Literally Literary -- The Idea

Literally Literary is a word analysis tool designed to help readers learn the meaning of words using definitions in-line.

Our team wanted to develop something that helps students get through difficult and unfamiliar articles easily. We chose to use a Chrome extension so it is easy to use while researching online.

What it does

It let's you hover over words and click on them if you don't know what they mean. This is useful for children and people learning english as a second language who are at a much lower reading level learn to read without going back and forth between dictionaries which takes away from reading engagement.

It also analyzes the reading level of the text.

How we built it

There are three major parts to our project, the data analysis, the back end and the front end.

How does the data work? After researching some statistical theory and natural language processing, we were able piece together standard formulas for determining reading levels of different webpages. It was also able to determine the parts of speech. We were able to take information about the word and link it to an online Dictionary called Webniks. This was done by both Krista and Katherine.

The front end was done through Javascript , HTML and CSS. She also designed the user interface, and how the definition window works. She also designed our beautiful logo.

Jose built our backend and the interface between the data analysis and the chrome extenstion.

Challenges we ran into

We had a lot of problems integrating our R code with the JavaScript backend. We resolved this by installing series of R-packages and extentions to the computer where the backend server is hosted.

We also had challeneges connecting the HTTP request from our application to our server which connects to the R code which connects to the JavaScript

Accomplishments that we're proud of

We had a first timer on our team (Katherine) and we're very proud that she contributed to the hackathon and worked tirelessly to make the project work.

Kim handled the front and with some help from Jose. Neither of them had ever created a chorme extention and we're proud that they went above and beyond in teaching themselves this skill soley to make the project work.

More importantly, we took a team of people who had never hacked together, from different schools, backgrounds, and coding specialties, and we all worked collaboratively towards a goal to make Litterally Literary litterally happen. We all worked hard to make it happen in 24 hours.

What we learned

Kim learned about making Google Chrome extentions.
Katherine learned how to use lots of packages like TreeTagger and Perl for natural language processing Jose learned how to integrate R into his Javascript backend. Krista learned how to interact and make requests from an API. She also learned how to format the output and make it take in command line arguements, which R is not originally designed to.

What's next for LITerally

We want to find a way to encorporate graphics to see how people learn over time. This way it can more accurately predict what grade level people are at. We want to store this data and use a combination of the Stwart Quality Control Charts and Time Series analyzes to measure how fast individuals are learning and how dependent they are on checking words to understand the meaning of the article.

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