Det utvidgade klassrummet – språkundervisning på distans
Bibliographic record
Abstract
AbstractThe sociocultural theory, the idea that we learn in interaction with others, has had an immense impact on the field of education. For the past 20 years, the theory has gained momentum within the field of online education and inspired a group of researchers at the University of Alberta (Garrison, Anderson & Archer 2000) to design a conceptual framework and an online learning model of the already existing idea Community of Inquiry. The model consists of three elements, all of which are pointed out as crucial prerequisites for a successful online learning environment: social presence, teaching presence and cognitive presence. This study examines how the courses in Swedish at UCLA were re-designed when evolving into blended synchronous language courses, and what specific measures were taken to meet the need for social presence and teaching presence. Key findings include 1) the need for visual and auditory presence to feel as part of the group, 2) the importance of carefully selecting technologies for active learning, and 3) the importance of pedagogical adaptation in an online classroom.
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.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.065 | 0.029 |
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".