Exploring how social media can enhance the teaching of action research
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
Action research has an extensive history of being used to improve teaching and learning in many different professional settings, for example, schools, colleges, universities health and social care services. Educational action research embodies a process that necessitates honesty and openness and which lends itself to the betterment of one’s practice; in the current e-learning climate, where education is rapidly changing and the role and practice of the educator is evolving yet uncertain, action research has never been more valuable. This article explores and presents how social media have been used to enhance the teaching of action research and also how students gained an understanding, appreciation and an evolving experience of action research. Exploring the intricate relationships between action research, new technologies and the learning that took place during an Understanding Action Research module, this article is written from the perspective that the module team was interested in ensuring that students acquired a fully rounded understanding of action research in order to utilize it in the improvement of their own practice.
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 | 0.019 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.006 |
| 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