“It’s not my dream, actually”: students’ identity work across figured worlds of construction engineering in Sweden
Bibliographic record
Abstract
Research in engineering education has pointed to the need for new engineers to develop a broader skill-set with an emphasis on “softer” social skills. However, there remains strong tensions in the identity work that engineers must engage in to balance the technical demands of the discipline with the new emphasis on heterogeneous skills (Faulkner, Social Studies of Science 37:331–356, 2007). This study explores how three unconventional students experience these tensions in the final year of their construction engineering program, and as they move in and out of workplace field experiences. Using a figured worlds framework (Holland et al., Identity and agency in cultural worlds, 1998), we explore the dominant subject positions for students in construction engineering classroom and workplaces in a 3-year Swedish engineering program. Results demonstrate that dominant subject positions for construction engineers can trouble students’ identity work as they move across classroom and workplace settings. This study expands our knowledge of the complexity of students’ identity work across classroom and workplace settings. The emergence of classroom and workplace masculinities that shape the dominant subject positions available to students are shown to trouble the identity work that students engage in as they move across these learning spaces. We examine students’ identity strategies that contribute to their persistence through the field. Finally, we discuss implications for teaching and research in light of students’ movements across these educational contexts.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.010 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".