Exploring the Collaborative Information Behaviour of Engineering Students: a Pilot Study Design
Bibliographic record
Abstract
Abstract: The paper reports the results and findings of a pilot study undertaken as part of a research project to explore the interaction between learning tasks and students ’ collaborative information behaviour when working as a group in a project-based undergraduate engineering design course at a Canadian university. Résumé: Cette communication présente les résultats d'une étude pilote entreprise dans le cadre d'un projet de recherche sur l'interaction entre les activités d'apprentissage et le comportement informationnel collaboratif des étudiants. L'étude s'est penchée sur un cours de génie de premier cycle offert dans une université canadienne et utilisant une méthode d'enseignement par projets de groupe. 1. Background Information seeking is an important and integrated part of work domains and work practices, and has been the focus of much research in information science. While many different models of information seeking have been proposed, most assume that the information seeker is an individual interacting with complex information spaces. Recent research, however, has found that people frequently collaborate and communicate when they retrieve and use information, and researchers have begun to challenge the individualistic approach by exploring the social, contextual and collaborative dimensions of information behaviour and information seeking (e.g., Bruce et al., 2002; Ingwersen &
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 | 0.015 | 0.021 |
| 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 | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 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".