FLEXIBLE DISTANCE LEARNING MODALITY THROUGH THE LENS OF
COLLEGE OF EDUCATION STUDENTS
ABAD, JANINE RIA J.
AGOSTOSA, ALLIAH MAE M.
CAMIGLA, KIRSTEN B.
CONTRERAS, ANGELICA L.
MENDOZA, JESSA A.
ORDOVEZ, MARICRIS G.
PUECA, JESSREL B.
VALDEZ, GEORGE B.
VALIENTE, JEROME A.
VILLARAZA, NICKA L.
An undergraduate thesis presented to the Faculty of the College of Education
of Central Bicol State University of Agriculture
Calabanga Campus
In Partial Fulfillment of the Requirements for the Subject
Issues, Trends, and Culture of Teaching
Bachelor of Secondary Education
Major in English
JANUARY 2022
i
ACKNOWLEDGMENT
This research became a fruitful reality with the help of the kind and usual
support of many individuals. We would like to express our deepest gratitude to
the following:
To our Almighty God, for the wisdom He bestowed upon us, the strength
and peace of mind as well as good health in order to finish this research.
To our Parents, for the financial and moral support they gave to us. To
their full consideration in allowing us to have some night over.
To our Instructor, for the well-supplemented discussions that inspired us
to accomplish this academic requirement.
To our friends, who continuously motivated us and assisted us during
the data gathering period.
To the University Registrar and Dean of Education Department, for
approving our request to conduct this study in our institution. This was made
possible with your favorable approval.
To our dearest respondents, third-year BSED English Majors, for their
full cooperation and informative response leading to the success of this paper.
Thank you for your active participation.
Our warm regards!
Abad, J; Agostosa, A; Camigla, K; Contreras, A; Mendoza, J; Ordovez, M;
Pueca, J; Valdez, G; Valiente, J; and Villaraza, N
Researchers
ABSTRACT
This study mainly focused on the preparedness and challenges of
college education students in the flexible distance learning modality. The
respondents of this study are third-year students taking Bachelor of Secondary
Education, Major in English at Central Bicol State University of AgricultureCalabanga Campus during the academic year 2021-2022. This research used
a quantitative approach and a descriptive-correlated research design was
adopted utilizing the survey questionnaires. The sampling technique used is a
total enumeration, where all members of the whole population are considered
and measured. It answered the questions: (1) What is the profile of the college
students of the Central Bicol State University of Agriculture, Calabanga
Campus, in terms of: (a) student type; (b) family income; and (c) residence
geographical location; (2) What is the level of preparedness of the college
students to the flexible distance learning modality along; (a) learning resources;
(b) internet access; and (c) technological literacy; (d) home learning space; (3)
What are the challenges of the respondents in Flexible Distance Learning
Modality in terms of: (a) self-regulation challenges (SRC); (b) technological
literacy and competency challenges (TLCC); (c) student isolation challenges
(SIC); (d) technical sufficiency challenges (TSC); (e) technological complexity
challenges (TCC); (f) learning resource challenges (LRC); and (g) learning
environment challenges (LEC); (4) Is there a significant relationship between
the students’ level of preparedness and the challenges experienced with
flexible distance learning modality?. The researchers found out that most of the
respondents are non-working students, identified as poor, and most of them
reside in an upland area. The respondents’ level of preparedness in FDLM is
iii
fairly prepared. Furthermore, the challenges that the respondents mostly
encountered
are
procrastination,
sometimes
experiencing
isolation,
accessibility to technological resources, the complexity of technological
resources, lack of available resources, and distracting and inconvenient
learning environment. The overall data and findings revealed that there is no
significant relationship between the students’ level of preparedness and the
challenges experienced with flexible distance learning modality. Thus, the
researchers highly recommended time management, teacher’s consideration,
and application for educational assistance and scholarships. Finally, the
researchers encourage the respondents to improve their learning strategies;
the parents to further contribute to a more conducive learning environment at
home and; the academe to promote awareness of the learning process and
conduct further enrichment programs and projects about technological literacy
and competency.
iv
TABLE OF CONTENTS
Page
TITLE PAGE ……………………………… …………………………………
i
ACKNOWLEDGEMENT ……………………………….………….……..…
ii
ABSTRACT …………..;………………………………….…………….……
iii
TABLE OF CONTENTS …………………..…….……………………..……
v
CHAPTER I – THE PROBLEM
Introduction ……………………………………………………………
1
Statement of the Problems ………………………………………….. 3
Objectives of the Study ………………………………………………. 4
Assumptions of the Study ……………………….…………………… 6
Hypothesis of the Study ………………………………………….…… 6
Significance of the Study ……………….………………………...…. 7
Scope and Limitation of the Study ………….…………………….... 8
Locale of the Study ………………………………..……………..…... 9
Definition of Terms ………………………………..…………..…….. 10
CHAPTER II – REVIEW OF RELATED LITERATURE AND STUDIES
Related Literature ………………………………………….…..…
13
Related Studies ……………………………………………………
17
v
Theoretical Framework …………………………………………….
22
Theoretical Paradigm ………………………………………………
24
Conceptual Framework …………………………………………….
25
Conceptual Paradigm ………………………………………………
25
Synthesis of State-of-the-Art ……………………………...……….
26
Gap Bridged by this Study ………………………………………….
27
CHAPTER III – RESEARCH DESIGN AND METHODOLOGY
Research Design ………………………………………………....…
30
Respondents of the Study ……………………………………….…
30
Data Gathering Procedure …………………………………………
31
Research Instruments …………………………………………...…
32
Statistical Treatment of Data ………………………………………
32
CHAPTER
IV
–
DATA
PRESENTATION,
ANALYSIS,
AND
INTERPRETATION
Student Profile…..……………………………………..……………..
36
Level of Preparedness in Flexible Distance Learning Modality … 39
Challenges in the Flexible Distance Learning Modality………….. 42
Pearson’s Correlation Between Students’ Level of Preparedness
and Challenges………………………………………………………… 51
CHAPTER V – SUMMARY, FINDINGS, CONCLUSIONS, AND
RECOMMENDATIONS
Summary ………….……………………………………………..…
vi
54
Problem No. 1: What is the profile of the college students of the Central
Bicol State University of Agriculture, Calabanga Campus, in terms of: a)
Student type; b) Family income; and c) Residence geographical location?
Findings …………..………………………………….………….…
55
Conclusions ……………….………………………………………
55
Recommendations …………………………..……………………
56
Problem No. 2: What is the level of preparedness of the college students
to the flexible distance learning modality along: a) Learning resources; b)
Internet Access; c) Technological Literacy; and d) Home Learning Space?
Findings ……………………………….…………………….……
56
Conclusions ………………………………..…………….………
57
Recommendations ……………………….….………..…………
57
Problem No. 3: What are the challenges of the respondents in Flexible
Distance Learning Modality in terms of: a) Self-Regulation Challenges
(SRC); b) Technological Literacy and Competency Challenges (TLCC); c)
Student Isolation Challenges (SIC); d) Technical Sufficiency Challenges
(TSC); e) Technological Complexity Challenges (TCC); f) Learning
Resource Challenges (LRC); and g) Learning Environment Challenges
(LEC)?
Findings ……………………………………………………………
58
Conclusions ……………………………….….……………………
60
Recommendations ……………………………..…………………
62
vii
Problem No. 4: Is there a significant relationship between the students’
level of preparedness and the challenges experienced with flexible
distance learning modality?
Findings ……………………………………………….……………
63
Conclusions …………………………………….……….…………
63
Recommendations ……………………….…….…………………
63
Bibliography ……………….…..…………………………………………
65
viii
APPENDICES
A. Letter of Request ……………………………………………………
68
B. Online Survey Questionnaire ………………………………………
69
C. Graphical Presentation of Survey Results ………………..………
81
D. Raw Test Data or Results ………………………………………..…
86
E. Values of Y for Person Product Correlation Coefficient …………
91
F. SOP3 Challenges: Overall Weighted Mean ………………………
93
G. Pearson’s Correlation Between Students’ Level of Preparedness and
Challenges with Flexible Learning Modality…………………….…
95
H. Table of Critical Values: Pearson Correlation ………………….…
I. Curriculum Vitae …………………………………………...….….….
98
99
List of Figures
Geographical Map Location of CBSUA Calabanga Campus…......
10
Theoretical Paradigm ……………………………..…………….……
24
Conceptual Paradigm ……………………………..………………….
25
List of Tables
Distribution of Respondents ……………………………………..…… 31
Four Anchors for the Likert Response Scale …..…………..….…… 34
Five Anchors for the Likert Response Scale ……………..………... 34
Student Type ……………………………….…………………....…… . 36
Family Income ………………………………………………..……… .. 37
ix
Residence’s Geographical Location ………………………….……….. 38
Level of Preparedness of the Respondents in Internet Access…..… 39
Level of Preparedness of the Respondents in Learning Resource … 40
Level of Preparedness of the respondents in Technological Literacy.. 40
Level of Preparedness of the respondents in Home Learning Space.. 41
Respondents’ Level of Preparedness…………………………………
41
Self-Regulation Challenges (SRC) ……………………………………
42
Technological Literacy and Competency Challenges (TLCC) ……
44
Student Isolation Challenges (SIC) ………………….………………
46
Technological Sufficiency Challenges (TSC) ………………………
47
Technological Complexity Challenges (TCC) ………………………
48
Learning Resource Challenges (LRC) ………..……………….……
49
Learning Environment Challenges………………….……….………
50
Overall Weighted Mean of Challenges…………………..…….……
51
Tabulated data for Pearson’s correlation ……………………..……
52
Strength of Relationship of Pearson r …………………..…….……
52
Table of Critical Value of Pearson r …………………..……….……
53
x
CHAPTER I
THE PROBLEM
Introduction
The COVID-19 pandemic has created issues and challenges on the
economic, social, and political aspects across the globe. More than just a health
crisis, it has also resulted in an educational crisis. To prevent the spread of the
virus, health protocols are strictly implemented. During lockdowns and
quarantines, 87 % of the worlds’ student population was affected and 1.52
billion learners were out of school and related educational institutions
(UNESCO Learning Portal,2020 cited in Dayagbil, et.al. 2021). The
suddenness of COVID-19 left the education sector in a rush of addressing the
changing of the learning system.
Commission on Higher Education (CHEd) issued COVID Advisory No. 6
on April 13, 2020, urging tertiary institutions to arrange flexible learning and
other alternative modalities of instruction. It authorized institutions to consider
ways on how to meet the requirements for the completion of a subject or
program. They may employ and incorporate responsive approaches and
strategies for student assessment. The Flexible Distance Learning Modality has
been popularized as the response to the challenge of innovating educational
delivery mechanisms in higher education. It is one of the viable ways to
continue learning beyond the pandemic realm. CHEd Chairperson, Prospero
De Vera even emphasizes the wider concept of flexible learning as more
encompassing than online learning. De Vera explains that flexible learning
does not necessarily require connectivity but instead it focuses on the design
1
and delivery of programs, courses, and learning interventions that address the
learners’ unique needs in terms of pace, place, process, and products of
learning (Parrocha, 2020). Flexibility can be found in several other learning
approaches: distance education, online learning, blended learning, classroom
learning, etc. Flexible learning is not a distinct educational mode but it
embraces, extends, and combines several familiar, existing, and evolving
approaches to learning and teaching.
Coping with the effects of the COVID-19 pandemic in HEIs demands a
variety of perspectives among its stakeholders. Consultation needs to include
the administration who supports the teaching-learning processes, the students
who are the core of the system, the faculty members or teachers who perform
various academic roles, parents, and guardians who share the responsibility of
learning continuity, the community, and the external partners who contribute to
the completion of the educational requirements of the students (Dayagbil, et al.
2021, cited in Illanes et al., 2020; Smalley, 2020). On the other hand, the
implementation of Flexible Learning Modality in the new normal education has
raised issues and challenges on its stakeholders, most especially to students
and teachers. Despite the efforts of education sectors to save the sustainability
and quality education of the country through flexible learning, Filipino university
students are still confronted with several difficulties in the practice of new
normal education. The accessible education for all advocacy was still in the
process as pandemic interrupted its successful implementation.
Pursuant to COVID Advisory No. 6, Central Bicol State University of
Agriculture (CBSUA) is one of those universities in the Philippines practicing
the Flexible Distance Learning Modality in the new normal set up to ensure that
2
quality education is still provided to students. There are major curricular
adjustments and interventions done by the university to make sure that
Stateans are not being left behind in this new normal education. However,
despite the effort extended by the university, several challenges are confronted
while in the process of implementation. Herein, as students of the university,
the researchers are interested in studying the students’ perspective on Flexible
Distance Learning Modality through the lens of College Education students.
The perspective of the students is crucial to consider because they are the main
recipient of this new mode of learning. One way to determine the state of
Flexible Distance Learning Modality in CBSUA is through recognizing the
perspective of Stateans in terms of their sociodemographic profile, level of
preparedness, encountered difficulties and challenges, and their adaptive
strategies.
Statement of the Problem
This study aims to determine the preparedness and challenges of the
College of Education students of the Central Bicol State University of
Agriculture, Calabanga Campus to flexible distance learning modality.
Specifically, this research aims to seek an answer to the following
questions:
1. What is the profile of the college students of the Central Bicol State
University of Agriculture, Calabanga Campus, in terms of:
a. Student type;
b. Family income; and
3
c. Residence geographical location
2. What is the level of preparedness of the college students to the
flexible distance learning modality along;
a. Learning resources;
b. Internet Access; and
c. Technological Literacy
d. Home Learning Space
3. What are the challenges of the respondents in Flexible Distance
Learning Modality in terms of:
a. Self-Regulation Challenges (SRC);
b. Technological Literacy and Competency Challenges (TLCC);
c. Student Isolation Challenges (SIC);
d. Technical Sufficiency Challenges (TSC);
e. Technological Complexity Challenges (TCC);
f.
