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Record W1989890492 · doi:10.1109/ipcc.2013.6623900

MyCI: Crossing the Border of student and communication instructor relationships

2013· article· en· W1989890492 on OpenAlexaff
Lydia Wilkinson, Peter Weiß, Raj Grainger

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicCommunication in Education and Healthcare
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAcronymConfusionComputer scienceMnemonicIdentity (music)Process (computing)Engineering educationPoint (geometry)MultimediaMathematics educationPsychologyEngineeringLinguisticsEngineering management

Abstract

fetched live from OpenAlex

In 2010, the Engineering Communication Program (ECP) teamed up with Engineering Strategic Communication to find a visual way to resolve ECP's identity issues. We wanted to integrate the university and our Faculty's recently developed “brand” in order to represent ourselves visibly as part of the engineering world, and so developed a type treatment of our name, and an insignia that introduced an acronym for communication instructors - MyCI. It was intended to resolve the confusion between TAs and Communication Instructors by introducing a mnemonic, an easy to say, easy to remember counterpart to the acronym for Teaching Assistant, while reinforcing the idea that developing a relationship with a Communication Instructor helps the learning process. We are investigating student response to the insignia before beginning work with their CIs, and as they become more familiar with the program. Our study consists of a survey administered at three points in first year, as well as focused interviews. Results will provide information about the degree to which students can identify and differentiate Communication Instructors and instruction from other parts of their academic experience, and the effectiveness of the MyCI insignia in transmitting accurate information about ECP and its instructors.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.008
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.025
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.005
Scholarly communication0.0080.008
Open science0.0010.008
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.118
GPT teacher head0.468
Teacher spread0.350 · 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 source (direct Gemma or distilled Codex), 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".

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Citations1
Published2013
Admission routes1
Has abstractyes

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