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Record W6986540563

PORTFOLIOS FOR LEARNING AND RE-CREDENTIALING FOR PHARMACISTS

2023· dissertation· en· W6986540563 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2023
Typedissertation
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsnot available
Fundersnot available
KeywordsPortfolioFeelingExperiential learningElectronic portfolioProfessional learning communityPerceptionActive learning (machine learning)Professional developmentLifelong learning
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this study was to explore the experiences of pharmacists using learning portfolios as part of continuing professional learning and re-credentialing in Saskatchewan. This study sought to describe the learning experiences and activities of the participants, and their perception and experience of portfolio use as part of their learning experiences. More specifically, the study focused on the participants' use of the learning portfolio as a self-assessment tool. \nSemi-structured interviews were conducted with 14 pharmacists who participated in a pilot study investigating the use of learning portfolios in the province. Participants' portfolios and other printed matter relating to participants' experiences were also used in this study. The information obtained was analyzed to identify categories and themes emerging from the participants' experiences. \nResults showed that participants learned via instruction from continuing professional education programs, and from self-initiated personal inquiry and experiences. Participants' learning efforts were directed by their professional goals and interest, and moderated by situational factors. While participation in educational programs helped participants to keep up-to-date, maintain a broad knowledge base, and meet re-licensing requirements, learning through personal inquiry and experiences were directed by meeting workplace needs. \nParticipants understood self-assessment to be a self-reflective process whereby they identified their personal strengths and weaknesses, and evaluated their progress and achievements. Difficulties with self-assessment occurred when participants did not have sufficient knowledge in the subject matter, or when they did not know what the larger professional community expected of them. \nParticipants were initially anxious and uncertain about learning portfolio use. These feelings abated with continued use of the learning portfolio. Participants indicated no changes in their learning activities with portfolio use. The only change was to record their learning into a portfolio, rather than to collect continuing education units from participating in educational programs for re-credentialing purposes. \nParticipants used the learning portfolio primarily as a record to showcase their learning activities. Majority of the participants did not use the portfolios actively for self- assessment, although when reporting according to the portfolio format presented, they had to identify their learning needs and evaluate their learning outcomes. \nDifficulties with portfolio use were related to the novelty of the process, re-credentialing context, discrepancy between individual reporting style and portfolio format, and time constraints. Benefits of portfolio use resulted from the need to account for one's learning in writing, reporting according to the portfolio format presented, and the recognition of a wider range of learning activities for re-licensure.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0010.004
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.022
GPT teacher head0.308
Teacher spread0.286 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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