Bibliographic record
Abstract
This study investigates the perceptions and behaviours of novice academic researchers in their first year of post-secondary education when conducting online research. Because this study was undertaken immediately following the COVID-19 pandemic lockdowns of 2020-2022 it provides a unique window into how this experience impacted our youth, their choices and behaviours when conducting online research at the point of entering university and then further along in the first year. Conducting online research in this context describes what students anticipate they will do during an information search process and the strategies and tools they use in practice to locate information. Using data from semi-structured interviews and cognitive maps, thematic analysis was used to identify themes of the students’ perceptions and behaviours. This exploratory research can serve to inform and provide insights into improving our science and health sciences libraries’ user experience, instruction, marketing, and e-resource collections, as well as students’ preparation for academic research in their secondary school years, particularly in the Canadian context. Findings indicate that the experience of secondary students conducting research for school is one of frustration. Credible information is highly valued but difficult to obtain without the proper resources and skills. The early perceptions of students were ones of hope that these frustrations would be appeased when having access to superior quality tools and learning the proper techniques of academic research. In today’s changing online world, library workers must continue the work of understanding how our students perceive and behave when conducting research.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.332 | 0.169 |
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".