DOI: 10.12688/f1000research.187953.2 ISSN: 2046-1402

From Needs Assessment to Instructional Design: Empirical Requirements for a DIF-PBL Model in Inclusive Numeracy Learning

Mentari Rama Putri, Arismunandar Arismunandar, Syafruddin Side, Erma Suryani Sahabuddin, Ahmad Swandi
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Inclusive elementary classrooms require instructional approaches that accommodate substantial variation in students’ numeracy readiness, learning characteristics, and support needs. This study examined teachers’ instructional needs and preliminary learner differences as an empirical basis for designing a Differentiation-Based Problem-Based Learning (DIF-PBL) model for inclusive numeracy learning. The study was conducted as a descriptive needs assessment within a broader research and development project. Participants included 20 classroom teachers and special education support teachers from three inclusive elementary schools in Bone Regency, South Sulawesi, Indonesia. Data were collected using a 13-item four-point Likert questionnaire and structured observations of three students representing different learner profiles. Questionnaire data were analyzed using item-level means, standard deviations, and response frequencies, while student observations were treated as illustrative contextual cases. Teachers reported substantial instructional challenges, including disparities in numeracy achievement, difficulty balancing instructional support, limitations in conventional Problem-Based Learning, and practical difficulties in implementing differentiated instruction. The strongest responses concerned the need for an integrated PBL and differentiation model (M = 3.95, SD = 0.22), an operational teacher guide (M = 4.00, SD = 0.00), and the urgency of developing the DIF-PBL model (M = 4.00, SD = 0.00). The findings support several design requirements, including differentiated learning pathways, flexible PBL procedures, Concrete–Pictorial–Abstract learning progression, systematic scaffolding, adaptive assessment, and practical teacher guidance. The findings provide an empirical starting point for subsequent prototype development and validation rather than evidence of model effectiveness.

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