Comparing Holistic and Mixed-Approach Rubrics for Academic Poster Quality
Bibliographic record
Abstract
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.
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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 | 0.122 | 0.318 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".