“Professional” Acts: Analyzing Sites of Identity and Interactive Response in Chemical Engineering Students
Bibliographic record
Abstract
Professional" Acts: Analyzing sites of identity and interactive response in chemical engineering studentsIn September 2012, we began a five-year longitudinal study following eleven (11) Chemical Engineering and Applied Chemistry (CHE) students who began their second year of study in 2012-2013.The study focuses on the development of professional identity and voice in CHE students at the University of Toronto.In this paper, we will present an analysis of one participant's experience in two related sites of learning, identity and interactive response, which will allow us to showcase early "professional" acts, the responses to them, and the ways in which they evolved over the first year of the study period.It is important to note that we have only been able to look closely at a small portion of the data collected in the first year of this five-year, longitudinal study.As a result, we are not yet in a position to extrapolate, responsibly draw firm conclusions or identify trends, nor can we identify specific curricular or pedagogical implications.What we can do at this stage is highlight some of our initial findings that will inform the analysis of the rest of the data.In this paper, we focus on Téa, 1 one of eleven participants, based on the artifacts collected to date, although reference will be made to comments and work of other participants.We hope to show through this preliminary analysis how one student uses the experiences and opportunities provided both by the curriculum and this research project to develop a sense of professionalism and how to practice it as a chemical engineer as she tries on/tries out versions of her chemical engineer identity.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".