| As the curriculum reform progresses,CHINA’S NATIONAL COLLEGE ENTRANCE EXAMINATION REPORT(2023)states that the college entrance examination in Mathematics will include complex contexts and emphasise the examination of mathematical thinking methods.The education reform emphasises that higher-order thinking and core literacy are essential qualities for high-quality talent to adapt to economic and social development,and deep learning aims to develop learners’ higher-order thinking and higher-order abilities,making deep learning a trend in mathematics teaching and learning.In order to achieve the teaching effectiveness of deep learning,it is necessary to understand the developmental patterns of learners’ cognitive skills.Since Adaptive Control of Thought-Rational(ACT-R)starts from simple cognitive activities to explain the complex human learning process,the ACT-R cognitive theory is used as a basis to set up teaching models that point to deep learning for students’ cognitive development.The research content of this paper: Firstly,through literature review,we learn about the development of ACT-R theory and the research of scholars at home and abroad on the teaching concept,implementation path strategies,evaluation methods and teaching models of deep learning.Secondly,we use questionnaires and test papers to understand the current situation of students’ learning motivation,learning strategies,learning reflection and students’ deep learning.Once again,the cognitive stages are divided according to ACT-R theory,and the inspiration of ACT-R theory for deep teaching is analyzed through specific analysis,and the path of ACT-R theory for deep teaching is set according to DELC route and "U" teaching model.The model of the deep teaching process is designed and analysed as a teaching case.Finally,on the basis of knowledge classification,teaching strategies and suggestions are proposed to promote deep learning.The following conclusions were drawn from the study.(1)Based on the questionnaire it was found that there were deficiencies in students’ internal motivation to learn,learning styles and metacognitive skills.The test method was used to understand the problems in classroom learning: the overall level of students was not high,the level of thinking was not deep enough,and the teacher’s leadership was not adequate.(2)Based on the analysis of Anderson’s classification of knowledge and the degree of internalisation of knowledge in ACT-R theory,the students’ cognitive stages were divided into four stages from superficial to deep: representational stage,declarative stage,procedural stage and conditionalisation stage.Teaching strategies are also proposed based on the perspectives of ACT-R theory and the current problems understood.(3)Based on the divided learning stages and the level of thinking objectives corresponding to each stage,a three-stage,seven-stage in-depth teaching model is constructed.(4)Based on ACT-R’s insights into deep learning,the recommendations offered for teaching declarative knowledge are: multiple representations and attention to the structural hierarchy of concepts.Procedural knowledge should be taught using selected examples,variation practice and inquiry-based teaching strategies.Suggested strategies for teaching problem solving skills are the creation of a hierarchy of problem goals and the use of ’pattern recognition’ problem solving strategies. |
