A Pragmatic Approach to the Usage of Digital Devices in Education in Developing
Countries
Dr.Deepshikha Aggarwala, Dr Deepti Sharmab, Dr Archana B. Saxenac a
Professor of Information Technology, Jagan Institute of Management Studies, Delhi, India
b
Associate Professor of Information Technology, Jagan Institute of Management Studies, Delhi, India c
Professor of Information Technology, Jagan Institute of Management Studies, Delhi, India Article History: Do not touch during review process(xxxx)
_____________________________________________________________________________________________________ Abstract: The world has faced one of the most catastrophic times for the human race with the COVID – 19 pandemic over the recent past and it’s still not over. During these times, technology has played a vital role in helping the mankind. We have seen the technology being embedded in all aspects of our lives right from communication, working, medical assistance to online education. The education sector has been at the forefront of technology adoption during this year as all schools and colleges were closed worldwide and we switched to the online mode of education. The adoption of digital mode of education has been difficult for many people especially in developing countries where this mode of education is still new. There have been various challenges faced by the education sector during the process of transition from physical classes to online mode. (Aggarwal, Using the Technology Acceptance Model to Understand the Use Bring Your Own Device (BYOD) to Classroom, 2018) Researchers always believe that adoption of any technology should be supported by the users’ acceptance of the technology and one of the most popular frameworks to predict user acceptance of technology is the Technology Acceptance Model (T AM) proposed by Davis (C. H. Davis, 2005). The paper describes the study conducted with the purpose of finding the impact of various factors on the adoption of the Usage of digital devices in education in developing countries based on TAM variables o f perceived ease of use, perceived usefulness and behavioural intention to use. Additional external variables have been adopted to study the user acceptance of Usage of digital devices in education on the basis of the stakeholders’ perspective towards the matter. This paper has adopted a pragmatic approach to understand the usage of digital devices in the educational paradigm of developing countries. The objective is accomplished by proposing a modified TAM (Technology Acceptance Model) (Aggarwal, Mobile Technology Adoption by Indian Consumers, 2019). In order to contextualize the research, a two -step approach was followed. First a set of interviews was conducted to identify the factors influencing the users while using the digital devices for teaching and learning. On the basis of these interviews, a questionnaire was prepared and distributed among 300 actioners that are using digital devices in their daily educational chores. Total 272 responses were collected and the mo del is based on these responses. The results indicate that the intention to use digital devices for education depends on the perceived usefulness and perceived ease of use which are influenced by factors such as ease of access to resources, technical skills of the user, student teacher interaction, privacy & security, infrastructure support and impact on health.
Keywords: TAM, Online education, digital devices, technology adoption, eLearning
1. Introduction
Development in technology has led to the transformation of education in a positive way and led to the improvement of administration and effectiveness of teaching. The growth in the field of online education has drastically increased in 2020 due to the Covid 19 pandemic when the whole world came to a lockdown situation for months and the education sector was literally forced to transform the teaching to online platforms. The recent decades have otherwise also seen an increased interest in online learning especially in the developing countries (Teo, 2019). The major reason for the interest of students in online education especially at the higher education level is that the students are able to continue education even when they are working on their job or are staying in regions where higher education facilities are limited. Initially the online education was limited to the usage of computers. But with the advent of various mobile devices such as laptops, tablets and smartphones, online education has become mobile education. In this paper, we explore the usage of various digital devices for education and study the perspective of various stakeholders towards digital education.
The countries with traditional education system are also coming up with upgradations in their policies. A good example of this is the NEP (New Education Policy 2020) unveiled by Ministry of MHRD (Ministry of Human Resource), India where one of the key aspects of “Digital India” is “Online Education” adoption and implementation. The government plans investments in digital infrastructure, emphasis on developing online tools and learning platforms, establishment of digital labs to train the teachers towards adoption of these platforms (Mitra& Singh, 2020) (National Education Policy 2020, 2020).
Though the above section highlights the importance of online education but the advancement and investment in technology does not always assure the acceptance and implementation by the masses. There are various factors that contribute the acceptance of technology among traditional populations. A very popular model is TAM (Technology Acceptance Model) which is a theoretical model that defines how users accept and use a new technology (Taherdoost, 2017).
