Education in the Third Dimension: 3D Stereoscopics as a Cognitive Tool for Learning
Notice bibliographique
Résumé
Three-dimensional (3D) stereoscopic technologies bring a whole new dimension to educational media and learning. Perception and orientation in the threedimensional world is propagated through many different object and environmental factors. The use of 3D stereoscopics as a cognitive tool for augmenting reality from the two-dimensional representations on a computer screen to one that is three-dimensional, interactive, and immersive provides researchers with a new tool to help understand how we learn. The purpose of this paper is to introduce and examine the techniques and technologies of 3D stereoscopics for learning. Implications and applications of 3D stereoscopics in education are proposed in hopes to begin a dialog for bringing 3D stereoscopic technology to the wider learning community in a meaningful and engaging way. Three-dimensional (3D) stereoscopic technologies bring a whole new dimension to educational media and learning. The ability to use inexpensive 3D glasses with regular computer monitors or media projectors makes stereoscopic images, animations, and movies accessible and affordable. The unique properties that stereoscopics provide, allows the user to gain a perspective that cannot be produced using virtual-3D or two-dimensional pictures. The distinctiveness of stereoscopic images, animation, and movies, make them an ideal media in which to explore, learn, and experience virtual three-dimensional worlds and objects. Stereoscopics, from the word stereo derived from Greek meaning relating to space and optic from the properties of sight (Howard, 2002), is a technique that has been used for over 150 years to produce images with three-dimensional depth. Used in such fields as visual data mining (E. Wegman, J. & J. Symanzik, 2002), cancer detection (Skelly, 2007), art (Layer, 1971; Sorenson & Russett, 1999), entertainment (Zone, 2007), and chemistry (Holford & Kempa, 1970), stereoscopic technologies have wide ranging applications and uses. However, given its long history and applications in research and industry, stereoscopic imaging has not a made a long or lasting impact in education. The purpose of this paper is to introduce and examine the techniques and technologies of 3D stereoscopics for learning. A brief introduction of three-dimensional perception and a history of stereoscopic techniques will be outlined to give some context of a technology that has been available for over 150 years. Second, the ranges of techniques that are available to produce stereoscopic images are reviewed. Third, applications of stereoscopics currently used in education and learning are addressed to draw some inferences of how these benefits can be realized by a larger educational audience. Fourth, a review of the literature on using graphics for learning, with specific reference to stereoscopic technologies as a cognitive tool is addressed. The unique properties of images, animations, and movies as they relate to learning, form a solid foundation in which to promote stereoscopics as an educational tool. Finally, implications and applications of 3D stereoscopics in education will be proposed to begin the dialog of bringing 3D stereoscopic technology to the wider learning community. 3D Vision, Perception, and Depth Perception and orientation in the three-dimensional world is propagated through many different object and environmental factors. Objects size, gradation of color, shadow, contrast, texture, occlusions, and movement all play a part in our perception of objects’ dimensionality in space (Mather, 2008). One of the
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 | 0,002 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,015 |
| Communication savante | 0,008 | 0,010 |
| Science ouverte | 0,001 | 0,005 |
| Intégrité de la recherche | 0,002 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 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 ».