Assessing student dance performance in physical education teacher education: a student–expert comparison of analytic rubric scoring and adaptive comparative judgment

Background Assessing dance performance in physical education teacher education (PETE) requires judges to integrate technical and aesthetic qualities. Analytic rubrics make relevant dimensions explicit, whereas Adaptive Comparative Judgment (ACJ) elicits holistic pairwise decisions and produces a relative performance scale. This study compared the outcomes and student perceptions associated with the two approaches. Methods Seventeen pre-service teachers assessed 46 video-recorded student dance performances using an analytic rubric and ACJ. An expert reference was derived from five PETE lecturers who had assessed the performances live using the rubric and subsequently evaluated the video recordings through ACJ. Analyses examined rubric reliability and ACJ precision, convergence between method-derived rankings, student–expert rank alignment, cross-condition rubric score differences, and students’ perceptions of ease of use, usefulness, transparency, and fairness. Results Rubric- and ACJ-derived rankings were strongly associated within the student panel (Spearman's ρ = .863) and the expert reference panel ( ρ = .879). Aggregated student rankings also aligned closely with the expert-reference rankings under rubric scoring ( ρ = .890) and ACJ ( ρ = .888), with no clear difference in alignment between the methods. Aggregated student rubric scores showed high reliability, ICC(2,17) = .955, while ACJ scale separation reliability was .780 for students and .836 for experts. Student video-based rubric scores were, on average, 0.77 points higher than the archived live expert consensus scores. Students perceived ACJ as easier to use but the analytic rubric as more transparent. Perceived usefulness did not differ clearly, while fairness ratings descriptively favored the rubric. Conclusion Analytic rubric scoring and ACJ produced strongly convergent aggregate rankings, and the aggregated student panel differentiated relative performance quality in ways closely aligned with the expert reference under both approaches. However, the methods differed in score interpretation and perceived transparency. The results support considering ACJ as a complementary approach for digitally supported assessment and moderation rather than as a direct replacement for criterion-based summative assessment.

Authors

Institutions

Publication Details

Journal
Frontiers in Education
Published
2026-10-29
DOI
https://doi.org/10.3389/feduc.2026.1988290
Primary Topic
Student Assessment and Feedback
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Assessing student dance performance in physical education teacher education: a student–expert comparison of analytic rubric scoring and adaptive comparative judgment

Eric Jeisy
1 links
Frontiers in Education
Student Assessment and Feedback
article

Assessing student dance performance in physical education teacher education: a student–expert comparison of analytic rubric scoring and adaptive comparative judgment

Eric Jeisy
article en

Abstract

Background Assessing dance performance in physical education teacher education (PETE) requires judges to integrate technical and aesthetic qualities. Analytic rubrics make relevant dimensions explicit, whereas Adaptive Comparative Judgment (ACJ) elicits holistic pairwise decisions and produces a relative performance scale. This study compared the outcomes and student perceptions associated with the two approaches. Methods Seventeen pre-service teachers assessed 46 video-recorded student dance performances using an analytic rubric and ACJ. An expert reference was derived from five PETE lecturers who had assessed the performances live using the rubric and subsequently evaluated the video recordings through ACJ. Analyses examined rubric reliability and ACJ precision, convergence between method-derived rankings, student–expert rank alignment, cross-condition rubric score differences, and students’ perceptions of ease of use, usefulness, transparency, and fairness. Results Rubric- and ACJ-derived rankings were strongly associated within the student panel (Spearman's ρ = .863) and the expert reference panel ( ρ = .879). Aggregated student rankings also aligned closely with the expert-reference rankings under rubric scoring ( ρ = .890) and ACJ ( ρ = .888), with no clear difference in alignment between the methods. Aggregated student rubric scores showed high reliability, ICC(2,17) = .955, while ACJ scale separation reliability was .780 for students and .836 for experts. Student video-based rubric scores were, on average, 0.77 points higher than the archived live expert consensus scores. Students perceived ACJ as easier to use but the analytic rubric as more transparent. Perceived usefulness did not differ clearly, while fairness ratings descriptively favored the rubric. Conclusion Analytic rubric scoring and ACJ produced strongly convergent aggregate rankings, and the aggregated student panel differentiated relative performance quality in ways closely aligned with the expert reference under both approaches. However, the methods differed in score interpretation and perceived transparency. The results support considering ACJ as a complementary approach for digitally supported assessment and moderation rather than as a direct replacement for criterion-based summative assessment.

Frontiers in EducationVol. 11
St.Gallen University of Teacher Education (CH), Institut Bewegung, Sport und Gesundheit (CH)
Quality education
Openalex Percentile: Top 4%
Student Assessment and Feedback
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon