Schools Division Office
City of Mandaluyong Science High school
SCIENCE AND TECHNOLOGY DEPARTMENT
JUNIOR HIGH SCHOOL DEPARTMENT
E. Pantaleon St., Brgy. Hulo, Mandaluyong City
Online Screen Time a factor in Academic Performance: A
Correlational study with junior science high school students
Proposed Investigatory Project
PROPONENT
CORTEZ, Carmela Joy B.
DE GUZMAN, Maria Gracy E.
JOAQUIN, Prince M.
NERIA, Ianna Chanel Eve P.
PACOG, Princess Gwyneth I.
PADUA, Gavin I.
TEH, Raphael Luis D.
RATIONALE AND BACKGROUND
Due to the COVID-19 that has spread from the People’s Republic of China to 20
other countries within the first 6 weeks of the new decade, the World Health
Organization (WHO) director general declared the novel coronavirus outbreak as a Public
Health Emergency of International Concern (PHEIC) on January 30, 2020 and a
pandemic on March 11, 2020. 1 From the first confirmed case of COVID-19 in the
country on January 30,2020 to the following months, the rapid spread of the COVID-19
virus caused various threats to the country specifically in resuming education. The
pandemic greatly affected our normal life in education making conflicts and arguments
1
https://www.who.int/director-general/speeches/detail/who-director-general-s-opening-remarks-at-the-media-briefingon-covid-19---11-march-2020
arose regarding the implementation of a new normal way of learning. 2 These discussions
pushed the Department of Education to introduce online learning as a way for students to
resume their education, by the means of using available gadgets and platforms such as
Facebook Messenger, Google Classroom, Google Meet, and Zoom, introducing screen
time as a normal factor in an online student’s life.
Notably, too much screen time may have alarming effects on developing the brain
and the student’s performance. A study conducted by the National Institute of Health
showed that those who spent more than two hours a day using screens scored lower on
language and thinking tests. Some children with more than seven hours a day of screen
time also experienced thinning of the brain’s cortex, the area related to critical thinking
and reasoning.3 Due to this, the Department of Education (DepEd) suggested that the
screen time for students who will be attending online distance learning (ODL) classes this
upcoming school year must be limited to 1-4 hours daily depending on their respective
grade levels. Junior High School Science Students, our target audience, has a
recommended screen time of 2-4 hours at maximum.4
However, even with the limit on screen time hours given by the Department of
Education, the combined screen time the students spend on their synchronous, and
asynchronous classes may be a factor that can determine if it affects the student’s
academic performance. This study aims to determine if the number of screen time hours
the Department of Education assigned will affect the academic performance of junior
high science school students.
2
https://mb.com.ph/2020/09/17/academic-freeze-pushed-rejected/
https://edsource.org/2020/distance-learning-stokes-fears-of-excessive-screen-time/644165
4
https://mb.com.ph/2020/09/04/deped-limits-screen-time-for-online-classes/
3
COVID-19
LOCKDOW
IMPLEMENTATIO
N OF NEW
ONLINE/MODULAR/
BLENDED
GRADE/BATC
Communication
with student and
HIGHSCHO
Online exposure =
Screen time
IMPEDES
KNOWLEDGE
RETAINED
HEALTH
ACADEMIC LEARNING
OF STUDENT
LOCALITY (City
of Mandaluyong
Science High
CURRICULUM
SUBJECTS
Figure 1. Theoretical framework
STATEMENT OF THE PROBLEM
The study aims to find the correlation between online screen time and academic
performance among junior science high school students in Mandaluyong City.
The study aims to specifically answer the following questions:
● Is there a correlation between online screen time and academic performance
among junior science high school students?
● Does the number of hours of screen time have a significant effect on the general
average grade of junior science high school students?
● Is there a variation on the online screen time between the students belonging to
the same grade level in junior science high school students?
HYPOTHESIS
NULL
The following null hypotheses will be tested in the study:
● There is no correlation between the online screen time and academic performance
among junior science high school students.
● Online screen time will not affect the academic performance of junior science high
school students.
ALTERNATIVE
Alternatively, the following hypotheses will be accepted if the null hypotheses are not
satisfied in the results:
● There is a correlation between the online screen time and academic performance
among junior science high school students.
● Online screen time will affect the academic performance of junior science high
school students.
