The Development of a Self-Assessment Instrument to Evaluate Selected Competencies of Continuing Education Practitioners
Bibliographic record
Abstract
Adult and continuing education practitioners must engage in continuing professional education as a means of developing and maintaining their professional competence. This paper reviews the literature on competencies for continuing educators and examines the strengths of existing instruments for continuing educators to self-assess their competencies. One of the challenges in this process has been a means to systematically and comprehensively assess existing knowledge and skills and to identify where competencies are not adequate. This paper describes an assessment instrument that addresses these challenges and builds on the strengths of existing tools. It describes the development of a tool through a consultative process that identified the range of practitioner competencies required of adult and continuing educators. The assessment tool incorporates a behaviorally based approach to assessing identified competencies. It is unique because it addresses many of the needs identified in the literature including well articulated criteria for making judgments about a person’s current knowledge and skills, a format that allows for clear identification of gaps in learning so that meaningful professional development can take place, the clear structure needed to develop a “portfolio” of skills, and a format that requires the provision of evidence to support claims of proficiency in the identified areas. Though the development of the tool was initiated through the development of Prior Learning Assessment and Recognition processes, it is anticipated that it will be useful for continuing educators to undertake self-assessments as a basis for hiring, career laddering, and planning their ongoing professional development activities and goals. In both cases it provides a framework for meaningful reflection, assessment, gap identification, and planning.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".