Learning Resource Challenges (LRC); and
g. Learning Environment Challenges (LEC)
4. Is there a significant relationship between the students’ level of
preparedness and the challenges experienced with flexible distance
learning modality?
Objectives of the Study
This study aims to determine the preparedness and challenges of the
College of Education students of the Central Bicol State University of
Agriculture, Calabanga Campus to flexible distance learning modality.
4
Specifically, this research aims to seek an answer to the following
objectives:
1. Determine the profile of the college students of the Central Bicol State
University of Agriculture, Calabanga Campus, in terms of:
a. Student type;
b. Family income; and
c. Residence geographical location
2. Determine the level of preparedness of the college students to the
flexible distance learning modality along;
a. Learning resources;
b. Internet Access; and
c. Technological Literacy
d. Home Learning Space
3. Determine challenges of the respondents in Flexible Distance
Learning Modality along:
a. Self-Regulation Challenges (SRC);
b. Technological Literacy and Competency Challenges (TLCC);
c. Student Isolation Challenges (SIC);
d. Technical Sufficiency Challenges (TSC);
e. Technological Complexity Challenges (TCC);
f.
Learning Resource Challenges (LRC); and
g. Learning Environment Challenges (LEC)
5
4. To know if there is a significant relationship between the students’
level of preparedness and the challenges experienced with flexible
distance learning modality.
Assumptions of the Study
In conducting this study, the following assumptions were made. It is assumed
that:
1. The respondents are from high and low land rural areas and they may
belong to wealthy and average families.
2. Not all students have sufficient access to technologies and stable
internet connections for online learning.
3. Students that are new to Learning Management System may find the
user interface confusing and hard to navigate, and not all students are
equipped in utilizing ICT in learning.
4. Attitudes and study habits of the students are significant factors affecting
their performance.
5. During Flexible
Distance Learning,
students may suffer from
psychological challenges such as anxiety and stress.
6. Students' demographic profiles may influence their access to innovative
learning within the implementation of flexible distance learning
modalities.
Hypothesis of the Study
From the problem stated above, the following hypotheses were formulated:
6
H01: There is no significant relationship between students' level of
preparedness and students' challenges during flexible learning modality.
Significance of the Study
The results of the study will be a great help to the following:
Students. This study will help them come up with learning strategies that are
more advantageous to them. It will help them be more aware of the outcomes
of their study habits in this flexible distance learning modality.
Teachers. This study will provide interventions on effective and efficient
teaching strategies in a flexible distance learning modality. It will provide data
that will help teachers to assess the situation of students in this time of the
pandemic.
Parents. This study can help the parents to monitor and have a knowledge of
what a flexible learning modality is and how it affects the learning of students,
which will enable them to better understand their children and provide
appropriate assistance.
Administration/Academe. The study will provide essential data that could be
used to improve management practices on flexible distance learning modalities.
Curriculum and Policy Makers. The study will provide pertinent data that will
help them come up with better policies that are accessible and appropriate to
the students and teachers.
Stakeholders/Community Members. This study will help the community to
better understand the situation of the teachers and the learners in this time of
7
the pandemic. It will encourage them to provide financial and technical
resources to aid the challenges they experience.
Future Researchers. This study will provide background knowledge that they
can use as a basis to further explore concepts about flexible distance learning
modality.
Scope and Delimitation of the Study
This study focused on the Flexible Distance Learning Modality being
implemented in the Central Bicol State University of Agriculture, Calabanga as
a response to pursuing quality education amidst the COVID 19 pandemic. This
research determined the preparedness and challenges of the College of
Education students to flexible distance learning modality. It includes the profile
of the college students in terms of a) Student type; b.) Family income; and c.)
Residence geographical location, the level of preparedness of the college
students to the flexible distance learning modality along; a.) Learning
resources; b.) Internet Access; and c.) Technological Literacy and d.) Home
Learning Space. It also explored the challenges of the respondents in Flexible
Distance Learning Modality, in terms of a.) Self-Regulation Challenges
(SRC);b.) Technological Literacy and Competency Challenges (TLCC); c.)
Student Isolation Challenges (SIC); d.) Technical Sufficiency Challenges
(TSC); e.) Technological Complexity Challenges (TCC); f.) Learning Resource
Challenges (LRC), and g.) Learning Environment Challenges (LEC). It also
contained the demographic profiles related to their level of preparedness and
the challenges they experienced in a flexible distance learning modality.
Moreover, the respondents of this study is limited to the Third-Year College of
8
Education students, enrolled in CBSUA Calabanga, this academic year 20212022. Other year levels of the said college were not covered by this study since
there were group of researchers investigated them.
Locale of the Study
This research was conducted at Central Bicol State University of
Agriculture (CBSUA). It is a state university in the province of Camarines Sur,
Philippines. CBSUA is the regional center for higher education in agriculture in
the Bicol Region. It has four campuses located in Pili, Calabanga, Sipocot, and
Pasacao Camarines Sur. This study specifically implemented in CBSUACalabanga Campus. It presently has three colleges namely, College of
Education (COE), College of Arts and Sciences (CAS), and College of Industrial
Technology (CIT). The following courses are offered in the COE: Bachelor of
Secondary Education, Majors in English, Mathematics, and Filipino; and
Bachelor of Elementary Education, Major in Content Area. The CAS offers
courses such as Bachelor of Arts in English Language, Bachelor of Science in
Mathematics, and Bachelor of Science in Fisheries. In CIT, Bachelor of Science
in Industrial Technology is the course offered, with major field specializations in
Automotive, Electrical, Electronics, Hospitality Management, and Refrigeration
and Air Conditioning. CBSUA-Calabanga is headed by its campus
administrator Dr. Cornelio B. Funtanar. It has a total student population of 2498.
The students enrolled in this University are known for their unity and
competitiveness, they share and uphold respect, discipline, and care. The
researchers chose the area for the following essential considerations: it is one
of the Universities that adapted a Flexible Distance Learning Modality in the
9
New Normal, to know the preparedness and challenges experienced by the
College of Education students; and also for convenient mapping of the
respondents.
https://goo.gl/maps/hjPaGYoXbGHGmNp88
Figure 1: Geographical Map Location of CBSUA Calabanga Campus
Definition of Terms
For a better understanding of this study, the following terms were defined
in the context of this research.
Preparedness. Conceptually, preparedness refers to the ability of communities
and individuals to anticipate and respond effectively to the impact of likely,
imminent,
or
current
hazards,
events,
or
conditions
(HR-OCHA,
2013). Operationally, it is generally perceived as an ongoing process to achieve
and maintain readiness in coping with the new learning modalities.
10
Flexible Distance Learning Modality. Conceptually, it is a particular mode
that assists students’ preparedness in distance learning (Joan, 2020). In all
cases, there are two basic concepts in FDLM according to Sotiropoulos (2020):
asynchronous learning (where the two parts are not communicating in realtime); and synchronous learning (where the two parts communicate in realtime). Operationally, it is a method of learning where teachers and students do
not meet in a classroom but make use of the Internet, email, mail, etc., to have
classes. The students are given freedom in how, what, when, and where they
learn.
Challenges. Conceptually, it is the situation being faced with something that
needs great mental or physical, or financial effort to be done successfully (IGI
Global, 2018). In this study, challenges constitute the problems that students
are encountering while studying online, including cognitive, affective,
psychomotor, and technological problems, which affect their learning
negatively.
11
Notes
Central Bicol State University, Calabanga Campus. Retrieved from Google
Maps:
https://www.google.com/maps/place/Central+Bicol+State+University,+
Calabanga+Campus/@13.7177876,123.2298967,16z/data=!4m5!3m4!
1s0x33a1f193c774b611:0xd044188aee00c6b3!8m2!3d13.718332!4d1
23.2311492
CHED (2020). CHED COVID ADVISORY NO.6: Guidelines for the
Prevention, Control and Mitigation of the Spread of Coronavirus
Disease 2019 (COVID-19) in Higher Education Institutions (HEIs).
https://ched.gov.ph/wp-content/uploads/CHED-COVID-19-AdvisoryNo.-6.pdf
Dayagbil, F.T. et.al. (2021). Teaching and Learning Continuity Amid and
Beyond the Pandemic.
https://www.frontiersin.org/articles/10.3389/feduc.2021.678692/full
HR-OCHA (2013) Humanitarian Response-Preparedness
https://www.humanitarianresponse.info/en/coordination/preparedness/whatpreparedness
Joan, R. (2020). Flexible Learning. Retrieved from TOP HAT GLOSSARY:
https://files.eric.ed.gov/fulltext/EJ1098325.pdf
/https://tophat.com/glossary/f/flexible-learning/
Joaquin, J., Biana, H., & Dacela, M. (2020). The Philippine Higher Education
Sector in the Time of COVID- 19.
https://www.frontiersin.org/articles/10.3389/feduc.2020.576371/full?fbcli
d=IwAR2lwOrhGXGUXmn32qJ0AKWgOO0msSnYv1lZi1T1UFK07CJ5
HU-7Ez-98ho
Magsambol, B. (2020). FAST FACTS: CHED's flexible learning.
https://www.rappler.com/newsbreak/iq/things-to-know-ched-flexiblelearning
IGI Global (2018). Concept of Challenges: https://www.igiglobal.com/publish/
Sotiropoulos, D. I. (2020). Basic Concepts Distance Learning. Retrieved from
https://www.classter.com/2020/04/29/basic-concepts-of-distancelearning-and-how-to-introduce-it-to-your-educational-organization/
12
CHAPTER II
REVIEW OF RELATED LITERATURE AND STUDIES
This chapter begins with an overview of several literature and studies
pertaining to the Flexible Distance Learning Modality through the Lens of
College Education Students. The next section discusses the Theoretical
Framework and Paradigm, and the Conceptual Framework and Paradigm.
Finally, the chapter finishes on the synthesis of the State-of-the-art and Gap
bridged of this study.
A. Related Literature
The snap of the pandemic brought tremendous changes in the learning
delivery modalities of education. Higher Education Institution adapts these
learning modalities particularly the flexible distance learning mode as an
immediate response to the call of new normal education. Students are the most
affected by this pandemic crisis because their learning is put in compromise.
Thus, Higher Education restructured the educational system to continuously
provide the best service to all students. Enable to successfully implement the
flexible learning education, curricular and instructional adjustment have to be
done by the institution, and the adjustment needs to be supported by the
academic policies and support systems. On the other hand, the existing
academic policies need to be reviewed, revised, or totally changed if necessary
(Pawilen, 2021).
In the Philippines, there are SUCs that allocated learning and support
partner providers to help the students learn effectively amidst flexible distance
learning. The recent study by Nadiahan and Cabauatan (2021) has presented
13
the status of learners’ support in the college of education of a state university in
the Cordillera-Philippines. The study revealed that Information support, Learner
Intake support, Technological support, Instructional Support, and Guidance and
Counselling support were accessible to both teachers and students in the
College of Education department. It is evident that the College of Education and
the support providers effectively delivered the learning in new modalities by the
support and resources given to students. There are really higher education
institutions in the country where implementing flexible learning was running in a
smooth operation. The recent study of Barrera et al. (2020) shows that the
students and teachers of Saint Michael College of Caraga are ready for flexible
learning, the majority of the respondents have technical requirements for online
learning: smartphones, laptops, and stable internet connection through mobile
data and Wi-Fi.
On the other hand, not all areas in the Philippines have equal access to
stable internet connectivity, the location of the students should consider the
flexible learning approach. The research study by Laguador (2021) has
identified the different challenges encountered among college students living in
urban, rural, and suburban areas in the Philippines during flexible learning. The
result of the study showed that students who reside in rural settings have
significantly higher problems in electricity power interruption and lack of
technical skills in operating technology. While students in rural areas have
encountered higher challenges in resources and communication and students
living in the suburban area usually faced difficulties in terms of the environment.
Despite the challenges entailed in flexible distance learning, Filipino
learners never see it as a hindrance to losing their opportunities to learn.
14
Education was highly valued by the Filipino learners, being tactful and
resourceful are their weapons to survive. The study of Rotas and Cahapay
(2020) has emphasized the coping strategies of Filipino students in remote
learning amid the COVID-19 pandemic. When students encounter poor internet
connection they look for a good space and time to gain a higher broadband
connection; when they have a lack of technological equipment they tend to
borrow learning resources from relatives or, seeking support from peers; when
they need guidance and help for their studies they approach the teachers; when
accomplishing their task they are practicing time management whether doing
learning tasks ahead or extending the time; doing leisure activities and diverting
attention can help to reduce their stress; regulating their self will help them to
lessen the burden and high expectation; taking an extra job to raise money for
their financial needs, and crying and praying to ease their emotional
breakdowns.
The occurrence of the COVID19 pandemic forces both teachers and
learners to do distance learning through online and embrace the new mode of
delivering lessons and instruction. Crawford (2021) introduces the Faculty
Collaborative Support where the steps done by teachers to continuously deliver
lessons to students are identified. The learning management system was
modified into synchronous and asynchronous learning, adjustment of
instructional materials, and providing socio-economic support. The shift from
conventional to distance learning reveals the problems with connectivity and
technology. On contrary, according to Dennis et al. (2020) flexibility in higher
education is not a novel practice anymore even before the pandemic occurs. In
fact, the number of enrollees under flexible distance learning in the US is
15
increasing. Flexible Learning is defined as a mode of learning designed based
on students' flexibility and preference. In addition, technological-enhance
learning is always associated with this mode of learning since technology and
the internet serve as a medium of transferring the lesson and instruction. Thus,
conducting flexible learning requires technological devices, knowledge, and
skill in operating technology, evaluating information, and exploring various
media and software. Sinecen (2018) identified advantages and opportunities of
flexible distance learning to students. First, students develop self-discipline as
they need to work independently, self-study, manage their own time, organize
their lessons and activities, and be self-motivated. Second, distance learning
provides flexibility for students who have other responsibilities, where they can
take time to plan and arrange their studies based on their available time. Third,
it enhances their attitude and skills in using technology and appreciates its
usefulness and accessibility. Lastly, for practical reasons distance learning
helps lessen the money needed to study because it is financially affordable.
