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Psychological Impact of Online Learning during the COVID-19 Pandemic: A Case Study on Vocational Higher Education

DOI: doi.org/10.31960/ ijolec. v3i2.833 Abstract. This study aimed to determine the psychological impact in students due to online learning in vocational higher education conducted during the Corona virus disease 2019 (COVID-19). The samples in this study were all the students of the Undergraduate Program Department of Commercial Administration of Politeknik Negeri Bengkalis. The Samples were taken using the purposive sampling technique focused solely on students who gained online learning in theory and Practice courses since the use of online learning because of the COVID-19. The Data was collected using a DASS 42 instrument through online questionnaire. The results of this study showed that online learning in the higher education of psychologically impactful, which resulted in 29% of students having a level of depression above normal, 70% of students had an anxiety level above normal, and 46% of students had a stress level above normal.


INTRODUCTION
The results of the Central Bureau of Statistics (BPS) survey in the third quarter of 2020 showed that there are 6 business sectors most affected during the coronavirus diseases  pandemic, namely accommodation and food/drink, other services, transportation and warehousing, construction, processing industry, and trade (BPS, 2020). Specifically from other service sectors, the education sector is one of the sectors that affected by COVID-19 in Indonesia. The government, especially the Ministry of Education and Culture, parents and students, and teachers are worried because of the rapid and difficulty of preventing the spread of COVID-19. One of the efforts that has been made by the government at the higher education level is to publish a Circular Letter of the Director General of Higher Education and Culture Number 1 Year 2020 on prevention of the spread of Corona Virus Disease  in universities. This then makes all universities have to change the process of teaching and learning activities (KBM) that were initially face-to-face in the classroom into online learning. Online learning is expected to be the best solution for the implementation of teaching and learning activities in the midst of the COVID-19 pandemic. Online learning is one of the applications of distance education. Online learning is expected to provide opportunities for learners to still be able to take lessons or courses without any distance and time restrictions. So that students can follow the learning in a safe environment with the aim of maintaining health and safety.
Although it has been agreed, but in its implementation online learning still causes controversy, especially from parents and learners. For teachers, online learning is considered only effective for assignments, while to make students understand the material is considered very difficult. In addition, each student has different technological and economic abilities. Not all students have facilities that support online learning activities. Devices that do not support inadequate internet connection, and expensive internet quotas become barriers to online learning. Nevertheless, learning must continue. Each education provider has its own policies in addressing this rule. Some higher education institutions provide internet quota assistance to students for the implementation of online learning. In addition, based on the circular of the Director General of Higher Education Kemendikbud Number 821 year 2020 concerning Internet Quota Provision Program for Students and Lecturers. The government through the Minister of Education and Culture provides this free program to students, students, educators and lecturers. This program aims to support the implementation of distance learning during the COVID-19 pandemic. The form of assistance provided in the form of internet quota (data package) to access conference meeting applications in order to keep face-to-face learning online.
Although there are some higher education institutions in Indonesia that are ready to do online learning, the presence of COVID-19 shows a greater number of higher education institutions that are not ready to implement online learning systems. For example, the use of online learning technology is still dominated by higher education institutions in big cities because of the financial capacity and availability of digital learning systems(e-learning)that are better thansmall campuses in rural areas or in districts. In addition, there are not a small number of educators who still have difficulty using online learning technology whether using e-learning or other platforms from third parties such as Zoom meeting or Google Classroom. This makes online learning only a medium to give assignments remotely by teachers without any feedback or interaction with learners. Therefore, if this is done continuously, it will be able to cause psychological impacts for learners in the form of depression, stress, and excessive anxiety. Maulana and Iswari (2020) conducted research on undergraduate Student's stress level in Vocational Study due to online learning of statistics for business course. The result showed that 3% of the student having stress level in extremely severe categories, 13% in severe categories, 8% in moderate categories, 24% in mild categories, and 52% in normal categories.
Several studies related to online learning have been done. Khairani, et al (2020) conducted research on students' perception of the use of Google Classroom inblended learning. The results showed that students' perception of Google Classroom usage was 69% with excellent categories. Tantri (2018) conducted research on social presence in online learning based on the point of view of open and distance education learners. The results showed that online learning has a positive impact on the expectation of connectedness, aspects of learning, and social aspects(socio-emotional). Khusniyah and Hakim (2019) conducted research on the effectiveness of online-based learning by utilizing the use of web blogs against students' ability to understand English text. The results showed that there are differences in students' comprehension skills. In addition, online learning with the web blog has a positive influence on improving students' English reading ability. Kuntarto (2017) conducted research on the effectiveness of online learning models in Indonesian language lectures using Online Interactive Learning Model (OILM) techniques. The results showed that this learning model was able to increase the absorption of lecture materials by students with an increase of more than 81%. Rusdiana and Nugroho (2020) conducted research on student response in online learning of Indonesian law delivery courses using VINESA UNESA e-learning. The results showed that students' motivation when attending online lectures was 71% and the effectiveness of lectures was 76.4%. Mustofa, et al. (2019) conducted research on the formulation of online lecture models by utilizing the official government website as an effort to reduce the disparity in the quality of universities. The results showed that the online lecture system has a positive contribution to encourage disparity in the quality of universities in Indonesia. Maulana and Hamidi (2020) have conducted research on students' perception of online learning in practical subjects in vocational education. The results showed that students give positive perceptions for aspects of the learning process, lecturer capabilities, and facilities and infrastructure.
Mustakim (2020) has conducted research related to the effectiveness of online learning in grade XI students of WAJO High School in mathematics subjects. The results showed that 23% of students rated online math learning as highly effective, 46.7% rated effective, 20% rated it as mediocre, and 10% rated ineffective.
Previous research has only focused on the impact of online learning on the effectiveness of learning, while research related to the impact of online learning on students' psychological is still not done. This is because during the COVID-19 pandemic, not only one or two courses are conducted online, but all courses must be conducted online. Especially in vocational higher education that is directed to produce graduates who master the ability in certain fields of work so that it can be directly absorbed as a workforce in industry / private, government institutions or entrepreneurship independently. Therefore, the burden of teaching in vocational education programs is prepared by prioritizing the burden of practical courses / skills compared to the burden of theoretical courses. This will be very difficult for students without direct guidance by lecturers who are teaching courses. Therefore, this study aims to find out the psychological impact of online learning on students in vocational higher education during the COVID-19 pandemic. It is hoped that this research can be a consideration for educators in designing online learning.

