Prior learning assessment at Northwest Community College: current status and future directions
Bibliographic record
Abstract
This study assessed the nature and potential of Prior Learning Assessment (PLA) at Northwest Community College (NWCC). The researcher, Karen Chrysler, worked with the college PLA committee and the University of Northern British Columbia to complete the study. The focus of the study was to determine the current level of support within the college community for PLA and to develop some recommendations. The participants were NWCC faculty, administrators and student advisors. Program Cluster Committee members and Student Success team members were asked to complete and return questionnaires. The Cluster Committee members returned a total of 58 surveys, making for an overall response rate of 65%. A total of 17 surveys were sent out and 10 were returned by the Student Success team members, making for a response rate of 59%. All twelve key informants, who were asked, agreed to participate and were interviewed. The concept of PLA itself was well supported by the program cluster members. The majority of faculty members would agree to an individual student request for PLA. Key informants definitely recognized the benefits for students, faculty and the college. The identified problems around PLA stem from the implementation and fall within three areas. First, there is a need to have operational language regarding PLA activity within the college's collective agreements. Second, there is a need to continue to provide training and professional development opportunities regarding the concept of PLA in general, and at NWCC specifically. Finally, it is important to continue the development of PLA policies and procedures in consultation with the appropriate stakeholders in the college community. Addressing these three areas will assist in addressing the expressed concerns of those individuals who are currently not supportive of PLA.
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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 | 0.036 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".