The Impact Of Mathematics Anxiety On Computational Estimation Between Different Contexts

As a commonly used form of mathematical estimation, computational estimation is a new angle of view to investigate the arithmetic cognition, which is very important to open out the mechanism of arithmetic cognition and the development of cognition in the mass. In daily life, financial management, shopping and other digital information processing services are required to participate in the estimation. For effective instruction, it is necessary to explore the process and impacting factor of computational estimation .At present, most people explore the influencing factors of computational estimation on either pure cognitive respects, such as conceptual understanding, problem characteristics, problem representation, or the external manifestations of cognition, there is no research about the how the emotional factors impact on computational estimation. As a negative emotion, mathematics anxiety influences not only the development of personal emotion, but also the development of mathematical cognition. Current study about the relationship of mathematics anxiety and mental arithmetic has shown that anxiety played an important role on arithmetical cognition, such as digital process, strategy choice. Previous studies about computational estimation have shown that context can make it easier or harder, there are no the last word. In order to provide the basis for estimation training, this research used experimental methods to inspect the impact of mathematics anxiety on computational estimation both in pure digital context and applied problems contexts.Domestic researches about mathematics anxiety are mainly to primary school students and middle school students, there is little study to college students. 417 grade one- to- three students randomly sampling from one college in Ji Nan City participated with Plake and Parkerin's the Revised Mathematics Anxiety Rating Scale in this research, in order to revise a mathematics anxiety rating scale which is the same with college students in China. Then this research explored the present status of college students. Finally, individuals at high, middle and low different mathematics anxiety levels took part to the experiment, which can investigate the impact of mathematics anxiety on computational estimation both in pure digital context and applied problems contexts, in addition to explore the Problem-size effect in computational estimation.The results showed that:(1) The Revised the Revised Mathematics Anxiety Rating Scale has 21 items, including 2 components: mathematics learning anxiety and mathematics evaluation anxiety. The scale has good reliability and validity.(2) The college students'mathematics anxiety is generally mild, mathematics evaluation anxiety is more obvious;Grade three students'anxiety is much higher than grade one and grade two; it doesn't reflect a stable gender difference.(3) On the whole, mathematics anxiety has a significant impact on computational estimation in two different contexts. The average RT in the low mathematics anxiety individuals is significant lower than the middle and high individuals; the average accuracy on the high individuals is lowest both in pure digital context and in applied problem context,(4) In pure digital context, there are significant differences on the RTs of high, middle and low mathematics anxiety individuals only in complex problems; in applied problem context, there are significant differences on the RTs of three levels individuals both in simple problems and complex problems, that is, the average RT of low anxiety individuals is significant lower than the high and middle individuals, the accuracy is significant higher than those two.(5) Context has a significant impact on the accuracy of estimation, the accuracy in pure digital context is significant higher than in applied problem context.(6) There are significant differences in estimation accuracy between simple problems and complex problems in different contexts. There are no significant differences in accuracy between simple problems and complex problems in pure context; however, the average accuracy on one-digit×two-digit is significant higher than two-digit×two-digit in applied problem context.Based on the above findings, the following conclusions are drawn:(1) The college students'mathematics anxiety college mathematics anxiety has a significant grade differences, but it doesn't reflect a stable gender difference.(2) The average RTs and accuracies among the high, middle and low mathematics anxiety individuals both have significant differences both in in pure digital context and in applied problem context. The low individuals'average accuracy is highest and their average RT is shortest.(3) Context affects the accuracy of estimation; the accuracy in pure digital context is significant higher than in applied problem context. Main effect of mathematics anxiety is significant only on simple problems in pure digital context, but the main effect is significant both on simple problems and complex problems in applied problem context.(4) There is no problem-size effect found in pure digital context; however, there is problem-size effect found in applied problem context.