Using Career Education to Help Students Build and Articulate Employability Skills
Bibliographic record
Abstract
For 80% of first-year students, the highestmotivators for attending University are related to gettinga good job and preparing for a career. Research hasshown that post-secondary students with some careergoals and engaged in career development experienceshave higher levels of engagement, academic performance,mental health, and persistence. Employers are placing agreater emphasis on a student’s skills and experience intheir recruitment process. No longer does a Universitydegree guarantee employment success upon graduation.Career education can provide the foundation andframework to help students make these connections andbe successful in transitioning into the world of work. Byunderstanding what employers’ value and knowing howto build and gain skills and experiences while inUniversity, students can enhance their employabilityoutcomes and successfully launch into their career upongraduation.The Faculty of Engineering along with Career Services atthe University of Manitoba, have developed an innovativepartnership to deliver career education embedded inrequired 1st and 2nd year Engineering courses. Theprogram called “Your Career Starts Here” wasintroduced in the Fall 2013 term in Design inEngineering (Eng 1430) and Technical Communications(Eng 2010) courses. The learning outcomes of theseinteractive modules for students include: recognizingcareer development as a life-long process of learning;identifying and describing employability skills; identifyingwhat employers value in the recruitment process;matching skills with an employer’s needs as well asidentifying gaps; and reflecting on opportunities atUniversity to build, enhance and develop skills andexperiences. Academic courses, work experiences,cooperative education and internship programs, researchexperiences, and involvement in campus groups and cocurricularprogramming are identified as careerdevelopment opportunities at the University of Manitoba.The modules include group discussions and acitivities to help students understand and identify ways to build theirskills and experiences as well as how to articulate theseskills to increase their employability outcomes upongraduation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".