Newman’s error analysis at mathematics pre-service teachers in solving literacy problems

This study aims to: (1) to provide an overview of the errors of prospective mathematics teacher students in solving mathematics literacy problems based on Newman's Error Analysis, and (2) to provide an overview of the factors that cause prospective mathematics teacher students to make errors in solving mathematics literacy problems. This research is qualitative research using a grounded theory approach. The subjects of this study are 92 prospective mathematics teacher students in the study program of Tadris Mathematics UIN Prof. K.H. Saifuddin Zuhri Purwokerto. The data collection techniques in this study are: (1) test and (2) interview. The analysis technique in this study uses qualitative data analysis techniques consisting of (1) data reduction, (2) data presentation, and (3) conclusion drawn. The data validity technique used in this study is triangulation. The results of the study show that: (1) reading error, comprehension error, and encoding error are not problems for students in solving mathematical literacy problems, transformation errors are problems for students because the errors are found in all four mathematics literacy questions, and process skill errors are problems for students in mathematics literacy questions that measure the ability to connect mathematical facts/concepts to make problem-solving procedures work, and (2) factors that cause prospective mathematics teacher students to make errors in solving mathematical literacy problems include: (a) errors in making mathematical models that involve time, (b) errors in length accuracy, (c) errors affected by images, (d) errors in replacing unknown values with spelling, (e) errors in recalling information, (f) errors in estimating the shape of the 3D Geometric Shapes, (g) errors in remembering mathematical formulas, (h) error in choosing adjacent concepts, (i) error not recognizing mathematical concepts, (j) error preparing calculations, (k) error converting units, and (l) error inferring with estimates.