Research On The Design Of College English Deep Learning Teaching Model Supported By Information Technology

In order to cultivate internationalized talents and solve various practical problems in college English teaching,this study,supported by the theory of Deep Learning,explores a teaching model based on information technology to promote college students' deep learning of English under the background of the reform of English teaching in S University.The research adopts the design-based research paradigm and constructs a deep hybrid teaching mode based on "cloud class+off-line classroom" by integrating information technology.It also evaluates the practical effect by using the mixed data collection method which combines quantitative and qualitative methods.According to the evaluation results,the hybrid teaching mode is designed in two iterations to make it operable,which is improved continuously.The first study aims at promoting students'learning engagement as a breakthrough and directing at the goal of deep learning.Researchers try to divide learning space into online extra-curricular learning space and offline classroom learning space from the perspective of learning space,increase students'online and offline learning input through task-driven,and use three research methods to analyze the experimental data in a multi-dimensional way.Firstly,the feedback of learning activities is qualitatively analyzed by using the semi-structured interview syllabus.The results show that most students like the English course under this mixed teaching mode,and think that the learning process of College English is more interesting and interactive,which helps to improve their comprehensive English ability.Secondly,the researcher classifies the students'homework data based on SOLO classification theory.It is found that the number of association structure(R)and extension structure(EA)is increasing with the passage of time,confirming the occurrence of deep learning.Thirdly,using the learning engagement scale as a measurement tool,we collect pre-and post-test data of experimental class A,and use SPSS software to analyze the data paired samples.The results show that after a semester of experimental study,students can learn more deeply.There is a significant change in behavioral input,however,the cognitive input needs to be further improved.Thus the researchers implemented the second round of optimization design research.The aim in the optimization study is to stimulate students' learning motivation and enhance students' ability to integrate and apply various learning strategies.Researchers optimize the teaching model from the dimension of learning time,dividing learning time into three periods:pre-class,classroom and after-class,giving full play to the advantages of group task activities,using learning resources and learning activities,and intervening in learning strategies,so as to promote students'cognitive ability in depth.Using the Learning Strategy Scale as a measurement tool,the data of class B are collected before and after the experiment,and paired samples are analyzed by SPSS software.The results show that students'learning strategies and motivations have been significantly improved.