This paper explores the use of various digital devices in the education system in developing countries. The research has been conducted by collecting data from different stakeholders like Students, Teachers and Parents who could provide their feedback and opinion on the adoption of digital devices for education. Certain reliability tests were performed on the questionnaire before it was circulated among the population. The factors selected for model building were based on TAM features of Perceived Usefulness and Perceived Ease of Use. Formulation of hypotheses and their testing is done with the help of Correlational Analysis. The results can be used to enhance the applications of digital devices in the education sector.
2.Literature review
The educationists worldwide have been making continuous attempts to include technology in education (Yee, 2009). Today when technology is supporting all walks of life, there has been a tremendous increase in usage of technology supported education. Though there remains a considerable gap in integrating technology with education especially in countries where most of the education system is traditional. There is a lack of understanding for various tools and methods that can be utilized for online education system and therefore a need for prediction of utilization and acceptance of technology in education exists.
Indian education system has been receiving considerable appreciation for its new education policy of skill-based education. It has jumped five ranks up in the WEFFI (Worldwide Educating for the Future Index, Published by Economist Intelligence Unit) for the performance in education sector in the year 2019 (Education, 2020). The credit for this performance goes to our education system that constantly modifies itself to incorporate changes. It is commendable that our educational system has upgraded drastically and stayed steady even in the difficult times of Covid -19 pandemic. Digital devices can acclaim this educational victory as they played a significant role in continuing education delivery through Online Model (De’, Pandey,, & Pal, 2020). It has been quoted by one of the leading online sellers that the sale of mobile phone has seen a sharp spike of 109% in the Covid-19 times. It includes both brand new and pre owned devices (Bhatia, 2020). Development in technology has led to the transformation of education in a positive way and led to the improvement of administration and effectiveness of teaching ( Ghavifekr, Athirah, & Rosdy, 2015). Although Digital education was practiced voluntarily in India before as well at Primary and Higher-level education levels but in the times of Corona pandemic when the whole world came to a lockdown situation for months, people were literally forced to transform the education system to online platforms using Digital Devices.
Another trend that can be noticed in the Education system is the sharp increase in the interest of people in distance education and online learning especially in the developing countries ( Huang & Teo, 2019) . The major motivation behind this alteration is the time and comfort flexibility that is offered in distance education and availability of Digital Devices in affordable range with all required benefits ( Hiltz & Turoff, 2005). People are much comfortable with this system as they can continue their work while completing studies in their suitable times. Distance education is a boom for students who are staying the regions that just don’t offer very promising higher education institutions and movement from the region is not just feasible for these scholars. Initially the online
education was limited to the usage of computers. But with the advent of various mobile devices such as laptops, tablets and smartphones, online education has become mobile education ( Basilaia & Kvavadze, 2020). The learners have a lot of flexibility regarding the means they wish to incorporate for learning. ( Reynolds, 2011). 3. Technology Acceptance Model (TAM)
The Technology Acceptance Model is a well-known model used by the researchers who wish to study the influence of various factors on the acceptance of a new technology among the users. This model is the baseline to understand whether the users will accept a technology and use it or not. TAM indicates that the intention of users to accept and use a technology is called the behavioural intention of use. It is determined by perceived ease of use and perceived usefulness. The three main components of TAM are therefore the following:
• BEHAVIOURAL INTENTION OF USE
Behavioural intention of use is specified as the probable user’s intention to accept and use a new technology. A user would consider various factors before accepting a technology and this is what the TAM focuses on. The intention to use a system leads to the actual use and therefore behavioural intention to use is tested before a new technology is adopted. Behavioural intention to use depends on perceived usefulness and perceived ease of use along with certain external factors that depend upon the type of technology that is being introduced.
• PERCEIVED USEFULNESS
Perceived Usefulness is specified as the potential user’s assessment about the use of a technology or system in terms of how useful the new technology for their tasks will be. A user would adopt a technology only when he/ she perceives that it would be useful for them and they would be better off with technology rather than without it. In other words, it is the extent to which a person imagines that using a specified technology would enrich his or her job performance. Therefore, perceived usefulness will influence the behavioural intention to use a technology.
• PERCEIVED EASE OF USE
Perceived Ease of Use indicates the level to which the probable user expects the technology/ system to be easy to learn and use. PEOU is defined as the perception of a person about whether learning and adapting the new technology would be easy or not. A person would be willing to adopt a technology if he/ she feels that they can learn to use it easily. Therefore, perceived ease of use would influence the behavioural intention to use a technology.
