rOpenSci | rOpenSci Champions Pilot Year: Training Wrap-Up

Our first cohort of the rOpenSci Champions Program has now completed the first phase of their training. One of the goals of this program was to ensure that all participants gained new skills and understanding. We wanted to support Champions and Mentors, but also those who applied to the program but were not selected. Therefore we ensured that all groups had access to different training opportunities.

In this article, we share the curriculum created for the Champions, Mentors, and non-selected applicants, as well as what we learned during this pilot.

🔗 Training for the Champions

We planned six weeks of training that covered the following topics:

  • how to plan and facilitate engaging and inclusive workshops to support participants’ success,
  • knowledge of various channels through which new members can engage in and contribute to rOpenSci and R projects, and
  • technical skills in software development and review.

The final curriculum for this pilot consisted of 5 courses. In addition, Champions were invited to the training session for non-selected applicants as an optional activity.

🔗 Making a PACT for engaging virtual meetings and events

In this 90-minute mini-workshop hosted by the Center for Scientific Collaboration and Community Engagement, participants explored designing and facilitating engaging and productive virtual meetings and events.

Participants discussed the opportunities and challenges of working together online and outlined the “Making a PACT” framework for effective meeting design. In addition to reviewing examples of the framework in action, attendees practiced applying it to some example scenarios to empower them to try using the framework in their own work. Participants were welcome to review the CSCCE’s free guidebook on Zenodo ahead of the session: A guide to using virtual events to facilitation community building: Making a PACT for more engaging virtual meetings and events

This training was mandatory for all Champions, and was taught by Camille Santistevan and Maya Sanghvi.

🔗 Package Development: The Mechanics

In this two-hour session with a live demo, an rOpenSci trainer demystified the creation of R packages. R packages are mostly well-organized folders, with automatic tools to help, such as usethis. This workshop was intended for Champions planning to develop a package who had not previously developed or contributed to packages.

This training was developed for the Champions Program and taught by Maëlle Salmon.

🔗 Package Development: Not Rocket Science

This two-hour workshop was for R users who had already developed or contributed to packages or had taken the “Package Development: The Mechanics workshop”. It was intended for Champions planning to develop a package or submit it for review and who wanted to learn several tips and tricks on package development. Ideally, participants attended with a package of their own to use as a playground.

This training was developed for the Champion Program and taught by Maëlle Salmon.

🔗 How rOpenSci Performs Peer Review

This one-hour workshop was for people wanting to try the rOpenSci review process, particularly for Champions planning to send a package to review or become reviewers. We reviewed the way we communicate, build, and review software with selected examples and resources, with some time for questions and comments.

This training was developed for the Champion Program and taught by Mauro Lepore.

🔗 How to contribute to base R

This workshop was a 60-minute walk-through of how to contribute to base R. It included how to contribute to a bug, confirm a bug, diagnose a bug, and propose a fix to code/documentation.

The workshop presented tools and strategies to find a bug to work on and discussed which features make a bug good for a first-timer. Using real bug reports, participants practiced identifying good first issues. Then the process of debugging code/documentation was introduced in a collaborative exercise. Participants were briefly shown how to propose a bug fix by commenting on Bugzilla or creating a patch using GitHub. Finally, pointers and resources were shared.

This training was developed and taught by Heather Turner.

🔗 Training for the Mentors

In addition to the following workshop, Mentors were invited to all the training sessions offered to Champions and non-selected applicants as an optional activity.

🔗 rOpenSci Champions Program. Mentorship Training and Orientation

Mentors developed their mentoring skills during this training and orientation, which covered active listening, effective questioning, and giving feedback. They received resources for their mentoring roles, such as the Mentors’ Guidelines, Meeting Templates, and details of the logistics of the Champions Program.

This training was mandatory for all Mentors. It was developed for the Champions Program and taught by Yanina Bellini Saibene.

🔗 Training for non-selected applicants

We also conducted a workshop for those not selected to be Champions. The aim of this workshop was to provide an opportunity for all applicants to develop skills in open-source software development to support their professional advancement, which may include future applications to this or other similar programs.

🔗 Developing Software Together

This was a three-hour course on using Git and GitHub to collaboratively develop open-source software with the R language. The training presented how to work with Git, using the command line, RStudio, and GitHub. The workshop introduced the concept of version control systems, local and remote repositories, and actions like stage, commit, push, pull, and merge. It also demonstrated how to collaborate with others through forks and pull requests. The workshop had hands-on and group exercises.

