Author Archives: Yue Jin

R Open Lab: Looking Back and Moving Forward

In the past academic year, I worked as a teaching intern with the Digital Social Science Center and Digital Science Center, hosting R open labs and workshops. Most of the people at R Open Lab are using R for their research projects; therefore in the past semester, I tried out several different teaching practices in search of the best way to enable the participants to harness the power of R as a research tool.


New Teaching Practices

  1. Peer learning: It was the first method I tried out and it seemed to be the most helpful one. By talking with people with similar research interests and learning from each other’s experiences, many participants expanded their professional networks and found a better way to apply R to their research. Exchanging learning experiences with people from different academic backgrounds helped the participants to gain a broader understanding of the functionality of R. However, creating a stimulating environment for peer learning but not making the participants feel pressured can be challenging.
  2. Group discussion: I tried to encourage group discussion by throwing open-ended questions at the participants during the instructions. The problem with this method is that more often than not, the discussions were very shallow, probably because the questions were not interesting enough. Looking forward, it might worth trying to prepare a thought-provoking question for each R Open Lab session and make group discussion as a standalone part.

Challenges and Solutions

Based upon my experience with both workshops and open labs, and the feedback from the attendees, the challenges facing the R Open Labs and possible ways to improve them are as follows:

  1. Due to lack of a clear syllabus for the whole semester and its self-paced nature, most participants are not motivated to attend R Open Labs regularly. To help participants have a better idea of the progress of open labs, we can try to post topics for each session a month in advance on the workshop list. We can also maintain a GitHub repository and upload materials used for instruction after each session so that other interested individuals could easily access them.
  2. Although the Swirl package is an immensely helpful starter kit, most people new to coding and statistics still struggle with very basic R operations. Furthermore, the huge gap between basic operations and being able to fully implement a research project can be frustrating and overwhelming. Therefore, instead of Swirl, we could provide participants with some sample code and links to GitHub repositories, so that they could use them as a starting point for their own projects and learn best practices of building a project with R
  3. Some questions are frequently asked by the participants, so we can probably provide participants with a list of FAQs and the general answers to maximize efficiency.

To conclude, this internship motivated me to think deeper about teaching and better understand people’s needs. It was an incredibly challenging and rewarding experience. As data analysis becomes increasingly important in a multitude of research areas ranging from biology to history, R is becoming an essential research tool. I hope by continuing to make improvements to the contents and structure of R Open Lab, it could serve as a platform to introduce R as a useful digital tool and promoting collaboration between scholars interested in R.

 

A Reflection on My Internship with DCIP

This fall semester I joined the Digital Center Intern Program(DCIP) as an instructor intern. My internship is primarily focused on developing lesson plans for and hosting weekly R Open Labs. This internship allowed me to try different teaching approaches and explore different topics about R. It was an intellectually challenging and rewarding experience. The highlights of my experience were discussing with people from diverse academic backgrounds about how to use R to help their research. I learned a lot about applications of statistical analysis from these discussions and it felt wonderful to help people.

At the beginning of the semester, I started R Open Lab as a very structured instructional session and covered the basic usage of R. Later on, after talking with other librarians, I decided to make the open lab more free-flowing and put more emphasis on discussion instead of instruction. I found that, by getting participants more engaged in conversation, I was able to better understand their needs and help them with their research.

The internship offered a great opportunity for me to see for myself how R and statistics could be used as a tool for research. For example, one of the open lab’s regular participants used R to conduct sentiment analysis to gain insights about stress measurement and management in medical research. Another participant used R to extract information from Russian literature and conducted text analysis to understand the political situation at different times. It never occurred to me that statistics are so broadly used in different fields until I talked with these people.

Considering the participants’ interest and needs, I am planning to talk more about plotting, data cleaning and data scraping in the next semester. Since people coming to the open lab often have completely different levels of understanding of R, I am hoping to encourage more peer learning at the open lab next semester.

This internship motivated me to gain a deeper understanding of R and enhanced my teaching skills. It is an amazing program and I had an incredibly fulfilling experience. I really look forward to the future work in the program and I hope to do better next semester.