Are contextual and designed student–student interaction treatments equally effective in distance education?
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
This systematic review draws from and builds upon the results of a meta-analysis of the achievement effects of three types of interaction treatments in distance education: student–student, student–teacher, and student–content (Bernard et al., Review of Educational Research, 79(3), 1243–1289, 2009). This follow-up study considers two forms of student–student interaction treatments, contextual interaction and designed interaction. Typical contextual interaction treatments contain the necessary conditions for student–student interaction to occur, but are not intentionally designed to create collaborative learning environments. By contrast, designed interaction treatments are intentionally implemented collaborative instructional conditions for increasing student learning. Our meta-analysis compared the effect of these two types of interaction treatments on student achievement outcomes. The results favored designed interaction treatments over contextual interaction treatments. Examples of designed interaction treatments and a discussion of study results and their potential implications for research and instruction in distance education and online learning are presented.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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