4.Theoretical Framework Based on TAM
Technology Acceptance Model (TAM) and its modified versions have been used by different researchers in their studies and this model is useful in establishing the acceptance of different technologies by stakeholders.
Figure 1: Version of TAM by Venkatesh & Davis
The TAM model version as shown in Fig 1 is an effective theoretical model used by various researchers to study the acceptance of a new technology in different sectors including education. The idea of using TAM to study technology acceptance by users is to determine the factors that are responsible for influencing the users for adoption of the new technology. These factors are determined by the intention of users to use a new system which is taken as a variable called Behavioural Intention to Use (BIU). The intention to use a technology is determined
by the variables of perceived usefulness (PU) and perceived ease of use (PEOU) (Yee, 2009). In determining the usage of digital devices for education, the BIU signifies the extent to which the stakeholders including the students, parents and teachers plan to use or not to use digital devices for learning related activities. TAM considers that the users accept actual use of a new technology when they consider it to be useful for them and easy to learn and use (Lee, 2003).
5. Purpose of the Study
Many researchers have given modified versions of TAM to accommodate different factors that are assumed to be influencing the user acceptance of technology. The current study has been undertaken to explore the usage of digital devices in education in developing countries. We have applied an extended version of TAM to explore the digital devices’ usage in education. We have taken this study in the perspective of developing countries. When using the Technology Acceptance model for the study, we have used Perceived Usefulness and Perceived Ease of Use from the traditional TAM.
The current study is conducted with the intention to identify the factors that encourage the stakeholders to use digital devices for education purpose and also to understand the reasons that lead to difficulties in the adoption of digital learning. In countries like India, where we follow a traditional education system with teaching and learning happening mostly in physical mode, adoption of digital education tools is not as easy as in the countries where the students are used to carrying their digital devices like laptops, tablets, etc. to schools. The current scenario is completely different because we were forced to transform the complete education system to online mode and the progress done is unbelievable. We have been able to digitize the education right from elementary school level to higher learning institutes. It is therefore important to make a proper framework so that a well-defined teaching pedagogy using digital devices is formulated.
6. Research Methodology
This paper takes a pragmatic approach to research where we have taken both quantitative and qualitative study process in which the data was collected using a questionnaire and set of interviews to explore the perception and intention of students, teachers and parents for using digital devices in education. We have not only considered the role of students in the study but given weightage to the aspect of teachers and parents too. This is because every stakeholder plays a role in the adoption of digital education. The process followed for this research has been divided into following stages:
DATA COLLECTION
Data collection is done in following steps
The data was collected using an online questionnaire. The questionnaire was prepared after conducting a set of interviews with different stakeholders. The major stakeholders in the process of implementing digital education are the students, teachers, parents and the management of the school/ college. For this paper we have taken into consideration the following stakeholders:
Students Teachers Parents Data Collection
Identification of factors
Reliability test for the factors Correlation Analysis of factors
Deriving Results
Interviews
with
stakeholders
Developing a
questionnaire
Collecting data
through
questionnaire
Since we had planned on using the TAM for this study, we conducted the interviews with the stakeholders to identify the external factors that are important for the adoption of digital devices for education.
Observations of the interviews
The interviews were conducted to formulate the questionnaire. The basic elements of TAM such as perceived ease of use and perceived usefulness are already applicable for the study so included in the questionnaire. Apart from these the following categories of questions were asked:
1) Questions related to “What makes using the digital education more useful than traditional methods?” The answers received for this question indicated towards ease of access to resources online. Therefore, this factor was included in the questionnaire.
2) Questions related to “What are the prerequisites to effectively use digital devices for education?”
The interviewees answered in terms of the technical skill requirements and internet infrastructure requirements. This led us to include the factors of technical skills of the user and infrastructure support in our questionnaire.
3) Questions related to “What are the issues and problems with using digital devices for education?” The answers to these questions related to doubts of the users about their privacy and security while using digital devices.
During the discussion with the interviewees, we also found that impact on health due to long exposure to digital devices also is an important factor and should be included in the questionnaire. Also the social interaction including the student teacher bonding is also an important factor of the education system.
Based on observations, the questionnaire is designed. We have identified the following factors that are influencing the users towards adoption of digital learning.
Ease of Access to resources Technical Skills of the User Student Teacher interaction Privacy & Security Infrastructure support Impact on health
7. Extended Version of Technology Acceptance Model
Based on the identified factors, we designed the questionnaire to create our extended TAM model. The factors here are divided into 2 categories.