However, Daniela & Visvisi (2021) pointed out challenges that students
face in flexible distance learning. Internet connection is the primary problem
that is being observed by students that lower their performance and
participation in class. Also, this mode of learning reveals that marginalized
students such as those living afar and economically insufficient are being left
behind. Flexible distance learning can be an effective alternative to traditional
learning but is impossible to overlook students who can’t afford to purchase
needed gadgets and face other situational barriers.
Despite these challenges, Gleason (2018) asserts that the world is now
in a period called “Industry 4.0” where advanced technologies are not merely
16
for massive and advanced production but particularly with enhancing advanced
knowledge. Living in this phase of time, people need to be used to automation
and technological base practices. In education distance learning, conducting
lessons, delivering instruction, performances, and assessments that are
technology base must be normalized. He also highlights the role of higher
education as a nurturer and educator of relevant knowledge and skills that will
be able to meet the demand of changing society. Developing strategies to
continuously cater relevant knowledge and skills despite difficulties, results in
achieving students’ lifelong learning and success.
B. Related Studies
According to Cortes (2020), in the study which aims to explore the
potentialities of flexible learning as an intervention in the current education crisis
through the perceptions of students and their environmental attitude,
participated by a second-year environmental science class composed of 32
students in a state university in Central Visayas, Philippines. The researcher
found out that the perceptions of the students on flexible learning pertain to the
six factors evaluated by Distance Education Learning Environments Survey
(DELES)
scale,
namely:
instructor
support,
student
interaction
and
collaboration, personal relevance, authentic learning, active learning, and
student autonomy. The researcher concluded that flexible learning setting in
environmental science courses promotes authentic learning, active learning,
and student autonomy. Meanwhile, perceptions of whether this instructional
modality is effective in terms of instructor support, student interaction and
collaboration, and promoting personal relevance were dispersed. In other
17
words, future studies may take into account how to further develop or promote
these factors in an FL setting.
In terms of the readiness of Filipino Higher Education Students for elearning from the University of the Philippines Los Baños, Reyes, et.al. (2021)
investigated the level of e-learning readiness among Filipino students in higher
education during the pandemic in terms of five dimensions: computer/internet
self-efficacy, self-directed learning, learner control, motivation for learning, and
online communication self-efficacy. It also confirmed significant differences in
readiness based on gender and program classification. The researcher
assessed that student readiness for e-learning is a multidimensional metric that
is consistent with many claims. Filipino students are ready in terms of
computer/internet self-efficacy; however, they are not ready in terms of learner
control. The differential item functioning (DIF) analysis showed that gender
significantly differentiates e-learning readiness under learner control and selfdirected learning. This means that the learning environment and controlling
learning progress are areas in which the students are not ready. Sources of
distraction such as social media, house chores, family duties, and work
responsibilities pull the learner’s focus away from his/her academic tasks,
resulting in loss of productivity.
The challenges faced by students in HEIs are not just limited to the
dimensions of learner control and self-directed learning. According to Rotas and
Cahapay (2020), the sudden migration of education from traditional on-campus
learning to remote learning has put students at a great disadvantage. While
universities already had great successes in establishing online learning
systems for their students, it has been recognized that this transition to a new
18
educational paradigm for most universities has not been properly organized. In
addition, Joaquin et al. (2020) state that there are gaps and challenges in the
educational alternative learning modes and technologies used by Philippine
HEIs. Specifically, the result of the content analysis revealed the following
categories of difficulties in remote learning: unstable internet connectivity;
inadequate learning resources; electric power interruptions; vague learning
contents; overloaded lesson activities; limited teacher scaffolds; poor peer
communication; conflict with home responsibilities; poor learning environment;
financial related problems; physical health compromises; and mental health
struggles.
In another study, Gocotano et al. (2021) learned that most students use
mobile phones and mobile data as their primary internet source, having
moderate to poor connection. The respondents of their study experienced the
unavailability of a network, economic instability, digital divide, the shortage of
digital devices, distractive learning environment, expensive internet data,
health-related problems, lack of resources, lack of digital literacy skills, and loss
of motivation. The researchers concluded that even if flexible online learning is
the best solution for the university still, it is not applicable and suitable to
students in rural areas. In light of these concerns, although e-learning is
centered on students, teachers play an important role in achieving course
learning goals. The study guides should include a detailed schedule of activities
for the entire semester so that the students will be able to manage their time
well. The course design should uphold the principles of empathy, understanding
each learner’s situation and differences as shown in the DIF results, and
inclusivity by considering the learner’s needs. Since students find it hard to
19
sustain their motivation for learning, teachers should find ways to pique the
interest of students through various resources such as videos, podcasts, online
games, and illustrations, which will suit the students’ profiles. It is also important
to include learning activities that will promote opportunities to work with their
peers.
In education, the impact of this pandemic is in the form of closure of
schools and universities and has reshaped education by shifting from face-toface to fully online learning. Although online learning is no longer a new norm
of instruction in higher education, previous reports reveal several challenges.
In connection with this, Amir et al. (2020), examined the differences of
readiness for online learning between freshmen and senior college students
and found significant differences existed between freshmen and senior
students in their preference on distance learning - with freshmen being
significantly preferred the said learning method than seniors. Therefore, it is
advisable that students should be taught basic ICT skills, time management,
and self-directed abilities at a younger age to better prepare them for online
learning environments. In the same manner, Ali (2020) states that student
accessibility, staff readiness, confidence, resources, and motivation impact ICT
integrated learning. The researcher proposes that staff members must learn
more about the use of technology to fulfill this mode of learning. Elfirdoussi et
al. (2020) discovered that Moroccan university professors and students found
online learning during COVID 19 pandemic as not more interesting as ordinary
learning and therefore professors must provide 50% of a face-to-face mode of
classes. The respondents of their study recommended that technical support
and training in using online tools for the enhancement of distance education
20
must be realized. In flexible distance learning, teachers and students suffer
from challenges of the Learning Management System. According to Aikina and
Bolsunovskaya (2020), for teachers, the main demotivating factors are
additional workload, technical problems, plagiarism in students’ works, and
difficulty in identifying the actual user in the assessment of knowledge. While
technical problems, set deadlines, misprints in the tests, and incorrect
automatic evaluation, as demotivating factors for the students. In addition,
Morze et al. (2021) also elaborate that it requires plenty of time for
implementation compared to traditional learning, and adaptive technologies
can't solve the problem of knowledge usage in real-life situations or students’
specialization.
Aside from technological challenges, personality types may influence
student preference for flexible distance learning. According to Wandler and
Imbriale (2017), one's personality influences how one perceive, judge, and
behave in specific situations. Students' adoption of online learning is frequently
linked to their ability to self-regulate. The ability to create goals, effective time
management, problem-solving aptitude, and knowledge of when to seek
guidance from instructors are all examples of self-regulatory behavior which
may strengthen the flexible distance learning preference. An exploration of
factors influencing learner self-efficacy in flexible distance learning was
revealed by Talosa, Javier, and Dirain (2021). According to their study, selfefficacy is the key to success in all activities, including flexible distance learning.
As a result, in a flexible learning situation, knowing the source of self-efficacy
is critical. As found in their investigation, learner self-efficacy in the flexible
distance learning setting is influenced by factors such as personal-related
21
factors, communication and interaction, motivation, technologically-related
characteristics, teacher factors, and home environment factors. Amid the
challenges of this new normal education, there is still an opportunity to further
explore alternative ways of learning (Dabalos and Gameng,2021).
Theoretical Framework
This study is anchored on three theories which are the Technology
Acceptance Model, Self-Determination Theory, and Online Collaborative
Learning theory. These theories were used as the guiding principles in studying
the level of preparedness and challenges on Flexible Learning of Education
students of Third-Year BSEd English Students at Central Bicol State University
of Agriculture – Calabanga Campus.
Since students live in the modern era, where anything is almost possible
with the help of technology, learning can be easy and deceiving. In addition,
technology also offers students a wide array of tools like software applications
that helps elevate their academic performance. The Technology Acceptance
Model (Davis, 1989) is a theory of information systems that explains how
students access, accept and use technology to their advantage. Davis further
stated that two factors influence whether a computer system is accepted by its
potential users: (1) perceived usefulness and (2) perceived ease of use. The
emphasis on the potential user's perceptions is a fundamental component of
this model. As a consequence, even if the majority of individuals believe the
product is valuable and user-friendly, it will not be accepted by its potential
consumers unless such opinions are shared.
22
The second theory is the self-determination theory (SDT) by Edward
Deci and Richard Ryan. According to research on Self-Determination Theory,
intrinsic motivation (doing something because it is inherently interesting or
enjoyable), and thus higher quality learning, thrives in contexts that meet
human needs for competence, autonomy, and relatedness. When students are
pushed and receive timely feedback, they feel competent. When students feel
empowered to explore, take initiative, develop, and apply answers to their
challenges, they experience autonomy. When students perceive people
listening and responding to them, they feel connected. Students are more
intrinsically motivated and actively engaged in their learning when these three
criteria are addressed. Numerous studies have revealed that students who are
more active in the process of setting educational goals are more likely to
achieve them. When students believe that the major goal of learning is to
acquire external benefits, such as a good score on an exam, they often perform
poorly, believe they are less competent and report more anxiety than when they
believe exams are just a tool to track their own progress. External rewards have
been shown in certain studies to decrease motivation for an activity that the
student was initially motivated about. In a review of 128 studies on the influence
of external rewards on intrinsic motivations published in 1999, Drs. Deci and
Ryan, working with psychologist Richard Koestner, Ph.D., concluded that such
rewards have a significant detrimental impact on intrinsic motivation because
they undermine people's ability to motivate or regulate themselves.
Linda Harasim (2012) proposed Online Collaborative Learning (OCL) as
a theory that focuses on the capabilities of the Internet to offer learning
environments that stimulate collaboration and knowledge acquisition. Harasim
23
also describes OCL as a new theory of learning that focuses on collaborative
learning, knowledge building, and Internet use as a way to reshape formal, nonformal, and informal education for the “Knowledge Age”. This theory explains
the moving of teaching and learning to the Internet and large-scale networked
education, not just as an alternative option in times of crisis, but a potent option
in integrating the modern systems for innovative and continuous education.
OCL is also influenced by social constructivism, since students are encouraged
to address issues collectively through discourse, and the teacher serves as
both a facilitator and a part of the learning community.
Theoretical Paradigm
Figure 2: Theoretical Paradigm
24
Conceptual Framework
Figure 3 below describes the conceptual framework of the study
wherein the expected input from the respondents consist of the following:
Student's Profile (Student type, Family income, and Residence Geographical
Location), Student's Level of Preparedness, and the Challenges faced by the
students. Moreover, the process is based on a descriptive-correlated approach
utilizing a survey questionnaire as the major data-gathering tool. The analysis
involves tabulating, depicting, and describing the collected data through the use
of percentage technique and weighted mean; while Pearson R was used to
determine if there is a significant relationship between the concerned variables
of the study. Hence, the output was the gathered data of college students'
preparedness and challenges on flexible learning modality together with the
student's insights on flexible learning modality.
Conceptual Paradigm
Figure 3: Conceptual Paradigm
25
Synthesis of the State-of-the-Art
As the pandemic globally prompts changes in education, the Higher
Education Institution in the local setting adapts new learning modalities
particularly the flexible distance learning mode as an immediate response to
the call of new normal education. Several literature and studies were reviewed
to further understand and investigate the effect and readiness for the adaptation
of the new learning modalities.
According to Dennis et al. (2020), flexibility in higher education is not a
novel practice anymore even before the pandemic occurs. Thus, conducting
flexible learning requires technological devices, knowledge, and skill in
operating technology, evaluating information, and exploring various media and
software. Gleason (2018) asserts that the world is now in a period called
“industry 4.0” where advanced technologies are not merely for massive and
advanced production but particularly with enhancing advanced knowledge. In
connection with this, Sincecen (2018) identified advantages and opportunities
of flexible distance learning to students, such as the development of selfdiscipline, it provides flexibility for students, it enhances their attitude and skills
in using technology and appreciates its usefulness and accessibility, and it
lessens the money needed to study for practical purposes. Moreover, Barrera
et al. (2020) showed in their study that the students and teachers of Saint
Michael College of Caraga are ready for flexible learning, the majority of the
respondents have technical requirements for online learning: smartphones,
laptops, and stable internet connection through mobile data and Wi-Fi. In the
recent study by Nadiahan and Cabauatan (2021), the College of Education and
the support providers were effectively delivered the learning in new modalities
by the support and resources given to students.
However, several works of literature and studies also revealed that the
students encountered different challenges and difficulties. According to Rotas
and Cahapay (2020), the sudden migration of education from traditional oncampus learning to remote learning has put students at a great disadvantage.
Reyes, et.al. (2021) investigated the level of e-learning readiness and
confirmed significant differences in readiness based on gender and program
26
classification while Joaquin et al. (2020) presented the categories of difficulties
in remote learning from the result of the content analysis of the study. In
addition, the result of the research study by Laguador (2021) showed that
students who reside in a rural setting have significantly higher problems in
electricity power interruption and lack of technical skills in operating technology.
This was supported by the study of Gocotano et al. (2021) which concluded
that even if flexible online learning is the best solution for universities, it is not
applicable and suitable to students in rural areas.
