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Record W3036319473 · doi:10.24908/pceea.vi0.14187

ENGINEERING UNDERGRADUATES AND THEIR SELF-REPORTED CONFIDENCE AND PROFICIENCY LEVELS IN LIFELONG LEARNING (A12)

2020· article· en· W3036319473 on OpenAlexafffundvenue
Kathryn Marcynuk, Anne Parker, Norma Godavari

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2020
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Curriculum Development
Canadian institutionsUniversity of Manitoba
FundersUniversity of Manitoba
KeywordsCapstoneLifelong learningTeamworkCompetence (human resources)Communication skillsMedical educationPsychologyCapstone courseMathematics educationPedagogyCurriculumComputer scienceMedicineManagement

Abstract

fetched live from OpenAlex

This paper reports on what we found when we surveyed second-year students in a Technical Communication class, once at the beginning of the semester and again at the end, and then when we surveyed two senior capstone design classes, one in Mechanical Engineering, one in Electrical and Computer Engineering, and one in Civil Engineering. In all these iterations, we asked students to indicate their levels of confidence and proficiency in their writing and speaking skills (communication skills), teamwork and personal skills development (lifelong learning). When we surveyed our second-year students, they indicated that they were only moderately confident in their communication skills (the aggregate was mostly 3 or slightly more on a scale of 5). At the end of the semester, when we asked them what they believed would be the competency level expected of them in these areas when they graduated, that number jumped to 4.5 on average. These students, however, were also decidedly more confident in their teamwork and lifelong learning skills, where the average hovered close to 3.5. On average, the capstone students were likewise confident in these areas, even slightly more so (3.87). Given the rapidity with which technical information grows and the complexity of the world around us, engineering students must be more prepared than ever to develop the drive to keep learning so that, as practicing professionals, they are equipped to maintain their competence and contribute to the advancement of knowledge.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.130
Threshold uncertainty score0.842

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 head0.007
GPT teacher head0.175
Teacher spread0.169 · 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

Citations3
Published2020
Admission routes3
Has abstractyes

Explore more

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