Integrating career development into biosystems engineering
Bibliographic record
Abstract
Career development is an important aspect of emerging adulthood and the experiences of post-secondary students. Particularly in the modern context, where technological advancement has significantly altered the world of work and will continue to do so, students need to be equipped with the skills to manage their careers and move forward amidst career uncertainty. This study is a grounded theory examination of students’ experiences of career supports integrated into a biosystems engineering design course offered in the first year of a Biosystems Engineering Program at the University of Manitoba. Very little research has been conducted on the integration of career development into the classroom, though there are promising preliminary studies that speak to the potential positive implications for students. Using the systems theory framework of career development as the theoretical framework, this study seeks to better understand how students in a professional engineering program, who are typically thought to be career decided, experience in-class career supports. The literature review in this thesis examines the central focus of this study, the career development of post-secondary students, and covers two cognate areas, emerging adulthood with a focus on vocational and engineering identity development and reflection in experiential learning. Through utilization of constructivist grounded theory, a rigorous, social constructivist approach to the study design and qualitative analyses of participant interviews and student coursework is presented. The study proposes a low-level theoretical model of these experiences, entitled Becoming a Biosystems Engineering Student, which demonstrates the ways high school students interested in math and science are drawn to first-year engineering, where they tend to use deficit language to describe biosystems engineering. Students then progress to biosystems by either stumbling into biosystems engineering or a planned journey to biosystems engineering. Once in biosystems, students are influenced by the integrated career development curriculum, where they become more connected to their peers, professionals, and program, learn more about the labour market, clarify career options, and eventually begin to see options for themselves, define biosystems, and increase their comfort in an uncertain labour market. This progresses over time, facilitated by the career curriculum integrated into their coursework, with students shifting from identities as more general students to a biosystems engineering student identity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".