Furthermore, Crawford (2021) introduces the faculty Collaborative
Support where the steps done by teachers to continuously deliver lessons to
students are identified, where the learning management system was modified
into synchronous and asynchronous learning, adjustment of instructional
materials, and providing socio-economic support. According to Wandler and
Imbriale (2017), one’s personality influences how one perceive, judge, and
behave in specific situations. Similarly, in the study of Talosa, Javier, and Dirain
(2021) self-efficacy is the key to success in all activities, including flexible
distance learning. As a whole, the foregoing literature and studies were
supportive of the variables used in this study, which are the preparedness and
challenges of College of Education students.
Gap Bridged by the Study
In the review of related literature and studies, it was observed that most
of the researches focused mainly on the preparedness of the students for the
flexible distance learning modality. There were studies reviewed that also
discusses the challenges that the students encountered during this new normal
education. However, there were no general studies regarding the relationship
between the preparedness of the students and the challenges encountered.
Therefore, this study was conducted to identify the level of preparedness as
well as determine the challenges faced by the college education students with
this flexible distance learning modality. Most of all, this study investigated the
relationship between the students preparedness and challenges experienced.
27
Notes
Aikina, T., Bolsunovskaya, L. (2020). Moodle-Based Learning: Motivating and
Demotivating Factors. International Journal of Emerging Technologies
in Learning (iJET), 15(2), 239-248. https://research.moodle.org/483/
Amir, L. R., Tanti, I., Maharani, D. A., Wimardhani, Y. S., Julia, V., Sulijaya,
B., & Puspitawati, R. (2020). Student perspective of classroom and
distance learning during COVID-19 pandemic in the undergraduate
dental study program Universitas Indonesia. BMC medical education,
20(1), 1-8. https://bmcmededuc.biomedcentral.com/articles/10.1186/
Barrera,K. ,Arcilla,F., & Jaminal, B. (2020). Readiness for Flexible Learning
amidst COVID-19 Pandemic of Saint Michael College of Caraga,
Philippines. SMCC Teacher Education Journal.11-12.
Cortes, S.T. (2020). Flexible Learning as an Instructional Modality in
Environmental Science Course during COVID-19.
https://www.aquademia-journal.com/download/flexible-learning-as-aninstructional-modality-in-environmental-science-course-during-covid19-8444.pdf
Crawford, C.M. (2021). Shifting to Online Learning Through Faculty
Collaborative Support. IGT Global.
https://www.semanticscholar.org/paper/Shifting-to-Online-LearningThrough-Faculty-Support-FragaHall/089e8d7acfb6d472273ce09c21233fd30ab74740
Daniela, L., & Visvizi, A. (2021). Remote Learning in Times of Pandemic.
Routhledge. doi: 10.4324/9781003167594.
https://www.routledge.com/Remote-Learning-in-Times-of-PandemicIssues-Implications-and-Best-Practice/DanielaVisvizi/p/book/9780367765705
Dennis, C., Abbott, S., Matehson, R., & Tangney, S. (Eds.). (2020), Flexibility
and Pedagogy in Higher Education: Delivering Flexibility in Learning
through Online Learning Communities. Brill Sense.
Gleason, N. (2018). Higher Education in the Era of the Fourth Industrial
Revolution. Palgrave MacMillan.
https://link.springer.com/content/pdf/10.1007%2F978-981-13-01940.pdf
Elfirdoussi, S., Lachgar, M., Kabaili, H., Rochdi, A., Goujdami, D., & El
Firdoussi, L. (2020). Assessing Distance Learning in Higher Education
during the COVID-19 Pandemic. Education Research
International, 2020, 1-13. doi: 10.1155/2020/8890633
Laguador, J. (2021). Challenges Encountered during Pandemic in Flexible
Learning Among College Students Living in Urban, Rural, and
28
Suburban Areas in the Philippines. Asia Pacific Journal of Educational
Perspectives,8(1),10-16.
Mahmut, S. (Ed.). (2018). Trends in E- learning. Intech Open.
doi.org/10.5772/intechopen.71183
Morze, N., Varchenko-Trotsenko, L., Terletska, T., & Smyrnova-Trybulska, E.
(2021, March). Implementation of adaptive learning at higher education
institutions by means of Moodle LMS. In Journal of Physics:
Conference Series (Vol. 1840, No. 1, p. 012062). IOP Publishing.
https://iopscience.iop.org/article/10.1088/1742-6596/1840/1/012062/pdf
Nadiahan, M., & Cabauatan, L. (2021). Status of learners’ support in the
college of education of a state university in the Cordillera-Philippines
during the COVID-19 pandemic. International Journal of Curriculum
and Instruction,13(3),1-26. ijci.wcci-international.org
Pawilen, G. (2021). Preparing Philippine higher education institutions for
flexible learning during the period of COVID-19 pandemic: Curricular
and instructional adjustments, challenges,
and issues.
International Journal of Curriculum and Instruction,13(3) ,2150–2166.
ijci.wcci-international.org
Picciano, A. G. (2017). Theories and frameworks for online education:
Seeking an integrated model. Online Learning, 21(3), 166-190.
Reyes, J.S., Grajo, J., Comia, L.N., Talento, M., Ebal, L.A. & Mendoza, J.O.
(2021). Assessment of Filipino Higher Education Students’ Readiness
for e-Learning During a Pandemic: A Rasch Technique Application.
Philippine Journal of Science.
Rotas, E.E. & Cahapay, M.B. (2020). Difficulties in Remote Learning: Voices
of Philippine University Students in the Wake of COVID-19 Crisis.
Asian Journal of Distance Learning Education.
https://files.eric.ed.gov/fulltext/EJ1285295.pdf
Rotas,E.,& Cahapay,M.(2021).From stress to success: Exploring how Filipino
students cope with remote learning amid COVID-19 pandemic.
Journal of Pedagogical Sociology and Psychology,3(1),32-33.
http://www.doi.org./10.33903/JPSP.2021366608
Talosa, A. D., Javier, B. S., & Dirain, E. L. (2021). The flexible-learning
journey: phenomenological investigation of self-efficacy influencing
factors among higher education students. Linguistics and Culture
Review, 5(S3), 422-434. 422-434.
https://doi.org/10.37028/lingcure.v5nS3.1590
Wandler, J. B., & Imbriale, W. J. (2017). Promoting undergraduate student
self-regulation in online learning environments. Online Learning.
https://files.eric.ed.gov/fulltext/EJ1149360.pdf
29
CHAPTER III
RESEARCH DESIGN AND METHODOLOGY
Research Design
A descriptive-correlated study design was adopted utilizing the survey
questionnaires among the Third-Year Bachelor of Secondary Education Major
in English students of CBSUA Calabanga Campus. This design was used to
estimate the extent to which different variables are related to each other. This
type of descriptive design usually answers the question of whether there exists
a significant relationship between independent and dependent variables. In this
study, it sought to measure the level of preparedness and identify the common
challenges of the respondents in the Flexible Learning Modality.
Respondents of the Study
The respondents of the study were Third-year students taking Bachelor
of Secondary Education in English at Central Bicol State University of
Agriculture-Calabanga Campus during the academic year 2021-2022. The
population of the study comprised of 58 respondents which include 15 male
and 43 female students. The sampling technique used is a total enumeration,
where all members of the whole population are considered and measured. Total
enumeration is a total population sampling which is a type of purposive
sampling where the whole population of interest (i.e., a group whose members
all share a given characteristic) is studied. It is most practical when the total
population is of manageable sizes, such as a well-defined subgroup of a larger
30
population. Thus, this enables the researchers to obtain research results with
hundred percent validity and accuracy.
Gender
Frequency
Percentage
Male
15
25.9%
Female
43
74.1%
Total
58
100%
Table 1: Distribution of Respondents
Data Gathering Procedure
Descriptive statistics allows the researchers to summarize the collected
data among the respondents using measures that are easily understood by an
observer or a reader. The purpose of summarizing the data is not only to
describe them as concisely as possible but also to enable one to make
comparisons between populations. Since the design used was a descriptivecorrelated study, after condensing the data, it proceeded to hypothesis testing
for establishing relationships among variables.
To gather the data, the following procedures were undertaken. The
researchers adopted a survey tool for the study from the other researchers to
ensure reliability and validity. The researchers wrote a letter for permission on
the use of survey tools. Next, the researchers evaluated and finalized the
survey tool. The researchers made the survey questionnaire through the use of
Google Form. The questionnaire was distributed to the respondents
concurrently online via messenger or email address. The confidentiality of any
information of the respondents in the study would be highly ensured. The
31
researchers classified the information gathered from the respondents in a tally
sheet and the responses were tabulated into graphical presentations of data.
Research Instruments
To gather the needed information, the data gathering tool consists of
three-part questionnaires. For part 1, the Survey Instrument used a checklist
type on the socio-demographic profile of the respondents which classified
the student location, family income, and geographical location. For part 2,
the researchers utilized their own structured questionnaire for the data
gathering on the level of preparedness of the students in flexible learning; it
specifically measures the availability of gadgets, access to the internet
connection, technical skills, and available home learning space. The scale
indicators implied a 5-point scale ranging from “Highly Prepared” (5), to
“Poorly Prepared” (1). The third part covers 7 sub-categories to determine
the common challenges faced in flexible learning of students, those were
measures based on the following: Self-Regulation Challenges (SRC),
Technological Literacy and Competency Challenges (TLCC), Student
Isolation Challenges (SIC), Technological Sufficiency Challenges (TSC),
Technological
Complexity
Challenges
(TCC),
Learning
Resource
Challenges (LRC), and Learning Environment Challenges (LEC). It was
adopted from a research study, which implied a 5-point scale ranging from
“Always (5) to Never (1).
Statistical Treatment of Data
The researchers used descriptive statistics to analyze, describe and
summarize the data using statistics. It involves tabulating, depicting, and
32
describing the collected data. Furthermore, percentage and mean, and
Pearson R were utilized.
Healey (2010) stated that percentage and proportion provide a frame of
reference for reporting research results by standardizing the raw data, that is,
percentage to the base 1.00. and proportion to the base 1.00. Mean is the
average or the most common value in a collection of numbers. In statistics, it is
a measure of the central tendency of a probability distribution along median and
mode. The Pearson R was also applied to determine the significant relationship
between the level of preparedness and challenges of the respondents in a
flexible learning modality.
Frequency and Percentage were used to determine the distribution of
the respondents according to their socio-demographic profile.
The formula for percentage is:
𝑓
% = 𝑁 (100)
Where:
% = percentage
f = frequency
N = number of cases
Weighted Mean was used to determine the preparedness and the
challenges of the respondents in the flexible distance learning modality. The
following are the Likert response scale used:
Likert Scale with Four anchors for the interpretation of the problem
number 2. The following options were allotted with corresponding weights such
that:
33
WEIGHTS
INTERPRETATION
3.50-4.00
Highly Prepared
2.50-3.49
Moderately Prepared
1.50-2.49
Fairly Prepared
1.0-1.49
Poorly Prepared
Table 2: Four Anchors for the Likert Response Scale
Likert Scale with Five anchors for the interpretation of the problem no. 3.
The following options were allotted with corresponding weights such that:
WEIGHTS
INTERPRETATION
4.21-5.0
Always
3.41-4.2
Often
2.61-3.4
Sometimes
1.81-2.6
Rarely
1.0-1.8
Never
Table 3: Five Anchors for the Likert Response Scale
The formula for weighted mean is:
Where:
X
𝑤
X
𝑤
=
𝛴𝑓𝑔𝑟𝑜𝑢𝑝 𝑥 𝑁𝑔𝑟𝑜𝑢𝑝
𝑁𝑡𝑜𝑡𝑎𝑙
= weighted mean
𝛴𝑓𝑔𝑟𝑜𝑢𝑝 = frequency in a particular scale/group
𝑁𝑔𝑟𝑜𝑢𝑝 = number of particular scale/group
𝑁𝑡𝑜𝑡𝑎𝑙
= total number of frequency in all groups
34
Pearson correlation coefficient was used to determine the relationship
between the level of preparedness and common challenges of the respondents
in the flexible distance learning modality. Below is the formula for the Pearson
correlation coefficient:
𝑟=
𝑠𝑝
df= N-2
√(𝑆𝑆𝑥)(𝑆𝑆𝑦)
Where:
Where:
SP= Sum of Products
df= degrees of freedom
SSx= Sum of the square of x
N= Number of respondents
SSy= Sum of the square of y
35
CHAPTER IV
PRESENTATION, ANALYSIS, AND INTERPRETATION OF DATA
This chapter presents the discussion of the gathered information and on
how the researchers analyzed and interpreted the different responses of the
respondents. It includes the demographic profile, preparedness, and
challenges experienced by the students in the Flexible Distance Learning
Modality. The researchers conducted an online survey wherein the problems
stated in Chapter One were answered.
I.
Student Profile
Tables 4, 5, and 6 presents the demographic profile of the college
students of Central Bicol State University, Calabanga Campus.
The
profile of the respondents was tabulated and computed according to the
following: student type, type of business, and residence geographical
location.
a. Student Type
Student type
Frequency
Percentage
Working Student
7
12.1%
Non-Working student
51
87.9%
Total
58
100%
Table 4: Student Type
In terms of student type, it shows that out of fifty-eight (58) respondents
there are 51 or 87.9% non-working students and 7 or 12.1% are working
36
students. It can be observed that the highest number of respondents are nonworking students.
