SCALING ISSUES ASSOCIATED WITH USING CLASSROOM TECHNOLOGIES
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
The modern engineering classroom has associated with it a myriad of educational technologies. Proponents of such technologies suggest that instructors avail themselves of technologies such as wikis, blogs, vidcasts, podcasts, screencasts, clickers, and backchannel instant messaging, in addition to managing their courses using the nigh ubiquitous online learning management systems. While the educational value of these technologies remains in question, their eventual inclusion into the classroom seems almost a certainty. Many of the discussions of educational technologies take place in the context of pilot studies or special-purpose initiatives. These contexts, where the ratio of students to teaching staff is generally small and where dedicated technical resources are usually available, do not mirror the usual Canadian undergraduate engineering classroom. This paper discusses the challenges faced when introducing education technologies into contexts where the number of students is much greater than the number of teaching staff, and where the resources to execute, support, and enhance the technologies are lacking.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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