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The iPad in the Classroom

2013· book-chapter· en· W4245558143 on OpenAlexaff
Nathaniel Ostashewski, Doug Reid

Bibliographic record

VenueIGI Global eBooks · 2013
Typebook-chapter
Languageen
FieldHealth Professions
TopicDigital Storytelling and Education
Canadian institutionsMacEwan University
Fundersnot available
KeywordsMultimediaDigital storytellingVariety (cybernetics)Computer scienceStorytellingImplementationMobile deviceMicrobloggingProcess (computing)Social mediaWorld Wide WebNarrativeSoftware engineering

Abstract

fetched live from OpenAlex

Mobile learning devices, such as the iPad tablet, have the potential of providing unique pedagogical strategies for the K-12 classroom. One of these strategies is digital storytelling, a constructivist approach using digital tools to create and share short stories. This chapter describes three iPad implementation projects involving multimedia database and digital storytelling creation that underscore the successes and challenges of these devices and the new classroom activities they make available to educators. The results of these projects suggest that the iPad is one device that can successfully support and sustain a variety of multimedia creation and use in the classroom. Specifically, this chapter reports on research that identifies mobile pedagogical strategies on the iPad, such as mobile small and large group demonstrations, student-directed control-and-playback activities, backchannel (microblogging) conversations, Web-based research activities, and digital storytelling. As with other types of technology implementations, management and process challenges exist that should be considered. This chapter details some of the challenges that are specific to iPads and multimedia creation on these devices.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.479
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.006

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 head0.056
GPT teacher head0.352
Teacher spread0.295 · 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.

Study designTheoretical or conceptual
Domainnot available
GenreOther

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
Published2013
Admission routes1
Has abstractyes

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