由於資訊科技的進步,數位學習已成為目前最熱門話題,使得數位學習已成為目前學習的主流。由於不受時空限制,隨時隨地都能學習,並能選擇自己想要的課程,十分的有彈性,使得學校與企業訓練學生或員工的方法有了革命性的改變。在本文中建構了一個數位學習系統的適性機制,此機制能在數位學習系統中夠提供給學習者一個選擇適性課程的決策。首先在本文中,我們提出一個循序式的Photoshop學習模型,即為傳統式的Photoshop學習模型。無論如何,此循序式模型並不能用於適性學習上。因此,我們使用派翠網(Petri Net)來塑模一個具有適性機制的數位學習系統。而本文是以Photoshop數位學習系統為個案研究。最後,我們比較與分析以上兩個模型。我們得到以派翠網塑模之數位學習模型的學習效果優於循序式Photoshop的學習模型。
Due to the information technology progressing, the electronic environment has become a hot topic. The Digital Learning is then becoming one of the most important applications. In this way, people can choose the courses they want, and learn in anytime and anywhere through digital materials. The Digital Learning makes fashionable both in schools and enterprises. In this paper, we construct an adaptive mechanism for digital learning system. This scheme can supply a decision-making for choosing adaptive courses for learner in a digital learning system. First, we proposed a successive learning model for Photoshop curriculum, which is a conventional learning model. However, the successive model is not suitable for suitability study. Therefore, we then use Petri Net to modeling the digital learning system for the purpose of constructing an adaptive mechanism. Then, the case studies of digital learning system for Photoshop are given in this paper. Finally, we give the comparison and analysis for both two models mentioned above. Our propose mechanism can achieve better learning results than progressive one.