@ccannon94 That made me roar with laughter. Thanks for that. Good to know other lecturers feel my pain.
I looked at the JUnit5 Github repository. Looking at how recent the Commits have occurred shows that the project is being actively worked on. (Most recent commit was today.) There are over 4700 commits from 85 contributors. The repository also has 2400 stars, over 500 forks and 148 issues.
The project is still active, it has 1872 commits, and the last was done today.
There were 3 Pull requests merged by 3 people, in the last 18 hours
I would asses collaborations in groups checking the number of commits and authours of them.
Checking dates of the different activities, and comment on changes.
Also it will be useful to check on the issues and who is closed by.
Very useful information to check on the progress of students !
This project has 182 pull requests, 23558 commits and more than 2000 contributors
44 active pull requests (7 merged and 37 proposed)
64 active Issues (36 closed and 28 Issues)
Users who contribute the most
All this information will be very useful information to check on the progress of students
100 Days of ML Coding is an interesting active project. It has 102 commits (the last was done 12 days ago) and 6 contributors (although if we check the insights, we realize that only 1 contributor is seriously working on the project.). We have 6 pull requests solved in the last month.
I would use these insights for checking the frequency of the commits, the contribution of each student to a group project or for knowing how quickly the pull requests are solved. A very useful tool!
My choice is Slimphp / Slim https://github.com/slimphp/Slim/graphs/commit-activity
With 3,130 commits 3 branches 186 contributors 9,203 Stars and 1,814 Forks the project is still alive.
There is a consistent contribution:
The most active ones are Codeguy and Akrabat.
The last commit was done on 05/08 2018. They are prety active.
sufficient acitve pull requests
various closed issues within a week time.
This is very much help in analyzing the individual contributions within a group of students.
Here is an active project https://github.com/eclipse/xtext-core/
Activity on it is continuous, huge number of contributors, all the metrics are high (stars, forks, you name it).
Great software btw
As for evaluating them based on these metrics, I don’t like it so much.
They should feel free to use the versioning system for what it is, not fear reprisal or policing of their usage (or I’ll get bogus commits to simulate activity etc…).
I do look at their activity profile to look if there is over the semester contributions every week.
I chose MongoDB.
Some interesting metrics:
Pull requests: 34 open, 1223 closed
Insights show that in the past week, 50 authors have pushed 103 commits (as well as other information).
When I look at the repository I like to see what my students have contributed through their commits. While commits are not necessarily indicative of work (you can do very little in 20 commits, or a lot in 1 commit), you can get an idea of how people are contributing based on frequency and content of commits. I would like to see my students have lots of commits spread out over the course of a week than one large commit.
Another interesting thing to see would be how often someone’s work is reverted in pull requests or merges; I’ve seen students’ work clobbered by other students (on purpose), so it would be interesting to see if whether it’s because the contributions were bad or some other reason.
Is active because:
Latest commit to master 7 days ago
Pull requests opened a week ago
Last release 18 days ago
I’m using it and they have a telegram group to post problems and questions about it.
Nice @ivonetafe! How might statistics like this help you evaluate or give feedback to your students?
I tend to agree about the effects of requiring students to “check the box” of committing often. I do find these useful for resolving group conflicts if members feel one teammate isn’t quite pulling their weight, it allows one avenue of investigation.
@CDNievas how might these statistics be useful on a student’s repository?
With the commits and branches you can see how they divide the work and who of them are doing it.
Also you can inspect their code and open issues to correct things, if the issues are closed fastly represents that they are active at the practice exercise and solving the different problems
On the other hand, traffic is not that high. Marketing a book is no small task, and I don’t have enough time to to it properly.
When assessing group work, I mainly look at commits and ask the team if I see huge differences between members.
I took a look at the AWS CLI project:
Some evidence that the project is active:
- 15 pull requests between 9/21 and 9/28.
- At least a few commits each week.
- More forks than GitHub can shake a stick at.
- Releases ever day or two.
In terms of group work for my classes, it’s going to come down to observing student contributions and being able to look at patterns of commits over the course of their sprints.
- Recently closed pull requests
- Regular commits
I have used this in my web programming course to monitor student participation. I ran into problems, however, because I was worried about taking too much time in teaching students who are novice programmers the process of merge conflicts. Often students would send each other changes and have a single student do the commits. Now that I better understand the git/Github workflow better, I want to revisit it and have them follow the proper processes.