This training was developed by Paola Corrales and taught by Paola and Yanina Bellini Saibene.

🔗 What do our participants think of the training received?

At the end of each workshop, we asked those who participated to fill out an anonymous survey asking three questions:

  • What did you like the most?

  • What did you like the least?

  • Can you rate this meeting? (on a scale from 1-worst to 5-best).

We plan to use this feedback to improve the next run of the Champions Program. The average score for all the training sessions was 4.6, which shows that the attendees are very satisfied with the workshops.

When we analyze the responses to “What did you like the most?” we found four positive aspects mentioned: Interaction with other participants, Structure of the workshop, Materials and Resources shared during the workshop, and Exercises performed during training.

The following plot shows the number of mentions for each aspect and an example comment explaining why it was perceived positively by the participants. The comments highlight various aspects of the training, such as enjoyable interactions, valuable tools provided, opportunities for reflection and a good structure based on practice after instruction.

Ranked quantities of four different positive aspects in a bar plot. The aspects are Material and Resources (15 mentions), Interaction with other participants, (10 mentions), Exercises (8 mentions), and Structure (7 mentions). Each aspect is followed by a comment explaining why it was perceived positively by the participants.

Even though the answers to “What did you like the least?” show that most attendees think there is Nothing they liked the least, we identify five areas for improvement: Level of the training, More time for all the content or exercises, Tools used during the workshops, Exercises during the workshop, and Pace of the teaching. In the plot we show the number of mentions and each aspect is followed by a comment explaining the specific improvement, suggestion, or feedback.

The comments highlight the need for more time to cover content, the desire for better collaboration tools, the request for additional exercises, and the suggestion to offer different levels of training, one for beginners and one for competent practitioners. The comments also include expressions of overall satisfaction while mentioning challenges, like time zones.

Ranked quantities of five areas of improvement in a bar plot. The aspect are Nothing (12 mentions), Level (5 mentions), More time (4 mentions), Tools (4 mentions), Exercises (3 mentions), and Pace (3 mentions). Each aspect has a comment explaining the specific improvement suggestion or feedback.

The survey data provided us with valuable insights into the participants’ perspectives on the strengths and areas for improvement of our workshops. We’re looking forward to taking these comments into account when we develop the next set of training sessions.

🔗 Next Steps

With a new cohort starting this year (you can apply now!) we plan to improve the schedule for each training session, allowing participants to choose between two runs of the session that cover different time zones, and recording the sessions for participants to watch after the meeting. We will develop guidelines to increase accessibility of each session and will change the order of the workshops. Specifically, training on how to organize events will be conducted closer to the time when Champions should start planning their outreach activities. In this way they will be able to use the workshop to work on their concrete proposals and receive feedback from the instructors and the rest of their peers.

We also plan to complete another assessment at the end of the program, including a final survey and interviews with Mentors and Champions with the support of CSCCE team.

🔗 Achievements

We developed a new curriculum involving not only rOpenSci staff but also Champions, Mentors, and individuals from other communities, which has strengthened connections among rOpenSci and others in our shared ecosystem.

We also published all the training material with open licenses. This has enabled other organizations, such as The Netherlands eScience Center, to adapt and reuse our materials for training Mentors for their own Fellowship program. If you use our training materials, please let us know by sharing your use case.

Overall, the rOpenSci Champions Program successfully trained participants in essential skills for their role as Champions and Mentors while fostering engagement and collaboration in open-source research software development.

🔗 Acknowledgements

The rOpenSci Champions Program is funded by The Chan Zuckerberg Initiative. This phase of the Champions Program was made possible by the work and feedback of many people.

We want to thank the CSCCE team, especially Lou Woodley, Camille Santistevan, and Maya Sanghvi, for their support in designing the overall program and for their “Making a PACT” workshop for the Champions.

We also want to thank Maëlle Salmon, Mauro Lepore, Paola Corrales, Heather Turner, and Yanina Bellini Saibene for developing and teaching the rest of the workshops in the program and to Yanina for supporting the design of the new workshops, the support infrastructure and organizing all the training.

We also thank Batool Almarzouq for her feedback on the idea of Mentor training and Abigail Cabunoc Mayes for her advice and material in developing the Mentor’s workshop.

Finally, thanks to our Champions and Mentors for actively participating and sharing their recommendations to improve the training sessions in this program.