From On-Campus to Online: A Trajectory of Innovation, Internationalization and Inclusion
Bibliographic record
Abstract
This paper presents a study focused on a trajectory for developing an online operating mode on a campus-based university in the area of Massachusetts, USA. It addresses the innovation process and the changes and challenges faced by faculty and administrators. Methodologically-speaking, a mainly ethnographic approach was used for a systematic process of collecting data in context, in order to understand organizational strategies put in place to launch and improve online course provision. Leaders of the process and teachers of online courses were also interviewed. What emerged was: a) the online operating mode was prepared much in advance and linked to scenarios of internationalization and inclusion in higher education; b) there was an underlying discourse of inter-connectedness among different places and groups of people; and c) the partnership and collaboration between administration and faculty was essential. One of the main conclusions demonstrates that, despite careful formulation of the online component, it still does not enjoy the same status as the face-to-face element of courses, and, as a result, is largely ignored in terms of promotion in the teaching profession.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".