Student Perceptions of Undergraduate Chemistry Laboratory Shaped by the COVID-19 Pandemic
Bibliographic record
Abstract
Laboratory activities are essential and important components of learning chemistry at the undergraduate level. The COVID-19 pandemic led to disruption of traditional modes of teaching and learning over the whole education spectrum including laboratory courses in chemistry. Although unfortunate, the COVID-19 lockdown period and following years challenged well accepted norms leading to new opportunities for higher education. The purpose of this work is to synthesize useful lessons from student experiences during COVID-19 pandemic and post-pandemic era aiming for improved future chemistry laboratories at the college and university level. Previously published studies addressed advantages and disadvantages of face-to-face vs. remote and online teaching of chemistry laboratory courses. However, there are only a few student-centered studies which analyze students’ perceptions of undergraduate chemistry laboratories in the post-pandemic era. Although the study was conducted at the university in the United States, we believe the lessons learned could be used globally. The present study contributes to the existing body of knowledge in this field of research. It is unique because surveyed students experienced different modalities of the laboratory and were given an opportunity to compare both modalities side by side. Therefore, student experiences provide stronger foundations of their preferences and perceptions described in this work. Based on our findings, it appears that post-pandemic undergraduate students taking a non-major course prefer hands-on experiments and a hybrid modality of chemistry laboratory.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".