Standing in the university classroom: A real possibility
Bibliographic record
Abstract
There are many health risks, independent of moderate-to-vigorous physical activity, associated with prolonged sedentary time; however breaking up periods of sitting can attenuate these risks. Alternative workstations have successfully reduced sedentary time without hindering productivity in office workers. However, to date there is limited research on the effect of active workstations on classroom performance of university students. This study investigated the effect of sitting, dynamic sitting, and standing desks on classroom performance (primary outcome). Secondary outcomes included cognitive performance, enjoyment, focus, discomfort and difficulty. Using a randomized counterbalance design, university students (N = 20, mean age = 21.85) listened to three 50-minute lectures followed by three quizzes pertaining to the lectures, performed cognitive tasks, and rated their discomfort, ease, enjoyment, focus, and future use after each desk condition. No significant difference for classroom performance, cognitive performance, enjoyment, or focus was found between the desks (all p values > .05). Significant differences however were found for discomfort and difficulty as well as future use (all p values < .05). Specifically, students rated the standing desks to cause slightly more discomfort and difficulty than the classic sitting desk and rated they were more likely to use a dynamic sitting desk over a standing desk in a classroom setting. Based on these findings, we recommend the use of standing and dynamic sitting desks in university classrooms to allow students to receive health benefits as they learn.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".