Alternative Assessment Methods in Competency-Based Education: A Mixed-Methods Evaluation of Authentic and Performance-Based Paradigm Shifts

Abstract

ABSTRACT Competency-Based Education (CBE) shifts the educational paradigm from time-bound instructional models to personalized, mastery-oriented pathways. While the structural benefits of CBE are well-documented, its scalable implementation remains limited by traditional, psychometrically rigid assessment paradigms like standardized multiple-choice testing. This paper presents a comprehensive, multi-site mixed-methods evaluation of alternative assessment methods—specifically authentic digital portfolios, Objective Structured Performance Appraisals (OSPAs), and continuous workplace simulations—across a cohort of 350 post-secondary learners over a 12-month period. Utilizing a matched-pairs quasi-experimental design, we compare the construct validity, ecological validity, and inter-rater reliability of these alternative frameworks against traditional summative examinations. Quantitative analysis reveals that students assessed via alternative methods exhibited a statistically significant improvement in real-world knowledge transfer (p < 0.001) and a 11% reduction in mastery achievement latency. Longitudinal alignment modeling confirmed that authentic portfolios yield superior predictive validity for post-graduation workplace performance compared to traditional exams (beta = 0.48 vs beta = 0.18). Qualitative thematic analysis of evaluator and student transcripts highlighted that transparent rubrics and iterative feedback loops enhanced learner autonomy and reduced systemic bias, though concerns regarding evaluator fatigue and cognitive workload persist. This study offers an empirically validated psychometric framework and structural blueprints for institutions transitioning to authentic, scalable alternative assessments within competency based architectures.

KEYWORDS: Competency-Based Education (CBE); Alternative Assessment; Performance-Based Metrics; Authentic Portfolios; Psychometric Validity; Learner Autonomy.