MétaCan
Menu
Back to cohort
Record W4391600548 · doi:10.18260/1-2--44459

The Impact of Documenting Design Thinking, the Engineering Design Process Canvas, and Project Communication on Design Self-Efficacy of First-Year Students

2024· article· en· W4391600548 on OpenAlexaff
Jack Bringardner, Elizabeth Castroverde, Paige Charette, Salma Moutasim Salaheldin Abuelgasim, McKenna Yoshinobu, Rui Li, Victoria Bill, Ingrid J. Paredes

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicDesign Education and Practice
Canadian institutionsYork University
FundersAmerican Society for Engineering Education
KeywordsEngineering design processProcess (computing)Computer scienceDesign processProcess designDesign thinkingEngineering managementSoftware engineeringArchitectural engineeringEngineeringWork in processHuman–computer interactionMechanical engineeringProgramming languageOperations management

Abstract

fetched live from OpenAlex

This complete evidence-based practice paper describes a study of three design interventions and a survey conducted of first-year engineering students at New York University to understand the impact on their design self-efficacy. The research question addressed in this study is whether there is an impact of documenting the design thinking process, the engineering design process, and project communication on students' level of self-efficacy to solve engineering design problems. And if so, to what extent did students find value in using the documentation activities for enhancing their engineering design capabilities? The aim of this study is to identify the best strategies for improving first-year students' design skills that will help them succeed in future design projects. Many tools have been developed to improve engineering design skills of first year students like design thinking exercises, the Engineering Design Canvas, and strategies for communicating ideas. The evidence-based practice described in this study consists of in-class exercises for each of these tools which include 1) an IDEO design thinking worksheet at the beginning of the project, 2) the Engineering Design Canvas at the middle of the project, and 3) the Heitmeier Catechism design communication strategies at the end of the project.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.830
Threshold uncertainty score0.439

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.030
GPT teacher head0.335
Teacher spread0.305 · 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 designSimulation or modeling
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
Published2024
Admission routes1
Has abstractyes

Explore more

Same topicDesign Education and PracticeFrench-language works237,207