Survey And Analysis Of Metacognitive Ability About Graduates’ Web-based Autonomous Learning

In the information society, efficient web-based autonomous learning is magic to adapt to thelearning society for graduates. Training graduate students with higher self-learning ability is thenew requirement proposed for higher education by community. Metacognitive ability act as avery important sub-capacity of self-learning ability, the level has a direct impact on self-learningability and the results of independent study. Through the relevant literature, the currentinvestigation of web-based autonomous learning or students’ metacognitive ability level is morea lack of, and has not been given sufficient attention. Therefore, in order to better grasp themetacognitive ability level of graduates’web-based autonomous, learning; metacognitive abilityof graduates’ web-based autonomous learning was investigated. By the problems found,exploring the strategies to improve learning metacognitive ability of graduates’ web-basedautonomous learning, and provide a reference for graduate students to better complete graduates‘web-based autonomous learning,. The research was done as follows:Firstly, based on a large amount of literature and fully understand the related concepts, theresearch define metacognition of graduates’ web-based autonomous learning, discusses themetacognitive structure of web-based autonomous learning: metacognitive knowledge ofweb-based autonomous Learning, metacognitive experience of web-based autonomous Learning,metacognitive monitoring of web-based autonomous learning.Secondly, According to the metacognitive structure of web-based autonomous learning, theresearch developed a metacognitive ability questionnaire of web-based autonomous learning.The questionnaire consists of two parts: The first part is the basic situation of web-basedautonomous learning. The second is investigation on the level of cognitive ability of web-basedautonomous learning.Thirdly, the research issues the questionnaire and analysis the questionnaire data usingExcel and SPSS software. The main conclusions are as follows: Overall graduate metacognitiveknowledge reached above average levels. But metacognitive experience and metacognitivemonitoring level is not high. Specific performance: Graduate students metacognitive knowledge is not rich enough; Lack of self-confidence and problem-solving initiative; No web-basedautonomous Learning planning, Lack of reasonable arrangement; Lack of ability to evaluate andsummarize the level of metacognition; Susceptible to external interference, Self-controlconsciousness is not strong.Lastly, for metacognitive ability problems of web-based autonomous Learning, the researchproposes suggestions to improve the metacognitive abilities of web-based autonomous Learningplanning, separately from the student body and improve the network environment. Specificincluding: The cultivation of metacognitive awareness and expanding the metacognitiveknowledge; Arousing students’ inner learning motivation and interests; Strengthening themonitoring of training, improving the supervisory ability of meta cognition and self-efficacy;Improving the students’ ability of reflection and evaluation, training students’ critical thinking; Acorrect understanding of the dominant position; Creating vivid and suitable web-based learningenvironment; Strengthening interaction design of e-learning platform; Building high qualityonline learning resources. The purpose of this study is to help postgraduates to improve theeffect of web-based autonomous learning.