Designing Virtual Laboratory Exercises Using Microsoft Forms
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Chemistry educators around the world have had to introduce innovative approaches for engaging students through virtual chemistry laboratory exercises, both out of necessity and to complement traditional in-person learning. As new methods are explored, instructors strive to offer experiences that are engaging and accessible and that foster skills transferable to in-person laboratories. Here, we introduce a method for designing virtual laboratory exercises using existing survey platforms, namely Microsoft Forms and Google Forms. These platforms offer the ability to integrate media content (e.g., videos and images) and questions which allow instructors to scaffold experiments with targeted inquiries as well as to encourage students to make decisions by the incorporation of branching points where the outcome(s) of the experiment can vary based on the selections chosen by students. Additionally, they are accessible to both teachers and students and offer instructors the flexibility to customize their virtual experiences to support their course learning outcomes. These exercises can also be easily shared and modified between instructors and potentially complement future in-person laboratories.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it