Research On Blended Learning Design To Promote Deep Learning Of College Students

With the rapid development of information technology and the popularity of intelligent terminals,blended learning(BL)has shown great application potentials based on the dual advantages of face-to-face learning and online learning.BL provided flexible learning time and space to learners.However,the effects of BL were not ideal,which was mainly manifested in the low level of learning input,less active participation,lack of deep learning experience,and so on.It was urgent to integrate new learning ideas to optimize BL design framework and practical methods.In 2020,with the epidemic of New Coronavirus pneumonia raged all over the world,BL became the new normal of "Suspend Classes not Stop Learning" for university students,which triggered the reconstruction and transformation of higher education teaching model.In the post epidemic era,people eagerly hope that BL gives full play to its own advantages,and makes greater contributions to the cultivation of high-quality talents.The typical characteristics of deep learning(DL)are active participation,cultivating high-order ability,learning for transformation.Deep learning has gradually become an important way to improve the learning engagement and quality.Therefore,the study took BL as the research field,DL as the research goal,and university students as the participants,thus,to explore effective strategies to improve the quality of BL.Under the design based research paradigm,the intervention model was designed,intervention curriculum was constructed,two rounds of iterative implementation and effect evaluation were carried out.The main research contents and results were as follows:1.Through bibliometrics and content analysis,this study systematically reviewed both BL and DL relative literature.It's revealed that blended learning to promote deep learning(DBL)has not yet achieved the consistency design of objectives,contents,activities and evaluations.The teaching process lacked the typical deep learning activities support.The evaluation methods were not rich enough and difficult to realize the comprehensive evaluation of learning results.2.A deep learning ability survey of 260 students was conducted from six dimensions which including cooperation,communication,autonomous learning,learning perseverance,critical thinking and innovative thinking ability.It was found that the deep learning abilities of university students were weak,among which the cooperative ability was relatively better,but the critical thinking ability and innovative thinking ability need to be improved urgently.These results revealed the necessity and feasibility of deep learning.3.Based on constructivism learning theory,situated cognition theory and meta-cognition theory,the DBL design model was proposed.The first key element was higher-order learning goals,which drives students' internal learning motivation and achievement expectation.The second element was the content system based the unified design idea,in which online content served to build solid knowledge base and offline content focused on promoting high-order ability development.The third element was the active participating and deep processing orientated learning activities,such as problem solving,case analysis,peer assessment and opinion integration,etc.The last element was the multiple-assessment system,which focused on both learning processes and learning outcomes.It should be effectively distinguish students' knowledge mastery,ability development,emotional experience and process performance.Taking the course of"retrieval and analysis of educational literature" as an example,the comprehensive intervention construction at the curriculum level was completed.It was the necessary artifact in the teaching reform.4.Combined with the time sequence of BL,a three-stage learning process named S-D-R was put forward,which was composed of self learning before class,in-depth seminar in class and reflection-expansion after class.A seven-step deep learning method was also proposed,which consists of learning situation feedback,preview detection,key points elaborate,collaborative problem solving,point sharing,thinking improvement and summary.It revealed the transition process from surface learning to deep learning in the BL environment.5.Taking the first round of S-D-R learning process as an intervention prototype,two rounds of iterative implementation were carried out in the fall of 2019 and the spring of 2020 for S university students.The data analysis results showed that:From the perspective of learning process,the blended learning class which aim to promote deep learning had the typical characteristics of learner-centered,active participation and plentiful interactions.In the learning process,a large number of relational-structure and extended-abstract structure mind maps were produced,and dialogue level and critical level reflection journals were also be found.They were important evidences of the occurrence of deep learning.From the aspect of learning outcomes,the students mastered the core subject knowledge effectively and got excellent achievements in the course.The 6 kinds of deep learning abilities,such as cooperation ability,study perseverance and creative thinking ability,have been improved significantly.The students' behavioral,cognitive and affective inputs were at a high level,showing the typical characteristics of affective input>behavioral input>cognitive Input.Students'satisfactions with the curriculum were high.The satisfactions of learning content,activities,quality,evaluation,interaction and platform were all more than 90%.The end-of-class interview revealed that the reasons of high satisfaction were mainly focused on meaningful learning contents,effective teaching methods,harmonious relationship between teacher and student and positive deep learning culture.After two rounds of iteration,a blended learning system solution to promote deep learning was formed from aspects of design,implementation and evaluation.It effectively solved the existing problem of "surface learning and low efficiency" of BL in nowadays.Genetic mechanism and design principles to promote deep learning in blended learning environment were deduced.These findings could provide enlightenment for improving BL quality and DL theories.