Independent Searching During One-Shot Information Literacy Instruction Sessions: Is It an Effective Use of Time?
Bibliographic record
Abstract
Objective – To test the assumption that giving students time to research independently during a one-shot information literacy instruction (ILI) session, combined with scaffolding, is an effective pedagogical practice and a good use of class time. Methods – The study was conducted at a student-focused, four-year undergraduate institution with 8,500 full load equivalent students. Following brief, focused instruction in 10 different ILI sessions, first-, second-, and third-year students in 80-minute one-shot ILI sessions were given time to research independently. The librarian and instructor were present to scaffold the instruction students received. Students were asked to track the research they did during class using a research log and to fill out a short Web survey about their preparedness to do research and the usefulness of the ILI session. Results – Students agreed to have 83 research logs and 73 Web surveys included in the study. Students indicated that they felt more prepared to do research for their assignment after the ILI session and rated individual help from the librarian as the most useful aspect of the instruction session. Students did not rate independent time to do research as valuable as anticipated. Examining the research logs indicated that several things are taking place during the ILI session, including that students are demonstrating what was taught in the session in their searches, that their searches are progressing in complexity, and that students are using feedback from previous searches to inform the formulation of search queries. While students appear to be putting independent search time to good use, many students’ articulation of their thesis statement remains poor and searches continue to be fairly simplistic. Conclusions – This study gives evidence that giving independent research time in ILI sessions, with scaffolding, is an effective use of class time. The study also demonstrates that the majority of students are able to use what is taught during classes and that they are using class time effectively, though searching remains fairly simple. The focus of ILI sessions is on skill development, and future research should be on integrating IL into the curriculum to develop more complex skills and thinking needed in the research process.
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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 | 0.012 | 0.078 |
| 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 | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".