CMALT and cMOOC - a community of educators and their learning 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
CMALT is a peer-reviewed accreditation based upon the UKPSF (UK Professional Standards Framework) to enable staff (whether academic or administrative) who embed learning technologies in either their teaching or support roles, to showcase their experiences and gain recognition. This programme has been developed by ALT and is co-delivered online, by ASCILITE.
 
 Building upon the experiences of supporting a geographically distributed project involving six institutions nationally across New Zealand during 2014-2015, we (AUT) have developed a support structure for building communities around CMALT accreditation using a cMOOC model. The cMOOC framework enables us to bridge and broker authentic participation within an international community of academics and learning technologists interested in exploring CMALT accreditation, and we have had participation from the UK, Japan, Canada, Australia, and NZ. The CMALT cMOOC was developed in 2017 by the Centre for Learning and Teaching, at Auckland University of Technology, and endorsed by ALT and ASCILITE in 2019.
 
 This presentation will highlight the ecology of resources that are used to support the community and hear from current participants of the programme
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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