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Record W7139502164

Creating Narrated Multimedia Presentations in the Second and Foreign Language Class

2003· article· W7139502164 on OpenAlexaff
Janet Flewelling

Bibliographic record

VenueDigitalCommons@Kennesaw State University (Kennesaw State University) · 2003
Typearticle
Language
FieldArts and Humanities
TopicLiteracy, Media, and Education
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsClass (philosophy)Foreign languageForeign language teachingLanguage educationLanguage industryLanguage acquisition
DOInot available

Abstract

fetched live from OpenAlex

With increasing frequency, teachers are being encouraged to integrate technology into their teaching programs. Their challenge is to find technological applications that promote and enhance learning on the part of their students. A further challenge for second and foreign language teachers is to ensure that the applications reflect principles associated with communicative teaching. This article discusses how students can create narrated multimedia presentations that can be published on the Internet. Suitable for second and foreign language programs at any grade level, this activity would facilitate and encourage authentic communication while developing technological and organizational skills. It would also lend itself well to interdisciplinary teaching and would foster student creativity. This article explores how creating narrated multimedia presentations reflects pedagogical principles associated with second and foreign language teaching and learning, provides information about software that can be used to build them, and suggests research topics related to their creation.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.290
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0010.004
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.202
Teacher spread0.187 · 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 designQualitative
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

Citations0
Published2003
Admission routes1
Has abstractyes

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