Institutions collaborating on an information literacy assessment tool
Bibliographic record
Abstract
Purpose – The purpose of this paper is to create an information literacy (IL) instruction assessment tool that responds to the unique needs of individual institutions and provides a strategic and relevant model for assessing IL skills among undergraduate students. Design/methodology/approach – The research team designed a post-test questionnaire comprised of two demographic questions, two open-ended questions and a pool of skill-based multiple-choice questions mapped to Association of College and Research Libraries Information Literacy (ACRL IL) Competency Standards for Higher Education. Participating librarians used a customized questionnaire to assess student learning at the end of their one-shot instruction sessions. Findings – In their responses to the multiple-choice questions, students demonstrated a clear understanding of ethical use of information and a strong ability to select appropriate tools for accessing information sources. Student responses to the open-ended questions revealed a wide range of confidence and ability levels, and provided insight into the frequency, depth and breadth with which various ACRL Standards are being addressed in library sessions. Research limitations/implications – This paper reports on student responses to questions that have subsequently been identified as problematic; therefore, strong inferences cannot be made about student learning from these responses. Questions have since been improved with further revision. In addition, the sample sizes for individual questions were too small to be generalizable. Practical implications – The intentional and strategic approach to the development of the assessment tool and its implementation is that it be practical and easy to implement for partner libraries. It is intended to make assessment of IL in the undergraduate context be assessable to all academic librarians who desire to participate. Originality/value – This paper describes a unique assessment tool that is designed to be responsive to local needs and provide a cost-free assessment option for academic libraries.
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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 | 0.053 | 0.101 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.013 |
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".