The Effects of Image Type and Signaling on Learning in Human Anatomy: Schematics versus Dissection‐based Cadaveric Photographs
Notice bibliographique
Résumé
The multimedia principle states that individuals learn best from a combination of images and text, rather than text alone. In gross anatomy education, images such as schematics and photographs are often utilized to promote the learning of anatomical concepts and effectively prepare students for laboratory sessions and course examinations. Students enrolled in human anatomy courses are typically offered a variety of resources containing either schematics, dissection‐based cadaveric photographs, or both – which are often laden with coloured highlights and text‐based labels. While ‘signalling’ (eg. using colours or labels to highlight important anatomical structures) has been shown to decrease cognitive load (an outcome associated with improved learning), it is unclear whether using schematics or dissection‐based cadaveric photographs influences students' learning efforts differently. The aim of this project was therefore to compare the influences of schematics and dissection‐based cadaveric photographs on students' examination performance and short‐term knowledge retention. At the onset of this project, a pilot study was conducted on students enrolled in an advanced undergraduate human anatomy course. Participants were randomly assigned to one of four modules containing specific image types: cadaveric photographs (CP), coloured cadaveric photographs (cCP), schematics (SC), or coloured schematics (cSC). They then used their assigned module to study an anatomical region prior to completing two examinations; (1) immediately after the study period, and (2) one week after the first examination. Performance on the examinations and short term knowledge retention were compared between groups, and no statistically significant differences in mean examination performance were detected between them ( p > 0.05). However, examination scores of those assigned to modules that contained images subjected to signalling demonstrated less drastic mean performance decreases in the second examination than those who studied the modules containing non‐coloured images. These findings suggested that the images subjected to signaling may have aided short‐term knowledge retention. The present study repeated the pilot study protocol on students enrolled in a large third‐year undergraduate introductory human anatomy course. The preliminary results indicated a similar trend, wherein signaling had beneficial effects on students' short‐term retention. The results of this project suggest that signaling using coloured highlights should be used when creating a novel resource, regardless of the type of image that is used. These findings may be used to inform the development of pedagogical resources and create teaching materials that promote the retention of anatomical knowledge and concepts. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,038 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».