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Record W2547557768

Differences in first year gender engagement through cross-disciplinary design projects

2014· article· en· W2547557768 on OpenAlexaboutno aff
Emily Marasco, Laleh Behjat, Marjan Eggermont

Bibliographic record

Venue25th Annual Conference of the Australasian Association for Engineering Education : Engineering the Knowledge Economy: Collaboration, Engagement & Employability · 2014
Typearticle
Languageen
FieldEngineering
TopicBiomedical and Engineering Education
Canadian institutionsnot available
Fundersnot available
KeywordsDisciplineCreativityDiversity (politics)EmployabilityStudent engagementTeamworkEngineering educationPracticumEngineeringPsychologyEngineering ethicsPedagogyPublic relationsSociologyPolitical scienceEngineering managementSocial scienceSocial psychology
DOInot available

Abstract

fetched live from OpenAlex

Background: Leading engineering companies across a variety of industries, such as Intel and Imperial Oil, are launching education initiatives to encourage well-rounded, diverse and creative future engineers (Intel Corporation, 2012) (University of Calgary, 2013). Employers are looking for graduates capable of critical, creative thinking, multi-disciplinary teamwork, and cross-disciplinary innovation, as well as demonstration of engineering graduate attributes. This work examines the use of student interests to create cross-disciplinary first year design projects to encourage engagement, creativity and diversity. Purpose: The long-term hypothesized impact of this work is to increase the level of engagement among first year engineering students, consequently improving retention and enhancing the comprehension of engineering design practices and attributes. Spanning multiple years, this study includes the development of real world design problems with connections to subject areas that are of interest to incoming students, including political/societal issues, artistic design concerns, and creative innovations. Preliminary analysis and implementation of these cross-disciplinary projects will be discussed, as well as considerations taken for the 2014 introductory design course projects. Design/Method: The outcomes for this study have been tested using both qualitative and quantitative research methods. Student interests and hobbies were measured through an anonymous survey distributed in 2012 and 2013. These surveys also examined the perceptions that students hold around engineering, and their opinions on gender diversity and gender capabilities within the field. In 2013, students were also asked to rate their first year design course projects and identify some of the positive and negative experiences found throughout the laboratory sessions. These projects were developed by a team of interdisciplinary researchers and incorporated engineering design techniques and graduate attributes with fine arts, societal issues, mathematics, physics, research, technology and writing. Results: To date, this study has shown trends regarding student interest in first year design projects. The quantitative data showed that 72% of female students care more about a project when it has real world applications, and their most preferred project in 2013 related to a local disaster issue. On the other hand, 72% of male students stated that they care more about a project when it challenges them. Their favourite project in the course was the least constrained design challenge with a single focused task. Male students were also significantly more likely to care about a project when it is very technical. Regardless of gender, 97% of all the students agreed or strongly agreed that they care more about a project when it relates to their hobbies and interests. Student perspectives and feedback will be examined again for the first year design course being run in September 2014. Conclusions: In summary, this research examines how gender diversity affects student engagement in the design process. The projects developed as part of this work also encouraged critical thinking, teamwork, and creativity, which are skills required in the engineering workplace. From the results shown, applying cross-disciplinary methods and integrating societal issues into introductory engineering design can help to create engaging engineering projects that appeal to both male and female students.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.408
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.043
GPT teacher head0.282
Teacher spread0.239 · 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.

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

Citations0
Published2014
Admission routes1
Has abstractyes

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