View of Psychological Impact of Online Learning on Mental Health of College Students in Chennai

Research Article

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Psychological Impact of Online Learning on Mental Health of College Students in

Chennai

Dr.C.K. Deepa1_{, Dr.R.Lakshmi}2_{, Ms. Dhivya devi}3_{, Dr. S.Amirthalingam}4

1_{HOD, PG and research department,} 2_{Asst. Professor, Department of Commerce,}

3_{Asst Professor, PG and research,Department, S.S.S. Shasun Jain College for Women, Chennai.} 4_{Asst. Professor, Gurunanak College.}

Article History: Received: 11 January 2021; Revised: 12 February 2021; Accepted: 27 March 2021; Published online: 10 May 2021

Abstract:

The whole world is affected by covid and that changes the entire activities including the student community. This scenario envisages a psychological impact on the students about their career. Learning becomes difficult for students who are resided in remote areas. We must thank the government as well as the higher education authorities to take immediate action regarding the continuance of learning through online. Though it is helping the students at a large but still students facing the problems in various factors which may include technical, environmental, and psychological and health problems. Thus, this research is mainly focusing on the impact of online learning and their impact on students' mental health. A well-structured questionnaire covering all the factors is constructed and circulated to college students through Google forms. Nearly 282 respondents received and the data is analyzed through SPSS. We found that there is a close relationship between the technical factor and mental health of college students.

Key words: online learning, Technical factors, environmental factors, psychological factors Introduction

Globally the people get affected due to the Corona which affected many sectors intensively including education. Many colleges and schools had to come with new teaching pedagogy which includes mainly online learning. Learning through new technologies which initially motivated students and gradually the interest got stuck due to some psychological factors. This research is mainly focused on the relationship between mental health and online learning. Taking the above, we delve into finding out the relationship we have circulated a well- structured questionnaire among the college students. Nearly 282 students responded to this research. The findings have proved that Male students have better attitudes towards factors rather than Female students. The impacts we found were E-learning will not encourage cooperation among the students through online classes and it is proved that the students are affected due to online learning and it has a major impact on their mental health as well as behavioral changes.

Objectives:

1.

To study the demographic characteristics of the respondents.

2.

To know the ratio of students who are comfortable with online learning.

3.

To understand the problems and challenges faced by students in online learning.

4.

To analyse the behavioral changes in the students due to online learning

5.

To analyse the impact of online education on students’ health and other social factors.

6.

To suggest measures to overcome these challenges.

Review of Literature

Najmul Hasan and Yukun Bao (2020) assessed the impact of elearning on psychological stress among students during the pandemic. Kessler psychological distress scale (K10) was used to evaluate stress symptoms. He conducted the survey online among 435 students in Bangladesh. According to the results, elearning has a significant impact on psychological stress of students. Fear of academic year loss and ineffective elearning systems are the most crucial factors responsible for this psychological stress. Students showed high levels of anxiety due to elearning during lockdown.

Pravat Kumar Jena (2020) focused on how online learning is beneficial during crises like pandemic. He pointed out the perceptions of learners on online learning systems during lockdown. Online learning encourages more productive use of time for both educators and learners. Digital recordings of online sessions can be saved for future reference. It is not possible for all the students to have sufficient

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knowledge, skills or resources. If students spend more time online, they may become vulnerable to unwanted information. Low income families may not be able to afford internet connection or electronic gadgets for online learning. Students may face poor data connectivity issues or slow network. Online learning may lead to laziness among students as they are at home most of the time. They may feel lonely and may not be in a position to share their views with peers. They may not be self-disciplined. There may not be an effective interpersonal relationship between the teacher and the students due to lack of face to face meeting.