This study aims to assess the relationship of online screen time and the academic
performance of junior science high school students. To see if there could be a relationship
between the general average and the number of hours of screen time a junior science high
school student from the City of Mandaluyong Science High School and possibly make a
conclusive statement whether more or less screen time can affect the academic
performance of the students.
CONCEPTUAL FRAMEWORK
INPUT
PROCESS
- The COVID-19 pandemic
made online learning possible,
wherein students are required
to attend classes and do their
schoolworks by the means of
using their laptops, tablets, etc.
that would require them much
more screen time.
- An online survey will be
conducted containing questions
such as, how long do the junior
high school science students
spend their estimated time per
day facing the screen doing
school related activities and
their 1st quarter general
average.
- Junior High School Science
Students from grades 7-10
living or residing in
Mandaluyong City will be the
respondents.
OUTPUT
- Researchers will
determine the correlation of
screen time to the academic
performance of Junior High
School Science students.
- Data from the online survey
conducted will be gathered and
the researchers will get the sum
of the average grades of the
students.
- The researchers will analyze
the data using Pearson R
statistical method.
Figure 2. The Conceptual Framework
GENERAL METHODOLOGY
The research design that will be used by the researchers is a correlational research
design. Since the aim of the study is to assess whether there is a relationship between
online screen time, and the academic performance of junior high school students under
online distance learning (ODL). The correlation of online screen time and academic
performance among science junior high school students whereas the online screen time
and academic performance are the independent variables that involve no manipulation.
The purpose of this study was to determine if there is a significant statistical relationship
between online screen time and academic performance among science junior high school
students.
Data will be collected with the use of a survey questionnaire that will be created by
the researchers and will be conducted through Google forms. The questionnaire survey
will consist of questions that focus on determining the estimated amount of screen time
the junior high school science students spend on doing school related activities, the
amount of requirements each grade level has in a quarter, and their general average for
the first quarter which is the results of their academic performance. The target
respondents will be the Junior science high school students living or residing in
Mandaluyong City within the range of 12 to 17 years of age.
The sampling design that will be used is the multistage sampling design. The sample
population size will be 30 participants per year level. The sample population will answer
a survey that will give the researchers the estimated hours of screen time they spend
doing school related activities on a day-to-day basis for one quarter, and their general
average for the whole quarter. By the means of Microsoft Excel, the researchers will
categorize the data collected based on their respective variables and get the sum of the
general average from the results of the survey. The researchers will then determine which
row contains the data that has the most correlation.
RESEARCH INSTRUMENT
The study will utilize the survey questionnaire as its research instrument which can
be an efficient way of obtaining large amounts of information on a large population.
Using a survey questionnaire will save time. The type of survey questionnaire that will be
used is a Guided Response Type for the responses the researchers will be looking for are
mostly multiple questions. The research instrument aims to measure the respondent’s
estimated amount of screen time per day and their 1st quarter General average
performance.
The survey questionnaire will observe proper rules and guidelines in making a
proper and reliable research instrument. The instrument will then be validated through
face validity where each researcher will have a cursory review on the contents of the test
and also review its construction, hence construct validity. For the Content validity and
the Criterion Validity, it will be validated with the help of the research instructor.
The validation of the survey would be a process in which the researchers would
construct the questionnaire taking in mind the rules and guidelines in making a proper
and reliable research instrument, and would then be checked for Face Validity and
Construct Validity by the researchers. Content Validity and Criterion Validity will be
checked with the help of the research instructor.
For the instrument’s performance, we will then measure its reliability in the form of
alternate form reliability where the researchers will utilize differently worded forms in
which rewording the questions that must address the same aspect of the amount of
screentime and the general average performance. The responses will then be divided into
two question sets where the response will measure the correlation of its results. Wherein
High correlation between the two indicates high alternate-forms reliability.
DATA PROCESSING
The data collected after Data Gathering will result in 2 columns of data. Column 1 will
be the sum of all the averages gathered through the Written Questionnaire, and Column 2
being the corresponding hour of screentime.
This then will be analyzed for correlation using the statistical treatment Pearson R
Linear Correlation, utilizing the Data Analysis Toolpak in Microsoft Excel.
The result of the treatment will be used to evaluate if there would be a correlation
between the two variables, the General Academic Performance of students and the
Number of Hours of Online Screen Time.
Figure 3. Sample Data Analysis
Figure 3. Sample Data Analysis