Getting Ready for the Real World: Final-Year Students and Their Virtual Recruitment Event Experiences
Bibliographic record
Abstract
Research problem: This study explores the experiences and perceptions of final-year undergraduate business students at a comprehensive university in central Canada regarding virtual recruitment events and their role in networking and advancing career opportunities for soon-to-be graduates. Although virtual recruitment events (activities that occur online to bring together employers and job seekers) have become more common since the COVID-19 pandemic, little research has focused on the student perspective of these events. Research questions: 1. What are the expectations and perceptions of university students regarding networking and advancing their job search? 2. What are the expectations and perceptions of university students regarding virtual recruitment events? 3. How do university students perceive the relationships between virtual and in-person events? a. Are virtual events seen as complementing or replacing in-person events? b. What are the strengths and limitations of virtual recruitment events? 4. How do virtual events support university students in forming social networks necessary for effective career advancement? Literature review: Social Network Theory and Weak-Tie Network Theory provide a foundation for understanding how relationships influence job search outcomes, with an emphasis on weak-tie (casual, infrequent) connections in accessing new opportunities. Genre theory helps explain how students interpret and engage with recruitment events based on familiar communication norms. Virtual events, while offering accessibility benefits to attendees, raise concerns about engagement and connection. Career Services play a key role in organizing these events, preparing students, and adapting formats to meet evolving needs. Methodology: This qualitative study used a collective case study approach. Five final-year undergraduate business students or recent graduates from a comprehensive university in central Canada were selected through purposive sampling. They were interviewed using semi-structured interviews, which were analyzed using thematic analysis following Braun and Clarke’s (2006) six-step method. Results and Conclusions: The findings suggest that students view networking as critical to job search success and career advancement. Although virtual recruitment events offer convenience and accessibility, participants agreed that they complement, but do not replace, in-person events. Virtual events are useful for gathering information, but students rely more on in-person experiences to build strong professional relationships. Additionally, the findings suggest that networking is a skill developed through practice, that intentional efforts made by Career Services and recruiters can support students in building their professional networks.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.009 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".