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Record W2887282874 · doi:10.24908/pceea.v0i0.10359

RELATIONAL LEADERSHIP IN DESIGN PROJECTS

2018· article· en· W2887282874 on OpenAlexafffundvenue
Claudia Bennett, Minha R. Ha

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2018
Typearticle
Languageen
FieldEngineering
TopicDesign Education and Practice
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsInterpersonal communicationPsychologyInterpersonal relationshipSocial skillsKnowledge managementApplied psychologySocial psychologyComputer scienceDevelopmental psychology

Abstract

fetched live from OpenAlex

Abstract – As a continuation of previous research pertaining to the self-assessed effectiveness in various interpersonal aspects by undergraduate Mechanical Engineering students as the Lassonde School of Engineering, the authors present in this paper, the findings of new research elaborating upon areas of concern surmised from the prior study. Motivation for this new research stems from the previous data relating to interpersonal and team relational skills inadequacies and the experiences of this paper, the authors present the findings of new research continue upon previous research pertaining to undergraduate students in Mechanical Engineering program self-assessment of effectiveness. The main objective of this paper is to present upon the common challenges of design team projects according to students, and the influence (or relation) effective and/or ineffective interpersonal relationship skills have upon those challenges. Results from this investigation indicates that human-related challenges experienced in team projects stem largely from ineffective manipulation of communication and relational skills and the various facets of team dynamics directly and indirectly affected by them. Additionally, research indicated that females team members had more gendered experiences with their teams. The author found there to be correlations between the negative female experiences and ineffective relational / interpersonal skills. 

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.476
Threshold uncertainty score0.557

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.081
GPT teacher head0.227
Teacher spread0.146 · 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 designNot applicable
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

Citations1
Published2018
Admission routes3
Has abstractyes

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