From Classroom to Boardroom: Employer Perspectives of Business Graduates’ Information Literacy Skills
Bibliographic record
Abstract
Information literacy includes the ability to locate, use, and manage information. While many libraries and academic programs incorporate information literacy into undergraduate business instruction and assignments, the linear and ordered nature of the curricula may not prepare students for the ill-structured and ever-changing work environments they will encounter after graduation. To understand the gaps between the current academic environment and the professional world that our business graduates will enter, we interviewed four employers in a pilot study to examine their expectations and perspectives regarding the abilities of new business hires to find and utilize information in the workplace. All the employers were from large, multi-national companies that hire extensively from our R1 university and other high ranking undergraduate business programs. We used a combination of deductive and inductive qualitative analyses to identify these major themes in the interview transcripts: gathering and using information; evidence and synthesis; using specific types of information; learning; navigating internal systems; satisfaction with new hires; and data. Our findings are useful to us, and potentially to other librarians and instructors at institutions with undergraduate business programs, to integrate into business information literacy instruction in a way which best prepares students for the information work environments they will encounter after graduation.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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".