The Non-Working student has the most among the students' types. This
may be attributed to the reason that majority of the students still rely on their
parents or guardians financially. The student’s type, family income, and
residence geographical location are the unseen external factor of a student’s
performance. This is because flexible learning requires time, focus, gadgets,
and a conducive learning environment.
b. Family Income
Average monthly family income
Frequency
Percentage
Less than ₱10,957
44
75.9%
Between ₱10,957 to ₱21,914
9
15.5%
At least ₱219,140 and up
2
3.4%
Between ₱21,914 to ₱43,828
2
3.4%
Between ₱131,484 to ₱219,140
1
1.7%
58
100%
Total
Table 5: Family Income
In terms of family income, it shows the average monthly income of the
respondent’s family. Out of fifty-eight (58) respondents, there are 44 or 75.9%
whose family income is less than ₱10,957. There are 9 or 15.5% whose family
income is between ₱10,957 to ₱21,914. There are 2 or 3.4% whose family
income is at Between ₱21,914 to ₱43,828. There are 2 or 3.4% whose family
income is at least ₱219,140 and up. And 1 or 1.7% whose family income is
between ₱131,484 to ₱219,140. It can be seen that most of the respondents
37
belong to a family that has an income of less than ₱10,957. The availability of
gadgets to use and financial needs to sustain the new modality are the burdens
faced by the students. Students who belong to families which are financially
unstable find it hard to attend online classes which require gadgets and internet
that are not affordable for them.
c. Residence’s Geographical Location
Residence’s Geographical Location
Frequency
Percentage
Upland
23
39.7%
Lowland
21
36.2%
Coastal
14
24.1%
58
100%
Total
Table 6. Residence’s Geographical Location
In terms of residence’s geographical location, it shows that out of fiftyeight (58) respondents there are 23 or equivalent of 39.7% that resides in the
upland, 21 or equivalent of 36.9% resides in the lowland, and 14 or equivalent
of 24.1% resides in the coastal area. It shows that there are greater
respondents in the upland, followed by the lowland, and the coastal.
This confirms the study of Laguador (2021) that has identified the
different challenges encountered among college students living in urban, rural,
and suburban areas in the Philippines during flexible learning. The result of the
study showed that students who reside in a rural setting have a significantly
higher problem in electricity, power interruption, and lack of technical skills in
operating technology. While students in rural areas have encountered higher
challenges in resources and communication and students living in the suburban
38
area usually faced difficulties in terms of the environment. Flexible learning
includes online classes which need internet that is most of the time unstable in
lowland and coastal areas. Power interruption is the struggle of those who
reside on the upland whenever there are online classes.
II.
Level of Preparedness in Flexible Distance Learning Modality
This part of the study presents the level of preparedness of the respondents
in Flexible Distance Learning Modality in terms of Learning Resources, Internet
Access, Technological Literacy, and Home Learning Space.
Learning Resources
𝑵𝒈𝒓𝒐𝒖𝒑
𝜮𝒇𝒈𝒓𝒐𝒖𝒑
𝜮𝒇𝒈𝒓𝒐𝒖𝒑 ˟
𝑵𝒈𝒓𝒐𝒖𝒑
Weighted
Mean
Highly Prepared
4
2
8
0.13
Moderately
Prepared
3
31
93
1.60
Fairly Prepared
2
22
44
0.75
Poorly Prepared
1
3
3
0.05
58
148
2.53
Interpretation
Total
Table 7: Level of Preparedness of the Respondents in Learning Resources
The table shows that the total weighted mean of the respondents’
preparedness in the availability of learning resources is 2.53 that is interpreted
as moderately prepared. The respondents have some available learning
resources like a laptop and smartphone necessary to support synchronous and
asynchronous classes.
39
Internet Access
𝑵𝒈𝒓𝒐𝒖𝒑
𝜮𝒇𝒈𝒓𝒐𝒖𝒑
𝜮𝒇𝒈𝒓𝒐𝒖𝒑 ˟
𝑵𝒈𝒓𝒐𝒖𝒑
Weighted
Mean
Highly Prepared
4
1
4
0.06
Moderately
Prepared
3
20
60
1.03
Fairly Prepared
2
28
56
0.96
Poorly Prepared
1
9
9
0.15
58
129
2.2
Interpretation
Total
Table 8: Level of Preparedness of the Respondents in Internet Access
It can be seen in the table that 2.2 is the total weighted mean of the
respondents’ level of preparedness which is interpreted as fairly prepared. The
respondents have moderate access to the internet through Cellular data only,
which somehow provides them the stability required to sustain synchronous
and asynchronous classes.
Technological Literacy
𝑵𝒈𝒓𝒐𝒖𝒑
𝜮𝒇𝒈𝒓𝒐𝒖𝒑
𝜮𝒇𝒈𝒓𝒐𝒖𝒑 ˟
𝑵𝒈𝒓𝒐𝒖𝒑
Weighted
Mean
Highly Prepared
4
2
8
0.13
Moderately
Prepared
3
36
108
1.86
Fairly Prepared
2
19
38
0.65
Poorly Prepared
1
1
1
0.01
58
155
2.65
Interpretation
Total
Table 9: Level of Preparedness of the Respondents in Technological Literacy
40
The table indicates the level of preparedness of the respondents in terms
of technical literacy. It can be seen in the table that the respondents have a total
weighted mean of 2.65 as their level of preparedness in technical skills that are
interpreted as moderately prepared. The respondents have good technical
skills and competence needed to navigate a virtual classroom, comply with
performance activities, and other related tasks.
Home Learning Space
𝑵𝒈𝒓𝒐𝒖𝒑
𝜮𝒇𝒈𝒓𝒐𝒖𝒑
𝜮𝒇𝒈𝒓𝒐𝒖𝒑 ˟
𝑵𝒈𝒓𝒐𝒖𝒑
Weighted
Mean
Highly Prepared
4
2
8
0.13
Moderately
Prepared
3
24
72
1.24
Fairly Prepared
2
26
52
0.89
Poorly Prepared
1
6
6
0.10
58
138
2.36
Interpretation
Total
Table 10: Level of Preparedness of the respondents in Home Learning Space
The table shows that 2.36 is the total weighted mean of the respondents’
level of preparedness in-home learning space that is interpreted as fairly
prepared, in which the respondents somehow have a good learning
environment. However, they do not have a study area at home that is why they
are usually distracted.
Overall Preparedness
Category
Weighted
Mean
𝜮𝒇𝒈𝒓𝒐𝒖𝒑 ˟
𝑵𝒈𝒓𝒐𝒖𝒑
41
Interpretation
Availability of
Learning
Resources
148
2.53
Moderately
Prepared
Access to Internet
129
2.2
Fairly Prepared
Technical Skills
155
2.65
Moderately
Prepared
Home Learning
Space
138
2.36
Fairly Prepared
Total
570
2.43
Fairly Prepared
Table 11: Respondents’ Level of Preparedness
The overall preparedness of the respondents in Flexible Distance
Learning Modality is evident in the table. The respondents are moderately
prepared in the availability of learning resources and technical skills. Thus, they
are fairly prepared in terms of Internet Access and Home Learning Space. The
total weighted mean of the four categories is 2.43. This indicates that the
respondents are Fairly Prepared.
III.
Challenges in the Flexible Distance Learning Modality
A. SELF-REGULATION
CHALLENGES (SRC)
Σ𝒇𝒈𝒓𝒐𝒖𝒑 ˟
𝑵𝒈𝒓𝒐𝒖𝒑
Weighted
Mean
Interpretation
1. I delay tasks related
to my studies so that
they are either not
fully completed by
their deadline or have
to be rushed to be
completed.
179
3.09
Sometimes
2. I fail to get appropriate
help
during
synchronous classes.
163
2.81
Sometimes
42
3. I lack the ability to
control
my
own
thoughts,
emotions,
and actions during
either synchronous or
asynchronous
classes.
189
3.26
Sometimes
4. I
have
limited
preparation before an
online class.
181
3.12
Sometimes
5. I have poor time
management skills.
190
3.28
Sometimes
6. I fail to properly use
peer
learning
strategies
(i.e.,
learning from one
another
to
better
facilitate learning such
as peer tutoring, group
discussion, and peer
feedback).
180
3.10
Sometimes
7. I have procrastinated
working
in
asynchronous
classes.
193
3.33
Sometimes
1,275
3.14
Sometimes
Total
Table 12: Self-Regulation Challenges (SRC)
The data reveals that all the indicators in the Self-Regulation Challenges
(SRC) Category garnered the same “Sometimes” interpretation. The result
implies that the respondents seem to be fairly well-organized but also have the
need to improve their organizational skills, especially when it comes to time
management. It can be observed from the table above that the 7 th statement, “I
have procrastinated working in asynchronous classes.”, has the highest
weighted mean average, 3.33, among all the indicators. It only speaks that
students become prone to procrastinate in the flexible distance learning
43
modality, which may be rooted due to their less accessibility to technical
resources and lack of structured support from the instructors and family.
Moreover, the following are the indicators with their corresponding
weighted mean averages: “I have poor time management skills.”, (3.28); “I lack
the ability to control my own thoughts, emotions, and actions during either
synchronous or asynchronous classes.”, (3.26); “I have limited preparation
before an online class.”, (3.12); “I delay tasks related to my studies so that they
are either not fully completed by their deadline or have to be rushed to be
completed.”, (3.09); “I fail to get appropriate help during synchronous classes.”,
(2.81). All in all, the respondents are sometimes experiencing challenges when
it comes to Self-Regulation in the FDLM.
B. TECHNOLOGICAL LITERACY Σ𝒇𝒈𝒓𝒐𝒖𝒑 ˟ 𝑵𝒈𝒓𝒐𝒖𝒑
AND
COMPETENCY
CHALLENGES (TLCC)
Weighte
d Mean
Interpretation
1. I
lack
competence
and
proficiency in using various
interfaces or systems that allow
me to control a computer or
another embedded system for
studying.
159
2.74
Sometimes
2. I resist learning technology
128
2.21
Rarely
3. I am distracted by an overly
complex technology
186
3.21
Sometimes
4. I have difficulties learning a new
technology.
154
2.66
Sometimes
5. I lack the ability to effectively use
technology to facilitate learning.
150
2.59
Rarely
6. I lack knowledge and training in
the use of technology.
150
2.59
Rarely
7. I am intimidated by the
technologies used for learning.
155
2.67
Sometimes
44
8. I resist and/or am confused
when getting appropriate help
during synchronous classes.
151
2.60
Rarely
9. I have poor understanding of
directions and expectations in
synchronous and asynchronous
classes.
155
2.67
Rarely
10. I perceive technology as a
barrier to getting help from
others
during
synchronous
classes.
117
2.02
Rarely
1,505
2.59
Rarely
Total
Table 13: Technological Literacy and Competency Challenges (TLCC)
The data shows that the indicators under the Technological Literacy and
Competency Challenges (TLCC) category fall mostly in “Sometimes” and
“Rarely” interpretations. The following are the indicators with “Sometimes”
interpretations: “I am distracted by an overly complex technology.”, (3.21); "I
lack competence and proficiency in using various interfaces or systems that
allow me to control a computer or another embedded system for studying.”,
(2.74); “I am intimidated by the technologies used for learning.”, (2.67); and “I
have difficulties learning a new technology.”, (2.66).
On the contrary, the following are the indicators with “Rarely”
interpretations: “I resist and/or am confused when getting appropriate help
during synchronous classes.”, (2.60); “I lack the ability to effectively use
technology to facilitate learning.” and “I lack knowledge and training in the use
of technology.”, (2.59); “I have a poor understanding of directions and
expectations in synchronous and asynchronous classes.”, (2.26); “I resist
learning technology.”, (2.21); and “I perceive technology as a barrier to getting
help from others during synchronous classes.”, (2.02). Hence, it is observable
45
that there are only minimal intervals in the weighted mean averages of all the
indicators, enabling the TLCC category to have a “Rarely” interpretation (2.55)
when summed up. It wants to emphasize that there is no resistance to change.
The respondents are willing to adapt and learn the online approach to
education. The problems only arise mostly due to external factors such as the
sudden switching of learning approach, unavailability of technical resources,
lack of digital orientation and training.
C. STUDENT ISOLATION
CHALLENGES (SIC)
Σ𝒇𝒈𝒓𝒐𝒖𝒑 ˟
𝑵𝒈𝒓𝒐𝒖𝒑
Weighted
Mean
Interpretation
1. I
feel
emotionally
disconnected or isolated
during neither synchronous
nor asynchronous classes.
184
3.17
Sometimes
2. I feel disinterested during
online class
150
2.58
Rarely
3. I
feel
uneasy
and
uncomfortable in using video
projection,
microphones,
and speakers.
156
2.68
Sometimes
4. I feel uncomfortable being
the centre of attention during
online classes
177
3.05
Sometimes
667
2.875
Total
Sometimes
Table 14: Student Isolation Challenges (SIC)
Table 14 presents that most of the students sometimes experience
isolation challenges with the total weighted mean of 2.875. Being emotionally
disconnected or isolated garnered 3.17 weighted mean. Feeling uneasy and
uncomfortable in using video projection, microphones and speakers have a
mean of 2.69. In addition, being the center of attention during online classes
46
make students feel uncomfortable as evidenced by the mean of 3.05. The three
aforementioned scenarios are sometimes experienced by the students. On the
other hand, the feeling of disinterest during online class has a mean of 2.59,
interpreted as rarely experienced by the respondents.
D. TECHNOLOGICAL
SUFFICIENCY
CHALLENGES (TSC)
Σ𝒇𝒈𝒓𝒐𝒖𝒑 ˟
𝑵𝒈𝒓𝒐𝒖𝒑
Weighted
Mean
Interpretation
1. I have insufficient access
to learning technology.
178
3.06
Sometimes
2. I experience inequalities
with regard to access to
and use of technologies
during flexible learning
classes because of my
socioeconomic, physical,
and
psychological
condition.
177
3.05
Sometimes
3. I
have
technology.
outdated
161
2.77
Sometimes
4. I do not have Internet
access
during
either
synchronous
or
asynchronous classes.
158
2.72
Sometimes
5. I have low bandwidth and
slow processing speeds
184
3.17
Sometimes
6. I experience technical
difficulties in completing
my assignments.
