Orchestrating Communities, Ubiquities, Time and Space: International Experiences in the Use of Educational Technology
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
In this brief introduction we frame the special issue on “Orchestrating communities, ubicuity, time and space: International experiences in the use of educational technology.“ It constitutes the result of the “International experiences in the use of Educational Technology” panel session celebrated within the XXI University Conference on Educational Technology (XXI Jornadas Universitarias de Tecnología Educativa) (JUTE) in Valladolid, Spain in 2013. Every article has gone through a double-blind peer review process with the aim of ensuring not only the quality of the issue but also the adaptation of the initial presentations given in the aforementioned panel session to the rules of scientific publications. This issue brings together five of the works presented in the panel to address a number of relevant challenges in the field of Educational Technology. The topics accomplished by the articles spin around the (mis-)uses of technology in the national accreditation process of teachers in the United States; the tensions derived from the use, re-use and sharing of Open Educational Resources (OER´s) in Europe; an interpretive proposal to orchestrate the evaluation of complex technology-enhanced learning settings, and finally; a experience in the collective generation of documentaries at the Galiano Islands (Canada).
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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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