Pinaki Chakraborty, Prabhat Mittal, Manu Sheel Gupta, Savita Yadav and Anshika Arora (2020) conducted a survey among 358 undergraduate students to understand their opinion on different aspects of online education during the pandemic. The survey was conducted using a questionnaire with 20 statements related to interaction, health and social impact due to online education. Most of the students responded that they have been suffering from depression and stress thus leading to negative impact on the mental health of the students. Lack of motivation and negative emotions are the factors that led to less focus by students on online education. Students in remote areas did not have proper access to technology and communication. These students faced difficulty in adapting themselves to online education. Some students live in houses that are not spacious and hence face problems in attending online classes. 66% of students felt that online education is affecting their health and causing the fear of losing internet connectivity. 82% felt that over use of electronic devices and screen time affected their sleep. They also felt that online education has negative social implications and is affecting the daily routine life of their family.

Data analysis and interpretation

A well-structured questionnaire is circulated through google form to college students across chennai. Nearly 282 forms were received and we have used the latest version of spss for analysis of collected data. Convenient sampling method is used for this research.

Table 1 : DEMOGRAPHIC FACTORS

Gender Male Female 125 157 Age 17-19 20-21 More than 21 203 67 12 Family Income Less than Rs.20,000 More than Rs.50,000 Rs.20,000 - Rs.50,000 112 76 94 Stream

Commerce Science Others

152 123 7

Type of College

Government Self-Finance Distance Education

97 160 25 Year of Degree I UG II UG III UG PG 98 69 75 36

Source: Primary data Inference:

It is identified from the above table that nearly 125 male and 157 female college students are actively participating in this research. The age group of 17-19 are found more in this demographic profile. Further to that there is moderate participation of commerce as well as science stream students are there in this research. In addition there is more that 50% of students who have taken part in this research are from self financing institutions, in that first year students are found more in this demographic analysis.

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Table 2. RELIABILITY TEST

KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling

Adequacy. .834

Bartlett's Test of Approx. Chi-Square 575.787

Sphericity df 10

Sig. .000

Source: Primary data

Inference

Bartlett's test is used to test the assumption that variances are equal. The test is easy to implement and produces valid results, assuming data points are randomly sampled from a normal distribution. The Significance value 0.001 shows the Reliability of the Data.

Table 3 T test for significant difference between Male and Female with respect to Factors affecting through online Class

Factors affecting through online Class

Gender t value P value

Male Female Mean SD Mean SD Psychology 2.20 0.777 1.94 0.617 1.056 0.029** Environment 2.22 0.761 2.03 0.645 2.295 0.022** Technical 1.81 0.726 1.67 0.593 1.733 0.007** Human 2.00 0.762 1.83 0.598 2.046 0.042* Health 2.06 0.704 1.82 0.594 3.134 0.002**

Source: Primary data

Note : 1. ** denotes significant at 1% level

2.

* denotes significant at 5% level Null Hypothesis H0: There is no significant difference between Male and Female with respect to Factors affecting through online Class

Inference:

The P value is less than 0.05, the null hypothesis is rejected at 5 % level of significance with regard to all the Factors affecting through online class. Based on the Mean Score the Male Students have a better attitude towards all the factors than the Female Students. This shows that Male Students are less affected in all the factors when comparing the Female Students.

Table 4 ANOVA for significant difference among Time spend in online class with respect to Factors affecting through online Class

Factors affecting through online Class F value P value

Psychology 3.948 0.004** Environment 2.071 0.085 Technical 2.815 0.026* Human 2.750 0.029*

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Health

2.823 0.025* Source: Primary data

Note : 1. The value within bracket refers to SD

2.

** denotes significant at 1% level

3.

* denotes significant at 5% level

Null Hypothesis H0 : There is no difference among Time spend in online class with respect to Factors affecting through online Class

Inference:

The P value is less than 0.05, the null hypothesis is rejected at 5 % level of significance with regard to all the Factors affecting through online class except Environment. Some of the reasons behind it: They may not get an equal chance of participation in Q&A and class discussion, the home environment doesn’t give the ambiance of the classroom . E-learning will not encourage cooperation among the students through online classes.

Table 5 Chi-square test for Level of comfortable with online mode of learning between Gender.