Traditional TAM factors Perceived Usefulness Perceived Ease of Use Behavioral intention to Use External Factors
Ease of Access to resources Technical Skills of the User Student Teacher interaction Privacy & Security Infrastructure support Impact on health
The questionnaire includes the questions based on all the above factors and the results of the analysis would indicate which factors have more influence on the users.
The questionnaire was distributed online to 300 people out of which 280 people responded. We selected 272 responses that were complete.
Table 1: Factors affecting the adoption of digital devices in education
Factors Questions Description
Perceived Usefulness
PU1 Using the Online learning platforms for learning/ teaching saves travel time to school/ college.
PU2 Using the Online learning platforms for learning/ teaching enables learning from far off sources.
PU3
Using the Online learning platforms for learning/ teaching is only useful at the times such as a pandemic when people have to stay at home.
Perceived Ease of Use
PEOU1 Learning to use the Online learning platforms for learning/ teaching is easy for new users.
PEOU2 Searching courses and content of choice is easy with the Online learning platforms.
PEOU3 It is easier to learn/ teach using the Online learning platforms rather than traditional/ physical teaching methods.
Ease of Access to resources
PE1 Using Online learning platforms for learning/ teaching gives access to tremendous learning resources and tools.
PE2 Online learning platforms make assessment and evaluation easier.
PE3 Transition from traditional learning/ teaching to online learning/ teaching is easy.
Behavioural Intention to Use
BIU1 Intention to continue using Online learning platforms for learning/ teaching in future
BIU2 Intention to learn/ teach through Online learning platforms even when traditional methods are available.
BIU3 Recommending others to use Online learning platforms for learning/ teaching.
Technical Skills of the User
TSU1 People having good technical skills have a better learning/ teaching experience on Online learning platforms
TSU2 People with good technical skills find it easy to search learning content online
TSU3 People with good technical skills are able to keep their data safer online
Student Teacher interaction
ST1 bonding. I feel the online learning platforms prevent student teacher
ST2 more participative in class. Online learning platforms enable introvert students to be
Privacy & Security
PS1 I feel that my personal information is safe on online learning platforms
PS2 I feel confident in making payments through online learning platforms.
Infrastructure support
IS1 Having a good internet connection is most important on online learning platforms
IS2 I feel the cost of learning through online learning platforms increases due to the need for devices and internet connectivity.
Impact on
health
HI1 Using online learning platforms leads to sedentary lifestyle and is harmful to the health of the users.
HI2 Using online learning platforms leads to long exposure to electronic devices and is harmful for the eyes.
Figure 2: Factors affecting the Intention to use digital devices in education Summary of participants PARTICIPANT COUNT Student 105 Teacher 62 Parent 73
Both Parent & Teacher 32
TOTAL 272
User usage of digital devices for education before Covid-19 pandemic
Reliability of the Factors
The reliability of the factors is checked through Cronbach Alpha. Perceived Usefulness
Perceived Ease of Use
Intention to use digital devices in education
Ease of Access to resources Technical Skills of the User
Student Teacher interaction Privacy & Security
Infrastructure support
Impact on health
Actual System Use
Summary statistics:
raw_alpha std.alpha lower alpha
G6(smc) average_r mean sd upper
95% confidence bo undaries
0.82 0.81 0.76 0.83 0.32 3.9 0.57 0.81 0.85
raw_alpha: Cronbach’s α (values ≥ .7 or .8 indicate good reliability; (Kline, 1999) std.alpha: this should be similar to raw_alpha
G6: Guttman’s lambda 6 (calculated from the squared multiple correlation or ‘smc’) average_r: average inter-item correlation (this is used to calculate std.alpha) mean: scale mean (the mean of the means of all individuals)
sd: scale sd
Reliability if an item is dropped:
raw_alpha std.alpha BIU 0.78 0.78 PEOU 0.78 0.78 ST 0.77 0.77 H 0.79 0.79 TSU 0.78 0.78 IS 0.82 0.82 PE 0.80 0.80 PU 0.78 0.77 PS 0.79 0.79
The overall α (raw_alpha) is .82. Each row refers to different factors and a raw alpha associated. This refers to the value of overall α when a particular factor is dropped/deleted from the analysis. The first row refers to BIU, and if it is dropped, the overall α becomes .78, which reflects lower reliability, therefore we keep this factor. Similarly we see that all other factors are important to have the reliability of 0.82. We do not drop any factor at this stage.