191
3.29
Sometimes
1049
3.014
Sometimes
Total
Table 15: Technological Sufficiency Challenges (TSC)
The respondents of this study sometimes experience insufficiency of
access to learning technology with the mean of 3.06. They also sometimes
47
experience inequalities in accessing or using technologies due to their socioeconomic, physical, and psychological condition. It has a weighted mean of
3.05. In addition, students sometimes have outdated technology with a mean
of 2.77. When it comes to internet access during synchronous and
asynchronous classes, students sometimes experience difficulties as noted by
the mean of 2.72. Moreover, students also sometimes have low bandwidth and
slow processing speeds as the mean of 3.17 expresses. Lastly, they sometimes
experience technical difficulties in completing assignments given to them with
a mean of 3.29. Generally, in Table 15 there is a total weighted mean of 3.01
which is interpreted as sometimes experienced by the students for the
technological sufficiency challenges.
Σ𝒇𝒈𝒓𝒐𝒖𝒑 ˟
𝑵𝒈𝒓𝒐𝒖𝒑
Weighted
Mean
Interpretation
1. I am distracted by the
complexity of the technology
during online classes.
173
2.98
Sometimes
2. I experience difficulties in
using complex technology
173
2.98
Sometimes
3. I experience difficulties when
using longer videos for
learning.
194
3.34
Sometimes
540
3.10
Sometimes
E. TECHNOLOGICAL
COMPLEXITY
CHALLENGES (TCC)
Total
Table 16: Technological Complexity Challenges (TCC)
In the aspect of technological complexity, Table 16 presents that
students substantially sometimes experienced challenges with the total
weighted mean of 3.10. They are sometimes distracted by the complexity of the
technology during online classes as seen through its mean of 2.98. They also
48
sometimes experienced difficulties in using complex technology with the mean
similar to the preceding scenario stated. The students sometimes encountered
difficulties when using longer videos for learning. It has a mean of 3.44.
F. LEARNING
RESOURCE
CHALLENGES (LRC)
Σ𝒇𝒈𝒓𝒐𝒖𝒑 ˟
𝑵𝒈𝒓𝒐𝒖𝒑
1. I have insufficient
access
to
library
resources
Weighted
Mean
Interpretation
199
3.43
Often
2. I have insufficient
access to laboratory
equipment
and
materials.
208
3.58
Often
3. I have limited access
to
textbooks,
worksheets, and other
instructional materials
163
2.81
Sometimes
4. I experience financial
challenges
when
accessing
learning
resources
and
technology
214
3.68
Often
784
3.37
Sometimes
Total
Table 17: Learning Resource Challenges (LRC)
The above table indicates that most of the respondents often suffer from
insufficient access to library resources, which accumulate 3.43 mean. It is
visible that they also experience insufficient access to laboratory equipment and
materials that gather a mean of 3.58. Then, with a mean of 2.81, respondents
sometimes encounter limited access to textbooks, worksheets, and other
instructional materials. Lastly, it was found out that they undergo financial
challenges when accessing learning resources and technology, which garner
49
of 3.68 mean. In general, most of the respondents sometimes encounter
learning resource challenges during FDLM.
G. LEARNING
ENVIRONMENT
CHALLENGES (LEC)
Σ𝒇𝒈𝒓𝒐𝒖𝒑 ˟
𝑵𝒈𝒓𝒐𝒖𝒑
Weighted
Mean
Interpretation
1. I experience online
distractions such as
social media during
online classes.
221
3.81
Often
2. I
experience
distractions at home as
a
learning
environment.
229
3.94
Often
3. I have difficulties in
selecting the best time
and area for learning at
home.
218
3.75
Often
4. Home set-up limits the
completion of certain
requirements for my
subject
(e.g.,
laboratory
and
physical activities).
207
3.56
Often
875
3.77
Often
Total
Table 18: Learning Environment Challenges
The table represents the learning environment challenges encountered
by the respondents. Mostly, during online classes, the respondents experience
online distractions such as browsing social media, which acquire a mean of
3.81. Obtaining a mean of 3.94 indicates that they often experience distractions
at home as a learning environment. Then, garnering of 3.75 mean implies that
they had a hard time in selecting the best time and area for learning at home.
Even home set-up limits them from completing certain requirements for their
subject, which got 3.56 mean.
50
Overall Weighted Mean of Challenges
Category
Weighted Mean
Interpretation
A. Self-Regulation
Challenges (SRC)
3.14
Sometimes
B. Technological Literacy
And Competency
Challenges (TLCC)
2.59
Rarely
C. Student Isolation
Challenges (SIC)
2.87
Sometimes
D. Technological
Sufficiency Challenges
(TSC)
3.01
Sometimes
E. Technological
Complexity Challenges
(TCC)
3.10
Sometimes
F. Learning Resource
Challenges (LRC)
3.37
Sometimes
G. Learning Environment
Challenges (LEC)
3.77
Often
3.12
Sometimes
Total
Table 19: Overall Weighted Mean of Challenges
IV.
Pearson’s Correlation Between Students’ Level of Preparedness
and Challenges with Flexible Learning Modality
𝑟=
𝑟=
𝑟=
𝑠𝑝
df=N-2
√(𝑆𝑆𝑥)(𝑆𝑆𝑦)
−753.6896552
√(170.2758621)(25690.22)
df= 58-2
−753.6896552
df=56
√4,374,424.3580387
−753.6896552
𝑟 = 2,091.5124570604
𝒓 = −𝟎. 𝟑𝟔𝟎𝟑𝟓𝟔𝟐𝟖𝟑𝟐 𝒐𝒓 − 𝟎. 𝟑𝟔
51
N
X
Y
x̅
y̅
(X-x̅) (Y- y̅)
(𝑿 − 𝒙̅)𝟐
( 𝒀 − 𝒚̅)𝟐
58
570
6695
9.827586
115.431
-753.68
170.27
25690.22
Table 20: Tabulated data for Pearson’s correlation
The table above presents the data on the Pearson’s correlation between
students’ level of preparedness (X) and challenges (Y) with flexible learning
modality. The data analysis shows the total number of respondents of the study,
total of sum of x and y, total weighted mean of x and y, sum of the square root
of x and sum of the square root of y.
SP
SSx
-753.6896552
170.2758621
SSy
Pearson
Strength of
𝒓
Relationship
-0.36
Moderate negative
25690.22
correlation
Table 21: Strength of Relationship of Pearson r
Formula for Pearson Correlation Coefficient
𝑟=
𝑠𝑝
df= N-2
√(𝑆𝑆𝑥)(𝑆𝑆𝑦)
Where:
Where:
SP= Sum of Products
df= degrees of freedom
SSx= Sum of the square of x
N= Number of respondents
SSy= Sum of the square of y
52
𝑟=
𝑟=
𝑟=
𝑠𝑝
df=N-2
√(𝑆𝑆𝑥)(𝑆𝑆𝑦)
−753.6896552
df= 58-2
√(170.2758621)(25690.22)
−753.6896552
df=56
√4374424.3580387
−753.6896552
𝑟 = 2091.5124570604
𝒓 = −𝟎. 𝟑𝟔𝟎𝟑𝟓𝟔𝟐𝟖𝟑𝟐 𝒐𝒓 − 𝟎. 𝟑𝟔
Table 21 presents the following data; sum of products (SP=753.6896552), sum of the square of x (SSx=170.2758621), and sum of the
square of y (SSy=25690.22). These data are used to obtain the Pearson 𝑟
which is -0.36, which show that the two variable lies at moderate negative
correlation base on Strength of Relationship. The correlation reveals that as the
level of students’ preparedness increases, the lower challenges they
experience, and vice versa.
df
α
56
0.05
Table of
Critical Value
0.250
Verbal Interpretation
There is no significant
relationship with students’
level of preparedness and
challenges.
Table 22: Table of Critical Value of Pearson r
Table 22 revealed that there was a moderate negative correlation
between the two variables as shown in table 21, where the critical value at the
0.05 level of significance is 0.250 and the degrees of freedom is 56. However,
the increase in the value of X is associated with a decrease in Y. This proves
that if the students’ level of preparedness increases, the challenges decreases
and vice versa. Therefore, there is no significant relationship with student’s level
of preparedness and challenges.
53
CHAPTER V
SUMMARY, FINDINGS, CONCLUSION, AND RECOMMENDATIONS
This chapter presents the brief summary, findings, conclusions, and as
well as the recommendations for the specific problems of the study.
Summary
This study mainly focused on the preparedness and challenges of
college education students in the flexible distance learning modality. The
demographic profiles of the respondents were also identified. The respondents
of this study are third-year students taking Bachelor of Secondary Education,
Major in English at Central Bicol State University of Agriculture-Calabanga
Campus during the academic year 2021-2022. This research used a
quantitative approach and a descriptive-correlated research design was
adopted utilizing the survey questionnaires. The sampling technique used is a
total enumeration, where all members of the whole population are considered
and measured. Frequency and Percentage were used to determine the
distribution of the respondents according to their socio-demographic profile.
Weighted Mean was used to determine the preparedness and the challenges
of the respondents in the flexible distance learning modality. The Pearson R
was also applied to determine the significant relationship between the level of
preparedness and challenges of the respondents in a flexible learning modality.
For the interpretation of the findings on the level of preparedness of students
Likert Scale with Four anchors was used while Likert Scale with Five anchors
was for challenges experienced.
54
Problem No. 1: What is the profile of the college students of the Central
Bicol State University of Agriculture, Calabanga Campus, in terms of: a)
Student type; b) Family income; and c) Residence geographical location?
Findings: For Student type, most of the respondents are non-working student
with 87.9% followed by the lowest in rank is working student with 12.1%. For
Family income, most of the respondents have less than Php 10,957 with 75.9%.
It is followed by between Php 10,957 to Php 21,914 with 15.5%, at least Php
219,140 and up, then between Php 21,914 to Php 43,828 with the same 3.4%
and the least is between Php 131,484 to Php 219,140 with 1.7%. For the
Residence's geographical location, most of the respondents reside in the
Upland area with 39.7%, while the lowest in rank is Lowland 36.2%, and
followed by Coastal area with 24.1%.
Conclusions: For Student type, it is concluded that mostly were non-working
student because this pandemic makes a lot of students rely on their parents
especially it has caused a lot of unemployment and makes it hard for those
students to find a part-time job. For Family income, it is concluded that most
average family income less than ₱10,957 with 75.9%. Monthly family income
less than ₱10,957 is identified as poor according to the Philippine Institute for
Development Studies (2018). For Residence’s geographical location, Upland
area has the highest percentage. Upland is an area habitually known as a
higher ground of a region or district; an elevated region with a closer distance
from the school, presence of public transportations, internet connection, data
signals, markets, and establishments it was way more convenient, more
55
suitable, and accessible to live in especially with the occurrence of flexible
learning compared to live in the lowland and coastal areas.
Recommendations: The researchers highly recommend that non-working and
working students should both practice time management. Non-working
students should look for a balance between household chores and school
works. Working students should balance work and school works. Moreover, it
is also recommended that teachers should consider students who fail to attend
the class if unscheduled power interruption and unstable internet connection
occurs during the scheduled online class meeting. Additionally, the researchers
recommend that students can apply for educational assistance and
scholarships provided by government and non-government organizations.
There were different bits of help that the government and non-government
organizations offer to college students of low-income families.
Problem No. 2: What is the level of preparedness of the college students
to the flexible distance learning modality along: a) Learning resources; b)
Internet Access; c) Technological Literacy; and d) Home Learning Space?
Findings. Through the weighted mean of each category: the learning
resources, internet access, technological literacy, and home learning space,
the researchers found out the respondents’ level of preparedness in these
categories. The respondents are fairly prepared in terms of Internet Access and
Home Learning Space, while they are moderately prepared in the availability of
56
learning resources and Home Learning Space. Generally, the respondents’
preparedness in Flexible Distance Learning Modality is fairly prepared.
Conclusions. The researchers then concluded that the respondents are
moderately prepared in Flexible Distance Learning Modality. They are
moderately prepared in the availability of learning resources, they are fairly
prepared in terms of access to the internet, they are literate enough in
technology with the level of moderately prepared, and almost all of them occupy
learning space at home in which they are moderately prepared. The
researchers also concluded that this result does not guarantee the respondents’
preference and effectivity of learning in Flexible Distance Learning Modality.
Recommendations. The researchers, therefore, recommended that although
the respondents are fairly prepared in flexible distance learning modality, they
still have to develop some strategies that will further ameliorate their
preparedness specifically in internet access and home learning space. Since
they have moderate access to the internet through Cellular data only, they may
also develop strategies such as finding a location that helps their mobile
phones’ cellular data works well for them to sustain their synchronous and
asynchronous classes. Thus, being fairly prepared in-home learning space,
they can learn to adjust to their learning environment. Although they are
moderately prepared in learning resources and technological literacy, they must
carry consistency and still try to improve their readiness in these areas. The
57
researchers also recommend continue being flexible and responsible in
distance learning to be more adaptable and effective learners.
Problem No. 3: What are the challenges of the respondents in Flexible
Distance Learning Modality in terms of: a) Self-Regulation Challenges
(SRC); b) Technological Literacy and Competency Challenges (TLCC); c)
Student Isolation Challenges (SIC); d) Technical Sufficiency Challenges
(TSC); e) Technological Complexity Challenges (TCC); f) Learning
Resource Challenges (LRC); and g) Learning Environment Challenges
(LEC)?
Findings: The following are the findings of each category:
A. Self-Regulation Challenges (SRC). The respondents seem to have
common experiences in this category as shown on the analyzed data,
with all the indicators having the same verbal interpretation of
“Sometimes”. Among the indicators, procrastination has the highest
weighted mean (3.33) and is followed by poor time-management skills
(3.28). Hence, it has an overall weighted mean of 3.14, with “Sometimes”
as its verbal interpretation as well. It wants to emphasize that they have
fair motivational and behavioral processes which explains why they
cannot sustain concentration on their goal and find it hard to complete
the task on time.
