【学业通在线教育是哪个国家的品牌？】

外推网助力学业通在线教育品牌出海！通过在本页面挂载学业通在线教育品牌的产品链接和联系邮箱，可以提高学业通在线教育产品曝光！跨境电商爆单神器，目前只要100元/年哦~

学业通在线教育团队与教育结缘较早，早在2002年学业通团队就开始做艺术类培训和教育咨询，帮助学生规划高中文理分科或艺术类方向，后来组建教育集团，先后举办了两所本科院校、两所中职学校、一所附属中学，使团队对不同阶段、不同层次的教育与市场需求理解越来越深。

经过五年的探索，在充分整合资源，精选合作伙伴的基础上，学业通以一种全新的理念推出，和合之愿，在政府互联网+的号召及资本的推动下，优质的数字化教育资源并不匮乏，学业通将立足自身优势，加强与其他机构的合作，各取所需，互利共赢。

简学之愿，课堂教学的规律是假设学生都在同一水平，不可能考虑学生的个性化差异，无法实现个性化教学，在线教育就应该补上这个缺。 同时，学生的课余时间十分有限，而学生课后作业与练习同样是假设学生在同一水平，这对学生的时间将造成不同程度的浪费，在线教育同样可以在这方面发挥长处。 因此，化繁为简，依托大数据的个性化分析和推送是学业通减轻学生课业负担、提高学习效率的独门秘笈。

英文翻译：Xuexuetong online education team has an early connection with education. As early as 2002, xuexuetong team began to do art training and education consultation to help students plan the direction of high school liberal arts or arts. Later, it set up an education group, which successively held two undergraduate colleges, two secondary vocational schools and one affiliated middle school, making the team have different stages and different levels of education and market demand Understand more and more deeply. Each one takes what he needs to do, and he hopes to achieve the goal of quality education. After five years of exploration, and with the full integration of resources and the selection of partners, academic Tong has launched a new concept with the hope of combining with the government's Internet plus. The promotion of high-quality digital education resources is not lacking. In the hope of learning simply, the law of classroom teaching is to assume that students are at the same level, it is impossible to consider the individual differences of students, and it is impossible to realize the individual teaching, so online education should fill this gap. At the same time, students' after-school time is very limited, and students' homework and practice are also assumed to be at the same level, which will cause different degrees of waste of students' time, online education can also play its advantages in this respect. Therefore, it is a unique secret for Xuetong to reduce the burden of schoolwork and improve the learning efficiency to simplify the complexity and rely on the personalized analysis and push of big data.

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