We are checking whether any of these raw alpha values are greater than the overall α of .82; if yes, this means that dropping that particular item will increase the overall α of the scale.
The other columns of this table refer to how the other statistics will change if that particular item is dropped/deleted.
Item statistics
N raw.r std.r r.cor r.drop mean sd
BIU 272 0.70 0.67 0.64 0.56 3.6 1.14
PEOU 272 0.68 0.67 0.64 0.58 3.9 0.86
ST 272 0.72 0.71 0.69 0.61 3.8 0.96
TSU 272 0.66 0.66 0.60 0.54 4.0 0.93
IS 272 0.38 0.41 0.28 0.24 4.4 0.80
PE 272 0.57 0.57 0.47 0.43 3.5 0.92
PU 272 0.71 0.72 0.69 0.61 4.0 0.80
PS 272 0.63 0.63 0.59 0.50 3.9 0.87
raw.r: correlation between the factor and the total score from the scale (factor-total correlations)
r.drop: total correlation without that factor itself (i.e., rest correlation or corrected factor-total correlation); low factor-factor-total correlations indicate that that factor doesn’t correlate well with the scale overall
r.cor: factor-total correlation corrected for factor overlap and scale reliability mean and sd: mean and sd of the scale if that factor is dropped
All factors should correlate to the total score, so we look for factors that do not correlate with the overall score from the scale. If r.drop values are less than about .3, it means that particular factor doesn’t correlate very well with the scale overall.
The factor of Infrastructure Support is having the r.drop value of 0.24 which is less than 3. This indicates that infrastructure support does not correlate well with the overall scale. Therefore we can drop this factor in the analysis. Though after correlation analysis it was found that this factor is highly correlated to the behavioural intention to use digital devices for online learning and we have not deleted this factor.
8. Formulation of hypothesis
The hypotheses have been formulated on the basis of TAM. We have researched on the impact of various factors on perceived usefulness and perceived ease of use for digital devices in education which would suggest the behavioural intention of the users and ultimately define the success of adoption of digital education. The factors are:
Ease of Access to resources Technical Skills of the User Student Teacher interaction Privacy & Security Infrastructure support Impact on health HYPOTHESES
H1: Ease of Access to resources positively impacts the Perceived Usefulness of using digital devices for education.
H2: Technical Skills of the User positively impacts Perceived ease of use of digital devices in education H3: Student Teacher interaction impacts the Perceived ease of use of digital devices for education. H4: Privacy & Security impacts the Perceived Usefulness of using digital devices for education. H5: Infrastructure support positively impacts Perceived ease of use of digital devices in education H6: Impact on health impacts the Perceived Usefulness of using digital devices for education.
H7: Perceived Usefulness positively impacts the behavioural intention of using digital devices for education.
H8: Perceived ease of use positively impacts the behavioural intention of using digital devices for education.
MODEL FOR HYPOTHESIS TESTING
Figure 3: Extended version of TAM
The likert scale values for the factor “Impact on health” are reversed as the questions framed for this variable are considering the negative effects of the usage of digital devices.
Correlation between the factors
IS PS PE H ST TS U PU PE OU BIU IS 1.00 0 0.03 8 0.01 9 0.28 3 0.15 3 0.30 9 0.13 1 0.20 3 0.72 5 PS 0.03 8 1.00 0 0.27 3 0.11 7 0.35 2 0.27 7 0.58 1 0.17 7 0.23 2 PE 0.01 9 0.27 3 1.00 0 0.19 2 0.34 8 0.31 9 0.33 4 0.16 2 0.23 7 H 0.28 3 0.11 7 0.19 2 1.00 0 0.22 6 0.22 3 0.41 3 0.30 0 0.68 4 ST 0.15 3 0.35 2 0.34 8 0.22 6 1.00 0 0.52 7 0.58 3 0.50 7 0.30 5 TS U 0.30 9 0.27 7 0.31 9 0.22 3 0.52 7 1.00 0 0.31 3 0.75 3 0.32 2 PU 0.13 1 0.58 1 0.33 4 0.41 3 0.58 3 0.31 3 1.00 0 0.62 4 0.73 2 PE OU 0.20 3 0.17 7 0.16 2 0.30 0 0.50 7 0.75 3 0.62 4 1.00 0 0.75 7 BIU 0.72 5 0.23 2 0.23 7 0.68 4 0.30 5 0.32 2 0.73 2 0.75 7 1.00 0 Perceived Usefulness Perceived Ease of Use Intention to use digital devices in education Ease of Access to resources Technical Skills of the User Student Teacher interaction Privacy & Security Infrastructure support Actual System Use Impact on Health
RESULTS
The hypotheses are tested through data analytics technique of correlation. The correlation analysis is used to establish the relationship between two variables. In this research, we have used Pearson’s correlation to test the hypotheses. A positive correlation indicates that the factors are related well to each other. A Pearson’s correlation value of greater than 0.5 indicates a strong correlation between the factors.
