Students’ and Educators’ Perceptions of Competency-based Assessments in Communication Sciences and Disorders Education in Canada
Bibliographic record
Abstract
Educational institutions offering Communication Sciences and Disorders programs aim to equip students with essential knowledge and skills required to become competent audiologists and speech-language pathologists, capable of meeting the demands of these rapidly evolving professions. Competency-based assessments (CBAs) play a crucial role in evaluating students' readiness by measuring their achievements against industry standards. Thus, the purpose of this study is to identify the CBAs used in Communication Sciences and Disorders education programs and to investigate the perceptions of both students and educators’ regarding the current practice of CBAs. A descriptive cross-sectional design was employed, using two parallel online surveys that consisted of scaled and open-ended questions to collect data independently from 44 students and 16 educators. The present study confirms that many Canadian universities employ some form of programmatic assessment approach, which involves using a combination of various low-stakes CBAs over time to determine students’ clinical competence. Many of these assessments are conducted in real clinical settings to evaluate performance in practice, rather than assessments conducted to evaluate the demonstration of learning in a controlled clinical environment. Among them direct observations by clinical educators are the most popular and preferred method of assessment by many students and educators. Both students and educators felt that the current CBA practices are well-organized, effective in achieving their purposes and maintain good quality. Given the crucial role of CBAs in evaluating students' clinical competence, the insights provided by this study are essential for further enhancing the effectiveness of CBA systems. Such improvements can lead to accurate measurement of student outcomes in clinical practice against regulatory competencies and contribute to the continued advancement of the audiology and speech-language pathology professions.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".