制作方:   明尼苏达大学

  • Loren Terveen

    教学方:    Loren Terveen, Professor

    Computer Science and Engineering

  • Haiyi Zhu

    教学方:    Haiyi Zhu, Assistant Professor

    Computer Science and Engineering

  • Lana Yarosh

    教学方:    Lana Yarosh, Assistant Professor

    Computer Science and Engineering

  • Dr. Brent Hecht

    教学方:    Dr. Brent Hecht, Assistant Professor

    Computer Science and Engineering

  • Joseph A Konstan

    教学方:    Joseph A Konstan, Distinguished McKnight Professor and Distinguished University Teaching Professor

    Computer Science and Engineering
基本信息
Course 2 of 5 in the User Interface Design Specialization.
语言
English
如何通过通过所有计分作业以完成课程。
用户评分
4.6 stars
Average User Rating 4.6查看学生的留言
Course 2 of Specialization
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制作方
明尼苏达大学
The University of Minnesota is among the largest public research universities in the country, offering undergraduate, graduate, and professional students a multitude of opportunities for study and research. Located at the heart of one of the nation’s most vibrant, diverse metropolitan communities, students on the campuses in Minneapolis and St. Paul benefit from extensive partnerships with world-renowned health centers, international corporations, government agencies, and arts, nonprofit, and public service organizations.
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评分和审阅
已评分 4.6,总共 5 个 44 评分

Nice, expesially the second part of the course.

Good, a lot about research and collecting data.

Important concepts like tasks, walkthrough scenarios, use cases, and personas are very well explained with good examples helping to understand the differences. There were methods like the quantitative analysis and ideation that I have not come across in 15 years of my professional life as a software developer - so there is certainly still a message to be spread. Questions are presented within the videos to make sure you are keeping track. A lot of hints for further reading are given. Great learning material!

There are two minor points I would like to mention although they do in no way make me downrate the course. The part on the quantitative analysis I found a little too shallow and short - but on the other hand, these methods are more common and easily accessable in statistics courses and books. The ideation assignment I found a little hard - to come up with 100 ideas alone, not in a team which the method is designed for. On the other hand, it helped experience that the method works as I could come up with several really different ideas for the given problem.

Good