Linking Adaptive Reasoning to Newman's Error Patterns in Digital Geometry Learning

Authors

DOI:

https://doi.org/10.58524/oler.v6i2.1143

Keywords:

Adaptive reasoning, Digital geometry learning, Error diagnosis, Newman’s error analysis, Pythagorean theorem

Abstract

Adaptive reasoning is a fundamental component of mathematical proficiency, yet limited research has examined how students’ reasoning relates to specific stages of problem-solving failure in digital geometry learning. Existing studies on Newman’s Error Analysis (NEA) primarily classify error types, whereas research on adaptive reasoning tends to evaluate reasoning quality without explaining its relationship to problem-solving errors. This study investigated students’ adaptive reasoning profiles, identified error patterns using Newman’s Error Analysis, and examined the relationship between reasoning ability and error occurrence in solving Pythagorean theorem problems within a digital geometry learning environment. An embedded mixed-methods design was employed involving 30 eighth-grade students from a junior secondary school in Indonesia. Students learned through an interactive digital flipbook integrated with GeoGebra before completing adaptive reasoning tasks and participating in semi-structured interviews. The findings revealed that students demonstrated moderate adaptive reasoning, with transformation errors emerging as the most frequent problem-solving difficulty, followed by comprehension and process-skill errors. Students with lower adaptive reasoning experienced substantially more difficulties in transforming contextual information into mathematical representations and constructing coherent solution strategies. This study extends current research by demonstrating a systematic relationship between adaptive reasoning and Newman’s error stages, providing diagnostic insights for designing reasoning-oriented scaffolding in technology-enhanced geometry instruction.

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Published

2026-06-30

How to Cite

Linking Adaptive Reasoning to Newman’s Error Patterns in Digital Geometry Learning. (2026). Online Learning In Educational Research (OLER), 6(2), 97-108. https://doi.org/10.58524/oler.v6i2.1143