GOAL-FREE PROBLEMS IN MATHEMATICS EDUCATION: A SYSTEMATIC REVIEW OF COGNITIVE LOAD AND PROBLEM-SOLVING RESEARCH - Syakira Zalfani Asla; Indra Budiman; Nur Azizah (Universitas Sembilanbelas November Kolaka, 2026)
Goal-Free Problems (GFP), based on Cognitive Load Theory (CLT), is an instructional strategy that reduces extraneous cognitive load by eliminating specific end goals from mathematical tasks. Although widely implemented in mathematics education, empirical findings remain fragmented and lack systematic synthesis. This study systematically reviews research on Goal-Free Problems with a focus on cognitive load and mathematical problem-solving. Literature was identified through Scopus, ERIC, and Google Scholar using Publish or Perish, covering publications from 2016–2026. Following the PRISMA 2020 guidelines, ten eligible studies were analyzed using narrative synthesis. The results indicate that Goal-Free Problems consistently reduce cognitive load and support learning outcomes such as transfer, retention, reasoning, flexible thinking, and higher-order thinking skills. However, their effectiveness is influenced by task complexity, prior knowledge, and instructional design. The review also reveals that direct evidence regarding mathematical problem-solving ability remains limited, as most studies emphasize cognitive load and related cognitive variables. These findings highlight the need for further experimental research examining mathematical problem-solving as the primary outcome.Goal-Free Problems (GFP), based on Cognitive Load Theory (CLT), is an instructional strategy that reduces extraneous cognitive load by eliminating specific end goals from mathematical tasks. Although widely implemented in mathematics education, empirical findings remain fragmented and lack systematic synthesis. This study systematically reviews research on Goal-Free Problems with a focus on cognitive load and mathematical problem-solving. Literature was identified through Scopus, ERIC, and Google Scholar using Publish or Perish, covering publications from 2016–2026. Following the PRISMA 2020 guidelines, ten eligible studies were analyzed using narrative synthesis. The results indicate that Goal-Free Problems consistently reduce cognitive load and support learning outcomes such as transfer, retention, reasoning, flexible thinking, and higher-order thinking skills. However, their effectiveness is influenced by task complexity, prior knowledge, and instructional design. The review also reveals that direct evidence regarding mathematical problem-solving ability remains limited, as most studies emphasize cognitive load and related cognitive variables. These findings highlight the need for further experimental research examining mathematical problem-solving as the primary outcome.