Students Speak Out: The Impact of Participation in an Undergraduate Research Journal
Bibliographic record
Abstract
Universities are places where writing plays a central role in knowledge creation and dissemination (Graves, 2011). Students engage with writing in their courses, at their institution’s Writing Centre, and, perhaps more recently, in co-curricular projects such as an undergraduate research journal club. By participating in an undergraduate journal club, students develop critical thinking skills (Roberts, 2009), learn skills in research (Sandefur & Gordy, 2016), and produce knowledge (Neville, Power, Barnes, & Haynes, 2012). In this paper, we explore the impact of participation in a particular undergraduate research journal, the Undergraduate Journal of the Arts1 (UJA), on students’ interactions with academic writing. To do so, we first surveyed the landscape of undergraduate research journals in Canada. We then conducted an online survey and interviewed the UJA’s authors, editors, reviewers, and management board members. Our findings show that regardless of the roles they held at the UJA, participants benefitted from participation in terms of the development of their writing, interpersonal, and communication skills. We also discovered that participants faced time management constraints but were able to turn these obstacles into an opportunity to gain time management skills. Overall, our research has contributed to a sparse area of literature on undergraduate research journals. It also shows the value of an undergraduate research journal for student development.
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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 | 0.011 | 0.087 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.016 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 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".