Yes No Chi-square value P value Male 105(59%) 20(16%) 1.983 0.009** Female 74(41%) 83(84%)

Source: Primary data

Note : ** denotes significant at 1% level

Null Hypothesis H0: Level of comfort with online mode of learning is equally distributed. Inference:

P value is less than 0.01, the null hypothesis is rejected at 1% level of significance. Hence we can conclude that Level of Comfortable with online mode of learning is not equally distributed. Based on percentage, the majority of Male Students feel comfort with online Class.

Table 6 Karl Pearson Correlation Coefficient between Factors Affecting Online Classes

Psychology Environment Technical Human Health

Psychology 1.000 0.216** 0.533** 0.184** 0.496**

Environment - 1.000 0.246** 0.033 0.282**

Technical - - 1.000 0.174** 0.467**

Human - - - 1.000 0.185**

Health - - - -. 1.000

Source: Primary data

Note : ** denotes significant at 1% level

Null Hypothesis H0: There is no relationship between Factors Affecting Online Classes Inference:

Correlation Coefficient between EP and OC is 0.533 which indicates (0.5332 _{= 0.284)}

28.4 percentage positive relationships between Technical Factor and Psychology Factor and issignificant at 1% level. In Same way other pairs such as Environment and Psychology, Human and Psychology, Health

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and Psychology, Technical and Psychology, Technical and Health, Technical and Human, Human and Health, Environment and Health and Environment and Technical are having Positive Relation between them. Thus there is a predominant impact of this technical factor on the mental health of students is proved statistically.

Major Findings:

● Male Students are less affected in all the factors when comparing the Female Students. ● E-learning will not encourage cooperation among the students through online classes. ● The majority of Male Students feel comfort with online Class.

● Apart from all the factors mentioned, technical factors which make a predominant impact on the mental health of students.

Suggestions

● Students can go for yoga to reduce their stress

● The Teacher and student relationship can be encouraged through arranging workshops for stress management.

● Teachers can build a personal connection with the students and understand their expectations.

● Teachers can split the class into smaller units and conduct ice breaking sessions. This will help the students to share their opinion and experience.

● Technical know-how can be taught to students for their ease of learning ● Introducing interesting games related to lesson will reduce stress ● Comfortable intervals between classes can encourage students.

● Right planning and support systems from family can ensure that their child can adjust to the changing environment.

Conclusion

The covid scenario continues still today and people are in fear of this virus. We are waiting to get rid of this situation and continue a normal life. Specifically the students community is affected by this at large. The entire student community is continuing their learning through digital. There are so many factors which disturbs their learning through online, like the environment factors which includes the situation that exists in home, the sounds due to public meetings and so on which may affect the mental health of a student. Taking into consideration this research is conducted to find psychological impact on online learning. The statistical evidence proves that there is a close relationship between mental health and online learning. Thus much care should be taken by both parents and teachers to get rid of this. They must create a situation where students feel comfortable and enjoy their learning. The utmost responsibility rests with the hands of teachers and parents to take care of their students and bring them back to normal and encourage them to achieve their goals.

References:

● Chakraborty, P, Mittal, P, Gupta, MS, Yadav, S, Arora, A. Opinion of students on online education during the COVID‐19 pandemic. Hum Behav & Emerg Tech. 2020; 1– 9. https://doi.org/10.1002/hbe2.240

● Jena, Pravat. (2020). ONLINE LEARNING DURING LOCKDOWN PERIOD FOR COVID-19 IN INDIA.

● Hasan N, Bao Y. Impact of "e-Learning crack-up" perception on psychological distress among college students during COVID-19 pandemic: A mediating role of "fear of academic year loss". Child Youth Serv Rev. 2020 Nov;118:105355. doi: 10.1016/j.childyouth.2020.105355. Epub 2020 Aug 12. PMID: 32834276; PMCID: PMC7422835.

● ttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7422835/

● https://www.researchgate.net/publication/342123356_ONLINE_LEARNING_DURING_ LOCKDOWN_PERIOD_FOR_COVID-19_IN_INDIA

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