Interiors, Affect, and Use: How Does an Academic Library’s Learning Commons Support Students’ Needs?
Bibliographic record
Abstract
Abstract Objective – This study sought to identify the learning needs, satisfaction levels, and preferences of students using an academic library’s learning commons. A particular focus was understanding whether the socio-collaborative environment facilitated by the learning commons was aligned with the institutional objectives of supporting intensive study and scholarly work. Methods – A mixed methods sequential explanatory study design was used, in which quantitative findings were supplemented by qualitative findings. Data for the study were drawn from 59 hours of observations documenting behaviors of 9,249 individuals, as well as survey responses from 302 students. Three semi-structured focus groups with 10 students were held to discuss and clarify findings. Results – Behavior mapping and survey data showed that students were largely satisfied with the learning commons and that it was considered a supportive environment for them to complete their stated tasks. Incongruity was observed between the learning commons’ intended and actual use; although 75% of spaces were designated for collaboration, 50% of survey respondents identified independent work as their primary task and 76% of individuals were observed working independently. In focus group discussions, students praised the space for its vibrant ambiance and facilitation of social connections, but acknowledged that more serious study required retreat into quieter spaces found elsewhere in the library. Conclusion – The learning commons is an important and desirable space for students, providing a safe and community-oriented environment that is located in the center of campus. While students deemed the atmosphere successful for fostering social relationships and creating an overall sense of belonging, care needs to be taken to maintain a proper balance between quiet and collaborative spaces. The methods used in this study underscore the importance of gathering data from multiple sources, offering guidance to other libraries seeking to create, re-envision, and assess their learning spaces.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".