Mapping cognitive load profiles in realistic mathematics education: A study with aerospace engineering students - Rindu Alriavindra Funny; Fajar Khanif Rahmawati (Jurnal Elemen, 2025)
Although Realistic Mathematics Education (RME) promotes deeper conceptual learning, empirical evidence mapping different types of cognitive loads in university engineering mathematics is limited. This mixed-methods study profiled intrinsic, extraneous, and germane cognitive loads among 76 first-year aeronautical engineering students working on RME-based task, a contextualized double integral problems modelling aircraft wing surface. We measured load components with a CLT questionnaire that adapted from Leppink et.al and mental effort with the Paas scale, then triangulated findings with student reflections and observations. Correlations showed intrinsic and germane load related to students’ mental effort, while extraneous load was minimal, suggesting clear task design. Multiple regression analysis clarified that the germane load was the main unique predictor of mental effort, whereas intrinsic complexity and extraneous factors contributed little uniquely. Qualitative data confirmed that students used strategies such as breaking tasks into sub-steps, activating prior knowledge, and peer explanation to manage effort. We propose an RME–CLT alignment framework that scaffolds intrinsic difficulty, minimizes extraneous processing, and cultivates germane engagement through reflective context-rich tasks. The findings also inform the design of cognitively efficient engineering-mathematics curricula. Thus, it offers practical guidance for designing cognitively efficient engineering mathematics instruction and recommends future studies using longitudinal and real-time measures.