Comparing the influence of doodling, drawing, and writing at encoding on memory.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The purpose of the present study was to determine the extent to which doodling, which we define as drawing that is semantically unrelated to to-be-remembered information, enhances memory performance. In Experiment 1, participants heard auditorily presented lists of categorized words. They were asked to either doodle, draw a picture of, or write out, each item while listening to the target words. Participants showed poorer free recall for words encoded while free-form doodling compared to words that were drawn or written, with drawing resulting in the best performance. In Experiment 2, target words were embedded in a narrative story to better resemble a real-world situation in which one might doodle. Participants monitored each auditorily presented narrative while either free-form doodling, drawing, or writing in response to the target words. As in Experiment 1, doodling led to the poorest subsequent recall for targets compared to drawing or writing during encoding. In Experiment 3, we used a structured doodling task at encoding, such that participants shaded in geometric shapes printed on paper rather than create their own doodles. Structured doodling led to similar levels of recall compared to simply writing. Creating a drawing of the words at encoding, rather than doodling, once again enhanced recall significantly. Taken together, these findings indicate that unlike task-relevant drawing, structured doodling during study provides no benefits to free recall, and free-form doodling leads to memory costs. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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.
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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it