Traditional visual communication design teaching courses only use books and courseware for teaching, which greatly limits students understanding and perception of visual communication design art courses. The visual communication design course is different from the teaching of other subjects; it requires students to have a deep understanding of the content of the video and the experience of emotion. Relying on courseware and book teaching methods will not only limit students’ imagination, but also make students tired of learning psychological activities. The teaching of visual communication design technology is to transmit the images, colors, words, and emotions of artworks to students in the form of video, which is a relatively abstract course. With the development of big data technology, this brings new opportunities for the teaching of visual communication design technology courses. In this study, data mining technology will be used to evaluate the effect of visual communication design teaching. And CNN will be used to predict the content characteristics of visual communication design teaching, which is part of the visual communication design teaching system. The research results show that the big data method has better performance in the visual communication design technology course; both the classification and prediction errors are within the acceptable range for the artwork of the visual communication design course. Big data technology can well predict the relevant features in visual communication design; the largest prediction error is only 2.66%, and the smallest error is only 1.21%.

Penulisan ini bertujuan untuk membincangkan pencapaian dan pemahaman prinsip ‘Appeal’ dalam reka bentuk watak animasi lokal. ‘Appeal’ adalah salah satu daripada 12 prinsip reka bentuk animasi dan kerap kali dianggap sebagai kurang jelas. Untuk mencapai ‘daya tarik’, salah satu kaedah yang digunakan ialah kata-kata kunci impresi penonton atau Viewer’s Impression Words (VIW), yang merupakan pengubahsuaian dari Kansei Words (KW). Kaedah ini menggabungkan teori formalistik dan semiotik visual untuk mencapai VIW, iaitu bahagian penting dalam Kejuruteraan Kansei. Kaedah ini disarankan sebagai teknik baharu untuk memperbaiki kaedah dalam memperoleh kata-kata VIW atau KW untuk digunakan dalam latihan pengukuran bagi menemukan kesan (emosi) dalam memahami ‘appeal’ sehingga dapat mencapai prinsip-prinsip longgar dalam reka bentuk watak animasi tempatan.This article discuss about the achievement and understand the ‘Appeal’ factor in local animated character design. ‘Appeal’ is one of the 12 principles of animation design and often considered ambiguous. To achieve ‘appeal,’ one of the methods used is audience impression keywords or Viewer’s Impression Words (VIW), which is a modification of Kansei Words (KW). This method combines formalistic theory and semiotic visuals to achieve Viewer’s Impression Words (VIW), which is an essential part of Kansei Engineering. This method is suggested as a new technique to improve the method in obtaining words VIW or Kansei Words to use in measurement exercises to find the effect (emotion) in understanding ‘appeal’ to achieve loose principles in local animated character design.