Inter-institutional collaborative chemistry assignments
Bibliographic record
Abstract
To help students learn the disciplinary language of chemistry, disciplinary communication was set up between chemistry learners who are in their first organic chemistry course at the University of Illinois Springfield and Mount Royal University. Students were assigned a series of organic compounds or reactions that they must describe using IUPAC nomenclature and correct chemical terminology to their partner at the other campus. The partners would then interpret the description provided to them and sketch the appropriate chemical representation. The students are then encouraged to discuss if the drawing is correct and if not, where the misunderstandings lie. We will discuss how instructional technologies were used to foster a valuable experience between learners from different campuses. An overview will be provided that shows different types of problems students worked on with their partners and model how they exchanged information. Successes and difficulties in integrating the interinstitutional collaborative assignments will be presented as well as how some difficulties have been addressed and future development needs. * Indicates faculty mentor.
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.
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 | 0.010 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.005 | 0.014 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.052 | 0.019 |
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".