The Tech4Good Lab is led by Professor David Lee and conducts research in social computing, exploring the intersection of computational systems and social interaction. Being a part of this lab allowed me to work on skills that are not usually developed through classes and contribute to useful projects at the same time.

January - March 2020

During my first quarter with Tech4Good, I was working on front end web development by coding UI/UX components using Angular, HTML, CSS, and Typescript. These components are a part of Relate (an activity platform for small groups that provides engaging activities designed forconnection) and Compass (conversational UX and chatbots for supporting career journeys through authentic reflection, goal-setting, and mentorship), applications that are developed by the lab.

April - June 2020

As a developer on the lab platforms team, I wrote Google Apps scripts in Javascript to make the lab's interviewing process more efficient and less time consuming. In the past, members of the lab's qualitative analysis team would need to manually transfer and format their comments from their interview transcript on Google Docs to a cumulative Google Spreadsheet with information from multiple interviews. This script was originally written for the lab and was adjusted for an assignment in Professor Lee's CSE 175 course at UCSC.

Lab's Qualitative Process:

The first time it is ran, my script would produce a timestamp (Time Last Ran of the script) and transfer all comments and their associated text from a Google Docs to a new tab on a Google Spreadsheet. After it has been ran once, the script only checks for new comments made after the timestamp, add these new comments to the correct spreadsheet tab, and update the timestamp. The script requires the user, a member of the interviewing team, to add 3 inputs: the spreadsheet and document IDs (a part of the file's URL), and the spreadsheet tab title. With that information and a few clicks of the mouse, the user is able to accomplish what could have previously taken hours of copying and pasting, something likely for long interview transcripts with lots of notes.

CSE 175 Assignment:

For one of their assignments, students were required to interview a business owner and make comments on the interview transcript on Google Docs. This script gathered comments and associated texts from approximately 50 Google Docs, reducing the tedious copy-and-pasting part of the workload for 155 students, and compiled these interview notes into a pre-formatted cumulative master spreadsheet. In addition, the script also enabled edit permissions to the master spreadsheet for all students and TAs, but limited edit abilities for each student to the tab corresponding to their team. Instead of manually setting permissions for over 50 tabs in the spreadsheet, the script set the privacy settings automatically with a few functions in Javascript, given a separate spreadsheet with students' emails and corresponding team numbers.