Back to Normal? Perspectives of Faculty and Teaching Librarians on Information Literacy Instruction After the Lockdowns
Bibliographic record
Abstract
Objective – While LIS scholars have extensively studied the widespread disruptions to library instruction during the lockdown period of the COVID-19 pandemic, there is a relative dearth of research concerning the longer-term implications for teaching information literacy (IL). This exploratory survey sought to examine how faculty have introduced IL skills to students before, during, and after the COVID-19 lockdowns. After returning to in-person operations in 2021, the authors observed a change in how faculty have engaged with libraries to teach IL to their students. Methods – Utilizing parallel survey instruments, we asked faculty and librarians for their perceptions of current and past practices with scheduling library IL sessions, evaluating student research skills and considering how they acquired those skills. Results – Although responses showed an unsurprising decrease in library instruction requests during the pandemic lockdowns, faculty respondents noted a return to nearly pre-pandemic norms after the resumption of in-person operations. Teaching modality and use of research assignments did not appear to impact faculty IL scheduling behaviors, but differences in faculty and librarian responses highlighted potential disagreements about the impact of COVID-19 on faculty use of library instruction. Additional questioning indicates a disconnect between how faculty perceive student research skills and their reasons for scheduling library instruction, which suggests misperceptions of librarian expertise and differences in understanding how librarians should teach information literacy. Open-ended responses provided additional context to these issues, while identifying potential barriers and opportunities. Conclusion – Overall, our findings indicate that, rather than fundamentally altering faculty approaches to information literacy, the COVID-19 disruptions revealed and exacerbated endemic problems with the prevalent one-shot model of library instruction.
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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 | 0.018 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.020 | 0.012 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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".