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Record W2350731322 · doi:10.5539/elt.v9n6p162

Teaching Shakespeare in the Digital Age: The eZoomBook Approach

2016· article· en· W2350731322 on OpenAlexvenueno aff
Christine Évain, Chris De Marco

Bibliographic record

VenueEnglish Language Teaching · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicLiteracy, Media, and Education
Canadian institutionsnot available
Fundersnot available
KeywordsReading (process)Computer scienceZoomMathematics educationSubject (documents)Function (biology)Process (computing)Collaborative writingMultimediaWorld Wide WebPsychologyLinguisticsEngineeringProgramming language

Abstract

fetched live from OpenAlex

<p>What collaborative process can teachers offer in order to stimulate their students’ reading of and writing on Shakespeare’s plays? How can new technologies contribute to facilitating the classroom experience? The eZoomBook (eZB) template was designed for teachers to create and share multi-level digital books called “eZoomBooks” that allow readers to access enriched versions of the original, organized according to different tabs related to places mentioned in the original text. A zooming in and out function enables the readers of the eZoomBooks to navigate freely between the original and the enriched tabulated versions. This paper focuses on a pilot study of the methodology using a simplified version of the template. The targeted learners were English as a Second Language engineering students. Our objective is to show that the eZB framework and pedagogical applications are especially appropriate in making a difficult subject easier to teach (giving and correcting group assignments) and learn by providing learners an innovative and motivating approach to reading literature.</p>

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.263
Threshold uncertainty score0.923

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
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 head0.017
GPT teacher head0.237
Teacher spread0.220 · 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 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

Citations5
Published2016
Admission routes1
Has abstractyes

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