MétaCan
Menu
Back to cohort
Record W3036957145 · doi:10.24908/pceea.vi0.14161

LEGO SERIOUS PLAY AND THE GRADUATE ATTRIBUTES

2020· article· en· W3036957145 on OpenAlexaffvenue
R. Balakrishnan, Jillian Seniuk Cicek, Priya S. Mani, Danny Mann

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2020
Typearticle
Languageen
FieldEngineering
TopicBiomedical and Engineering Education
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsTeamworkTheme (computing)Grounded theoryContext (archaeology)Career developmentPsychologyInterpersonal communicationProcess (computing)PedagogyCreativityQualitative researchSociologyManagementComputer scienceSocial psychology

Abstract

fetched live from OpenAlex

As part of a longitudinal project to integrate career development supports into a biosystems engineering classroom, students engaged in a LEGO© Serious Play workshop and wrote reflections on their experiences. This workshop provided opportunities for teambuilding and deliberations on what constitutes a strong team. A constructivist grounded theory analysis of students’ reflections was conducted. Through this analysis, a preliminary theme of Perceptions of Engineering Skill emerged, with three subthemes of the necessity of teamwork and communication to engineering; the vulnerability in making interpersonal connection; and the explicit connection of engineering to creativity. These skills can be conceptualized within the CEAB graduate attributes and theorized within the systems theory framework (STF) of career development, which positions the students’ skill development within the larger context of their career. Ultimately, the preliminary findings of this study provide a starting point for further analysis, and for the development of an interview protocol for the longitudinal study this project sits within, with the overarching goal to investigate the impact of career supports and process of career development in a professional degree program.

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)0.001
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.438
Threshold uncertainty score0.474

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.009
GPT teacher head0.174
Teacher spread0.166 · 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
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the Canadian Engineering Education Association (CEEA)Same topicBiomedical and Engineering EducationFrench-language works237,207