Implementing a First-Year Experience Curriculum in a Large Lecture Course: Opportunities, Challenges and Myths
Bibliographic record
Abstract
This article documents the design, delivery, and evaluation of a first-year experience (FYE) course in media and communication studies. It was decided that CMNS 110: Introduction to Communication Studies would start to include elements to address a perceived and documented sense of disconnectedness among first-year students in the School of Communication at Simon Fraser University. These elements included coping, learning, and writing workshops facilitated by various services units across campus. We present results from surveys and focus groups conducted with students at the end of the course and discuss the predicaments that the new realities of an accreditation and audit paradigm—under the cloak of the neoliberal university—produce. On one hand the FYE course may help students transition into a post-secondary institution; on the other hand, too much emphasis on the FYE can result in an instrumental approach to education, jeopardizing the integrity of the course. We offer some insights into the challenges and opportunities of implementing FYE curricula within a large classroom setting.
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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 | 0.001 | 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 | 0.000 | 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) | 0.003 | 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".