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Pradina Parameswari; Purwanto; Sudirman; Susiswo – Mathematics Teaching Research Journal, 2024
Students' difficulties in differentiating the direct proportion and inverse proportion problems cause interference. Proactive interference is the error that occurs when old information (concept of direct proportion) interferes with new information (concept of inverse proportion). In solving the problem of inverse proportion, students often use the…
Descriptors: Problem Solving, Mathematical Concepts, Mathematics Instruction, Grade 8
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Frinz Adrian O. Valdez; Eduard C. Taganap – Mathematics Teaching Research Journal, 2024
Mathematics proficiency in the Philippines is a persistent concern, seen by many as a sign of an educational crisis. Teachers are responsible for improving learning outcomes in any discipline, including math. Thus, the study intended to conduct an error analysis of verbal problems among pre-service mathematics teachers. The researcher employed…
Descriptors: Preservice Teachers, Error Patterns, Mathematics Teachers, Problem Solving
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Marijana Zeljic; Milana Dabic Boricic; Svetlana Ilic – Journal of Educational Research, 2024
Previous research examining comparison relations in word problems primarily focused on students' achievements in word problems with one operation. In this paper, we extend previous research to examine the achievement of students of different ages on word problems that integrate compare and combine word problems, hereafter referred to as…
Descriptors: Mathematics Education, Word Problems (Mathematics), Mathematical Concepts, Vocabulary
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Kelly-Ann Gesuelli; Nancy C. Jordan – Journal of Educational Psychology, 2024
Fraction arithmetic facility is fundamental to learning more advanced math topics. However, attaining the ability to add and subtract fractions is hard for many students. The present longitudinal study examined students' growth on simple addition and subtraction word problems between fourth and sixth grades (N = 536). Latent class growth analyses…
Descriptors: Fractions, Arithmetic, Error Patterns, Mathematics Instruction
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Katherine T. Rhodes; Julie A. Washington; Sibylla Leon Guerrero – Educational Assessment, 2024
Little is known about mismatches between the language of mathematics testing instruments and the rich linguistic repertoires that African American children develop at home and in the community. The current study aims to provide a proof of concept and novel explanatory item response design that uses error analysis to investigate the relationship…
Descriptors: Black Dialects, African American Students, Language Usage, Mathematics Tests
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Lisa M. Domke; María A. Cerrato; Elizabeth H. Sanders; Michael Vo – Language and Education, 2025
Because word problems present mathematical information through a scenario, they are language-intensive and require mathematical and reading comprehension skills to solve them. In addition, they are linguistically complex, which makes them challenging for all learners, especially multilingual learners. Given the rising number of dual-language…
Descriptors: Difficulty Level, Word Problems (Mathematics), Mathematics Instruction, Mathematics Skills
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Samuel Kenney; Forster D. Ntow – SAGE Open, 2024
This article uses the concurrent mixed methods design to explore the errors made by 171 Grade Seven learners in algebraic problem-solving within the Assin Central Municipality in Ghana. The participants were categorized into low-achieving and high-achieving groups based on their performance in a pretest, to help provide a detailed examination of…
Descriptors: Problem Solving, Algebra, Mathematics Instruction, Low Achievement
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Kole A. Norberg; Husni Almoubayyed; Logan De Ley; April Murphy; Kyle Weldon; Steve Ritter – Grantee Submission, 2024
Large language models (LLMs) offer an opportunity to make large-scale changes to educational content that would otherwise be too costly to implement. The work here highlights how LLMs (in particular GPT-4) can be prompted to revise educational math content ready for large scale deployment in real-world learning environments. We tested the ability…
Descriptors: Artificial Intelligence, Computer Software, Computational Linguistics, Educational Change