B. Technological Literacy and Competency Challenges (TLCC). The data
shows that the respondents do not usually have issues and concerns
58
with computer knowledge, as the TLCC category has a 2.59 weighted
mean average, with corresponding “Rarely” verbal interpretation.
C. Student Isolation Challenges (SIC). Based on the gathered data, the SIC
Category has a total of 2.875 weighted mean average, enabling to have
a “Sometimes” interpretation. It is because the newly implemented
learning modality limits social interaction, making the students
vulnerable to isolation, feeling disconnected, and loneliness.
D. Technological Sufficiency Challenges (TSC). According to the results
obtained, the TSC category has an overall 3.01 weighted mean and
“Sometimes” as its verbal interpretation. It wants to suggest that
accessibility to technological resources is one of the challenges they
occasionally experienced in FDLM.
E. Technological Complexity Challenges (TCC). The research results show
that all the indicators in the TCC category have the same “Sometimes”
interpretation, with a total of 3.10 weighted mean. It tries to emphasize
that the respondents have an existing concern on the complexity of
technological resources utilized in the university (e.g., navigating the
complex user interface of Virtual Learning Portal).
F. Learning Resource Challenges (LRC). For the LRC category, the
weighted mean is 3.37, with “Sometimes” as its verbal interpretation. It
wants to imply that the respondents somehow experienced a lack of
available resources they can use as they go along the learning process.
G. Learning Environment Challenges (LEC). Among all the categories, LEC
is the one with the highest total weighted mean, 3.77, and with a
corresponding “Often” verbal interpretation. It reveals that the
59
respondents’ learning environment has had a significant impact on their
learning experience, which they found to be distracting and
inconvenient.
Conclusions:
A. The findings of the study revealed that the students had difficulties in
organizing their self-regulated learning, felt overwhelmed by the
requirements of distance learning, reported having problems with
concentrating on their tasks, or described that it was difficult for them to
do their homework on their own. It may also conclude the importance of
self-efficacy, goal setting, and help-seeking for students to succeed in
Flexible Distance Learning Modality.
B. Technical problems and lack of proficiency on ICT were revealed as one
of the demotivating factors for the students while learning. On the
contrary, when students are better equipped to engage with and utilize
technological tools, the students will gain self-motivation to learn and
engage in the class. Also, teachers can make the learning process more
interactive and effective.
C. Generally, for students' experiences, it seemed too hard in coping with
the social demands of lockdown. Most of the students reported feeling
bored during lockdown while they engage in distance learning, some of
them reported feeling frequently lonely or having problems keeping in
touch with their friends. Nevertheless, the vast majority of students were
longing to get back into a face-to-face class.
60
D. Students who do not have access to technology faces significant
problems, such as inequalities in gaining knowledge, and delay in
receiving learning materials. Increased usage of technology during
distance learning would let the students who are not sufficed with
advanced technology get insufficient time to finish their tasks. Also, their
privilege to develop their skills was held up and might be ignored.
E. This study concluded that the students consume much of their time in
managing complex technology and skip plenty of time for learning during
online classes. There is no doubt that students will continue to work with
the complex technology for online classes. Students must be cognizant
of the technological proficiency skills necessary to be successful in
online learning.
F. The findings indicate that a substantial number of students had
difficulties in coping with the learning resource requirements during
distance learning. The insufficient access to resources and support at
home might be considered to be a disadvantage to students in times of
the COVID-19 pandemic.
G. It can be concluded that in a distance learning setup, the learning
environment can be considered as a factor that influences the level of
students' motivation in learning. Lackness of teacher supervision to the
students during online classes will lead them to get distracted easily with
a disturbing scenario within their learning space. Therefore, students
may lose their eagerness to engage with class discussion and activities.
61
Recommendations: After the thorough assessment and considering the
foregoing findings and conclusions of the study, the following recommendations
are presented:
1. The third-year College of Education students of the Central Bicol State
University of Agriculture may be able to improve their learning strategies,
time management, and organization skills for better self-regulation
practices in this Flexible Distance Learning Modality.
2. The parents may help their students at home during the flexible distance
learning modality by being aware of how the learning process works and
contributing to an adequate and satisfactory learning environment.
3. The teachers may formulate more engaging class activities and set a
comfortable atmosphere during online classes to capture students’
interest and engagement.
4. The academe may conduct further enrichment programs and projects
about technological literacy and competency as well as using technology
to ensure a more conducive learning process for the students.
5. The Commission on Higher Education and the academe may address
the challenges of students on technological sufficiency and learning
resources by creating and implementing programs and projects such as
technological assistance, gadgets, and facilities for students to utilize,
and others.
Problem No. 4: Is there a significant relationship between the students’
level of preparedness and the challenges experienced with flexible
distance learning modality?
62
Findings. A Pearson product-moment correlation coefficient was computed to
determine the significant relationship between students’ level of preparedness
and challenges with flexible learning modality where the results shows that the
sum of the products is -753.6896552. For the students’ level of preparedness,
the sum of the squares is 170.2758621 while 25690.22 for the sum of the
squares of the challenges with flexible learning modality. The result revealed
that the Pearson 𝑟 (-0.36) corresponds to moderate negative correlation as strength
of the relationship.
Conclusions. There is no significant relationship in the level of students’
preparedness and challenges. This is evidenced by the result of Pearson
Correlation Coefficient which show a significance level of 0.250. The
significance level is greater than the Pearson 𝑟 (-0.36). It concludes that the Ho
is accepted, which show that there is no significant relationship in the level of
students’ preparedness and challenges during Flexible Learning Modality. In
sum, the result highlight that the two variables are inverse correlated, where;
the higher students’ preparedness the lower they will experience the challenge,
meanwhile, the lower students’ preparedness the higher chance they will
experience challenges.
Recommendations: After the thorough assessment and considering the
foregoing findings and conclusions of the study, the following recommendations
are presented:
63
1. The third year English majors of CBSUA must increases their level of
preparedness in terms of learning resources, internet access,
technological literacy, and home learning space to lessen the challenges
they may encounter in flexible distance learning modality.
2. The teacher may consider the level of preparedness of the students in
generating instruction to effectively deliver their lesson in flexible
learning modality.
3. The parents may recognize the challenges encounter by their child
during flexible learning distance, so that they can offer corresponding
supports to address the needs of the student.
4. The future researcher may conduct further study which cover larger
population to strengthen the validity of this study.
64
Bibliography
Amir, L. R., Tanti, I., Maharani, D. A., Wimardhani, Y. S., Julia, V., Sulijaya,
B., & Puspitawati, R. (2020). Student perspective of classroom and
distance learning during COVID-19 pandemic in the undergraduate
dental study program Universitas Indonesia. BMC medical education,
20(1), 1-8.
https://bmcmededuc.biomedcentral.com/articles/10.1186/s12909-02002312-0
Aikina, T., Bolsunovskaya, L. (2020). Moodle-Based Learning: Motivating and
Demotivating Factors. International Journal of Emerging Technologies
in Learning (iJET), 15(2), 239-248. https://research.moodle.org/483/
Barrera, K. , Arcilla, F., & Jaminal, B. (2020). Readiness for Flexible Learning
amidst COVID-19 Pandemic of Saint Michael College of Caraga,
Philippines. SMCC Teacher Education Journal.11-12.
https://dx.doi.org/10.18868/cte.02.060120.01
CHED (2020). CHED COVID ADVISORY NO.6: Guidelines for the Prevention,
Control, and Mitigation of the Spread of Coronavirus Disease 2019
(COVID-19)
in
Higher
Education
Institutions
(HEIs).
https://ched.gov.ph/wp-content/uploads/CHED-COVID-19-AdvisoryNo.-6.pdf
Cortes, S.T. (2020). Flexible Learning as an Instructional Modality in
Environmental Science Course during COVID-19.
https://www.aquademia-journal.com/download/flexible-learning-as-aninstructional-modality-in-environmental-science-course-during-covid19-8444.pdf
Crawford, C.M. (2021). Shifting to Online Learning Through Faculty
Collaborative Support. IGT Global.
https://www.semanticscholar.org/paper/Shifting-to-Online-LearningThrough-Faculty-Support-FragaHall/089e8d7acfb6d472273ce09c21233fd30ab74740
Daniela, L., & Visvizi, A. (2021). Remote Learning in Times of Pandemic.
Routhledge. doi: 10.4324/9781003167594.
https://www.routledge.com/Remote-Learning-in-Times-of-PandemicIssues-Implications-and-Best-Practice/DanielaVisvizi/p/book/9780367765705
Dayagbil, F.T. et.al. (2021). Teaching and Learning Continuity Amid and
Beyond the Pandemic.
https://www.frontiersin.org/articles/10.3389/feduc.2021.678692/full
Dennis, C., Abbott, S., Matehson, R., & Tangney, S. (Eds.). (2020), Flexibility
and Pedagogy in Higher Education: Delivering Flexibility in Learning
65
through Online Learning Communities. Brill Sense.
https://brill.com/view/title/58559
Dr. Dimitrios I. Sotiropoulos (2020) Basic Concepts Distance Learning
https://www.classter.com/2020/04/29/basic-concepts-of-distance-learningand-how-to-introduce-it-to-your-educational-organization/
Dr. Robert Joan (2020) TOP HAT GLOSSARY-Flexible Learning
https://files.eric.ed.gov/fulltext/EJ1098325.pdf
/https://tophat.com/glossary/f/flexible-learning/
Elfirdoussi, S., Lachgar, M., Kabaili, H., Rochdi, A., Goujdami, D., & El
Firdoussi, L. (2020). Assessing Distance Learning in Higher Education
during the COVID-19 Pandemic. Education Research
International, 2020, 1-13. doi: 10.1155/2020/8890633
https://www.hindawi.com/journals/edri/2020/8890633/
Gleason, N. (2018). Higher Education in the Era of the Fourth Industrial
Revolution. Palgrave MacMillan.
https://link.springer.com/content/pdf/10.1007%2F978-981-13-01940.pdf
HR-OCHA (2013) Humanitarian Response-Preparedness
https://www.humanitarianresponse.info/en/coordination/preparedness/whatpreparedness
IGI
Global
(2018)
global.com/publish/
Concept
of
Challenges-https://www.igi-
Joaquin, J., Biana, H., & Dacela, M. (2020). The Philippine Higher Education
Sector in the Time of COVID-19.
https://www.frontiersin.org/articles/10.3389/feduc.2020.576371/full?fbcli
d=IwAR2lwOrhGXGUXmn32qJ0AKWgOO0msSnYv1lZi1T1UFK07CJ5
HU-7Ez-98ho
Magsambol, B. (2020). FAST FACTS: CHED's flexible learning.
https://www.rappler.com/newsbreak/iq/things-to-know-ched-flexiblelearning
Laguador, J. (2021). Challenges Encountered during Pandemic in Flexible
Learning Among College Students Living in Urban, Rural, and
Suburban Areas in the Philippines. Asia Pacific Journal of Educational
Perspectives,8(1),10-16.
Mahmut, S. (Ed.). (2018). Trends in E-learning. Intech Open.
doi.org/10.5772/intechopen.71183
66
Morze, N., Varchenko-Trotsenko, L., Terletska, T., & Smyrnova-Trybulska, E.
(2021, March). Implementation of adaptive learning at higher education
institutions by means of Moodle LMS. In Journal of Physics:
Conference Series (Vol. 1840, No. 1, p. 012062). IOP Publishing.
https://iopscience.iop.org/article/10.1088/1742-6596/1840/1/012062/pdf
Nadiahan, M., & Cabauatan, L. (2021). Status of learners’ support in the
college of education of a state university in the Cordillera-Philippines
during the COVID-19 pandemic. International Journal of Curriculum
and Instruction,13(3),1-26. ijci.wcci-international.org
Pawilen, G. (2021). Preparing Philippine higher education institutions for
flexible learning during the period of COVID-19 pandemic: Curricular
and instructional adjustments, challenges,
and issues.
International Journal of Curriculum and Instruction,13(3),2150–2166.
ijci.wcci-international.org
Rotas, E.,& Cahapay, M.(2021).From stress to success: Exploring how
Filipino students cope with remote learning amid COVID-19 pandemic.
Journal of Pedagogical Sociology and Psychology,3(1),32-33.
http://www.doi.org./10.33903/JPSP.2021366608
Reyes, J.S., Grajo, J., Comia, L.N., Talento, M., Ebal, L.A. & Mendoza, J.O.
(2021).
Assessment of Filipino Higher Education Students’ Readiness for e-Learning
During a Pandemic: A Rasch Technique Application. Philippine Journal
of Science.
https://philjournalsci.dost.gov.ph/images/pdf/pjs_pdf/vol150no3/assess
ment_of_Filipino_Higher_Education_students_.pdf
Rotas, E.E. & Cahapay, M.B. (2020). Difficulties in Remote Learning: Voices
of Philippine University Students in the Wake of COVID-19 Crisis.
