ANALYSIS OF STUDENTS' MATHEMATICAL REPRESENTATION ABILITY THROUGH GEOGEBRA-ASSISTED DISCOVERY LEARNING IN TERMS OF SELF-CONCEPT AND LEARNING MOTIVATION

Abstract

Mathematical representation ability enables students to communicate mathematical ideas through visual, symbolic, and verbal forms. This study analyzed students’ mathematical representation ability through GeoGebra-assisted Discovery Learning in terms of self-concept and learning motivation. A qualitative descriptive approach involved 36 Grade XI-5 students at SMA Negeri 3 Tegal in 2025/2026, with seven students purposively selected based on self-concept and learning motivation categories. Data were collected through questionnaires, mathematical representation tests, and semi-structured interviews and analyzed using Miles, Huberman, and Saldaña’s interactive model. The findings showed that mathematical representation ability varied according to self-concept and learning motivation. Students with high self-concept and high learning motivation performed well across visual, symbolic, and verbal representations, while those with lower levels experienced difficulties, particularly in constructing mathematical models and expressing ideas verbally. Symbolic representation was strongest, whereas verbal representation was most challenging. GeoGebra-assisted Discovery Learning supported representation development, while self-concept and learning motivation influenced reasoning.