Hypothesis Pearson’s
Correlation
Result H1: Ease of Access to
resources positively impacts the Perceived Usefulness of using digital devices for education.
PE>>PU = 0.334 Hypothesis Rejected
The ease of accessing the resources on digital devices does not make the users much inclined towards digital education. H2: Technical Skills of
the User positively impacts Perceived ease of use of digital devices in education
TSU>>PEOU=0.753 Hypothesis Accepted
The users with good technical skills find it easier to adopt digital devices in education.
This leads to the suggestion that proper training is required for all the stakeholders to make digital education effective.
H3 : Student Teacher interaction impacts the Perceived ease of use of digital devices for education
ST>>PEOU = 0.507 Hypothesis Accepted
Interaction between the students and teacher is an important aspect of traditional education system. If we have tools to enhance the student teacher interaction, we can develop a more effective digital education system.
H4: Privacy & Security impacts the Perceived Usefulness of using digital devices for education.
PS>>PU = 0.581 Hypothesis Accepted
Using digital devices always raises the privacy concerns among the users about their personal data. Adequate privacy features increase the usefulness of digital devices.
H5: Infrastructure IS>>BIU = 0.725 Hypothesis Accepted
0% 20% 40% 60% 80% 100% IS PS PE H ST TSU PU PEOU BIU
Correlation between Factors
support positively impacts the behavioural intention of using digital devices in education
Support in terms of infrastructure such as internet connectivity and appropriate hardware and software would positively impact the users to adopt digital learning. H6: Impact on health
negatively impacts the behavioural intention of using digital devices for education.
H>>BIU = 0.684 Hypothesis Accepted
In spite of the benefits discussed, the overuse of digital devices may impact the health of the users in a negative manner. Therefore it raises concern for the stakeholders while adopting digital education. Proper guidelines need to be in place in order to minimize the negative impact on user health due to the usage of digital devices.
H7: Perceived
Usefulness positively impacts the behavioural intention of using digital devices for education.
PU>>BIU = 0.732 Hypothesis Accepted
While using the TAM, perceived usefulness of a technology impacts the intention of users to adopt it.
H8: Perceived ease of use positively impacts the behavioural intention of using digital devices for education.
PEOU>>BIU = 0.757 Hypothesis Accepted
While using the TAM, perceived ease of use of a technology impacts the intention of users to adopt it.
9. Conclusion
The college environment plays an important role in shaping sustaining healthy eating habits among youngsters. Since prospective teachers are the upcoming teachers who will be the role model for their school children, they can promote valuable nutritional information through their own daily food practices. College campus, canteen and college dining halls plays a crucial role in guiding dietary eating environments among students. Display of information about healthy diet in the college notice boards provides knowledge to a large number of socio economic and cultural backgrounds. The continuous healthy eating habits effective policies and managerial strategies followed inside the college campus helps to fight malnutrition such as obesity, anorexia , and micro-deficiency. Proper diet and physical activity will lead to maintain healthy weight and lifestyle among Prospective teachers. Diets rich in high fibre reduce the risk of obesity and various health problems. Healthy dietary habits help to maintain good physique, relieve stress, stroke prevention, improve learning, mental health, build better mood, and self-esteem. Parents also influence more in their children’s food preference through their verbal dietary comments and restrictions employed in consuming un healthy food items. Consuming fruits and vegetables are
one of the important healthy behaviours to achieve one’s optimal physical function. Social media plays a vital role
in encouraging healthy eating behaviours through various traditional cooking programs, advertisements, talk shows, debates, panel discussion etc. Parents continuous monitoring of their wards is very important in maintaining good health. Thus constant practice, knowledge and monitoring of the health practice of the college students will create a healthy nation.
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