Assessing the Measurement Quality of a Model Lecturer TPACK Instrument: Evidence from Rasch Analysis - Susanti, Nova; Iriani, Dewi; Aina, Mia (Educational Leadership and Management Journal, 2026)
Technological Pedagogical Content Knowledge (TPACK) is a fundamental competency for educators in integrating technology, pedagogy, and content knowledge into effective teaching practices. Ensuring the psychometric quality of TPACK instruments is therefore essential for obtaining accurate and reliable measurement results. This study aimed to evaluate the measurement quality of a TPACK instrument for model lecturers using Rasch Measurement Theory. A quantitative survey design was employed involving 32 respondents who completed a 25-item TPACK questionnaire using a four-point Likert scale. Data were analyzed using WINSTEPS to examine respondent reliability, item reliability, item fit, item difficulty, and rating scale functioning. The results indicated excellent respondent reliability (0.91) and person separation (3.24), demonstrating that the instrument effectively differentiated respondents across multiple competency levels. However, item reliability (0.45) and item separation (0.91) revealed limited variation in item difficulty. The item difficulty measures ranged from −0.68 to 1.43 logits, with PCK4 identified as the most difficult item and TK1 and TK4 as the easiest. Most items fit the Rasch model, although several items (CK1, CK2, PK3, PCK4, and TPACK1) exhibited misfit characteristics requiring revision. Rating scale analysis showed that the four-point Likert categories generally functioned as intended, but response concentrations in the upper categories suggested a potential ceiling effect and limited discrimination among higher-ability respondents. The novelty of this study lies in the comprehensive application of Rasch Measurement Theory to evaluate a TPACK instrument within a Lesson Study context. The findings provide empirical evidence for improving instrument quality through item refinement, broader difficulty calibration, and optimization of response categories. This study contributes to the development of more valid and reliable assessment tools for measuring technology integration competencies in physics education and professional development programs.