How Grade 11 Students Match Audio to Function Graphs: Distractor Patterns and Error Pathways

Samuel John Parreño; Alleander Kate Gicale

doi:10.70148/rise.v3i4.14

Authors

Samuel John Parreño Department of Teacher Education, University of Mindanao, Digos City, Davao del Sur, Philippines Author
Alleander Kate Gicale Senior High School Department, Padada National High School, Padada, Davao del Sur, Philippines Author

DOI:

https://doi.org/10.70148/rise.v3i4.14

Keywords:

audio-to-graph matching, graph interpretation, distractor analysis, error pathways, mathematics assessment

Abstract

Multiple-choice responses can reveal which graph features guide students’ choices, not only whether an answer is correct. This study examined distractor patterns and pretest-to-posttest error pathways in audio-to-graph matching among 194 Grade 11 students from seven classes in a Philippine public secondary school. Parallel nine-item forms used level-coded audio, in which pitch tracked graph value, and rate-coded audio, in which pitch tracked local change. Responses were classified by correctness, graph family, mapping mismatch, and mathematical error category. Mean scores increased from 2.12 (SD = 1.32) to 3.64 (SD = 1.72) out of 9, W = 1972, p < .001, r = .601. Level-coded tasks showed marked movement from rate-coded lures to correct responses. Rate-coded tasks retained broader patterns of graph-level fallback, constant-versus-changing-rate confusion, concavity confusion, and nonlinear-rate confusion. Across 1,746 paired item attempts, 31.0% moved from incorrect to correct and 28.8% shifted between different incorrect categories. The study contributes a diagnostic pathway approach that identifies which distinctions in graph level, slope, concavity, and changing rate stabilized after instruction and which remained unsettled.

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