View on GitHub

TRAIN-GO-SORRY---pages

View ALL THE STUFF: creation and development process, timeline, in-progress work and app demos, and milestones of TGS at this Wiki

View Our Presentation And Visit Our App!

View our TRAIN GO SORRY presentation
Visit TRAIN GO SORRY (train-go-sorry.com)

TRAIN GO SORRY Vision

There are many American Sign Language (ASL) dictionaries and study tools that allow a user to look up a word and see its sign, but there are limited tools for users to identify a sign from a video. This is problematic for learners because any person learning a new language must be able to communicate both expressively and receptively. This means that people must be able to speak/sign the language (expressive), in addition to understanding others when they speak/sign the language (receptive). ASL dictionaries provide videos with the name of the sign already visible, so users are not able to guess what is being signed in order to practice their receptive skills. Without proper receptive learning tools, it is more difficult for a person to learn on their own.

This is where TRAIN GO SORRY comes in. TRAIN GO SORRY is a free, receptive American Sign Language (ASL) study tool. The purpose of this tool is to provide ASL students with a way to test their ability to recognize signs and improve their receptive skills. We provide a web-based platform for ASL students to build lists of ASL signs they wish to study from a dictionary of 2,000 (and growing) sign videos we provide. A student can choose to study one or more lists at a time. While studying, TRAIN GO SORRY will show a random video from the list(s) of words the student chose to study. The student must identify the sign in the video by inputting the name of the sign in GLOSS. ASL GLOSS is a written approximation of ASL where each sign has a designated label (written in all caps).

Learn more by viewing our final report.

Team

image

(From left to right)

Daniel Kuiper

Daniel has no prior experience with ASL but has an interest in building tools to help facilitate learning and creativity.

Nikita Sietsema

Nikita has 4 years of ASL experience and has been an ASL student herself. She is passionate about ASL and creating a tool to help others improve their signing ability.

Jason Pruim

Jason has minimal experience with ASL, but has a few family members who are quite fluent. As a past avid user of Quizlet, he sees the value in tools to assist learning and drilling language vocab.

Acknowledgments

Dr. Victor Norman:

project advisor. Professor Norman is a Computer Science professor at Calvin University in Grand Rapids, Michigan. He supervises TGS to make sure it stays on track and approves the developers’ weekly plans. He is also a great resource when the developers have questions about how best to implement something or need other advice.

Keisha Thomas:

ASL contact. Mrs. Thomas is Nikita’s former ASL teacher. She is currently a second-grade teacher for deaf, hard of hearing, and hearing students at West Oakview Elementary School in Grand Rapids, Michigan. She has helped review TGS for accuracy and shared the tool with other ASL interpreters. Mrs. Thomas also connected us to ASL students at Northview High School so that they could study with the tool and provide feedback on their experience.

Marie DeRegnaucourt & Her ASL Students:

reviewers. Ms. DeRegnaucourt and her 2021 ASL students at Northview High School reviewed our app while it was in progress. Their time and feedback allowed us to improve the app for future users.

Datamuse:

lexical search service. We use Datamuse in our app to provide most of our word definitions. We also use it to enable us to suggest guesses that are close in spelling or phonetically close to a user’s guess so that students are not penalized for poor spelling or typos while studying. You can visit Datamuse here.

Visit Our Codebase Repo

Our main code repo is private.
You can access it from this link.
To request access, contact one of us:

Changes to Project Proposal

In addition to our planned manual testing, we will write tests for crucial methods and functions using mock data.

Design Norm - Cultural Appropriateness

Throughout the development of this project, we have been focusing on the design norm of Cultural Appropriateness. In short, Cultural Appropriateness means that “technology should alleviate burdens while still preserving what is good” (From Professor Schuurman’s “Redemption and Responsible Technology”, page 8).
For us, this means that TRAIN GO SORRY should make studying and communicating with ASL easier, without taking away from ASL or Deaf culture, and without taking away from the student’s learning success.

Additional Materials