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Kristen Vroom; Tenchita Alzaga Elizondo – International Journal of Research in Undergraduate Mathematics Education, 2024
Undergraduate students are expected to produce and comprehend constructive existence proofs; yet, these proofs are notoriously difficult for students. This study investigates students' thinking about these proofs by asking students to validate two arguments for the existence of a mathematical object. The first argument featured a common structural…
Descriptors: Mathematics Instruction, Validity, Mathematical Logic, Student Attitudes
Conrad Borchers; Paulo F. Carvalho; Meng Xia; Pinyang Liu; Kenneth R. Koedinger; Vincent Aleven – Grantee Submission, 2023
In numerous studies, intelligent tutoring systems (ITSs) have proven effective in helping students learn mathematics. Prior work posits that their effectiveness derives from efficiently providing eventually-correct practice opportunities. Yet, there is little empirical evidence on how learning processes with ITSs compare to other forms of…
Descriptors: Problem Solving, Intelligent Tutoring Systems, Mathematics Education, Learning Processes
Hai Li; Wanli Xing; Chenglu Li; Wangda Zhu; Simon Woodhead – Journal of Learning Analytics, 2025
Knowledge tracing (KT) is a method to evaluate a student's knowledge state (KS) based on their historical problem-solving records by predicting the next answer's binary correctness. Although widely applied to closed-ended questions, it lacks a detailed option tracing (OT) method for assessing multiple-choice questions (MCQs). This paper introduces…
Descriptors: Mathematics Tests, Multiple Choice Tests, Computer Assisted Testing, Problem Solving
Christina Areizaga Barbieri; Elena M. Silla – Journal of Experimental Education, 2024
Prior research highlights a positive effect of incorrect worked examples on mathematics learning. Yet the mechanisms underlying these benefits are unclear. To investigate potential mechanisms of the benefits of various worked example types, we examined process data from a previously published classroom-based experiment. More specifically, we…
Descriptors: Middle School Students, Ethnic Diversity, Racial Relations, Public Schools
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
Barbieri, Christina Areizaga; Booth, Julie L.; Begolli, Kreshnik N.; McCann, Nicholas – Instructional Science: An International Journal of the Learning Sciences, 2021
The present study examines the effectiveness of incorporating worked examples with prompts for self-explanation into a middle school math textbook. Algebra 1 students (N = 75) completed an equation-solving unit with textbooks either containing the original practice problems or in which a portion of those problems were converted into a combination…
Descriptors: Algebra, Learning Processes, Mathematics Instruction, Middle School Students
Wakhata, Robert; Balimuttajjo, Sudi; Mutarutinya, Védaste – Mathematics Teaching Research Journal, 2023
The present study explored 285 11th-grade students' preconceptions, misconceptions, and errors in solving mathematics tasks by graphical method. A descriptive-explorative study design was adopted. Cluster sampling was used to select students from sampled secondary schools in eastern and central Uganda. Students' paper and pen solution sketches…
Descriptors: Foreign Countries, Secondary School Mathematics, High School Students, Grade 11
Chitpin, Stephanie – International Journal of Educational Management, 2017
Purpose: The purpose of this paper is to illustrate how associationism mistakenly assumes that direct experience is possible; that is, there is expectation-free observation and association without prior expectation. Thus, associationism assumes that learning involves the absorption of information from the environment itself. However, contrary…
Descriptors: Abstract Reasoning, Associative Learning, Association (Psychology), Philosophy
Mughaz, Dror; Cohen, Michael; Mejahez, Sagit; Ades, Tal; Bouhnik, Dan – Interdisciplinary Journal of e-Skills and Lifelong Learning, 2020
Aim/Purpose: Using Artificial Intelligence with Deep Learning (DL) techniques, which mimic the action of the brain, to improve a student's grammar learning process. Finding the subject of a sentence using DL, and learning, by way of this computer field, to analyze human learning processes and mistakes. In addition, showing Artificial Intelligence…
Descriptors: Artificial Intelligence, Teaching Methods, Brain Hemisphere Functions, Grammar
Metcalfe, Janet – Grantee Submission, 2017
Although error avoidance during learning appears to be the rule in American classrooms, laboratory studies suggest that it may be a counterproductive strategy, at least for neurologically typical students. Experimental investigations indicate that errorful learning followed by corrective feedback is beneficial to learning. Interestingly, the…
Descriptors: Error Patterns, Error Correction, Feedback (Response), Educational Benefits
Jupri, Al; Drijvers, Paul – EURASIA Journal of Mathematics, Science & Technology Education, 2016
To investigate student difficulties in solving word problems in algebra, we carried out a teaching experiment involving 51 Indonesian students (12/13 year-old) who used a digital mathematics environment. The findings were backed up by an interview study, in which eighteen students (13/14 year-old) were involved. The perspective of mathematization,…
Descriptors: Foreign Countries, Grade 7, Algebra, Word Problems (Mathematics)
Ottmar, Erin; Landy, David – Journal of the Learning Sciences, 2017
Learning algebra is difficult for many students in part because of an emphasis on the memorization of abstract rules. Algebraic reasoners across expertise levels often rely on perceptual-motor strategies to make these rules meaningful and memorable. However, in many cases, rules are provided as patterns to be memorized verbally, with little overt…
Descriptors: Mathematics Instruction, Algebra, Outcomes of Education, Learning Processes
Feng, Mingyu, Ed.; Käser, Tanja, Ed.; Talukdar, Partha, Ed. – International Educational Data Mining Society, 2023
The Indian Institute of Science is proud to host the fully in-person sixteenth iteration of the International Conference on Educational Data Mining (EDM) during July 11-14, 2023. EDM is the annual flagship conference of the International Educational Data Mining Society. The theme of this year's conference is "Educational data mining for…
Descriptors: Information Retrieval, Data Analysis, Computer Assisted Testing, Cheating
Star, Jon R.; Foegen, Anne; Larson, Matthew R.; McCallum, William G.; Porath, Jane; Zbiek, Rose Mary; Caronongan, Pia; Furgeson, Joshua,; Keating, Betsy; Lyskawa, Julia – What Works Clearinghouse, 2015
Mastering algebra is important for future math and postsecondary success. Educators will find practical recommendations for how to improve algebra instruction in the What Works Clearinghouse (WWC) practice guide, "Teaching Strategies for Improving Algebra Knowledge in Middle and High School Students". The methods and examples included in…
Descriptors: Algebra, Mathematics Instruction, Secondary School Mathematics, Teaching Methods

Gerber, Michael – Learning Disability Quarterly, 1984
Based on research results on learning disabled children's spelling, it is argued that spelling errors produced by carefully selected LD elementary-school students cannot be interpreted as deviating from errors expected from younger, normally achieving children. Data are interpreted to support a cognitive-developmental model of spelling…
Descriptors: Error Patterns, Learning Disabilities, Learning Processes, Orthographic Symbols
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