Asian Journal of Distance Learning Education.
https://files.eric.ed.gov/fulltext/EJ1285295.pdf
Talosa, A. D., Javier, B. S., & Dirain, E. L. (2021). The flexible-learning
journey: phenomenological investigation of self-efficacy influencing
factors among higher education students. Linguistics and Culture
Review, 5(S3), 422-434. 422-434.
https://doi.org/10.37028/lingcure.v5nS3.1590
Wandler, J. B., & Imbriale, W. J. (2017). Promoting undergraduate student
self-regulation in online learning environments. Online Learning.
https://files.eric.ed.gov/fulltext/EJ1149360.pdf
67
APPENDIX A
Letter of Request
68
APPENDIX B
Research Instrument: Online Survey Questionnaire
69
70
71
72
73
74
75
76
77
78
79
80
APPENDIX C
Graphical Presentation of Survey Results
81
82
83
84
85
APPENDIX D
Raw Test Data or Results
86
87
88
89
90
APPENDIX E
Values of Y for Person Product Correlation Coefficient
Y-Challenges
RESPONDENTS
A
B
C
D
E
F
G
Total
1
26
21
15
21
10
16
17
126
2
17
19
10
12
7
12
13
90
3
19
28
13
24
11
16
14
125
4
23
27
12
13
9
11
19
114
5
21
17
6
13
7
12
14
90
6
27
36
16
22
11
14
16
142
7
26
30
12
24
9
12
19
132
8
25
26
12
18
11
14
11
117
9
16
14
6
10
5
12
13
76
10
22
33
8
19
12
13
14
121
11
26
41
15
27
13
20
19
161
12
18
30
13
19
9
15
14
118
13
22
18
8
15
6
11
13
93
14
20
20
7
12
9
15
11
94
15
23
29
9
22
10
13
16
122
16
27
26
14
18
10
15
20
130
17
19
26
10
13
9
12
11
100
18
22
20
12
9
7
12
17
99
19
27
38
17
25
11
15
19
152
20
25
31
11
16
9
15
20
127
21
25
31
14
27
15
19
18
149
22
23
24
16
17
10
14
20
124
23
21
30
15
23
11
20
19
139
24
15
21
10
21
9
13
11
100
25
26
26
11
26
12
19
20
140
26
16
15
7
14
9
13
13
87
27
20
30
10
17
9
15
14
115
28
16
14
5
14
6
9
15
79
29
22
33
16
23
13
16
17
140
30
27
25
12
18
9
16
18
125
91
31
18
28
11
20
15
17
20
129
32
19
22
11
16
9
12
13
102
33
27
30
14
24
10
17
19
141
34
21
13
9
14
7
11
9
84
35
11
13
11
15
9
12
7
78
36
21
24
11
16
9
13
15
109
37
22
30
12
18
9
12
12
115
38
22
29
14
19
9
9
10
112
39
13
23
10
8
6
9
15
84
40
27
33
14
20
9
13
15
131
41
22
31
11
21
10
13
12
120
42
17
20
12
12
9
12
12
94
43
24
34
13
21
12
14
16
134
44
18
27
12
19
9
12
11
108
45
9
14
4
8
6
9
10
60
46
30
27
16
15
9
12
18
127
47
23
30
11
15
9
11
14
113
48
23
12
12
22
7
12
16
104
49
21
30
11
20
9
13
16
120
50
26
38
12
21
9
10
17
133
51
25
27
13
16
9
15
17
122
52
25
32
13
20
11
16
19
136
53
24
17
10
25
9
18
20
123
54
21
24
10
16
10
13
20
114
55
30
36
11
21
10
13
8
129
56
26
28
17
23
7
18
16
135
57
23
29
11
20
9
11
15
118
58
25
25
8
12
6
8
8
92
1275
1505
667
1049
540
784
875
6695
92
RESPONDENTS
C
4
2.5
3.25
3
1.5
4
3
3
1.5
2
3.75
3.25
2
1.75
2.25
3.5
2.5
3
4.25
2.75
3.5
4
3.75
2.5
2.75
1.75
2.5
1.25
4
D
3.5
2
4
2.166666667
2.166666667
3.666666667
4
3
1.666666667
3.166666667
3.166666667
2.5
2
3.666666667
3
2.166666667
1.5
4.166666667
2.666666667
4.5
2.833333333
3.833333333
3.5
4.333333333
2.333333333
2.833333333
2.333333333
3.833333333
E
3.333333333
2.333333333
3.666666667
3
2.333333333
3.666666667
3
3.666666667
1.666666667
4
4.333333333
3
2
3
3.333333333
3.333333333
3
2.333333333
3.666666667
3
5
3.333333333
3.666666667
3
4
3
3
2
4.333333333
F
4
3
4
2.75
3
3.5
3
3.5
3
3.25
5
3.75
2.75
3.75
3.25
3.75
3
3
3.75
3.75
4.75
3.5
5
3.25
4.75
3.25
3.75
2.25
4
G
4.25
3.25
3.5
4.75
3.5
4
4.75
2.75
3.25
3.5
4.75
3.5
3.25
2.75
4
5
2.75
4.25
4.75
5
4.5
5
4.75
2.75
5
3.25
3.5
3.75
4.25
TOTAL
3.556802721
2.487414966
3.418707483
3.093197279
2.457142857
3.755782313
3.494897959
3.155442177
2.109863946
3.194217687
4.306802721
3.176870748
2.491836735
2.586734694
3.240816327
3.577210884
2.67585034
2.746598639
4.034353741
3.405442177
4.131632653
3.478911565
3.857142857
2.748979592
3.878231293
2.481292517
3.06292517
2.181292517
3.83707483
APPENDIX F
B
2.1
1.9
2.8
2.7
1.7
3.6
3
2.6
1.4
3.3
4.1
3
1.8
2
2.9
2.6
2.6
2
3.8
3.1
3.1
2.4
3
2.1
2.6
1.5
3
1.4
3.3
SOP3 Challenges: Overall Weighted Mean
93
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
A
3.714285714
2.428571429
2.714285714
3.285714286
3
3.857142857
3.714285714
3.571428571
2.285714286
3.142857143
3.714285714
2.571428571
3.142857143
2.857142857
3.285714286
3.857142857
2.714285714
3.142857143
3.857142857
3.571428571
3.571428571
3.285714286
3
2.142857143
3.714285714
2.285714286
2.857142857
2.285714286
3.142857143
94
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
Total
3.857142857
2.571428571
2.714285714
3.857142857
3
1.571428571
3
3.142857143
3.142857143
1.857142857
3.857142857
3.142857143
2.428571429
3.428571429
2.571428571
1.285714286
4.285714286
3.285714286
3.285714286
3
3.714285714
3.571428571
3.571428571
3.428571429
3
4.285714286
3.714285714
3.285714286
3.571428571
3.140394089
2.5
3
2.8
2.75
2.2
2.75
3
3.5
1.3
2.25
1.3
2.75
2.4
2.75
3
3
2.9
3.5
2.3
2.5
3.3
3.5
3.1
2.75
2
3
3.4
3.25
2.7
3
1.4
1
2.7
4
3
2.75
1.2
3
3
2.75
3.8
3
2.7
3.25
3.2
3.25
1.7
2.5
2.4
2.5
3.6
2.75
2.8
4.25
2.9
2.75
2.5
2
2.594827586 2.875
3
3.333333333
2.666666667
4
2.333333333
2.5
2.666666667
3
3.166666667
1.333333333
3.333333333
3.5
2
3.5
3.166666667
1.333333333
2.5
2.5
3.666666667
3.333333333
3.5
2.666666667
3.333333333
4.166666667
2.666666667
3.5
3.833333333
3.333333333
2
3.014367816
3
4
4.5
5
4.25
5
3
3
3.25
3.333333333
4.25
4.75
2.333333333
2.75
2.25
3
3
1.75
3
3.25
3.75
3
3
3
3
2.25
2.5
2
2.25
3.75
3
3.25
3.75
3.333333333
3.25
3
3
3
3
4
3.5
4
3
3
2.75
2
2.25
2.5
3
3
4.5
3
2.75
3.5
2.333333333
3
4
3
3.25
4
3
2.5
4.25
3
3.75
4.25
3.666666667
4
4.75
3
4.5
5
3.333333333
3.25
5
3.333333333
3.25
2
2.333333333
4.5
4
3
2.75
3.75
2
2
2
3.103448276 3.379310345 3.771551724
3.408163265
3.672108844
2.797278912
3.81292517
2.316666667
2.267346939
2.973809524
3.020408163
2.922789116
2.284353741
3.427210884
3.153741497
2.632653061
3.582653061
2.884013605
1.681292517
3.426530612
2.969387755
2.926530612
3.19047619
3.394897959
3.312585034
3.681632653
3.470748299
3.164285714
3.245578231
3.632993197
3.109863946
2.295918367
3.125557119
APPENDIX G
Pearson’s Correlation Between Students’ Level of Preparedness and Challenges with Flexible Learning Modality
95
Respondents
X
Y
(X-x̅)
(Y- y̅)
1
2
3
4
5
6
7
8
9
12
9
13
11
11
12
11
127
90
125
114
90
142
132
117
-0.82758621
2.172413793
-0.82758621
3.172413793
1.172413793
1.172413793
2.172413793
1.172413793
11.56896552
-25.43103448
9.568965517
-1.431034483
-25.43103448
26.56896552
16.56896552
1.568965517
-9.57431629
-55.24673008
-7.919143876
-4.539833532
-29.8156956
31.14982164
35.99464923
1.839476813
0.68489893
4.719381688
0.68489893
10.06420927
1.374554102
1.374554102
4.719381688
1.374554102
133.841
646.7375
91.5651
2.04786
646.7375
705.9099
274.5306
2.461653
9
10
11
12
13
14
15
16
17
18
19
20
11
10
9
8
12
12
9
10
11
10
10
9
76
121
161
118
93
94
122
130
100
99
152
127
1.172413793
0.172413793
-0.82758621
-1.82758621
2.172413793
2.172413793
-0.82758621
0.172413793
1.172413793
0.172413793
0.172413793
-0.82758621
-39.43103448
5.568965517
45.56896552
2.568965517
-22.43103448
-21.43103448
6.568965517
14.56896552
-15.43103448
-16.43103448
36.56896552
11.56896552
-46.2294887
0.960166468
-37.71224732
-4.695005945
-48.7294887
-46.55707491
-5.436385256
2.511890606
-18.09155767
-2.83293698
6.304994055
-9.57431629
1.374554102
0.029726516
0.68489893
3.340071344
4.719381688
4.719381688
0.68489893
0.029726516
1.374554102
0.029726516
0.029726516
0.68489893
1554.806
31.01338
2076.531
6.599584
503.1513
459.2892
43.15131
212.2548
238.1168
269.9789
1337.289
133.841
(X-x̅) ( Y- y̅)
(𝑋 − 𝑥̅)2
( 𝑌 − 𝑦̅)2
96
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
8
9
9
9
8
10
12
10
12
11
12
9
9
9
10
12
6
9
12
8
9
11
8
10
13
12
9
13
8
149
124
139
100
140
87
115
79
140
125
129
102
141
84
78
109
112
84
131
120
94
134
108
60
127
113
104
120
-1.82758621
-0.82758621
-0.82758621
-0.82758621
-1.82758621
0.172413793
2.172413793
0.172413793
2.172413793
1.172413793
2.172413793
-0.82758621
-0.82758621
-0.82758621
0.172413793
2.172413793
-3.82758621
-0.82758621
2.172413793
-1.82758621
-0.82758621
1.172413793
-1.82758621
0.172413793
3.172413793
2.172413793
-0.82758621
3.172413793
-1.82758621
33.56896552
8.568965517
23.56896552
-15.43103448
24.56896552
-28.43103448
-0.431034483
-36.43103448
24.56896552
9.568965517
13.56896552
-13.43103448
25.56896552
-31.43103448
-37.43103448
-6.431034483
-0.431034483
-3.431034483
-31.43103448
15.56896552
4.568965517
-21.43103448
18.56896552
-7.431034483
-55.43103448
11.56896552
-2.431034483
-11.43103448
4.568965517
-61.35017836
-7.091557669
-19.50535077
12.7705113
-44.9019025
-4.901902497
-0.936385256
-6.281212842
53.37395957
11.21878716
29.47740785
11.11533888
-21.16052319
26.01189061
-6.453626635
-13.97086801
1.649821641
2.839476813
-68.28121284
-28.45362663
-3.781212842
-25.12604043
-33.93638526
-1.281212842
-175.8501784
25.13258026
2.011890606
-36.26397146
-8.350178359
3.340071344
0.68489893
0.68489893
0.68489893
3.340071344
0.029726516
4.719381688
0.029726516
4.719381688
1.374554102
4.719381688
0.68489893
0.68489893
0.68489893
0.029726516
4.719381688
14.65041617
0.68489893
4.719381688
3.340071344
0.68489893
1.374554102
3.340071344
0.029726516
10.06420927
4.719381688
0.68489893
10.06420927
3.340071344
1126.875
73.42717
555.4961
238.1168
603.6341
808.3237
0.185791
1327.22
603.6341
91.5651
184.1168
180.3927
653.772
987.9099
1401.082
41.3582
0.185791
11.772
987.9099
242.3927
20.87545
459.2892
344.8065
55.22027
3072.6
133.841
5.909929
130.6685
20.87545
50
51
52
53
54
55
56
57
58
9
9
9
6
10
6
8
9
8
133
122
136
123
114
129
135
118
92
570
6695
-0.82758621
-0.82758621
-0.82758621
-3.82758621
0.172413793
-3.82758621
-1.82758621
-0.82758621
-1.82758621
17.56896552
6.568965517
20.56896552
7.568965517
-1.431034483
13.56896552
19.56896552
2.568965517
-23.43103448
-14.53983353
-5.436385256
-17.02259215
-28.97086801
-0.246730083
-51.93638526
-35.76397146
-2.126040428
42.82223543
0.68489893
0.68489893
0.68489893
14.65041617
0.029726516
14.65041617
3.340071344
0.68489893
3.340071344
308.6685
43.15131
423.0823
57.28924
2.04786
184.1168
382.9444
6.599584
549.0134
SP=-753.6896552
SSx=170.2758621
SSy=25690.22
97
APPENDIX H
Table of Critical Values: Pearson Correlation
98
APPENDIX I
Curriculum Vitae
99
100
101
102
103
104
105
106
107
108