Results 281 to 290 of about 497,585 (360)

Approaching math increases math=me and math=pleasant

Journal of Experimental Social Psychology, 2008
Abstract In two studies, we examined the effect of extensive practice in approaching math on implicit identification with math, implicit math attitudes, and behavior during a math test. The results from Study 1 demonstrated that women trained to approach math showed more identification with and positive implicit attitudes toward math than women ...
Kerry Kawakami, Jennifer R Steele, Curtis E Phills   +2 more
exaly   +2 more sources

Math self-efficacy or anxiety? The role of emotional and motivational contribution in math performance

Social Psychology of Education, 2023
Various studies have highlighted the important influence of math ability in a numerate society. In this study, we investigated the influence of emotional (math anxiety and math enjoyment) and cognitive-motivational (math self-efficacy) factors on math ...
Marija Zivkovic, Sandra Pellizzoni, Eleonora Doz   +2 more
exaly   +2 more sources

Math-Shepherd: Verify and Reinforce LLMs Step-by-step without Human Annotations

Annual Meeting of the Association for Computational Linguistics, 2023
In this paper, we present an innovative process-oriented math process reward model called \textbf{Math-Shepherd}, which assigns a reward score to each step of math problem solutions.
Peiyi Wang, Lei Li, Zhihong Shao, R. Xu, Damai Dai, Yifei Li, Deli Chen, Y.Wu, Zhifang Sui   +8 more
semanticscholar   +1 more source

Disentangling the individual and contextual effects of math anxiety: A global perspective

Proceedings of the National Academy of Sciences of the United States of America, 2022
Significance Using three large-scale international assessments of student achievement, the current study examined the antecedents of math anxiety and the relation between math anxiety and math achievement across the globe. Results suggest that individual
Nathan T T Lau, Zachary Hawes, Paul F Tremblay   +2 more
exaly   +2 more sources

Memories of math: Narrative predictors of math affect, math motivation, and future math plans

Contemporary Educational Psychology, 2020
Abstract This mixed-methods study focuses on narratives that undergraduates tell about pivotal moments (i.e., turning points) in their prior history with math. A key objective was to examine whether these turning points would be associated with participants’ current math affect, math motivation, and future plans with math. Undergraduate participants (
Jennifer E. John, Paul A. Nelson, Brittany Klenczar, Rachael D. Robnett   +3 more
openaire   +1 more source

rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking

International Conference on Machine Learning
We present rStar-Math to demonstrate that small language models (SLMs) can rival or even surpass the math reasoning capability of OpenAI o1, without distillation from superior models.
Xinyu Guan, L. Zhang, Yifei Liu, Ning Shang, Youran Sun, Yi Zhu, Fan Yang, Mao Yang   +7 more
semanticscholar   +1 more source

Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement

arXiv.org
In this report, we present a series of math-specific large language models: Qwen2.5-Math and Qwen2.5-Math-Instruct-1.5B/7B/72B. The core innovation of the Qwen2.5 series lies in integrating the philosophy of self-improvement throughout the entire ...
An Yang, Beichen Zhang, Binyuan Hui, Bofei Gao, Bowen Yu, Chengpeng Li, Dayiheng Liu, Jianhong Tu, Jingren Zhou, Junyang Lin, Keming Lu, Mingfeng Xue, Runji Lin, Tianyu Liu, Xingzhang Ren, Zhenru Zhang   +15 more
semanticscholar   +1 more source

Math by the Month: Math by the Book

Teaching Children Mathematics, 2005
The “Math by the Month” activities are designed to engage students to think like mathematicians. Students may work on the activities individually or in small groups, or they may be used with the whole class as problems of the week. No solutions are suggested so that students will look to themselves for mathematical justification, thereby developing the
Kristen Forrest, Denise Schnabel, Margaret Williams   +2 more
openaire   +1 more source

MathArena: Evaluating LLMs on Uncontaminated Math Competitions

arXiv.org
The rapid advancement of reasoning capabilities in large language models (LLMs) has led to notable improvements on mathematical benchmarks. However, many of the most commonly used evaluation datasets (e.g., AIME 2024) are widely available online, making ...
Mislav Balunovi'c, Jasper Dekoninck, Ivo Petrov, Nikola Jovanovi'c, Martin T. Vechev   +4 more
semanticscholar   +1 more source

Measuring Multimodal Mathematical Reasoning with MATH-Vision Dataset

arXiv.org
Recent advancements in Large Multimodal Models (LMMs) have shown promising results in mathematical reasoning within visual contexts, with models approaching human-level performance on existing benchmarks such as MathVista. However, we observe significant
Ke Wang, Junting Pan, Weikang Shi, Zimu Lu, Mingjie Zhan, Hongsheng Li   +5 more
semanticscholar   +1 more source