| The rising of MOOC(Massive open online course)brings the video education to a climax.MOOC advocates video as the carrier,in which the learner according to the needs of knowledge points for independent study.But the existing video classification or search engines are not based on learner’s cognitive differences.The videos are not matched with the learners’ interest.When learners search through the Internet,it is difficult to find suitable video resources quickly and accurately.Focusing on the differences of learners from the perspective of cognitive style,this paper proposes multi-modal classification model based on cognitive style and aims at providing learners with suitable resources and improving their learning efficiency.The main content of this research is described as the following:(1)The multi-modal classification model for MOOC videos is built.Based on the system theories,the factors such as the learners,the videos and the instructor are taken into account,the dimension model of Verbal-Imagery,Field independence-Field dependence,Polymerization-Divergence,Impulse-Meditation and Extensive-Sensitive cognitive style is proposed by analyzing the features of learners and videos.(2)Taking the Verbal-Imagery,Field independence-Field dependence cognitive style for example,the questionnaire of cognitive style is designed and new method and formula is proposed to classify the learners and the videos.(3)388 junior students were tested to verify the model’s validity.The results show that the cognitive style and the video style had significant effect on students’ score.After watching videos,learners got 30 percent higher than before.When watching the same cognitive style’s video,learners’ score are 14.9 points higher than watching unsuitable video.(4)Finally,suggestions on the MOOC video production and the strategy of video recommendation system are proposed based on cognitive style.The experiment investigation confirmed the validity of the model. |
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