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Record W3025323617 · doi:10.5539/ijps.v12n2p31

Doodle Away: Exploring the Effects of Doodling on Recall Ability of High School Students

2020· article· en· W3025323617 on OpenAlexvenueno aff
Deekshita Sundararaman

Bibliographic record

VenueInternational Journal of Psychological Studies · 2020
Typearticle
Languageen
FieldNeuroscience
TopicMind wandering and attention
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyRecallBlankDistractionSocial psychologyMathematics educationDevelopmental psychologyCognitive psychology

Abstract

fetched live from OpenAlex

Doodling is often misinterpreted as a distraction to students in an academic setting– a hindrance to learning. However, recent research has shown that doodling may be beneficial to learning and memory retention. The current study expands upon previous research by investigating the impact of structured and unstructured doodling on auditory recall. This experiment was designed using a multi-method quantitative approach with an experiment that consisted of a control, structured doodling, and unstructured doodling group, and a questionnaire to assess students’ doodling experience. A group of 39 high school juniors were chosen for this study. In all three conditions, students listened to a history lecture in their normal classroom circumstances and took a quiz over the information afterward. Students doodled in both experimental conditions– they shaded a structured doodling sheet in the first condition and doodled in a blank, white A4 sheet in the second condition. The results indicated that those in the structured and unstructured doodling group performed significantly better than those in the control group, with structured doodling scoring the highest out of the three. The Post Doodling Questionnaire indicated that the majority of students experienced less daydreaming and increased recall while doodling; furthermore, the majority of students reported doodling naturalistically.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.568
Threshold uncertainty score0.533

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.218
GPT teacher head0.422
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2020
Admission routes1
Has abstractyes

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