learning in the 21st
century. Abc-Clio. https://bit.ly/3AZoJuQ
Lord, T., & Baviskar, S. (2007). Moving students
from information recitation to information
understanding-Exploiting Bloom's Taxonomy
in creating science questions. Journal of
College Science Teaching, 36(5), 40. https://bit.
ly/3ARCM5y
Malik, M., & Fatima, G. (2017). E-Learning: Students'
Perspectives about Asynchronous and
Synchronous Resources at Higher Education
Level. Bulletin of Education and Research, 39(2),
183-195. https://eric.ed.gov/?id=EJ1210223
Moore, R. L. (2020). Developing lifelong learning
with heutagogy: contexts, critiques, and
challenges. Distance Education, 41(3), 381-
401. https://doi.org/10.1080/01587919.2020.
1766949
Moreillon, J. (2015). Increasing interactivity in
the online learning environment: Using
digital tools to support students in socially
constructed meaning-making. TechTrends,
59(3), 41-47. https://doi.org/10.1007/s11528-
015-0851-0
Piaget, J. (1964). Part I: Cognitive development in
children: Piaget development and learning.
Journal of research in science teaching, 2(3),
176-186. https://bit.ly/3ARCb3O
Ramos, A. (2015). Methods and Teaching Strategies
Used by Teacher Education Faculty Members
of one State University in the Philippines. Asia
Pacic Journal of Multidisciplinary Research,
3(5). https://bit.ly/2JfLxic
SeltzerKelly, D. (2013). Feynman diagrams, problem
spaces, and the Kuhnian revolution to come in
teacher education. Educational Theory, 63(2),
133-150. https://doi.org/10.1111/edth.12014
Triyason, T., Tassanaviboon, A., & Kanthamanon,
P. (2020, July). Hybrid Classroom: Designing
for the New Normal after COVID-19
Pandemic. In Proceedings of the 11th
International Conference on Advances in
Information Technology (pp. 1-8). https://doi.
org/10.1145/3406601.3406635
Tumapon, T. (2020). Fostering Students’ Self-
ecacy in The New Normal. Manila Bulletin
July 23, 2020 issue. https://bit.ly/2IbwQxV
Villena, D & Asano, K., Jr. (2020). Flexible Learning
December
Recoletos Multidisciplinary Research Journal
13
Program: A Framework For Letran’s Instructional
Delivery Platform. Pages 6-8. https://bit.
ly/3ezJfHX
Wong, C. L., Chu, H. E., & Yap, K. C. (2014). Developing
a framework for analyzing denitions: A
study of the Feynman Lectures. International
Journal of Science Education, 36(15), 2481-
2513. https://doi.org/10.1080/09500693.201
4.893594
2021 Reyes, Blanco, Doroon, Limana, & Torcende
