Analyzing the Mathematical Literacy of Indonesian Students: Characteristics, Challenges, and Technology-Enhanced Solutions - Muhaimin, Lukman Hakim; Vrapi, Asllan; Anggareni, Peni; Abadi, Ma'ulfi Kharis; Kholid, Muhammad Noor; Dewi, Deshinta A (Journal of Educational Technology and Learning Creativity, 2025)
Purpose of the study: This study aims to uncover the characteristics of Indonesian students' mathematical literacy, the challenges they face in solving mathematical problems, and to propose effective solutions, including technology-enhanced interventions, for improvement. Methodology: This study uses a qualitative phenomenological approach to explore students’ experiences in mathematical literacy. Data were collected through AKM-based algebra tasks, interviews, and observations involving three purposively selected middle school students. Method triangulation ensured validity, while digital tools, including audio recording and NVivo software, supported systematic qualitative data coding and analysis. Main Findings: The findings indicate that students’ incorrect answers often arise from difficulties in identifying key problem elements. This misidentification triggers cascading errors across subsequent problem-solving steps, creating a domino effect. Analysis revealed distinct patterns in communication, mathematization, representation, problem-solving strategies, symbolic operations, and reasoning. These patterned error trajectories align well with digital logging, automated analysis, and real-time feedback, enabling direct application in designing digital assessment platforms, intelligent tutoring systems, and learning analytics dashboards to diagnose learning breakdowns. Novelty/Originality of this study: This study uniquely bridges qualitative phenomenological analysis with concrete technological design, systematically translating error patterns into detection algorithms, scaffolding rules, and dashboard specifications. Unlike prior research that either describes difficulties or proposes technology, we explicitly operationalize how intelligent systems can detect and respond to cascading error patterns in real time. The result is a contextually grounded framework for AKM-aligned technology implementation tailored to Indonesian educational realities, including infrastructure constraints and teacher capacity.