Education is a right of all, however, every individual is different than others. Teachers in post-communism era discover inherent individualism to equally train all towards job market of fourth industrial revolution. We can consider scenario of ethnic minority education in academic practices. Ethnic minority group has grown in their own culture and would prefer to be taught in their native way. We have formulated such linguistic anthropology(how people learn)based engagement as semi-supervised problem. Then, we have developed an conditional deep generative adversarial network algorithm namely LA-GAN to classify linguistic ethnographic features in student engagement. Theoretical justification proves the objective, regularization and loss function of our semi-supervised adversarial model. Survey questions are prepared to reach some form of assumptions about z-generation and ethnic minority group, whose learning style, learning approach and preference are our main area of interest.
教育是所有人民的权柄,然而,每个个体都与其他个体不同。后共产主义时期的教师发现了内在个人主义,旨在平等地训练所有人向第四工业革命的就业市场迈进。我们可以考虑种族少数群体的学术实践中的情况。种族少数群体在自己的文化中成长,并更喜欢以他们自己的学习方式进行教学。我们将这些基于语言人类学(人们如何学习)的活动归纳为半监督问题。然后,我们开发了一种新型的Conditional Deep Generative Adversarial Network算法,即LA-GAN,以分类学生参与中的语言人类学特征。理论证明证明了我们的半监督对抗模型的目标、正则化和损失函数。调查问题准备用于确定z世代和种族少数群体的学习风格、学习方法和偏好,这些群体的学习风格、学习方法和偏好是我们主要兴趣的领域。