The Research On The Current Status And Factors Of Deep Learning For College Students In Internet

An emerging learning paradigm has taken shape along with the advent of the digital world comprised of Internet and mobile computing. However, the efficacy and efficiency of this new learning paradigm is not yet supported by substantial evidence. The new learning activities are usually fragmented in time and superficial in terms of professionalism, of which Internet is deemed culprit. Deep learning, a concept seen in some countries’education policies, is also, to some extent, reflected in China’s education reform, which advocates proactive learning, autonomous learning, and cooperative learning in projects, among other modern learning modes. The education reform in China indicates the emphasis the Ministry of Education has placed on the depth of learning. It is of great practical importance to research on the current status of deep learning and what factors would determine the efficacy and efficiency of deep learning for college students in the digital world, given that new problems emerges with the new learning paradigm. This study is described in seven chapters in detail.The first chapter is introduction, which includes background, rationale and value of this study. It also includes literature review of the current status of deep learning for college students in the context of digital world and Internet, both in China and other countries.The second chapter describes the theoretical basis of deep learning and the difference between deep learning and shallow learning. It also introduces the cognitive education target classification theory, the situated cognition theory and the new theory of constructivism.The third chapter describes questionnaire reliability and validity test. The questionnaire combines the 2015 national college students’ learning engagement survey (NSSE 2015) and deep learning theory. The survey subjects are from students of Yunnan University who chose "desired" courses in "wisdom tree". Questionnaires were then collected and validated by the validity test.The fourth chapter is the analysis of current deep learning status for college students, conducted in six aspects including students’ knowledge of deep learning, driving force of study, resource utilization, construction of knowledge understanding, problem solving ability and communication skills.The fifth chapter is the analysis of factors that affect deep learning. Principal component analysis and linear regression analysis are employed to quantitatively determine the key factors based on the current status of deep learning in college students. Factors are also analyzed from five dimensions including the level of college students’ academic challenge, communication frequency, active cooperation, deep processing and reflection evaluation levels.The sixth chapter describes the strategies that improve college students’ deep learning in the context of digital world and Internet, based on scientific reasoning.The seventh chapter is conclusion and prospect. It also lays out potential improvements of this study that can be achieved in future work.