An Investigation Of Laboratory Activities For Non-STEM-Majors During The COVID-19 Pandemic
Bibliographic record
Abstract
Laboratory activities have been an aspect of teaching chemistry for the past 200 years. However, their effectiveness in the teaching of chemistry content and skills have, until recently, been largely unexplored. This is especially the case for non-STEM-majors taking introductory and general chemistry courses, who were found in a review of the literature to often be regarded as a lower priority for research efforts due to goals of increasing STEM-major engagement. In an attempt to fill this gap in the literature, this study was designed to investigate if introductory chemistry laboratory activities foster the development of science identity in non-STEM-majors. However, as the COVID-19 pandemic continued into its second wave and people began discussing the future of laboratory activities, the purpose of this study shifted as well. As a result, this study looked at the influence of in-person activities for non-STEM-majors and sought to help support decisions on whether non-STEM-majors should return to in-person laboratory activities in introductory/general chemistry post COVID-19 pandemic. Making use of qualitative research methods, data was collected through a set of interviews with one student and three instructors at the University of Calgary and then analyzed for convergent themes. Results indicated that in-person laboratory activities are beneficial to non-STEM-majors for three primary reasons: 1) The disciplinary skills taught in chemistry laboratory activities are beneficial for daily life beyond laboratory settings; 2) Laboratory activities present students with a toolbox of skills that transfer between disciplines; and 3) Chemistry laboratory activities improve student science identity by showcasing the processes of science. Additionally, participants presented two considerations for returning to in-person laboratory activities following the COVID-19 pandemic: 1) Laboratory activities should change to emphasize student creativity and intrigue in order to improve their accessibility and effectiveness of teaching STEM-majors and non-STEM-majors; and 2) Accessibility of laboratory activities may be improved by implementing remote learning models that have been explored during the COVID-19 pandemic, such as making use of recordings and alternative methods of participation.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".