Stereotype threat (ST) research has focused exclusively on how negative group stereotypes reduce performance. The present work examines if pejorative stereotypes about women in math inhibit their ability to learn the mathematical rules and operations necessary to solve math problems. In Experiment 1, women experiencing ST had difficulty encoding math-related information into memory and, therefo...

Learning-by-invention is an approach to mathematical instruction where small groups explore possible methods of solution before learning the “right answer” (e.g., Schwartz & Martin, 2004; Kapur & Bielaczyc, 2011). In a series of studies we have been investigating the effects of group composition in terms of math ability on learning by invention. An initial result showed that groups consisting o...

This paper presents a deep neural solver to automatically solve math word problems. In contrast to previous statistical learning approaches, we directly translate math word problems to equation templates using a recurrent neural network (RNN) model, without sophisticated feature engineering. We further design a hybrid model that combines the RNN model and a similarity-based retrieval model to a...

Mathematics education in the future faces enormous opportunities from the availability of ubiquitous digital networks, from innovative educational approaches based on theories of collaborative learning and from rich resources for interactive, online, dynamic math exploration. The fact that more and more teachers and students are learning online—with distance education, online masters programs, ...

Positive attitude is thought to impact academic achievement and learning in children, but little is known about its underlying neurocognitive mechanisms. Using a large behavioral sample of 240 children, we found that positive attitude toward math uniquely predicted math achievement, even after we accounted for multiple other cognitive-affective factors. We then investigated the neural mechanism...

The goal of Multiple Kernel Learning (MKL) is to combine kernels derived from multiple sources in a data-driven way with the aim to enhance the accuracy of a kernel based machine. In this paper, we propose a time and space efficient MKL algorithm that can easily cope with hundreds of thousands of kernels and more. We compared our algorithm with other baselines plus three state-of-the-art MKL me...

Recent research indicates that children’s learning-related skills (including self-regulation and social competence) contribute to early school success. The present study investigated the relation of kindergarten learning-related skills to reading and math trajectories in 538 children between kindergarten and sixth grade, and examined how children with poor learning-related skills fared througho...

When learning a new math concept, should learners be first taught the concept and its associated procedures and then solve problems, or solve problems first even if it leads to failure and then be taught the concept and the procedures? Two randomized-controlled studies found that both methods lead to high levels of procedural knowledge. However, students who engaged in problem solving before be...

Math anxiety indicates psychologically a negative mind-set towards solving mathematical problems which impacts on students‟ learning practices and outcomes. In looking more closely at why a remarkable no of students may be struggling for improvement in mathematics in comparison to other subjects, it is timely to consider, the math anxiety factor. This literature review looks at the concept of m...