Computer-supported collaborative inquiry in remote networked schools
Bibliographic record
Abstract
This study addressed computer-supported collaborative scientific inquiries in Remote Networked Schools. Three dyads of grade 5-6 classrooms from remote locations collaborated using the knowledge-buildng tool Knowledge Forum. Customized scaffold supports embedded in the online tool were used to support student understanding and practice of an authentic inquiry process. The study studied how the use of the scaffolds could help students to understand and put into practice an authentic inquiry process, how the students' collaborative problem solving could translate into a deeper understanding of the phenomena explored and if this could lead to conceptual change. Students created notes and used the scaffold supports to support their inquiry process however without sufficient direct teacher modeling, coherent use of the scaffolds stayed low across activities. Pre- and post-test results show that the students gained a better understanding of the inquiry process, but low post-test scores suggest further need for direct teacher modeling of the inquiry process during science instruction. Content analysis of the ideas expressed by the students in two of the sites showed that students were able to generate high-level ideas especially when the directives were explanation-seeking rather than fact-seeking in nature. Teacher mediation in the online discussion tended to generate longer threads than when teachers were absent from the online environment. Unless effective collaborative conversation is already a part of the classroom culture, efforts are required to generate richer student interactions and foster deeper understanding. Recurring technical and logistical difficulties in the sites prevented teachers from concentrating on the learning objectives and should be more seriously addressed by school authorities. Evidence of conceptual change was found through micro-analysis of the students' ideas about buoyancy in the pre- and post-tests as well as in their notes showing that conceptual change is possible in this innovative collaborative learning context. Further insistence for students to complete the inquiry process is needed in order to created additional opportunities for students to express their knowledge about a scientific phenomenon and promote deeper understanding through collaboration.
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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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.007 |
| 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".