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Record W228543513

Picture This! A Spate of New Multimedia Tools Is Putting a Whole New Face on the Learning Process

2006· article· en· W228543513 on OpenAlexaboutno aff
Matt Villano

Bibliographic record

VenueT.H.E. Journal Technological Horizons in Education · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Technology Integration
Canadian institutionsnot available
Fundersnot available
KeywordsPower pointWhiteboardInteractive whiteboardMultimediaPoint (geometry)Variety (cybernetics)Computer scienceMobile deviceProcess (computing)Mathematics educationWorld Wide WebPsychologyMathematics
DOInot available

Abstract

fetched live from OpenAlex

AMONG THE OLD-SCHOOL resources that the digital age is making obsolete, or at least less consequential, count the chalkboard. For decades, the chalkboard was the focal point of all instruction, the big screen on which teachers wrote out and directed lesson after lesson after lesson. Today, while chalkboards still exist, they are losing their status as the classroom centerpiece--districts are now investing in technology to modernize classroom displays. From interactive whiteboards to handheld tablets, from digital projectors to newfangled video-editing systems, the most successful of these products are those that grab student attention and don't let go. New displays have not come of age in a vacuum. According to the American Academy of Pediatrics (www.aap.org), kids in the United States watch an average of four hours of television a day. What's more, a recent report from the National Academy of Sciences (www.nationalacademies.org) shows that 26 percent of US teenagers spend between one and two hours online a day. The statistics indicate that kids prefer to learn in a visual world and like to have information at their fingertips. Across the board, the latest and greatest classroom display products meet these needs. A Smarter Chalkboard Electronic whiteboards are no longer new, but they are still cutting edge. Introduced by Canada-based Smart Technologies (www.smarttech.com) in 1991, the technology combines the simplicity of a whiteboard with the power of a computer. Essentially, the device is one giant computer screen that teachers can manipulate with a variety of tools, enabling them to present slides, take notes, and do a host of other things. Teachers also can use electronic whiteboards to control applications on a computer, write notes in digital ink, or save work to share later. Of course, the best part of the technology is that every student can see it. This is precisely why teachers in the Jennings School District (MO) recently turned to Smart Technologies' Smart Boards to increase student involvement. Last year, the district, in which 77 percent of students qualify for free-lunch programs, applied E-Rate funds to purchase 52 Smart Boards for classrooms in grades 3-12. Once the technology was in place, the school launched a new, inquiry-based approach to learning--an approach Cindy Kicielinski, district instructional technology specialist, says has forced students to find answers for themselves and figure out how to incorporate technology to present those answers to the class.4 You'll see students in the front of the room collaborating in teams, being able to talk effectively about the knowledge that they have, and present it back in a way that everyone understands it, she says. That's a lifelong skill. At J.P. Ryan Elementary Sehool in Waldorf, MD, teachers have deployed whiteboard technology from GTCO CalComp (www.tcocalcom.com) to achieve similar results. Dubbed the InterWrite SchoolBoard, the device incorporates infrared wireless transmitters, which students use to answer questions and record responses with a simple click of a button. Fourth-grade teacher Jill Barnes says the interface makes learning seem like a video game--something to which youngsters are drawn. Barnes describes one geometry lesson in which she used the SchoolBoard to create a memory game similar to the old game show Concentration. The game required kids to move around different pictures of shapes and select the appropriate name for each one. In another lesson, Barnes used the SchoolBoard's spotlight feature to emphasize words she wanted the students to memorize. While both lessons worked well, Barnes says one drawback of the technology is the time it takes to learn to use it. It does take awhile to learn and plan your lessons, she says, noting that it took her the better part of a year to become completely comfortable with the InterWrite board. If you're dedicated to your job, though, that's not really a downside. …

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.762
Threshold uncertainty score0.648

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.038
GPT teacher head0.352
Teacher spread0.314 · 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 designTheoretical or conceptual
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

Citations1
Published2006
Admission routes1
Has abstractyes

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