CIRCA:Google analytics report

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Revision as of 13:41, 7 December 2015

Google analytics report of GWrit

To have a better understanding of the usage of GWrit, we use google analytics to analyze some basic information of users, including audience overview, user behaviors, and the relationship between events flow and due date.

Audience overview The most commonly used language is American English, followed by Canada English, Chinese, Great Britain English and korean. The language usage is judged by users’ browser setting, and not by the nationality of user. So, we can see the most of the users are English speakers.

The most commonly used operating system is windows system, followed by Macintosh, iOS, Android, Linux and Chrome OS. The usage of mobile development is opposite from the PC operating system. The iOS is the most commonly used system, and then it comes Windows and Android. We can also see the browser usage from google analytics. Users using Chrome browser accounts for 44.68%, ranks first, and the second one is Safari, accounting for 30.83%. From the service provider section, we can see the most of users (48.68%) visit GWrit through the university service.

User behavior analysis We draw two different trajectories of user behavior in different time according to the data from google analytics. The first one is the behavior when there is no task due. The second one is in task due date. The first trajectory is: User login and selects course from the courses list. Then he select a project of this course. In the project page, he clicks “View Other Submissions” for a specific task. In the task submissions page, he selects another user’s work to view. The second trajectory is:User login and selects course from the courses list. Then he select a task, and views the completed task or comments on this task. After make some modification, he saves the completed task.

Usage & Task Due Date

This is a figure shows the relationship between pageview and task due date. Sep.18, Oct.9 and Oct.16 are three due date during the selected time. From the statistic, we can see that in the beginning of the term, users visit GWrit frequently. As time goes by, the pageview changes according the the task due date. Pageview of GWrit achieves to peak point when there is a task deadline.

This is a picture shows the relationship between due date and user’s actions. The time points in X array are three task due dates: Sep.18, Oct.9 and Oct.16. Y array stands for the accounts of actions. We can see the trend line of set, triggerreward, save and login reach to peak point on the due date. While the trend line of profile, submit_comment and word_cloud seems have little relationship with due date. The account of the word_cloud events is quite small compared to other events, especially the save event. So, it seems that using word_cloud is not a necessary action before writing submission. Since the current word-cloud analysis tool is only used to show the word frequency, so we plan to make it more functional for future version, making it more interactive. The line of submit_comment shows that there is not a clear relationship between commenting and task due date. And the the account of commenting action is not very big compared with other actions. From the small-scale of commenting action, the only way of social communication among GWrit users, we can see that the social function is not an outstanding part of the current version of GWrit. Besides, comments from others plays a less important role to help improve online writing than we hypothesised.

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