Analyzing student errors in PISA “Change and Relationship” tasks using the AVAEM framework

This study aims to describe students' difficulties in solving PISA problem-solving tasks in the "Change and Relationship" content domain by analyzing errors based on the AVAEM framework, which includes Arithmetic, Variables, Algebraic Expression, Equation Structure, and Mathematical Representation. This study employed a mixed-methods approach with an embedded design. The research participants consisted of 30 eighth-grade students from a junior high school in the city of Bandung. Data were collected through tests, questionnaires, observations, and interviews, and analyzed using the stages of data reduction, data display, and conclusion drawing. The results showed that students’ problem-solving abilities were predominantly in the low (50%), medium (27%), and high (23%) categories. Students experienced various difficulties that led to specific types of errors. Arithmetic errors were found across all student categories. Variable errors were mainly observed among students in the frustrated learner category. Algebraic Expression errors were identified in both the instruction learner and frustration learner categories. Meanwhile, no equation errors were identified in any student category, but mathematical errors occurred in all student categories. These findings emphasize the importance of identifying and understanding students’ error patterns when solving PISA-type problems as a basis for improving their mathematical problem-solving skills.

Authors

Institutions

Publication Details

Journal
Infinity Journal
Published
2025-11-20
DOI
https://doi.org/10.22460/infinity.v14i4.p1105-1128
Primary Topic
Mathematics Education and Pedagogy
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analyzing student errors in PISA “Change and Relationship” tasks using the AVAEM framework

Poppy Yaniawati, In In Supianti, Sabariah Sharif, Achmad Mudrikah et al.
Infinity Journal
Mathematics Education and Pedagogy
article

Analyzing student errors in PISA “Change and Relationship” tasks using the AVAEM framework

Poppy Yaniawati, In In Supianti, Sabariah Sharif, Achmad Mudrikah, Beni Yusepa Ginanjar Putra, Nurul Fitri
article en

Abstract

This study aims to describe students' difficulties in solving PISA problem-solving tasks in the "Change and Relationship" content domain by analyzing errors based on the AVAEM framework, which includes Arithmetic, Variables, Algebraic Expression, Equation Structure, and Mathematical Representation. This study employed a mixed-methods approach with an embedded design. The research participants consisted of 30 eighth-grade students from a junior high school in the city of Bandung. Data were collected through tests, questionnaires, observations, and interviews, and analyzed using the stages of data reduction, data display, and conclusion drawing. The results showed that students’ problem-solving abilities were predominantly in the low (50%), medium (27%), and high (23%) categories. Students experienced various difficulties that led to specific types of errors. Arithmetic errors were found across all student categories. Variable errors were mainly observed among students in the frustrated learner category. Algebraic Expression errors were identified in both the instruction learner and frustration learner categories. Meanwhile, no equation errors were identified in any student category, but mathematical errors occurred in all student categories. These findings emphasize the importance of identifying and understanding students’ error patterns when solving PISA-type problems as a basis for improving their mathematical problem-solving skills.

Infinity JournalVol. 14(4)
Universiti of Malaysia Sabah (MY), Universitas Pasundan (ID)
Openalex Percentile: Top 52%
Mathematics Education and Pedagogy
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.