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《Distance Education in China》 2017-08
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An empirical study of deep learning content and its resource representation

Hang Hu;Yuqi Dong;  
Adopting the research framework for deep learning and built on the experiment to explore how technology enhances learning, this study focused on learning content and resource representation. Informed by cognitive and brain science as well as the psychology of learning mathematics, the study designed two types of classroom: two control groups and two experiment groups, with four variables. The fourweek experiment was carried out among Year Five pupils at a primary school in City T, one hour per day. The experiment covered subject knowledge, learning strategies corresponding to subject knowledge,cognitive structure, 4S of social skills as well as development and application of CRF digital learning resources. Based on data from academic achievement, eye tracker and ERP brainwave recordings, the study came to the following conclusions. First, learning content based on cognitive processes and the reconstruction of resources have significant effects on academic achievement. Second, there exists interplay between the quality of learning and technology. Third, it is the design of technology, not technology itself, that enhances learner development. Fourth, results from the verification experiment are basically consistent with those from the exploratory experiment. Last, academic achievement, eye tracker and ERP brainwave recordings can form a solid triangulation of findings.
【Fund】: 全国教育科学“十二五”规划2014年度教育部青年课题“‘复杂问题解决’学习的实证研究”(项目编号:ECA140369)研究成果之一
【CateGory Index】: G420
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