Faculty Intentions, Preparation and Learning Processes Influencing Student Career Development
Bibliographic record
Abstract
Career education has become central to the lives of young people as it has moved from the periphery to the core (Ho, 2017, Shea, 2010) in secondary and post-secondary school activities. In Ontario, the integration of practical career planning tools (such as myBlueprint) and work-integrated learning (such as internships, field placements, co-ops and professional practicums) into some university programs has occurred and increased (Co-operative Education and Work-Integrated Learning Canada [CEWIL], 2021). Underpinning these activities has been a focus on career development theory, a “continuous lifelong method of developmental experiences that focuses on seeking, getting and processing information regarding self, occupational and educational alternatives, lifestyles and role choices” (Firmante, 2019, p. 2). The concept of career influencers (CIs) has emerged within the literature, to reflect how key players in student career development activities have the “ability to support students [to] thrive in this uncertain world of work” (Ho, 2017, 2019; Stebleton & Ho, 2023, pp. 189-190). Recent studies reveal, however, that it remains a challenge for faculty to see themselves in career influencing roles (Ho, 2017, 2019; Stebleton & Ho, 2023). This challenge is complicated further by a limited understanding of the extent to which faculty have exposure to the foundations of career development theory or to effective career-influencing principles and practices (Ho, 2017). Faculty uptake of the role of career influencer is relevant to an institution’s graduate employability success since students highly value their interactions with faculty members and rely on them for guidance and support (Ho, 2019; Grantham et al., 2015). In the Ontario context, where new performance-based metrics are intended to increasingly inform post-secondary funding, graduate employability outcomes figure centrally. The preparation of faculty to do the effective work of career influencing, and the need to understand the extent of their preparation to do so, is set against complex and long-standing relationships between the labour market and higher education which have never been more fraught. The following study explored a small sample of post-secondary teaching faculty: their attitudes and views about the importance of student career development and the extent to which they intend and prepare to influence student career development within the learning processes. This study took place in a large teaching-intensive undergraduate Canadian university, located in Ontario. Participants indicated that the integration of career elements into the curriculum was important and were motivated to try. The study helped to locate and distinguish between career influencing and skill development activities undertaken by participants and suggests that the preparation of faculty to do the work of student career development more coherently inside the classroom should be explored.
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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 | 0.007 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".