Assessing Online Anatomy Teaching Effectiveness: Instrument Design and Validation at Ho Chi Minh City University of Physical Education and Sports

Abstract

Background: The institutional integration of digital learning in higher education has underscored the critical necessity of assessing domain-specific instructional effectiveness. In morphology-heavy disciplines such as Anatomy within pre-service physical education teacher education, virtual delivery poses profound pedagogical and cognitive challenges due to high intrinsic content density and the deprivation of physical tactile models.

Objectives: This study designed, operationalized, and preliminarily validated the Online Teaching Effectiveness in Anatomy Instrument (OTE-AI) to diagnose student-perceived instructional quality and cognitive bottlenecks at Ho Chi Minh City University of Physical Education and Sports (UPES).

Methods: Grounded in Cognitive Load Theory (Sweller, 2011) and international scale development standards (Boateng et al., 2018), a 15-item diagnostic instrument structured across four evaluative dimensions was developed. The instrument was empirically piloted with an exploratory sample (n = 43) drawn from a target cohort of N = 172 undergraduate pre-service physical education teachers (25.0% completion rate). Data were gathered via an institutional digital platform and analyzed using descriptive statistics, frequency distributions, and qualitative diagnostic synthesis.

Results: Findings revealed unanimous consensus regarding the fundamental curricular necessity of Anatomy (74.4% “Very Important”, 25.6% “Important”), alongside substantial perceived knowledge density (86.0% rating volume as “Large” or “Very Large”). The Musculoskeletal system exhibited the highest practical utility for physical education pedagogy (60.5%), yet represented the second-largest driver of cognitive overload (20.9% recommending content reduction), following the Excretory system (30.2%). While digital classroom management and instructor facilitation were rated exceptionally high (79.1% “Very Good”), perceived learning efficacy revealed marked dispersion, with 23.2% reporting suboptimal learning gains due to cognitive fatigue and virtual delivery constraints.

Conclusions: The OTE-AI provides a valid, theory-grounded diagnostic framework capable of distinguishing technological classroom orchestration from authentic domain-specific learning efficacy. The empirical findings provide actionable justification for targeted syllabus recalibration under institutional frameworks (Decision No. 1028/QĐ-ĐHSPTDTT) and alignment with national professional teacher standards (Circular No. 20/2018/TT-BGDĐT).