Are Document Cameras the Next Big Thing? the Versatile Projection Technology Could Be the Next Recipient of That Rarest of Educational Honors: Ubiquitous Classroom Adoption
Notice bibliographique
Résumé
IT'S NO EASY THING for a technology to go from introduction to universal adoption. And if trends over the last 200 years are any indicator, the honor is not eagerly doled out, no matter how useful the innovation is. It took nearly 50 years after their arrival in 1801 for chalkboards to become a classroom staple, paving the way for teachers to provide instruction to large classes, eliminating the need to handcopy materials for each student. Since then, just one presentation technology has enjoyed the same level of acceptance: the overhead projector. And despite how overhead transparencies have made it practical for teachers to prepare notes and drawings ahead of time to project during class, it took 40 years to get the technology into their hands. Current presentation technologies far surpass overhead projectors, but none has seen ubiquitous classroom adoption. Enter the document camera. This cost-effective, easy-to-use device works in conjunction with a projector, television, plasma screen, or monitor to display documents and 3-D objects. Capable of capturing images and video to upload to a computer for use in multimedia projects and web pages, some models even allow users to share the screen display or freeze and annotate images. More importantly, students of all ages can use document cameras to share their work. As a result, schools are purchasing them in increasing numbers. The growing popularity of the device has not escaped the notice of education leaders in the state of Washington, where document cameras are now more widely used in classrooms than digital cameras. In fact, two well-established regional projects in Washington use document cameras in their professional development curricula. One project is for K-12 teachers, while the other targets secondary school math teachers. Each is designed to help participating teachers make better use of technology to impact teaching and learning. The K-12 program is led by Debbie Tschirgi. In 2005-06, Tschirgi, the director of educational technology programs for Educational Service District 112 in Vancouver, WA, designed and launched a program called the Sustainable Classroom Project (www.esd112.org/edtech/scp/index.cfm). She explains that the program is a response to the need for educators to a replicable classroom model of technology integration that is sustainable and supports research-based instructional strategies. The technologies used in the program are highly visual and interactive, and can be operated with a single classroom computer. The instructional strategies are derived from the book Classroom Instruction That Works: Research-Based Strategies for Increasing Student Achievement by Marzano, Pickering, and Pollock (Association for Supervision and Curriculum Development, 2001). The original program was piloted by 10 technology-proficient 14-12 teachers and reviewed by an external evaluator, who concluded that key decisionmakers for educational organizations and institutions should consider the document camera as a standard technology solution that will provide visually rich learning experiences for their students. Even before Tschirgi organized the Sustainable Classroom Project, math integration specialist Mary Anderson was working with teachers in ESD 123 (Pasco, WA) to improve mathematics instruction in grades 6 through 12. Seven years ago, many districts in Anderson's region adopted a reformed math curriculum that required middle and high school students to not only find the correct answer to a problem, but also explain the reasoning they used to arrive at the solution. This approach to mathematics instruction required major shifts in both teaching and learning. About the same time, ESD 123 decided to use funds from Title II, Part D of the No Child Left Behind Act to support a program called No Limit!. Designed to develop instructional models that support deeper understanding of mathematics concepts, No Limit! …
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».