The Use of Learning and Study Strategies by Students Taking a Remedial Workshop at Selkirk College, Castlegar, British Columbia
Bibliographic record
Abstract
The purpose of this study was to discover what the students’ use of learning and study strategies, as measured by the Learning and Study Strategies Inventory (LASSI), is at Selkirk College on the Castlegar Campus, British Columbia. Nineteen students completed the second, online version of LASSI, developed by Weinstein, Palmer, and Schulte (2002) at the beginning of the semester and prior to taking a 15-hour “Student Success Skills” workshop, and again after having completed the workshop and after having completed one semester. Overall the results confirm other studies that students, in general, are not prepared for the college experience regarding the non-content related area of learning strategies, and although scores and percentiles increased in all ten LASSI scales and seven out of the ten LASSI scales experienced a significant increase in means (p>0.5), students still need to improve their learning and study strategies further. \nBecause of the small sample size, methodological weaknesses, and Selkirk College’s unique geographical and demographical situation, care should be taken when trying to generalize the results of this study to other student populations and institutions. Nevertheless, this research gives rise to numerous possibilities for follow-up studies, which include large-scale studies for the entire student population at Selkirk College, small-scale program-specific studies, as well as correlation studies. The existing data can be used for the improvement of the currently existing Learning and Study Skills Centre on the Castlegar Campus and the program it offers, as well as the development of a first-year, three-credit, university-transfer course in college success skills.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".