The Influence Of Selection Self-explanation On Accuracy Of Monitoring In Problem-solving Tasks

How to improve the accuracy of students' meta-cognitive monitoring is an important field of meta-cognitive research.It is found that the generative learning strategy can improve the accuracy of meta-cognitive monitoring of reading text.However,different from reading textual materials,solving problems not only depends on students' active generative learning,but also depends on the quality of generative strategies.Especially when learning complex materials,the quality of generation strategy will affect the accuracy of meta-cognitive monitoring.Therefore,it is necessary to explore the influence of the quality of generation strategy on improving the accuracy of meta-cognitive monitoring when students learn complex problems.This research will use a new generative learning strategy--selective self-explanation,that is,a menu-based explanatory prompt,to provide specific and explicit rule interpretation for students in the learning process.In the first study,80 junior high school students were selected,and a mixed experimental design of 3(material difficulty: simple,medium,and complex)×2(learning condition: selective self-explanation,sample learning)was used to explore the effects of selective self-explanation and material difficulty on the accuracy of problem solving monitoring.The results showed that the monitoring accuracy of the simple level was better than that of the medium level and the complex level in both the selective self-explanation group and the sample group.The monitoring accuracy of the selective self-explanation group was better than that of the sample group at different levels of difficulty.The results show that selective self-explanation is helpful to improve the monitoring accuracy of students,but it is better at the simple level than the complex level.The second study considered that the complexity of mathematical problems depends on the learning of the key steps.Can selective self-explanation be used to explain only the key steps to reduce the complexity of the materials,so as to improve the monitoring accuracy of students on complex problems?In Experiment 2,the "complementary writing method" was used to determine the key steps of each question,and then a two-factor mixed experimental design of 2(material difficulty: medium and complex)×2(interpretation type: selective self-explanation of the whole step and selective self-explanation of the key step)was adopted.The results show that selective self-interpretation of only key steps can improve the monitoring accuracy of complex problems compared with selective self-interpretation of the whole steps.The results of this study indicate that selective self-explanation is helpful to improve the monitoring accuracy of problem solving,but it is more effective for relatively simple problems.For complex mathematical problems,self-explanation for the key steps can effectively improve the monitoring accuracy.The results of this study provide scientific guidance for the use of strategies in mathematics learning.