Enhancing ethnomathematical-ethnolinguistic understandings: A problem-based learning approach for postgraduate Sundanese language students

Abstract

As an interdisciplinary field within ethnolinguistics, ethnomathematics presents distinctive pedagogical challenges at the postgraduate level; however, research on Problem-Based Learning (PBL) in this context remains limited. This study examines postgraduate students’ perceptions of PBL for learning ethnomathematics in an ethnolinguistics course, investigates their use of Systemic Functional Linguistics (SFL) metafunctions to represent ethnomathematical knowledge, and proposes a mathematical model of knowledge growth during PBL. The study used a mixed-methods approach combining a qualitative case study and descriptive statistics with 23 master’s students from a Sundanese Education Study Program at a public university in Bandung, Indonesia. Participants engaged in collaborative PBL activities focusing on Sundanese numerical systems, traditional measurement practices, and cultural calendrical computations. Data were collected through perception questionnaires, observations of group presentations, and analysis of student-created documents. Findings indicate that students perceived PBL as enhancing cognitive development (90%), reflective capacity (91%), and critical thinking (93%). Collaborative PBL also promoted communicative competence, motivation, and confidence in sharing cultural-mathematical knowledge. SFL analysis revealed the use of ideational metafunctions through material and relational processes to encode mathematical and astronomical concepts; interpersonal metafunctions through declarative mood and graded modality to construe knowledge as factual and authoritative; and textual metafunctions through thematic progression and lexical cohesion to organize knowledge systematically. Students successfully documented Sundanese numerical systems, traditional measurement units such as kibik and bata, and calendrical calculations in the Palintangan manuscript. Based on these learning dynamics, the study proposes a Knowledge Growth Dynamics Model using differential equations to represent knowledge development through collaborative and self-directed learning.