Research On Evaluation Of High School Mathematics Deep Learning Based On SOLO Classification Theory

The release of "General High School Mathematics Curriculum Standards"(2017Edition)means a new round of mathematics education reform.The overall goal of this development and change is to effectively implement the "core literacy of students".The shallow-level classroom teaching of purely mechanical memory and exercises cannot cultivate the core literacy of students in mathematics.Only the in-depth teaching of teachers and the in-depth learning of students can in-depth understand the importance of core concepts and arguments,carry out active learning,and improve students’ mathematics.Level thinking ability,and strive to improve the core literacy of students.The concept and concept of "deep learning" is becoming more and more popular,and further research is needed for its case application,strategy implementation and evaluation in order to achieve the goal of perfecting the deep learning theoretical system.This research is mainly to study two issues,one is to integrate SOLO classification theory into the quality evaluation of high school mathematics deep learning,and the other is to use this tool to conduct case analysis in high school mathematics classrooms.First,use the literature research method to construct the theory from the three aspects of research focus,guidance framework,and subject carrier,to illustrate the suitability of SOLO classification theory to the evaluation of mathematics deep learning.Then use the SOLO classification theory as the framework,combined with the national mathematics curriculum standards,to classify the specific knowledge of the three main content of high school mathematics,according to the actual problems,the inquiry activities,the operation of the geometry sketchpad,the thinking of open questions and supplementary exercises five The sequence of each teaching link refines the evaluation indicators,and then uses the Delphi method to collect expert feedback,revises and supplements the evaluation indicators,and finally forms the evaluation criteria for high school mathematics deep learning.This study selects N City in Jiangxi Province as the survey area,B middle school as the survey school,and 6 students in the second grade as the sample students.Each student has different academic backgrounds.The mathematics learning performance is divided into three levels,and the mathematics inquiry class is the research object.The topics are "Judgment of a straight line parallel to a plane" and "Judgment of a straight line perpendicular to a plane".Observe the classroom from both quantitative and qualitative perspectives.Use classroom observation tools and student task tables to count the specific learning levels of the sample students.It is found that most of the learning results of the sample students appear at the multi-point structure level,in a shallow learning state,and deep processing Insufficient mathematical information ability,insufficient knowledge to solve comprehensive problems,and weak ability to critically understand knowledge;on the other hand,it is found that there is a significant positive correlation between academic performance and students’ deep learning level.According to students’ deep learning learning quality,three teaching suggestions are put forward: one is to focus on the construction of knowledge systems to improve deep processing ability;the other is to focus on the transfer of comprehensive question types to improve problem-solving skills;the third is to focus on the formation of critical thinking and promote in-depth thinking skills.