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Record W3013261139 · doi:10.24926/iip.v11i1.2333

An Infographic Assignment to Translate Self-Care Therapeutics into Practical Application

2020· article· en· W3013261139 on OpenAlexafffund
Nardine Nakhla, Paul Malik

Bibliographic record

VenueINNOVATIONS in pharmacy · 2020
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsUniversity of Waterloo
FundersCanadian Institutes of Health Research
KeywordsInfographicComputer scienceInformation retrievalData mining

Abstract

fetched live from OpenAlex

INNOVATION: An infographic assignment was developed and integrated into an advanced self-care therapeutics elective course in a School of Pharmacy to facilitate practical communication of dynamic and innovative approaches to patient care while supporting diversity in assessment. DESCRIPTION: The 'Spotlight on Self-Care' assignment required pharmacy students to develop three infographic deliverables detailing comprehensive care for one minor ailment. The three deliverables were: 1) a magazine insert for healthcare professionals, 2) a patient-friendly handout, and 3) a pharmacists' companion practice tool. All deliverables were assessed by rubrics using consistent criteria, including: clinical content, logical presentation, research quality, visual elements and formatting. The five highest-scoring magazine inserts were offered publication in the Pharmacy Practice and Business Magazine after peer review. CRITICAL APPRAISAL: The submitted infographics put clinical content from the course into action by leveraging recent trends in effective communication. As an assessment, the infographic assignment recognized a unique profile of skills in the students that was statistically different from the profile of skills that was evaluated by the multiple-choice examinations. The key issues to address include reducing grading time requirements and developing strategies to detect copyrighted materials. Future investigations into the nature of the skills gained by the students through the exercise, as well as their perceptions regarding the professional value of the exercise, are important for refining the administration of this assignment.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.884
Threshold uncertainty score0.606

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.183
GPT teacher head0.502
Teacher spread0.319 · 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 teacher head, not a consensus.

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

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

Citations4
Published2020
Admission routes2
Has abstractyes

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