The Importance of Support Programs to Science and Technology Students Enrolled at Vancouver Island University Nanaimo, British Columbia
Bibliographic record
Abstract
It is important to get an understanding of 1) how Science and Technology (S&T) \nstudents feel supported at Vancouver Island University and 2) the level of knowledge of \nthe available support programs by the faculty themselves since they are the first point of \ncontact by students looking for guidance. \nThis study was designed with a mixed methodology approach that included conducting \non-line surveys and face to face interviews. Surveys were issued to S&T faculty at the \nNanaimo Campus as well as to 400 students enrolled in S&T based courses during the \nspring 2016 semester. Fifteen faculty and seventy student participants were asked to \nprovide comments on how to improve the overall student experience in the upper part of \nthe campus. Face to face interviews were conducted with 8 student volunteers. The \nresponses provided insight to what is important to S&T students at VIU. The \nimportance of feeling connected with other like-minded peers, and faculty were very \nstrong factors in the overall positive academic experience. \nThrough the use of thematic analysis, responses to the suggestions from both surveys \nand the interview responses were coded and categorized. These major categories \nincluded academic support programs, electronic support, social support, faculty support, \nand program structural support, barriers to support and finally, recommendations. \nResults showed what was important to the enrolled students were also important to the \nfaculty: accessibility to support programs, peer support programs, feeling connected to \nfaculty and other students, and interdisciplinary discussion. Student participants \nexpressed the importance of social media to feel connected to the campus and further \ndevelop student social structure. \nDuring the interview process, barriers to accessing support were identified that included \nfirst year struggles, scheduling, transit/parking, computer access, library access, \nlocation and faculty access. \nThe researcher provided a list of recommendations that may be useful for faculty and \nVIU Administration in identifying key supports that could be offered with a science \nbased focus in the upper campus.
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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 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".