Literature‐based collaborative internet projects in elementary classrooms
Bibliographic record
Abstract
The purpose of this study was to examine teachers’ use of literature‐based collaborative Internet projects (CIP) in their elementary classrooms. These practices require two or more classrooms to read and analyze texts on specified topics and then share responses over the Internet. The participants, all female, represented 15 different U.S. states as well as Canada and Australia. Three types of data were collected and analyzed including electronic surveys, semi‐structured email interviews, and project websites. Results indicated that teachers’ pedagogical beliefs led to the introduction of CIP. Specifically, teachers reported the projects provided opportunities to foster learning by helping students (1) make connections between new content and their background knowledge, (2) actively participate in their own learning, and (3) recognize and appreciate differences among their peers. Teachers also reported CIP supported literacy curriculum standards. Finally, data indicated differences in how CIP were implemented across grade levels. In light of the study's results, four lessons are shared along with educational and research implications.
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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 | 0.009 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".