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Record W2764058625

De-duotanging Core French: Case study of a Digital Learning Space Portfolio in a Grade 8 Classroom

2017· dissertation· en· W2764058625 on OpenAlexaboutno aff
Susanna Jurkowski

Bibliographic record

VenueQSpace (Queen's University Library) · 2017
Typedissertation
Languageen
FieldSocial Sciences
TopicEducation and Technology Integration
Canadian institutionsnot available
Fundersnot available
KeywordsCore (optical fiber)PortfolioSpace (punctuation)Mathematics educationComputer sciencePsychologyBusinessTelecommunicationsOperating system
DOInot available

Abstract

fetched live from OpenAlex

This case study explored the use of a digital learning space portfolio by Grade 8 French as a Second Language (FSL) students. The focus of this study was on the meaning students assigned to the use of the digital learning space portfolios and how their perceptions of themselves as FSL learners changed while using the system. The study addresses the existing gap in the literature. The digital learning space portfolio was created based on the needs of adolescent learners as identified in the literature. The literature also suggests that embedding assessment and learning in one place, that is accessible to all, improves student engagement. The study took place at a rural school in Eastern Ontario and included fourteen students, six male and eight female. The results indicate that students had positive experiences using the digital learning space portfolio which supported student participation in the FSL classroom. In addition, the students reported positive perceptions of themselves as FSL learners while they were engaged in using the tool. The results also indicate that the teacher was integral in developing and modelling positive use of the digital learning space portfolio. Further research regarding the use of the digital learning space portfolio in other disciplines and at other grade levels should focus on teacher support to ensure successful use of these types of tools in education.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.796
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.018
GPT teacher head0.270
Teacher spread0.252 · 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
Published2017
Admission routes1
Has abstractyes

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