KECEMASAN MAHASISWA SELAMA PEMBELAJARAN JARAK JAUH PADA MASA PANDEMI COVID-19
Bibliographic record
Abstract
The COVID-19 pandemic (Coronavirus Disease 2019) is an epidemic that is occurring worldwide and causing a number of psychological reactions and mental health. In response to the outbreak, the government established ‘Pembelajaran Jarak Jauh’ (PJJ). However, PJJ has had a number of negative effects. In addition, students are also prone to experiencing anxiety. There is increasing attention to the mental health of students at the higher education due to the COVID-19 situation. This study aims to determine the impact of the COVID-19 pandemic on student mental health, especially anxiety among students in Indonesia. The study was conducted using an online survey, with an anxiety scale from the DASS (Depression Anxiety Stress Scale), and a questionnaire related to the anxiety. The participants were 166 active undergraduate (S-1) students who were doing PJJ. The results showed that most students experienced extremely severe level of anxiety (44%). The anxiety that students experience might come from the COVID-19 pandemic situation, and the PJJ situation. Most of the students were worried that they would be infected by COVID-19 (83.13%). In addition, students also experience anxiety about the PJJ activities. They feel more anxious about carrying out academic activities compared to the period before the pandemic (76.5%). In addition, there are several conditions that affect student anxiety, such as: (a) feeling bored and less enthusiastic about online learning activities (78.31%); (b) the signal is bad, the quota runs out (68.67%), and (c) there is a lot of disturbance to the surrounding environment when online classes (67.47%). This state of academic anxiety is considered disturbing for students. Pandemi COVID-19 (Coronavirus Disease 2019) merupakan epidemi yang terjadi di seluruh dunia dan menyebabkan sejumlah reaksi psikologis dan kesehatan mental. Dalam menanggapi adanya wabah yang sedang merebak, pemerintah menetapkan Pembelajaran Jarak Jauh (PJJ). Namun demikian, PJJ menyebabkan sejumlah dampak negatif. Selain itu, mahasiswa juga rentan mengalami kecemasan. Terjadi peningkatan perhatian terhadap kesehatan mental siswa pada tingkat pendidikan tinggi karena situasi COVID-19. Penelitian ini berusaha mengetahui dampak pandemi COVID-19 pada kesehatan mental mahasiswa, khususnya kecemasan pada mahasiswa di Indonesia. Penelitian dilakukan menggunakan online survey, dengan skala kecemasan dari DASS (Depression Anxiety Stress Scale), dan survey terkait kecemasan yang mahasiswa rasakan yang diciptakan peneliti. Partisipan berjumlah 166 mahasiswa aktif Strata 1 (S-1) yang sedang melakukan PJJ. Hasil penelitian menunjukkan bahwa sebagian besar siswa mengalami kecemasan dengan tingkat sangat parah (44%). Kecemasan yang dialami siswa dapat berasal dari situasi pandemi COVID-19 dan situasi PJJ. Sebagian besar mahasiswa cemas akan terjangkit COVID-19 (83,13%). Selain itu, mahasiswa juga mengalami kecemasan mengenai kegiatan PJJ yang berlangsung. Mereka merasa lebih cemas dalam menjalankan kegiatan akademik dibandingkan dengan masa sebelum pandemi (76,5%). Selain itu, terdapat beberapa kondisi yang mempengaruhi kecemasan mahasiswa, seperti: (a) perasaan bosan dan kurang antusias mengenai kegiatan belajar online (78,31%); (b) sinyal buruk, kuota habis (68,67%), dan (c) banyaknya gangguan lingkungan sekitar ketika sedang kelas online (67,47%). Keadaan kecemasan akademik ini dianggap mengganggu bagi mahasiswa.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".