Scaffolding in information search: Effects on less experienced searchers
Bibliographic record
Abstract
This study aims to investigate how expert scaffolded training could help, from novice postgraduate students’ point of view, and foster development of information search ability among postgraduate students. Using a quasiexperimental design over a year and a half, eight doctoral students (novice searchers) participated in a series of five sessions with an expert searcher who was an information professional. A novice-expert comparison examined the differences between novices and experts in information searching; and the effect of scaffolding sessions in which the expert information searcher helped novice information searchers was examined. Findings showed differences existed between the novice and the expert searchers in use of complex formulation of query statements, choice of keywords, and operators. Scaffolding sessions with the expert searcher resulted in self-reported and observable improvement in information searching among the novice searchers. The paper concludes with a discussion of the design of information retrieval systems and recommendations for library programmes to support the continued development of research students’ information literacy skills.
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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 | 0.005 | 0.052 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".