METHODS
This research is a qualitative descriptive research. The population in this study is all students of the Applied Bachelor Program of the Department of Commercial Administration of Bengkalis State Polytechnic. The samples were taken using purposive sampling techniques that focused only on students who were taking practical and theoretical courses and were carried out online. Students get online learning for all courses starting from March 27 to June 12, 2020, namely since the enactment of the Circular Letter of the Director of Bengkalis State Polytechnic on March 24 on the implementation of online learning to avoid the spread of COVID-19. Online lectures start from the 6th to the 14th meeting using the Google Classroom platform and come with learning videos uploaded on YouTube.
The research data was obtained using a questionnaire filled out online by students at the end of the 14th meeting using Google Form. The questionnaire used adapted the DASS 42 Instrument issued by the Psychology Foundation of Australia and has been translated into Indonesian by Damanik (2006), Faculty of Psychology, University of Indonesia. The validity and reliability of the instruments were tested in two independent groups with a total sample of 144 people, and were declared valid with the lowest validity being 0.3532, while the reliability value was 0.9483 (Damanik, 2011). Respondents were asked to respond using a likert scale, namely: 0 = never, 1 = sometimes, 2 = often, 3 = almost always. In addition, in-depth interviews are also used to some students to get more detailed information.
Data analysis techniques used in this research are qualitative analysis consisting of data collection, data reduction, data presentation, and conclusion drawing. The interpretation of stress levels experienced by students in this study refers to the measurement standard of DASS 42, as in Table 1. Furthermore, kendal's tau-b correlation test was conducted with the help of SPSS to find out the relationship between student gender variables and psychological impact, and student age on psychological impact.

RESULT AND DISCUSSION
DASS 42 instruments in the form of questionnaires are filled out online by students majoring in commercial administration from the applied undergraduate program of international business administration (ABI) first and second years students, and applied undergraduate study program of public finance accounting (AKP) first year students with a total of 180 respondents.
Students majoring in commercial administration are chosen because they can conduct practical courses online. This is because the required device is only a computer device. The characteristics of respondents can be seen in Table 2.  ( 100) Source: Processed Data, 2020 After the 14th meeting students were asked to fill out the online DASS 42 instrument consisting of 42 statements. But the one used to measure stress levels consisted of only 14 statements. Each item of the statement uses an ordinal scale in the form of a likert scale, i.e.: 0 = never, 1 = sometimes, 2 = often, 3 = almost always. The results of the questionnaire can be seen in Table 3. Table 3, it appears that after attending online lectures ranging from the 6th to the 14th meeting, there are students who have levels of depression, anxiety, and stress that are above normal levels. The abovenormal level of student depression was 29%, i.e. 11% were depressed in the mild category, 11% in the moderate category, 4% in the severe category, and 3% in the extremely severe category as shown in Figure 1. Depression is a mood disorder, a prolonged emotional condition that colors the entire mental process (thinking, feeling, and behaving a person) . In the discussion of emotions covered include affects, mood, other emotions, psychological disorders related to mood . Based on the results of interviews with students who have very severe levels of depression shows that their mood changes because in every online lecture is always constrained by unstable internet networks / connections. This is due to the domicile of students who are on the island of Bengkalis which is in the outermost category of regions, so that there is still uneven internet access. This is in line with  and  who stated that depression is more common in rural areas than in urban areas.

Based on
Then the level of anxiety of students who are above normal is 70%, i.e. 13% experience anxiety in the mild category, 26% in the moderate category, 14% in the weight category, and 17% in the very heavy category as shown in Figure 2.

