Collaborative Inquiry in Digital Information Environments
Bibliographic record
Abstract
This paper presents selected findings from current research being undertaken by the Center for International Scholarship in School Libraries (CISSL) at Rutgers University that examines the research and writing processes of high school students undertaking a group research task in a New Jersey High school library. The purpose of this task was for students to produce a co-constructed product that represents the group’s understanding of their chosen curriculum topic. The study involved 42 grade 9 students undertaking an accelerated English Language Arts curriculum unit focusing on examining a wide range of challenging literature in the genres of short story, novel, drama, nonfiction, and poetry. The course includes independent reading assignments, and stresses critical thinking and speaking skills, study skills, and research strategies. The learning environment was supported by a Wiki/ Google documents digital environment that tracked the group dynamics, student-to-student interactions, resource use patterns, and knowledge building processes, as well as classroom teacher and school librarian interactions with the students, as groups and as individuals. This paper reports specifically on cognitive, personal and interpersonal dynamics reported by students as they worked in groups.
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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 | 0.015 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.007 | 0.014 |
| Scholarly communication | 0.021 | 0.014 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".