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Record W2295570895 · doi:10.18192/olbiwp.v4i0.1105

Digital Documentation: Using digital technologies to promote language assessment for the 21st century

2012· article· en· W2295570895 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueOLBI Journal · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicStudent Assessment and Feedback
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsFormative assessmentDocumentationCurriculumComputer scienceProcess (computing)Language acquisitionDigital learningMultimediaMathematics educationPedagogyPsychology

Abstract

fetched live from OpenAlex

The article describes how the use of digital technologies such as iPod and iPad contributes to the gathering of tangible evidence of students’ learning, and promotes the emergence of a new means of formative assessment that supports language teaching and learning for the 21st century. In particular, the use of such technologies by Early French Immersion learners promotes digital documentation (audio and video recording) of language learning across the curriculum, to help make the learning and thinking process more visible to teachers and students. The process of revisiting the digital documentation constitutes a new means of formative assessment that informs both the teaching and the learning. Moreover, the use of digital technologies allows students to become active participants in their own learning and assessment process. Finally, the article examines the role of oral language in the digital documentation and revision process and how this enhances the assessment of students’ learning in the 21st century language classroom.

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.

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 categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.861
Threshold uncertainty score0.999

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 communication0.0020.002
Open science0.0000.000
Research integrity0.0000.000
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 head0.029
GPT teacher head0.384
Teacher spread0.354 · 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