True Grit in Learning Math: The Math Anxiety-Achievement Link Is Mediated by Math-Specific Grit

In this study, we tested a possible mechanism of the association between math anxiety and math achievement: the mediating role of math-specific grit (i.e., sustaining effort in the face of adversity when learning math). In Study 1, a sample of 10th grade students (N = 222) completed a battery of personality and attitude questionnaires, and math achievement was indexed by curriculum-based examination scores. Mediation analyses indicated that math-specific grit, but not domain-general grit, mediated the relationship between math anxiety and math achievement. In Study 2, we replicated and extended the above findings with another sample of 11th grade students (N = 465). Mediation analyses indicated that math-specific grit and math-specific procrastination played sequential mediating roles in the relationship between math anxiety and math achievement. That is, individuals with higher math anxiety were less gritty in math learning, possibly further leading them to be more procrastinated in performing math work, which may finally result in worse math achievement. In summary, the current study provides the first evidence that math-specific grit may mediate the relationship between math anxiety and math achievement. Furthermore, it also demonstrated the value of math-specific grit over domain-general grit in predicting math success, which invites a broader investigation on subject-specific grit.

Predicting Math Identity Through Language and Click-Stream Patterns in a Blended Learning Mathematics Program for Elementary Students

This study builds on prior research by leveraging natural language processing (NLP), click-stream analyses, and survey data to predict students’ mathematics success and math identity (namely, self-concept, interest, and value of mathematics). Specifically, we combine NLP tools designed to measure lexical sophistication, text cohesion, and sentiment with analyses of student click-stream data within an online mathematics tutoring system. We combine these data sources to predict elementary students’ success within the system as well as components of their math identity as measured though a standardized survey. Data from 147 students was examined longitudinally over a year of study. The results indicated links between math success and non-cognitive measures of math identity. Additionally, the results indicate that math identity was strongly predicted by click-stream variables and the production of more lexically sophisticated and cohesive language. In addition, significant variance in math identity was explained by affective and cognitive variables. The results indicate that NLP and click-stream data can combine to provide insights into non-cognitive constructs such as math identity.

Urban School District–University Research Collaboration: Challenges and Strategies for Success

School district–university research collaborations represent one strategy to increase educators’ ability to use current, research-based information in program decision making and efforts to improve student achievement. However, differences in organizational structures, goals, values, and prior collaborative experiences have made successful school–university research partnerships challenging. This project intentionally structured and examined a mutually beneficial research collaboration between one small urban university with a significant percentage of first-generation college-going students and two local school districts (P-12) to examine high school math achievement and subsequent college math success. One partnership successfully conducted the study and identified actions to increase student success. The other was successful only to the point of partial data collection. This article describes the structures, mechanisms, and conditions that led to the successful partnership and compares them with the unsuccessful one. It contributes to our understanding of developing effective, mutually beneficial school–university research collaborations to improve student outcomes.

Intensive math training does not affect approximate number acuity: Evidence from a three-year longitudinal curriculum intervention

Does nonverbal, approximate number acuity predict mathematics performance? Some studies report a correlation between acuity of representations in the Approximate Number System (ANS) and early math achievement, while others do not. Few previous reports have addressed (1) whether reported correlations remain when other domain-general capacities are considered, and (2) whether such correlations are causal. In the present study, we addressed both questions using a large (N = 204) 3-year longitudinal dataset from a successful math intervention, which included a wide array of non-numerical cognitive tasks. While we replicated past work finding correlations between approximate number acuity and math success, these correlations were very small when other domain-general capacities were considered. Also, we found no evidence that changes to math performance induced changes to approximate number acuity, militating against one class of causal accounts.