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Record W4408051164 · doi:10.1016/j.ajpe.2025.101379

Comparing Holistic and Mixed-Approach Rubrics for Academic Poster Quality

2025· article· en· W4408051164 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAmerican Journal of Pharmaceutical Education · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicAcademic Writing and Publishing
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsRubricQuality (philosophy)Computer scienceMultimethodologyPsychologyMathematics education

Abstract

fetched live from OpenAlex

OBJECTIVE: Poster quality at academic conferences has varied. Furthermore, the few poster-quality rubrics in the literature have limited psychometric evidence. Thus, we compared holistic vs mixed-approach scoring using a recently created poster rubric, scored by multiple raters, to evaluate validation evidence and time-to-score utility. METHODS: Sixty research posters were randomly selected from an academic conference's online poster repository. Using a previously created rubric (and without rubric training), 4 pharmacy education faculty members with varying levels of poster-related experience scored each poster. Initially, each rater holistically scored the posters, providing a single overall score for each. Approximately 1 month later, the raters scored the posters again using a mixed approach, assigning 4 sub-scores and a new overall score. We used the Generalizability Theory to assess the effect of rater experience and the Rasch Measurement Model to examine rating scale effectiveness and construct validation. Time-to-score for each poster was also compared. RESULTS: Generalizability Theory showed greater reliability with more experienced raters or when using the mixed approach. Rasch analysis indicated that rating scales functioned better with the mixed approach, and Wright maps of the construct provided useful measurement validation evidence. Raters reported scoring more quickly (30-60 s per poster) with holistic scoring, though differences in rater experience affected reliability. Meanwhile, mixed-approach scoring was slightly slower (60-90 s per poster), but the impact of the rater experience was reduced. CONCLUSION: Scoring was slightly faster with the holistic approach than with the mixed-approach rubric; however, differences in rater experience were lessened using the mixed-approach. The mixed approach was preferable because it allowed for quick scoring while reducing the need for prior training. This rubric could be used by students and new faculty when creating posters or by poster-competition judges. Furthermore, mixed-approach rubrics may be applied beyond posters, including oral presentations or objective structured clinical examination stations.

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.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.806
Threshold uncertainty score0.340

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.168
GPT teacher head0.438
Teacher spread0.270 · 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