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Record W1507507185

Understanding I/We positions in a blended university course: Polyphony and chronotopes as dialogical features

2014· article· en· W1507507185 on OpenAlexaff
Feldia Fedela Loperfido, Nadia Sansone, Maria Beatrice Ligorio, Nobuko Fujita

Bibliographic record

VenueIRIS Research product catalog (Sapienza University of Rome) · 2014
Typearticle
Languageen
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsDialogical selfPolyphonyChronotopeFocus (optics)SituatedSociologyFacilitatorPedagogyPsychologyArtSocial psychologyComputer scienceLiteratureArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

This paper uses Dialogical Self Theory to explore university students’ I/We positions before and after participating in a blended course with both individual and collaborative learning activities. Two focus group discussions were held; one at the beginning and the other one at the end (18 students in total; 3 M, 15F; average age 24 years old). The focus groups were analyzed through discursive analysis by referring to the Bakhtinian concepts of chronotope and polyphony, as dialogical features of positioning. Results show that at the end of the course the polyphony became richer, including also technology. This was initially “suppressed” and became later a voice supporting both We-position and collaborative learning. A shift from initial I-positions rooted in a broad chronotope (including past, present and future) toward We-positions placed in the specific and situated chronotope of the course occurred. This result poses the question of sustainability and transferability of innovation.

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)0.004
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.753
Threshold uncertainty score0.836

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
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 head0.123
GPT teacher head0.386
Teacher spread0.263 · 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 designObservational
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

Citations4
Published2014
Admission routes1
Has abstractyes

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