External–Internal–Self-experience Reading Motivation Scale (EISeM-RMS): Development and Rasch Validation among Elementary School Students - Abror Huda, Tiyas; Haenilah, Een Yayah; Setiyadi, Agustinus Bambang (Tadris: Jurnal Keguruan dan Ilmu Tarbiyah, 2026)
Reading motivation is crucial for elementary school students’ literacy development and lifelong learning. However, existing instruments are often unidimensional, lack contextual sensitivity, and fail to adequately capture students’ personal reading experiences. Existing motivation measures grounded in Self-Determination Theory (SDT) do not sufficiently incorporate experiential aspects of reading engagement. This study developed and validated the External–Internal–Self-experiential Reading Motivation Scale (EISeM-RMS). Employing a cross-sectional survey design, data were collected from 1,045 fourth-grade students across 20 elementary schools in Indonesia. The 27-item instrument covers three theoretically grounded dimensions: External Motivation (11 items), Internal Motivation (9 items), and Self-Experiential Motivation (7 items). Psychometric properties were rigorously evaluated using the Rasch Measurement Model with Winsteps software (version 3.73). Results demonstrated excellent model fit (Infit and Outfit MNSQ values ranging from 0.85 to 1.21), high measurement reliability (person reliability = 0.86; item reliability = 0.98), strong separation indices (person separation = 2.43; item separation = 6.84), and effectively functioning four-point Likert response categories with ordered thresholds. Notably, items in the self-experiential dimension exhibited higher difficulty estimates, reflecting the deeper cognitive and affective engagement required for experience-based reading motivation. This study extends SDT by positioning self-experience as a conceptually distinct and empirically supported dimension of reading motivation. Limitations include a single-site sampling frame, reliance on self-reported data, and an exclusive focus on elementary education. Future research should conduct cross-cultural, multi-site, and mixed-method validation studies, including digital adaptation of the EISeM-RMS.