Figure 2. Student's Anxiety Level
Anxiety disorders are disorders that occur due to the interaction of biopsychosocial factors, including genetic susceptibility that interacts with certain conditions. It is characterized by excessive and irrational anxiety and worry even sometimes unrealistic to various events of daily life. This condition is experienced for at least 6 months (Sullivan et al., 2007). The results of interviews with students who experience anxiety at a very severe level indicate that there are several causes, namely: limited internet quota, unstable internet connection, and a lot of lecture assignments in a short time. This causes anxiety and anxiety from yourself to be able to attend lectures online and complete tasks given on time. So that students have responded incorrectly and incorrectly to threats caused by selective attention to negative things in the environment, distortions in the processing of information and a very negative view of the ability to deal with threats (Howard et al. 2007).
Furthermore, student stress levels that were above normal were 46%, i.e. 18% experienced anxiety in the mild category, 12% in the moderate category, 13% in the weight category, and 3% in the very heavy category as shown in Figure 3.

Figure 3. Student's Stress Level
Stress is an unpleasant feeling and is interpreted differently from one individual to another (Kaplan & Saddock, 2010). Stress can be defined as a state when there is a discrepancy between the demands received and the ability to cope (Maramis, 2009). Based on the results of interviews with students who have stress levels in very heavy categories indicate that there are several causes, namely: unin favourable or compatible devices/gadgets, limited internet quota, unstable internet connection, many lecture assignments in a short period of time, and elusive material. This is because to participate in online learning every student must have supporting facilities/devices. In addition, in terms of lecture materials, especially in vocational higher education that has more composition of practical courses, during this time when facing obstacles during practicum, it can directly ask the lecturers or laborans who help the course of lectures. But this cannot be done through online learning. Moreover, students sometimes find it difficult to express the obstacles experienced when conducting practical lectures online. The type of stress experienced by students in the form of frustration is the expectations desired and the reality that occurs is not as expected. This is due to the demands of too many lectures and makes students work too hard because of having to do it (Smet, 1994). Each student's response will be different to the stressor given. Personality type and level of student development can affect the body's response where the more mature in its development, the better the ability to overcome stressors (Yusuf, 2008).

Relationship
Between Gender and Depression, Anxiety, and Stress Level The relationship between the gender and the psychological impact of depression, anxiety and stress can be found using Kendall's tau-b correlation test. This test was chosen because all the variables studied consisted of nominal and ordinal scales. As for the results as in Table 4. Based on p-value in Table 4, it can be concluded that the gender of students in online learning does not have a significant relationship with depression level (p-value= 0.790), anxiety (p-value=0.206), and stress (p-value= 0.959) experienced by students. This result is different from Hawari (2014) which states that based on gender, it is estimated that the ratio of the number suffering from both acute and chronic anxiety reaches 5% between women and men is 2 to 1. The results of Tran et al. (2018) showed that women are more at high risk of experiencing stress to the response of psychic disorders, but the coping mechanism of men is higher in overcoming problems. Ratnawati's research (2011) found that gender is very related to disease response, anxiety, and the use of coping in dealing with problems. In addition, women are also more often exposed to environmental stressors and the threshold against stressors is lower when compared to men (Aryawangsa, 2015). If viewed further in students, then in online learning students can discuss with each other and help each other to complete lecture assignments online and there is no difference between male and female students related to materials and assignments given at the time of Study online. This is what causes the absence of a relationship between the gender and the psychological level of the student.

Relationship Between Age and Depression, Anxiety, and Stress Level
Age is one of the references in determining the level of development in individuals where the more mature a person is in his development, the better the ability to overcome psychological problems faced. The relationship between age and psychological impact consisting of depression, anxiety, and stress can be known by using Kendall's tau-b correlation test. As for the results as in Table  5. Based on p-value in Table 5 it can be concluded that the age of students in online learning does not have a significant relationship with anxiety levels (p-value=0.131), and stress (p-value= 0.385). But age has a significant association with the level of depression (p-value= 0.050) experienced by students. This result shows that the anxiety and stress does not have significant relationship with the age of the student, but the depression have the significant relationship. The results of this study are in line with Ulfah (2017) which states that there is no relationship between age and anxiety levels. But the level of depression is different from Shafa et al. (2018) which states that there is no significant relationship between age and depression levels.
Students who are the object of research are classified as late teens and range against stress. Kinantie (2012) suggested that adolescence has a significantly greater stress response than underage. Nasution (2007) also stated that teenagers aged 15-18 years experience many changes cognitively, emotionally and socially and tend to think more complexly. Students begin to learn to think maturely and tend to solve their own problems without asking for help. According to Yusinta (2015) signs of increased depression, which is an advanced stage of stress, appear between the ages of 14-16 years and reach its peak there are 17 years of age.

CONCLUSIONS AND SUGGESTION
Based on the results of the study, it can be concluded that online learning in vocational higher education has a psychological impact, namely resulting in 29% of students having above normal depression levels, 70% of students having above normal anxiety levels, and 46% of students having above normal stress levels. The gender of the student does not have a significant relationship to the psychological impact that students experience in the form of depression, anxiety, and stress. While the age of the student has a significant relationship but in a very low category with the level of depression experienced by the student. Advice for further research to examine whether there is a psychological level effect on student learning achievement that is the effect of online learning. This can be used as a reference in looking at the effectiveness of online learning carried out so far.